specify features of good research work

Criteria for Good Qualitative Research: A Comprehensive Review

• Regular Article
• Open access
• Published: 18 September 2021
• Volume 31 , pages 679–689, ( 2022 )

Cite this article

You have full access to this open access article

• Drishti Yadav   ORCID: orcid.org/0000-0002-2974-0323 1  

89k Accesses

35 Citations

72 Altmetric

Explore all metrics

This review aims to synthesize a published set of evaluative criteria for good qualitative research. The aim is to shed light on existing standards for assessing the rigor of qualitative research encompassing a range of epistemological and ontological standpoints. Using a systematic search strategy, published journal articles that deliberate criteria for rigorous research were identified. Then, references of relevant articles were surveyed to find noteworthy, distinct, and well-defined pointers to good qualitative research. This review presents an investigative assessment of the pivotal features in qualitative research that can permit the readers to pass judgment on its quality and to condemn it as good research when objectively and adequately utilized. Overall, this review underlines the crux of qualitative research and accentuates the necessity to evaluate such research by the very tenets of its being. It also offers some prospects and recommendations to improve the quality of qualitative research. Based on the findings of this review, it is concluded that quality criteria are the aftereffect of socio-institutional procedures and existing paradigmatic conducts. Owing to the paradigmatic diversity of qualitative research, a single and specific set of quality criteria is neither feasible nor anticipated. Since qualitative research is not a cohesive discipline, researchers need to educate and familiarize themselves with applicable norms and decisive factors to evaluate qualitative research from within its theoretical and methodological framework of origin.

Similar content being viewed by others

What is Qualitative in Qualitative Research

Systematic review or scoping review guidance for authors when choosing between a systematic or scoping review approach.

How to use and assess qualitative research methods

Avoid common mistakes on your manuscript.

Introduction

“… It is important to regularly dialogue about what makes for good qualitative research” (Tracy, 2010 , p. 837)

To decide what represents good qualitative research is highly debatable. There are numerous methods that are contained within qualitative research and that are established on diverse philosophical perspectives. Bryman et al., ( 2008 , p. 262) suggest that “It is widely assumed that whereas quality criteria for quantitative research are well‐known and widely agreed, this is not the case for qualitative research.” Hence, the question “how to evaluate the quality of qualitative research” has been continuously debated. There are many areas of science and technology wherein these debates on the assessment of qualitative research have taken place. Examples include various areas of psychology: general psychology (Madill et al., 2000 ); counseling psychology (Morrow, 2005 ); and clinical psychology (Barker & Pistrang, 2005 ), and other disciplines of social sciences: social policy (Bryman et al., 2008 ); health research (Sparkes, 2001 ); business and management research (Johnson et al., 2006 ); information systems (Klein & Myers, 1999 ); and environmental studies (Reid & Gough, 2000 ). In the literature, these debates are enthused by the impression that the blanket application of criteria for good qualitative research developed around the positivist paradigm is improper. Such debates are based on the wide range of philosophical backgrounds within which qualitative research is conducted (e.g., Sandberg, 2000 ; Schwandt, 1996 ). The existence of methodological diversity led to the formulation of different sets of criteria applicable to qualitative research.

Among qualitative researchers, the dilemma of governing the measures to assess the quality of research is not a new phenomenon, especially when the virtuous triad of objectivity, reliability, and validity (Spencer et al., 2004 ) are not adequate. Occasionally, the criteria of quantitative research are used to evaluate qualitative research (Cohen & Crabtree, 2008 ; Lather, 2004 ). Indeed, Howe ( 2004 ) claims that the prevailing paradigm in educational research is scientifically based experimental research. Hypotheses and conjectures about the preeminence of quantitative research can weaken the worth and usefulness of qualitative research by neglecting the prominence of harmonizing match for purpose on research paradigm, the epistemological stance of the researcher, and the choice of methodology. Researchers have been reprimanded concerning this in “paradigmatic controversies, contradictions, and emerging confluences” (Lincoln & Guba, 2000 ).

In general, qualitative research tends to come from a very different paradigmatic stance and intrinsically demands distinctive and out-of-the-ordinary criteria for evaluating good research and varieties of research contributions that can be made. This review attempts to present a series of evaluative criteria for qualitative researchers, arguing that their choice of criteria needs to be compatible with the unique nature of the research in question (its methodology, aims, and assumptions). This review aims to assist researchers in identifying some of the indispensable features or markers of high-quality qualitative research. In a nutshell, the purpose of this systematic literature review is to analyze the existing knowledge on high-quality qualitative research and to verify the existence of research studies dealing with the critical assessment of qualitative research based on the concept of diverse paradigmatic stances. Contrary to the existing reviews, this review also suggests some critical directions to follow to improve the quality of qualitative research in different epistemological and ontological perspectives. This review is also intended to provide guidelines for the acceleration of future developments and dialogues among qualitative researchers in the context of assessing the qualitative research.

The rest of this review article is structured in the following fashion: Sect.  Methods describes the method followed for performing this review. Section Criteria for Evaluating Qualitative Studies provides a comprehensive description of the criteria for evaluating qualitative studies. This section is followed by a summary of the strategies to improve the quality of qualitative research in Sect.  Improving Quality: Strategies . Section  How to Assess the Quality of the Research Findings? provides details on how to assess the quality of the research findings. After that, some of the quality checklists (as tools to evaluate quality) are discussed in Sect.  Quality Checklists: Tools for Assessing the Quality . At last, the review ends with the concluding remarks presented in Sect.  Conclusions, Future Directions and Outlook . Some prospects in qualitative research for enhancing its quality and usefulness in the social and techno-scientific research community are also presented in Sect.  Conclusions, Future Directions and Outlook .

For this review, a comprehensive literature search was performed from many databases using generic search terms such as Qualitative Research , Criteria , etc . The following databases were chosen for the literature search based on the high number of results: IEEE Explore, ScienceDirect, PubMed, Google Scholar, and Web of Science. The following keywords (and their combinations using Boolean connectives OR/AND) were adopted for the literature search: qualitative research, criteria, quality, assessment, and validity. The synonyms for these keywords were collected and arranged in a logical structure (see Table 1 ). All publications in journals and conference proceedings later than 1950 till 2021 were considered for the search. Other articles extracted from the references of the papers identified in the electronic search were also included. A large number of publications on qualitative research were retrieved during the initial screening. Hence, to include the searches with the main focus on criteria for good qualitative research, an inclusion criterion was utilized in the search string.

From the selected databases, the search retrieved a total of 765 publications. Then, the duplicate records were removed. After that, based on the title and abstract, the remaining 426 publications were screened for their relevance by using the following inclusion and exclusion criteria (see Table 2 ). Publications focusing on evaluation criteria for good qualitative research were included, whereas those works which delivered theoretical concepts on qualitative research were excluded. Based on the screening and eligibility, 45 research articles were identified that offered explicit criteria for evaluating the quality of qualitative research and were found to be relevant to this review.

Figure  1 illustrates the complete review process in the form of PRISMA flow diagram. PRISMA, i.e., “preferred reporting items for systematic reviews and meta-analyses” is employed in systematic reviews to refine the quality of reporting.

PRISMA flow diagram illustrating the search and inclusion process. N represents the number of records

Criteria for Evaluating Qualitative Studies

Fundamental criteria: general research quality.

Various researchers have put forward criteria for evaluating qualitative research, which have been summarized in Table 3 . Also, the criteria outlined in Table 4 effectively deliver the various approaches to evaluate and assess the quality of qualitative work. The entries in Table 4 are based on Tracy’s “Eight big‐tent criteria for excellent qualitative research” (Tracy, 2010 ). Tracy argues that high-quality qualitative work should formulate criteria focusing on the worthiness, relevance, timeliness, significance, morality, and practicality of the research topic, and the ethical stance of the research itself. Researchers have also suggested a series of questions as guiding principles to assess the quality of a qualitative study (Mays & Pope, 2020 ). Nassaji ( 2020 ) argues that good qualitative research should be robust, well informed, and thoroughly documented.

Qualitative Research: Interpretive Paradigms

All qualitative researchers follow highly abstract principles which bring together beliefs about ontology, epistemology, and methodology. These beliefs govern how the researcher perceives and acts. The net, which encompasses the researcher’s epistemological, ontological, and methodological premises, is referred to as a paradigm, or an interpretive structure, a “Basic set of beliefs that guides action” (Guba, 1990 ). Four major interpretive paradigms structure the qualitative research: positivist and postpositivist, constructivist interpretive, critical (Marxist, emancipatory), and feminist poststructural. The complexity of these four abstract paradigms increases at the level of concrete, specific interpretive communities. Table 5 presents these paradigms and their assumptions, including their criteria for evaluating research, and the typical form that an interpretive or theoretical statement assumes in each paradigm. Moreover, for evaluating qualitative research, quantitative conceptualizations of reliability and validity are proven to be incompatible (Horsburgh, 2003 ). In addition, a series of questions have been put forward in the literature to assist a reviewer (who is proficient in qualitative methods) for meticulous assessment and endorsement of qualitative research (Morse, 2003 ). Hammersley ( 2007 ) also suggests that guiding principles for qualitative research are advantageous, but methodological pluralism should not be simply acknowledged for all qualitative approaches. Seale ( 1999 ) also points out the significance of methodological cognizance in research studies.

Table 5 reflects that criteria for assessing the quality of qualitative research are the aftermath of socio-institutional practices and existing paradigmatic standpoints. Owing to the paradigmatic diversity of qualitative research, a single set of quality criteria is neither possible nor desirable. Hence, the researchers must be reflexive about the criteria they use in the various roles they play within their research community.

Improving Quality: Strategies

Another critical question is “How can the qualitative researchers ensure that the abovementioned quality criteria can be met?” Lincoln and Guba ( 1986 ) delineated several strategies to intensify each criteria of trustworthiness. Other researchers (Merriam & Tisdell, 2016 ; Shenton, 2004 ) also presented such strategies. A brief description of these strategies is shown in Table 6 .

It is worth mentioning that generalizability is also an integral part of qualitative research (Hays & McKibben, 2021 ). In general, the guiding principle pertaining to generalizability speaks about inducing and comprehending knowledge to synthesize interpretive components of an underlying context. Table 7 summarizes the main metasynthesis steps required to ascertain generalizability in qualitative research.

Figure  2 reflects the crucial components of a conceptual framework and their contribution to decisions regarding research design, implementation, and applications of results to future thinking, study, and practice (Johnson et al., 2020 ). The synergy and interrelationship of these components signifies their role to different stances of a qualitative research study.

Essential elements of a conceptual framework

In a nutshell, to assess the rationale of a study, its conceptual framework and research question(s), quality criteria must take account of the following: lucid context for the problem statement in the introduction; well-articulated research problems and questions; precise conceptual framework; distinct research purpose; and clear presentation and investigation of the paradigms. These criteria would expedite the quality of qualitative research.

How to Assess the Quality of the Research Findings?

The inclusion of quotes or similar research data enhances the confirmability in the write-up of the findings. The use of expressions (for instance, “80% of all respondents agreed that” or “only one of the interviewees mentioned that”) may also quantify qualitative findings (Stenfors et al., 2020 ). On the other hand, the persuasive reason for “why this may not help in intensifying the research” has also been provided (Monrouxe & Rees, 2020 ). Further, the Discussion and Conclusion sections of an article also prove robust markers of high-quality qualitative research, as elucidated in Table 8 .

Quality Checklists: Tools for Assessing the Quality

Numerous checklists are available to speed up the assessment of the quality of qualitative research. However, if used uncritically and recklessly concerning the research context, these checklists may be counterproductive. I recommend that such lists and guiding principles may assist in pinpointing the markers of high-quality qualitative research. However, considering enormous variations in the authors’ theoretical and philosophical contexts, I would emphasize that high dependability on such checklists may say little about whether the findings can be applied in your setting. A combination of such checklists might be appropriate for novice researchers. Some of these checklists are listed below:

The most commonly used framework is Consolidated Criteria for Reporting Qualitative Research (COREQ) (Tong et al., 2007 ). This framework is recommended by some journals to be followed by the authors during article submission.

Standards for Reporting Qualitative Research (SRQR) is another checklist that has been created particularly for medical education (O’Brien et al., 2014 ).

Also, Tracy ( 2010 ) and Critical Appraisal Skills Programme (CASP, 2021 ) offer criteria for qualitative research relevant across methods and approaches.

Further, researchers have also outlined different criteria as hallmarks of high-quality qualitative research. For instance, the “Road Trip Checklist” (Epp & Otnes, 2021 ) provides a quick reference to specific questions to address different elements of high-quality qualitative research.

Conclusions, Future Directions, and Outlook

This work presents a broad review of the criteria for good qualitative research. In addition, this article presents an exploratory analysis of the essential elements in qualitative research that can enable the readers of qualitative work to judge it as good research when objectively and adequately utilized. In this review, some of the essential markers that indicate high-quality qualitative research have been highlighted. I scope them narrowly to achieve rigor in qualitative research and note that they do not completely cover the broader considerations necessary for high-quality research. This review points out that a universal and versatile one-size-fits-all guideline for evaluating the quality of qualitative research does not exist. In other words, this review also emphasizes the non-existence of a set of common guidelines among qualitative researchers. In unison, this review reinforces that each qualitative approach should be treated uniquely on account of its own distinctive features for different epistemological and disciplinary positions. Owing to the sensitivity of the worth of qualitative research towards the specific context and the type of paradigmatic stance, researchers should themselves analyze what approaches can be and must be tailored to ensemble the distinct characteristics of the phenomenon under investigation. Although this article does not assert to put forward a magic bullet and to provide a one-stop solution for dealing with dilemmas about how, why, or whether to evaluate the “goodness” of qualitative research, it offers a platform to assist the researchers in improving their qualitative studies. This work provides an assembly of concerns to reflect on, a series of questions to ask, and multiple sets of criteria to look at, when attempting to determine the quality of qualitative research. Overall, this review underlines the crux of qualitative research and accentuates the need to evaluate such research by the very tenets of its being. Bringing together the vital arguments and delineating the requirements that good qualitative research should satisfy, this review strives to equip the researchers as well as reviewers to make well-versed judgment about the worth and significance of the qualitative research under scrutiny. In a nutshell, a comprehensive portrayal of the research process (from the context of research to the research objectives, research questions and design, speculative foundations, and from approaches of collecting data to analyzing the results, to deriving inferences) frequently proliferates the quality of a qualitative research.

Prospects : A Road Ahead for Qualitative Research

Irrefutably, qualitative research is a vivacious and evolving discipline wherein different epistemological and disciplinary positions have their own characteristics and importance. In addition, not surprisingly, owing to the sprouting and varied features of qualitative research, no consensus has been pulled off till date. Researchers have reflected various concerns and proposed several recommendations for editors and reviewers on conducting reviews of critical qualitative research (Levitt et al., 2021 ; McGinley et al., 2021 ). Following are some prospects and a few recommendations put forward towards the maturation of qualitative research and its quality evaluation:

In general, most of the manuscript and grant reviewers are not qualitative experts. Hence, it is more likely that they would prefer to adopt a broad set of criteria. However, researchers and reviewers need to keep in mind that it is inappropriate to utilize the same approaches and conducts among all qualitative research. Therefore, future work needs to focus on educating researchers and reviewers about the criteria to evaluate qualitative research from within the suitable theoretical and methodological context.

There is an urgent need to refurbish and augment critical assessment of some well-known and widely accepted tools (including checklists such as COREQ, SRQR) to interrogate their applicability on different aspects (along with their epistemological ramifications).

Efforts should be made towards creating more space for creativity, experimentation, and a dialogue between the diverse traditions of qualitative research. This would potentially help to avoid the enforcement of one's own set of quality criteria on the work carried out by others.

Moreover, journal reviewers need to be aware of various methodological practices and philosophical debates.

It is pivotal to highlight the expressions and considerations of qualitative researchers and bring them into a more open and transparent dialogue about assessing qualitative research in techno-scientific, academic, sociocultural, and political rooms.

Frequent debates on the use of evaluative criteria are required to solve some potentially resolved issues (including the applicability of a single set of criteria in multi-disciplinary aspects). Such debates would not only benefit the group of qualitative researchers themselves, but primarily assist in augmenting the well-being and vivacity of the entire discipline.

