how to read and understand a research study

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• v.16(7); 2020 Jul

Ten simple rules for reading a scientific paper

Maureen a. carey.

Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America

Kevin L. Steiner

William a. petri, jr, introduction.

“There is no problem that a library card can't solve” according to author Eleanor Brown [ 1 ]. This advice is sound, probably for both life and science, but even the best tool (like the library) is most effective when accompanied by instructions and a basic understanding of how and when to use it.

For many budding scientists, the first day in a new lab setting often involves a stack of papers, an email full of links to pertinent articles, or some promise of a richer understanding so long as one reads enough of the scientific literature. However, the purpose and approach to reading a scientific article is unlike that of reading a news story, novel, or even a textbook and can initially seem unapproachable. Having good habits for reading scientific literature is key to setting oneself up for success, identifying new research questions, and filling in the gaps in one’s current understanding; developing these good habits is the first crucial step.

Advice typically centers around two main tips: read actively and read often. However, active reading, or reading with an intent to understand, is both a learned skill and a level of effort. Although there is no one best way to do this, we present 10 simple rules, relevant to novices and seasoned scientists alike, to teach our strategy for active reading based on our experience as readers and as mentors of undergraduate and graduate researchers, medical students, fellows, and early career faculty. Rules 1–5 are big picture recommendations. Rules 6–8 relate to philosophy of reading. Rules 9–10 guide the “now what?” questions one should ask after reading and how to integrate what was learned into one’s own science.

Rule 1: Pick your reading goal

What you want to get out of an article should influence your approach to reading it. Table 1 includes a handful of example intentions and how you might prioritize different parts of the same article differently based on your goals as a reader.

1 Yay! Welcome!

2 A journal club is when a group of scientists get together to discuss a paper. Usually one person leads the discussion and presents all of the data. The group discusses their own interpretations and the authors’ interpretation.

Rule 2: Understand the author’s goal

In written communication, the reader and the writer are equally important. Both influence the final outcome: in this case, your scientific understanding! After identifying your goal, think about the author’s goal for sharing this project. This will help you interpret the data and understand the author’s interpretation of the data. However, this requires some understanding of who the author(s) are (e.g., what are their scientific interests?), the scientific field in which they work (e.g., what techniques are available in this field?), and how this paper fits into the author’s research (e.g., is this work building on an author’s longstanding project or controversial idea?). This information may be hard to glean without experience and a history of reading. But don’t let this be a discouragement to starting the process; it is by the act of reading that this experience is gained!

A good step toward understanding the goal of the author(s) is to ask yourself: What kind of article is this? Journals publish different types of articles, including methods, review, commentary, resources, and research articles as well as other types that are specific to a particular journal or groups of journals. These article types have different formatting requirements and expectations for content. Knowing the article type will help guide your evaluation of the information presented. Is the article a methods paper, presenting a new technique? Is the article a review article, intended to summarize a field or problem? Is it a commentary, intended to take a stand on a controversy or give a big picture perspective on a problem? Is it a resource article, presenting a new tool or data set for others to use? Is it a research article, written to present new data and the authors’ interpretation of those data? The type of paper, and its intended purpose, will get you on your way to understanding the author’s goal.

Rule 3: Ask six questions

When reading, ask yourself: (1) What do the author(s) want to know (motivation)? (2) What did they do (approach/methods)? (3) Why was it done that way (context within the field)? (4) What do the results show (figures and data tables)? (5) How did the author(s) interpret the results (interpretation/discussion)? (6) What should be done next? (Regarding this last question, the author(s) may provide some suggestions in the discussion, but the key is to ask yourself what you think should come next.)

Each of these questions can and should be asked about the complete work as well as each table, figure, or experiment within the paper. Early on, it can take a long time to read one article front to back, and this can be intimidating. Break down your understanding of each section of the work with these questions to make the effort more manageable.

Rule 4: Unpack each figure and table

Scientists write original research papers primarily to present new data that may change or reinforce the collective knowledge of a field. Therefore, the most important parts of this type of scientific paper are the data. Some people like to scrutinize the figures and tables (including legends) before reading any of the “main text”: because all of the important information should be obtained through the data. Others prefer to read through the results section while sequentially examining the figures and tables as they are addressed in the text. There is no correct or incorrect approach: Try both to see what works best for you. The key is making sure that one understands the presented data and how it was obtained.

For each figure, work to understand each x- and y-axes, color scheme, statistical approach (if one was used), and why the particular plotting approach was used. For each table, identify what experimental groups and variables are presented. Identify what is shown and how the data were collected. This is typically summarized in the legend or caption but often requires digging deeper into the methods: Do not be afraid to refer back to the methods section frequently to ensure a full understanding of how the presented data were obtained. Again, ask the questions in Rule 3 for each figure or panel and conclude with articulating the “take home” message.

Rule 5: Understand the formatting intentions

Just like the overall intent of the article (discussed in Rule 2), the intent of each section within a research article can guide your interpretation. Some sections are intended to be written as objective descriptions of the data (i.e., the Results section), whereas other sections are intended to present the author’s interpretation of the data. Remember though that even “objective” sections are written by and, therefore, influenced by the authors interpretations. Check out Table 2 to understand the intent of each section of a research article. When reading a specific paper, you can also refer to the journal’s website to understand the formatting intentions. The “For Authors” section of a website will have some nitty gritty information that is less relevant for the reader (like word counts) but will also summarize what the journal editors expect in each section. This will help to familiarize you with the goal of each article section.

Research articles typically contain each of these sections, although sometimes the “results” and “discussion” sections (or “discussion” and “conclusion” sections) are merged into one section. Additional sections may be included, based on request of the journal or the author(s). Keep in mind: If it was included, someone thought it was important for you to read.

Rule 6: Be critical

Published papers are not truths etched in stone. Published papers in high impact journals are not truths etched in stone. Published papers by bigwigs in the field are not truths etched in stone. Published papers that seem to agree with your own hypothesis or data are not etched in stone. Published papers that seem to refute your hypothesis or data are not etched in stone.

Science is a never-ending work in progress, and it is essential that the reader pushes back against the author’s interpretation to test the strength of their conclusions. Everyone has their own perspective and may interpret the same data in different ways. Mistakes are sometimes published, but more often these apparent errors are due to other factors such as limitations of a methodology and other limits to generalizability (selection bias, unaddressed, or unappreciated confounders). When reading a paper, it is important to consider if these factors are pertinent.

Critical thinking is a tough skill to learn but ultimately boils down to evaluating data while minimizing biases. Ask yourself: Are there other, equally likely, explanations for what is observed? In addition to paying close attention to potential biases of the study or author(s), a reader should also be alert to one’s own preceding perspective (and biases). Take time to ask oneself: Do I find this paper compelling because it affirms something I already think (or wish) is true? Or am I discounting their findings because it differs from what I expect or from my own work?

The phenomenon of a self-fulfilling prophecy, or expectancy, is well studied in the psychology literature [ 2 ] and is why many studies are conducted in a “blinded” manner [ 3 ]. It refers to the idea that a person may assume something to be true and their resultant behavior aligns to make it true. In other words, as humans and scientists, we often find exactly what we are looking for. A scientist may only test their hypotheses and fail to evaluate alternative hypotheses; perhaps, a scientist may not be aware of alternative, less biased ways to test her or his hypothesis that are typically used in different fields. Individuals with different life, academic, and work experiences may think of several alternative hypotheses, all equally supported by the data.

Rule 7: Be kind

The author(s) are human too. So, whenever possible, give them the benefit of the doubt. An author may write a phrase differently than you would, forcing you to reread the sentence to understand it. Someone in your field may neglect to cite your paper because of a reference count limit. A figure panel may be misreferenced as Supplemental Fig 3E when it is obviously Supplemental Fig 4E. While these things may be frustrating, none are an indication that the quality of work is poor. Try to avoid letting these minor things influence your evaluation and interpretation of the work.

Similarly, if you intend to share your critique with others, be extra kind. An author (especially the lead author) may invest years of their time into a single paper. Hearing a kindly phrased critique can be difficult but constructive. Hearing a rude, brusque, or mean-spirited critique can be heartbreaking, especially for young scientists or those seeking to establish their place within a field and who may worry that they do not belong.

Rule 8: Be ready to go the extra mile

To truly understand a scientific work, you often will need to look up a term, dig into the supplemental materials, or read one or more of the cited references. This process takes time. Some advisors recommend reading an article three times: The first time, simply read without the pressure of understanding or critiquing the work. For the second time, aim to understand the paper. For the third read through, take notes.

Some people engage with a paper by printing it out and writing all over it. The reader might write question marks in the margins to mark parts (s)he wants to return to, circle unfamiliar terms (and then actually look them up!), highlight or underline important statements, and draw arrows linking figures and the corresponding interpretation in the discussion. Not everyone needs a paper copy to engage in the reading process but, whatever your version of “printing it out” is, do it.

Rule 9: Talk about it

Talking about an article in a journal club or more informal environment forces active reading and participation with the material. Studies show that teaching is one of the best ways to learn and that teachers learn the material even better as the teaching task becomes more complex [ 4 – 5 ]; anecdotally, such observations inspired the phrase “to teach is to learn twice.”

Beyond formal settings such as journal clubs, lab meetings, and academic classes, discuss papers with your peers, mentors, and colleagues in person or electronically. Twitter and other social media platforms have become excellent resources for discussing papers with other scientists, the public or your nonscientist friends, or even the paper’s author(s). Describing a paper can be done at multiple levels and your description can contain all of the scientific details, only the big picture summary, or perhaps the implications for the average person in your community. All of these descriptions will solidify your understanding, while highlighting gaps in your knowledge and informing those around you.

Rule 10: Build on it

One approach we like to use for communicating how we build on the scientific literature is by starting research presentations with an image depicting a wall of Lego bricks. Each brick is labeled with the reference for a paper, and the wall highlights the body of literature on which the work is built. We describe the work and conclusions of each paper represented by a labeled brick and discuss each brick and the wall as a whole. The top brick on the wall is left blank: We aspire to build on this work and label this brick with our own work. We then delve into our own research, discoveries, and the conclusions it inspires. We finish our presentations with the image of the Legos and summarize our presentation on that empty brick.

Whether you are reading an article to understand a new topic area or to move a research project forward, effective learning requires that you integrate knowledge from multiple sources (“click” those Lego bricks together) and build upwards. Leveraging published work will enable you to build a stronger and taller structure. The first row of bricks is more stable once a second row is assembled on top of it and so on and so forth. Moreover, the Lego construction will become taller and larger if you build upon the work of others, rather than using only your own bricks.

Build on the article you read by thinking about how it connects to ideas described in other papers and within own work, implementing a technique in your own research, or attempting to challenge or support the hypothesis of the author(s) with a more extensive literature review. Integrate the techniques and scientific conclusions learned from an article into your own research or perspective in the classroom or research lab. You may find that this process strengthens your understanding, leads you toward new and unexpected interests or research questions, or returns you back to the original article with new questions and critiques of the work. All of these experiences are part of the “active reading”: process and are signs of a successful reading experience.

In summary, practice these rules to learn how to read a scientific article, keeping in mind that this process will get easier (and faster) with experience. We are firm believers that an hour in the library will save a week at the bench; this diligent practice will ultimately make you both a more knowledgeable and productive scientist. As you develop the skills to read an article, try to also foster good reading and learning habits for yourself (recommendations here: [ 6 ] and [ 7 ], respectively) and in others. Good luck and happy reading!

Acknowledgments

Thank you to the mentors, teachers, and students who have shaped our thoughts on reading, learning, and what science is all about.

Funding Statement

MAC was supported by the PhRMA Foundation's Postdoctoral Fellowship in Translational Medicine and Therapeutics and the University of Virginia's Engineering-in-Medicine seed grant, and KLS was supported by the NIH T32 Global Biothreats Training Program at the University of Virginia (AI055432). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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How to read and understand a scientific paper

How to read and understand a scientific paper: a guide for non-scientists, london school of economics and political science, jennifer raff.

From vaccinations to climate change, getting science wrong has very real consequences. But journal articles, a primary way science is communicated in academia, are a different format to newspaper articles or blogs and require a level of skill and undoubtedly a greater amount of patience. Here  Jennifer Raff   has prepared a helpful guide for non-scientists on how to read a scientific paper. These steps and tips will be useful to anyone interested in the presentation of scientific findings and raise important points for scientists to consider with their own writing practice.

My post,  The truth about vaccinations: Your physician knows more than the University of Google  sparked a very lively discussion, with comments from several people trying to persuade me (and the other readers) that  their  paper disproved everything that I’d been saying. While I encourage you to go read the comments and contribute your own, here I want to focus on the much larger issue that this debate raised: what constitutes scientific authority?

It’s not just a fun academic problem. Getting the science wrong has very real consequences. For example, when a community doesn’t vaccinate children because they’re afraid of “toxins” and think that prayer (or diet, exercise, and “clean living”) is enough to prevent infection, outbreaks happen.

“Be skeptical. But when you get proof, accept proof.” –Michael Specter

What constitutes enough proof? Obviously everyone has a different answer to that question. But to form a truly educated opinion on a scientific subject, you need to become familiar with current research in that field. And to do that, you have to read the “primary research literature” (often just called “the literature”). You might have tried to read scientific papers before and been frustrated by the dense, stilted writing and the unfamiliar jargon. I remember feeling this way!  Reading and understanding research papers is a skill which every single doctor and scientist has had to learn during graduate school.  You can learn it too, but like any skill it takes patience and practice.

I want to help people become more scientifically literate, so I wrote this guide for how a layperson can approach reading and understanding a scientific research paper. It’s appropriate for someone who has no background whatsoever in science or medicine, and based on the assumption that he or she is doing this for the purpose of getting a  basic  understanding of a paper and deciding whether or not it’s a reputable study.

The type of scientific paper I’m discussing here is referred to as a  primary research article . It’s a peer-reviewed report of new research on a specific question (or questions). Another useful type of publication is a  review article . Review articles are also peer-reviewed, and don’t present new information, but summarize multiple primary research articles, to give a sense of the consensus, debates, and unanswered questions within a field.  (I’m not going to say much more about them here, but be cautious about which review articles you read. Remember that they are only a snapshot of the research at the time they are published.  A review article on, say, genome-wide association studies from 2001 is not going to be very informative in 2013. So much research has been done in the intervening years that the field has changed considerably).

Before you begin: some general advice

Reading a scientific paper is a completely different process than reading an article about science in a blog or newspaper. Not only do you read the sections in a different order than they’re presented, but you also have to take notes, read it multiple times, and probably go look up other papers for some of the details. Reading a single paper may take you a very long time at first. Be patient with yourself. The process will go much faster as you gain experience.

Most primary research papers will be divided into the following sections: Abstract, Introduction, Methods, Results, and Conclusions/Interpretations/Discussion. The order will depend on which journal it’s published in. Some journals have additional files (called Supplementary Online Information) which contain important details of the research, but are published online instead of in the article itself (make sure you don’t skip these files).

Before you begin reading, take note of the authors and their institutional affiliations. Some institutions (e.g. University of Texas) are well-respected; others (e.g.  the Discovery Institute ) may appear to be legitimate research institutions but are actually agenda-driven.  Tip:  g oogle  “Discovery Institute” to see why you don’t want to use it as a scientific authority on evolutionary theory.

Also take note of the journal in which it’s published. Reputable (biomedical) journals will be indexed by  Pubmed . [EDIT: Several people have reminded me that non-biomedical journals won’t be on Pubmed, and they’re absolutely correct! (thanks for catching that, I apologize for being sloppy here). Check out  Web of Science  for a more complete index of science journals. And please feel free to share other resources in the comments!]  Beware of  questionable journals .

As you read, write down  every single word  that you don’t understand. You’re going to have to look them all up (yes, every one. I know it’s a total pain. But you won’t understand the paper if you don’t understand the vocabulary. Scientific words have extremely precise meanings).

Step-by-step instructions for reading a primary research article

1. Begin by reading the introduction, not the abstract.

The abstract is that dense first paragraph at the very beginning of a paper. In fact, that’s often the only part of a paper that many non-scientists read when they’re trying to build a scientific argument. (This is a terrible practice—don’t do it.).  When I’m choosing papers to read, I decide what’s relevant to my interests based on a combination of the title and abstract. But when I’ve got a collection of papers assembled for deep reading, I always read the abstract last. I do this because abstracts contain a succinct summary of the entire paper, and I’m concerned about inadvertently becoming biased by the authors’ interpretation of the results.

2. Identify the BIG QUESTION.

Not “What is this paper about”, but “What problem is this entire field trying to solve?”

This helps you focus on why this research is being done.  Look closely for evidence of agenda-motivated research.

3. Summarize the background in five sentences or less.

Here are some questions to guide you:

What work has been done before in this field to answer the BIG QUESTION? What are the limitations of that work? What, according to the authors, needs to be done next?

The five sentences part is a little arbitrary, but it forces you to be concise and really think about the context of this research. You need to be able to explain why this research has been done in order to understand it.

4.   Identify the SPECIFIC QUESTION(S)

What  exactly  are the authors trying to answer with their research? There may be multiple questions, or just one. Write them down.  If it’s the kind of research that tests one or more null hypotheses, identify it/them.

Not sure what a null hypothesis is? Go read this one  and try to identify the null hypotheses in it. Keep in mind that not every paper will test a null hypothesis.

5. Identify the approach

What are the authors going to do to answer the SPECIFIC QUESTION(S)?

6. Now read the methods section. Draw a diagram for each experiment, showing exactly what the authors did.

I mean  literally  draw it. Include as much detail as you need to fully understand the work.  As an example, here is what I drew to sort out the methods for a paper I read today ( Battaglia et al. 2013: “The first peopling of South America: New evidence from Y-chromosome haplogroup Q” ). This is much less detail than you’d probably need, because it’s a paper in my specialty and I use these methods all the time.  But if you were reading this, and didn’t happen to know what “process data with reduced-median method using Network” means, you’d need to look that up.

Image credit: author

You don’t need to understand the methods in enough detail to replicate the experiment—that’s something reviewers have to do—but you’re not ready to move on to the results until you can explain the basics of the methods to someone else.

7.   Read the results section. Write one or more paragraphs to summarize the results for each experiment, each figure, and each table. Don’t yet try to decide what the results  mean , just write down what they  are.

You’ll find that, particularly in good papers, the majority of the results are summarized in the figures and tables. Pay careful attention to them!  You may also need to go to the Supplementary Online Information file to find some of the results.

 It is at this point where difficulties can arise if statistical tests are employed in the paper and you don’t have enough of a background to understand them. I can’t teach you stats in this post, but  here , and here   are some basic resources to help you.  I STRONGLY advise you to become familiar with them.

Things to pay attention to in the results section:

• Any time the words “significant” or “non-significant” are used. These have precise statistical meanings. Read more about this  here .
• If there are graphs, do they have  error bars  on them? For certain types of studies, a lack of confidence intervals is a major red flag.
• The sample size. Has the study been conducted on 10, or 10,000 people? (For some research purposes, a sample size of 10 is sufficient, but for most studies larger is better).

8. Do the results answer the SPECIFIC QUESTION(S)? What do you think they mean?

Don’t move on until you have thought about this. It’s okay to change your mind in light of the authors’ interpretation—in fact you probably will if you’re still a beginner at this kind of analysis—but it’s a really good habit to start forming your own interpretations before you read those of others.

9. Read the conclusion/discussion/Interpretation section.

What do the authors think the results mean? Do you agree with them? Can you come up with any alternative way of interpreting them? Do the authors identify any weaknesses in their own study? Do you see any that the authors missed? (Don’t assume they’re infallible!) What do they propose to do as a next step? Do you agree with that?

10. Now, go back to the beginning and read the abstract.

Does it match what the authors said in the paper? Does it fit with your interpretation of the paper?

11. FINAL STEP:  (Don’t neglect doing this)  What do other researchers say about this paper?

Who are the (acknowledged or self-proclaimed) experts in this particular field? Do they have criticisms of the study that you haven’t thought of, or do they generally support it?

Here’s a place where I do recommend you use google! But do it last, so you are better prepared to think critically about what other people say.

(12. This step may be optional for you, depending on why you’re reading a particular paper. But for me, it’s critical! I go through the “Literature cited” section to see what other papers the authors cited. This allows me to better identify the important papers in a particular field, see if the authors cited my own papers (KIDDING!….mostly), and find sources of useful ideas or techniques.)

UPDATE: If you would like to see an example of how to read a science paper using this framework, you can find one  here .

I gratefully acknowledge Professors José Bonner and Bill Saxton for teaching me how to critically read and analyze scientific papers using this method. I’m honored to have the chance to pass along what they taught me.

I’ve written a shorter version of this guide for teachers to hand out to their classes. If you’d like a PDF, shoot me an email: jenniferraff (at) utexas (dot) edu. For further comments and additional questions on this guide, please see the Comments Section on  the original post .

This piece originally appeared on the  author’s personal blog  and is reposted with permission.

Featured image credit:  Scientists in a laboratory of the University of La Rioja  by  Urcomunicacion  (Wikimedia CC BY3.0)

Note: This article gives the views of the authors, and not the position of the LSE Impact blog, nor of the London School of Economics. Please review our  Comments Policy  if you have any concerns on posting a comment below.

Jennifer Raff (Indiana University—dual Ph.D. in genetics and bioanthropology) is an assistant professor in the Department of Anthropology, University of Kansas, director and Principal Investigator of the KU Laboratory of Human Population Genomics, and assistant director of KU’s Laboratory of Biological Anthropology. She is also a research affiliate with the University of Texas anthropological genetics laboratory. She is keenly interested in public outreach and scientific literacy, writing about topics in science and pseudoscience for her blog ( violentmetaphors.com ), the Huffington Post, and for the  Social Evolution Forum .

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Organizing Your Social Sciences Research Paper

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Reading a Scholarly Article or Research Paper

Identifying a research problem to investigate usually requires a preliminary search for and critical review of the literature in order to gain an understanding about how scholars have examined a topic. Scholars rarely structure research studies in a way that can be followed like a story; they are complex and detail-intensive and often written in a descriptive and conclusive narrative form. However, in the social and behavioral sciences, journal articles and stand-alone research reports are generally organized in a consistent format that makes it easier to compare and contrast studies and to interpret their contents.

General Reading Strategies

W hen you first read an article or research paper, focus on asking specific questions about each section. This strategy can help with overall comprehension and with understanding how the content relates [or does not relate] to the problem you want to investigate. As you review more and more studies, the process of understanding and critically evaluating the research will become easier because the content of what you review will begin to coalescence around common themes and patterns of analysis. Below are recommendations on how to read each section of a research paper effectively. Note that the sections to read are out of order from how you will find them organized in a journal article or research paper.

1.  Abstract

The abstract summarizes the background, methods, results, discussion, and conclusions of a scholarly article or research paper. Use the abstract to filter out sources that may have appeared useful when you began searching for information but, in reality, are not relevant. Questions to consider when reading the abstract are:

• Is this study related to my question or area of research?
• What is this study about and why is it being done ?
• What is the working hypothesis or underlying thesis?
• What is the primary finding of the study?
• Are there words or terminology that I can use to either narrow or broaden the parameters of my search for more information?

2.  Introduction

If, after reading the abstract, you believe the paper may be useful, focus on examining the research problem and identifying the questions the author is trying to address. This information is usually located within the first few paragraphs of the introduction or in the concluding paragraph. Look for information about how and in what way this relates to what you are investigating. In addition to the research problem, the introduction should provide the main argument and theoretical framework of the study and, in the last paragraphs of the introduction, describe what the author(s) intend to accomplish. Questions to consider when reading the introduction include:

• What is this study trying to prove or disprove?
• What is the author(s) trying to test or demonstrate?
• What do we already know about this topic and what gaps does this study try to fill or contribute a new understanding to the research problem?
• Why should I care about what is being investigated?
• Will this study tell me anything new related to the research problem I am investigating?

3.  Literature Review

The literature review describes and critically evaluates what is already known about a topic. Read the literature review to obtain a big picture perspective about how the topic has been studied and to begin the process of seeing where your potential study fits within the domain of prior research. Questions to consider when reading the literature review include:

• W hat other research has been conducted about this topic and what are the main themes that have emerged?
• What does prior research reveal about what is already known about the topic and what remains to be discovered?
• What have been the most important past findings about the research problem?
• How has prior research led the author(s) to conduct this particular study?
• Is there any prior research that is unique or groundbreaking?
• Are there any studies I could use as a model for designing and organizing my own study?

4.  Discussion/Conclusion

The discussion and conclusion are usually the last two sections of text in a scholarly article or research report. They reveal how the author(s) interpreted the findings of their research and presented recommendations or courses of action based on those findings. Often in the conclusion, the author(s) highlight recommendations for further research that can be used to develop your own study. Questions to consider when reading the discussion and conclusion sections include:

• What is the overall meaning of the study and why is this important? [i.e., how have the author(s) addressed the " So What? " question].
• What do you find to be the most important ways that the findings have been interpreted?
• What are the weaknesses in their argument?
• Do you believe conclusions about the significance of the study and its findings are valid?
• What limitations of the study do the author(s) describe and how might this help formulate my own research?
• Does the conclusion contain any recommendations for future research?

5.  Methods/Methodology

The methods section describes the materials, techniques, and procedures for gathering information used to examine the research problem. If what you have read so far closely supports your understanding of the topic, then move on to examining how the author(s) gathered information during the research process. Questions to consider when reading the methods section include:

• Did the study use qualitative [based on interviews, observations, content analysis], quantitative [based on statistical analysis], or a mixed-methods approach to examining the research problem?
• What was the type of information or data used?
• Could this method of analysis be repeated and can I adopt the same approach?
• Is enough information available to repeat the study or should new data be found to expand or improve understanding of the research problem?

6.  Results

After reading the above sections, you should have a clear understanding of the general findings of the study. Therefore, read the results section to identify how key findings were discussed in relation to the research problem. If any non-textual elements [e.g., graphs, charts, tables, etc.] are confusing, focus on the explanations about them in the text. Questions to consider when reading the results section include:

• W hat did the author(s) find and how did they find it?
• Does the author(s) highlight any findings as most significant?
• Are the results presented in a factual and unbiased way?
• Does the analysis of results in the discussion section agree with how the results are presented?
• Is all the data present and did the author(s) adequately address gaps?
• What conclusions do you formulate from this data and does it match with the author's conclusions?

7.  References

The references list the sources used by the author(s) to document what prior research and information was used when conducting the study. After reviewing the article or research paper, use the references to identify additional sources of information on the topic and to examine critically how these sources supported the overall research agenda. Questions to consider when reading the references include:

• Do the sources cited by the author(s) reflect a diversity of disciplinary viewpoints, i.e., are the sources all from a particular field of study or do the sources reflect multiple areas of study?
• Are there any unique or interesting sources that could be incorporated into my study?
• What other authors are respected in this field, i.e., who has multiple works cited or is cited most often by others?
• What other research should I review to clarify any remaining issues or that I need more information about?

NOTE :  A final strategy in reviewing research is to copy and paste the title of the source [journal article, book, research report] into Google Scholar . If it appears, look for a "cited by" followed by a hyperlinked number [e.g., Cited by 45]. This number indicates how many times the study has been subsequently cited in other, more recently published works. This strategy, known as citation tracking, can be an effective means of expanding your review of pertinent literature based on a study you have found useful and how scholars have cited it. The same strategies described above can be applied to reading articles you find in the list of cited by references.

Reading Tip

Specific Reading Strategies

Effectively reading scholarly research is an acquired skill that involves attention to detail and an ability to comprehend complex ideas, data, and theoretical concepts in a way that applies logically to the research problem you are investigating. Here are some specific reading strategies to consider.

As You are Reading

• Focus on information that is most relevant to the research problem; skim over the other parts.
• As noted above, read content out of order! This isn't a novel; you want to start with the spoiler to quickly assess the relevance of the study.
• Think critically about what you read and seek to build your own arguments; not everything may be entirely valid, examined effectively, or thoroughly investigated.
• Look up the definitions of unfamiliar words, concepts, or terminology. A good scholarly source is Credo Reference .

Taking notes as you read will save time when you go back to examine your sources. Here are some suggestions:

• Mark or highlight important text as you read [e.g., you can use the highlight text  feature in a PDF document]
• Take notes in the margins [e.g., Adobe Reader offers pop-up sticky notes].
• Highlight important quotations; consider using different colors to differentiate between quotes and other types of important text.
• Summarize key points about the study at the end of the paper. To save time, these can be in the form of a concise bulleted list of statements [e.g., intro has provides historical background; lit review has important sources; good conclusions].

Write down thoughts that come to mind that may help clarify your understanding of the research problem. Here are some examples of questions to ask yourself:

• Do I understand all of the terminology and key concepts?
• Do I understand the parts of this study most relevant to my topic?
• What specific problem does the research address and why is it important?
• Are there any issues or perspectives the author(s) did not consider?
• Do I have any reason to question the validity or reliability of this research?
• How do the findings relate to my research interests and to other works which I have read?

Adapted from text originally created by Holly Burt, Behavioral Sciences Librarian, USC Libraries, April 2018.

