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• Doing Survey Research | A Step-by-Step Guide & Examples

Doing Survey Research | A Step-by-Step Guide & Examples

Published on 6 May 2022 by Shona McCombes . Revised on 10 October 2022.

Survey research means collecting information about a group of people by asking them questions and analysing the results. To conduct an effective survey, follow these six steps:

• Determine who will participate in the survey
• Decide the type of survey (mail, online, or in-person)
• Design the survey questions and layout
• Distribute the survey
• Analyse the responses
• Write up the results

Surveys are a flexible method of data collection that can be used in many different types of research .

Table of contents

What are surveys used for, step 1: define the population and sample, step 2: decide on the type of survey, step 3: design the survey questions, step 4: distribute the survey and collect responses, step 5: analyse the survey results, step 6: write up the survey results, frequently asked questions about surveys.

Surveys are used as a method of gathering data in many different fields. They are a good choice when you want to find out about the characteristics, preferences, opinions, or beliefs of a group of people.

Common uses of survey research include:

• Social research: Investigating the experiences and characteristics of different social groups
• Market research: Finding out what customers think about products, services, and companies
• Health research: Collecting data from patients about symptoms and treatments
• Politics: Measuring public opinion about parties and policies
• Psychology: Researching personality traits, preferences, and behaviours

Surveys can be used in both cross-sectional studies , where you collect data just once, and longitudinal studies , where you survey the same sample several times over an extended period.

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Before you start conducting survey research, you should already have a clear research question that defines what you want to find out. Based on this question, you need to determine exactly who you will target to participate in the survey.

Populations

The target population is the specific group of people that you want to find out about. This group can be very broad or relatively narrow. For example:

• The population of Brazil
• University students in the UK
• Second-generation immigrants in the Netherlands
• Customers of a specific company aged 18 to 24
• British transgender women over the age of 50

Your survey should aim to produce results that can be generalised to the whole population. That means you need to carefully define exactly who you want to draw conclusions about.

It’s rarely possible to survey the entire population of your research – it would be very difficult to get a response from every person in Brazil or every university student in the UK. Instead, you will usually survey a sample from the population.

The sample size depends on how big the population is. You can use an online sample calculator to work out how many responses you need.

There are many sampling methods that allow you to generalise to broad populations. In general, though, the sample should aim to be representative of the population as a whole. The larger and more representative your sample, the more valid your conclusions.

There are two main types of survey:

• A questionnaire , where a list of questions is distributed by post, online, or in person, and respondents fill it out themselves
• An interview , where the researcher asks a set of questions by phone or in person and records the responses

Which type you choose depends on the sample size and location, as well as the focus of the research.

Questionnaires

Sending out a paper survey by post is a common method of gathering demographic information (for example, in a government census of the population).

• You can easily access a large sample.
• You have some control over who is included in the sample (e.g., residents of a specific region).
• The response rate is often low.

Online surveys are a popular choice for students doing dissertation research , due to the low cost and flexibility of this method. There are many online tools available for constructing surveys, such as SurveyMonkey and Google Forms .

• You can quickly access a large sample without constraints on time or location.
• The data is easy to process and analyse.
• The anonymity and accessibility of online surveys mean you have less control over who responds.

If your research focuses on a specific location, you can distribute a written questionnaire to be completed by respondents on the spot. For example, you could approach the customers of a shopping centre or ask all students to complete a questionnaire at the end of a class.

• You can screen respondents to make sure only people in the target population are included in the sample.
• You can collect time- and location-specific data (e.g., the opinions of a shop’s weekday customers).
• The sample size will be smaller, so this method is less suitable for collecting data on broad populations.

Oral interviews are a useful method for smaller sample sizes. They allow you to gather more in-depth information on people’s opinions and preferences. You can conduct interviews by phone or in person.

• You have personal contact with respondents, so you know exactly who will be included in the sample in advance.
• You can clarify questions and ask for follow-up information when necessary.
• The lack of anonymity may cause respondents to answer less honestly, and there is more risk of researcher bias.

Like questionnaires, interviews can be used to collect quantitative data : the researcher records each response as a category or rating and statistically analyses the results. But they are more commonly used to collect qualitative data : the interviewees’ full responses are transcribed and analysed individually to gain a richer understanding of their opinions and feelings.