To conclude, I speculate that the criteria, and my perspective, may transfer to other methods, approaches, and contexts. I hope that they spark dialog and debate – about criteria for excellent qualitative research and the underpinnings of the discipline more broadly – and, therefore, help improve the quality of a qualitative study. Further, I anticipate that this review will assist the researchers to contemplate on the quality of their own research, to substantiate research design and help the reviewers to review qualitative research for journals. On a final note, I pinpoint the need to formulate a framework (encompassing the prerequisites of a qualitative study) by the cohesive efforts of qualitative researchers of different disciplines with different theoretic-paradigmatic origins. I believe that tailoring such a framework (of guiding principles) paves the way for qualitative researchers to consolidate the status of qualitative research in the wide-ranging open science debate. Dialogue on this issue across different approaches is crucial for the impending prospects of socio-techno-educational research.

Amin, M. E. K., Nørgaard, L. S., Cavaco, A. M., Witry, M. J., Hillman, L., Cernasev, A., & Desselle, S. P. (2020). Establishing trustworthiness and authenticity in qualitative pharmacy research. Research in Social and Administrative Pharmacy, 16 (10), 1472–1482.

Article   Google Scholar  

Barker, C., & Pistrang, N. (2005). Quality criteria under methodological pluralism: Implications for conducting and evaluating research. American Journal of Community Psychology, 35 (3–4), 201–212.

Bryman, A., Becker, S., & Sempik, J. (2008). Quality criteria for quantitative, qualitative and mixed methods research: A view from social policy. International Journal of Social Research Methodology, 11 (4), 261–276.

Caelli, K., Ray, L., & Mill, J. (2003). ‘Clear as mud’: Toward greater clarity in generic qualitative research. International Journal of Qualitative Methods, 2 (2), 1–13.

CASP (2021). CASP checklists. Retrieved May 2021 from https://casp-uk.net/casp-tools-checklists/

Cohen, D. J., & Crabtree, B. F. (2008). Evaluative criteria for qualitative research in health care: Controversies and recommendations. The Annals of Family Medicine, 6 (4), 331–339.

Denzin, N. K., & Lincoln, Y. S. (2005). Introduction: The discipline and practice of qualitative research. In N. K. Denzin & Y. S. Lincoln (Eds.), The sage handbook of qualitative research (pp. 1–32). Sage Publications Ltd.

Google Scholar  

Elliott, R., Fischer, C. T., & Rennie, D. L. (1999). Evolving guidelines for publication of qualitative research studies in psychology and related fields. British Journal of Clinical Psychology, 38 (3), 215–229.

Epp, A. M., & Otnes, C. C. (2021). High-quality qualitative research: Getting into gear. Journal of Service Research . https://doi.org/10.1177/1094670520961445

Guba, E. G. (1990). The paradigm dialog. In Alternative paradigms conference, mar, 1989, Indiana u, school of education, San Francisco, ca, us . Sage Publications, Inc.

Hammersley, M. (2007). The issue of quality in qualitative research. International Journal of Research and Method in Education, 30 (3), 287–305.

Haven, T. L., Errington, T. M., Gleditsch, K. S., van Grootel, L., Jacobs, A. M., Kern, F. G., & Mokkink, L. B. (2020). Preregistering qualitative research: A Delphi study. International Journal of Qualitative Methods, 19 , 1609406920976417.

Hays, D. G., & McKibben, W. B. (2021). Promoting rigorous research: Generalizability and qualitative research. Journal of Counseling and Development, 99 (2), 178–188.

Horsburgh, D. (2003). Evaluation of qualitative research. Journal of Clinical Nursing, 12 (2), 307–312.

Howe, K. R. (2004). A critique of experimentalism. Qualitative Inquiry, 10 (1), 42–46.

Johnson, J. L., Adkins, D., & Chauvin, S. (2020). A review of the quality indicators of rigor in qualitative research. American Journal of Pharmaceutical Education, 84 (1), 7120.

Johnson, P., Buehring, A., Cassell, C., & Symon, G. (2006). Evaluating qualitative management research: Towards a contingent criteriology. International Journal of Management Reviews, 8 (3), 131–156.

Klein, H. K., & Myers, M. D. (1999). A set of principles for conducting and evaluating interpretive field studies in information systems. MIS Quarterly, 23 (1), 67–93.

Lather, P. (2004). This is your father’s paradigm: Government intrusion and the case of qualitative research in education. Qualitative Inquiry, 10 (1), 15–34.

Levitt, H. M., Morrill, Z., Collins, K. M., & Rizo, J. L. (2021). The methodological integrity of critical qualitative research: Principles to support design and research review. Journal of Counseling Psychology, 68 (3), 357.

Lincoln, Y. S., & Guba, E. G. (1986). But is it rigorous? Trustworthiness and authenticity in naturalistic evaluation. New Directions for Program Evaluation, 1986 (30), 73–84.

Lincoln, Y. S., & Guba, E. G. (2000). Paradigmatic controversies, contradictions and emerging confluences. In N. K. Denzin & Y. S. Lincoln (Eds.), Handbook of qualitative research (2nd ed., pp. 163–188). Sage Publications.

Madill, A., Jordan, A., & Shirley, C. (2000). Objectivity and reliability in qualitative analysis: Realist, contextualist and radical constructionist epistemologies. British Journal of Psychology, 91 (1), 1–20.

Mays, N., & Pope, C. (2020). Quality in qualitative research. Qualitative Research in Health Care . https://doi.org/10.1002/9781119410867.ch15

McGinley, S., Wei, W., Zhang, L., & Zheng, Y. (2021). The state of qualitative research in hospitality: A 5-year review 2014 to 2019. Cornell Hospitality Quarterly, 62 (1), 8–20.

Merriam, S., & Tisdell, E. (2016). Qualitative research: A guide to design and implementation. San Francisco, US.

Meyer, M., & Dykes, J. (2019). Criteria for rigor in visualization design study. IEEE Transactions on Visualization and Computer Graphics, 26 (1), 87–97.

Monrouxe, L. V., & Rees, C. E. (2020). When I say… quantification in qualitative research. Medical Education, 54 (3), 186–187.

Morrow, S. L. (2005). Quality and trustworthiness in qualitative research in counseling psychology. Journal of Counseling Psychology, 52 (2), 250.

Morse, J. M. (2003). A review committee’s guide for evaluating qualitative proposals. Qualitative Health Research, 13 (6), 833–851.

Nassaji, H. (2020). Good qualitative research. Language Teaching Research, 24 (4), 427–431.

O’Brien, B. C., Harris, I. B., Beckman, T. J., Reed, D. A., & Cook, D. A. (2014). Standards for reporting qualitative research: A synthesis of recommendations. Academic Medicine, 89 (9), 1245–1251.

O’Connor, C., & Joffe, H. (2020). Intercoder reliability in qualitative research: Debates and practical guidelines. International Journal of Qualitative Methods, 19 , 1609406919899220.

Reid, A., & Gough, S. (2000). Guidelines for reporting and evaluating qualitative research: What are the alternatives? Environmental Education Research, 6 (1), 59–91.

Rocco, T. S. (2010). Criteria for evaluating qualitative studies. Human Resource Development International . https://doi.org/10.1080/13678868.2010.501959

Sandberg, J. (2000). Understanding human competence at work: An interpretative approach. Academy of Management Journal, 43 (1), 9–25.

Schwandt, T. A. (1996). Farewell to criteriology. Qualitative Inquiry, 2 (1), 58–72.

Seale, C. (1999). Quality in qualitative research. Qualitative Inquiry, 5 (4), 465–478.

Shenton, A. K. (2004). Strategies for ensuring trustworthiness in qualitative research projects. Education for Information, 22 (2), 63–75.

Sparkes, A. C. (2001). Myth 94: Qualitative health researchers will agree about validity. Qualitative Health Research, 11 (4), 538–552.

Spencer, L., Ritchie, J., Lewis, J., & Dillon, L. (2004). Quality in qualitative evaluation: A framework for assessing research evidence.

Stenfors, T., Kajamaa, A., & Bennett, D. (2020). How to assess the quality of qualitative research. The Clinical Teacher, 17 (6), 596–599.

Taylor, E. W., Beck, J., & Ainsworth, E. (2001). Publishing qualitative adult education research: A peer review perspective. Studies in the Education of Adults, 33 (2), 163–179.

Tong, A., Sainsbury, P., & Craig, J. (2007). Consolidated criteria for reporting qualitative research (COREQ): A 32-item checklist for interviews and focus groups. International Journal for Quality in Health Care, 19 (6), 349–357.

Tracy, S. J. (2010). Qualitative quality: Eight “big-tent” criteria for excellent qualitative research. Qualitative Inquiry, 16 (10), 837–851.

Download references

Open access funding provided by TU Wien (TUW).

Author information

Authors and affiliations.

Faculty of Informatics, Technische Universität Wien, 1040, Vienna, Austria

Drishti Yadav

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Drishti Yadav .

Ethics declarations

Conflict of interest.

The author declares no conflict of interest.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Yadav, D. Criteria for Good Qualitative Research: A Comprehensive Review. Asia-Pacific Edu Res 31 , 679–689 (2022). https://doi.org/10.1007/s40299-021-00619-0

Download citation

Accepted : 28 August 2021

Published : 18 September 2021

Issue Date : December 2022

DOI : https://doi.org/10.1007/s40299-021-00619-0

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Qualitative research
• Evaluative criteria
• Find a journal
• Publish with us
• Track your research

10 Qualities of a Good Researcher: Quest for Excellence

• Post author By admin
• November 9, 2023

Discover the essential 10 qualities of a good researcher! Uncover the traits that drive success in the world of research. Learn what it takes to excel in the quest for knowledge and innovation

Suppose a vast landscape of knowledge, uncharted and waiting to be discovered. Research is the compass guiding us through this territory, and at the helm of every great exploration stands a good researcher.

But what sets them apart? It’s not just knowledge; it’s a unique set of qualities that propel them towards understanding.

In this journey, we’ll uncover the very essence of a good researcher. We’ll delve into the top 10 qualities that define them. From unquenchable curiosity to unwavering perseverance, these qualities are the secret sauce behind their success in academia and exploration.

Whether you’re already treading the path of research or gearing up for the adventure, understanding and embracing these qualities will transform you into a research dynamo. So, let’s embark on this quest to unravel what makes a good researcher tick.

Table of Contents

10 Qualities of a Good Researcher

Check out the 10 qualities of a good researcher:-

1. Inquisitiveness: The Craving for Knowledge

Think of a good researcher as that friend who’s always full of questions. They’re the eternal curious cats of the academic world, forever wondering, forever seeking, and forever hungry for knowledge. It’s like they have a built-in “Why?” button that never switches off.

A good researcher’s inquisitiveness is like the spark that lights up a dark room. It’s what pushes them to ask the questions no one else has thought of and venture into uncharted territories. They’re the ultimate seekers, the champions of “What if?” and “Why not?” It’s this insatiable curiosity that keeps their research fresh, exciting, and always on the hunt for more knowledge.

2. Patience: Sifting Through Data

Imagine a good researcher as a treasure hunter in the vast desert of data. Research can sometimes feel like slogging through quicksand – slow, meticulous, and demanding. But here’s the thing: good researchers have an incredible treasure map, and it’s called “patience.”

They understand that research isn’t a race; it’s a journey. It’s about sifting through tons of data, the way a prospector pans for gold. Every grain of information matters, and they’re willing to invest the time needed to collect, analyze, and interpret data accurately.

This patience isn’t about twiddling thumbs; it’s about meticulously building the puzzle of knowledge, piece by piece. They understand that no detail is too small to be overlooked, and in the end, it’s these small pieces that complete the big picture.

Good researchers don’t rush; they savor the journey, knowing that the best discoveries often lie in the details. They are the patient architects of knowledge, and it’s their patience that ensures that no gem of information goes undiscovered.

3. Attention to Detail: Devil in the Details

In research, it’s the little things that matter most. A good researcher understands this like no other. They’re the ones who spot the faintest footprints in the sand and the almost invisible fingerprints on the glass because they know that in research, the devil truly lies in the details.

For them, every piece of information is a precious puzzle piece. They’re like puzzle enthusiasts, and they’re determined to find and fit every piece perfectly. Because, in their world, even the tiniest detail holds the potential to make or break a study.

In a realm where precision reigns supreme, good researchers are the vigilant guardians of information. They’re the ones who make sure no stone is left unturned, no detail is too minor, and it’s this unwavering attention to detail that transforms their research into something truly extraordinary.

4. Critical Thinking: Questioning the Norm

Let’s picture a good researcher as the ultimate rebel of the research realm. They don’t just follow the herd; they’re the ones breaking the mold, challenging established theories, and stirring up the intellectual pot. Their secret weapon? It’s called critical thinking.

Critical thinking is like their sidekick, the Watson to their Holmes. It’s their power to look at information with a discerning eye, to cut through the noise, and make informed judgments. Good researchers? They’ve got critical thinking in their toolkit, and they’re not afraid to use it.

They’re not content with nodding along to the norm. No, they’re the ones who dare to ask, “Why?” and “What if?” They’re the Sherlock Holmes of academia, seeking the hidden clues that others might overlook. They’re the explorers who venture beyond the boundaries of convention.

For them, curiosity isn’t just a casual interest; it’s a full-blown investigation. They’re the skeptics, the truth-seekers, and the challengers of the status quo. Because they know that the road to enlightenment is paved with skepticism and paved with profound insights.

In a world where knowledge is the ultimate treasure, good researchers are the rebels with a cause. They’re the ones who question, challenge, and redefine the norm, making the pursuit of knowledge a thrilling adventure.

5. Organization: Chaos to Clarity

Let’s paint a mental picture of a good researcher as the master organizer of the research universe. Picture this: researchers often find themselves wading through mountains of data, like explorers in an information jungle.

But what sets good researchers apart is their exceptional skill in turning chaos into clarity through one magic word – organization.

These researchers are like the conductors of a grand symphony, where data plays the melodious tunes. They understand that without a meticulously organized score, the music may fall into chaos.

This is why they keep their work structured and well-organized. It’s like having a treasure map to navigate through the data wilderness.

For them, organization isn’t just a preference; it’s a necessity. It ensures that every piece of data, every note in the symphony, can be easily accessed and referenced when needed. It’s the librarian’s skill of categorizing, labeling, and arranging knowledge in a way that makes sense.

In a world where data can be overwhelming, good researchers are the navigators who chart the course from chaos to clarity. They bring order to the information realm, making sure that every piece of data finds its place in the grand mosaic of knowledge.

6. Effective Communication: Sharing Insights

Imagine a good researcher as not just a discoverer of hidden treasures but also a gifted storyteller. Research isn’t merely about uncovering the unknown; it’s about sharing those discoveries with the world. Good researchers possess a unique superpower – effective communication.

They are the bards of academia, able to weave intricate tales of data and insight. It’s not enough to gather knowledge; they understand the importance of conveying it to their peers and the wider community. They’re like skilled translators, turning complex data into understandable narratives.

For them, research isn’t a solitary endeavor but a communal one. They can articulate their findings, transforming raw data into gems of wisdom. They speak not just to fellow researchers but to anyone who seeks understanding.

In a world where information is abundant but understanding can be scarce, good researchers are the bridges that connect data to meaning. They’re the ones who bring clarity to complexity, ensuring that their discoveries benefit not just themselves but all who thirst for knowledge.

7. Ethical Integrity: The Moral Compass

Picture a good researcher as a moral compass, always pointing in the direction of what’s right. In their world, there’s no room for ethical shortcuts; they’re the guardians of integrity, setting the highest standards.

Ethical conduct is their unwavering principle, not a mere guideline. These researchers tread the path of knowledge with profound respect for all beings, be it humans, animals, or the environment.

They understand that research isn’t just about facts and figures; it’s about the impact on the world.

They are the ethical warriors who ensure that every discovery is made with the utmost respect for boundaries. They’re the ones who hold the torch of integrity, even when the road gets dark and uncertain.

In a world where ethical dilemmas can cloud the way, good researchers are the beacons of moral clarity. They remind us that the pursuit of knowledge should always be illuminated by the light of ethics, leaving a positive and lasting legacy.

8. Adaptability: Rolling with Research’s Twists

Now, picture a good researcher as the ultimate research ninja. They know that in the world of research, surprises are the name of the game. What makes them exceptional? Their uncanny ability to adapt.

In their world, every research project is like a thrilling rollercoaster ride. They’re fully aware that not everything will go as planned.

But instead of dreading the unexpected, they welcome it with open arms. It’s not about dodging hurdles; it’s about using them as springboards for new discoveries.

Adaptability is their secret weapon. They don’t panic when faced with unexpected twists and turns; they thrive on them. They’re the daredevils of research, excited by the idea that every surprise brings a chance for a breakthrough.

They understand that research isn’t a linear path; it’s an expedition full of surprises. Good researchers approach each twist and turn as a new opportunity to learn, grow, and uncover the unknown.