Another Reading Tip

When is it Important to Read the Entire Article or Research Paper

Laubepin argues, "Very few articles in a field are so important that every word needs to be read carefully." However, this implies that some studies are worth reading carefully. As painful and time-consuming as it may seem, there are valid reasons for reading a study in its entirety from beginning to end. Here are some examples:

• Studies Published Very Recently .  The author(s) of a recent, well written study will provide a survey of the most important or impactful prior research in the literature review section. This can establish an understanding of how scholars in the past addressed the research problem. In addition, the most recently published sources will highlight what is currently known and what gaps in understanding currently exist about a topic, usually in the form of the need for further research in the conclusion .
• Surveys of the Research Problem .  Some papers provide a comprehensive analytical overview of the research problem. Reading this type of study can help you understand underlying issues and discover why scholars have chosen to investigate the topic. This is particularly important if the study was published very recently because the author(s) should cite all or most of the key prior research on the topic. Note that, if it is a long-standing problem, there may be studies that specifically review the literature to identify gaps that remain. These studies often include the word review in their title [e.g., Hügel, Stephan, and Anna R. Davies. "Public Participation, Engagement, and Climate Change Adaptation: A Review of the Research Literature." Wiley Interdisciplinary Reviews: Climate Change 11 (July-August 2020): https://doi.org/10.1002/ wcc.645].
• Highly Cited .  If you keep coming across the same citation to a study while you are reviewing the literature, this implies it was foundational in establishing an understanding of the research problem or the study had a significant impact within the literature [positive or negative]. Carefully reading a highly cited source can help you understand how the topic emerged and motivated scholars to further investigate the problem. It also could be a study you need to cite as foundational in your own paper to demonstrate to the reader that you understand the roots of the problem.
• Historical Overview .  Knowing the historical background of a research problem may not be the focus of your analysis. Nevertheless, carefully reading a study that provides a thorough description and analysis of the history behind an event, issue, or phenomenon can add important context to understanding the topic and what aspect of the problem you may want to examine further.
• Innovative Methodological Design .  Some studies are significant and worth reading in their entirety because the author(s) designed a unique or innovative approach to researching the problem. This may justify reading the entire study because it can motivate you to think creatively about pursuing an alternative or non-traditional approach to examining your topic of interest. These types of studies are generally easy to identify because they are often cited in others works because of their unique approach to studying the research problem.
• Cross-disciplinary Approach .  R eviewing studies produced outside of your discipline is an essential component of investigating research problems in the social and behavioral sciences. Consider reading a study that was conducted by author(s) based in a different discipline [e.g., an anthropologist studying political cultures; a study of hiring practices in companies published in a sociology journal]. This approach can generate a new understanding or a unique perspective about the topic . If you are not sure how to search for studies published in a discipline outside of your major or of the course you are taking, contact a librarian for assistance.

Laubepin, Frederique. How to Read (and Understand) a Social Science Journal Article . Inter-University Consortium for Political and Social Research (ISPSR), 2013; Shon, Phillip Chong Ho. How to Read Journal Articles in the Social Sciences: A Very Practical Guide for Students . 2nd edition. Thousand Oaks, CA: Sage, 2015; Lockhart, Tara, and Mary Soliday. "The Critical Place of Reading in Writing Transfer (and Beyond): A Report of Student Experiences." Pedagogy 16 (2016): 23-37; Maguire, Moira, Ann Everitt Reynolds, and Brid Delahunt. "Reading to Be: The Role of Academic Reading in Emergent Academic and Professional Student Identities." Journal of University Teaching and Learning Practice 17 (2020): 5-12.

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Research Process

• Brainstorming
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Reading a Scientific Article

• Website Evaluation
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Library Tutorial

• Reading a Scholarly Article Tutorial This interactive tutorial provides practice reading a scholarly or scientific article.

Additional Resources

• Anatomy of a Scholarly Article
• How to Read (and Understand) a Social Science Journal Article
• How to Read a Scientific Paper
• How to Read a Scientific Paper Interactive Tutorial
• How to Read Scientific Literature (YouTube Video)

General Dictionaries

• The American Heritage Dictionary of the English Language
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Attempting to read a scientific or scholarly research article for the first time may seem overwhelming and confusing. This guide details how to read a scientific article step-by-step. First, you should not approach a scientific article like a textbook— reading from beginning to end of the chapter or book without pause for reflection or criticism. Additionally, it is highly recommended that you highlight and take notes as you move through the article. Taking notes will keep you focused on the task at hand and help you work towards comprehension of the entire article.

• Skim the article. This should only take you a few minutes. You are not trying to comprehend the entire article at this point, but just get a basic overview. You don’t have to read in order; the discussion/conclusions will help you to determine if the article is relevant to your research. You might then continue on to the Introduction. Pay attention to the structure of the article, headings, and figures.  
• Grasp the vocabulary. Begin to go through the article and highlight words and phrases you do not understand. Some words or phrases you may be able to get an understanding from the context in which it is used, but for others you may need the assistance of a medical or scientific dictionary. Subject-specific dictionaries available through our Library databases and online are listed below.  
• The abstract gives a quick overview of the article. It will usually contain four pieces of information: purpose or rationale of study (why they did it); methodology (how they did it); results (what they found); conclusion (what it means). Begin by reading the abstract to make sure this is what you are looking for and that it will be worth your time and effort.   
• The introduction gives background information about the topic and sets out specific questions to be addressed by the authors. You can skim through the introduction if you are already familiar with the paper’s topic.  
• The methods section gives technical details of how the experiments were carried out and serves as a “how-to” manual if you wanted to replicate the same experiments as the authors. This is another section you may want to only skim unless you wish to identify the methods used by the researchers or if you intend to replicate the research yourself.  
• The results are the meat of the scientific article and contain all of the data from the experiments. You should spend time looking at all the graphs, pictures, and tables as these figures will contain most of the data.  
• Lastly, the discussion is the authors’ opportunity to give their opinions. Keep in mind that the discussions are the authors’ interpretations and not necessarily facts. It is still a good place for you to get ideas about what kind of research questions are still unanswered in the field and what types of questions you might want your own research project to tackle. (See the Future Research Section of the Research Process for more information).  
•   Read the bibliography/references section. Reading the references or works cited may lead you to other useful resources. You might also get a better understanding of the basic terminology, main concepts, major researchers, and basic terminology in the area you are researching.  
• Have I taken time to understand all the terminology?
• Am I spending too much time on the less important parts of this article?
• Do I have any reason to question the credibility of this research?
• What specific problem does the research address and why is it important?
• How do these results relate to my research interests or to other works which I have read?  
• Read the article a second time in chronological order. Reading the article a second time will reinforce your overall understanding. You may even start to make connections to other articles that you have read on this topic.

Reading a Scholarly Article Workshop

This workshop presents effective techniques for reading and understanding a scholarly article, as well as locating definitions related to your research topic.

Subject-Specific Dictionaries

• Health Sciences
• Marriage & Family Science
• Research Methods
• Social Work

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May 9th, 2016

How to read and understand a scientific paper: a guide for non-scientists.

94 comments | 1967 shares

Estimated reading time: 7 minutes

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My post,  The truth about vaccinations: Your physician knows more than the University of Google  sparked a very lively discussion, with comments from several people trying to persuade me (and the other readers) that their paper disproved everything that I’d been saying. While I encourage you to go read the comments and contribute your own, here I want to focus on the much larger issue that this debate raised: what constitutes scientific authority?

It’s not just a fun academic problem. Getting the science wrong has very real consequences. For example, when a community doesn’t vaccinate children because they’re afraid of “toxins” and think that prayer (or diet, exercise, and “clean living”) is enough to prevent infection, outbreaks happen .

“Be skeptical. But when you get proof, accept proof.” –Michael Specter

What constitutes enough proof? Obviously everyone has a different answer to that question. But to form a truly educated opinion on a scientific subject, you need to become familiar with current research in that field. And to do that, you have to read the “primary research literature” (often just called “the literature”). You might have tried to read scientific papers before and been frustrated by the dense, stilted writing and the unfamiliar jargon. I remember feeling this way!  Reading and understanding research papers is a skill which every single doctor and scientist has had to learn during graduate school.  You can learn it too, but like any skill it takes patience and practice.

I want to help people become more scientifically literate, so I wrote this guide for how a layperson can approach reading and understanding a scientific research paper. It’s appropriate for someone who has no background whatsoever in science or medicine, and based on the assumption that he or she is doing this for the purpose of getting a  basic understanding of a paper and deciding whether or not it’s a reputable study.

The type of scientific paper I’m discussing here is referred to as a primary research article . It’s a peer-reviewed report of new research on a specific question (or questions). Another useful type of publication is a review article . Review articles are also peer-reviewed, and don’t present new information, but summarize multiple primary research articles, to give a sense of the consensus, debates, and unanswered questions within a field.  (I’m not going to say much more about them here, but be cautious about which review articles you read. Remember that they are only a snapshot of the research at the time they are published.  A review article on, say, genome-wide association studies from 2001 is not going to be very informative in 2013. So much research has been done in the intervening years that the field has changed considerably).

Before you begin: some general advice

Reading a scientific paper is a completely different process than reading an article about science in a blog or newspaper. Not only do you read the sections in a different order than they’re presented, but you also have to take notes, read it multiple times, and probably go look up other papers for some of the details. Reading a single paper may take you a very long time at first. Be patient with yourself. The process will go much faster as you gain experience.

Most primary research papers will be divided into the following sections: Abstract, Introduction, Methods, Results, and Conclusions/Interpretations/Discussion. The order will depend on which journal it’s published in. Some journals have additional files (called Supplementary Online Information) which contain important details of the research, but are published online instead of in the article itself (make sure you don’t skip these files).

Before you begin reading, take note of the authors and their institutional affiliations. Some institutions (e.g. University of Texas) are well-respected; others (e.g. the Discovery Institute ) may appear to be legitimate research institutions but are actually agenda-driven. Tip: g oogle “Discovery Institute” to see why you don’t want to use it as a scientific authority on evolutionary theory.

Also take note of the journal in which it’s published. Reputable (biomedical) journals will be indexed by Pubmed . [EDIT: Several people have reminded me that non-biomedical journals won’t be on Pubmed, and they’re absolutely correct! (thanks for catching that, I apologize for being sloppy here). Check out Web of Science for a more complete index of science journals. And please feel free to share other resources in the comments!]  Beware of questionable journals .

As you read, write down every single word that you don’t understand. You’re going to have to look them all up (yes, every one. I know it’s a total pain. But you won’t understand the paper if you don’t understand the vocabulary. Scientific words have extremely precise meanings).

Step-by-step instructions for reading a primary research article

1. Begin by reading the introduction, not the abstract.

The abstract is that dense first paragraph at the very beginning of a paper. In fact, that’s often the only part of a paper that many non-scientists read when they’re trying to build a scientific argument. (This is a terrible practice—don’t do it.).  When I’m choosing papers to read, I decide what’s relevant to my interests based on a combination of the title and abstract. But when I’ve got a collection of papers assembled for deep reading, I always read the abstract last. I do this because abstracts contain a succinct summary of the entire paper, and I’m concerned about inadvertently becoming biased by the authors’ interpretation of the results.

2. Identify the BIG QUESTION.

Not “What is this paper about”, but “What problem is this entire field trying to solve?”

This helps you focus on why this research is being done.  Look closely for evidence of agenda-motivated research.

3. Summarize the background in five sentences or less.

Here are some questions to guide you:

What work has been done before in this field to answer the BIG QUESTION? What are the limitations of that work? What, according to the authors, needs to be done next?

The five sentences part is a little arbitrary, but it forces you to be concise and really think about the context of this research. You need to be able to explain why this research has been done in order to understand it.

4. Identify the SPECIFIC QUESTION(S)

What exactly are the authors trying to answer with their research? There may be multiple questions, or just one. Write them down.  If it’s the kind of research that tests one or more null hypotheses, identify it/them.

Not sure what a null hypothesis is? Go read this , then go back to my last post and read one of the papers that I linked to (like this one ) and try to identify the null hypotheses in it. Keep in mind that not every paper will test a null hypothesis.

5. Identify the approach

What are the authors going to do to answer the SPECIFIC QUESTION(S)?

6. Now read the methods section. Draw a diagram for each experiment, showing exactly what the authors did.

I mean literally draw it. Include as much detail as you need to fully understand the work.  As an example, here is what I drew to sort out the methods for a paper I read today ( Battaglia et al. 2013: “The first peopling of South America: New evidence from Y-chromosome haplogroup Q” ). This is much less detail than you’d probably need, because it’s a paper in my specialty and I use these methods all the time.  But if you were reading this, and didn’t happen to know what “process data with reduced-median method using Network” means, you’d need to look that up.

Image credit: author

You don’t need to understand the methods in enough detail to replicate the experiment—that’s something reviewers have to do—but you’re not ready to move on to the results until you can explain the basics of the methods to someone else.

7. Read the results section. Write one or more paragraphs to summarize the results for each experiment, each figure, and each table. Don’t yet try to decide what the results mean , just write down what they are.

You’ll find that, particularly in good papers, the majority of the results are summarized in the figures and tables. Pay careful attention to them!  You may also need to go to the Supplementary Online Information file to find some of the results.

 It is at this point where difficulties can arise if statistical tests are employed in the paper and you don’t have enough of a background to understand them. I can’t teach you stats in this post, but here , here , and here are some basic resources to help you.  I STRONGLY advise you to become familiar with them.

Things to pay attention to in the results section:

• Any time the words “significant” or “non-significant” are used. These have precise statistical meanings. Read more about this here .
• If there are graphs, do they have error bars on them? For certain types of studies, a lack of confidence intervals is a major red flag.
• The sample size. Has the study been conducted on 10, or 10,000 people? (For some research purposes, a sample size of 10 is sufficient, but for most studies larger is better).

8. Do the results answer the SPECIFIC QUESTION(S)? What do you think they mean?

Don’t move on until you have thought about this. It’s okay to change your mind in light of the authors’ interpretation—in fact you probably will if you’re still a beginner at this kind of analysis—but it’s a really good habit to start forming your own interpretations before you read those of others.

9. Read the conclusion/discussion/Interpretation section.

What do the authors think the results mean? Do you agree with them? Can you come up with any alternative way of interpreting them? Do the authors identify any weaknesses in their own study? Do you see any that the authors missed? (Don’t assume they’re infallible!) What do they propose to do as a next step? Do you agree with that?

10. Now, go back to the beginning and read the abstract.

Does it match what the authors said in the paper? Does it fit with your interpretation of the paper?

11. FINAL STEP: (Don’t neglect doing this) What do other researchers say about this paper?

Who are the (acknowledged or self-proclaimed) experts in this particular field? Do they have criticisms of the study that you haven’t thought of, or do they generally support it?

Here’s a place where I do recommend you use google! But do it last, so you are better prepared to think critically about what other people say.

(12. This step may be optional for you, depending on why you’re reading a particular paper. But for me, it’s critical! I go through the “Literature cited” section to see what other papers the authors cited. This allows me to better identify the important papers in a particular field, see if the authors cited my own papers (KIDDING!….mostly), and find sources of useful ideas or techniques.)

UPDATE: If you would like to see an example of how to read a science paper using this framework, you can find one here .

I gratefully acknowledge Professors José Bonner and Bill Saxton for teaching me how to critically read and analyze scientific papers using this method. I’m honored to have the chance to pass along what they taught me.

I’ve written a shorter version of this guide for teachers to hand out to their classes. If you’d like a PDF, shoot me an email: jenniferraff (at) utexas (dot) edu. For further comments and additional questions on this guide, please see the Comments Section on the original post .

This piece originally appeared on the author’s personal blog and is reposted with permission.

Featured image credit:  Scientists in a laboratory of the University of La Rioja  by Urcomunicacion  (Wikimedia CC BY3.0)

Note: This article gives the views of the authors, and not the position of the LSE Impact blog, nor of the London School of Economics. Please review our  Comments Policy  if you have any concerns on posting a comment below.

About the Author

Jennifer Raff (Indiana University—dual Ph.D. in genetics and bioanthropology) is an assistant professor in the Department of Anthropology, University of Kansas, director and Principal Investigator of the KU Laboratory of Human Population Genomics, and assistant director of KU’s Laboratory of Biological Anthropology. She is also a research affiliate with the University of Texas anthropological genetics laboratory. She is keenly interested in public outreach and scientific literacy, writing about topics in science and pseudoscience for her blog ( violentmetaphors.com ), the Huffington Post , and for the Social Evolution Forum .

About the author

94 Comments

Very good Indeed.I always Read Abstract First Time always ……Thanks

Great information and guide to reading and understanding scientific paper. However, there are non-scientific student asked to do scientific research and it would be great to actually give an example and you point out the answers to the steps in the sample article or journal cited. Thank you.

• Pingback: Very useful (for scientists too): How to read and understand a scientific paper: a guide for non-scientists – microBEnet: the microbiology of the Built Environment network.
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• Pingback: Research Roundup: DOAJ’s Clean Sweep, A.I. In The Classroom And More | PLOS Blogs Network

I can summarize it eve further: three stars by a number in a table = good, no stars = bad

within the context of the fact that a very sizable portion of scientific papers are falsified, what does this article mean?

Your “fact” needs explanation and evidence, otherwise it can be considered alternative.

That’s why you don’t skip step 11

I think it would be useful also to point out that, even after diligently pursuing all of these excellent steps, the reader is usually still unable to determine whether the subjects or materials even existed. Unlike with lay media, where most important stories are covered by multiple sources, and where facts are sometimes checkable from primary sources – even by readers – it is rare indeed that a reader can go beyond the words on the page.

Is the fact that you read instructions on how to read a paper not evidence that there is something wrong with the way we write papers?

The issue of scientific literacy is always challenging for my students. But this is the most practical and helpful guide I’ve ever seen on the web, thanks for this. I usually share with my students the following tips already mentioned above: – Learn the vocabulary before reading – Summarize the background in five sentences or less – Identify the BIG QUESTION

But the pieces of advice this guide gives are structured better and easier. I especially love this one: Don’t yet try to decide what the results mean, just write down what they are. Thanks again for writing this piece!

• Pingback: Como ler um artigo científico – um guia para não-cientistas | Antônio Carlos Lessa

you left out ask for the data, so you can check for yourself… (ie trust but verify)

an example a psychology paper that surveyed a group of people about conspiracy theories (n=137) and it’s main/only novel finding was that people that believed in conspiracies theories, there was a tendency for people to believe in mutually contradictory conspiracy theories. ie individual could believe that Princess Diana faked her own death, whilst at the same time had been murdered by MI5

The paper, was duly called – Dead and Alive – M Wood et al…

However. after requesting the data. there was not a single individual person that ticked the survey boxes, that simultaneously believed this finding. Not one person.

The problem, most people surveyed did not believe either of those conspiracies, and inappropriate stats method was applied to data, that assumed a non skewed dataset. Thus, not believing in A and not believing in B correlated, but it also gave a ‘result that believing in A, and Believing in B also correlated..

A very dumb paper… Author still hasn’t retracted it yet.

• Pingback: How to Read a Scientific Paper as a Non-Scientist » Public(s) Sociology

I love this! Great simmered-down resource for my undergrads- both science and non-science majors. Thanks for sharing!

“Web of Science” link is broken (at least for me) but a useable alternative is webofknowledge.com (same resource, different name).

I think it is important to note that the journal in which a paper is published is no proof as to the rigor of that paper. A listing in PubMed does not guarantee quality; thus, you need to focus on teaching people how to interpret the paper without relying on a simple JTASS approach to initial assessment. This may be a guide, but nothing more. I say this as a former editor of a MEDLINE journal. There can be good papers in bad journals and bad papers in good ones. But you are correct. Key questions are: What is the question? How will we answer the question? What answer did we get? Did we use the right tools to answer the question? What do we think it means? What else could we do? And thus we can train people to watch for sleights of hand, such as shifting primary outcomes, data mining, salami slicing, etc.

• Pingback: How to read and understand a scientific paper: a guide for non-scientists – Sociology of Knowledge

Yikes! This is a lot of work just to read a single paper! It’s almost the same as writing a paper! I understand the logic in why you recommend this, but the average person is going to be willing to spend 20-30 minutes reading and trying to learn. This method calls for multiple hours of effort and I just don’t seem many non-scientist people being willing to do that when they’re more curious than actually invested. I was really hoping this entry was going to make it easier to navigate the foreign and confusing world that these papers represent, and it probably will if someone does this process repeatedly for quite some time…..like a scientist…..but most of us aren’t scientists and don’t have that kind of time to dedicate to something that’s not our work or family.

By tradition, we expect our scientists to report their findings by codifying them in unreadable gobbledygook. Then we write instructions on how to decode that unreadable nonsense!!

We need to encourage papers to be written in everyday language so it is easier for all. Problem solved.

I wholeheartedly agree with Kaveh Bazargan. From personal experience as a non-scientist trying to do this with medical research papers is a very intimidating and isolating experience. Most people don’t have the time spare to even try to learn this skill. It would be great if systematic reviewers who are acknowledged experts in reading and analysing papers could find a way of communicating the important information about individual papers to non-scientists before – or instead of – burying them in systematic reviews and meta-analyses which are even more difficult to understand. Structured plain language summaries of primary research would be very helpful rather than individuals having to teach themselves how to read and understand a scientific paper which is written for other scientists in “unreadable goggledygook”. Many (most?) papers conceal methodogical flaws in the research conduct which are almost impossible to spot without years of scientific training.

I love this! Extraordinary cooled off assets for my students both science and non-science majors. A debt of gratitude is in order for sharing!

Regarding step 11, if you have access to Web of Science I recommend looking up how many citations the paper has (this will also vary depending on the age of the paper) and who cites it, and whether there even any replies to it in the peer-reviewed literature.

Do you literally do this for every paper you read? I’m curious how much time it takes you to go from start to finish on what you would consider a typical paper. How often do you read new articles a week?

This post has the laudable goal of helping nonscientists understand the primary literature, but the recommendations seem even more onerous than they have to be. For example, the idea that one should write down every single word that he/she doesn’t know? That sounds more like a task for a scientist scrutinizing the work of a rival. For a nonscientist, there may be dozens and dozens of unknown words, and chasing down the meaning of each one may cause a serious forest/trees problem. I agree that there’s no substitute for the hard work of digging into a paper, but following the prescribed advice to the letter would be utterly exhausting for almost any lay reader. I base these comments on my experiences as a biology researcher and undergraduate instructor.

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I really like your post and the effort, but much of the problem wouldn’t exist if we, academics, did a better job in writing down the correct conclusions. Researcher degrees of freedom are seldom properly understood and we keep on having the tendency to be overdeterministic about statistics that are not intended as such. Of course we want to communicate in black and white about our tests (significance!) because it is a human tendency to persuade the reader. Most of the research probably is not as inconsistent as it first seems but we forget to report the proper statistics to see so (CI around the ES)

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Thank you very much for sharing a guide that will help me to follow the best standards for writing a scientific paper even I am not a scientist.

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Reading the abstract last is one, not the, way to read a paper. It it biases the naive reader, then they are not reviewing with a level of skepticism required to evaluate science. We put abstracts first because they lay out the problem, overview the sample and design, and tersely describe what they think they discovered. Then, as I read, I have a roadmap in my head of what to look for to determine for myself whether or not they found something noteworthy.

What is the problem? Are hypotheses to be tested likely to illuminate/clarify the problem? Is the sample appropriate for testing and was it sampled without imputing bias? Were measures appropriate and do they have a history of validity? We the analytics applied appropriate for testing at the level of power needed give the sample size? [Here even many scientist are ill-equipped to judge.] After enumerating results, do the authors list weaknesses in their design that might suggest replication is necessary? If not, check for snow – as in snowjob. If significance levelsare low or variables correlate with one another too much, are moderators discussed? [e.g., results hold for males but not females, old vs young, fat vs skinny, etc.). If so, why were data not re-analyzed to control for moderator effects on results?

Lastly, if the word “prove” appears anywhere in the paper, assume it is junk science (like fake news). Research is never ever done to prove anything. Research is only done to find out. Once a preponderance of studies report a similar finding looking at the same problem with different people, measures, designs, and statistical analyses, then you have something like proof; consensus.

Lastly, if you are a conspiracy theory believer, you will disbelieve any scientific study that does not support your word view. Keep this in mind. A few studies that run counter to the prevailing consensus is not PROOF that your conspiracy is correct, and mainstream science is wrong. I do not know a single scientist (and I know thousands globally) who do not consider climate change to be well-evidenced. Similarly, evolutionary theory remains useful – our current understanding of genomic medicine hinges on cellular mutation, which is evolution on a microscopic scale.

This is a very useful set of instructions, but I found the following statement highly amusing: “Before you begin reading, take note of the authors and their institutional affiliations. Some institutions (e.g. University of Texas) are well-respected; others (e.g. the Discovery Institute) may appear to be legitimate research institutions but are actually agenda-driven.”

All research institutions are agenda driven (including my alma mater, the University of Texas), because funding and professional advancement depend on results. Researchers are fallible humans and subject to temptation and error. There is a very big lawsuit pending against Duke University (see below) for falsifying data.

When I read any research (especially medical), I now search for evidence of legal or professional action. So you might add that as #12: “Lawsuits? Retractions?” Caveat lector.

http://science.sciencemag.org/content/353/6303/977.full

http://www.dukechronicle.com/article/2016/09/experts-address-research-fabrication-lawsuit-against-duke-note-litigation-could-be-protracted

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Weird advice, like: ‘I always read the abstract last’ . This is advice for referees, not for general readers. I always read the abstract first.

An abstract can be misleading, but I am often not qualified enough to judge that. Actually, this blog post title and abstract are misleading too: your advice is for referees, not for non-scientists. So you wanted to provide an immersive experience into a misleading piece, well done 😉

First thing, get rid of the word proof. This is a huge error in that even if you have reputable scientists, journals, institutions, etc. that what is published, especially in a single article, is anything resembling a fact. It is merely research findings from one instance and in no way forms a fact. This is the next level of misinterpretation of science, even among those able to comprehend the journal article, that science produces or discovers facts. There is nothing that is factual that we know of.

Several comments:

For the mid-term exam in a graduate class I took in experimental design the professor would select half a dozen articles from the peer reviewed literature, tell her students to pick three and explain what they had done wrong. New articles for every class and she never ran out.

Beware of articles published in inappropriate journals, no matter how respectable (E.g., something about sociology or criminology published in a medical journal). This is a strategy for sneaking agenda driven research past the peer review process by going to a journal whose reviewers are likely to be unfamiliar with the subject while the editors are sympathetic to the agenda.

There is a reason research papers are written in what looks like “scientific gobbledygook” to lay persons. They are not intended for a lay audience and the goal is to be extremely precise with the technical details of what was done and found so other scientists can examine the results and, most important, attempt to replicate them.. There is no way to simplify the language and put it in lay terms without losing the precision required for a scientific study. E.g., a particle physicist may give a lay explanation of an experiment in metaphorical terms of little balls of energy smashing into each other, but their peers are going to want to see the pages and pages of mathematics that really describe what was happening.

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I would add “Check the source of funding for the research.” If paper on the safety of glyphosate is funded by Bayer or Monsanto, or a paper on climactic change is funded by Exxon, read no further.

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Get the dissertation writing service students look for these days with the prime focus being creating a well researched and lively content on any topic.

The non-scientist should pay extra attention towards this article for the non-technical writing and understanding for them.

A lot of a researcher’s work includes perusing research papers, regardless of whether it’s to remain progressive in their field, propel their logical comprehension, survey compositions, or assemble data for a task proposition or concede application. Since logical articles are not the same as different writings, similar to books or daily paper stories, they ought to be perused in an unexpected way.

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Thanks, I’ll use this a lot for my MSc Thesis.

Those are some great tips but please don’t forget that each school has its own requirements to academic papers.

Clarifying your methodology for reading science paper: excellent idea and great information. Thanks a lot!

Thanks for sharing this blog. Its very helpful for me and I bookmarked this for future

Excelente trabajo, original. Lo recomendaré para mis estudiantes de Posgrado. Si no hay problema, me gustaría hacer una traducción al castellano para el uso de mis estudiantes de pregrado de Sociología.

Excellent work,original. I will recommend it for my graduate students. If there is no problem, I would like to make a translation into Spanish for the use of my undergraduate Sociology students.

Hi Luis, all our works are CC licensed so you are more than welcome to make a translation provided you link back to the original source. See here for details: https://creativecommons.org/licenses/by/3.0/deed.en_GB

Great information , it is very helpful thanks for sharing the blog .

Step 1 and 10 is a great idea, but I still think it’s possible to read the abstract with the introduction and still keep an open mind? and shouldn’t they keep their results for the interpretation section? sorry new to reading scientific papers

Step 1 and 10 is a great idea, but I still think it’s possible to read the abstract with the introduction and still keep an open mind? and shouldn’t they keep their results for the interpretation section? sorry new to reading scientific papers

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Thank you for sharing the tips, they were very helpful.

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The article is extremely helpful. Considering that scientific research are not as easy, the tips in the article are great.

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Thank you for posting this. It has really helped a lot, especially for those of us who always read the abstract first haha

Thanks for writing this blog. It is very much informative and at the same time useful for me

Yeah, great advice on how to be objective from someone who openly declares their prejudice in the opening statement.

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Do you in a real sense do this for each paper you read? I’m interested what amount of time it requires for you to go beginning to end on what you would think about an average paper. How frequently do you read new articles seven days?