Next, you need to decide which questions you will ask and how you will ask them. It’s important to consider:

• The type of questions
• The content of the questions
• The phrasing of the questions
• The ordering and layout of the survey

Open-ended vs closed-ended questions

There are two main forms of survey questions: open-ended and closed-ended. Many surveys use a combination of both.

Closed-ended questions give the respondent a predetermined set of answers to choose from. A closed-ended question can include:

• A binary answer (e.g., yes/no or agree/disagree )
• A scale (e.g., a Likert scale with five points ranging from strongly agree to strongly disagree )
• A list of options with a single answer possible (e.g., age categories)
• A list of options with multiple answers possible (e.g., leisure interests)

Closed-ended questions are best for quantitative research . They provide you with numerical data that can be statistically analysed to find patterns, trends, and correlations .

Open-ended questions are best for qualitative research. This type of question has no predetermined answers to choose from. Instead, the respondent answers in their own words.

Open questions are most common in interviews, but you can also use them in questionnaires. They are often useful as follow-up questions to ask for more detailed explanations of responses to the closed questions.

The content of the survey questions

To ensure the validity and reliability of your results, you need to carefully consider each question in the survey. All questions should be narrowly focused with enough context for the respondent to answer accurately. Avoid questions that are not directly relevant to the survey’s purpose.

When constructing closed-ended questions, ensure that the options cover all possibilities. If you include a list of options that isn’t exhaustive, you can add an ‘other’ field.

Phrasing the survey questions

In terms of language, the survey questions should be as clear and precise as possible. Tailor the questions to your target population, keeping in mind their level of knowledge of the topic.

Use language that respondents will easily understand, and avoid words with vague or ambiguous meanings. Make sure your questions are phrased neutrally, with no bias towards one answer or another.

Ordering the survey questions

The questions should be arranged in a logical order. Start with easy, non-sensitive, closed-ended questions that will encourage the respondent to continue.

If the survey covers several different topics or themes, group together related questions. You can divide a questionnaire into sections to help respondents understand what is being asked in each part.

If a question refers back to or depends on the answer to a previous question, they should be placed directly next to one another.

Before you start, create a clear plan for where, when, how, and with whom you will conduct the survey. Determine in advance how many responses you require and how you will gain access to the sample.

When you are satisfied that you have created a strong research design suitable for answering your research questions, you can conduct the survey through your method of choice – by post, online, or in person.

There are many methods of analysing the results of your survey. First you have to process the data, usually with the help of a computer program to sort all the responses. You should also cleanse the data by removing incomplete or incorrectly completed responses.

If you asked open-ended questions, you will have to code the responses by assigning labels to each response and organising them into categories or themes. You can also use more qualitative methods, such as thematic analysis , which is especially suitable for analysing interviews.

Statistical analysis is usually conducted using programs like SPSS or Stata. The same set of survey data can be subject to many analyses.

Finally, when you have collected and analysed all the necessary data, you will write it up as part of your thesis, dissertation , or research paper .

In the methodology section, you describe exactly how you conducted the survey. You should explain the types of questions you used, the sampling method, when and where the survey took place, and the response rate. You can include the full questionnaire as an appendix and refer to it in the text if relevant.

Then introduce the analysis by describing how you prepared the data and the statistical methods you used to analyse it. In the results section, you summarise the key results from your analysis.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviours. It is made up of four or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with five or seven possible responses, to capture their degree of agreement.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyse your data.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analysing data from people using questionnaires.

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Home Market Research

Survey Research: Definition, Examples and Methods

Survey Research is a quantitative research method used for collecting data from a set of respondents. It has been perhaps one of the most used methodologies in the industry for several years due to the multiple benefits and advantages that it has when collecting and analyzing data.

LEARN ABOUT: Behavioral Research

In this article, you will learn everything about survey research, such as types, methods, and examples.