9. Perseverance: Never Giving Up

Now, picture a good researcher as the indomitable hero of the research saga. The journey to groundbreaking discoveries is no walk in the park; it’s an epic adventure filled with obstacles and trials. What makes a good researcher extraordinary? Their unshakable perseverance.

In their world, setbacks are not dead ends; they are the very soil in which success takes root. They grasp that the path to pioneering research is not a sprint but a demanding marathon.

When confronted with challenges, they don’t retreat; they roll up their sleeves and forge ahead with unwavering resolve.

In their universe, perseverance is the North Star guiding them through the darkest nights of research. It’s the fire that keeps them warm when faced with the chilling winds of doubt.

They understand that every stumble is a lesson, every hurdle is an opportunity, and every fall is a chance to rise even higher.

In a realm where remarkable discoveries are born from sheer determination, good researchers are the embodiment of perseverance.

They don’t just weather the storms of research; they harness them to soar to new heights of understanding and innovation.

10. Problem-Solving Skills: Creative and Determined Issue Resolution

Think of a good researcher as a maverick in the world of problem-solving. They possess an innate ability to tackle research-related issues with a unique blend of creativity and unwavering determination. They’re not just issue-spotters; they’re issue-solvers.

In their realm, challenges aren’t roadblocks; they’re opportunities for innovation. Whether it’s deciphering a complex data conundrum, navigating unexpected research detours, or confronting formidable roadblocks, they approach each problem with a dash of unconventional thinking.

Their toolkit isn’t limited to traditional solutions; it includes a healthy dose of creativity. They know that sometimes the most extraordinary answers emerge from unconventional thinking.

When faced with adversity, they don’t back down; they dive headfirst into the challenge, armed with resourcefulness and an unyielding spirit.

In the world of research, where every obstacle conceals a chance for a groundbreaking discovery, these good researchers are the daring explorers.

They turn problems into springboards, propelling the journey of knowledge and unveiling new insights along the way.

What is the qualities of good researcher?

Exceptional researchers are a unique breed, possessing a blend of innate traits and developed skills that set them apart in the world of discovery. Here are the qualities that define an outstanding researcher:

Inherent Curiosity

Exceptional researchers are born with an insatiable curiosity about the world. They perpetually question, driven by an unrelenting thirst for knowledge. This curiosity fuels their exploration of new ideas and their deep dives into complex problems.

Independence and Initiative

They are fiercely independent, unafraid to challenge conventions and think outside the box. This independence empowers them to conduct research with rigor and objectivity, free from preconceived notions.

Critical Thinking

Exceptional researchers are expert critical thinkers. They scrutinize information, identifying biases and assumptions. This skill enables them to draw well-founded conclusions from their research, undeterred by misinformation.

Effective Communication

They are adept communicators, capable of presenting their findings clearly and concisely. Their ability to convey complex ideas is vital for sharing their discoveries with the broader scientific community.

Collaboration Prowess

Collaboration is second nature to them. Exceptional researchers seamlessly collaborate with others to achieve common research objectives. Their skill in teamwork is essential for handling large-scale research projects effectively.

Problem-Solving Expertise

Problem-solving is in their DNA. They spot issues, conceive and test solutions, and rigorously evaluate their effectiveness. This skill is the backbone of conducting thorough research.

In addition to these qualities, exceptional researchers boast an in-depth understanding of their chosen field. They stay abreast of the latest research findings and expertly apply this knowledge to their own work.

Furthermore, they adhere to ethical guidelines that govern research, conducting their inquiries responsibly and ethically.

Armed with these remarkable qualities, exceptional researchers not only expand our comprehension of the world but also contribute to solving critical problems and enhancing the quality of life for all.

What are the 7 major characteristics of research?

Research is a multifaceted endeavor, marked by seven pivotal characteristics that define its essence:

1, Empirical Foundation

At its core, research is grounded in empiricism. It shuns opinions, personal beliefs, and conjecture. Instead, it thrives on data and evidence drawn from real-world observations and experiments, bolstering its conclusions with solid support.

2. Systematic Approach

Research unfolds systematically, adhering to a meticulously designed process. It commences with defining the research question, identifying research methods, collecting data, rigorously analyzing it, and ultimately deriving well-founded conclusions. This systematic journey ensures both rigor and objectivity.

3. Logical Underpinning

Logic forms the backbone of research. It forges conclusions that harmonize seamlessly with the laws of logic, yielding findings that are not only profound but also reliable.

4. Cyclical Nature

Research possesses a cyclical essence. It commences with a question or problem, each exploration invariably begetting new inquiries. This continuous cycle propels researchers toward a deeper understanding of the ever-evolving world.

5. Analytical Rigor

Research demands meticulous data analysis. Researchers employ diverse analytical techniques to uncover patterns, trends, and relationships within the data. This scrutiny unveils the latent significance of the data, facilitating the derivation of meaningful conclusions.

6. Objective Stance

An unwavering objectivity characterizes research. Researchers diligently strive to avoid bias and partiality, ensuring that their personal beliefs or opinions exert no undue influence on their findings.

7. Replicability Standard

Research adheres to a replicability standard. Other researchers should be capable of replicating the study and achieving congruent results. This commitment to replicability bolsters the reliability and validity of research findings.

Incorporating these seven key characteristics, research emerges as a powerful tool for the exploration of the unknown, the validation of hypotheses, and the continuous advancement of knowledge.

What are the 3 important qualities of a good research?

When we delve into the world of outstanding research, we uncover the pillars that set it apart. Imagine these as the main characters in a compelling story:

1. Credibility

This is the unwavering foundation. Exceptional research is built on solid evidence and meticulous reasoning. It follows a rigorous and objective path, supported by thorough data and in-depth analysis.

2. Relevance

Consider this the heart of the matter. Exceptional research doesn’t shy away from addressing pressing questions and challenges.

It aims to contribute significantly to our understanding of the world and has the potential to solve crucial problems.

3. Originality

Think of this as the trailblazer, the innovator. Exceptional research ventures into uncharted territories, offering fresh and unique perspectives.

It doesn’t retrace well-worn paths; instead, it opens new doors to insights that haven’t been explored before.

These are the three pillars of remarkable research, igniting our quest to comprehend our world more deeply, confront significant challenges, and provide solutions that truly enhance our lives and the lives of those around us.

What are the 4 characteristics of a good research?

When we delve into the world of research, we discover the four cornerstones that define what makes research truly exceptional:

Imagine research as a sturdy ship navigating the vast sea of knowledge. What keeps it afloat? Credibility – the anchor of solid evidence and logical reasoning.

It’s about following a rigorous and objective methodology, with findings firmly supported by a wealth of data and meticulous analysis.

Good research is like a compass pointing to the critical questions and challenges that pique the curiosity of the research community and society.

It’s not just an exploration; it’s a journey with a purpose – to deepen our understanding of the world and unravel solutions to the most pressing problems.

Think of research as an explorer venturing into uncharted territory. It doesn’t follow the trodden paths; it forges its own.

Good research doesn’t echo what’s been said before; it blazes new trails, offering fresh insights and unique perspectives.

Effective research is a lighthouse, guiding others through the maze of complexity. Its findings are not buried in jargon or obscured by ambiguity.

They are presented with clarity and conciseness, ensuring that everyone can navigate the discoveries with ease.

These attributes, like the North Star, lead us in the pursuit of knowledge and understanding, casting light on the uncharted waters of research.

In the grand tapestry of knowledge, good researchers stand as the weavers of profound discovery. They embody a unique blend of qualities, shaping the course of understanding and change.

From the inquisitiveness that fuels their journey to the unwavering patience that carries them through the most intricate of labyrinths, these qualities are the compass, the guiding light.

The unquenchable curiosity of a good researcher keeps the embers of exploration burning bright. Patience, the steadfast companion, ensures that no detail remains in obscurity.

Their critical thinking propels them beyond the boundaries of convention, unraveling new layers of understanding.

In the chaos of data, they find serenity through organization, and in the midst of complexity, they wield the sword of effective communication.

Ethical integrity acts as their moral compass, while adaptability embraces the unpredictability of research’s twists.

But it’s perseverance, the indomitable spirit, that carries them through the darkest hours. They recognize that the path to groundbreaking research is often fraught with obstacles, but those obstacles serve as stepping stones to success.

These ten qualities, woven into the very fabric of their being, make good researchers the architects of transformation.

With every study they undertake, they draw closer to unraveling the mysteries of our world, bridging gaps in knowledge, and contributing to the betterment of humanity.

As we celebrate these qualities, we acknowledge the significance of their work. Through their endeavors, we glimpse the limitless potential of human exploration, and we are inspired to never cease questioning, exploring, and, above all, learning.

Frequently Asked Questions

Can anyone become a good researcher.

Yes, with dedication and a willingness to develop these qualities, anyone can become a good researcher.

Why is adaptability crucial for a researcher?

Research is unpredictable, and adaptability allows researchers to navigate unexpected challenges effectively.

What role does ethics play in research?

Ethical integrity is vital in research to ensure the well-being of participants and the integrity of the study.

How do researchers maintain their inquisitiveness?

Researchers stay curious by continually seeking new questions and exploring uncharted territories in their field.

Is critical thinking a natural talent, or can it be developed?

Critical thinking can be developed through practice and a commitment to questioning and evaluating information.

• australia (2)
• duolingo (13)
• Education (283)
• General (78)
• How To (16)
• IELTS (127)
• Latest Updates (162)
• Malta Visa (6)
• Permanent residency (1)
• Programming (31)
• Scholarship (1)
• Sponsored (4)
• Study Abroad (187)
• Technology (12)
• work permit (8)

Recent Posts

• Research Process

The Top 5 Qualities of Every Good Researcher

• 3 minute read

Table of Contents

What makes a good researcher? Is it some undefinable, innate genius, or is it something that we can practice and build upon? If it was just the former, then there would be far fewer innovations in the history of humankind than there have been. A careful look at researchers through the ages reveals that they all have certain attributes in common that have helped contribute to their success.

The characteristics of a good researcher:

1. curiosity.

They ask questions. An endless thirst for knowledge is what sets the best of the best apart from the others. Good researchers constantly strive to learn more, not just about their own field, but about other fields as well. The world around us is fascinating, be it the physics behind the way light refracts, or the anthropological constructions of our society. A good researcher keeps exploring the world and keeps searching for answers.

2. Analytical ability and foresight

They look for connections. Information is useless without interpretation. What drives research forward is finding meaning in our observations and data. Good researchers evaluate data from every angle and search for patterns. They explore cause and effect and untangle the tricky web that interconnects everyday phenomena. And then take it one step further to ask, ‘What is the bigger picture? How will the research develop in the future?’

3. Determination

They try, try, and try again. Research can be a frustrating experience. Experiments may not pan out how we expect them to. Even worse, sometimes experiments may run smoothly until they are 95% complete before failing. What sets an average researcher apart from a truly good one? The truly good researcher perseveres. They accept this disappointment, learn from the failure, reevaluate their experiment, and keep moving forward.

4. Collaboration

Teamwork makes the dream work. Contrary to the common perception of the solitary genius in their lab, research is an extremely collaborative process. There is simply too much to do for just one person to do it all. Moreover, research is becoming increasingly multidisciplinary. It is impossible for just one person to have expertise in all these fields. In general, research is conducted in teams , with each researcher having their individual roles and responsibilities. Being able to coordinate, communicate, and get along with team members is a major factor that can contribute to one’s success as a researcher.

5. Communication

They get their message across. Communication skills are an essential asset for every researcher. Not only do they have to communicate with their team members, but they also have to communicate with co-authors, journals, publishers, and funders. Whether it is writing a crisp and effective abstract, presenting at a conference, or writing a persuasive grant proposal to secure research funding, communication appears everywhere in a researcher’s life. The message in the old adage, ‘If a tree falls in the forest, but no one is around to hear it, does it make a sound?’ applies to research too. A discovery could be groundbreaking, but what is the use if the researcher can’t communicate this discovery to the rest of the world?

These are just a few of the skills required by researchers to make it to the top of their field. Other attributes like creativity and time management are also worth mentioning. Nevertheless, having one or more of these top five characteristics will make the research process smoother for you and increase the chances of positive results. Set yourself up for success by building up these skills, focusing on excellence, and asking for help when you need it. Elsevier Author Services is here to aid you at every step of the research journey. From translation services by experts in the field, to preparing your manuscript for publication, to helping you submit the best possible grant proposal, you can trust us to guide you in your journey to doing great research.

• Manuscript Preparation

What is the Background of a Study and How Should it be Written?

• Publication Process

Writing an Effective Cover Letter for Manuscript Resubmission

You may also like.

Descriptive Research Design and Its Myriad Uses

Five Common Mistakes to Avoid When Writing a Biomedical Research Paper

Making Technical Writing in Environmental Engineering Accessible

To Err is Not Human: The Dangers of AI-assisted Academic Writing

When Data Speak, Listen: Importance of Data Collection and Analysis Methods

Choosing the Right Research Methodology: A Guide for Researchers

Why is data validation important in research?

Writing a good review article

Input your search keywords and press Enter.

What Constitutes a Good Research?

The Declining Art of Good Research

We seem to be compromising our commitment to good research in favor of publishable research, and there are a combination of trends that are accountable for this.

The first is the continued pressure of “publish or perish” for young academics seeking to move forward on the track for fewer and fewer tenured positions (or increasingly draconian renewable contracts).

Secondly, the open access model of research publication has created a booming population of academic journals with pages to fill and new researchers willing to pay article publication fees (APFs).

Thirdly, budget-strapped institutions have been aggressively targeting doctoral research candidates and the higher fees they bring to the table.

When these three trends are combined, the resulting onslaught of quantity over quality leads us to question what “good” research looks like anymore.

Is it the institution from which the research originated, or the debatable rank of the journal that published it?

Good Research as a Methodological Question

When looking to learn how to recognize what “good” research looks like, it makes sense to start at the beginning with the basic scope of the project:

• Does the research have a solid hypothesis?
• Is there evidence of a comprehensive literature review from reputable sources that clearly defines a target area for valuable research?
• Is the research team allocating sufficient time/resources to do the job properly, or were compromises made in order to accommodate the available funding?
• Is there evidence of a willingness to refine the hypothesis and research strategy if needed?
• Are the expectations of the implications of the research realistic?

Characteristics of a Good Research

For conducting a systematic research, it is important understand the characteristics of a good research.

• Its relevance to existing research conducted by other researchers.
• A good research is doable and replicable in future.
• It must be based on a logical rationale and tied to theory.
• It must generate new questions or hypotheses for incremental work in future.
• It must directly or indirectly address some real world problem.
• It must clearly state the variables of the experiment.
• It must conclude with valid and verifiable findings.

Good Research as an Ethical Question

The question as to whether or not the research is worth conducting at all could generate an extended and heated debate. Researchers are expected to publish, and research budgets are there to be spent.

We can hope that there was some degree of discussion and oversight before the research project was given the green light by a Principal Investigator or Research Supervisor, but those decisions are often made in a context of simple obligation rather than perceived need.

Consider the example of a less than proactive doctoral student with limited time and resources to complete a dissertation topic. A suggestion is made by the departmental Research Supervisor to pick a dissertation from a decade ago and simply repeat it. The suggestion meets the need for expediency and simplicity, but raises as many questions as it answers:

• What is the validity of the study – just because it can be repeated, should it?
• What was the contribution of the original study to the general body of knowledge? Will this additional data be an improvement?
• Given the lack of interest among academic journals in replicated studies, is the suggestion denying the student the opportunity to get published?
• Is directing a student to replication in the interests of expediency meeting a broader academic goal of graduating proficient researchers?

The Building Blocks of “Good” Research

There is no shortage of reputable, peer-reviewed journals that publish first-rate research material for new researchers to model.

That doesn’t mean you should copy the research topic or the methodology, but it wouldn’t hurt to examine the protocol in detail and make note of the specific decisions made and criteria put in place when that protocol was developed and implemented.

The challenge lies in sticking to those tried-and-true methodologies when your research data doesn’t prove to be as rich and fruitful as you had hoped.

Have you ever been stuck while in the middle of conducting a research? How did you cope with that? Let us know your approach while conducting a good research in the comments section below!

You can also visit our  Q&A forum  for frequently asked questions related to different aspects of research writing and publishing answered by our team that comprises subject-matter experts, eminent researchers, and publication experts.

Rate this article Cancel Reply

Your email address will not be published.