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That is literally my question too, I see it as quite time consuming to conduct such a lengthy process for all scientific articles we come across especially as one has other responsibilities to give attention too

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There is a reason research papers are written in what looks like “scientific gobbledygook” to lay persons. They are not intended for a lay audience and the goal is to be extremely precise with the technical details of what was done and found so other scientists can examine the results and, most important, attempt o replicate them.

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Thanks for posting this. You are doing a service to the general public and also graduate students by not only posting this but answering all sincere questions. I have a Ph. D. in Zoology and have been a peer-reviewer for at least 12 papers and am first author of three peer-reviewed papers. I have taught statistics in two universities as a contract professor and all of my papers rely on use of statistics. To answer a frequently asked question, yes, personally it can take me a couple of hours or several more to read some papers. This is true for my colleagues as well. Scientific papers are written so as to be as concise as possible and this can make them hard to read. They often also use technical terms which one has to look up. At least biology and statistics. nothing I have read (or written) has been in “goobledygook” or purposely incomprehensible jargon but they do use terms and concepts that are probably unfamiliar to the layman. I think what the author means, by her comment on absstracts can be intepreted as “don’t JUST read the abstract. Be sure to read the introduction. Personally I go to the discussion and conclusion next.

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Your writing skills and passion for sharing your knowledge and experiences are truly outstanding. . Keep writing and inspiring others with your words.

I would add, look at who funded the study and their financial interests. Most science is not independent it is funded by those with an agenda. Look at the demographic data, length of time the study took place, what was left out, where you might need more information. Look at who was included and excluded in the data set. Anyone that has taken statistics knows what you include or exclude in the data set can skew and or outright change the outcome.

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How to Read Research Papers— Unveiling AI Tool for Reading

Table of Contents

Reading research papers is an essential skill for students, academics, and professionals in various fields. It allows you to stay updated with the latest findings, develop critical thinking skills, and contribute to scholarly discussions. However, understanding these papers can be challenging due to their complex language and structure. That’s why we have written this article, which will provide you with comprehensive strategies on how to read a research paper effectively.

Let’s get started with how to identify the structure of a research paper!

Identify the structure of a research paper

Understanding the structure of a research paper is the first step toward how to read research paper effectively. Most research papers follow a standard structure, which includes an abstract , introduction , methodology , results, discussion and conclusion . Familiarizing yourself with the research paper structure can help you navigate the paper and understand its content.

Each section of a research paper serves a specific purpose. The abstract provides a summary of the entire research paper, the introduction presents the research question, the methodology explains how the research was conducted, the results section presents the findings, the discussion interprets these findings, and the conclusion summarizes the paper and suggests areas for future research.

Source: University of Wisconsin

Abstract: The abstract serves as a concise summary of the entire research paper. To efficiently grasp its content, focus on key elements such as the research question, methodology, and significant findings. This will provide a quick overview and help you decide whether the paper aligns with your interests.

Introduction: The research paper introduction sets the stage for the research, presenting the problem statement and the purpose of the study. Take note of the research gap, hypotheses, and objectives discussed here to understand the context of the paper.

Methodology: Understanding the methods employed in a study is crucial for evaluating the research's validity. Take note of the research design, data collection, and analysis methods to comprehend how the study was conducted.

Results: The results section presents the outcomes of the research. Approach this section with a critical mindset, assessing whether the results align with the research question and the methods used. Consider the implications of the findings within the broader context of the field.

Conclusion: The conclusion summarizes the key findings and their significance. It's a crucial part of the paper that brings together the entire study. Take the time to reflect on how the research contributes to the existing body of knowledge.

Citations: Follow the trail of references provided in the paper. This not only enhances your understanding but also leads you to related works that can deepen your knowledge of the subject.

More tips on how to read research papers effectively

Developing effective reading strategies can help you understand research papers more efficiently. These strategies include active reading, note-taking, and using AI tools for summarizing and understanding research papers.

Active reading involves engaging with the text, asking questions, and making connections. Note-taking helps you remember important information and organize your thoughts. Summarizing using AI tools allows you to condense the information and understand the main points of the paper easily.

Active Reading:

Active reading is a strategy that involves interacting with the text. This can include highlighting important information, making notes in the margins, and asking questions. Active reading can help you understand the content of the paper and remember it more effectively.

When reading a research paper, try to identify the main points, arguments, and evidence. Ask yourself questions like:

• What is the research question?
• What methods were used to answer it?
• What were the results? What conclusions were drawn?

This will help you engage with the paper and understand its content.

Source: https://idaho.pressbooks.pub/write/chapter/reading-for-writing/

Note-Taking:

Note-taking is another effective reading strategy. It involves writing down important information, ideas, and questions. Note-taking can help you remember the content of the paper, organize your thoughts, and prepare for discussions or writing assignments.

When taking notes, try to be concise and use your own words. This will help you understand the information and remember it more effectively. You can also use symbols or diagrams to represent complex ideas.

Source: University of Toronto

Using AI Tools to Summarize Research Paper:

When research papers are flooded with complex language, jargon, and acronyms, it’s important to use AI summarizer that helps you breakdown the sentences and makes it easier to read the information. In that case, you can make use of SciSpace Copilot which not only explains the highlighted section or paragraph, but also explains you the equations, tables, figures, and images present in the research paper. You can also rely on other AI tools to comprehend research papers in a short span of time.

Watch this video to learn how to use the AI summarizer:

Dealing with Technical Jargon:

Research papers often contain a lot of technical jargon. Don't be intimidated; instead, create a glossary for yourself. Look up unfamiliar terms and gradually build your understanding of the terminology used in your field of interest. As mentioned above, you can use AI summarizer to decode the jargon and get the essence of the research paper.

Joining Academic Communities:

Engage in discussions and forums related to your area of interest. Academic communities provide valuable insights, differing perspectives, and opportunities for networking with experts in the field.

Staying Updated on Research Trends:

To read research papers effectively, it's crucial to stay informed about the latest developments in your field. Subscribe to academic journals, follow reputable researchers on social media, and attend conferences or webinars to stay updated.

Using Academic Search Engines:

Make use of online tools and databases such as Google Scholar, PubMed, SciSpace , and academic journals to access a vast repository of research papers. These platforms often provide additional features like citation tracking and related articles, enriching your reading experience.

Also Read: Beast Academic Search Engines(2024)

Reading research papers is a complex task that requires a good understanding of the structure of a research paper, effective reading strategies, and the ability to interpret results. However, with practice and patience, you can develop these skills and become proficient at reading research papers.

Remember, the goal is not just to read the paper, but to understand it, evaluate it, and use it to contribute to your own research or professional development.

Frequently Asked Questions

Active reading helps understand research papers better. It involves activities like highlighting, taking notes, asking questions, and summarizing. This makes it easier to understand and evaluate the research material.

Taking notes during research helps you remember important information, stay organized, avoid plagiarism, think critically, and serve as a reference for future use, allowing you to revisit key points and findings as needed.

SciSpace notebook is the go-to tool for taking notes effortlessly

The best AI tool for reading research papers varies based on individual needs. A popular AI tools include SciSpace Copilot.

Using AI tools to read research papers is easy. First, choose a tool, example — SciSpace Copilot. Then, upload your paper. It analyzes it and explains it in a language of your choice. You can then use this summary to help with your research or understanding of the topic.

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How to Read a Scientific Paper overview

Below, you'll find two different articles about how to read a scientific paper. The second one is written by a science journalist and was added to this guide in 2024. We hope you find both articles useful. They overlap and bring useful techniques to light. 

How to read and understand a scientific paper: a guide for non-scientists

• Handout for How to Read and Understand a Scientific Paper: A Guide for Non-Scientists

Reprinted by permission of the author, Jennifer Raff, Assistant Professor, Department of Anthropology, University of Kansas,  https://about.me/jenniferraff  ::  original URL:  https://violentmetaphors.com/2013/08/25/how-to-read-and-understand-a-scientific-paper-2/ Last week’s post ( The truth about vaccinations: Your physician knows more than the University of Google ) sparked a very lively discussion, with comments from several people trying to persuade me (and the other readers) that  their  paper disproved everything that I’d been saying. While I encourage you to go read the comments and contribute your own, here I want to focus on the much larger issue that this debate raised: what constitutes scientific authority?

It’s not just a fun academic problem. Getting the science wrong has very real consequences. For example, when a community doesn’t vaccinate children because they’re afraid of “toxins” and think that prayer (or diet, exercise, and “clean living”) is enough to prevent infection,  outbreaks happen .

“Be skeptical. But when you get proof, accept proof.” –Michael Specter

What constitutes enough proof? Obviously everyone has a different answer to that question. But to form a truly educated opinion on a scientific subject, you need to become familiar with current research in that field.  And to do that, you have to read the “primary research literature” (often just called “the literature”). You might have tried to read scientific papers before and been frustrated by the dense, stilted writing and the unfamiliar jargon. I remember feeling this way!  Reading and understanding research papers is a skill which every single doctor and scientist has had to learn during graduate school.  You can learn it too, but like any skill it takes patience and practice.

I want to help people become more scientifically literate, so I wrote this guide for how a layperson can approach reading and understanding a scientific research paper. It’s appropriate for someone who has no background whatsoever in science or medicine, and based on the assumption that he or she is doing this for the purpose of getting a basic  understanding of a paper and deciding whether or not it’s a reputable study.

The type of scientific paper I’m discussing here is referred to as a  primary research article . It’s a peer-reviewed report of new research on a specific question (or questions). Another useful type of publication is a  review article . Review articles are also peer-reviewed, and don’t present new information, but summarize multiple primary research articles, to give a sense of the consensus, debates, and unanswered questions within a field.  (I’m not going to say much more about them here, but be cautious about which review articles you read. Remember that they are only a snapshot of the research at the time they are published.  A review article on, say, genome-wide association studies from 2001 is not going to be very informative in 2013. So much research has been done in the intervening years that the field has changed considerably).

Before you begin: some general advice Reading a scientific paper is a completely different process than reading an article about science in a blog or newspaper. Not only do you read the sections in a different order than they’re presented, but you also have to take notes, read it multiple times, and probably go look up other papers for some of the details. Reading a single paper may take you a very long time at first. Be patient with yourself. The process will go much faster as you gain experience.

Most primary research papers will be divided into the following sections: Abstract, Introduction, Methods, Results, and Conclusions/Interpretations/Discussion. The order will depend on which journal it’s published in. Some journals have additional files (called Supplementary Online Information) which contain important details of the research, but are published online instead of in the article itself (make sure you don’t skip these files).

Before you begin reading, take note of the authors and their institutional affiliations. Some institutions (e.g. University of Texas) are well-respected; others (e.g.  the Discovery Institute ) may appear to be legitimate research institutions but are actually agenda-driven.  Tip: g oogle “Discovery Institute” to see why you don’t want to use it as a scientific authority on evolutionary theory.

Also take note of the journal in which it’s published. Reputable (biomedical) journals will be indexed by  Pubmed . [ EDIT: Several people have reminded me that non-biomedical journals won’t be on Pubmed, and they’re absolutely correct! (thanks for catching that, I apologize for being sloppy here). Check out  Web of Science  for a more complete index of science journals. And please feel free to share other resources in the comments!]    Beware of  questionable journals .

  As you read, write down  every single word  that you don’t understand. You’re going to have to look them all up (yes, every one. I know it’s a total pain. But you won’t understand the paper if you don’t understand the vocabulary. Scientific words have extremely precise meanings).

Step-by-step instructions for reading a primary research article

1. Begin by reading the introduction, not the abstract.

The abstract is that dense first paragraph at the very beginning of a paper. In fact, that’s often the  only  part of a paper that many non-scientists read when they’re trying to build a scientific argument. (This is a terrible practice—don’t do it.).  When I’m choosing papers to read, I decide what’s relevant to my interests based on a combination of the title and abstract. But when I’ve got a collection of papers assembled for deep reading, I always read the abstract  last . I do this because abstracts contain a succinct summary of the entire paper, and I’m concerned about inadvertently becoming biased by the authors’ interpretation of the results.

2. Identify the BIG QUESTION.

Not “What is this paper about”, but “What problem is this entire field trying to solve?”

This helps you focus on why this research is being done.  Look closely for evidence of agenda-motivated research.

3. Summarize the background in five sentences or less.

Here are some questions to guide you:

What work has been done before in this field to answer the BIG QUESTION? What are the limitations of that work? What, according to the authors, needs to be done next?

The five sentences part is a little arbitrary, but it forces you to be concise and really think about the context of this research. You need to be able to explain  why  this research has been done in order to understand it.

4.   Identify the SPECIFIC QUESTION(S)

What  exactly  are the authors trying to answer with their research? There may be multiple questions, or just one. Write them down.  If it’s the kind of research that tests one or more null hypotheses, identify it/them.

Not sure what a null hypothesis is? Go read  this , then go back to my last post and read one of the papers that I linked to (like  this one ) and try to identify the null hypotheses in it. Keep in mind that not every paper will test a null hypothesis.

5. Identify the approach

What are the authors going to do to answer the SPECIFIC QUESTION(S)?

  6. Now read the methods section. Draw a diagram for each experiment, showing exactly what the authors did.

I mean  literally  draw it. Include as much detail as you need to fully understand the work.  As an example, here is what I drew to sort out the methods for a paper I read today ( Battaglia et al. 2013: “The first peopling of South America: New evidence from Y-chromosome haplogroup Q” ). This is much less detail than you’d probably need, because it’s a paper in my specialty and I use these methods all the time.  But if you were reading this, and didn’t happen to know what “process data with reduced-median method using Network” means, you’d need to look that up.

You don’t need to understand the methods in enough detail to replicate the experiment—that’s something reviewers have to do—but you’re not ready to move on to the results until you can explain the basics of the methods to someone else.

7.   Read the results section. Write one or more paragraphs to summarize the results for each experiment, each figure, and each table. Don’t yet try to decide what the results  mean , just write down what they  are.

You’ll find that, particularly in good papers, the majority of the results are summarized in the figures and tables. Pay careful attention to them!  You may also need to go to the Supplementary Online Information file to find some of the results.

 It is at this point where difficulties can arise if statistical tests are employed in the paper and you don’t have enough of a background to understand them. I can’t teach you stats in this post, but  here ,  here , and  here  are some basic resources to help you.  I STRONGLY advise you to become familiar with them.

  THINGS TO PAY ATTENTION TO IN THE RESULTS SECTION:

-Any time the words “ significant ” or “ non-significant ” are used. These have precise statistical meanings. Read more about this  here .

-If there are graphs, do they have  error bars  on them? For certain types of studies, a lack of confidence intervals is a major red flag.

-The sample size. Has the study been conducted on 10, or 10,000 people? (For some research purposes, a sample size of 10 is sufficient, but for most studies larger is better).

8. Do the results answer the SPECIFIC QUESTION(S)? What do you think they mean?

Don’t move on until you have thought about this. It’s okay to change your mind in light of the authors’ interpretation—in fact you probably will if you’re still a beginner at this kind of analysis—but it’s a really good habit to start forming your own interpretations before you read those of others.

9. Read the conclusion/discussion/Interpretation section.

What do the authors  think  the results mean? Do you agree with them? Can you come up with any  alternative  way of interpreting them? Do the authors identify any weaknesses in their own study? Do you see any that the authors missed? (Don’t assume they’re infallible!) What do they propose to do as a next step? Do you agree with that?

10. Now, go back to the beginning and read the abstract.

Does it match what the authors said in the paper? Does it fit with your interpretation of the paper?

11. FINAL STEP:  (Don’t neglect doing this)  What do other researchers say about this paper?

Who are the (acknowledged or self-proclaimed) experts in this particular field? Do they have criticisms of the study that you haven’t thought of, or do they generally support it?

Here’s a place where I do recommend you use google! But do it last, so you are better prepared to think critically about what other people say.

(12. This step may be optional for you, depending on why you’re reading a particular paper. But for me, it’s critical! I go through the “Literature cited” section to see what other papers the authors cited. This allows me to better identify the important papers in a particular field, see if the authors cited my own papers (KIDDING!….mostly), and find sources of useful ideas or techniques.)

Now brace for more conflict– next week we’re going to use this method to go through a paper on a controversial subject! Which one would you like to do? Shall we critique one of the papers I posted last week?

UPDATE: If you would like to see an example, you can find one  here ———————————————————————————————————

I gratefully acknowledge Professors José Bonner and Bill Saxton for teaching me how to critically read and analyze scientific papers using this method. I’m honored to have the chance to pass along what they taught me.

How to Read a Scientific Paper by a science journalist

How to read a scientific paper.

• Alexandra Witze
• November 6, 2018

   Léelo en español

It’s one of the first, and likely most intimidating, assignments for a fledgling science reporter. “Here,” your editor says. “Write up this paper that’s coming out in  Science  this week.” And suddenly you’re staring at an impenetrable PDF—pages of scientific jargon that you’re supposed to understand, interview the author and outside commenters about, and describe in ordinary English to ordinary readers.

Fear not!  The Open Notebook  is here with a primer on how to read a scientific paper. These tips and tricks will work whether you’re covering developmental biology or deep-space exploration. The key is to familiarize yourself with the framework in which scientists describe their discoveries, and to not let yourself get bogged down in detail as you’re trying to understand the overarching point of it all. As a specific example, we’ve marked up a  Science  paper in the accompanying image.

But first, let’s break down what a typical scientific paper contains. Most include these basic sections, usually in this order:

The  author list  is as it sounds, a roster of the scientists involved in the discovery. But hidden within the names are  clues that will help you navigate the politics  of reporting the story. The first name in the list is often (but not always) the person who did the most work, perhaps the graduate student or postdoc who is the lead on the project. This person is usually (but not always) designated as the “corresponding author” by an asterisk by their name, or by their email address being given on the first or last page of the paper. If the corresponding author is not the first name in the author list, then take extra care to Google the various authors and figure out how they relate to one another. (In many fields, such as biology and psychology, the last author in the list is typically the senior author or lab head. In others, such as experimental physics where the author list can number in the dozens or hundreds, authors are usually listed alphabetically.) The senior author might be able to provide some broad perspective as to why and how the study was undertaken. But the first or corresponding author is much more likely to be the person who actually did the work, and therefore your better request for an interview.

The  abstract  is a summary of the paper’s conclusions. Always read this first, several times over. Usually the significance of the paper will be laid out here, albeit in technical terms. A good abstract will summarize what research was undertaken, what the scientists found, and why it’s important. (Compare the abstract of  this recent  Nature  paper , on the discovery of a prehistoric human hybrid, to the first three paragraphs of  Sarah Kaplan’s  Washington Post  story reporting the discovery . Kaplan clearly captures the essence of the new findings as described in the abstract.) Relevant numbers such as the statistical significance of the finding are often highlighted here as well. Abstracts are prone to typographical errors, so be sure to double-check numbers against the body of the paper as well as your interview with the author.

The  body  of the paper lays out the bulk of the scientific findings. Pay special attention to the first couple of paragraphs, which often serve as an introduction, describing previous research in the field and why the new work is important. This is an excellent place to hunt for references to other papers that can serve as your guidepost for outside commenters (more on that later). Next will come the details of how the research was done; sometimes much of this is broken out into a later  methods  section (see below). Then come the  results , which may be lengthy. Look for phrases such as “we concluded” to clue you in to their most important points. If statistics are involved, see Rachel Zamzow’s  primer on how to spot shady statistics.

The final section (sometimes labeled as  discussion ) often summarizes the new findings, puts them in context, and describes the likely next steps to be taken. If your reading has been dragging through the results section, now is the time to refocus. “That sort of information will help a writer answer the nearly inevitable “so what?” question for their readers as well as their editors,” says Sid Perkins, a freelance science writer in Crossville, Tennessee, who writes for outlets including  Science  and  Science News for Students .

The  figures  are the data, graphics, or other visual representations of the discovery. Read these and their captions carefully, as they often contain the bulk of the new findings. If you don’t understand the figures, ask the scientist to walk you through them during your interview. Don’t be afraid to say things like, “I don’t understand what  the x-axis  means.”

The  references  are your portal into a world of additional inscrutable PDFs. You need to plow through at least a couple of the citations, because they are your initial guide in figuring out who you need to call for outside comment. The references are referenced (usually by number) within the body of the text, so you can pinpoint the ones that will be most helpful. For instance, if the text talks about how previous studies have found the opposite of this new one, go look up the cited references, because those authors would be excellent outside commenters. If you do not have access to the journals described in the references, you can at least look at the paper abstract, which is always  outside the paywall , to get a sense of what those earlier studies concluded. (For further caveats on references, see below.)

The  acknowledgments  are meant for transparency, to show the contributions of the various authors and where they got their funding from. Things to look for in here are whether they thank other scientists for “discussions” or “review” of the work; sometimes peer reviewers are explicitly acknowledged as such, in which case you can call those people right away for outside comment. Occasionally there are humorous tidbits that  you can pick up on for a story , such as when authors thank the field-camp guards who kept them  safe from predatory polar bears . The funding section is usually pro forma, but it is worth scanning for mention of unusual sources of income, such as from a science-loving philanthropist. If the authors declare competing financial interests (such as a patent filing) you will need to report those out and make sure you understand what financial conflicts of interest may be clouding their objectivity.

The  methods  often appear in a ridiculously small typeface after the body of the paper. These lay out how the actual experiments were done. Scour these for any details that will bring your story to life. For instance, they might describe how the climate models were so complicated that they took more than a year to run on one of the world’s most powerful supercomputers.

Supplementary information  comes with some but not all papers. In most cases it is extra material that the journal did not want to devote space to describing in the paper itself. Always check it out, because there may be hidden gems. In  a 2015 study of global lake warming , the only way to find out which specific lakes were warming—and  talk about the nearest ones for readers —was to wade through the supplementary information. In another recent example, Harvard researchers left it to the supplementary information to explain  that they cranked up a leaf-blower  to see how lizards fared during hurricanes, a fact that the Associated Press’s Seth Borenstein  turned into his lede .

So now you’re armed with the basics of what makes up a science paper. How should you tackle reading for your next assignment? The task will be more manageable if you break it into a series of jobs.

Strategize During the First Pass

Your first dive into a paper should be aimed at gathering the most important information for your story—that is, what the research found and why anyone should care. For that, consider following the approach of Mark Peplow, a freelance science journalist in Cambridge, England, who writes for publications including  Nature  and  Chemical & Engineering News .

If it’s a field he’s relatively familiar with, such as chemistry or materials science, Peplow takes a first pass through the paper, underlining with a red pen all the facts that are likely to make it into his initial draft. “That means I can produce a skeleton first draft of the story by simply writing a series of sentences containing what I’ve underlined, and then go into editing mode to jigsaw them into the right order,” he says. (In my annotated example, I’ve done this for the abstract using a purple pen.)

As Peplow reads, he looks for numbers to help make the story sing (“… so porous that a chunk of material the size of a sugar cube contains the surface area of 17 tennis courts”—see orange highlighter in the annotated paper) and methodological details that might prompt a fun interview question (“How scary was it to be pouring that very hazardous liquid into another one?”). He also keeps an eye out for anything indicating an emerging trend or other examples of the same phenomenon, which can be useful for context within the story or as a forward-looking kicker (see how he pulls this off in  this  Chemical & Engineering News  story) .

But what if the paper is in a field you’re not experienced with, and you don’t understand the terminology? Peplow has a plan for that too. “I read the abstract, bathe in my lack of understanding, and mentally throw the abstract away,” he says.

Then he goes through the paper, underlining fragments he understands and putting wiggly lines next to paragraphs that he thinks sound important, but doesn’t actually know what they mean. Jargon words get circled, and equations ignored. He forges onward, paying attention to phrases such as “our findings,” “revealed,” “established,” or “our measurements show”—signs that these are the new and important bits. “Once I’ve reached the end of the paper, and I’m sure I don’t understand it, I remind myself it’s not my fault,” Peplow says.

At that point, Peplow starts looking up definitions for the jargon words, either with Google or Wikipedia or in a stack of science reference books he picked up for free when a local library closed. He jots definitions of the words on the paper. To understand concepts, he sometimes searches  EurekAlert!  for past press releases that explain core concepts, or Googles a string of keywords and adds “review” to hunt for a more comprehensible description.

By this point, Peplow can circle back to the paragraphs marked with wiggly lines and start to understand them better. What he doesn’t yet comprehend, he marks down as an interview question for the researcher.

Circle Back for What You May Have Missed

Before picking up the phone for that interview, it’s worth making a second pass through the paper to see what else you need to help you in your reporting. Check, usually near the end of the paper, to see whether the scientists discuss what the next steps should be—either for their own team or for other groups following up to confirm or expand on the new results, says Perkins. That can provide a ready-made kicker for your story.

Susan Milius, a reporter who covers the life sciences for  Science News , often makes a beeline straight for the references to try to start identifying outside commenters for a piece. She will find those PDFs and then look within the references’ references to build a broad understanding of the field. One caveat, though: Be sure to research how these possible commenters are connected to the author of the current study. Once, Milius phoned an outside commenter who had published on the topic in question some years earlier—but that scientist turned out to be the spouse of the new paper’s author. She had a different last name than her husband.

It’s also worth remembering that the authors may well be biased in which references they include in the paper. Self-citations, in which authors try to boost their citation count by adding their previous publications to the reference list, are common. And sometimes authors deliberately omit papers by competing groups, a fact that is not always caught during the peer-review process. So don’t rely on the references within the PDF to be comprehensive; try a Google Scholar search using keywords from the paper to unearth whether there are competing groups out there.

Other clues may lie in how long the manuscript took to make it through the peer-review process. For many journals these dates come at the very end of the paper, marked something like “submitted” and “accepted.” Different journals have different timescales for publishing, but it is always worth looking to see whether the manuscript languished an extraordinary amount of time (like many months) in the review process. If so, ask the author why things took so long. (A fairly innocuous way to do this is to say something like, “I noticed it took a while for this paper to be accepted. Can you tell me how that process went?” Then be prepared for the authors to go on a rant about peer review.)

Hunt for Extra Details

Finally, see if there are additional sources of information you can sweep into your reporting. Check to see if the author’s institution is issuing a press release about the work; if this isn’t already posted on EurekAlert!, ask the author during the interview if they are preparing additional press materials and, if so, how you can get hold of those. This is also a good time to ask for any art, such as photos or videos to illustrate your story. You will of course have already looked at all their figures in detail, so you’ll be well placed to request the art that is most relevant to what you and your editor are looking for.

With these tools at your side, you should be well suited to tackle your next scientific paper.

Alexandra Witze  is a science journalist in Boulder, Colorado, and a member of  The Open Notebook ’s board of directors.  Her news story on the Martian subglacial lake  (marked up above) appeared in  Nature . Follow her on 

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How to Read a Research Paper – A Guide to Setting Research Goals, Finding Papers to Read, and More

If you work in a scientific field, you should try to build a deep and unbiased understanding of that field. This not only educates you in the best possible way but also helps you envision the opportunities in your space.

A research paper is often the culmination of a wide range of deep and authentic practices surrounding a topic. When writing a research paper, the author thinks critically about the problem, performs rigorous research, evaluates their processes and sources, organizes their thoughts, and then writes. These genuinely-executed practices make for a good research paper.

If you’re struggling to build a habit of reading papers (like I am) on a regular basis, I’ve tried to break down the whole process. I've talked to researchers in the field, read a bunch of papers and blogs from distinguished researchers, and jotted down some techniques that you can follow.

Let’s start off by understanding what a research paper is and what it is NOT!

What is a Research Paper?

A research paper is a dense and detailed manuscript that compiles a thorough understanding of a problem or topic. It offers a proposed solution and further research along with the conditions under which it was deduced and carried out, the efficacy of the solution and the research performed, and potential loopholes in the study.

A research paper is written not only to provide an exceptional learning opportunity but also to pave the way for further advancements in the field. These papers help other scholars germinate the thought seed that can either lead to a new world of ideas or an innovative method of solving a longstanding problem.

What Research Papers are NOT

There is a common notion that a research paper is a well-informed summary of a problem or topic written by means of other sources.

But you shouldn't mistake it for a book or an opinionated account of an individual’s interpretation of a particular topic.

Why Should You Read Research Papers?

What I find fascinating about reading a good research paper is that you can draw on a profound study of a topic and engage with the community on a new perspective to understand what can be achieved in and around that topic.

I work at the intersection of instructional design and data science. Learning is part of my day-to-day responsibilities. If the source of my education is flawed or inefficient, I’d fail at my job in the long term. This applies to many other jobs in Science with a special focus on research.

There are three important reasons to read a research paper:

• Knowledge —  Understanding the problem from the eyes of someone who has probably spent years solving it and has taken care of all the edge cases that you might not think of at the beginning.
• Exploration —  Whether you have a pinpointed agenda or not, there is a very high chance that you will stumble upon an edge case or a shortcoming that is worth following up. With persistent efforts over a considerable amount of time, you can learn to use that knowledge to make a living.
• Research and review —  One of the main reasons for writing a research paper is to further the development in the field. Researchers read papers to review them for conferences or to do a literature survey of a new field. For example, Yann LeCun’ s paper on integrating domain constraints into backpropagation set the foundation of modern computer vision back in 1989. After decades of research and development work, we have come so far that we're now perfecting problems like object detection and optimizing autonomous vehicles.

Not only that, with the help of the internet, you can extrapolate all of these reasons or benefits onto multiple business models. It can be an innovative state-of-the-art product, an efficient service model, a content creator, or a dream job where you are solving problems that matter to you.