Survey Research Definition

Survey Research is defined as the process of conducting research using surveys that researchers send to survey respondents. The data collected from surveys is then statistically analyzed to draw meaningful research conclusions. In the 21st century, every organization’s eager to understand what their customers think about their products or services and make better business decisions. Researchers can conduct research in multiple ways, but surveys are proven to be one of the most effective and trustworthy research methods. An online survey is a method for extracting information about a significant business matter from an individual or a group of individuals. It consists of structured survey questions that motivate the participants to respond. Creditable survey research can give these businesses access to a vast information bank. Organizations in media, other companies, and even governments rely on survey research to obtain accurate data.

The traditional definition of survey research is a quantitative method for collecting information from a pool of respondents by asking multiple survey questions. This research type includes the recruitment of individuals collection, and analysis of data. It’s useful for researchers who aim to communicate new features or trends to their respondents.

LEARN ABOUT: Level of Analysis Generally, it’s the primary step towards obtaining quick information about mainstream topics and conducting more rigorous and detailed quantitative research methods like surveys/polls or qualitative research methods like focus groups/on-call interviews can follow. There are many situations where researchers can conduct research using a blend of both qualitative and quantitative strategies.

LEARN ABOUT: Survey Sampling

Survey Research Methods

Survey research methods can be derived based on two critical factors: Survey research tool and time involved in conducting research. There are three main survey research methods, divided based on the medium of conducting survey research:

• Online/ Email:   Online survey research is one of the most popular survey research methods today. The survey cost involved in online survey research is extremely minimal, and the responses gathered are highly accurate.
• Phone:  Survey research conducted over the telephone ( CATI survey ) can be useful in collecting data from a more extensive section of the target population. There are chances that the money invested in phone surveys will be higher than other mediums, and the time required will be higher.
• Face-to-face:  Researchers conduct face-to-face in-depth interviews in situations where there is a complicated problem to solve. The response rate for this method is the highest, but it can be costly.

Further, based on the time taken, survey research can be classified into two methods:

• Longitudinal survey research:  Longitudinal survey research involves conducting survey research over a continuum of time and spread across years and decades. The data collected using this survey research method from one time period to another is qualitative or quantitative. Respondent behavior, preferences, and attitudes are continuously observed over time to analyze reasons for a change in behavior or preferences. For example, suppose a researcher intends to learn about the eating habits of teenagers. In that case, he/she will follow a sample of teenagers over a considerable period to ensure that the collected information is reliable. Often, cross-sectional survey research follows a longitudinal study .
• Cross-sectional survey research:  Researchers conduct a cross-sectional survey to collect insights from a target audience at a particular time interval. This survey research method is implemented in various sectors such as retail, education, healthcare, SME businesses, etc. Cross-sectional studies can either be descriptive or analytical. It is quick and helps researchers collect information in a brief period. Researchers rely on the cross-sectional survey research method in situations where descriptive analysis of a subject is required.

Survey research also is bifurcated according to the sampling methods used to form samples for research: Probability and Non-probability sampling. Every individual in a population should be considered equally to be a part of the survey research sample. Probability sampling is a sampling method in which the researcher chooses the elements based on probability theory. The are various probability research methods, such as simple random sampling , systematic sampling, cluster sampling, stratified random sampling, etc. Non-probability sampling is a sampling method where the researcher uses his/her knowledge and experience to form samples.

LEARN ABOUT: Survey Sample Sizes

The various non-probability sampling techniques are :

• Convenience sampling
• Snowball sampling
• Consecutive sampling
• Judgemental sampling
• Quota sampling

Process of implementing survey research methods:

• Decide survey questions:  Brainstorm and put together valid survey questions that are grammatically and logically appropriate. Understanding the objective and expected outcomes of the survey helps a lot. There are many surveys where details of responses are not as important as gaining insights about what customers prefer from the provided options. In such situations, a researcher can include multiple-choice questions or closed-ended questions . Whereas, if researchers need to obtain details about specific issues, they can consist of open-ended questions in the questionnaire. Ideally, the surveys should include a smart balance of open-ended and closed-ended questions. Use survey questions like Likert Scale , Semantic Scale, Net Promoter Score question, etc., to avoid fence-sitting.

LEARN ABOUT: System Usability Scale

• Finalize a target audience:  Send out relevant surveys as per the target audience and filter out irrelevant questions as per the requirement. The survey research will be instrumental in case the target population decides on a sample. This way, results can be according to the desired market and be generalized to the entire population.