Enago Academy's Most Popular Articles

• Reporting Research

Academic Essay Writing Made Simple: 4 types and tips

The pen is mightier than the sword, they say, and nowhere is this more evident…

Ensuring Academic Integrity and Transparency in Academic Research: A comprehensive checklist for researchers

Academic integrity is the foundation upon which the credibility and value of scientific findings are…

• AI in Academia

AI vs. AI: How to detect image manipulation and avoid academic misconduct

The scientific community is facing a new frontier of controversy as artificial intelligence (AI) is…

• Diversity and Inclusion

Need for Diversifying Academic Curricula: Embracing missing voices and marginalized perspectives

In classrooms worldwide, a single narrative often dominates, leaving many students feeling lost. These stories,…

• Career Corner
• Trending Now

Recognizing the Signs: A guide to overcoming academic burnout

As the sun set over the campus, casting long shadows through the library windows, Alex…

7 Steps of Writing an Excellent Academic Book Chapter

When Your Thesis Advisor Asks You to Quit

Virtual Defense: Top 5 Online Thesis Defense Tips

Sign-up to read more

Subscribe for free to get unrestricted access to all our resources on research writing and academic publishing including:

• 2000+ blog articles
• 50+ Webinars
• 10+ Expert podcasts
• 50+ Infographics
• 10+ Checklists
• Research Guides

We hate spam too. We promise to protect your privacy and never spam you.

I am looking for Editing/ Proofreading services for my manuscript Tentative date of next journal submission:

What would be most effective in reducing research misconduct?

Literature Searching

Characteristics of a good research question

The first step in a literature search is to construct a well-defined question.  This helps in ensuring a comprehensive and efficient search of the available literature for relevant publications on your topic.  The well-constructed research question provides guidance for determining search terms and search strategy parameters.

A good or well-constructed research question is:

• Original and of interest to the researcher and the outside world
• It is clear and focused: it provides enough specifics that it is easy to understand its purpose and it is narrow enough that it can be answered. If the question is too broad it may not be possible to answer it thoroughly. If it is too narrow you may not find enough resources or information to develop a strong argument or research hypothesis.  
• The question concept is researchable in terms of time and access to a suitable amount of quality research resources.
• It is analytical rather than descriptive.  The research question should allow you to produce an analysis of an issue or problem rather than a simple description of it.  In other words, it is not answerable with a simple “yes” or “no” but requires a synthesis and analysis of ideas and sources.
• The results are potentially important and may change current ideas and/or practice
• And there is the potential to develop further projects with similar themes

The question you ask should be developed for the discipline you are studying. A question appropriate for Physical Therapy, for instance, is different from an appropriate one in Sociology, Political Science or Microbiology .

The well-constructed question provides guidance for determining search terms and search strategy parameters. The process of developing a good question to research involves taking your topic and breaking each aspect of it down into its component parts. 

One well-established way that can be used both for creating research questions and developing strategies is known as PICO(T). The PICO framework was designed primarily for questions that include clinical interventions and comparisons, however other types of questions may also be able to follow its principles.  If the PICO framework does not precisely fit your question, using its principles can help you to think about what you want to explore even if you do not end up with a true PICO question.

References/Additional Resources

Fandino W. (2019). Formulating a good research question: Pearls and pitfalls.   Indian journal of anaesthesia ,  63 (8), 611–616. 

Vandenbroucke, J. P., & Pearce, N. (2018). From ideas to studies: how to get ideas and sharpen them into research questions .  Clinical epidemiology ,  10 , 253–264.

Ratan, S. K., Anand, T., & Ratan, J. (2019). Formulation of Research Question - Stepwise Approach .  Journal of Indian Association of Pediatric Surgeons ,  24 (1), 15–20.

Lipowski, E.E. (2008). Developing great research questions. American Journal of Health-System Pharmacy, 65(17) , 1667–1670.

FINER Criteria

Another set of criteria for developing a research question was proposed by Hulley (2013) and is known as the FINER criteria. 

FINER stands for:

Feasible – Writing a feasible research question means that it CAN be answered under objective aspects like time, scope, resources, expertise, or funding. Good questions must be amenable to the formulation of clear hypotheses.

Interesting – The question or topic should be of interest to the researcher and the outside world. It should have a clinical and/or educational significance – the “so what?” factor. 

Novel – In scientific literature, novelty defines itself by being an answer to an existing gap in knowledge. Filling one of these gaps is highly rewarding for any researcher as it may represent a real difference in peoples’ lives.

Good research leads to new information. An investigation which simply reiterates what is previously proven is not worth the effort and cost. A question doesn’t have to be completely original. It may ask whether an earlier observation could be replicated, whether the results in one population also apply to others, or whether enhanced measurement methods can make clear the relationship between two variables.  

Ethical – In empirical research, ethics is an absolute MUST. Make sure that safety and confidentiality measures are addressed, and according to the necessary IRB protocols.

Relevant – An idea that is considered relevant in the healthcare community has better chances to be discussed upon by a larger number of researchers and recognized experts, leading to innovation and rapid information dissemination.

The results could potentially be important and may change current ideas and/or practice.

Cummings, S.R., Browner, W.S., & Hulley, S.B. (2013). Conceiving the research question and developing the study plan. In: Designing clinical research (Hulley, S. R. Cummings, W. S. Browner, D. Grady, & T. B. Newman, Eds.; Fourth edition.). Wolters Kluwer/Lippincott Williams & Wilkins. Pp. 14-22.    

• << Previous: Major Steps in a Literature Search
• Next: Types of Research Questions >>

What is Research Design? Characteristics, Types, Process, & Examples

Link Copied

Share on Facebook

Share on Twitter

Share on LinkedIn

Your search has come to an end!

Ever felt like a hamster on a research wheel fast, spinning with a million questions but going nowhere? You've got your topic; you're brimming with curiosity, but... what next? Think of it as your roadmap, ensuring you don't end up lost in a sea of confusing data. So, forget the research rut and get your papers! This ultimate guide to "what is research design?" will have you navigating your project like a pro, uncovering answers and avoiding dead ends. Know the features of good research design, what you mean by research design, elements of research design, and more.

What is Research Design?

Before starting with the topic, do you know what is research design in research? Well, research design is the plan that shows how the study will be done. This plan covers everything from how data will be collected to how it will be analysed. A good research design has a clear question to answer, a detailed plan for gathering information, and a way to make sense of the findings. A good research design has three key ingredients:

1. A clear question: What exactly are you trying to learn? ‍

2. Data collection: How will you gather information (surveys, interviews, experiments)?

3. Analysis: How will you make sense of the data you collect?

Elements of Research Design 

Now that you know what is research design, it is important to know the elements. The elements or components of research design help to ensure that it is reliable, valid and can yield meaningful results. They also provide a guide for the research process, helping the researcher from the initial stages of formulating the research question to the final stages of interpreting the findings. 

1. Purpose Statement: This is a clear and concise statement of the research objectives and the specific goals the research aims to achieve.

2. Research Questions: These are the specific questions the research aims to answer.

3. Research Methodology: This refers to the overall approach and specific methods used to collect and analyse data.

4. Data Collection Methods: These are the specific techniques used to gather data for the research.

5. Data Analysis Techniques: These are the methods used to analyse and interpret the collected data.

6. Units of Analysis: These are the specific entities (e.g., individuals, groups, organisations) that the research focuses on.

7. Linking Data to Propositions: This involves connecting the data collected to the research questions or hypotheses.

8. Interpretation of Findings: This involves making sense of the data and drawing conclusions based on the research objectives.

9. Possible Obstacles to the Research: This involves identifying potential challenges or issues that may arise during the research process.

10. Settings for Research Study: This refers to the context or environment in which the research is conducted.

11. Time of the Research Study: This refers to the timeframe of the research, whether it’s cross-sectional (at one specific point in time) or longitudinal (over an extended period).

Characteristics of Research Design

Research design has several key characteristics that contribute to the validity, reliability, and overall success of a research study. To know the answer for what is research design, it is important to know the characteristics. These are-

1. Reliability: A reliable research design ensures that each study’s results are accurate and can be replicated. This means that if the research is conducted again under the same conditions, it should yield similar results.

2. Validity: A valid research design uses appropriate measuring tools to gauge the results according to the research objective. This ensures that the data collected and the conclusions drawn are relevant and accurately reflect the phenomenon being studied.

3. Neutrality: A neutral research design ensures that the assumptions made at the beginning of the research are free from bias. This means that the data collected throughout the research is based on these unbiased assumptions.

4. Generalizability: A good research design draws an outcome that can be applied to a large set of people and is not limited to the sample size or the research group.

Got a hang of research, now book yout student accommodation with one click!

Book through amber today!

The Process of Research Design

What is research design? A good research helps you do a really good study that gives fair, trustworthy, and useful results. But it's also good to have a bit of wiggle room for changes. If you’re wondering how to conduct a research in just 5 mins , here's a breakdown and examples to work even better.

Step 1: Establish Priorities for Research Design: 

Before conducting any research study, you must address an important question: "what is research design and how to create one?" For example, if you're researching the impact of remote learning on student performance, your priority might be to establish a clear research question and objectives.

Step 2: Choose your Data Type you Need for Research

One of the best features of research design is to decide on the type of data you need for your research. For instance, if you’re studying the effects of a new drug, you might need quantitative data like clinical trial results.

There are lots of ways to answer your research questions. Think about what you want to achieve before you decide how to do your research. The first thing, do you know what is qualitative research design and what is quantitative research design? Here's a quick difference between the two:

What is Research Design in Quantitative Research?

There are 4 main types of quantitative research design- 

What are Research Design Examples?

1. Experimental Research Methods: 

Drug Efficacy Study: A pharmaceutical company wants to test the effectiveness of a new drug. They randomly assign participants to two groups: one group receives the new drug (experimental group), and the other group receives a placebo (control group). The company then measures the health outcomes of the two groups.

2. Quasi-Experimental Research Methods:

Teaching Method Evaluation: A researcher is interested in the impact of a new teaching method. A group of students are taught using the new method, while another group is taught using the traditional method. The researcher then compares the academic performance of the two groups.

3. Descriptive Research Methods:

Consumer Behavior Survey: A company wants to understand the shopping habits of their customers. They conduct a survey asking customers about their shopping frequency, preferred products, and reasons for their preferences.

4. Correlational Research Methods:

Health and Lifestyle Study: A health researcher is interested in the relationship between physical activity levels and heart disease. They collect data on the physical activity levels and heart health of a large group of people over several years. The researcher then analyses the data to see if there is a correlation between physical activity and heart disease

What is Qualitative Research Design?

Qualitative research designs are more flexible and open-ended. They're all about deeply understanding a particular situation or topic, and you have room to be imaginative and adaptable in planning your study. Below, you'll find a list of typical qualitative research designs.

Step 3: Decide your Data Collection Techniques

Now that you understand what is research design in research, you should also know the types of what are the different types of research design techniques. Choose the methods you’ll use to gather your data. If you’re surveying consumer behaviour, for example, you might use questionnaires or interviews.

Survey methods

Surveys are like questionnaires or interviews where you ask people about what they think, do, feel, or are like. They help you gather information straight from the source. So, when you're planning a research project, you can pick either questionnaires or interviews as your main way to get data. Research design is just the plan you make for how you're going to do your research, including what methods you'll use, like surveys.

Observation methods

Observational studies are a way to gather information without bothering anyone. You just watch and note down what you see, like people's actions or how they interact, without asking them directly. You can do this right then and there, jotting down stuff, or you can record videos to check out later. Depending on what you're studying, these observations can focus on describing things or counting them up.

Secondary Data

If you can't gather data yourself, you can use info already collected by other researchers, like from government surveys or past studies. You can then analyse this data to explore new questions. This can broaden your research because you might access bigger and more diverse samples. But, since you didn't collect the data yourself, you can't choose what to measure or how, which limits your conclusions.

In simple terms, research design is about how you plan to gather and analyse data to answer your research questions. If you can't collect data directly, you might use data already gathered by others, known as secondary data, to still answer your questions.

Step 4: Sort Out your Data Analysis

When you find what research design in research, just having a bunch of raw data isn't enough to answer your questions. You also need to figure out how you're going to make sense of that data. This is where research design comes in.

If you're working with quantitative research, you'll probably use statistics to analyse your data. Statistics help you understand things like how your data is spread out, what the average is, and how different groups compare. For example, you might use tests to see if there's a connection between two things or if one group is different from another.

But if you're dealing with more qualitative research, you'll need a different approach. Instead of crunching numbers, you'll be diving deep into your data, looking for patterns and meanings. You might use methods like thematic analysis or discourse analysis to make sense of it all.

Sampling Procedures

Choosing the right way to pick people for your study is important. But it's not just about that. You also need a solid plan for how you'll reach out and get those people to join in.

Here's what you need to think about:

1. How many people do you need to join to make sure your study is good?

2. What rules will you use to decide who can join and who can't?

3. How will you get in touch with them—by mail, online, phone, or meeting them in person?

4. If you're picking people randomly, it's crucial that everyone who gets chosen actually takes part. How can you make sure most of them do?

If you're not picking people randomly, how will you ensure that your study is unbiased and represents different kinds of people? 

Benefits of Research Design

After learning about what is research design and the process, it is important to know the key benefits of a well-structured research design:

1. Minimises Risk of Errors: A good research design minimises the risk of errors and reduces inaccuracy. It ensures that the study is carried out in the right direction and that all the team members are on the same page.

2. Efficient Use of Resources: It facilitates a concrete research plan for the efficient use of time and resources. It helps the researcher better complete all the tasks, even with limited resources.

3. Provides Direction: The purpose of the research design is to enable the researcher to proceed in the right direction without deviating from the tasks. It helps to identify the major and minor tasks of the study.

4. Ensures Validity and Reliability: A well-designed research enhances the validity and reliability of the findings and allows for the replication of studies by other researchers. The main advantage of a good research design is that it provides accuracy, reliability, consistency, and legitimacy to the research.

5. Facilitates Problem-Solving: A researcher can easily frame the objectives of the research work based on the design of experiments (research design). A good research design helps the researcher find the best solution for the research problems.

6. Better Documentation: It helps in better documentation of the various activities while the project work is going on.

That's it! You've explored all the answers for what is research design in research? Remember, it's not just about picking a fancy method – it's about choosing the perfect tool to answer your burning questions. By carefully considering your goals and resources, you can design a research plan that gathers reliable information and helps you reach clear conclusions. 

Frequently Asked Questions

What are the 4 types of research design, what are the important concepts of research design, what are the 5 components of a research, what are different types of research, what are the 4 major elements of a research design.

Your ideal student home & a flight ticket awaits

Follow us on :

Related Posts

How To Make A Cover Page For An Assignment? An Ultimate Guide

Externship vs Internship - How Does it Differ?

How to Deal with Academic Pressure

Planning to Study Abroad ?

Your ideal student accommodation is a few steps away! Please fill in your details below so we can find you a new home!

We have got your response

amber © 2024. All rights reserved.

4.8/5 on Trustpilot

Rated as "Excellent" • 4800+ Reviews by students

Rated as "Excellent" • 4800+ Reviews by Students

• school Campus Bookshelves
• menu_book Bookshelves
• perm_media Learning Objects
• login Login
• how_to_reg Request Instructor Account
• hub Instructor Commons

Margin Size

• Download Page (PDF)
• Download Full Book (PDF)
• Periodic Table
• Physics Constants
• Scientific Calculator
• Reference & Cite
• Tools expand_more
• Readability

selected template will load here

This action is not available.

9.2: Characteristics of a good research question

• Last updated
• Save as PDF
• Page ID 135132

• Matthew DeCarlo, Cory Cummings, & Kate Agnelli
• Open Social Work Education

\( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

\( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

\( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\)

( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\)

\( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

\( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\)

\( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

\( \newcommand{\Span}{\mathrm{span}}\)

\( \newcommand{\id}{\mathrm{id}}\)

\( \newcommand{\kernel}{\mathrm{null}\,}\)

\( \newcommand{\range}{\mathrm{range}\,}\)

\( \newcommand{\RealPart}{\mathrm{Re}}\)

\( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

\( \newcommand{\Argument}{\mathrm{Arg}}\)

\( \newcommand{\norm}[1]{\| #1 \|}\)

\( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\AA}{\unicode[.8,0]{x212B}}\)

\( \newcommand{\vectorA}[1]{\vec{#1}}      % arrow\)

\( \newcommand{\vectorAt}[1]{\vec{\text{#1}}}      % arrow\)

\( \newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

\( \newcommand{\vectorC}[1]{\textbf{#1}} \)

\( \newcommand{\vectorD}[1]{\overrightarrow{#1}} \)

\( \newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}} \)

\( \newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}} \)

Learning Objectives

Learners will be able to…

• Identify and explain the key features of a good research question
• Explain why it is important for social workers to be focused and clear with the language they use in their research questions

Now that you’ve made sure your working question is empirical, you need to revise that working question into a formal research question. So, what makes a good research question? First, it is generally written in the form of a question. To say that your research question is “the opioid epidemic” or “animal assisted therapy” or “oppression” would not be correct. You need to frame your topic as a question, not a statement. A good research question is also one that is well-focused. A well-focused question helps you tune out irrelevant information and not try to answer everything about the world all at once. You could be the most eloquent writer in your class, or even in the world, but if the research question about which you are writing is unclear, your work will ultimately lack direction.