Goals for Reading a Research Paper — What Should You Read About?

The first thing to do is to figure out your motivation for reading the paper. There are two main scenarios that might lead you to read a paper:

• Scenario 1 —  You have a well-defined agenda/goal and you are deeply invested in a particular field. For example, you’re an NLP practitioner and you want to learn how GPT-4 has given us a breakthrough in NLP. This is always a nice scenario to be in as it offers clarity.
• Scenario 2 —  You want to keep abreast of the developments in a host of areas, say how a new deep learning architecture has helped us solve a 50-year old biological problem of understanding protein structures. This is often the case for beginners or for people who consume their daily dose of news from research papers (yes, they exist!).

If you’re an inquisitive beginner with no starting point in mind, start with scenario 2. Shortlist a few topics you want to read about until you find an area that you find intriguing. This will eventually lead you to scenario 1.

ML Reproducibility Challenge

In addition to these generic goals, if you need an end goal for your habit-building exercise of reading research papers, you should check out the ML reproducibility challenge.

You’ll find top-class papers from world-class conferences that are worth diving deep into and reproducing the results.

They conduct this challenge twice a year and they have one coming up in Spring 2021. You should study the past three versions of the challenge, and I’ll write a detailed post on what to expect, how to prepare, and so on.

Now you must be wondering – how can you find the right paper to read?

How to Find the Right Paper to Read

In order to get some ideas around this, I reached out to my friend, Anurag Ghosh who is a researcher at Microsoft. Anurag has been working at the crossover of computer vision, machine learning, and systems engineering.

Here are a few of his tips for getting started:

• Always pick an area you're interested in.
• Read a few good books or detailed blog posts on that topic and start diving deep by reading the papers referenced in those resources.
• Look for seminal papers around that topic. These are papers that report a major breakthrough in the field and offer a new method perspective with a huge potential for subsequent research in that field. Check out papers from the morning paper or C VF - test of time award/Helmholtz prize (if you're interested in computer vision).
• Check out books like Computer Vision: Algorithms and Applications by Richard Szeliski and look for the papers referenced there.
• Have and build a sense of community. Find people who share similar interests, and join groups/subreddits/discord channels where such activities are promoted.

In addition to these invaluable tips, there are a number of web applications that I’ve shortlisted that help me narrow my search for the right papers to read:

• r/MachineLearning  — there are many researchers, practitioners, and engineers who share their work along with the papers they've found useful in achieving those results.

• Arxiv Sanity Preserver  — built by Andrej Karpathy to accelerate research. It is a repository of 142,846 papers from computer science, machine learning, systems, AI, Stats, CV, and so on. It also offers a bunch of filters, powerful search functionality, and a discussion forum to make for a super useful research platform.

• Google Research  — the research teams at Google are working on problems that have an impact on our everyday lives. They share their publications for individuals and teams to learn from, contribute to, and expedite research. They also have a Google AI blog that you can check out.

How to Read a Research Paper

After you have stocked your to-read list, then comes the process of reading these papers. Remember that NOT every paper is useful to read and we need a mechanism that can help us quickly screen papers that are worth reading.

To tackle this challenge, you can use this Three-Pass Approach by S. Keshav . This approach proposes that you read the paper in three passes instead of starting from the beginning and diving in deep until the end.

The three pass approach

• The first pass —  is a quick scan to capture a high-level view of the paper. Read the title, abstract, and introduction carefully followed by the headings of the sections and subsections and lastly the conclusion. It should take you no more than 5–10 mins to figure out if you want to move to the second pass.
• The second pass —  is a more focused read without checking for the technical proofs. You take down all the crucial notes, underline the key points in the margins. Carefully study the figures, diagrams, and illustrations. Review the graphs, mark relevant unread references for further reading. This helps you understand the background of the paper.
• The third pass —  reaching this pass denotes that you’ve found a paper that you want to deeply understand or review. The key to the third pass is to reproduce the results of the paper. Check it for all the assumptions and jot down all the variations in your re-implementation and the original results. Make a note of all the ideas for future analysis. It should take 5–6 hours for beginners and 1–2 hours for experienced readers.

Tools and Software to Keep Track of Your Pipeline of Papers

If you’re sincere about reading research papers, your list of papers will soon grow into an overwhelming stack that is hard to keep track of. Fortunately, we have software that can help us set up a mechanism to manage our research.

Here are a bunch of them that you can use:

• Mendeley [not free]  — you can add papers directly to your library from your browser, import documents, generate references and citations, collaborate with fellow researchers, and access your library from anywhere. This is mostly used by experienced researchers.

• Zotero [free & open source] —  Along the same lines as Mendeley but free of cost. You can make use of all the features but with limited storage space.

• Notion —  this is great if you are just starting out and want to use something lightweight with the option to organize your papers, jot down notes, and manage everything in one workspace. It might not stand anywhere in comparison with the above tools but I personally feel comfortable using Notion and I have created this board to keep track of my progress for now that you can duplicate:

⚠️ Symptoms of Reading a Research Paper

Reading a research paper can turn out to be frustrating, challenging, and time-consuming especially when you’re a beginner. You might face the following common symptoms:

• You might start feeling dumb for not understanding a thing a paper says.
• Finding yourself pushing too hard to understand the math behind those proofs.
• Beating your head against the wall to wrap it around the number of acronyms used in the paper. Just kidding, you’ll have to look up those acronyms every now and then.
• Being stuck on one paragraph for more than an hour.

Here’s a complete list of emotions that you might undergo as explained by Adam Ruben in this article .

Key Takeaways

We should be all set to dive right in. Here’s a quick summary of what we have covered here:

• A research paper is an in-depth study that offers an detailed explanation of a topic or problem along with the research process, proofs, explained results, and ideas for future work.
• Read research papers to develop a deep understanding of a topic/problem. Then you can either review papers as part of being a researcher, explore the domain and the kind of problems to build a solution or startup around it, or you can simply read them to keep abreast of the developments in your domain of interest.
• If you’re a beginner, start with exploration to soon find your path to goal-oriented research.
• In order to find good papers to read, you can use websites like arxiv-sanity, google research, and subreddits like r/MachineLearning.
• Reading approach — Use the 3-pass method to find a paper.
• Keep track of your research, notes, developments by using tools like Zotero/Notion.
• This can get overwhelming in no time. Make sure you start off easy and increment your load progressively.

Remember: Art is not a single method or step done over a weekend but a process of accomplishing remarkable results over time.

You can also watch the video on this topic on my YouTube channel :

Feel free to respond to this blog or comment on the video if you have some tips, questions, or thoughts!

If this tutorial was helpful, you should check out my data science and machine learning courses on Wiplane Academy . They are comprehensive yet compact and helps you build a solid foundation of work to showcase.

Web and Data Science Consultant | Instructional Design

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• Knowledge Base
• Starting the research process

A Beginner's Guide to Starting the Research Process

When you have to write a thesis or dissertation , it can be hard to know where to begin, but there are some clear steps you can follow.

The research process often begins with a very broad idea for a topic you’d like to know more about. You do some preliminary research to identify a  problem . After refining your research questions , you can lay out the foundations of your research design , leading to a proposal that outlines your ideas and plans.

This article takes you through the first steps of the research process, helping you narrow down your ideas and build up a strong foundation for your research project.

Table of contents

Step 1: choose your topic, step 2: identify a problem, step 3: formulate research questions, step 4: create a research design, step 5: write a research proposal, other interesting articles.

First you have to come up with some ideas. Your thesis or dissertation topic can start out very broad. Think about the general area or field you’re interested in—maybe you already have specific research interests based on classes you’ve taken, or maybe you had to consider your topic when applying to graduate school and writing a statement of purpose .

Even if you already have a good sense of your topic, you’ll need to read widely to build background knowledge and begin narrowing down your ideas. Conduct an initial literature review to begin gathering relevant sources. As you read, take notes and try to identify problems, questions, debates, contradictions and gaps. Your aim is to narrow down from a broad area of interest to a specific niche.

Make sure to consider the practicalities: the requirements of your programme, the amount of time you have to complete the research, and how difficult it will be to access sources and data on the topic. Before moving onto the next stage, it’s a good idea to discuss the topic with your thesis supervisor.

>>Read more about narrowing down a research topic

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So you’ve settled on a topic and found a niche—but what exactly will your research investigate, and why does it matter? To give your project focus and purpose, you have to define a research problem .

The problem might be a practical issue—for example, a process or practice that isn’t working well, an area of concern in an organization’s performance, or a difficulty faced by a specific group of people in society.

Alternatively, you might choose to investigate a theoretical problem—for example, an underexplored phenomenon or relationship, a contradiction between different models or theories, or an unresolved debate among scholars.

To put the problem in context and set your objectives, you can write a problem statement . This describes who the problem affects, why research is needed, and how your research project will contribute to solving it.

>>Read more about defining a research problem

Next, based on the problem statement, you need to write one or more research questions . These target exactly what you want to find out. They might focus on describing, comparing, evaluating, or explaining the research problem.

A strong research question should be specific enough that you can answer it thoroughly using appropriate qualitative or quantitative research methods. It should also be complex enough to require in-depth investigation, analysis, and argument. Questions that can be answered with “yes/no” or with easily available facts are not complex enough for a thesis or dissertation.

In some types of research, at this stage you might also have to develop a conceptual framework and testable hypotheses .

>>See research question examples

The research design is a practical framework for answering your research questions. It involves making decisions about the type of data you need, the methods you’ll use to collect and analyze it, and the location and timescale of your research.

There are often many possible paths you can take to answering your questions. The decisions you make will partly be based on your priorities. For example, do you want to determine causes and effects, draw generalizable conclusions, or understand the details of a specific context?

You need to decide whether you will use primary or secondary data and qualitative or quantitative methods . You also need to determine the specific tools, procedures, and materials you’ll use to collect and analyze your data, as well as your criteria for selecting participants or sources.

>>Read more about creating a research design

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Finally, after completing these steps, you are ready to complete a research proposal . The proposal outlines the context, relevance, purpose, and plan of your research.

As well as outlining the background, problem statement, and research questions, the proposal should also include a literature review that shows how your project will fit into existing work on the topic. The research design section describes your approach and explains exactly what you will do.

You might have to get the proposal approved by your supervisor before you get started, and it will guide the process of writing your thesis or dissertation.

>>Read more about writing a research proposal

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

Methodology

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

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Ten simple rules for reading a scientific paper

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Affiliation Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America

• Maureen A. Carey, 
• Kevin L. Steiner, 
• William A. Petri Jr

Published: July 30, 2020

• https://doi.org/10.1371/journal.pcbi.1008032
• Reader Comments

Citation: Carey MA, Steiner KL, Petri WA Jr (2020) Ten simple rules for reading a scientific paper. PLoS Comput Biol 16(7): e1008032. https://doi.org/10.1371/journal.pcbi.1008032

Editor: Scott Markel, Dassault Systemes BIOVIA, UNITED STATES

Copyright: © 2020 Carey et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: MAC was supported by the PhRMA Foundation's Postdoctoral Fellowship in Translational Medicine and Therapeutics and the University of Virginia's Engineering-in-Medicine seed grant, and KLS was supported by the NIH T32 Global Biothreats Training Program at the University of Virginia (AI055432). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

“There is no problem that a library card can't solve” according to author Eleanor Brown [ 1 ]. This advice is sound, probably for both life and science, but even the best tool (like the library) is most effective when accompanied by instructions and a basic understanding of how and when to use it.

For many budding scientists, the first day in a new lab setting often involves a stack of papers, an email full of links to pertinent articles, or some promise of a richer understanding so long as one reads enough of the scientific literature. However, the purpose and approach to reading a scientific article is unlike that of reading a news story, novel, or even a textbook and can initially seem unapproachable. Having good habits for reading scientific literature is key to setting oneself up for success, identifying new research questions, and filling in the gaps in one’s current understanding; developing these good habits is the first crucial step.

Advice typically centers around two main tips: read actively and read often. However, active reading, or reading with an intent to understand, is both a learned skill and a level of effort. Although there is no one best way to do this, we present 10 simple rules, relevant to novices and seasoned scientists alike, to teach our strategy for active reading based on our experience as readers and as mentors of undergraduate and graduate researchers, medical students, fellows, and early career faculty. Rules 1–5 are big picture recommendations. Rules 6–8 relate to philosophy of reading. Rules 9–10 guide the “now what?” questions one should ask after reading and how to integrate what was learned into one’s own science.

Rule 1: Pick your reading goal

What you want to get out of an article should influence your approach to reading it. Table 1 includes a handful of example intentions and how you might prioritize different parts of the same article differently based on your goals as a reader.

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https://doi.org/10.1371/journal.pcbi.1008032.t001

Rule 2: Understand the author’s goal

In written communication, the reader and the writer are equally important. Both influence the final outcome: in this case, your scientific understanding! After identifying your goal, think about the author’s goal for sharing this project. This will help you interpret the data and understand the author’s interpretation of the data. However, this requires some understanding of who the author(s) are (e.g., what are their scientific interests?), the scientific field in which they work (e.g., what techniques are available in this field?), and how this paper fits into the author’s research (e.g., is this work building on an author’s longstanding project or controversial idea?). This information may be hard to glean without experience and a history of reading. But don’t let this be a discouragement to starting the process; it is by the act of reading that this experience is gained!

A good step toward understanding the goal of the author(s) is to ask yourself: What kind of article is this? Journals publish different types of articles, including methods, review, commentary, resources, and research articles as well as other types that are specific to a particular journal or groups of journals. These article types have different formatting requirements and expectations for content. Knowing the article type will help guide your evaluation of the information presented. Is the article a methods paper, presenting a new technique? Is the article a review article, intended to summarize a field or problem? Is it a commentary, intended to take a stand on a controversy or give a big picture perspective on a problem? Is it a resource article, presenting a new tool or data set for others to use? Is it a research article, written to present new data and the authors’ interpretation of those data? The type of paper, and its intended purpose, will get you on your way to understanding the author’s goal.

Rule 3: Ask six questions

When reading, ask yourself: (1) What do the author(s) want to know (motivation)? (2) What did they do (approach/methods)? (3) Why was it done that way (context within the field)? (4) What do the results show (figures and data tables)? (5) How did the author(s) interpret the results (interpretation/discussion)? (6) What should be done next? (Regarding this last question, the author(s) may provide some suggestions in the discussion, but the key is to ask yourself what you think should come next.)

Each of these questions can and should be asked about the complete work as well as each table, figure, or experiment within the paper. Early on, it can take a long time to read one article front to back, and this can be intimidating. Break down your understanding of each section of the work with these questions to make the effort more manageable.

Rule 4: Unpack each figure and table

Scientists write original research papers primarily to present new data that may change or reinforce the collective knowledge of a field. Therefore, the most important parts of this type of scientific paper are the data. Some people like to scrutinize the figures and tables (including legends) before reading any of the “main text”: because all of the important information should be obtained through the data. Others prefer to read through the results section while sequentially examining the figures and tables as they are addressed in the text. There is no correct or incorrect approach: Try both to see what works best for you. The key is making sure that one understands the presented data and how it was obtained.

For each figure, work to understand each x- and y-axes, color scheme, statistical approach (if one was used), and why the particular plotting approach was used. For each table, identify what experimental groups and variables are presented. Identify what is shown and how the data were collected. This is typically summarized in the legend or caption but often requires digging deeper into the methods: Do not be afraid to refer back to the methods section frequently to ensure a full understanding of how the presented data were obtained. Again, ask the questions in Rule 3 for each figure or panel and conclude with articulating the “take home” message.

Rule 5: Understand the formatting intentions

Just like the overall intent of the article (discussed in Rule 2), the intent of each section within a research article can guide your interpretation. Some sections are intended to be written as objective descriptions of the data (i.e., the Results section), whereas other sections are intended to present the author’s interpretation of the data. Remember though that even “objective” sections are written by and, therefore, influenced by the authors interpretations. Check out Table 2 to understand the intent of each section of a research article. When reading a specific paper, you can also refer to the journal’s website to understand the formatting intentions. The “For Authors” section of a website will have some nitty gritty information that is less relevant for the reader (like word counts) but will also summarize what the journal editors expect in each section. This will help to familiarize you with the goal of each article section.

https://doi.org/10.1371/journal.pcbi.1008032.t002

Rule 6: Be critical

Published papers are not truths etched in stone. Published papers in high impact journals are not truths etched in stone. Published papers by bigwigs in the field are not truths etched in stone. Published papers that seem to agree with your own hypothesis or data are not etched in stone. Published papers that seem to refute your hypothesis or data are not etched in stone.

Science is a never-ending work in progress, and it is essential that the reader pushes back against the author’s interpretation to test the strength of their conclusions. Everyone has their own perspective and may interpret the same data in different ways. Mistakes are sometimes published, but more often these apparent errors are due to other factors such as limitations of a methodology and other limits to generalizability (selection bias, unaddressed, or unappreciated confounders). When reading a paper, it is important to consider if these factors are pertinent.

Critical thinking is a tough skill to learn but ultimately boils down to evaluating data while minimizing biases. Ask yourself: Are there other, equally likely, explanations for what is observed? In addition to paying close attention to potential biases of the study or author(s), a reader should also be alert to one’s own preceding perspective (and biases). Take time to ask oneself: Do I find this paper compelling because it affirms something I already think (or wish) is true? Or am I discounting their findings because it differs from what I expect or from my own work?

The phenomenon of a self-fulfilling prophecy, or expectancy, is well studied in the psychology literature [ 2 ] and is why many studies are conducted in a “blinded” manner [ 3 ]. It refers to the idea that a person may assume something to be true and their resultant behavior aligns to make it true. In other words, as humans and scientists, we often find exactly what we are looking for. A scientist may only test their hypotheses and fail to evaluate alternative hypotheses; perhaps, a scientist may not be aware of alternative, less biased ways to test her or his hypothesis that are typically used in different fields. Individuals with different life, academic, and work experiences may think of several alternative hypotheses, all equally supported by the data.

Rule 7: Be kind

The author(s) are human too. So, whenever possible, give them the benefit of the doubt. An author may write a phrase differently than you would, forcing you to reread the sentence to understand it. Someone in your field may neglect to cite your paper because of a reference count limit. A figure panel may be misreferenced as Supplemental Fig 3E when it is obviously Supplemental Fig 4E. While these things may be frustrating, none are an indication that the quality of work is poor. Try to avoid letting these minor things influence your evaluation and interpretation of the work.

Similarly, if you intend to share your critique with others, be extra kind. An author (especially the lead author) may invest years of their time into a single paper. Hearing a kindly phrased critique can be difficult but constructive. Hearing a rude, brusque, or mean-spirited critique can be heartbreaking, especially for young scientists or those seeking to establish their place within a field and who may worry that they do not belong.

Rule 8: Be ready to go the extra mile

To truly understand a scientific work, you often will need to look up a term, dig into the supplemental materials, or read one or more of the cited references. This process takes time. Some advisors recommend reading an article three times: The first time, simply read without the pressure of understanding or critiquing the work. For the second time, aim to understand the paper. For the third read through, take notes.

Some people engage with a paper by printing it out and writing all over it. The reader might write question marks in the margins to mark parts (s)he wants to return to, circle unfamiliar terms (and then actually look them up!), highlight or underline important statements, and draw arrows linking figures and the corresponding interpretation in the discussion. Not everyone needs a paper copy to engage in the reading process but, whatever your version of “printing it out” is, do it.

Rule 9: Talk about it

Talking about an article in a journal club or more informal environment forces active reading and participation with the material. Studies show that teaching is one of the best ways to learn and that teachers learn the material even better as the teaching task becomes more complex [ 4 – 5 ]; anecdotally, such observations inspired the phrase “to teach is to learn twice.”

Beyond formal settings such as journal clubs, lab meetings, and academic classes, discuss papers with your peers, mentors, and colleagues in person or electronically. Twitter and other social media platforms have become excellent resources for discussing papers with other scientists, the public or your nonscientist friends, or even the paper’s author(s). Describing a paper can be done at multiple levels and your description can contain all of the scientific details, only the big picture summary, or perhaps the implications for the average person in your community. All of these descriptions will solidify your understanding, while highlighting gaps in your knowledge and informing those around you.

Rule 10: Build on it

One approach we like to use for communicating how we build on the scientific literature is by starting research presentations with an image depicting a wall of Lego bricks. Each brick is labeled with the reference for a paper, and the wall highlights the body of literature on which the work is built. We describe the work and conclusions of each paper represented by a labeled brick and discuss each brick and the wall as a whole. The top brick on the wall is left blank: We aspire to build on this work and label this brick with our own work. We then delve into our own research, discoveries, and the conclusions it inspires. We finish our presentations with the image of the Legos and summarize our presentation on that empty brick.

Whether you are reading an article to understand a new topic area or to move a research project forward, effective learning requires that you integrate knowledge from multiple sources (“click” those Lego bricks together) and build upwards. Leveraging published work will enable you to build a stronger and taller structure. The first row of bricks is more stable once a second row is assembled on top of it and so on and so forth. Moreover, the Lego construction will become taller and larger if you build upon the work of others, rather than using only your own bricks.

Build on the article you read by thinking about how it connects to ideas described in other papers and within own work, implementing a technique in your own research, or attempting to challenge or support the hypothesis of the author(s) with a more extensive literature review. Integrate the techniques and scientific conclusions learned from an article into your own research or perspective in the classroom or research lab. You may find that this process strengthens your understanding, leads you toward new and unexpected interests or research questions, or returns you back to the original article with new questions and critiques of the work. All of these experiences are part of the “active reading”: process and are signs of a successful reading experience.

In summary, practice these rules to learn how to read a scientific article, keeping in mind that this process will get easier (and faster) with experience. We are firm believers that an hour in the library will save a week at the bench; this diligent practice will ultimately make you both a more knowledgeable and productive scientist. As you develop the skills to read an article, try to also foster good reading and learning habits for yourself (recommendations here: [ 6 ] and [ 7 ], respectively) and in others. Good luck and happy reading!

Acknowledgments

Thank you to the mentors, teachers, and students who have shaped our thoughts on reading, learning, and what science is all about.

• 1. Brown E. The Weird Sisters. G. P. Putnam’s Sons; 2011.
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Organizing Your Social Sciences Research Paper: Reading Research Effectively

• Purpose of Guide
• Writing a Research Proposal
• Design Flaws to Avoid
• Independent and Dependent Variables
• Narrowing a Topic Idea
• Broadening a Topic Idea
• The Research Problem/Question
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• The C.A.R.S. Model
• Background Information
• Theoretical Framework
• Citation Tracking
• Evaluating Sources
• Reading Research Effectively
• Primary Sources
• Secondary Sources
• What Is Scholarly vs. Popular?
• Is it Peer-Reviewed?
• Qualitative Methods
• Quantitative Methods
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism [linked guide]
• Annotated Bibliography
• Grading Someone Else's Paper

Reading a Scholarly Article or Research Paper

Reading Research Publications Effectively

It's easy to feel overwhelmed and frustrated when first reading a scholarly article or research paper. The text is dense and complex and often includes abstract or convoluted language . In addition, the terminology may be confusing or applied in a way that is unfamiliar. To help overcome these challenges w hen you first read an article or research paper, focus on asking specific questions about each section. This strategy can help with overall comprehension and understanding how the content relates [or does not relate] to the research problem you are investigating. This approach will also help identify key themes as you read additional studies on the same topic. As you review more and more studies about your topic, the process of understanding and critically evaluating the research will become easier because the content of what you review will begin to coalescence around common themes and patterns of analysis.

Think about the following in this general order:

1.  Read the Abstract

An abstract summarizes the basic content of a scholarly article or research paper. Questions to consider when reading the abstract are: What is this article about? What is the working hypothesis or thesis? Is this related to my question or area of research? The abstract can be used to help filter out sources that may have appeared useful when you began searching for information but, in reality, are not relevant.

2.  Identify the Research Problem and Underlying Questions? 

If, after reading the abstract, you believe the paper may be useful, focus on examining the research problem and identifying the questions the author is trying to address. Look for information that is relevant to your research problem and make note of how and in what way this information relates to what you are investigating.

3.  Read the Introduction and Discussion/Conclusion

The introduction provides the main argument and theoretical framework of the article. Questions to consider for the introduction include what do we already know about this topic and what is left to discover? What other research has been conducted about this topic? How is this research unique? Will this study tell me anything new related to the research problem I am investigating?

Questions to ask yourself while reading the discussion and conclusion sections include what does the study mean and why is it important? What are the weaknesses in their argument? Does the conclusion contain any recommendations for future research and do you believe conclusions about the significance of the study and its findings are valid?

4.  Read about the Methods/Methodology

If what you have read so far closely relates to your research problem, then move on to reading about how the author(s) gathered information for their research. Questions to consider include how did the author do the research? Was it a qualitative, quantitative, or mixed-methods project? What data is the study based on? Could I repeat their work and is all the information available to repeat the study?

5.  Read about the Results and Analysis

Next, read the outcome the research and how it was discussed and analyzed. If any non-textual elements [e.g., graphs, charts, tables, etc.] are confusing, focus on the explanations about them in the text. Questions to consider are what did the author find and how did they find it? Are the results presented in a factual and unbiased way? Does their analysis of results agree with the data presented? Is all the data present? What conclusions do you formulate from this data and does it match with the author's conclusions?

6.  Review the References

The list of references, or works cited, shows you the basis of prior research used by the author(s) to support their study. The references can be an effective way to identify additional sources of information on the topic. Questions to ask include what other research studies should I review? What other authors are respected in this field, i.e., who is cited most often by others? What other research should be explored to learn about issues I am unclear or need more information about?

Reading Tips

Preparing to Read a Scholarly Article or Research Paper for the First Time

Reading scholarly publications effectively is an acquired skill that involves attention to detail and the ability to comprehend complex ideas, data, and concepts in a way that applies logically to the research problem you are investigating. Here are some strategies to consider.

While You are Reading

• Focus on information in the publication that is most relevant to the research problem
• Think critically about what you read and seek to build your own arguments; not everything is 100% true or examined effectively
• Read out of order! This isn't a novel or movie; you want to start with the spoiler
• Look up the definitions of words you don't know as you read

There are any number of ways to take notes as you read, but use the method that you feel most comfortable with. Taking notes as you read will save time when you go back to examine your sources. Below are some suggestions:

• Print the article and highlight, circle, and/or underline text as you read [or, you can use the highlight text   feature in a PDF document]
• Take notes in the margins [Adobe Reader offers pop-up sticky notes]
• Focus on highlighting important quotes; consider using a different color to differentiate between quotes and other types of text you want to return to when writing
• Quickly summarize the main or key points at the end of the paper

As you read, write down questions that come to mind that relate to or may clarify your research problem. Here are a few questions that might be helpful:

• Have I taken time to understand all the terminology?
• Am I spending too much time on the less important parts of this article?
• Are there any issues that the authors did not consider?
• Do I have any reason to question the credibility of this research?
• What specific problem does the research address and why is it important?
• How do these results relate to my research interests or to other works which I have read?

Adapted from text originally created by Holly Burt, USC Libraries, April 2018. Thank you, Holly!

• << Previous: Evaluating Sources
• Next: Primary Sources >>
• Last Updated: Sep 8, 2023 12:19 PM
• URL: https://guides.library.txstate.edu/socialscienceresearch

Psychological Research

How to Read Research

Learning objectives.

• Describe the basic structure of a psychological research article

In this course and throughout your academic career, you’ll be reading journal articles (meaning they were published by experts in a peer-reviewed journal) and reports that explain psychological research. It’s important to understand the format of these articles so that you can read them strategically and understand the information presented. Scientific articles vary in content or structure, depending on the type of journal to which they will be submitted. Psychological articles and many papers in the social sciences follow the writing guidelines and format dictated by the American Psychological Association (APA). In general, the structure follows: abstract, introduction, methods, results, discussion, and references.

• Abstract : the abstract is the concise summary of the article. It summarizes the most important features of the manuscript, providing the reader with a global first impression on the article. It is generally just one paragraph that explains the experiment as well as a short synopsis of the results.
• Introduction : this section provides background information about the origin and purpose of performing the experiment or study. It reviews previous research and presents existing theories on the topic.
• Method : this section covers the methodologies used to investigate the research question, including the identification of participants , procedures , and  materials  as well as a description of the actual procedure . It should be sufficiently detailed to allow for replication.
• Results : the results section presents key findings of the research, including reference to indicators of statistical significance.
• Discussion : this section provides an interpretation of the findings, states their significance for current research, and derives implications for theory and practice. Alternative interpretations for findings are also provided, particularly when it is not possible to conclude for the directionality of the effects. In the discussion, authors also acknowledge the strengths and limitations/weaknesses of the study and offer concrete directions about for future research.

Watch this video for an explanation on how to read scholarly articles. Look closely at the example article shared just before the two minute mark.

https://player.vimeo.com/video/27119325

Practice identifying these key components in the following experiment:  Food-Induced Emotional Resonance Improves Emotion Recognition .

CC licensed content, Original

• Modification, adaptation, and original content. Provided by : Lumen Learning. License : CC BY: Attribution

CC licensed content, Shared previously

• Reading a Scientific Paper for Psychology and the Social Sciences: A Critical Guide. Authored by : Pedro Cordeiro, Victor E. C. Ortuu00f1o, Maria Paula Paixu00e3o, Jou00e3o Maru00f4co. Provided by : Faculty of Psychology and Educational Sciences, University of Coimbra. Located at : http://pch.psychopen.eu/article/view/136/html . License : CC BY: Attribution
• What is a Scholarly Article? video. Provided by : Coastal Carolina University. Located at : http://www.coastal.edu/intranet/library/videos/browse.html . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

General Psychology Copyright © by OpenStax and Lumen Learning is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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• Published: 10 May 2022

Understanding and shaping the future of work with self-determination theory

• Marylène Gagné   ORCID: orcid.org/0000-0003-3248-8947 1 ,
• Sharon K. Parker   ORCID: orcid.org/0000-0002-0978-1873 1 ,
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Nature Reviews Psychology volume  1 ,  pages 378–392 ( 2022 ) Cite this article

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Self-determination theory has shaped our understanding of what optimizes worker motivation by providing insights into how work context influences basic psychological needs for competence, autonomy and relatedness. As technological innovations change the nature of work, self-determination theory can provide insight into how the resulting uncertainty and interdependence might influence worker motivation, performance and well-being. In this Review, we summarize what self-determination theory has brought to the domain of work and how it is helping researchers and practitioners to shape the future of work. We consider how the experiences of job candidates are influenced by the new technologies used to assess and select them, and how self-determination theory can help to improve candidate attitudes and performance during selection assessments. We also discuss how technology transforms the design of work and its impact on worker motivation. We then describe three cases where technology is affecting work design and examine how this might influence needs satisfaction and motivation: remote work, virtual teamwork and algorithmic management. An understanding of how future work is likely to influence the satisfaction of the psychological needs of workers and how future work can be designed to satisfy such needs is of the utmost importance to worker performance and well-being.

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Introduction

The nature of work is changing as technology enables new forms of automation and communication across many industries. Although the image of human-like robots replacing human jobs is vivid, it does not reflect the typical ways people will engage with automation and how technology will change job requirements in the future. A more relevant picture is one in which people interact over dispersed networks using continuously improving communication platforms mediated by artificial intelligence (AI). Examples include the acceleration of remote working arrangements caused by the COVID-19 pandemic and the increased use of remote control operations across many industries including mining, manufacturing, transport, education and health.

Historically, automation has replaced more routine physically demanding, dangerous or repetitive work in industries such as manufacturing, with little impact on professional and managerial occupations 1 . However, since the mid-2010s, automation has replaced many repetitive error-prone administrative tasks such as processing legal documents, directing service queries and employee selection screening 2 , 3 . Thus, work requirements for employees are increasingly encompassing tasks that cannot be readily automated, such as interpersonal negotiations and service innovations 4 : in other words, work that cannot be easily achieved through algorithms.

The role of motivation is often overlooked when designing and implementing technology in the workplace, even though technological changes can have a major impact on people’s motivation. Self-determination theory offers a useful multidimensional conceptualization of motivation that can help predict these impacts. According to self-determination theory 5 , 6 , three psychological needs must be fulfilled to adequately motivate workers and ensure that they perform optimally and experience well-being. Specifically, people need to feel that they are effective and masters of their environment (need for competence), that they are agents of their own behaviour as opposed to a ‘pawn’ of external pressures (need for autonomy), and that they experience meaningful connections with other people (need for relatedness) 5 , 7 . Meta-analytic evidence shows that satisfying these three needs is associated with better performance, reduced burnout, more organizational commitment and reduced turnover intentions 8 .

Self-determination theory also distinguishes between different types of motivation that workers might experience: intrinsic motivation (doing something for its own sake, out of interest and enjoyment), extrinsic motivation (doing something for an instrumental reason) and amotivation (lacking any reason to engage in an activity). Extrinsic motivation is subdivided according to the degree to which external influences are internalized (absorbed and transformed into internal tools to regulate activity engagement) 5 , 9 . According to meta-analytic evidence, more self-determined (that is, intrinsic or more internalized) motivation is more positively associated with key attitudinal and performance outcomes, such as job satisfaction, organizational commitment, job performance and proactivity than more controlled motivation (that is, extrinsic or less internalized) 10 . Consequently, researchers advocate the development and promotion of self-determined motivation across various life domains, including work 11 . Satisfaction of the three psychological needs described above is significantly related to more self-determined motivation 8 .

Given the impact of the needs proposed in self-determination theory on work motivation and consequently work outcomes (Fig.  1 ), it is important to find ways to satisfy these needs and avoid undermining them in the workplace. Organizational research has consequently focused on managerial and leadership behaviours that support or thwart these needs and promote different types of work motivation 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 (Fig.  2 ). There is also substantial research on the effects of work design (the nature and organization of people’s work tasks within a job or role, such as who makes what decisions, the extent to which people’s tasks are varied, or whether people work alone or in a team structure) and compensation systems on need satisfaction and work motivation 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , and how individuals can seek to meet their needs and enhance their motivation through proactive efforts to craft their jobs 38 , 39 , 40 .

According to self-determination theory, satisfaction of three psychological needs (competence, autonomy and relatedness) influences work motivation, which influences outcomes. More intrinsic and internalized motivations are associated with more positive outcomes than extrinsic and less internalized motivations. These needs and motivations might be influenced by the increased uncertainty and interdependence that characterize the future of work.

Summary of research findings 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 and available meta-analyses 8 , 10 . In cases where the evidence is mixed, a negative sign indicates a negative correlation, a positive sign indicates a positive correlation, and a zero indicates no statistically significant correlation.

Importantly, the work tasks that people are more likely to do in future work will require high-level cognitive and emotional skills that are more likely to be developed, used, and sustained when underpinned by self-determined motivation 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 . Therefore, if individuals are to be effective in future work, it is important to understand how future work might meet — or fail to meet — the psychological needs proposed by self-determination theory.

In this Review, we outline how work is changing and explain the consequences of these changes for satisfying workers’ psychological needs. We then focus on two areas where technology is already changing the worker experience: when workers apply for jobs and go through selection processes; and when the design of their work — what work they do, as well as how, when and where they do it — is transformed by technology. In particular, we focus on three domains where technology is already changing work design: remote work, virtual teams and algorithmic management. We conclude by discussing the importance of satisfying the psychological needs of workers when designing and implementing technologies in the workplace.

Future work requirements

The future workplace might evolve into one where psychological needs are better fulfilled, or one where they are neglected. In addition, there is growing concern that future work will meet the needs of people with adequate access to technology and the skills to use it, but will further diminish fulfillment for neglected and disadvantaged groups 51 (Box  1 ). To understand how future work might align with human needs, it is necessary to map key work features to core constructs of self-determination theory. Future work might be characterized by environmental uncertainty interdependence, complexity, volatility and ambiguity 52 . Here we focus on uncertainty and interdependence because these features capture core concerns about the future and its implication for connections among people in the changing context of work 53 . Higher levels of uncertainty require more adaptive behaviours, whereas higher levels of interdependence require more social, team-oriented and network-oriented behaviours 54 .

We first consider the increasing role of uncertainty in the workplace. Rapid changes in technology and global supply chains mean that the environment is more unpredictable and that there is increasing uncertainty about what activities are needed to be successful. Reducing uncertainty is central to most theories of human adaptation 55 and is a strong motivational basis for goals and behaviour 56 . If uncertainty becomes a defining and pervasive feature of organizational life, organizational leaders should think beyond reducing uncertainty and instead leverage and even create it 55 . In other words, in a highly dynamic context, it might be more functional and adaptive for employees and organizational leaders to consider more explorative approaches to coping with uncertainty, such as experimentation and improvization. All of these considerations imply that future effective work will require adaptive behaviours such as modifying the way work is done, and proactive behaviours such as innovating and creating new ways of working 54 .

Under higher levels of uncertainty, specific actions are difficult to define in advance. In contrast to action sequences that can be codified (for example, with algorithms) and repeated in predictable environments, the best action sequence is likely to involve flexibility and experimentation when the workplace is more uncertain. In this context, individuals must be motivated to explore new ideas, adjust their behaviour and engage with ongoing change. In stable and predictable environments, less self-determined forms of motivation might be sufficient to maintain the enactment of repetitive tasks and automation is more feasible as a replacement or support. However, under conditions of uncertainty, individuals will benefit from showing cognitive flexibility, creativity and proactivity, all behaviours that are more likely to emerge when people have self-determined motivation 40 , 41 , 44 , 46 , 47 , 48 , 49 , 57 .

Adaptive (coping with and responding to change) and proactive (initiating change) performance can be promoted by satisfying the needs for competence, autonomy and relatedness, and self-determined motivation 4 , 58 . For example, when individuals experience internalized motivation, they have a ‘reason to’ engage in the sometimes psychologically risky behaviour of proactivity 40 . Both adaptivity and proactivity depend on individuals having sufficient autonomy to work differently, try new ideas and negotiate multiple pathways to success. Hence, successful organizational functioning depends on people who can act autonomously to regulate their behaviour in response to a more unpredictable and changing environment 31 , 54 , 59 .

The second feature of the evolving workplace is an increasing level of interdependence among people, systems and technology. People will connect with each other in more numerous and complex ways as communication technologies become more reliable, deeply networked and faster. For example, medical teams from disparate locations might collaborate more easily in real time to support remote surgical procedures. They will also connect with automated entities such as cobots (robots that interact with humans) and decision-making aids supported by constantly updating algorithms. For example, algorithms might provide medical teams with predictive information about patient progress based on streaming data such as heart rate. As algorithms evolve in complexity and predictive accuracy, they will modify the work context and humans will need to adapt to work with the new information created 60 .

This interconnected and evolving future workplace requires individuals who can interact effectively across complex networks. The nature of different communication technologies can both increase and decrease feelings of relatedness depending on the extent to which they promote meaningful interactions. Typically, work technologies are developed to facilitate productivity and efficiency. However, given that human performance is also influenced by feelings of relatedness 8 , it is important to ensure that communication technologies and the way networks of people are managed by these technologies can fulfill this need.

The rapid growth of networks enabled by communication technologies (for example, Microsoft Teams, Slack and Webex) has produced positive and negative effects on performance and well-being. For example, these technologies can be a buffer against loneliness for remote workers or homeworkers 61 and enable stronger connections among distributed workers 62 . However, networking platforms lead some individuals to experience more isolation rather than more connectedness 63 . Workplace networks might also engender these contrasting effects by, for example, building a stronger understanding between individuals in a work group who do not usually get to interact or by limiting contact to more superficial communication that prevents individuals from building stronger relationships.

Both uncertainty and interdependence will challenge people’s feelings of competence. Uncertainty can lead to reduced access to predictable resources and less certainty about the success of work effort; the proliferation of networks and media can lead to feeling overwhelmed and to difficulties in managing communication and relationships. Moreover, technologies and automation can lead to the loss of human competencies as people stop using these skills 64 , 65 , 66 , 67 . For example, automating tasks that require humans to have basic financial skills diminishes opportunities for humans to develop expertise in financial skills.

Uncertainty and interdependence are likely to persist and increase in the future. This has implications for whether and how psychological needs will be satisfied or frustrated. In addition, because uncertainty and interdependence require people to behave in more adaptive and proactive ways, it is important to create future work that satisfies psychological needs.

Box 1 Inequalities caused by future work

Future work is likely to exacerbate inequalities. First, the digital divide (unequal access to, and ability to use, information communication technologies) 51 is likely to be exacerbated by technological advances that might become more costly and require more specialized skills. Moreover, the COVID-19 pandemic exacerbated work inequalities by providing better opportunities to those with digital access and skills 210 , 211 . The digital divide now also includes ‘algorithm awareness’ (knowing what algorithms do) which influences whether and how people are influenced by technology. Indeed, the degree to which algorithms influence attitudes and behaviours is negatively associated with the degree to which people are aware of algorithms and understand how they work 212 .

Second, future work is likely to require new technical and communication skills, as well as adaptive and proactive skills. Thus, people with such skills are more likely to find work than those who do not or who have fewer opportunities (for example, education access) to develop them. Even gig work requires that workers have access to relevant platforms and adequate skills for using them. These future work issues are therefore likely to increase gaps between skilled and non-skilled segments of the population, and consequently to increase societal pay disparities and poverty.

For example, workforce inequalities between mature and younger workers are likely to increase owing to real or perceived differences in technology-related skills, with increased disparities in the type of jobs these workers engage in 210 , 213 . Older workers might miss out on opportunities to upskill or might choose to leave the workforce early rather than face reskilling. This could decrease workforce diversity and strengthen negative stereotypes about mature workers (such as that they are not flexible, adaptable or motivated to keep up with changing times) 214 . Furthermore, inequalities in terms of pay have already been observed between men and women 215 . Increased robotization increases the gender pay gap 216 , and this gap is likely to be exacerbated as remote working becomes more common (as was shown during the pandemic) 217 . For example, one study found that salaries did not increase as much for women working flexibly compared to men 218 ; another study found that home workers tended to be employees with young children and these workers were 50% less likely to be promoted than those based in the office 140 .

To promote equality in future work and ensure that psychological needs are met, managers will need to adopt ‘meta-strategies’ to promote inclusivity (ensuring that all employees feel included in the workplace and are treated fairly, regardless of whether they are working remotely or not), individualization of work (ensuring that work is tailored to individual needs and desires) and employee integration (promoting interaction between employees of all ages, nationalities and backgrounds) 213 .

The future of employee selection

Changing economies are increasing demand for highly skilled labour, meaning that employers are forced to compete heavily for talent 68 . Meanwhile, technological developments, largely delivered online, have radically increased the reach, scalability and variety of selection methods available to employers 69 . Technology-based assessments also afford candidates the autonomy to interact with prospective employers at times and locations of their choosing 70 , 71 . Furthermore, video-based, virtual, gamified and AI-based assessment technologies 3 , 72 , 73 , 74 have improved the fidelity and immersion of the selection process. The fidelity of a selection assessment represents the extent to which it can reproduce the physical and psychological aspects of the work situation that the assessment is intended to simulate 75 . Virtual environments and video-based assessments can better reproduce working environments than traditional ‘paper and pencil’ assessments, and AI is being used to simulate social interactions in work or similar contexts 74 . Immersion represents how engrossing or absorbing an assessment experience is. Immersion is enhanced by richer media and gamified assessment elements 75 , 76 . These benefits have driven the widespread adoption of technology in recruitment practices 77 , but they have also attracted criticism. For example, the use of AI to analyse candidate data (such as CVs, social media profiles, text-based responses to interview questions, and videos) 78 raises concerns about the relevance of data being collected for selecting employees, transparency in how the data are used, and biases in selection based on these data 79 .

Candidates with a poor understanding of what data are being collected and how they are being used might experience a technology-based selection process as autonomy-thwarting. For example, the perceived job-relatedness of an assessment is associated with whether or not candidates view the assessment positively 69 , 80 . However, with today’s technology, assessments that appear typical or basic (such as a test or short recorded interview response) might also involve the collection of additional ‘trace’ data such as mouse movements and clicks (in the case of tests), or ancillary information such as ‘micro-expressions’ or candidates’ video backdrops 81 . We expect that it would be difficult for candidates to evaluate the job-relatedness of this information, unless provided with a rationale. Candidates may also feel increasing pressure to submit to employers’ requests to share personal information, such as social media profiles, which may further frustrate autonomy to the extent that candidates are reluctant to share this information 82 .

Furthermore, if candidates do not understand how technology-driven assessments work and are not able to receive feedback from assessment systems, their need for competence may be thwarted 83 . For example, initial research shows that people perceive fewer opportunities to demonstrate their strengths and capabilities in interviews they know will be evaluated by AI, compared to those evaluated by humans 83 .

Finally, because candidates are increasingly interacting with systems, rather than people, their opportunities to build relatedness with employers might be stifled. A notable exemplar is the use of asynchronous video interviews 70 , 71 , a type of video-based assessment where candidates log into an online system, are presented with a series of questions, and are asked to video-record their responses. Unlike a traditional or videoconference interview, candidates completing an asynchronous video interview do not interact directly with anyone from the employer organization, and they consequently often describe the experience as impersonal 84 . Absent any interventions, the use of asynchronous video interviews removes the opportunity for candidates to meet the employer and get a feel for what it might be like to work for the employer, or to ask questions of their own 84 .

Because technologies have changed rapidly, research on candidates’ reactions to these new selection methods has not kept up 69 . Nonetheless, to the extent that test-related and technology-related anxiety influences motivation and performance when completing an online assessment or a video interview, the performance of applicants might be adversely affected 85 . Furthermore, candidate experience can influence decisions to accept a job offer and how positively the candidate will talk about the organization to other potential candidates and even clients, thereby influencing brand reputation 86 . Thus, technology developments offer clear opportunities to improve the satisfaction of candidates’ needs and to assess them in richer environments that more closely resemble work settings. However, there are risks that technology that is needs-thwarting or is implemented in a needs-thwarting manner, will add to the uncertainty already inherent in competitive job applications. In the context of a globally competitive skills market, employers risk losing high-quality candidates.

The future of work design

Discussion in the popular press about the impact of AI and other forms of digitalization focuses on eradicating large numbers of jobs and mass unemployment. However, the reality is that tasks within jobs are being influenced by digitalization rather than whole jobs being replaced 87 . Most occupations in most industries have at least some tasks that could be replaced by AI, yet currently there is no occupation in which all tasks could be replaced 88 . The consequence of this observation is that people will need to increasingly interact with machines as part of their jobs. This raises work design questions, such as how people and machines should share tasks, and the consequences of different choices in this respect.

Work design theory is intimately connected to self-determination theory, with early scholars arguing that work arrangements should create jobs in which employees can satisfy their core psychological needs 89 . Core aspects of work design, including decision-making power, the opportunity to use skills and do a variety of tasks, the ability to ascertain the impact of one’s work, performance feedback 90 , social contact, time pressure, emotional demands and role conflict 91 are important predictors of job satisfaction, job performance 92 and work motivation 93 . Some evidence suggests that these motivating characteristics (considered ‘job resources’ according to the jobs demands–resources model) 94 are especially important for fostering motivation or reducing strain when job demands (aspects of a job that require sustained physical, emotional or mental effort) are high 93 , 95 . For example, autonomy and social support can reduce the effect of workload on negative outcomes such as exhaustion 96 .

Technology can potentially influence work design and therefore employee motivation in positive ways 1 . Increasing workers’ task variety and opportunities for more complex problem-solving should occur whenever technology takes over tasks (such as assembly line or mining work). Leaving the less routine and more interesting tasks for people to do 97 increases the opportunity for workers to fulfill their need for competence. For example, within manufacturing, complex production systems in which cyber-machines are connected in a factory-wide information network require strategic human decision-makers operating in complex, varied and high-level autonomy jobs 98 . Technology (such as social media) can also enhance social contact and support in some jobs and under some circumstances 86 , 87 (but see ref. 63 ), increasing opportunities for meeting relatedness needs.

However, new technologies can also undermine the design of motivating work, and thus reduce workers’ need satisfaction 1 . For example, in the aviation industry, manual flying skills can become degraded due to a lack of opportunity to practice when aircraft are highly automated 99 , decreasing the opportunity for pilots to meet their need for competence. As another example, technology has enabled the introduction of ‘microwork’ in which jobs are broken down into small tasks that are then carried out via information communication technologies 100 . Such jobs often lack variety, skill use and meaning 101 , again reducing the opportunity for the work to meet competence needs. In an analysis of robots in surgery, technology designed purely for ‘efficiency’ reduced the opportunities for trainee surgeons to engage in challenging tasks and resulted in impaired skill development 102 , and therefore probably reduced competence need satisfaction. Thus, poor work design might negatively influence work motivation through poor need satisfaction, especially the need for competence, owing to the lack of opportunity to maintain one’s skills or gain new ones 2 .

As the above examples show, the impact of new technologies on work design, and hence on need satisfaction, is powerful — but also mixed. That is, digital technologies can increase or decrease motivational work characteristics and can thereby influence need satisfaction (Fig.  3 ). The research shows that there is no deterministic relationship between technology and work design; instead, the effect of new technology on work design, and hence on motivation, depends on various moderating factors 1 . These moderating factors include individual aspects, such as the level of skill an individual has or the individual’s personality. Highly skilled individuals or those with proactive personalities might actively shape the technology and/or craft their work design to better meet their needs and increase their motivation 1 . For example, tech-savvy Uber drivers subject to algorithmic management sometimes resist or game the system, such as by cancelling rides to avoid negative ratings from passengers 103 .

The causal relationships among the possible (but not exhaustive) variables implicated in the influence of technology on work design and work motivation discussed in this Review.

More generally, individuals proactively seek a better fit with their job through behaviours such as idiosyncratic deals (non-standard work arrangements negotiated between an employee and an employer) and job crafting (changing one’s work design to align one’s job with personal needs, goals and skills) 39 , 40 (Box  2 ). Consequently, although there is relatively little research on proactivity in work redesign through technology, it is important to recognize that individuals will not necessarily be passive in the face of negative technologies. Just as time pressure can stimulate proactivity 104 , we should expect that technology that creates poor work design will motivate job crafting and other proactive behaviours from workers seeking to meet their psychological needs better 105 . This perspective fits with a broader approach to technology that emphasizes human agency 106 .

Importantly, mitigating and managing the impact of technology on work is not the sole responsibility of individuals. Organizational implementation factors (for example, whether technology is selected, designed and implemented in a participatory way or how much training is given to support the introduction of technology) and technological design factors (for example, how much worker control is built into automated systems) are also fundamental in shaping the effect of technology on work design. Understanding these moderating factors is important because they provide potential ‘levers’ for creating more motivating work while still capitalizing on the advantages of technologies. For example, in one case study 107 , several new digital technologies such as cobots and digital paper flow (systems that integrate and automate different organizational functions, such as sales and purchasing with accounting, inventory control and dispatch) were implemented following a strong technocentric approach (that is, highly focused on engineering solutions) with little worker participation, and with limited attention to creating motivating work design. A more human-centred approach could have prevented the considerable negative outcomes that followed (including friction, reduced morale, loss of motivation, errors and impaired performance) 107 . Ultimately, how technology is designed and implemented should be proactively adapted to better meet human competencies, needs and values.

Box 2 The future of careers

Employment stability started to decline during the 1980s with the rise of public ownership and international trade, the increased use of performance-based incentives and contracts, and the introduction of new technologies. Employment stability is expected to continue to decline with the growth of gig work and continued technological developments 219 , 220 . Indeed, people will more frequently be asked to change career paths as work is transformed by technology, to use and ‘sell’ their transferrable skills in creative ways, and to reskill. The rise of more precarious work and new employment relationships (for example, in gig work) adds to these career challenges 221 . The current generation of workers is likely to experience career shocks (disruptive events that trigger a sensemaking process regarding one’s career) caused by rapid technological changes, and indeed many workers have already experienced career shocks from the pandemic 222 . Moreover, rapid technological change and increasing uncertainty pushes organizations to hire for skill sets rather than fitting people into set jobs, requiring people to be aware of their skills and to know how to market them.

In short, the careers of the current and future workforce will be non-linear and will require people to be more adaptive and proactive in crafting their career. For this reason, the concept of a protean career, whereby people have an adaptive and self-directed career, is likely to be increasingly important 223 . A protean career is a career that is guided by a search for self-fulfillment and is characterized by frequent learning cycles that push an individual into constant transformation; a successful protean career therefore requires a combination of adaptivity skills and identity awareness 224 , 225 . Adaptivity allows people to forge their career by using, or even creating, emerging opportunities. Having a solid sense of self helps individuals to make choices according to personal strengths and values. However, a protean career orientation might fit only a small segment of the labour market. Change-averse individuals might regard protean careers as career-destructive and the identity changes associated with a protean career might be regarded as stressful. In addition, overly frequent transitions might limit deep learning opportunities and achievements, and disrupt important support networks 221 .

Nonetheless, career-related adaptive and proactive behaviours can be encouraged by satisfying psychological needs. In fact, protean careers tend to flourish in environments that provide autonomy and allow for proactivity, with support for competence and learning 223 , 226 . Moreover, people have greater self-awareness when they feel autonomous. Indeed, self-awareness is a component of authenticity and mindfulness, both of which are linked to the satisfaction of the need for autonomy 227 , 228 . Thus, supporting psychological needs during training, development and career transitions is likely to assist people in crafting successful careers.

Applications

In what follows, we describe three specific cases where technology is already influencing work design (virtual and remote work, virtual teamwork, and algorithmic management), and consider the potential consequences for worker need satisfaction and motivation.

Virtual and remote work

Technologies have significantly altered when and where people can work, with the Covid-19 pandemic vastly accelerating the extent of working from home (Box  3 ). Remote work has persisted beyond the early stages of the Covid-19 pandemic with hybrid working — where people work from home some days a week and at the workplace on other days — becoming commonplace 108 . The development of information communication technologies (such as Microsoft Teams) has enabled workers to easily connect with colleagues, clients and patients remotely 105 , for example, via online patient ‘telehealth’ consultations, webinars and discussion forums. Technology has even enabled the remote control of other technologies, such as manufacturing machinery, vehicles and remote systems that monitor hospital ward patient vital signs through AI 1 . However, even when people are working on work premises (that is, not working remotely), an increasing amount of work in many jobs is done virtually (for example, online training or communicating with a colleague next door via email).

Working virtually is inherently tied to changes in uncertainty and interdependence. Virtual work engenders uncertainty because workplace and interpersonal cues are less available or reliable in providing virtual employees with role clarity and ensuring smooth interactions. Indeed, ‘screen’ interactions are more stressful and effortful than face-to-face interactions. It is more difficult to decipher and synchronize non-verbal behaviour on a screen than face-to-face, particularly given the lack of body language cues due to camera frame limitations, increasing the cognitive load for meeting attendees 109 , 110 , 111 , 112 . Non-verbal synchrony can be affected by the video streaming speed, which also increases cognitive load 109 , 110 , 111 , 112 . Virtual interactions involve ‘hyper gaze’ from seeing grids of staring faces, which the brain interprets as a threat 109 , 110 , 111 , 112 . Seeing oneself on screen increases self-consciousness during social interactions, which can cause anxiety, especially in women and those from minoritized groups 109 , 110 , 111 , 112 . Finally, reduced mobility from having to stay in the camera frame has been shown to reduce individual performance relative to face-to-face meetings 109 , 110 , 111 , 112 . Research on virtual interactions is still in its infancy. In one study, workers were randomly assigned to have their camera either on or off during their daily virtual meetings for a week. Those with the camera on during meetings experienced more daily fatigue and less daily work engagement than those with the camera off 113 .

Lower-quality virtual communication between managers and colleagues can leave individuals unclear about their goals and priorities, and how they should achieve them 114 . This calls for more self-regulation 115 because employees must structure their daily work activities and remind themselves of their work priorities and goals, without relying on the physical presence of colleagues or managers. If virtual workers must coordinate some of their work tasks with colleagues, it can be difficult to synchronize and coordinate actions, working schedules and breaks, motivate each other, and assist each other with timely information exchange 115 . This can make it harder for employees to acquire and share information 53 .

Virtual work also affects work design and changes how psychological needs can be satisfied and frustrated (Table  1 ), which has implications for both managers and employees. Physical workplace cues that usually guide work behaviours and routines in the office do not exist in virtual work, consequently demanding more autonomous regulation of work behaviours 116 , 117 . Some remote workers experience an increased sense of control and autonomy over their work environment 118 , 119 , 120 under these circumstances, resulting in lower family–work conflict, depression and turnover 121 , 122 . However, managers and organizations might rob workers of this autonomy by closely monitoring them, for example by checking their computer or phone usage 123 . This type of close monitoring reflects a lack of manager trust in individuals’ abilities or intentions to work effectively remotely. This lack of trust leads to decreased feelings of autonomy 124 , increased employee home–work conflict 105 and distress 125 , 126 . Surveillance has been shown to decrease self-determined motivation 127 . It is therefore important to train managers in managing remote workers in an autonomy-supportive way to avoid these negative consequences 128 . The negative effects of monitoring can also be reduced if monitoring is used constructively to help employees develop through feedback 129 , 130 , 131 , 132 , 133 , and when employees participate in the design and control of the monitoring systems 134 , 135 .

Information communication technology might satisfy competence needs by increasing access to global information and communication and the ability to analyse data 136 . For example, online courses, training and webinars can improve workers’ knowledge, skills and abilities, and can therefore help workers to carry out their work tasks more proficiently, which increases self-efficacy and a sense of competence. Furthermore, the internet allows people to connect rapidly and asynchronously with experts around the world, who may be able to provide information needed to solve a work problem that local colleagues cannot help with 136 . This type of remote work is increasingly occurring whether or not individuals themselves are based remotely, and can potentially enhance performance.

At the same time, technology might thwart competence needs, and increase fatigue and stress. For example, constant electronic messages (such as email or keeping track of online messaging platforms such as Slack or Microsoft Teams) are likely to increase in volume when working remotely, but can be distracting and prevent individuals from completing core tasks while they respond to incoming messages 136 . The frustration of the need for competence can increase if individuals are constantly switching tasks to deal with overwhelming correspondence and failing to finish tasks in a timely manner. In addition, information communication technology enables access to what some individuals might perceive as an overwhelming amount of information (for example, through the internet, email and messages) which can lead to a lot of time spent sifting and processing information. This can be interpreted as a job demand that might make individuals feel incompetent if it is not clear what information is most important. Individuals might also require training in the use of information communication technology, and even then, technology can malfunction, preventing workers from completing tasks, and causing frustration and distress 136 , 137 .