In addition to being written in the form of a question and being well-focused, a good research question is one that cannot be answered with a simple yes or no. For example, if your interest is in gender norms, you could ask, “Does gender affect a person’s performance of household tasks?” but you will have nothing left to say once you discover your yes or no answer. Instead, why not ask, about the relationship between gender and household tasks. Alternatively, maybe we are interested in how or to what extent gender affects a person’s contributions to housework in a marriage? By tweaking your question in this small way, you suddenly have a much more fascinating question and more to say as you attempt to answer it.

A good research question should also have more than one plausible answer. In the example above, the student who studied the relationship between gender and household tasks had a specific interest in the impact of gender, but she also knew that preferences might be impacted by other factors. For example, she knew from her own experience that her more traditional and socially conservative friends were more likely to see household tasks as part of the female domain, and were less likely to expect their male partners to contribute to those tasks. Thinking through the possible relationships between gender, culture, and household tasks led that student to realize that there were many plausible answers to her questions about  how  gender affects a person’s contribution to household tasks. Because gender doesn’t exist in a vacuum, she wisely felt that she needed to consider other characteristics that work together with gender to shape people’s behaviors, likes, and dislikes. By doing this, the student considered the third feature of a good research question–she thought about relationships between several concepts. While she began with an interest in a single concept—household tasks—by asking herself what other concepts (such as gender or political orientation) might be related to her original interest, she was able to form a question that considered the relationships  among  those concepts.

This student had one final component to consider. Social work research questions must contain a target population. Her study would be very different if she were to conduct it on older adults or immigrants who just arrived in a new country. The target population  is the group of people whose needs your study addresses. Maybe the student noticed issues with household tasks as part of her social work practice with first-generation immigrants, and so she made it her target population. Maybe she wants to address the needs of another community. Whatever the case, the target population should be chosen while keeping in mind social work’s responsibility to work on behalf of marginalized and oppressed groups.

In sum, a good research question generally has the following features:

• It is written in the form of a question
• It is clearly written
• It cannot be answered with “yes” or “no”
• It has more than one plausible answer
• It considers relationships among multiple variables
• It is specific and clear about the concepts it addresses
• It includes a target population

Key Takeaways

• A poorly focused research question can lead to the demise of an otherwise well-executed study.
• Research questions should be clearly worded, consider relationships between multiple variables, have more than one plausible answer, and address the needs of a target population.

Okay, it’s time to write out your first draft of a research question.

• Once you’ve done so, take a look at the checklist in this chapter and see if your research question meets the criteria to be a good one.

Brainstorm whether your research question might be better suited to quantitative or qualitative methods.

• Describe why your question fits better with quantitative or qualitative methods.
• Provide an alternative research question that fits with the other type of research method.

Educational resources and simple solutions for your research journey

What is a Research Problem? Characteristics, Types, and Examples

A research problem is a gap in existing knowledge, a contradiction in an established theory, or a real-world challenge that a researcher aims to address in their research. It is at the heart of any scientific inquiry, directing the trajectory of an investigation. The statement of a problem orients the reader to the importance of the topic, sets the problem into a particular context, and defines the relevant parameters, providing the framework for reporting the findings. Therein lies the importance of research problem s.  

The formulation of well-defined research questions is central to addressing a research problem . A research question is a statement made in a question form to provide focus, clarity, and structure to the research endeavor. This helps the researcher design methodologies, collect data, and analyze results in a systematic and coherent manner. A study may have one or more research questions depending on the nature of the study.   

Identifying and addressing a research problem is very important. By starting with a pertinent problem , a scholar can contribute to the accumulation of evidence-based insights, solutions, and scientific progress, thereby advancing the frontier of research. Moreover, the process of formulating research problems and posing pertinent research questions cultivates critical thinking and hones problem-solving skills.   

Table of Contents

What is a Research Problem ?  

Before you conceive of your project, you need to ask yourself “ What is a research problem ?” A research problem definition can be broadly put forward as the primary statement of a knowledge gap or a fundamental challenge in a field, which forms the foundation for research. Conversely, the findings from a research investigation provide solutions to the problem .  

A research problem guides the selection of approaches and methodologies, data collection, and interpretation of results to find answers or solutions. A well-defined problem determines the generation of valuable insights and contributions to the broader intellectual discourse.  

Characteristics of a Research Problem  

Knowing the characteristics of a research problem is instrumental in formulating a research inquiry; take a look at the five key characteristics below:  

Novel : An ideal research problem introduces a fresh perspective, offering something new to the existing body of knowledge. It should contribute original insights and address unresolved matters or essential knowledge.   

Significant : A problem should hold significance in terms of its potential impact on theory, practice, policy, or the understanding of a particular phenomenon. It should be relevant to the field of study, addressing a gap in knowledge, a practical concern, or a theoretical dilemma that holds significance.  

Feasible: A practical research problem allows for the formulation of hypotheses and the design of research methodologies. A feasible research problem is one that can realistically be investigated given the available resources, time, and expertise. It should not be too broad or too narrow to explore effectively, and should be measurable in terms of its variables and outcomes. It should be amenable to investigation through empirical research methods, such as data collection and analysis, to arrive at meaningful conclusions A practical research problem considers budgetary and time constraints, as well as limitations of the problem . These limitations may arise due to constraints in methodology, resources, or the complexity of the problem.  

Clear and specific : A well-defined research problem is clear and specific, leaving no room for ambiguity; it should be easily understandable and precisely articulated. Ensuring specificity in the problem ensures that it is focused, addresses a distinct aspect of the broader topic and is not vague.  

Rooted in evidence: A good research problem leans on trustworthy evidence and data, while dismissing unverifiable information. It must also consider ethical guidelines, ensuring the well-being and rights of any individuals or groups involved in the study.

Types of Research Problems  

Across fields and disciplines, there are different types of research problems . We can broadly categorize them into three types.  

• Theoretical research problems

Theoretical research problems deal with conceptual and intellectual inquiries that may not involve empirical data collection but instead seek to advance our understanding of complex concepts, theories, and phenomena within their respective disciplines. For example, in the social sciences, research problem s may be casuist (relating to the determination of right and wrong in questions of conduct or conscience), difference (comparing or contrasting two or more phenomena), descriptive (aims to describe a situation or state), or relational (investigating characteristics that are related in some way).  

Here are some theoretical research problem examples :   

• Ethical frameworks that can provide coherent justifications for artificial intelligence and machine learning algorithms, especially in contexts involving autonomous decision-making and moral agency.  
• Determining how mathematical models can elucidate the gradual development of complex traits, such as intricate anatomical structures or elaborate behaviors, through successive generations.  
• Applied research problems

Applied or practical research problems focus on addressing real-world challenges and generating practical solutions to improve various aspects of society, technology, health, and the environment.  

Here are some applied research problem examples :   

• Studying the use of precision agriculture techniques to optimize crop yield and minimize resource waste.  
• Designing a more energy-efficient and sustainable transportation system for a city to reduce carbon emissions.  
• Action research problems

Action research problems aim to create positive change within specific contexts by involving stakeholders, implementing interventions, and evaluating outcomes in a collaborative manner.  

Here are some action research problem examples :   

• Partnering with healthcare professionals to identify barriers to patient adherence to medication regimens and devising interventions to address them.  
• Collaborating with a nonprofit organization to evaluate the effectiveness of their programs aimed at providing job training for underserved populations.  

These different types of research problems may give you some ideas when you plan on developing your own.  

How to Define a Research Problem  

You might now ask “ How to define a research problem ?” These are the general steps to follow:   

• Look for a broad problem area: Identify under-explored aspects or areas of concern, or a controversy in your topic of interest. Evaluate the significance of addressing the problem in terms of its potential contribution to the field, practical applications, or theoretical insights.
• Learn more about the problem: Read the literature, starting from historical aspects to the current status and latest updates. Rely on reputable evidence and data. Be sure to consult researchers who work in the relevant field, mentors, and peers. Do not ignore the gray literature on the subject.
• Identify the relevant variables and how they are related: Consider which variables are most important to the study and will help answer the research question. Once this is done, you will need to determine the relationships between these variables and how these relationships affect the research problem . 
• Think of practical aspects : Deliberate on ways that your study can be practical and feasible in terms of time and resources. Discuss practical aspects with researchers in the field and be open to revising the problem based on feedback. Refine the scope of the research problem to make it manageable and specific; consider the resources available, time constraints, and feasibility.
• Formulate the problem statement: Craft a concise problem statement that outlines the specific issue, its relevance, and why it needs further investigation.
• Stick to plans, but be flexible: When defining the problem , plan ahead but adhere to your budget and timeline. At the same time, consider all possibilities and ensure that the problem and question can be modified if needed.

Key Takeaways  

• A research problem concerns an area of interest, a situation necessitating improvement, an obstacle requiring eradication, or a challenge in theory or practical applications.   
• The importance of research problem is that it guides the research and helps advance human understanding and the development of practical solutions.  
• Research problem definition begins with identifying a broad problem area, followed by learning more about the problem, identifying the variables and how they are related, considering practical aspects, and finally developing the problem statement.  
• Different types of research problems include theoretical, applied, and action research problems , and these depend on the discipline and nature of the study.  
• An ideal problem is original, important, feasible, specific, and based on evidence.  

Frequently Asked Questions  

Why is it important to define a research problem?  

Identifying potential issues and gaps as research problems is important for choosing a relevant topic and for determining a well-defined course of one’s research. Pinpointing a problem and formulating research questions can help researchers build their critical thinking, curiosity, and problem-solving abilities.   

How do I identify a research problem?  

Identifying a research problem involves recognizing gaps in existing knowledge, exploring areas of uncertainty, and assessing the significance of addressing these gaps within a specific field of study. This process often involves thorough literature review, discussions with experts, and considering practical implications.  

Can a research problem change during the research process?  

Yes, a research problem can change during the research process. During the course of an investigation a researcher might discover new perspectives, complexities, or insights that prompt a reevaluation of the initial problem. The scope of the problem, unforeseen or unexpected issues, or other limitations might prompt some tweaks. You should be able to adjust the problem to ensure that the study remains relevant and aligned with the evolving understanding of the subject matter.

How does a research problem relate to research questions or hypotheses?  

A research problem sets the stage for the study. Next, research questions refine the direction of investigation by breaking down the broader research problem into manageable components. Research questions are formulated based on the problem , guiding the investigation’s scope and objectives. The hypothesis provides a testable statement to validate or refute within the research process. All three elements are interconnected and work together to guide the research.  

R Discovery is a literature search and research reading platform that accelerates your research discovery journey by keeping you updated on the latest, most relevant scholarly content. With 250M+ research articles sourced from trusted aggregators like CrossRef, Unpaywall, PubMed, PubMed Central, Open Alex and top publishing houses like Springer Nature, JAMA, IOP, Taylor & Francis, NEJM, BMJ, Karger, SAGE, Emerald Publishing and more, R Discovery puts a world of research at your fingertips.  

Try R Discovery Prime FREE for 1 week or upgrade at just US$72 a year to access premium features that let you listen to research on the go, read in your language, collaborate with peers, auto sync with reference managers, and much more. Choose a simpler, smarter way to find and read research – Download the app and start your free 7-day trial today !  

Related Posts

How Publishers Can Enhance Reader Engagement with R Discovery’s Article Recommendation System

Turabian Format: A Beginner’s Guide

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Published: 08 February 2023

Quality research needs good working conditions

• Rima-Maria Rahal   ORCID: orcid.org/0000-0002-1404-0471 1 ,
• Susann Fiedler 2 ,
• Adeyemi Adetula   ORCID: orcid.org/0000-0001-9344-576X 3 , 4 ,
• Ronnie P.-A. Berntsson   ORCID: orcid.org/0000-0001-6848-322X 5 , 6 ,
• Ulrich Dirnagl 7 ,
• Gordon B. Feld   ORCID: orcid.org/0000-0002-1238-9493 8 ,
• Christian J. Fiebach   ORCID: orcid.org/0000-0003-0827-1721 9 ,
• Samsad Afrin Himi   ORCID: orcid.org/0000-0001-6955-1757 10 ,
• Aidan J. Horner   ORCID: orcid.org/0000-0003-0882-9756 11 , 12 ,
• Tina B. Lonsdorf   ORCID: orcid.org/0000-0003-1501-4846 13 ,
• Felix Schönbrodt   ORCID: orcid.org/0000-0002-8282-3910 14 ,
• Miguel Alejandro A. Silan   ORCID: orcid.org/0000-0002-7480-3661 15 , 16 ,
• Michael Wenzler   ORCID: orcid.org/0000-0001-5248-2660 17 &
• Flávio Azevedo   ORCID: orcid.org/0000-0001-9000-8513 18  

Nature Human Behaviour volume  7 ,  pages 164–167 ( 2023 ) Cite this article

31k Accesses

14 Citations

924 Altmetric

Metrics details

High-quality research requires appropriate employment and working conditions for researchers. However, many academic systems rely on short-term employment contracts, biased selection procedures and misaligned incentives, which hinder research quality and progress. We discuss ways to redesign academic systems, emphasizing the role of permanent employment.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

The workplace culture, mental health and wellbeing of early- and mid-career health academics: a cross-sectional analysis

• Claudia H. Marck
• , Darshini Ayton
•  …  Ankur Singh

BMC Public Health Open Access 23 April 2024

Access options

Access Nature and 54 other Nature Portfolio journals

Get Nature+, our best-value online-access subscription

24,99 € / 30 days

cancel any time

Subscribe to this journal

Receive 12 digital issues and online access to articles

111,21 € per year

only 9,27 € per issue

Buy this article

• Purchase on Springer Link
• Instant access to full article PDF

Prices may be subject to local taxes which are calculated during checkout

Bello, M. & Galindo-Rueda, F. Charting the Digital Transformation of Science: Findings from the 2018 OECD International Survey of Scientific Authors (ISSA2) (OECD Science, Technology and Industry Working Papers No. 2020/03) (OECD Publishing, 2020).

IJzerman, H. et al. APS Obs . 34 , www.go.nature.com/3WOu0PJ (2021).

Platt, M. O. Nat. Rev. Mater. 5 , 783–784 (2020).

Article   Google Scholar  

Taris, T. W. & Schaufeli, W. B. in Current Issues in Work and Organizational Psychology (ed. Cooper, C.) 189–204 (Routledge, 2004).

Goodhart, C. (1975). in Monetary Theory and Practice (ed. Goodhart, C.) 91–121 (Macmillan International Higher Education, 1975).

John, L. K., Loewenstein, G. & Prelec, D. Psychol. Sci. 23 , 524–532 (2012).

Article   PubMed   Google Scholar  

Desai, T. A., Eniola-Adefeso, O., Stevens, K. R., Vazquez, M. & Imoukhuede, P. Nat. Rev. Mater. 6 , 556–559 (2021).

Mustajoki, H. et al. Making FAIReR Assessments Possible. Final Report of EOSC Co-Creation Projects: ‘European Overview of Career Merit Systems’ and ‘Vision for Research Data in Research Careers’, https://zenodo.org/record/4701375 (2021).

Götz, F. M., Gosling, S. D. & Rentfrow, P. J. Perspect. Psychol. Sci. 17 , 205–215 (2022).

Tiokhin, L., Lakens, D., Smaldinon, P. E. & Panchanathan, K. Preprint at https://doi.org/10.31222/osf.io/juwck (2021).

Allen, L., O’Connell, A. & Kiermer, V. Learn. Publ. 32 , 71–74 (2019).

Vazire, S. Perspect. Psychol. Sci. 13 , 411–417 (2018).

Pownall, M. et al. Scholarsh. Teach. Learn. Psychol. , https://doi.org/10.1037/stl0000307 (2021).

Azevedo, F. et al. BMC Res. Notes 15 , 75 (2022).

Article   PubMed   PubMed Central   Google Scholar  

Lewis, N. A. Jr & Wai, J. Perspect. Psychol. Sci. 16 , 1242–1254 (2021).

Download references

Acknowledgements

This work was conceived in the scope of the German Reproducibility Network ( https://reproducibilitynetwork.de ). We thank F. Henninger for his helpful comments, and L. Wagner and B. Heling for their help with formatting the document.

Author information

Authors and affiliations.

Behavioral Law & Economics, Max Planck Institute for Research on Collective Goods, Bonn, Germany

Rima-Maria Rahal

Department Strategy & Innovation, Vienna University of Economics and Business, Vienna, Austria

Susann Fiedler

Department of Psychology, Alex Ekwueme Federal University Ndufu-Alike, Abakaliki, Nigeria

Adeyemi Adetula

Laboratoire Interuniversitaire de Psychologie, Personnalité, Cognition, Changement Social, Université Grenoble Alpes, Grenoble, France

Department of Medical Biochemistry and Biophysics, Umeå University, Umeå, Sweden

Ronnie P.-A. Berntsson

Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden

QUEST Center for Responsible Research, Berlin Institute of Health, Berlin, Germany

Ulrich Dirnagl

Central Institute of Mental Health, Heidelberg University, Mannheim, Germany

Gordon B. Feld

Department of Psychology, Goethe University Frankfurt, Frankfurt am Main, Germany

Christian J. Fiebach

Department of Psychology, Jagannath University, Dhaka, Bangladesh

Samsad Afrin Himi

Department of Psychology, University of York, York, UK

Aidan J. Horner

York Biomedical Research Institute, University of York, York, UK

Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

Tina B. Lonsdorf

Department of Psychology, LMU Munich, München, Germany

Felix Schönbrodt

Development, Individual, Process, Handicap, Education (DIPHE) Research Unit, Université Lumière Lyon 2, Lyon, France

Miguel Alejandro A. Silan

Annecy Behavioral Science Lab, Menthon-Saint-Bernard, France

Tübingen, Germany

Michael Wenzler

Department of Psychology, University of Cambridge, Cambridge, UK

Flávio Azevedo

You can also search for this author in PubMed   Google Scholar

Contributions

R.M.R., S.F., U.D. and C.J.F. conceived the work. R.M.R. wrote the original draft, and R.M.R., S.F., F.A., G.B.F., U.D., C.J.F., F.S., T.B.L., M.W., A.J.H., A.A., M.A.A.S., S.A.H. and R.P.A.B. reviewed and edited the Comment.

Corresponding author

Correspondence to Rima-Maria Rahal .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Supplementary information

Supplementary information.

Supplementary Discussion, and Supplementary Figure 1

Rights and permissions

Reprints and permissions

About this article

Cite this article.

Rahal, RM., Fiedler, S., Adetula, A. et al. Quality research needs good working conditions. Nat Hum Behav 7 , 164–167 (2023). https://doi.org/10.1038/s41562-022-01508-2

Download citation

Published : 08 February 2023

Issue Date : February 2023

DOI : https://doi.org/10.1038/s41562-022-01508-2

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

• Darshini Ayton
• Ankur Singh

BMC Public Health (2024)

Five creative ways to promote reproducible science

• Josefina Weinerova
• Rotem Botvinik-Nezer

Nature Human Behaviour (2024)

Rethink funding by putting the lottery first

• Finn Luebber
• Sören Krach
• Jule Specht

Nature Human Behaviour (2023)

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Higher Education News , Tips for Online Students , Tips for Students

A Comprehensive Guide to Different Types of Research

Updated: June 19, 2024

Published: June 15, 2024

When embarking on a research project, selecting the right methodology can be the difference between success and failure. With various methods available, each suited to different types of research, it’s essential you make an informed choice. This blog post will provide tips on how to choose a research methodology that best fits your research goals .

We’ll start with definitions: Research is the systematic process of exploring, investigating, and discovering new information or validating existing knowledge. It involves defining questions, collecting data, analyzing results, and drawing conclusions.

Meanwhile, a research methodology is a structured plan that outlines how your research is to be conducted. A complete methodology should detail the strategies, processes, and techniques you plan to use for your data collection and analysis.

Research Methods

The first step of a research methodology is to identify a focused research topic, which is the question you seek to answer. By setting clear boundaries on the scope of your research, you can concentrate on specific aspects of a problem without being overwhelmed by information. This will produce more accurate findings. 

Along with clarifying your research topic, your methodology should also address your research methods. Let’s look at the four main types of research: descriptive, correlational, experimental, and diagnostic.

Descriptive Research

Descriptive research is an approach designed to describe the characteristics of a population systematically and accurately. This method focuses on answering “what” questions by providing detailed observations about the subject. Descriptive research employs surveys, observational studies , and case studies to gather qualitative or quantitative data. 

A real-world example of descriptive research is a survey investigating consumer behavior toward a competitor’s product. By analyzing the survey results, the company can gather detailed insights into how consumers perceive a competitor’s product, which can inform their marketing strategies and product development.

Correlational Research

Correlational research examines the statistical relationship between two or more variables to determine whether a relationship exists. Correlational research is particularly useful when ethical or practical constraints prevent experimental manipulation. It is often employed in fields such as psychology, education, and health sciences to provide insights into complex real-world interactions, helping to develop theories and inform further experimental research.

An example of correlational research is the study of the relationship between smoking and lung cancer. Researchers observe and collect data on individuals’ smoking habits and the incidence of lung cancer to determine if there is a correlation between the two variables. This type of research helps identify patterns and relationships, indicating whether increased smoking is associated with higher rates of lung cancer.

Experimental Research

Experimental research is a scientific approach where researchers manipulate one or more independent variables to observe their effect on a dependent variable. This method is designed to establish cause-and-effect relationships. Fields like psychology , medicine, and social sciences frequently employ experimental research to test hypotheses and theories under controlled conditions. 

A real-world example of experimental research is Pavlov’s Dog experiment. In this experiment, Ivan Pavlov demonstrated classical conditioning by ringing a bell each time he fed his dogs. After repeating this process multiple times, the dogs began to salivate just by hearing the bell, even when no food was presented. This experiment helped to illustrate how certain stimuli can elicit specific responses through associative learning.

Diagnostic Research

Diagnostic research tries to accurately diagnose a problem by identifying its underlying causes. This type of research is crucial for understanding complex situations where a precise diagnosis is necessary for formulating effective solutions. It involves methods such as case studies and data analysis and often integrates both qualitative and quantitative data to provide a comprehensive view of the issue at hand. 

An example of diagnostic research is studying the causes of a specific illness outbreak. During an outbreak of a respiratory virus, researchers might conduct diagnostic research to determine the factors contributing to the spread of the virus. This could involve analyzing patient data, testing environmental samples, and evaluating potential sources of infection. The goal is to identify the root causes and contributing factors to develop effective containment and prevention strategies.

Using an established research method is imperative, no matter if you are researching for marketing , technology , healthcare , engineering, or social science. A methodology lends legitimacy to your research by ensuring your data is both consistent and credible. A well-defined methodology also enhances the reliability and validity of the research findings, which is crucial for drawing accurate and meaningful conclusions. 

Additionally, methodologies help researchers stay focused and on track, limiting the scope of the study to relevant questions and objectives. This not only improves the quality of the research but also ensures that the study can be replicated and verified by other researchers, further solidifying its scientific value.

How to Choose a Research Methodology

Choosing the best research methodology for your project involves several key steps to ensure that your approach aligns with your research goals and questions. Here’s a simplified guide to help you make the best choice.

Understand Your Goals

Clearly define the objectives of your research. What do you aim to discover, prove, or understand? Understanding your goals helps in selecting a methodology that aligns with your research purpose.

Consider the Nature of Your Data

Determine whether your research will involve numerical data, textual data, or both. Quantitative methods are best for numerical data, while qualitative methods are suitable for textual or thematic data.

Understand the Purpose of Each Methodology

Becoming familiar with the four types of research – descriptive, correlational, experimental, and diagnostic – will enable you to select the most appropriate method for your research. Many times, you will want to use a combination of methods to gather meaningful data. 

Evaluate Resources and Constraints

Consider the resources available to you, including time, budget, and access to data. Some methodologies may require more resources or longer timeframes to implement effectively.

Review Similar Studies

Look at previous research in your field to see which methodologies were successful. This can provide insights and help you choose a proven approach.

By following these steps, you can select a research methodology that best fits your project’s requirements and ensures robust, credible results.

Completing Your Research Project

Upon completing your research, the next critical step is to analyze and interpret the data you’ve collected. This involves summarizing the key findings, identifying patterns, and determining how these results address your initial research questions. By thoroughly examining the data, you can draw meaningful conclusions that contribute to the body of knowledge in your field. 

It’s essential that you present these findings clearly and concisely, using charts, graphs, and tables to enhance comprehension. Furthermore, discuss the implications of your results, any limitations encountered during the study, and how your findings align with or challenge existing theories.

Your research project should conclude with a strong statement that encapsulates the essence of your research and its broader impact. This final section should leave readers with a clear understanding of the value of your work and inspire continued exploration and discussion in the field.

Now that you know how to perform quality research , it’s time to get started! Applying the right research methodologies can make a significant difference in the accuracy and reliability of your findings. Remember, the key to successful research is not just in collecting data, but in analyzing it thoughtfully and systematically to draw meaningful conclusions. So, dive in, explore, and contribute to the ever-growing body of knowledge with confidence. Happy researching!

At UoPeople, our blog writers are thinkers, researchers, and experts dedicated to curating articles relevant to our mission: making higher education accessible to everyone.

Related Articles

• The Scientist University

How to Present a Research Study’s Limitations

All studies have imperfections, but how to present them without diminishing the value of the work can be tricky..

Nathan Ni holds a PhD from Queens University. He is a science editor for The Scientist’s Creative Services Team who strives to better understand and communicate the relationships between health and disease.

View full profile.

Learn about our editorial policies.

Scientists work with many different limitations. First and foremost, they navigate informational limitations, work around knowledge gaps when designing studies, formulating hypotheses, and analyzing data. They also handle technical limitations, making the most of what their hands, equipment, and instruments can achieve. Finally, researchers must also manage logistical limitations. Scientists will often experience sample scarcity, financial issues, or simply be unable to access the technology or materials that they want.

All scientific studies have limitations, and no study is perfect. Researchers should not run from this reality, but engage it directly. It is better to directly address the specific limitations of the work in question, and doing so is actually a way to demonstrate an author’s proficiency and aptitude.

Do: Be Transparent

From a practical perspective, being transparent is the main key to directly addressing the specific limitations of a study. Was there an experiment that the researchers wanted to perform but could not, or a sample that existed that the scientists could not obtain? Was there a piece of knowledge that would explain a question raised by the data presented within the current study? If the answer is yes, the authors should mention this and elaborate upon it within the discussion section.

Asking and addressing these questions demonstrates that the authors have knowledge, understanding, and expertise of the subject area beyond what the study directly investigated. It further demonstrates a solid grasp of the existing literature—which means a solid grasp of what others are doing, what techniques they are using, and what limitations impede their own studies. This information helps the authors contextualize where their study fits within what others have discovered, thereby mitigating the perceived effect of a given limitation on the study’s legitimacy. In essence, this strategy turns limitations, often considered weaknesses, into strengths.

For example, in their 2021 Cell Reports study on macrophage polarization mechanisms, dermatologist Alexander Marneros and colleagues wrote the following. 1

A limitation of studying macrophage polarization in vitro is that this approach only partially captures the tissue microenvironment context in which many different factors affect macrophage polarization. However, it is likely that the identified signaling mechanisms that promote polarization in vitro are also critical for polarization mechanisms that occur in vivo. This is supported by our observation that trametinib and panobinostat inhibited M2-type macrophage polarization not only in vitro but also in skin wounds and laser-induced CNV lesions.

This is a very effective structure. In the first sentence ( yellow ), the authors outlined the limitation. In the next sentence ( green ), they offered a rationalization that mitigates the effect of the limitation. Finally, they provided the evidence ( blue ) for this rationalization, using not just information from the literature, but also data that they obtained in their study specifically for this purpose. 

Don't: Be Defensive

It can feel natural to avoid talking about a study’s limitations. Scientists may believe that mentioning the drawbacks still present in their study will jeopardize their chances of publication. As such, researchers will sometimes skirt around the issue. They will present “boilerplate faults”—generalized concerns about sample size/diversity and time limitations that all researchers face—rather than honestly discussing their own study. Alternatively, they will describe their limitations in a defensive manner, positioning their problems as something that “could not be helped”—as something beyond what science can currently achieve.

However, their audience can see through this, because they are largely peers who understand and have experienced how modern research works. They can tell the difference between global challenges faced by every scientific study and limitations that are specific to a single study. Avoiding these specific limitations can therefore betray a lack of confidence that the study is good enough to withstand problems stemming from legitimate limitations. As such, researchers should actively engage with the greater scientific implications of the limitations that they face. Indeed, doing this is actually a way to demonstrate an author’s proficiency and aptitude.

In an example, neurogeneticist Nancy Bonini and colleagues, in their publication in Nature , discussed a question raised by their data that they have elected not to directly investigate in this study, writing “ Among the intriguing questions raised by these data is how senescent glia promote LDs in other glia. ” To show both the legitimacy of the question and how seriously they have considered it, the authors provided a comprehensive summary of the literature in the following seven sentences, offering two hypotheses backed by a combined eight different sources. 2 Rather than shying away from a limitation, they attacked it as something to be curious about and to discuss. This is not just a very effective way of demonstrating their expertise, but it frames the limitation as something that, when overcome, will build upon the present study rather than something that negatively affects the legitimacy of their current findings.

Striking the Right Balance

Scientists have to navigate the fine line between acknowledging the limitations of their study while also not diminishing the effect and value of their own work. To be aware of legitimate limitations and properly assess and dissect them shows a profound understanding of a field, where the study fits within that field, and what the rest of the scientific community are doing and what challenges they face.

All studies are parts of a greater whole. Pretending otherwise is a disservice to the scientific community.

Looking for more information on scientific writing? Check out  The Scientist’ s  TS SciComm  section. Looking for some help putting together a manuscript, a figure, a poster, or anything else?  The Scientist ’s  Scientific Services  may have the professional help that you need.

• He L, et al. Global characterization of macrophage polarization mechanisms and identification of M2-type polarization inhibitors . Cell Rep . 2021;37(5):109955.
• Byrns CN, et al. Senescent glia link mitochondrial dysfunction and lipid accumulation . Nature . 2024.

Dinosaur With Giant, Loki-Like Horns Has the ‘Craziest, Coolest’ Headgear—and Could Be a New Species

The discovery sheds light on the evolution of a surprisingly diverse group of horned dinosaurs in the western United States

Rudy Molinek

Mass Media Fellow, AAAS

In what sounds like a crossover episode between The  Land Before Time and the Marvel Cinematic Universe, paleontologists have uncovered Lokiceratops —a new dinosaur that had an ornate set of horns resembling those worn by the Norse trickster god, Loki .

“If you’re into dinosaurs and you love bizarre headgear on dinosaurs, this is probably the craziest, coolest horned dinosaur to come along in a really long time,”  Joseph Sertich , a paleontologist at the Smithsonian Tropical Research Institute and Colorado State University, says in a video interview with the journal PeerJ .

The creature boasted two horns between its eyes and a spiky frill at the back of its head, which sprouted the largest frill horns ever found on a dinosaur. Weighing in at more than five tons and measuring 22 feet long, Lokiceratops lived about 78 million years ago during the Late Cretaceous.

A commercial paleontologist found the skull of the dinosaur in the arid badlands of northern Montana in 2019, about two miles south of the Canadian border. Then, the Museum of Evolution in Maribo, Denmark, acquired the specimen. Now, after studying the fossil, Sertich and others argue it represents a previously unknown species, dubbed Lokiceratops rangiformis , in a paper published Thursday in  PeerJ .

When Lokiceratops lived, its habitat was a swampy floodplain on the western shores of an inland sea that split North America in two. This area is already noted among paleontologists for its diversity of horned dinosaurs.

“There are four other species of horned dinosaurs known from this particular region,” Sertich tells CNN ’s Jacopo Prisco. “So, when we started working on it, we assumed that it was going to be one of those four—we were completely shocked to find out that it was a totally new species.”

As the fifth horned dinosaur to be found in the same rock formation, the specimen sheds light on the evolution of dinosaur species living in that time and place. These so-called ceratopsids were somewhat isolated from other geographic areas, which might have led to a greater diversity of horn shapes.

The horns of Lokiceratops , impressive as they are, don’t seem to have been used for defense like the nose horn on a Triceratops . The newly discovered species doesn’t have a nose horn at all, suggesting its other headgear was not meant to be protective, writes Will Dunham for Reuters .

Instead, “it’s becoming more clear that [horned dinosaurs] were using these [bony features] as ornaments, in order to attract mates, or intimidate rivals of the same species,” the study’s co-lead author Mark Loewen , a paleontologist at the University of Utah, tells Carolyn Gramling of Science News .