Finally, remote workers can suffer from professional isolation because there are fewer opportunities to meet or be introduced to connections that enable career development and progression 138 , which could influence their feelings of competence in the long run. Although some research suggests that those who work flexibly are viewed as less committed to their career 139 and might be overlooked for career progression 140 , other research has found no relationship between remote working and career prospects 119 .

Virtual work can also present challenges for meeting workers’ need for relatedness 141 . Remote workers can feel isolated from, and excluded by, colleagues and fail to gain the social support they might receive if co-located 142 , 143 , weakening their sense of belonging to a team or organization 144 and their job performance 145 . This effect will probably be accentuated in the future: if the current trend for working from home continues, more people will be dissociated from office social environments more often and indefinitely. Office social environments could be degraded permanently if fewer people frequent the office on a daily basis, such that workers may not be in the office at the same time as collaborators, and there might be fewer people to ask for help or talk with informally. We do not yet know the long-term implications of a degraded social environment, but some suggest that extended virtual working could create a society where people have poor communication skills and in which social isolation and anxiety are exacerbated 146 . Self-determination theory suggests that it will be critical to actively design hybrid and remote work that meets relatedness needs to prevent these long-term issues. When working remotely, simple actions could be effective, such as actively providing opportunities for connecting with others, for example, through ‘virtual coffee breaks’ 147 . Individuals could also be ‘buddied’ up into pairs who regularly check in with each other via virtual platforms.

Hybrid work seems to offer the best of both worlds, providing opportunities for connection and collaboration while in the workplace, and affording autonomy in terms of flexible working. Some research suggests that two remote workdays a week provides the optimum balance 148 . However, it is likely that this balance will be affected by individual characteristics and desires, as well as by differences in work roles and goals. For example, Israeli employees with autism who had to work from home during the COVID-19 pandemic experienced significantly lower competence and autonomy satisfaction than before the pandemic 149 . Yet remote workers high in emotional stability and job autonomy reported higher autonomy and relatedness satisfaction compared to those with low emotional stability 120 . These findings suggest that managers and individuals should consider the interplay between individual characteristics, work design and psychological need satisfaction when considering virtual and remote work.

Box 3 The ‘great resignation’

‘The great resignation’ refers to the massive wave of employee departures during the COVID-19 pandemic in several parts of the world, including North America, Europe and China 229 , 230 , that can be attributed in part to career shocks caused by the pandemic 222 . In the healthcare profession, the shock consisted of an exponential increase in workload and the resulting exhaustion, coupled with the disorganization caused by lack of resources and compounded by health fears 231 . In other industries, the pandemic caused work disruptions by forcing or allowing people to work from home, furloughing employees for varying periods of time, or lay-offs caused by an abrupt loss of business (such as in the tourism and hospitality industries).

Scholars have speculated that these shocks have resulted in a staggering number of people not wanting to go back to work or quitting their current jobs 232 . For example, the hospitality and tourism industries failed to attract employees back following lay-offs 233 . Career shocks can trigger a sensemaking process that can lead one to question how time is spent at work and the benefits one draws from it. For example, the transition to working from home made employees question how and why they work 234 . Frequent health and financial concerns, juggling school closures and complications in caring for dependents have compounded exhaustion and disorganization issues. Some have even renamed ‘the great resignation’ as ‘the great discontent’ to highlight that many people reported wanting to quit because of dissatisfaction with their work conditions 235 .

It might be helpful to understand ‘the great resignation’ through the lens of basic psychological need satisfaction. Being stretched to the limit might influence the need for competence and relatedness when workers feel they have suboptimal ways to connect with colleagues and insufficient time to balance work with other life activities that connect them to family and friends 128 , 236 . The sensemaking process that accompanies career shocks might highlight a lack of meaningful work that decreases the satisfaction of the need for autonomy. This lack of need satisfaction might lead people to take advantage of the disruption to ‘cut their losses’ by reorienting their life priorities and career goals, leading to resignation from their current jobs 237 , 238 .

Alternatively, the experiences gained from working differently during the COVID-19 pandemic might have made many workers aware of how work could be (for example, one does not have to commute), emboldening them to demand better work design and work conditions for themselves. Not surprisingly, barely a year after ‘the great resignation’ many are now talking about ‘the great reshuffle’, suggesting that many people who quit their jobs used this time to rethink their careers and find more satisfying work 239 . Generally, this has meant getting better pay and seeking work that aligns better with individual values and that provides a better work–life balance: in other words, work that better meets psychological needs for competence, autonomy and relatedness.

Virtual teamwork

Uncertainty and interconnectedness make work more complex, increasing the need for teamwork across many industries 150 . Work teams are groups of individuals that must both collaborate and work interdependently to achieve shared objectives 151 . Technology has created opportunities to develop work teams that operate virtually. Virtual teams are individuals working interdependently towards a common goal but who are geographically dispersed and who rely on electronic technologies to perform their work 152 , 153 . Thus, virtual teamwork is a special category of virtual work that also involves collective psychological experiences (that are shaped by and interact with virtual work) 154 . This adds another layer of complexity and therefore requires a separate discussion.

Most research conceptualizes team virtuality as a construct with two dimensions: geographical dispersion and reliance on technology 153 , 155 . Notably, these dimensions are not completely independent because team members require technology to communicate and coordinate tasks when working in different locations 156 , 157 . Virtuality differs between and within teams. Team members might be in different locations on some days and the same location on other days, which changes the level of team virtuality over time. Thus, teams are not strictly virtual or non-virtual. Team virtuality influences how team members coordinate tasks and share information 130 , which is critical for team effectiveness (usually assessed by a team’s tangible outputs, such as their productivity, and team member reactions, such as satisfaction with, or commitment to, the team) 158 .

Although individual team members might react differently to working in a virtual team, multi-level theory suggests that team members collectively develop shared experiences, called team emergent states 159 , 160 . Team emergent states include team cohesion (the bond among group members) 161 , team trust 162 , and team motivation and engagement 159 , 163 . These emergent states arise out of individual psychological behaviours and states 164 and are influenced by factors that are internal (for example, interactions between team members) and external (for example, organizational team rewards, organizational leadership and project deadlines) to the team, as well as team structure (for example, team size and composition). Team emergent states, particularly team trust, are critical for virtual team effectiveness because reliance on technology often brings uncertainties and fewer opportunities for social control 165 .

Team virtuality is likely to affect team functioning via its impact on psychological need satisfaction, in a fashion similar to remote work. However, the need for coordination and information sharing to achieve team goals is likely to be enhanced by how team members support and satisfy each other’s psychological needs 166 , which might be more difficult under virtual work conditions. In addition to affecting individual performance, need satisfaction within virtual teams can also influence collective-level team processes, such as coordination and trust, which ultimately affect team performance. For example, working in a virtual team might make it more difficult to feel meaningful connections because team members in different locations often have less contact than co-located team members. Virtual team members predominantly interact via technology, which — as described in the previous section — might influence the quality of relationships they can develop with their team members 141 , 167 , 168 and consequently the satisfaction of relatedness needs 169 .

Furthermore, virtual team members must master electronic communication technology (including virtual meeting and breakout rooms, internet connectivity issues, meeting across different time zones, and email overload), which can lead to frustrations and ‘technostress’ 170 . Frustrations with electronic communication might diminish the psychological need for competence because team members might feel ineffective in mastering their environment.

In sum, virtual team members might experience lower relatedness and competence need satisfaction. However, these needs are critical determinants of work motivation. Furthermore, virtual team members can also develop shared collective experiences around their need satisfaction. Thus, self-determination theory offers explanatory mechanisms (that is, team members’ need satisfaction, which influences work motivation) that are at play in virtual teams and that organizations should consider when implementing virtual teams.

Algorithmic management

Algorithmic management refers to the use of software algorithms to partially or completely execute workforce management functions (for example, hiring and firing, coordinating work, and monitoring performance) 2 , 123 , 171 , 172 . This phenomenon first appeared on gig economy platforms such as Uber, Instacart and Upwork, where all management is automated 173 . However, it is rapidly spreading to traditional work settings. Examples include monitoring the productivity, activity and emotions of remote workers 174 , the algorithmic determination of truck drivers’ routes and time targets 175 , and automated schedule creation in retail settings 176 . The constant updating of the algorithms as more data is collected and the opacity of this process makes algorithmic management unpredictable, which produces more uncertainty for workers 177 .

Algorithmic management has repercussions for work design. Specifically, whether algorithmic management systems consider human motivational factors in their design influences whether workers are given enough autonomy, skills usage, task variety, social contact, role clarity (including knowing the impact of one’s work) and a manageable workload 123 . So far, empirical evidence show that algorithmic management features predominantly reduce employees’ basic needs for autonomy, competence and relatedness because of how they influence work design (Fig.  4 ).

Summary of the features and consequences of algorithmic management on autonomy needs, relatedness needs and competence needs.

Algorithmic management tends to foster the ‘working-for-data’ phenomenon (or datafication of work) 172 , 178 , 179 , leading workers to focus their efforts on aspects of work that are being monitored and quantified at the expense of other tasks that might be more personally valued or meaningful. This tendency is reinforced by the fact that algorithms are updated with new incoming data, increasing the need for workers to pay close attention to what ‘pays off’ at any given moment. Monitoring and quantifying worker behaviours might reduce autonomy because it is experienced as controlling and narrows goal focus to only quantifiable results 127 , 180 ; there is some evidence that this is the case when algorithmic management systems are used to this end 172 , 178 , 181 . Rigid rules about how to carry out work often determine performance ratings (for example, imposing a route to deliver goods or prescribing how equipment and materials must be used) and even future task assignments and firing decisions, with little to no opportunity for employee input 182 , 183 , 184 . Thus, the combination of telling workers what to do to reach performance targets and how to get it done significantly limits their autonomy to make decisions based on their knowledge and skills.

Some algorithmic management platforms do not reveal all aspects of a given task (for example, not revealing the client destination before work is accepted) or penalize workers who decline jobs 185 , thereby severely restricting their choices. This encourages workers to either overwork to the point of exhaustion, find ways to game the system 184 , or misbehave 186 . Moreover, the technical complexity and opacity of algorithmic systems 187 , 188 , 189 deprives workers of the ability to understand and master the system that governs their work, which limits their voice and enpowerment 172 , 185 , 190 . Workers’ typical response to the lack of transparency is to organize themselves on social media to share any insights they have on what the algorithm ‘wants’ as a way to gain back some control over their work 183 , 191 .

Finally, algorithmic management usually provides comparative feedback (comparing one’s results to other workers’) and is linked to incentive pay structures, both of which reduce self-determined motivation as they are experienced as more controlling 26 , 192 . For instance, after algorithms estimated normal time standards for each ‘act’, algorithmic tracking and case allocation systems forced homecare nurses to reduce the ‘social’ time spent with patients because they were assigned more patients per day, thereby limiting nurses’ autonomy to decide how to perform their work 181 . Because these types of quantified metric are often directly linked to performance scores, pay incentives and future allocation of tasks or schedules (that is, getting future work), algorithmic management reduces workers’ freedom in decision-making related to their work, which can significantly reduce their self-determined motivation 123 .

Algorithmic management also tends to individualize work, which affects the need for relatedness. For example, algorithmic management inevitably transforms or reduces (sometimes even eliminates) contact with a supervisor 2 , 182 , 193 , leading to the feeling that the organization does not care about the worker and provides little social support 194 , 195 . ‘App-workers’, who obtain work through gig-work platforms such as Uber, reportedly crave more social interactions and networking opportunities 179 , 185 , 194 and often attempt to compensate for a lack of relatedness by creating support groups that connect virtually and physically 183 , 191 , 195 . Increased competitive climates due to comparative feedback or displaying team members’ individual rankings 175 , 196 can also hamper relatedness. Indeed, when workers have to compete against each other to rank highly (which influences their chances of getting future work and the financial incentives they receive), they are less likely to develop trusting and supportive relationships.

Researchers have formulated contradictory predictions about the potential implications of algorithmic management on competence satisfaction. On the one hand, using quantified metrics, algorithmic management systems can provide more frequent, unambiguous and performance-related feedback, often in the form of ratings and rankings 177 , and simultaneously link this feedback to financial rewards. Informational feedback can enhance intrinsic motivation because it provides information about one’s competence. At the same time, linking rewards to this feedback could decrease intrinsic motivation, because the contingency between work behaviour and pay limits worker discretion and therefore reduces their autonomy 26 . The evidence so far suggests that the mostly comparative feedback provided by algorithmic management is insufficiently informative because the value of the feedback is short-lived — continuously updating algorithms change what is required to perform well 177 , 183 , 185 . This short-lived feedback can undermine feelings of mastery or competence. In addition, algorithmic management is often associated with simplified tasks, and with lower problem-solving opportunities and job variety 123 . However, gamification features on some platforms might increase intrinsic motivation 179 , 183 .

The nascent research on the effects of algorithmic management on workers’ motivation indicates mostly negative effects on self-determined forms of motivation, because the way it is designed decreases the satisfaction of competence, autonomy and relatedness needs. Algorithmic management is being rapidly adopted across an increasing number of industries. Thus, technology developers and those who implement the technology in organizations will need to pay closer attention to how it changes work design to avoid negative effects on work motivation.

Summary and future directions

Self-determination theory can help predict the motivational consequences of future work and these motivational considerations should be taken into account when designing and implementing technology. More self-determined motivation will be needed to deal with the uncertainty and interdependence that will characterize future work. Thus, research examining how need satisfaction and work motivation influence people’s ability to adapt to uncertainty, or even leverage it, is needed. For example, future research could examine how different managerial styles influence adaptivity and proactivity in highly uncertain work environments 197 . Need-satisfying leadership, such as transformational leadership (charismatic or inspirational) 15 , can encourage job crafting and other proactive work behaviours 198 , 199 . Transactional leadership (focused on monitoring, rewarding and sanctioning) might promote self-determined motivation during organizational crises 23 . In addition, research on the quality of interconnectedness (the breadth and depth of interactions and networks) could provide insight on how to manage the increased interconnectedness workers are experiencing.

Technology can greatly assist in recruiting and selecting workers; self-determination theory can inform guidelines on how to design and use such technologies. It is important that the technology is easy to use and perceived as useful to the candidates for best representing themselves 200 , 201 . This can be done by ensuring that candidates have complete instructions before an assessment starts, even possibly getting a ‘practice run’, to improve their feelings of competence. It is also important for candidates to feel some amount of control and less pressure associated with online asynchronous assessments. Giving candidates some choice over testing platforms and the order of questions or settings, explaining how the results will be used, or allowing candidates to ask questions, could improve feelings of autonomy 70 . Finally, it is crucial to enhance perceptions that the organization cares about getting to know candidates and forging connections with them despite using these tools. For example, enhancing these tools with personalized videos of organizational members and providing candidates with feedback following selection decisions might increase feelings of relatedness. These suggestions need to be empirically tested 202 .

More research is also needed on how technology is transforming work design, and consequently influencing worker need satisfaction and motivation. Research in behavioural health has examined how digital applications that encourage healthy behaviours can be designed to fulfill the needs for competence, autonomy and relatedness 203 . Whether and how technology designed for other purposes (such as industrial robots, information communication technology, or automated decision-making systems) can be deliberately designed to meet these core human needs remains an open question. To date, little research has examined how work technologies are created, and what can be done to influence the process to create more human-centred designs. Collaborative research across social science and technical disciplines (such as engineering and computing) is needed.

In terms of implementation, although there is a long history of studies investigating the impact of technology on work design, current digital technologies are increasingly autonomous. This situation presents new challenges: a human-centred approach to automation in which the worker has transparent influence over the technical system has frequently been recommended as the optimal way to achieve high performance and to avoid automation failures 1 , 204 . But it is not clear that this work design strategy will be equally effective in terms of safety, productivity and meeting human needs when workers can no longer understand or control highly autonomous technology.

Given the likely persistence of virtual and remote work into the future, there is a critical need to understand how psychological needs can be satisfied when working remotely. Multi-wave studies that explore the boundary conditions of need satisfaction would advance knowledge around who is most likely to experience need satisfaction, when and why. Such knowledge can be leveraged to inform the design of interventions, such as supervisor training, to improve well-being and performance outcomes for virtual and remote workers. Similarly, no research to date has used self-determination theory to better understand how team virtuality affects how well team members support each other’s psychological needs. Within non-virtual teams, need satisfaction is influenced by the extent to which team members exhibit need-supportive behaviours towards each other 205 . For example, giving autonomy and empowering virtual teams is crucial for good team performance 206 . Studies that track team activities and interaction patterns, including virtual communication records, over time could be used to examine the effects of need support and thwarting between virtual team members 207 , 208 .

Finally, although most studies have shown negative effects of algorithmic management on workers’ motivation and work design characteristics, researchers should not view the effects of algorithmic management as predetermined and unchangeable. Sociotechnical aspects of the system 2 , 209 (such as transparency, privacy, accuracy, invasiveness and human control) and organizational policies surrounding their use could mitigate the motivational effects of algorithmic management. In sum, it is not algorithms that shape workers’ motivation, but how organizations design and use them 3 . Given that applications that use algorithmic management are developed mostly by computer and data scientists, sometimes with input from marketing specialists 185 , organizations would benefit from employing psychologists and human resources specialists to enhance the motivational potential of these applications.

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Gagné, M., Parker, S.K., Griffin, M.A. et al. Understanding and shaping the future of work with self-determination theory. Nat Rev Psychol 1 , 378–392 (2022). https://doi.org/10.1038/s44159-022-00056-w

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Neuroscience Study Taps Into Brain Network Patterns to Understand Deep Focus, Attention

Apr 08, 2024 —.

From completing puzzles and playing music, to reading and exercising, growing up Dolly Seeburger loved activities that demanded her full attention. “It was in those times that I felt most content, like I was in the zone,” she remembers. “Hours would pass, but it would feel like minutes.”

While this deep focus state is essential to highly effective work, it’s still not fully understood. Now, a new study led by Seeburger, a graduate student in the School of Psychology , alongside her advisor, Eric Schumacher , a professor in the School of Psychology is unearthing the mechanisms behind it. 

The interdisciplinary Georgia Tech team also includes Nan Xu, Sam Larson  and Shella Keilholz ( Coulter Department of Biomedical Engineering ), alongside Marcus Ma ( College of Computing ), and Christine Godwin ( School of Psychology ).

The researchers’ study, “ Time-varying functional connectivity predicts fluctuations in sustained attention in a serial tapping task ,” was published in Cognitive, Affective, and Behavioral Neuroscience earlier this year, and it investigates brain activity via fMRI during periods of deep focus and less-focused work. 

The work is the first to investigate low-frequency fluctuations between different networks in the brain during focus, and could act as a springboard to study more complex behaviors and focus states.

“Your brain is dynamic! Nothing is just on or off,” Seeburger explains. “This is the phenomenon we wanted to study. How does one get into the zone? Why is it that some people can sustain their attention better than others? Is this something that can be trained? If so, can we help people get better at it?”

The dynamic brain

The team’s work is also the first to study the relationship between fluctuations in attention and the brain network patterns within these low-frequency 20-second cycles. “For quite a while, the studies on neural oscillations focused on faster temporal frequencies, and the appreciation of these very low-frequency oscillations is relatively new,” Seeburger says. “But, these low-frequency fluctuations may play a key role in regulating higher cognition such as sustained attention.”

“One of the things we've discovered in previous research is that there's a natural fluctuation in activity in certain brain networks. When a subject is not doing a specific task while in the MRI scanner, we see that fluctuation happen roughly every 20 seconds,” adds co-author Schumacher, explaining that the team was interested in the pattern because it is quasi-periodic, meaning that it doesn’t repeat exactly every 20 seconds, and it varies between different trials and subjects.

By studying these quasi-periodic cycles, the team hoped to measure the relationship between the brain fluctuation in these networks and the behavioral fluctuation associated with changes in attention.

Your attention needed

To measure attention, participants tapped along to a metronome while in an fMRI scanner. The team could measure how “in the zone” participants were by measuring how much variability was in each participant’s taps — more variability suggested the participant was less focused, while precise tapping suggested the participant was “in the zone.”

The researchers found that when a subject’s focus level changed, different regions of the brain synchronized and desychronized, in particular the fronto-parietal control network (FPCN) and default mode network (DMN), The FPCN is engaged when a person is trying to stay on task, whereas the DMN is correlated with internally-oriented thoughts (which a participant might be having when less focused). “When one is out-of-the-zone, these two networks synchronize, and are in phase in the low frequency,” Seeburger explains. “When one is in the zone, these networks desynchronize.”

The results suggest that the 20-second patterns could help predict if a person is sustaining their attention or not, and could provide key insight for researchers developing tools and techniques that help us deeply focus.

The big picture

While the direct relationship between behavior and brain activity is still unknown, these 20-second patterns in brain fluctuation are seen universally, and across species. “If you put someone in a scanner and their mind is wandering, you find these fluctuations. You can find these quasi-period patterns in rodents. You can find it in primates,” Schumacher says. “There's something fundamental about this brain network activity.”

“I think it answers a really fundamental question about the relationship between behavior and brain activity,” he adds. “Understanding how these brain networks work together and impact behavior could lead to new therapies to help people organize their brain networks in the most efficient way.”

And while this simple task might not investigate complex behaviors, the study could act as a springboard to move into more complicated behaviors and focus states. “Next, I would like to study sustained attention in a more naturalistic way,” Seeburger says. “I hope that we can further the understanding of attention and help people get a better handle on their ability to control, sustain, and increase it.”

DOI: https://doi.org/10.3758/s13415-024-01156-1

Dolly Seeburger

Written by Selena Langner

Contact: Jess Hunt-Ralston

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Research News

Scientists study brains to understand the joy that's felt when caring for siblings.

Michaeleen Doucleff

For our series The Science of Siblings, we hear how researchers have found out that caring for siblings can make people happier.

STEVE INSKEEP, HOST:

Every Saturday evening inside a blue house in Odessa, Texas, you hear this.

(CROSSTALK)

UNIDENTIFIED PERSON #1: This is the fresas with crema.

UNIDENTIFIED PERSON #2: That's perfect.

UNIDENTIFIED PERSON #3: That's good.

INSKEEP: The Almance family gets together, cooks together, including the family's special taco recipe, and they laugh together.

CINDY ALMANCE: Tell daddy and you, and he was like, ma (laughter).

INSKEEP: This is much more than a good time because layered into that social gathering is a way to teach brothers and sisters to stop fighting and care for each other. For our series, The Science of Siblings, Michaeleen Doucleff traveled to the family's home in West Texas.

MICHAELEEN DOUCLEFF, BYLINE: Several months ago, Caitlynn Almance graduated from college. She's 22 years old. And as she thinks back to high school and college, she's had the same best friend the entire time.

CAITLYNN ALMANCE: My sister is my best friend in the entire world, and I tell people that all the time. I don't think I could, like, make it, like, day-to-day basis without her. Like, she's the person that I depend on for everything.

DOUCLEFF: Caitlynn grew up in Odessa, but she went to college in another town two hours away. Sometimes her sister, who's still in high school, will call up Caitlynn and ask her to borrow her clothes or a pair of boots. And Caitlynn would stop what she's doing and drive four hours.

CAITLYNN ALMANCE: There was one time that I had, like, just like a four-hour break. That's all I had. And I drove all the way down, like, dropped it off in the front door and, like, took all the way back off to, like, Alpine. It's 'cause she needed it. She needed it. And, you know, in that moment, she really does need it.

DOUCLEFF: Caitlynn's love and caring doesn't end with her sister. She feels the same about her little brother. A few years ago, she seriously considered moving with him to Los Angeles to help support him through school.

CAITLYNN ALMANCE: And I was like, look, Eddie, if that's what you really want to do, like, I'll, like, get up, and I'll pick up my life. And I'll move over there, and I'd work.

DOUCLEFF: To help him pay for schooling?

CAITLYNN ALMANCE: Yeah. Yeah. And so he wouldn't have to struggle either. 'Cause I know, like, how hard it was for me to, like, work and go to school at the same time and, like, juggle. And, like, if he doesn't have to do that, then I wouldn't want him to do that.

DOUCLEFF: For the past few decades, scientists have been studying how parents all around the world teach their children to build deep, fulfilling relationships with their siblings. Belinda Campos is a psychologist at the University of California, Irvine. She says that in Latino families like Caitlynn's, parents are often doing something very specific, and scientists can even see what it is inside the brains of young adults. In one study, researchers brought college students into the laboratory from two cultural groups.

BELINDA CAMPOS: They had European American and Latino participants come in, and they had them play a resource game.

DOUCLEFF: During the game, the students had to decide whether or not to help a family member who needed money.

CAMPOS: Both groups assisted their family members when there was a perceived need.

DOUCLEFF: But here's the key. While the participants gave their family money, the researchers studied their brains with an MRI scanner. What happened inside the brains of the Latino participants was quite different than inside European Americans' brains. While giving their family money...

CAMPOS: The brains of the Latino participants - the reward centers of the brain lit up when they were doing so.

DOUCLEFF: In fact, their reward centers lit up more when they gave money than when they received money themselves. But that didn't happen with European American students.

CAMPOS: It makes such a compelling argument that some of us find the act of giving - or because we're socialized to - to be, like, really rewarding.

DOUCLEFF: Now, the reward center of our brains helps us feel pleasure and joy. Mariano Rojas is a behavioral economist at Mexico's Technology Institute. He says many studies, including his own, show that Latino parents often teach their children not so much that they have to help their siblings, but to actually want to help their siblings. And they do that by teaching them that helping brings you joy.

MARIANO ROJAS: It's about enjoyment and relations that provide happiness.

DOUCLEFF: In other words, helping your sister - bringing her a pair of boots - isn't so much a huge burden or obligation, but a major source of joy in your life. It gives children...

ROJAS: What I call relational wealth.

DOUCLEFF: This relational wealth has massive repercussions for Latin American communities. Rojas' research finds it's the major reason why people in these communities tend to score very high on surveys about happiness.

ROJAS: Latin Americans perform outstandingly well. Their happiness is very high.

DOUCLEFF: That's across all economic levels.

CINDY ALMANCE: The funniest story of my life.

DOUCLEFF: Back in Odessa, the sun has just set over the dry West Texas prairie. It's around dinnertime, and the Almance family is doing what they do almost every day. They're gathered around the kitchen island. There's Caitlynn's grandmother, her parents, an aunt and an uncle. They're telling stories about trips they've taken all together and reliving all the fun.

CINDY ALMANCE: Welcome to the family. I mean...

DOUCLEFF: That's Caitlynn's mom, Cindy. I asked her, how do you teach children to find joy in helping their siblings?

CINDY ALMANCE: It's the modeling, right?

DOUCLEFF: Modeling. And what Cindy models is the joy she gets from the relationships she has with her own brothers and sisters.

CINDY ALMANCE: I guess it's a close, close bond.

DOUCLEFF: Even after some of her siblings left Odessa, she still loves to talk to them on the phone.

CINDY ALMANCE: You know, 6:30 in the morning on my way to work, I'm talking to them already, but it's every single day.

DOUCLEFF: And her daughter Caitlynn not only notices these calls - she even joins them.

CAITLYNN ALMANCE: My mom's older sister, they're in a different time zone than we are, so they have to wake up an hour earlier than their day would start, just so that we could, like, have that, like, daily, like, dose before we get to work.

DOUCLEFF: Perhaps most importantly, Caitlynn says, is the family enjoys being together - multiple generations of brothers and sisters all having fun together.

CAITLYNN ALMANCE: This is, like, your everyday people. And they have such, like, an everyday impact on my life rather than, like, us, like, searching each other up on Facebook. Like, that doesn't exist. Like, we all know each other.

DOUCLEFF: And now Caitlynn is going to add the next generation of siblings. She's expecting her first child this summer, and she's already talking about having a second baby.

CAITLYNN ALMANCE: This one isn't even out yet, but I'm like, let's hurry up and make the other one.

DOUCLEFF: Why? Because she wants her baby to have a sibling right away.

CAITLYNN ALMANCE: Just, like, imagining my kid growing up without that - there's probably nothing worse than that. That would be, like, the biggest sin I could ever imagine.

DOUCLEFF: For NPR News, I'm Michaeleen Doucleff.

(SOUNDBITE OF MUSIC)

INSKEEP: Hey, join us tomorrow for a story of identical twins. Both are autistic and have different experiences.

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The new science of death: ‘There’s something happening in the brain that makes no sense’

New research into the dying brain suggests the line between life and death may be less distinct than previously thought

P atient One was 24 years old and pregnant with her third child when she was taken off life support. It was 2014. A couple of years earlier, she had been diagnosed with a disorder that caused an irregular heartbeat, and during her two previous pregnancies she had suffered seizures and faintings. Four weeks into her third pregnancy, she collapsed on the floor of her home. Her mother, who was with her, called 911. By the time an ambulance arrived, Patient One had been unconscious for more than 10 minutes. Paramedics found that her heart had stopped.