Local populations of female ceratopsids likely developed attractions to different displays of horns, leading to an explosive evolution of headgear variety in the area. “In modern ecosystems, that process has led closely related birds of paradise to develop different displays while sharing ecological niches,” writes Asher Elbein in the New York Times .

Other experts urge caution in naming Lokiceratops as a new species based on its limited remains. Denver Fowler , a paleontologist at the Dickinson Museum in North Dakota who was not involved with the study, tells Science News the Montana specimen could feasibly be a very mature individual of a different species that had its ornamental horns change shape over time. Or, it might represent the gradual evolutionary change of an already described species.

Nevertheless, Fowler tells the Times that “it’s a spectacular specimen, and it absolutely needs to be described. It really helps us to flesh out the fauna.”

In the video interview, Loewen says the field of dinosaur paleontology is still vibrant, and Lokiceratops is evidence of that.

“When I started as a paleontologist, I tended to think all the cool stuff has already been found,” he says in the video. “[But] there really are new lessons to be learned every day and new specimens to be uncovered.”

Get the latest stories in your inbox every weekday.

Rudy Molinek | READ MORE

Rudy Molinek is  Smithsonian  magazine's 2024 AAAS Mass Media Fellow.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Turk J Anaesthesiol Reanim
• v.44(4); 2016 Aug

What is Scientific Research and How Can it be Done?

Scientific researches are studies that should be systematically planned before performing them. In this review, classification and description of scientific studies, planning stage randomisation and bias are explained.

Research conducted for the purpose of contributing towards science by the systematic collection, interpretation and evaluation of data and that, too, in a planned manner is called scientific research: a researcher is the one who conducts this research. The results obtained from a small group through scientific studies are socialised, and new information is revealed with respect to diagnosis, treatment and reliability of applications. The purpose of this review is to provide information about the definition, classification and methodology of scientific research.

Before beginning the scientific research, the researcher should determine the subject, do planning and specify the methodology. In the Declaration of Helsinki, it is stated that ‘the primary purpose of medical researches on volunteers is to understand the reasons, development and effects of diseases and develop protective, diagnostic and therapeutic interventions (method, operation and therapies). Even the best proven interventions should be evaluated continuously by investigations with regard to reliability, effectiveness, efficiency, accessibility and quality’ ( 1 ).

The questions, methods of response to questions and difficulties in scientific research may vary, but the design and structure are generally the same ( 2 ).

Classification of Scientific Research

Scientific research can be classified in several ways. Classification can be made according to the data collection techniques based on causality, relationship with time and the medium through which they are applied.

• Observational
• Experimental
• Descriptive
• Retrospective
• Prospective
• Cross-sectional
• Social descriptive research ( 3 )

Another method is to classify the research according to its descriptive or analytical features. This review is written according to this classification method.

I. Descriptive research

• Case series
• Surveillance studies

II. Analytical research

• Observational studies: cohort, case control and cross- sectional research
• Interventional research: quasi-experimental and clinical research
• Case Report: it is the most common type of descriptive study. It is the examination of a single case having a different quality in the society, e.g. conducting general anaesthesia in a pregnant patient with mucopolysaccharidosis.
• Case Series: it is the description of repetitive cases having common features. For instance; case series involving interscapular pain related to neuraxial labour analgesia. Interestingly, malignant hyperthermia cases are not accepted as case series since they are rarely seen during historical development.
• Surveillance Studies: these are the results obtained from the databases that follow and record a health problem for a certain time, e.g. the surveillance of cross-infections during anaesthesia in the intensive care unit.

Moreover, some studies may be experimental. After the researcher intervenes, the researcher waits for the result, observes and obtains data. Experimental studies are, more often, in the form of clinical trials or laboratory animal trials ( 2 ).

Analytical observational research can be classified as cohort, case-control and cross-sectional studies.

Firstly, the participants are controlled with regard to the disease under investigation. Patients are excluded from the study. Healthy participants are evaluated with regard to the exposure to the effect. Then, the group (cohort) is followed-up for a sufficient period of time with respect to the occurrence of disease, and the progress of disease is studied. The risk of the healthy participants getting sick is considered an incident. In cohort studies, the risk of disease between the groups exposed and not exposed to the effect is calculated and rated. This rate is called relative risk. Relative risk indicates the strength of exposure to the effect on the disease.

Cohort research may be observational and experimental. The follow-up of patients prospectively is called a prospective cohort study . The results are obtained after the research starts. The researcher’s following-up of cohort subjects from a certain point towards the past is called a retrospective cohort study . Prospective cohort studies are more valuable than retrospective cohort studies: this is because in the former, the researcher observes and records the data. The researcher plans the study before the research and determines what data will be used. On the other hand, in retrospective studies, the research is made on recorded data: no new data can be added.

In fact, retrospective and prospective studies are not observational. They determine the relationship between the date on which the researcher has begun the study and the disease development period. The most critical disadvantage of this type of research is that if the follow-up period is long, participants may leave the study at their own behest or due to physical conditions. Cohort studies that begin after exposure and before disease development are called ambidirectional studies . Public healthcare studies generally fall within this group, e.g. lung cancer development in smokers.

• Case-Control Studies: these studies are retrospective cohort studies. They examine the cause and effect relationship from the effect to the cause. The detection or determination of data depends on the information recorded in the past. The researcher has no control over the data ( 2 ).

Cross-sectional studies are advantageous since they can be concluded relatively quickly. It may be difficult to obtain a reliable result from such studies for rare diseases ( 2 ).

Cross-sectional studies are characterised by timing. In such studies, the exposure and result are simultaneously evaluated. While cross-sectional studies are restrictedly used in studies involving anaesthesia (since the process of exposure is limited), they can be used in studies conducted in intensive care units.

• Quasi-Experimental Research: they are conducted in cases in which a quick result is requested and the participants or research areas cannot be randomised, e.g. giving hand-wash training and comparing the frequency of nosocomial infections before and after hand wash.
• Clinical Research: they are prospective studies carried out with a control group for the purpose of comparing the effect and value of an intervention in a clinical case. Clinical study and research have the same meaning. Drugs, invasive interventions, medical devices and operations, diets, physical therapy and diagnostic tools are relevant in this context ( 6 ).

Clinical studies are conducted by a responsible researcher, generally a physician. In the research team, there may be other healthcare staff besides physicians. Clinical studies may be financed by healthcare institutes, drug companies, academic medical centres, volunteer groups, physicians, healthcare service providers and other individuals. They may be conducted in several places including hospitals, universities, physicians’ offices and community clinics based on the researcher’s requirements. The participants are made aware of the duration of the study before their inclusion. Clinical studies should include the evaluation of recommendations (drug, device and surgical) for the treatment of a disease, syndrome or a comparison of one or more applications; finding different ways for recognition of a disease or case and prevention of their recurrence ( 7 ).

Clinical Research

In this review, clinical research is explained in more detail since it is the most valuable study in scientific research.

Clinical research starts with forming a hypothesis. A hypothesis can be defined as a claim put forward about the value of a population parameter based on sampling. There are two types of hypotheses in statistics.

• H 0 hypothesis is called a control or null hypothesis. It is the hypothesis put forward in research, which implies that there is no difference between the groups under consideration. If this hypothesis is rejected at the end of the study, it indicates that a difference exists between the two treatments under consideration.
• H 1 hypothesis is called an alternative hypothesis. It is hypothesised against a null hypothesis, which implies that a difference exists between the groups under consideration. For example, consider the following hypothesis: drug A has an analgesic effect. Control or null hypothesis (H 0 ): there is no difference between drug A and placebo with regard to the analgesic effect. The alternative hypothesis (H 1 ) is applicable if a difference exists between drug A and placebo with regard to the analgesic effect.

The planning phase comes after the determination of a hypothesis. A clinical research plan is called a protocol . In a protocol, the reasons for research, number and qualities of participants, tests to be applied, study duration and what information to be gathered from the participants should be found and conformity criteria should be developed.

The selection of participant groups to be included in the study is important. Inclusion and exclusion criteria of the study for the participants should be determined. Inclusion criteria should be defined in the form of demographic characteristics (age, gender, etc.) of the participant group and the exclusion criteria as the diseases that may influence the study, age ranges, cases involving pregnancy and lactation, continuously used drugs and participants’ cooperation.

The next stage is methodology. Methodology can be grouped under subheadings, namely, the calculation of number of subjects, blinding (masking), randomisation, selection of operation to be applied, use of placebo and criteria for stopping and changing the treatment.

I. Calculation of the Number of Subjects

The entire source from which the data are obtained is called a universe or population . A small group selected from a certain universe based on certain rules and which is accepted to highly represent the universe from which it is selected is called a sample and the characteristics of the population from which the data are collected are called variables. If data is collected from the entire population, such an instance is called a parameter . Conducting a study on the sample rather than the entire population is easier and less costly. Many factors influence the determination of the sample size. Firstly, the type of variable should be determined. Variables are classified as categorical (qualitative, non-numerical) or numerical (quantitative). Individuals in categorical variables are classified according to their characteristics. Categorical variables are indicated as nominal and ordinal (ordered). In nominal variables, the application of a category depends on the researcher’s preference. For instance, a female participant can be considered first and then the male participant, or vice versa. An ordinal (ordered) variable is ordered from small to large or vice versa (e.g. ordering obese patients based on their weights-from the lightest to the heaviest or vice versa). A categorical variable may have more than one characteristic: such variables are called binary or dichotomous (e.g. a participant may be both female and obese).

If the variable has numerical (quantitative) characteristics and these characteristics cannot be categorised, then it is called a numerical variable. Numerical variables are either discrete or continuous. For example, the number of operations with spinal anaesthesia represents a discrete variable. The haemoglobin value or height represents a continuous variable.

Statistical analyses that need to be employed depend on the type of variable. The determination of variables is necessary for selecting the statistical method as well as software in SPSS. While categorical variables are presented as numbers and percentages, numerical variables are represented using measures such as mean and standard deviation. It may be necessary to use mean in categorising some cases such as the following: even though the variable is categorical (qualitative, non-numerical) when Visual Analogue Scale (VAS) is used (since a numerical value is obtained), it is classified as a numerical variable: such variables are averaged.

Clinical research is carried out on the sample and generalised to the population. Accordingly, the number of samples should be correctly determined. Different sample size formulas are used on the basis of the statistical method to be used. When the sample size increases, error probability decreases. The sample size is calculated based on the primary hypothesis. The determination of a sample size before beginning the research specifies the power of the study. Power analysis enables the acquisition of realistic results in the research, and it is used for comparing two or more clinical research methods.

Because of the difference in the formulas used in calculating power analysis and number of samples for clinical research, it facilitates the use of computer programs for making calculations.

It is necessary to know certain parameters in order to calculate the number of samples by power analysis.

• Type-I (α) and type-II (β) error levels
• Difference between groups (d-difference) and effect size (ES)
• Distribution ratio of groups
• Direction of research hypothesis (H1)

a. Type-I (α) and Type-II (β) Error (β) Levels

Two types of errors can be made while accepting or rejecting H 0 hypothesis in a hypothesis test. Type-I error (α) level is the probability of finding a difference at the end of the research when there is no difference between the two applications. In other words, it is the rejection of the hypothesis when H 0 is actually correct and it is known as α error or p value. For instance, when the size is determined, type-I error level is accepted as 0.05 or 0.01.

Another error that can be made during a hypothesis test is a type-II error. It is the acceptance of a wrongly hypothesised H 0 hypothesis. In fact, it is the probability of failing to find a difference when there is a difference between the two applications. The power of a test is the ability of that test to find a difference that actually exists. Therefore, it is related to the type-II error level.

Since the type-II error risk is expressed as β, the power of the test is defined as 1–β. When a type-II error is 0.20, the power of the test is 0.80. Type-I (α) and type-II (β) errors can be intentional. The reason to intentionally make such an error is the necessity to look at the events from the opposite perspective.

b. Difference between Groups and ES

ES is defined as the state in which statistical difference also has clinically significance: ES≥0.5 is desirable. The difference between groups is the absolute difference between the groups compared in clinical research.

c. Allocation Ratio of Groups

The allocation ratio of groups is effective in determining the number of samples. If the number of samples is desired to be determined at the lowest level, the rate should be kept as 1/1.

d. Direction of Hypothesis (H1)

The direction of hypothesis in clinical research may be one-sided or two-sided. While one-sided hypotheses hypothesis test differences in the direction of size, two-sided hypotheses hypothesis test differences without direction. The power of the test in two-sided hypotheses is lower than one-sided hypotheses.

After these four variables are determined, they are entered in the appropriate computer program and the number of samples is calculated. Statistical packaged software programs such as Statistica, NCSS and G-Power may be used for power analysis and calculating the number of samples. When the samples size is calculated, if there is a decrease in α, difference between groups, ES and number of samples, then the standard deviation increases and power decreases. The power in two-sided hypothesis is lower. It is ethically appropriate to consider the determination of sample size, particularly in animal experiments, at the beginning of the study. The phase of the study is also important in the determination of number of subjects to be included in drug studies. Usually, phase-I studies are used to determine the safety profile of a drug or product, and they are generally conducted on a few healthy volunteers. If no unacceptable toxicity is detected during phase-I studies, phase-II studies may be carried out. Phase-II studies are proof-of-concept studies conducted on a larger number (100–500) of volunteer patients. When the effectiveness of the drug or product is evident in phase-II studies, phase-III studies can be initiated. These are randomised, double-blinded, placebo or standard treatment-controlled studies. Volunteer patients are periodically followed-up with respect to the effectiveness and side effects of the drug. It can generally last 1–4 years and is valuable during licensing and releasing the drug to the general market. Then, phase-IV studies begin in which long-term safety is investigated (indication, dose, mode of application, safety, effectiveness, etc.) on thousands of volunteer patients.

II. Blinding (Masking) and Randomisation Methods

When the methodology of clinical research is prepared, precautions should be taken to prevent taking sides. For this reason, techniques such as randomisation and blinding (masking) are used. Comparative studies are the most ideal ones in clinical research.

Blinding Method

A case in which the treatments applied to participants of clinical research should be kept unknown is called the blinding method . If the participant does not know what it receives, it is called a single-blind study; if even the researcher does not know, it is called a double-blind study. When there is a probability of knowing which drug is given in the order of application, when uninformed staff administers the drug, it is called in-house blinding. In case the study drug is known in its pharmaceutical form, a double-dummy blinding test is conducted. Intravenous drug is given to one group and a placebo tablet is given to the comparison group; then, the placebo tablet is given to the group that received the intravenous drug and intravenous drug in addition to placebo tablet is given to the comparison group. In this manner, each group receives both the intravenous and tablet forms of the drug. In case a third party interested in the study is involved and it also does not know about the drug (along with the statistician), it is called third-party blinding.

Randomisation Method

The selection of patients for the study groups should be random. Randomisation methods are used for such selection, which prevent conscious or unconscious manipulations in the selection of patients ( 8 ).

No factor pertaining to the patient should provide preference of one treatment to the other during randomisation. This characteristic is the most important difference separating randomised clinical studies from prospective and synchronous studies with experimental groups. Randomisation strengthens the study design and enables the determination of reliable scientific knowledge ( 2 ).

The easiest method is simple randomisation, e.g. determination of the type of anaesthesia to be administered to a patient by tossing a coin. In this method, when the number of samples is kept high, a balanced distribution is created. When the number of samples is low, there will be an imbalance between the groups. In this case, stratification and blocking have to be added to randomisation. Stratification is the classification of patients one or more times according to prognostic features determined by the researcher and blocking is the selection of a certain number of patients for each stratification process. The number of stratification processes should be determined at the beginning of the study.

As the number of stratification processes increases, performing the study and balancing the groups become difficult. For this reason, stratification characteristics and limitations should be effectively determined at the beginning of the study. It is not mandatory for the stratifications to have equal intervals. Despite all the precautions, an imbalance might occur between the groups before beginning the research. In such circumstances, post-stratification or restandardisation may be conducted according to the prognostic factors.

The main characteristic of applying blinding (masking) and randomisation is the prevention of bias. Therefore, it is worthwhile to comprehensively examine bias at this stage.

Bias and Chicanery

While conducting clinical research, errors can be introduced voluntarily or involuntarily at a number of stages, such as design, population selection, calculating the number of samples, non-compliance with study protocol, data entry and selection of statistical method. Bias is taking sides of individuals in line with their own decisions, views and ideological preferences ( 9 ). In order for an error to lead to bias, it has to be a systematic error. Systematic errors in controlled studies generally cause the results of one group to move in a different direction as compared to the other. It has to be understood that scientific research is generally prone to errors. However, random errors (or, in other words, ‘the luck factor’-in which bias is unintended-do not lead to bias ( 10 ).