After being driven to a hospital where she couldn’t be treated, Patient One was taken to the emergency department at the University of Michigan. There, medical staff had to shock her chest three times with a defibrillator before they could restart her heart. She was placed on an external ventilator and pacemaker, and transferred to the neurointensive care unit, where doctors monitored her brain activity. She was unresponsive to external stimuli, and had a massive swelling in her brain. After she lay in a deep coma for three days, her family decided it was best to take her off life support. It was at that point – after her oxygen was turned off and nurses pulled the breathing tube from her throat – that Patient One became one of the most intriguing scientific subjects in recent history.

For several years, Jimo Borjigin, a professor of neurology at the University of Michigan, had been troubled by the question of what happens to us when we die. She had read about the near-death experiences of certain cardiac-arrest survivors who had undergone extraordinary psychic journeys before being resuscitated. Sometimes, these people reported travelling outside of their bodies towards overwhelming sources of light where they were greeted by dead relatives. Others spoke of coming to a new understanding of their lives, or encountering beings of profound goodness. Borjigin didn’t believe the content of those stories was true – she didn’t think the souls of dying people actually travelled to an afterworld – but she suspected something very real was happening in those patients’ brains. In her own laboratory, she had discovered that rats undergo a dramatic storm of many neurotransmitters, including serotonin and dopamine, after their hearts stop and their brains lose oxygen. She wondered if humans’ near-death experiences might spring from a similar phenomenon, and if it was occurring even in people who couldn’t be revived.

Dying seemed like such an important area of research – we all do it, after all – that Borjigin assumed other scientists had already developed a thorough understanding of what happens to the brain in the process of death. But when she looked at the scientific literature, she found little enlightenment. “To die is such an essential part of life,” she told me recently. “But we knew almost nothing about the dying brain.” So she decided to go back and figure out what had happened inside the brains of people who died at the University of Michigan neurointensive care unit. Among them was Patient One.

At the time Borjigin began her research into Patient One, the scientific understanding of death had reached an impasse. Since the 1960s, advances in resuscitation had helped to revive thousands of people who might otherwise have died. About 10% or 20% of those people brought with them stories of near-death experiences in which they felt their souls or selves departing from their bodies. A handful of those patients even claimed to witness, from above, doctors’ attempts to resuscitate them. According to several international surveys and studies, one in 10 people claims to have had a near-death experience involving cardiac arrest, or a similar experience in circumstances where they may have come close to death. That’s roughly 800 million souls worldwide who may have dipped a toe in the afterlife.

As remarkable as these near-death experiences sounded, they were consistent enough that some scientists began to believe there was truth to them: maybe people really did have minds or souls that existed separately from their living bodies. In the 1970s, a small network of cardiologists, psychiatrists, medical sociologists and social psychologists in North America and Europe began investigating whether near-death experiences proved that dying is not the end of being, and that consciousness can exist independently of the brain. The field of near-death studies was born.

Over the next 30 years, researchers collected thousands of case reports of people who had had near-death experiences. Meanwhile, new technologies and techniques were helping doctors revive more and more people who, in earlier periods of history, would have almost certainly been permanently deceased. “We are now at the point where we have both the tools and the means to scientifically answer the age-old question: What happens when we die?” wrote Sam Parnia, an accomplished resuscitation specialist and one of the world’s leading experts on near-death experiences, in 2006. Parnia himself was devising an international study to test whether patients could have conscious awareness even after they were found clinically dead.

But by 2015, experiments such as Parnia’s had yielded ambiguous results, and the field of near-death studies was not much closer to understanding death than it had been when it was founded four decades earlier. That’s when Borjigin, together with several colleagues, took the first close look at the record of electrical activity in the brain of Patient One after she was taken off life support. What they discovered – in results reported for the first time last year – was almost entirely unexpected, and has the potential to rewrite our understanding of death.

“I believe what we found is only the tip of a vast iceberg,” Borjigin told me. “What’s still beneath the surface is a full account of how dying actually takes place. Because there’s something happening in there, in the brain, that makes no sense.”

F or all that science has learned about the workings of life, death remains among the most intractable of mysteries. “At times I have been tempted to believe that the creator has eternally intended this department of nature to remain baffling, to prompt our curiosities and hopes and suspicions all in equal measure,” the philosopher William James wrote in 1909.

The first time that the question Borjigin began asking in 2015 was posed – about what happens to the brain during death – was a quarter of a millennium earlier. Around 1740, a French military physician reviewed the case of a famous apothecary who, after a “malign fever” and several blood-lettings, fell unconscious and thought he had travelled to the Kingdom of the Blessed . The physician speculated that the apothecary’s experience had been caused by a surge of blood to the brain. But between that early report and the mid-20th century, scientific interest in near-death experiences remained sporadic.

In 1892, the Swiss climber and geologist Albert Heim collected the first systematic accounts of near-death experiences from 30 fellow climbers who had suffered near-fatal falls. In many cases, the climbers underwent a sudden review of their entire past, heard beautiful music, and “fell in a superbly blue heaven containing roseate cloudlets”, Heim wrote. “Then consciousness was painlessly extinguished, usually at the moment of impact.” There were a few more attempts to do research in the early 20th century, but little progress was made in understanding near-death experiences scientifically. Then, in 1975, an American medical student named Raymond Moody published a book called Life After Life.

In his book, Moody distilled the reports of 150 people who had had intense, life-altering experiences in the moments surrounding a cardiac arrest. Although the reports varied, he found that they often shared one or more common features or themes. The narrative arc of the most detailed of those reports – departing the body and travelling through a long tunnel, having an out-of-body experience, encountering spirits and a being of light, one’s whole life flashing before one’s eyes, and returning to the body from some outer limit – became so canonical that the art critic Robert Hughes could refer to it years later as “the familiar kitsch of near-death experience”. Moody’s book became an international bestseller.

In 1976, the New York Times reported on the burgeoning scientific interest in “life after death” and the “emerging field of thanatology”. The following year, Moody and several fellow thanatologists founded an organisation that became the International Association for Near-Death Studies. In 1981, they printed the inaugural issue of Vital Signs , a magazine for the general reader that was largely devoted to stories of near-death experiences. The following year they began producing the field’s first peer-reviewed journal, which became the Journal of Near-Death Studies . The field was growing, and taking on the trappings of scientific respectability. Reviewing its rise in 1988, the British Journal of Psychiatry captured the field’s animating spirit: “A grand hope has been expressed that, through NDE research, new insights can be gained into the ageless mystery of human mortality and its ultimate significance, and that, for the first time, empirical perspectives on the nature of death may be achieved.”

But near-death studies was already splitting into several schools of belief, whose tensions continue to this day. One influential camp was made up of spiritualists, some of them evangelical Christians, who were convinced that near-death experiences were genuine sojourns in the land of the dead and divine. As researchers, the spiritualists’ aim was to collect as many reports of near-death experience as possible, and to proselytise society about the reality of life after death. Moody was their most important spokesman; he eventually claimed to have had multiple past lives and built a “psychomanteum” in rural Alabama where people could attempt to summon the spirits of the dead by gazing into a dimly lit mirror.

The second, and largest, faction of near-death researchers were the parapsychologists, those interested in phenomena that seemed to undermine the scientific orthodoxy that the mind could not exist independently of the brain. These researchers, who were by and large trained scientists following well established research methods, tended to believe that near-death experiences offered evidence that consciousness could persist after the death of the individual. Many of them were physicians and psychiatrists who had been deeply affected after hearing the near-death stories of patients they had treated in the ICU. Their aim was to find ways to test their theories of consciousness empirically, and to turn near-death studies into a legitimate scientific endeavour.

Finally, there emerged the smallest contingent of near-death researchers, who could be labelled the physicalists. These were scientists, many of whom studied the brain, who were committed to a strictly biological account of near-death experiences. Like dreams, the physicalists argued, near-death experiences might reveal psychological truths, but they did so through hallucinatory fictions that emerged from the workings of the body and the brain. (Indeed, many of the states reported by near-death experiencers can apparently be achieved by taking a hero’s dose of ketamine.) Their basic premise was: no functioning brain means no consciousness, and certainly no life after death. Their task, which Borjigin took up in 2015, was to discover what was happening during near-death experiences on a fundamentally physical level.

Slowly, the spiritualists left the field of research for the loftier domains of Christian talk radio, and the parapsychologists and physicalists started bringing near-death studies closer to the scientific mainstream. Between 1975, when Moody published Life After Life, and 1984, only 17 articles in the PubMed database of scientific publications mentioned near-death experiences. In the following decade, there were 62. In the most recent 10-year span, there were 221. Those articles have appeared everywhere from the Canadian Urological Association Journal to the esteemed pages of The Lancet.

Today, there is a widespread sense throughout the community of near-death researchers that we are on the verge of great discoveries. Charlotte Martial, a neuroscientist at the University of Liège in Belgium who has done some of the best physicalist work on near-death experiences, hopes we will soon develop a new understanding of the relationship between the internal experience of consciousness and its outward manifestations, for example in coma patients. “We really are in a crucial moment where we have to disentangle consciousness from responsiveness, and maybe question every state that we consider unconscious,” she told me. Parnia, the resuscitation specialist, who studies the physical processes of dying but is also sympathetic to a parapsychological theory of consciousness, has a radically different take on what we are poised to find out. “I think in 50 or 100 years time we will have discovered the entity that is consciousness,” he told me. “It will be taken for granted that it wasn’t produced by the brain, and it doesn’t die when you die.”

I f the field of near-death studies is at the threshold of new discoveries about consciousness and death, it is in large part because of a revolution in our ability to resuscitate people who have suffered cardiac arrest. Lance Becker has been a leader in resuscitation science for more than 30 years. As a young doctor attempting to revive people through CPR in the mid-1980s, senior physicians would often step in to declare patients dead. “At a certain point, they would just say, ‘OK, that’s enough. Let’s stop. This is unsuccessful. Time of death: 1.37pm,’” he recalled recently. “And that would be the last thing. And one of the things running through my head as a young doctor was, ‘Well, what really happened at 1.37?’”

In a medical setting, “clinical death” is said to occur at the moment the heart stops pumping blood, and the pulse stops. This is widely known as cardiac arrest. (It is different from a heart attack, in which there is a blockage in a heart that’s still pumping.) Loss of oxygen to the brain and other organs generally follows within seconds or minutes, although the complete cessation of activity in the heart and brain – which is often called “flatlining” or, in the case of the latter, “brain death” – may not occur for many minutes or even hours.

For almost all people at all times in history, cardiac arrest was basically the end of the line. That began to change in 1960, when the combination of mouth-to-mouth ventilation, chest compressions and external defibrillation known as cardiopulmonary resuscitation, or CPR, was formalised. Shortly thereafter, a massive campaign was launched to educate clinicians and the public on CPR’s basic techniques , and soon people were being revived in previously unthinkable, if still modest, numbers.

As more and more people were resuscitated, scientists learned that, even in its acute final stages, death is not a point, but a process. After cardiac arrest, blood and oxygen stop circulating through the body, cells begin to break down, and normal electrical activity in the brain gets disrupted. But the organs don’t fail irreversibly right away, and the brain doesn’t necessarily cease functioning altogether. There is often still the possibility of a return to life. In some cases, cell death can be stopped or significantly slowed, the heart can be restarted, and brain function can be restored. In other words, the process of death can be reversed.

It is no longer unheard of for people to be revived even six hours after being declared clinically dead. In 2011, Japanese doctors reported the case of a young woman who was found in a forest one morning after an overdose stopped her heart the previous night; using advanced technology to circulate blood and oxygen through her body, the doctors were able to revive her more than six hours later, and she was able to walk out of the hospital after three weeks of care. In 2019, a British woman named Audrey Schoeman who was caught in a snowstorm spent six hours in cardiac arrest before doctors brought her back to life with no evident brain damage.

“I don’t think there’s ever been a more exciting time for the field,” Becker told me. “We’re discovering new drugs, we’re discovering new devices, and we’re discovering new things about the brain.”

T he brain – that’s the tricky part. In January 2021, as the Covid-19 pandemic was surging toward what would become its deadliest week on record, Netflix released a documentary series called Surviving Death . In the first episode, some of near-death studies’ most prominent parapsychologists presented the core of their arguments for why they believe near-death experiences show that consciousness exists independently of the brain. “When the heart stops, within 20 seconds or so, you get flatlining, which means no brain activity,” Bruce Greyson, an emeritus professor of psychiatry at the University of Virginia and one of the founding members of the International Association for Near-Death Studies, says in the documentary. “And yet,” he goes on to claim, “people have near-death experiences when they’ve been (quote) ‘flatlined’ for longer than that.”

That is a key tenet of the parapsychologists’ arguments: if there is consciousness without brain activity, then consciousness must dwell somewhere beyond the brain. Some of the parapsychologists speculate that it is a “non-local” force that pervades the universe, like electromagnetism. This force is received by the brain, but is not generated by it, the way a television receives a broadcast.

In order for this argument to hold, something else has to be true: near-death experiences have to happen during death, after the brain shuts down. To prove this, parapsychologists point to a number of rare but astounding cases known as “veridical” near-death experiences, in which patients seem to report details from the operating room that they might have known only if they had conscious awareness during the time that they were clinically dead. Dozens of such reports exist. One of the most famous is about a woman who apparently travelled so far outside her body that she was able to spot a shoe on a window ledge in another part of the hospital where she went into cardiac arrest; the shoe was later reportedly found by a nurse.

At the very least, Parnia and his colleagues have written, such phenomena are “inexplicable through current neuroscientific models”. Unfortunately for the parapsychologists, however, none of the reports of post-death awareness holds up to strict scientific scrutiny. “There are many claims of this kind, but in my long decades of research into out-of-body and near-death experiences I never met any convincing evidence that this is true,” Sue Blackmore, a well-known researcher into parapsychology who had her own near-death experience as a young woman in 1970, has written .

The case of the shoe, Blackmore pointed out, relied solely on the report of the nurse who claimed to have found it. That’s far from the standard of proof the scientific community would require to accept a result as radical as that consciousness can travel beyond the body and exist after death. In other cases, there’s not enough evidence to prove that the experiences reported by cardiac arrest survivors happened when their brains were shut down, as opposed to in the period before or after they supposedly “flatlined”. “So far, there is no sufficiently rigorous, convincing empirical evidence that people can observe their surroundings during a near-death experience,” Charlotte Martial, the University of Liège neuroscientist, told me.

The parapsychologists tend to push back by arguing that even if each of the cases of veridical near-death experiences leaves room for scientific doubt, surely the accumulation of dozens of these reports must count for something. But that argument can be turned on its head: if there are so many genuine instances of consciousness surviving death, then why should it have so far proven impossible to catch one empirically?

P erhaps the story to be written about near-death experiences is not that they prove consciousness is radically different from what we thought it was. Instead, it is that the process of dying is far stranger than scientists ever suspected. The spiritualists and parapsychologists are right to insist that something deeply weird is happening to people when they die, but they are wrong to assume it is happening in the next life rather than this one. At least, that is the implication of what Jimo Borjigin found when she investigated the case of Patient One.

In the moments after Patient One was taken off oxygen, there was a surge of activity in her dying brain. Areas that had been nearly silent while she was on life support suddenly thrummed with high-frequency electrical signals called gamma waves. In particular, the parts of the brain that scientists consider a “hot zone” for consciousness became dramatically alive. In one section, the signals remained detectable for more than six minutes. In another, they were 11 to 12 times higher than they had been before Patient One’s ventilator was removed.

“As she died, Patient One’s brain was functioning in a kind of hyperdrive,” Borjigin told me. For about two minutes after her oxygen was cut off, there was an intense synchronisation of her brain waves, a state associated with many cognitive functions, including heightened attention and memory. The synchronisation dampened for about 18 seconds, then intensified again for more than four minutes. It faded for a minute, then came back for a third time.

In those same periods of dying, different parts of Patient One’s brain were suddenly in close communication with each other. The most intense connections started immediately after her oxygen stopped, and lasted for nearly four minutes. There was another burst of connectivity more than five minutes and 20 seconds after she was taken off life support. In particular, areas of her brain associated with processing conscious experience – areas that are active when we move through the waking world, and when we have vivid dreams – were communicating with those involved in memory formation. So were parts of the brain associated with empathy. Even as she slipped irrevocably deeper into death, something that looked astonishingly like life was taking place over several minutes in Patient One’s brain.

Those glimmers and flashes of something like life contradict the expectations of almost everyone working in the field of resuscitation science and near-death studies. The predominant belief – expressed by Greyson, the psychiatrist and co-founder of the International Association of Near Death Studies, in the Netflix series Surviving Death – was that as soon as oxygen stops going to the brain, neurological activity falls precipitously. Although a few earlier instances of brain waves had been reported in dying human brains, nothing as detailed and complex as what occurred in Patient One had ever been detected.

Given the levels of activity and connectivity in particular regions of her dying brain, Borjigin believes it’s likely that Patient One had a profound near-death experience with many of its major features: out-of-body sensations, visions of light, feelings of joy or serenity, and moral re-evaluations of one’s life. Of course, Patient One did not recover, so no one can prove that the extraordinary happenings in her dying brain had experiential counterparts. Greyson and one of the other grandees of near-death studies, a Dutch cardiologist named Pim van Lommel, have asserted that Patient One’s brain activity can shed no light on near-death experiences because her heart hadn’t fully flatlined, but that is a self-defeating argument: there is no rigorous empirical evidence that near-death experiences occur in people whose hearts have completely stopped.

At the very least, Patient One’s brain activity – and the activity in the dying brain of another patient Borjigin studied, a 77-year-old woman known as Patient Three – seems to close the door on the argument that the brain always and nearly immediately ceases to function in a coherent manner in the moments after clinical death. “The brain, contrary to everybody’s belief, is actually super active during cardiac arrest,” Borjigin said. Death may be far more alive than we ever thought possible.

B orjigin believes that understanding the dying brain is one of the “holy grails” of neuroscience. “The brain is so resilient, the heart is so resilient, that it takes years of abuse to kill them,” she pointed out. “Why then, without oxygen, can a perfectly healthy person die within 30 minutes, irreversibly?” Although most people would take that result for granted, Borjigin thinks that, on a physical level, it actually makes little sense.

Borjigin hopes that understanding the neurophysiology of death can help us to reverse it. She already has brain activity data from dozens of deceased patients that she is waiting to analyse. But because of the paranormal stigma associated with near-death studies, she says, few research agencies want to grant her funding. “Consciousness is almost a dirty word amongst funders,” she added. “Hardcore scientists think research into it should belong to maybe theology, philosophy, but not in hardcore science. Other people ask, ‘What’s the use? The patients are gonna die anyway, so why study that process? There’s nothing you can do about it.’”

Evidence is already emerging that even total brain death may someday be reversible. In 2019, scientists at Yale University harvested the brains of pigs that had been decapitated in a commercial slaughterhouse four hours earlier. Then they perfused the brains for six hours with a special cocktail of drugs and synthetic blood. Astoundingly, some of the cells in the brains began to show metabolic activity again, and some of the synapses even began firing. The pigs’ brain scans didn’t show the widespread electrical activity that we typically associate with sentience or consciousness. But the fact that there was any activity at all suggests the frontiers of life may one day extend much, much farther into the realms of death than most scientists currently imagine.

Other serious avenues of research into near-death experience are ongoing. Martial and her colleagues at the University of Liège are working on many issues relating to near-death experiences. One is whether people with a history of trauma, or with more creative minds, tend to have such experiences at higher rates than the general population. Another is on the evolutionary biology of near-death experiences. Why, evolutionarily speaking, should we have such experiences at all? Martial and her colleagues speculate that it may be a form of the phenomenon known as thanatosis, in which creatures throughout the animal kingdom feign death to escape mortal dangers. Other researchers have proposed that the surge of electrical activity in the moments after cardiac arrest is just the final seizure of a dying brain, or have hypothesised that it’s a last-ditch attempt by the brain to restart itself, like jump-starting the engine on a car.

Meanwhile, in parts of the culture where enthusiasm is reserved not for scientific discovery in this world, but for absolution or benediction in the next, the spiritualists, along with sundry other kooks and grifters, are busily peddling their tales of the afterlife. Forget the proverbial tunnel of light: in America in particular, a pipeline of money has been discovered from death’s door, through Christian media, to the New York Times bestseller list and thence to the fawning, gullible armchairs of the nation’s daytime talk shows. First stop, paradise; next stop, Dr Oz.

But there is something that binds many of these people – the physicalists, the parapsychologists, the spiritualists – together. It is the hope that by transcending the current limits of science and of our bodies, we will achieve not a deeper understanding of death, but a longer and more profound experience of life. That, perhaps, is the real attraction of the near-death experience: it shows us what is possible not in the next world, but in this one.

• The long read
• Death and dying
• Consciousness
• Neuroscience

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College of Biological Sciences

New research suggests cerebellum may play important role in autism.

NIMH grant will fund studies on how autism risk gene impacts a crucial, but long-overlooked brain area

• by Douglas Fox
• April 02, 2024

Researchers in the College of Biological Sciences have received a grant to study the role of the cerebellum in autism. “We need a more holistic understanding of the brain circuits that drive this disorder,” says Alex Nord, an associate professor of neurobiology, physiology and behavior (NPB), and a researcher at the Center for Neuroscience (CNS). “The cerebellum is a key component that has been largely overlooked until recently.”

Nord partnered with Diasynou Fioravante, also an associate professor of NPB and CNS researcher, and received an R21 grant from the National Institute of Mental Health (NIMH). Announced in November, it will provide $435,000 of funding over the next two years.

With this grant, they will study how a potent autism risk gene, called chromodomain helicase DNA binding protein 8 ( Chd8 ), alters function in the cerebellum, which plays a crucial role in physical movement, and how this drives autism-like behaviors. Their research ties together two emerging trends in autism research.

Surprising discoveries in autism

Researchers long believed that autism involved genes that regulate communications between neurons — especially the synapses, where neurotransmitters carry signals from one neuron to another. But starting in the early 2010s, genetic studies revealed that many autism risk genes actually play a very different role: they encode proteins that reside far from the synapses — in the cell’s nucleus, where the DNA is located, and regulate the activity of hundreds of other genes.

“This was a huge surprise,” says Nord. Chd8 , a typical member of this group, regulates how tightly DNA is packaged and coiled with proteins. As such, it may regulate many genes that govern the formation and function of synapses.

At the same time, another major area of study is advancing the field of autism research. Scientists had assumed that autism was driven by changes in the cerebral cortex, which performs all sorts of tasks, such as recognizing words and faces, and “executive function” — controlling working memory, guiding our spotlight of attention, and making choices — such as whether to act on the impulse to withdraw one's hand when an unfamiliar dog approaches.

But in 2012, researchers reported that mice with mild abnormalities in the cerebellum developed behaviors that resembled autism in humans, such as reduced social interaction with other mice. “The autism field was really rocked by this discovery,” says Fioravante.

People had previously believed that the cerebellum mainly coordinates body movements such as walking, speaking, and typing. “When you damage the cerebellum, it causes profound movement problems, and this probably made it difficult to see more subtle changes in behavior,” says Fioravante.

But she points out that the cerebellum has significant connections with brain structures like the prefrontal cortex, which guides executive function, and limbic system, which regulates sociability, mood and emotions . People with cerebellar injuries often show autism-like changes in their emotions and social interactions.

Then in 2017, Nord and his colleagues reported a discovery that tied together these two intriguing threads : they found that the autism risk gene Chd8 helped guide the development of the cerebellum. Mice with one non-functioning copy of the gene had smaller cerebella.

That discovery “planted the idea of our project,” says Fioravante. She and Nord sat in offices next door to one another. And while Nord studied Chd8 , she worked on the cerebellum. In 2021 they applied for, and received, an earlier NIMH grant, to study how Chd8 influences the development of the cerebellum in mice, before and shortly after birth. Fioravante also received a pilot grant from the Behavioral Health Center of Excellence at UC Davis that launched Chd8 cerebellar studies in adult mice.

Working on these earlier grants from 2021 to 2023, they found that Chd8 mutations in mice triggered changes in the cerebellum and in behavior that resemble what is seen in humans with autism. For example, mice with a mutant copy of the gene had impaired social cognition. While regular mice prefer to explore and interact with mice they have not met before, mice with mutant Chd8 had more restricted interests — preferring mice or objects that they already knew.

New targets for treatment

With the new grant, Fioravante and Nord will pick up where they left off. In adult mice with normally developed cerebella, they will use genetic tools to disrupt Chd8 . They will examine how loss of Chd8 alters gene expression and function in neurons of the cerebellum, and how the connections between it and other brain areas change. They will also study whether disruption of Chd8 causes autism-like behavioral changes, such as reduced social interaction with other mice, or reduced interest in novelty. Cesar Canales, an assistant professional researcher in NPB, who has expertise in cerebellar anatomy, will take part in these studies.

These experiments “will help shed light on the totality of what the cerebellum does,” says Fioravante — getting beyond the traditional narrow view that it mainly coordinates movement. The team also hopes to uncover new strategies for treating autism.

Although autism involves early brain development, the condition usually isn’t diagnosed until children are years older — when the abnormal brain connections are already established, potentially making treatment difficult.

In these upcoming studies, Nord and Fioravante hope to explore whether the treatment window for autism can be extended. “If we see changes in behavior or neural circuits when Chd8 is disrupted in the developed cerebellum, then we know there is a treatment target,” says Nord.

These studies could also shed light on schizophrenia and obsessive-compulsive disorder, which occur more frequently in people with mutations in this gene, says Nord: “It’s a molecular handle, an entry point into the pathophysiology of these other complex diseases.”

Media Resources

• Douglas Fox is a freelance science writer based in the Bay Area.
• Fioravante Lab
• Germline Chd8 haploinsufficiency alters brain development in mouse ( Nature Neuroscience 2017)
• Cognitive-affective functions of the cerebellum ( The Journal of Neuroscience 2023)

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Understanding science

#188 – ama #30: how to read and understand scientific studies.

by Peter Attia

Read Time 41 minutes

In this “Ask Me Anything” (AMA) episode, Peter and Bob dive deep into all things related to studying studies to help one sift through all the noise to find the signal. They define the various types of studies, how a study progresses from idea to execution, and how to identify study strengths and limitations. They explain how clinical trials work, as well as the potential for bias and common pitfalls to watch out for. They dig into key factors that contribute to the rigor (or lack thereof) of an experiment, and they discuss how to measure effect size, differentiate relative risk from absolute risk, and what it really means when a study is statistically significant. Finally, Peter lays out his personal process when reading through scientific papers.

Below is a sneak peek of the episode. If you’re a member, you can listen to this full episode on your private RSS feed or on our website here . If you are not a member, subscribe now to gain immediate access to this full episode, our entire back catalog of AMA episodes, plus more great benefits!

AMA #30 Sneak Peak:

We discuss:

• The ever changing landscape of scientific literature [2:15];
• The process for a study to progress from idea to design to execution [4:15];
• The various types of studies and how they differ [7:30];
• The different phases of a clinical trial [19:15];
• Observational studies and the potential for bias [26:30];
• Experimental studies: Randomization, blinding, and other factors that make or break a study [44:00];
• Power, p-values, and statistical significance [56:15];
• Measuring effect size: Relative risk vs. absolute risk, hazard ratios, and “Number Needed to Treat” [1:07:45];
• How to interpret confidence intervals [1:17:30];
• Why a study might be stopped before its completion [1:23:45];
• Why only a fraction of studies are ever published and how to combat publication bias [1:31:30];
• Why certain journals are more respected than others [1:40:30];
• Peter’s process when reading a scientific paper [1:43:45]; and

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The ever changing landscape of scientific literature [2:15]

• Peter was on The Tim Ferriss Show in June where the topic of studies came up
• Peter has also written a five part series on Studying Studies
• i)  help people make sense of the “ ever changing landscape of scientific literature and how to distinguish between the signal and the noise of the research news cycle ”; and
• ii) be a primer for people to really understand the process of scientific experiments and everything from how studies are published and obviously what some of the limitations are

The process for a study to progress from idea to design to execution [4:15]

Broad steps:

• Hypothesis: The default position in an experiment is that there is no relationship between two phenomena. This is called the null (i.e., zero) hypothesis. 
• Experimental design 
• power analysis 
• primary and secondary outcomes, protocol, stats plan, and preregistration

Step 1 : Null hypothesis

• In theory, it should start with a hypothesis—” Good science is generally hypothesis-driven .”
• Null hypothesis: Take the position that there is no relationship between two phenomena
• For instance, the hypothesis might be that drinking coffee makes your eyes turn darker
• Then it must be framed in a way that says the null hypothesis is that when you drink coffee, your eyes do not change in color in any way
• That would imply that the alternative of hypothesis is that when you drink coffee, your eyes do change color
• But there’s nuance to this… because am I specifying what color it changes to? Does it get darker? Does it get lighter? Does it change to blue, green? Does it just get the darker shade 
• To be able to formulate that cleanly is the first step here

Step 2 : Conduct an experimental design

• A really elegant way to test this is using a randomized controlled experiment and even better if it’s possible to blind it
• How long should we make people drink coffee? 
• How frequently should they drink coffee? 
• How are we going to measure eye color? 