Another issue, which is different from bias, is chicanery. It is defined as voluntarily changing the interventions, results and data of patients in an unethical manner or copying data from other studies. Comparatively, bias may not be done consciously.

In case unexpected results or outliers are found while the study is analysed, if possible, such data should be re-included into the study since the complete exclusion of data from a study endangers its reliability. In such a case, evaluation needs to be made with and without outliers. It is insignificant if no difference is found. However, if there is a difference, the results with outliers are re-evaluated. If there is no error, then the outlier is included in the study (as the outlier may be a result). It should be noted that re-evaluation of data in anaesthesiology is not possible.

Statistical evaluation methods should be determined at the design stage so as not to encounter unexpected results in clinical research. The data should be evaluated before the end of the study and without entering into details in research that are time-consuming and involve several samples. This is called an interim analysis . The date of interim analysis should be determined at the beginning of the study. The purpose of making interim analysis is to prevent unnecessary cost and effort since it may be necessary to conclude the research after the interim analysis, e.g. studies in which there is no possibility to validate the hypothesis at the end or the occurrence of different side effects of the drug to be used. The accuracy of the hypothesis and number of samples are compared. Statistical significance levels in interim analysis are very important. If the data level is significant, the hypothesis is validated even if the result turns out to be insignificant after the date of the analysis.

Another important point to be considered is the necessity to conclude the participants’ treatment within the period specified in the study protocol. When the result of the study is achieved earlier and unexpected situations develop, the treatment is concluded earlier. Moreover, the participant may quit the study at its own behest, may die or unpredictable situations (e.g. pregnancy) may develop. The participant can also quit the study whenever it wants, even if the study has not ended ( 7 ).

In case the results of a study are contrary to already known or expected results, the expected quality level of the study suggesting the contradiction may be higher than the studies supporting what is known in that subject. This type of bias is called confirmation bias. The presence of well-known mechanisms and logical inference from them may create problems in the evaluation of data. This is called plausibility bias.

Another type of bias is expectation bias. If a result different from the known results has been achieved and it is against the editor’s will, it can be challenged. Bias may be introduced during the publication of studies, such as publishing only positive results, selection of study results in a way to support a view or prevention of their publication. Some editors may only publish research that extols only the positive results or results that they desire.

Bias may be introduced for advertisement or economic reasons. Economic pressure may be applied on the editor, particularly in the cases of studies involving drugs and new medical devices. This is called commercial bias.

In recent years, before beginning a study, it has been recommended to record it on the Web site www.clinicaltrials.gov for the purpose of facilitating systematic interpretation and analysis in scientific research, informing other researchers, preventing bias, provision of writing in a standard format, enhancing contribution of research results to the general literature and enabling early intervention of an institution for support. This Web site is a service of the US National Institutes of Health.

The last stage in the methodology of clinical studies is the selection of intervention to be conducted. Placebo use assumes an important place in interventions. In Latin, placebo means ‘I will be fine’. In medical literature, it refers to substances that are not curative, do not have active ingredients and have various pharmaceutical forms. Although placebos do not have active drug characteristic, they have shown effective analgesic characteristics, particularly in algology applications; further, its use prevents bias in comparative studies. If a placebo has a positive impact on a participant, it is called the placebo effect ; on the contrary, if it has a negative impact, it is called the nocebo effect . Another type of therapy that can be used in clinical research is sham application. Although a researcher does not cure the patient, the researcher may compare those who receive therapy and undergo sham. It has been seen that sham therapies also exhibit a placebo effect. In particular, sham therapies are used in acupuncture applications ( 11 ). While placebo is a substance, sham is a type of clinical application.

Ethically, the patient has to receive appropriate therapy. For this reason, if its use prevents effective treatment, it causes great problem with regard to patient health and legalities.

Before medical research is conducted with human subjects, predictable risks, drawbacks and benefits must be evaluated for individuals or groups participating in the study. Precautions must be taken for reducing the risk to a minimum level. The risks during the study should be followed, evaluated and recorded by the researcher ( 1 ).

After the methodology for a clinical study is determined, dealing with the ‘Ethics Committee’ forms the next stage. The purpose of the ethics committee is to protect the rights, safety and well-being of volunteers taking part in the clinical research, considering the scientific method and concerns of society. The ethics committee examines the studies presented in time, comprehensively and independently, with regard to ethics and science; in line with the Declaration of Helsinki and following national and international standards concerning ‘Good Clinical Practice’. The method to be followed in the formation of the ethics committee should be developed without any kind of prejudice and to examine the applications with regard to ethics and science within the framework of the ethics committee, Regulation on Clinical Trials and Good Clinical Practice ( www.iku.com ). The necessary documents to be presented to the ethics committee are research protocol, volunteer consent form, budget contract, Declaration of Helsinki, curriculum vitae of researchers, similar or explanatory literature samples, supporting institution approval certificate and patient follow-up form.

Only one sister/brother, mother, father, son/daughter and wife/husband can take charge in the same ethics committee. A rector, vice rector, dean, deputy dean, provincial healthcare director and chief physician cannot be members of the ethics committee.

Members of the ethics committee can work as researchers or coordinators in clinical research. However, during research meetings in which members of the ethics committee are researchers or coordinators, they must leave the session and they cannot sign-off on decisions. If the number of members in the ethics committee for a particular research is so high that it is impossible to take a decision, the clinical research is presented to another ethics committee in the same province. If there is no ethics committee in the same province, an ethics committee in the closest settlement is found.

Thereafter, researchers need to inform the participants using an informed consent form. This form should explain the content of clinical study, potential benefits of the study, alternatives and risks (if any). It should be easy, comprehensible, conforming to spelling rules and written in plain language understandable by the participant.

This form assists the participants in taking a decision regarding participation in the study. It should aim to protect the participants. The participant should be included in the study only after it signs the informed consent form; the participant can quit the study whenever required, even when the study has not ended ( 7 ).

Peer-review: Externally peer-reviewed.

Author Contributions: Concept - C.Ö.Ç., A.D.; Design - C.Ö.Ç.; Supervision - A.D.; Resource - C.Ö.Ç., A.D.; Materials - C.Ö.Ç., A.D.; Analysis and/or Interpretation - C.Ö.Ç., A.D.; Literature Search - C.Ö.Ç.; Writing Manuscript - C.Ö.Ç.; Critical Review - A.D.; Other - C.Ö.Ç., A.D.

Conflict of Interest: No conflict of interest was declared by the authors.

Financial Disclosure: The authors declared that this study has received no financial support.

• SUGGESTED TOPICS
• The Magazine
• Newsletters
• Managing Yourself
• Managing Teams
• Work-life Balance
• The Big Idea
• Data & Visuals
• Reading Lists
• Case Selections
• HBR Learning
• Topic Feeds
• Account Settings
• Email Preferences

How to Make a “Good” Presentation “Great”

• Guy Kawasaki

Remember: Less is more.

A strong presentation is so much more than information pasted onto a series of slides with fancy backgrounds. Whether you’re pitching an idea, reporting market research, or sharing something else, a great presentation can give you a competitive advantage, and be a powerful tool when aiming to persuade, educate, or inspire others. Here are some unique elements that make a presentation stand out.

• Fonts: Sans Serif fonts such as Helvetica or Arial are preferred for their clean lines, which make them easy to digest at various sizes and distances. Limit the number of font styles to two: one for headings and another for body text, to avoid visual confusion or distractions.
• Colors: Colors can evoke emotions and highlight critical points, but their overuse can lead to a cluttered and confusing presentation. A limited palette of two to three main colors, complemented by a simple background, can help you draw attention to key elements without overwhelming the audience.
• Pictures: Pictures can communicate complex ideas quickly and memorably but choosing the right images is key. Images or pictures should be big (perhaps 20-25% of the page), bold, and have a clear purpose that complements the slide’s text.
• Layout: Don’t overcrowd your slides with too much information. When in doubt, adhere to the principle of simplicity, and aim for a clean and uncluttered layout with plenty of white space around text and images. Think phrases and bullets, not sentences.

As an intern or early career professional, chances are that you’ll be tasked with making or giving a presentation in the near future. Whether you’re pitching an idea, reporting market research, or sharing something else, a great presentation can give you a competitive advantage, and be a powerful tool when aiming to persuade, educate, or inspire others.

• Guy Kawasaki is the chief evangelist at Canva and was the former chief evangelist at Apple. Guy is the author of 16 books including Think Remarkable : 9 Paths to Transform Your Life and Make a Difference.

Partner Center

COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK

Research Assistant

• Gertrude H. Sergievsky Center
• Columbia University Medical Center
• Opening on: Jun 18 2024
• Technical Grade 5
• Job Type: Support Staff - Union
• Bargaining Unit: SSA
• Regular/Temporary: Regular
• End Date if Temporary:
• Hours Per Week: 35
• Standard Work Schedule:
• Salary Range: $59,845.49 - $59,845.49 annually

Position Summary

The Research Assistant will work at the Sergievsky Center/Taub Institute in a study of memory, aging and Alzheimer's disease among racially and ethnically diverse adults. The incumbent will perform telephone and in-person interviews and assessments of study participants. 

Responsibilities

• Administering standardized interviews of medical and family history.
• Every-day functioning, neuropsychological testing, and recruitment of research participants for brain donation.
• Assess capacity to consent and obtain informed consent in this minimal risk study following Institutional Review Board policies and regulations.
• Scoring protocols
• Data cleaning
• Xeroxing materials
• Presenting data collected
• Collecting and preparing biological samples
• Perform other related duties and responsibilities as assigned/requested.

This work will take place under the supervision of the principal investigator.

Minimum Qualifications

• Requires a bachelor's degree and at least 1.5 years of related experience or equivalent in education, training and experience.

Other Requirements

• Good organizational and time management skills.
• Excellent oral and written communication, and interpersonal skills.
• Computer skills, ability to conduct chart reviews.
• Must be able to learn and operate research project software.

Equal Opportunity Employer / Disability / Veteran

Columbia University is committed to the hiring of qualified local residents.

Commitment to Diversity 

Columbia university is dedicated to increasing diversity in its workforce, its student body, and its educational programs. achieving continued academic excellence and creating a vibrant university community require nothing less. in fulfilling its mission to advance diversity at the university, columbia seeks to hire, retain, and promote exceptionally talented individuals from diverse backgrounds.  , share this job.

Thank you - we'll send an email shortly.

Other Recently Posted Jobs

Administrative Coordinator

Administrator, program manager of administration.

Refer someone to this job

• ©2022 Columbia University
• Accessibility
• Administrator Log in

Wait! Before you go, are you interested in a career at Columbia University? Sign up here! 

Thank you, for sharing your information. A member of our team will reach out to you soon!

This website uses cookies as well as similar tools and technologies to understand visitors' experiences. By continuing to use this website, you consent to Columbia University's usage of cookies and similar technologies, in accordance with the Columbia University Website Cookie Notice .

• MyU : For Students, Faculty, and Staff

Wen Zhou: First Ph.D to Complete MOT Minor

Congratulations to Wen Zhou , who successfully defended her doctoral thesis last week! Wen is the first Ph.D. candidate to complete TLI's Management of Technology minor. 

She received her B.S. in electrical engineering (instrumentation) from the Nanjing University of Aeronautics and Astronautics, and her M.S. in electrical engineering (RF and Microwave) from the University of Minnesota in 2015 and 2019, respectively. Her research interest includes mm-wave IC design, sensing system, and bioinstrumentation

Q: What did you study for your Ph.D, and what was the subject of your thesis?

A: My major is in Electrical Engineering and the subject of my dissertation is: Phase-Modulated Millimeter-Wave Radar SoCs based on Analog Correlators. My advisor Prof. Yahya Tousi and I proposed an innovative radar architecture for millimeter-wave distributed sensing. We spent six years together developing the theory and the prototype system-on-chips of this proposed idea. We have completed the proof-of-concept design and the qualitative validation, and have reached the point of integrating the POC design into a full-functioning radar sensor module and conducting quantitative evaluations.

Q: What drew you to the Management of Technology minor, and how do you feel it was helpful for you?

Q: After I completed the idea proposition and the system design of my research project, I encountered challenges in project planning and tasks breakdown. Back then, moving from a conceptual idea to the realization on silicon looked overwhelmingly complex. To figure out the pathway from idea to prototype, I started to explore graduate level coursework in project management and found the MOT program. Then after the consultation with MOT faculty, I started taking MOT courses and declared it as the minor.

The MOT program exposed me to the full design cycle of innovation process. I took project-based courses on new product design and business development, product innovation and management, financial accounting and corporate venturing. I also audited courses in organization development and technology policy.

The knowledge I learned from the MOT courses effectively guided the direction of my research. We methodically compiled a list of essential features for a minimum viable system, and then implemented the feature list in our radar system-on-chip design, and successfully demonstrated the functionalities of our designed radar system. In the later phase of the project, when we were working on the refinement of the design, we were also following the guidelines to factor in more practical considerations and focusing on the full-solution delivery. The MOT program also made me aware of the business potential of the project. I have also explored the value proposition and the product-market fit of our research project during my free time.

I strongly believe that MOT should be integrated into graduate level engineering programs. My personal view of the mission of higher education is not only to build technical expertise in specific domains, but also to provide candidates the visions of how to direct our expertise to better serve the communities. The MOT curriculum fills in the gap between the technologies we develop in the lab at the U and the real-life needs.

Q: What are your plans post-Ph.D?

After Ph.D. I will join the R&D lab of Samsung Semiconductor at San Diego to work on mm-Wave system architecture. I believe it is a good match to my technical background and research interest, where hopefully I can make direct contributions to the team from the early design definition stage to the product commercialization stage.    

I will also make the most of the nice weather in San Diego and explore outdoor opportunities. Still, I will definitely miss the lakes in Minnesota. I have not finished my adventures here yet--snowkiting on the lake and entering the sea caves along Lake Superior shoreline on foot are still on my bucket list.

• Future undergraduate students
• Future transfer students
• Future graduate students
• Future international students
• Diversity and Inclusion Opportunities
• Learn abroad
• Living Learning Communities
• Mentor programs
• Programs for women
• Student groups
• Visit, Apply & Next Steps
• Information for current students
• Departments and majors overview
• Departments
• Undergraduate majors
• Graduate programs
• Integrated Degree Programs
• Additional degree-granting programs
• Online learning
• Academic Advising overview
• Academic Advising FAQ
• Academic Advising Blog
• Appointments and drop-ins
• Academic support
• Commencement
• Four-year plans
• Honors advising
• Policies, procedures, and forms
• Career Services overview
• Resumes and cover letters
• Jobs and internships
• Interviews and job offers
• CSE Career Fair
• Major and career exploration
• Graduate school
• Collegiate Life overview
• Scholarships
• Diversity & Inclusivity Alliance
• Anderson Student Innovation Labs
• Information for alumni
• Get engaged with CSE
• Upcoming events
• CSE Alumni Society Board
• Alumni volunteer interest form
• Golden Medallion Society Reunion
• 50-Year Reunion
• Alumni honors and awards
• Outstanding Achievement
• Alumni Service
• Distinguished Leadership
• Honorary Doctorate Degrees
• Nobel Laureates
• Alumni resources
• Alumni career resources
• Alumni news outlets
• CSE branded clothing
• International alumni resources
• Inventing Tomorrow magazine
• Update your info
• CSE giving overview
• Why give to CSE?
• College priorities
• Give online now
• External relations
• Giving priorities
• CSE Dean's Club
• Donor stories
• Impact of giving
• Ways to give to CSE
• Matching gifts
• CSE directories
• Invest in your company and the future
• Recruit our students
• Connect with researchers
• K-12 initiatives
• Diversity initiatives
• Research news
• Give to CSE
• CSE priorities
• Corporate relations
• Information for faculty and staff
• Administrative offices overview
• Office of the Dean
• Academic affairs
• Finance and Operations
• Communications
• Human resources
• Undergraduate programs and student services
• CSE Committees
• CSE policies overview
• Academic policies
• Faculty hiring and tenure policies
• Finance policies and information
• Graduate education policies
• Human resources policies
• Research policies
• Research overview
• Research centers and facilities
• Research proposal submission process
• Research safety
• Award-winning CSE faculty
• National academies
• University awards
• Honorary professorships
• Collegiate awards
• Other CSE honors and awards
• Staff awards
• Performance Management Process
• Work. With Flexibility in CSE
• K-12 outreach overview
• Summer camps
• Outreach events
• Enrichment programs
• Field trips and tours
• CSE K-12 Virtual Classroom Resources
• Educator development
• Sponsor an event