Step 3: Power analysis 

• A very important variable is how many subjects will you have 
• That will depend on a number of things, including how many arms you will have in this study
• It comes down to doing something that’s called a power analysis

Step 4: IRB approval 

• If this study involves human subjects or animal subjects, you will have to get something called an Institutional Review Board to approve the ethics of the study

Step 5: Determine your primary and secondary outcomes

• Get the protocol approved, develop a plan for statistics, and then pre-register the study
• And in parallel to this, you have to have funding

*Note: there are some studies that are not experimental where some of these steps are obviously skipped

The various types of studies and how they differ [7:30]

Three main categories of studies/papers:

• 1) observational studies
• 2) experimental studies
• 3) papers that analyze/review those studies

Figure 1. The evidence-based medicine pyramid. Credit: Purdue University

• NOTE: One thing Peter doesn’t like about the pyramid above is that it puts a hierarchy in place that suggests a meta analysis better than a randomized control trial, which is not necessarily true

Individual case report

• It was about a patient who had come into the clinic with metastatic melanoma and their calcium was dangerously high
• The first assumption was that this patient had metastatic disease to their bone and that they were lysing bone and calcium was leaching into their bloodstream
• That tuned out to not be the case — instead, they had something that had not been previously reported in patients with melanoma, which was, they had developed this parathyroid hormone related like hormone in response to their melanoma
• This is a hormone that exists normally, but it doesn’t exist in this format
• So their cancer was causing them to have more of this hormone that was causing them to raise their calcium level
• It was interesting because it had never been reported before in the literature, so Peter wrote up an individual case report
• What’s the value in that? Well, the next time a patient with melanoma shows up to clinic and their calcium is sky-high and someone goes to the literature to search for it, they’ll see that report and it will hopefully save them time in getting to the diagnosis
• To start the process for a study—from idea, to design, to execution—you must have a hypothesis that begins with an observation
• In other words, an interesting observation is hypothesis generating and it might kickstart a larger trial 
• That said, with one observation/case report, you can’t make any statement about the frequency of this in the broader subset of patients or make any comment about any intervention that may or may not change the outcome of this

Case series or set of studies [11:15]

• Here you’re basically doing the same thing, but you would look at more than one patient
• So for example, looking back at one’s clinical practice and noticing that 27 patients over the last 40 years have demonstrated a very unusual finding
• For instance, one could write a paper that looks at all spontaneous regressions of cancer—this is incredibly rare, but there are certainly enough of them that one could write a case series.

Cohort studies [12:00]

• Cohort studies are larger studies and they can be retrospective or they can be prospective
• For instance, go back and look at all the people who have used saunas for the last 10 years and look at how they’re doing today relative to people who didn’t use saunas over the last 10 years
• It’s observational, no intervention, and the hope when you do this is that you’re going to see some sort of pattern
• Undoubtedly, you will see a pattern, but the real question is, will you be able to establish causality in that pattern?
• For instance, one would follow people over the next 5-10 years who use saunas and compare them to a similar number of people who don’t
• In a forward looking fashion, we’re going to be examining the other behaviors of these people and ultimately what their outcomes are— Do they have different rates of death, heart disease, cancer, Alzheimer’s disease, other metrics of health that we might be interested in?
• Again, not intervening and not an experiment per se, just observing

Experimental studies [13:30]

• This is where you take two groups of people and you give one of them a treatment and you give the other one, either a placebo or a different treatment, but you don’t randomize them (i.e., There’s a reason that they’re in that group)
• So you take all the people that come in who look a certain way (fever, white blood cell count, etc.) and you’re going to give them the antibiotic
• And the people who come in but they don’t have those exact signs or symptoms, you do NOT give an antibiotic and you’re just going to follow them
• In summary, there are enormous limitation to non-randomized trials because presumably there’s a reason you’re making that decision. And that reason will undoubtedly introduce bias
• “Blinding” is another important aspect that Peter will discuss later in the podcast

Meta-analysis [16:15]

• This is a statistical technique where you can combine data from multiple studies that are attempting to look at the same question 
• Each study gets a relative weighting and the weighting of a study is a function of its precision (sample size, other events in the study)
• For instance, larger studies, which have smaller standard errors are given more weight than smaller studies with larger standard errors, for example.
• You’ll know you’re looking at a meta analysis because usually there will be a figure somewhere in there that will show across rows all of the studies.
• Let’s say there’s 10 studies included in the meta-analysis, and then they’ll have the hazard ratios for each of the studies
• They’ll represent them usually as little triangles, the triangle will represent the 95% confidence interval of what the hazard ratio is (basically a marker of the risk)
• You’ll see all 10 studies and then they’ll show you the final summation of them at the bottom, which of course you wouldn’t be able to deduce looking at the figure, but it takes into account that mathematical waiting

The truth about meta-analyses

• On the surface, meta-analyses seem really, really great because if one trial, one randomized trial is good, 10 must be better
• But as James Yang once once said during a journal club about a meta analysis that was being presented, he said something to the effect of, “ 1000 sows ears makes not a pearl necklace ” — just an eloquent way to say that garbage in garbage out.
• If you do a meta-analysis of a bunch of garbage studies, you get a garbage meta-analysis
• So a meta-analysis of great randomized control trials will produce a great meta-analysis.

The different phases of a clinical trial [19:15]

• When talking about human clinical trials, the different “phases” is the phraseology is used by the FDA here in the United States

Origins of this process…

• Say you have an interesting idea—e.g.., a color cancer drug or molecule that you think will have some benefit
• Say you’ve done some interesting experiments in animals, maybe started with some mice and you went up to some rats and maybe even you’ve done something in primates
• Now you’re really committed to this as the success of this and it’s both safe and efficacious in animals
• You now decide you want to foray into the human space
• Step 1 is you have to file for something called an IND, an Investigational New Drug application that basically sets your intention of testing this as a drug in humans
• If you can the IND, you go to phase 1

Figure 2. Different phases of a trial.

• Phase I is geared specifically to dose escalate this drug from a very, very low level to determine what the toxicity is across a range of doses that will hopefully have efficacy
• Very small studies, usually less than 100 people typically done in cohorts
• E.g., the first 12 people are going to be at 0.1 mg/kg, and assuming we see no adverse effects there, we’ll go up to 0.15 mg/kg per kilogram for the next 12 people. If we have no issues there, we’ll escalate it to 0.25 and so on
• Notice there is nothing in there about whether the drug works or not
• They have progressed through all other standard treatments without much luck
• If the drug gets through phase I safely, then it goes to phase II
• The goal of phase II is to continue to evaluate for safety, but also to start to look for efficacy
• This is done in an open label fashion—they’re not randomizing patients to one drug versus the other typically
• Usually it’s at point where the investigators now we think that one or two doses are going to produce efficacy
• The dose levels were deemed safe in the phase I, so now we’re now going to take patients and give them this drug and look for an effect
• A lot of times, if there’s no control arm in this study, you’re going to compare the drug to the natural history
• For instance, let’s assume that we know that patients with metastatic colon cancer on standard of care, have a medium survival of X months
• Now we’re going to give these patients this drug and see if that extends it anymore
• Typically these are very small studies — Can be in the 20-50 range, maybe up to a few hundred people
• There are lots of things that can introduce bias to a phase II if it does not have randomization
• The goal would be to still randomize in phase II, because you really do want to tease out efficacy
• So if a compound succeeds in phase II, which means it continues to show no significant adverse safety effects — note, no adverse events doesn’t mean no side effects…it’s just that it doesn’t have side effects that are deemed unacceptable for the risk profile of the patient
• So if it shows efficacy without adverse events, you then proceed to phase III
• Phase III is a really rigorous trial
• It’s typically a log step up in the number of patients to thousands of patients
• This is absolutely either a placebo-controlled trial or it can be standard of care versus standard of care plus this new agent
• It will be randomized and whenever possible, it is blinded
• And these are typically longer studies
• And because you have so much more sample size, you’re going to potentially pick up side effects that weren’t there in the first place
• Now you really have that gold standard for measuring efficacy
• And it’s on the basis of the phase I, phase II and mostly phase III data that a drug will get approved or not approved for broad use, which leads to a fourth phase
• This is a post marketing study
• Phase IV studies take place after the drug has been approved, and they’re used to basically get additional information because once a drug is approved, you now have more people taking it
• And they may also be using this to look at other indications for the drug
• It was a trial that used semaglutide to look at obesity versus its original phase III trials, which we’re looking at diabetes
• Semaglutide is a drug that’s already been approved — the trial is basically expanding the indication for semaglutide, in this case so that insurance companies would actually pay for it for a new indication
• In phase 4, you’re also looking for whether there is another side effect that was missed in the phase 3 trial

Observational studies and the potential for bias [26:30]

Are there things you look for in an observational study that increase or decrease your confidence in it?

{end of show notes preview}

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Fantastic episode….

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All my best,

Peter/ Bob- This would be a really valuable episode for my undergrad students to hear. Any means by which this could be unlocked for educational settings? Undergrads won’t buy subscriptions; they resist buying books. Rob Niewoehner

Very helpful! I’m an MS2 getting ready for STEP1 and this episode was actually a fantastic review for biostats. You all are always the best educators and I appreciate all the work you guys put into these shows.

Peter and Bob,

First of all, thank you for the nuancing this information in an easy to understand fashion. This was probably more valuable than my whole statistics for health practitioners course in grad school (we have a long ways to go on this front). I was hoping to find in the show notes the reference to the podcast which Peter refers to at around the 30:37 mark on “covering some of the most cutting edge tools of neuroscience”. Assistance on which podcast(s) he was referring to would be much appreciated.

That episode will be out in Q1 2022.

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April 5, 2024

How Ancient Humans Studied—And Predicted—Solar Eclipses

Dragon bones, mysterious carvings and simple math reveal ancient eclipses

By Leo DeLuca

An annular solar eclipse as seen over the Pueblo Bonito at Chaco Culture National Historical Park.

Stan Honda/AFP/GettyImages

This article is part of a special report on the total solar eclipse that will be visible from parts of the U.S., Mexico and Canada on April 8, 2024.

During an eclipse , as the moon slowly begins to veil the sun, crescent-shaped shadows appear on the ground, and the world drops into an eerie daytime twilight. On Monday , this will happen across a large swath of North America.

How did ancient cultures respond to the darkness shrouding the light? In the past few decades, a scientific field called archeoastronomy has emerged to investigate questions such as this. Although it’s a challenge to know what earlier humans saw when they stood in the shadow of an eclipse—especially the further back we go—archeoastronomers have used clues ranging from bark books to petroglyphs to ancient Chinese oracle bones to piece together these bygone stories of the cosmos.

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The “Six-Five Beat”

Humans have been calculating the recurrence of solar eclipses for thousands of years. Many ancient cultures predicted these events mathematically using what Anthony Aveni, a pioneer of archeoastronomy and professor emeritus at Colgate University, calls the “six-five beat.” Solar and lunar eclipses usually recur every six lunar months or, more rarely, every five lunar months. Over time, by observing and calculating these intervals, the ancient Maya, Chinese and Babylonians all homed in on two predictable patterns for when identical solar and lunar eclipses would recur: one pattern spans 41 months, the other 47. Here’s how these patterns, denoted as “A” and “B”, come about:

A. The 41-month pattern: 6 + 6 + 6 + 6 + 6 + 6 + 5 = 41 months , or some 3.4 years, after a total or near-total eclipse, an almost identical eclipse occurs.

B. The 47-month pattern: 6 + 6 + 6 + 6 + 6 + 6 + 6 + 5 = 47 months , or some 3.9 years, after a total or near-total eclipse, an almost identical eclipse occurs.

Then, after more time, these cultures found even more patterns. The Babylonians, for instance, noticed that after A + A + B + B + B, or 223 months (18.5 years), another identical sequence of eclipses occurred, called the Saros cycle. All these patterns, governed by the laws of planetary motion, were made by simply observing the sky with the naked eye—so it’s possible, or even likely, that these Maya, Chinese and Babylonian cultures had been using the six-five beat to predict eclipses even in prehistoric times, before written records. “I have no doubt that people could do this a few thousand years [prior] and then pass that information on orally,” Aveni says.

Cairn Carvings

The oldest surviving depiction of an eclipse might be one from Loughcrew Megalithic Cemetery , also known as the Hills of the Witch, near Oldcastle, Ireland. This site’s Neolithic passage tombs, marked by large cairns, were built in the fourth millennium B.C.E.—making them nearly a millennium older than Stonehenge.

Examining one of the cairns in 1999, archaeoastronomer Paul Griffin discovered a stone carving of overlapping concentric circles that he thought may depict an eclipse. He found that a near-total eclipse occurred at Loughcrew on November 30, 3340 B.C.E., around the time the cairns were built; this makes it plausible that the carving, called a petroglyph, did indeed represent an eclipse. But such a thing can’t be proven, and Aveni says the concentric circles could have any number of possible meanings.

Dragon Bones and Oracle Bones

A few millennia later, the oldest verifiable solar eclipse records were carved in Anyang, China. This city, then called Yin, was the capital of the ancient Shang dynasty (1600–1045 B.C.E.)—the first Chinese period that left behind written records. This legacy was rediscovered relatively recently, in 1899, when an Anyang pharmacist gave antiquarian and philologist Wang Yirong a prescription for a traditional remedy made by grinding up “dragon bones.” Wang was about to grind the bones when he noticed that they were adorned with ancient Chinese inscriptions. These weren’t dragon bones but oracle bones : oxen shoulder blades and tortoise shells once used to predict the future. Eventually the artifacts were traced to a site near Anyang where some 50,000 inscribed oracle bones dating from 1400 to 1200 B.C.E. have since been discovered.

“Divination played an enormously important role at the time,” says Xueshun Liu , a Chinese language lecturer in the Department of Asian Studies at the University of British Columbia. These bone inscriptions are the oldest known Chinese-language documents—and they include descriptions of eclipses. During the Shang dynasty, when an eclipse loomed, specially marked oracle bones were placed over a fire; heating caused small cracks that were believed to be messages from deceased ancestors. A diviner, or oracle, then interpreted the cracks and inscribed prophecies on the bones.

One of the many oracle bones that mentions an eclipse says: “The king, reading the crack, said: ‘There will be harm.’ Another simply read, “The sun has been eaten.”

A Dark, Belching Sun

Any given place on Earth’s surface will only experience one total solar eclipse, lasting only a few minutes, every 375 years on average. So it’s even rarer for this to coincide with another solar event called a coronal mass ejection, or CME. These occur when giant bubbles of plasma and magnetic field burst from the sun’s corona, or its outer atmosphere. These ejections could be visible to the naked eye during a total solar eclipse, with the moon shielding everything but the sun’s corona.

“CMEs are not that rare. We get several of them during the day, especially during solar maximum,” or the peak of the sun’s 11-year activity cycle, says C. Alex Young , associate director for science in the Heliophysics Science Division at NASA’s Goddard Space Flight Center. But he notes that the odds of one coinciding with “four or so minutes of an eclipse are slim.”

It’s possible, however, that the ancient Pueblo people of Chaco Canyon, a city that thrived from C.E. 850–1250, may have witnessed such a spectacle. Evidence comes from Piedra del Sol, or “Rock of the Sun,” a large boulder in modern-day New Mexico inscribed with numerous previously identified Chaco astronomical markers. In 1992 solar astronomer Kim Malville was helping lead a three-week field trip for college students when he “noticed a peculiar petroglyph” on the boulder. It looked like the sun was belching out rays. What’s more, “there was a pecked mark where [Venus] would have been,” says Malville, a professor emeritus of astrophysical and planetary sciences at the University of Colorado. Venus can be visible during an eclipse.

After referencing a list of historic eclipses, Malville discovered that only one total solar eclipse—that of June 29, 1097 —occurred at the peak of Chacoan culture. A few years later, solar physicists confirmed that the 1097 eclipse occurred during a period of high solar activity, making the tandem appearance of an eclipse and a CME likelier.

Credit: Katie Peek; Source: NASA ( eclipse track data )

This year on April 8, eclipse watchers in North America will have similarly elevated chances of seeing a CME because the sun is currently at the peak of its activity—and is belching out plasma multiple times per day. “While the chances of seeing a coronal mass ejection coincide with an eclipse are rare, the chances are much higher right now,” Young says. “I’ve studied these things for 20 years, and the idea of seeing this from the ground, with my own eyes—well, that would really be quite a sight.”

Look Outside the Lens

As we try to understand how the peoples of the past experienced the world, it’s important to look around the lens of our modern and often Western-dominated culture, says Aveni, who began his career as an astronomer and then moved to studying the cosmos through anthropology and Native American studies.

“We must be very careful about treating all cultures that came before us as capital-O ‘Other,’” Aveni says. “They traveled a totally different road from Western eclipse science. Sometimes our questions can be misguided. Did they know the Earth was round? Did they know about the galaxy?” Those aren’t the right questions to ask, he says. “They didn’t live in our world.”

And we don’t live in theirs. With our ultraprecise clocks and compasses, we can often choose to forget the sky altogether—something unthinkable for many peoples of the past. “When it comes down to it, other cultures didn’t do things the way we do them,” Aveni says. “And that’s what makes studying them so fascinating.”

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Healthy Living with Diabetes

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How can I plan what to eat or drink when I have diabetes?

How can physical activity help manage my diabetes, what can i do to reach or maintain a healthy weight, should i quit smoking, how can i take care of my mental health, clinical trials for healthy living with diabetes.

Healthy living is a way to manage diabetes . To have a healthy lifestyle, take steps now to plan healthy meals and snacks, do physical activities, get enough sleep, and quit smoking or using tobacco products.

Healthy living may help keep your body’s blood pressure , cholesterol , and blood glucose level, also called blood sugar level, in the range your primary health care professional recommends. Your primary health care professional may be a doctor, a physician assistant, or a nurse practitioner. Healthy living may also help prevent or delay health problems  from diabetes that can affect your heart, kidneys, eyes, brain, and other parts of your body.

Making lifestyle changes can be hard, but starting with small changes and building from there may benefit your health. You may want to get help from family, loved ones, friends, and other trusted people in your community. You can also get information from your health care professionals.

What you choose to eat, how much you eat, and when you eat are parts of a meal plan. Having healthy foods and drinks can help keep your blood glucose, blood pressure, and cholesterol levels in the ranges your health care professional recommends. If you have overweight or obesity, a healthy meal plan—along with regular physical activity, getting enough sleep, and other healthy behaviors—may help you reach and maintain a healthy weight. In some cases, health care professionals may also recommend diabetes medicines that may help you lose weight, or weight-loss surgery, also called metabolic and bariatric surgery.

Choose healthy foods and drinks

There is no right or wrong way to choose healthy foods and drinks that may help manage your diabetes. Healthy meal plans for people who have diabetes may include

• dairy or plant-based dairy products
• nonstarchy vegetables
• protein foods
• whole grains

Try to choose foods that include nutrients such as vitamins, calcium , fiber , and healthy fats . Also try to choose drinks with little or no added sugar , such as tap or bottled water, low-fat or non-fat milk, and unsweetened tea, coffee, or sparkling water.

Try to plan meals and snacks that have fewer

• foods high in saturated fat
• foods high in sodium, a mineral found in salt
• sugary foods , such as cookies and cakes, and sweet drinks, such as soda, juice, flavored coffee, and sports drinks

Your body turns carbohydrates , or carbs, from food into glucose, which can raise your blood glucose level. Some fruits, beans, and starchy vegetables—such as potatoes and corn—have more carbs than other foods. Keep carbs in mind when planning your meals.

You should also limit how much alcohol you drink. If you take insulin  or certain diabetes medicines , drinking alcohol can make your blood glucose level drop too low, which is called hypoglycemia . If you do drink alcohol, be sure to eat food when you drink and remember to check your blood glucose level after drinking. Talk with your health care team about your alcohol-drinking habits.

Find the best times to eat or drink

Talk with your health care professional or health care team about when you should eat or drink. The best time to have meals and snacks may depend on

• what medicines you take for diabetes
• what your level of physical activity or your work schedule is
• whether you have other health conditions or diseases

Ask your health care team if you should eat before, during, or after physical activity. Some diabetes medicines, such as sulfonylureas  or insulin, may make your blood glucose level drop too low during exercise or if you skip or delay a meal.

Plan how much to eat or drink

You may worry that having diabetes means giving up foods and drinks you enjoy. The good news is you can still have your favorite foods and drinks, but you might need to have them in smaller portions  or enjoy them less often.

For people who have diabetes, carb counting and the plate method are two common ways to plan how much to eat or drink. Talk with your health care professional or health care team to find a method that works for you.

Carb counting

Carbohydrate counting , or carb counting, means planning and keeping track of the amount of carbs you eat and drink in each meal or snack. Not all people with diabetes need to count carbs. However, if you take insulin, counting carbs can help you know how much insulin to take.

Plate method

The plate method helps you control portion sizes  without counting and measuring. This method divides a 9-inch plate into the following three sections to help you choose the types and amounts of foods to eat for each meal.

• Nonstarchy vegetables—such as leafy greens, peppers, carrots, or green beans—should make up half of your plate.
• Carb foods that are high in fiber—such as brown rice, whole grains, beans, or fruits—should make up one-quarter of your plate.
• Protein foods—such as lean meats, fish, dairy, or tofu or other soy products—should make up one quarter of your plate.

If you are not taking insulin, you may not need to count carbs when using the plate method.

Work with your health care team to create a meal plan that works for you. You may want to have a diabetes educator  or a registered dietitian  on your team. A registered dietitian can provide medical nutrition therapy , which includes counseling to help you create and follow a meal plan. Your health care team may be able to recommend other resources, such as a healthy lifestyle coach, to help you with making changes. Ask your health care team or your insurance company if your benefits include medical nutrition therapy or other diabetes care resources.

Talk with your health care professional before taking dietary supplements

There is no clear proof that specific foods, herbs, spices, or dietary supplements —such as vitamins or minerals—can help manage diabetes. Your health care professional may ask you to take vitamins or minerals if you can’t get enough from foods. Talk with your health care professional before you take any supplements, because some may cause side effects or affect how well your diabetes medicines work.

Research shows that regular physical activity helps people manage their diabetes and stay healthy. Benefits of physical activity may include

• lower blood glucose, blood pressure, and cholesterol levels
• better heart health
• healthier weight
• better mood and sleep
• better balance and memory

Talk with your health care professional before starting a new physical activity or changing how much physical activity you do. They may suggest types of activities based on your ability, schedule, meal plan, interests, and diabetes medicines. Your health care professional may also tell you the best times of day to be active or what to do if your blood glucose level goes out of the range recommended for you.

Do different types of physical activity

People with diabetes can be active, even if they take insulin or use technology such as insulin pumps .

Try to do different kinds of activities . While being more active may have more health benefits, any physical activity is better than none. Start slowly with activities you enjoy. You may be able to change your level of effort and try other activities over time. Having a friend or family member join you may help you stick to your routine.

The physical activities you do may need to be different if you are age 65 or older , are pregnant , or have a disability or health condition . Physical activities may also need to be different for children and teens . Ask your health care professional or health care team about activities that are safe for you.

Aerobic activities

Aerobic activities make you breathe harder and make your heart beat faster. You can try walking, dancing, wheelchair rolling, or swimming. Most adults should try to get at least 150 minutes of moderate-intensity physical activity each week. Aim to do 30 minutes a day on most days of the week. You don’t have to do all 30 minutes at one time. You can break up physical activity into small amounts during your day and still get the benefit. 1

Strength training or resistance training

Strength training or resistance training may make your muscles and bones stronger. You can try lifting weights or doing other exercises such as wall pushups or arm raises. Try to do this kind of training two times a week. 1

Balance and stretching activities

Balance and stretching activities may help you move better and have stronger muscles and bones. You may want to try standing on one leg or stretching your legs when sitting on the floor. Try to do these kinds of activities two or three times a week. 1

Some activities that need balance may be unsafe for people with nerve damage or vision problems caused by diabetes. Ask your health care professional or health care team about activities that are safe for you.

Stay safe during physical activity

Staying safe during physical activity is important. Here are some tips to keep in mind.

Drink liquids

Drinking liquids helps prevent dehydration , or the loss of too much water in your body. Drinking water is a way to stay hydrated. Sports drinks often have a lot of sugar and calories , and you don’t need them for most moderate physical activities.

Avoid low blood glucose

Check your blood glucose level before, during, and right after physical activity. Physical activity often lowers the level of glucose in your blood. Low blood glucose levels may last for hours or days after physical activity. You are most likely to have low blood glucose if you take insulin or some other diabetes medicines, such as sulfonylureas.

Ask your health care professional if you should take less insulin or eat carbs before, during, or after physical activity. Low blood glucose can be a serious medical emergency that must be treated right away. Take steps to protect yourself. You can learn how to treat low blood glucose , let other people know what to do if you need help, and use a medical alert bracelet.

Avoid high blood glucose and ketoacidosis

Taking less insulin before physical activity may help prevent low blood glucose, but it may also make you more likely to have high blood glucose. If your body does not have enough insulin, it can’t use glucose as a source of energy and will use fat instead. When your body uses fat for energy, your body makes chemicals called ketones .

High levels of ketones in your blood can lead to a condition called diabetic ketoacidosis (DKA) . DKA is a medical emergency that should be treated right away. DKA is most common in people with type 1 diabetes . Occasionally, DKA may affect people with type 2 diabetes  who have lost their ability to produce insulin. Ask your health care professional how much insulin you should take before physical activity, whether you need to test your urine for ketones, and what level of ketones is dangerous for you.

Take care of your feet

People with diabetes may have problems with their feet because high blood glucose levels can damage blood vessels and nerves. To help prevent foot problems, wear comfortable and supportive shoes and take care of your feet  before, during, and after physical activity.

If you have diabetes, managing your weight  may bring you several health benefits. Ask your health care professional or health care team if you are at a healthy weight  or if you should try to lose weight.

If you are an adult with overweight or obesity, work with your health care team to create a weight-loss plan. Losing 5% to 7% of your current weight may help you prevent or improve some health problems  and manage your blood glucose, cholesterol, and blood pressure levels. 2 If you are worried about your child’s weight  and they have diabetes, talk with their health care professional before your child starts a new weight-loss plan.

You may be able to reach and maintain a healthy weight by

• following a healthy meal plan
• consuming fewer calories
• being physically active
• getting 7 to 8 hours of sleep each night 3

If you have type 2 diabetes, your health care professional may recommend diabetes medicines that may help you lose weight.

Online tools such as the Body Weight Planner  may help you create eating and physical activity plans. You may want to talk with your health care professional about other options for managing your weight, including joining a weight-loss program  that can provide helpful information, support, and behavioral or lifestyle counseling. These options may have a cost, so make sure to check the details of the programs.

Your health care professional may recommend weight-loss surgery  if you aren’t able to reach a healthy weight with meal planning, physical activity, and taking diabetes medicines that help with weight loss.

If you are pregnant , trying to lose weight may not be healthy. However, you should ask your health care professional whether it makes sense to monitor or limit your weight gain during pregnancy.

Both diabetes and smoking —including using tobacco products and e-cigarettes—cause your blood vessels to narrow. Both diabetes and smoking increase your risk of having a heart attack or stroke , nerve damage , kidney disease , eye disease , or amputation . Secondhand smoke can also affect the health of your family or others who live with you.

If you smoke or use other tobacco products, stop. Ask for help . You don’t have to do it alone.

Feeling stressed, sad, or angry can be common for people with diabetes. Managing diabetes or learning to cope with new information about your health can be hard. People with chronic illnesses such as diabetes may develop anxiety or other mental health conditions .

Learn healthy ways to lower your stress , and ask for help from your health care team or a mental health professional. While it may be uncomfortable to talk about your feelings, finding a health care professional whom you trust and want to talk with may help you

• lower your feelings of stress, depression, or anxiety
• manage problems sleeping or remembering things
• see how diabetes affects your family, school, work, or financial situation

Ask your health care team for mental health resources for people with diabetes.

Sleeping too much or too little may raise your blood glucose levels. Your sleep habits may also affect your mental health and vice versa. People with diabetes and overweight or obesity can also have other health conditions that affect sleep, such as sleep apnea , which can raise your blood pressure and risk of heart disease.

NIDDK conducts and supports clinical trials in many diseases and conditions, including diabetes. The trials look to find new ways to prevent, detect, or treat disease and improve quality of life.

What are clinical trials for healthy living with diabetes?

Clinical trials—and other types of clinical studies —are part of medical research and involve people like you. When you volunteer to take part in a clinical study, you help health care professionals and researchers learn more about disease and improve health care for people in the future.

Researchers are studying many aspects of healthy living for people with diabetes, such as

• how changing when you eat may affect body weight and metabolism
• how less access to healthy foods may affect diabetes management, other health problems, and risk of dying
• whether low-carbohydrate meal plans can help lower blood glucose levels
• which diabetes medicines are more likely to help people lose weight

Find out if clinical trials are right for you .

Watch a video of NIDDK Director Dr. Griffin P. Rodgers explaining the importance of participating in clinical trials.

What clinical trials for healthy living with diabetes are looking for participants?

You can view a filtered list of clinical studies on healthy living with diabetes that are federally funded, open, and recruiting at www.ClinicalTrials.gov . You can expand or narrow the list to include clinical studies from industry, universities, and individuals; however, the National Institutes of Health does not review these studies and cannot ensure they are safe for you. Always talk with your primary health care professional before you participate in a clinical study.

This content is provided as a service of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), part of the National Institutes of Health. NIDDK translates and disseminates research findings to increase knowledge and understanding about health and disease among patients, health professionals, and the public. Content produced by NIDDK is carefully reviewed by NIDDK scientists and other experts.

NIDDK would like to thank: Elizabeth M. Venditti, Ph.D., University of Pittsburgh School of Medicine.