LEARN ABOUT:  Testimonial Questions

• Send out surveys via decided mediums:  Distribute the surveys to the target audience and patiently wait for the feedback and comments- this is the most crucial step of the survey research. The survey needs to be scheduled, keeping in mind the nature of the target audience and its regions. Surveys can be conducted via email, embedded in a website, shared via social media, etc., to gain maximum responses.
• Analyze survey results:  Analyze the feedback in real-time and identify patterns in the responses which might lead to a much-needed breakthrough for your organization. GAP, TURF Analysis , Conjoint analysis, Cross tabulation, and many such survey feedback analysis methods can be used to spot and shed light on respondent behavior. Researchers can use the results to implement corrective measures to improve customer/employee satisfaction.

Reasons to conduct survey research

The most crucial and integral reason for conducting market research using surveys is that you can collect answers regarding specific, essential questions. You can ask these questions in multiple survey formats as per the target audience and the intent of the survey. Before designing a study, every organization must figure out the objective of carrying this out so that the study can be structured, planned, and executed to perfection.

LEARN ABOUT: Research Process Steps

Questions that need to be on your mind while designing a survey are:

• What is the primary aim of conducting the survey?
• How do you plan to utilize the collected survey data?
• What type of decisions do you plan to take based on the points mentioned above?

There are three critical reasons why an organization must conduct survey research.

• Understand respondent behavior to get solutions to your queries:  If you’ve carefully curated a survey, the respondents will provide insights about what they like about your organization as well as suggestions for improvement. To motivate them to respond, you must be very vocal about how secure their responses will be and how you will utilize the answers. This will push them to be 100% honest about their feedback, opinions, and comments. Online surveys or mobile surveys have proved their privacy, and due to this, more and more respondents feel free to put forth their feedback through these mediums.
• Present a medium for discussion:  A survey can be the perfect platform for respondents to provide criticism or applause for an organization. Important topics like product quality or quality of customer service etc., can be put on the table for discussion. A way you can do it is by including open-ended questions where the respondents can write their thoughts. This will make it easy for you to correlate your survey to what you intend to do with your product or service.
• Strategy for never-ending improvements:  An organization can establish the target audience’s attributes from the pilot phase of survey research . Researchers can use the criticism and feedback received from this survey to improve the product/services. Once the company successfully makes the improvements, it can send out another survey to measure the change in feedback keeping the pilot phase the benchmark. By doing this activity, the organization can track what was effectively improved and what still needs improvement.

Survey Research Scales

There are four main scales for the measurement of variables:

• Nominal Scale:  A nominal scale associates numbers with variables for mere naming or labeling, and the numbers usually have no other relevance. It is the most basic of the four levels of measurement.
• Ordinal Scale:  The ordinal scale has an innate order within the variables along with labels. It establishes the rank between the variables of a scale but not the difference value between the variables.
• Interval Scale:  The interval scale is a step ahead in comparison to the other two scales. Along with establishing a rank and name of variables, the scale also makes known the difference between the two variables. The only drawback is that there is no fixed start point of the scale, i.e., the actual zero value is absent.
• Ratio Scale:  The ratio scale is the most advanced measurement scale, which has variables that are labeled in order and have a calculated difference between variables. In addition to what interval scale orders, this scale has a fixed starting point, i.e., the actual zero value is present.

Benefits of survey research

In case survey research is used for all the right purposes and is implemented properly, marketers can benefit by gaining useful, trustworthy data that they can use to better the ROI of the organization.

Other benefits of survey research are:

• Minimum investment:  Mobile surveys and online surveys have minimal finance invested per respondent. Even with the gifts and other incentives provided to the people who participate in the study, online surveys are extremely economical compared to paper-based surveys.
• Versatile sources for response collection:  You can conduct surveys via various mediums like online and mobile surveys. You can further classify them into qualitative mediums like focus groups , and interviews and quantitative mediums like customer-centric surveys. Due to the offline survey response collection option, researchers can conduct surveys in remote areas with limited internet connectivity. This can make data collection and analysis more convenient and extensive.
• Reliable for respondents:  Surveys are extremely secure as the respondent details and responses are kept safeguarded. This anonymity makes respondents answer the survey questions candidly and with absolute honesty. An organization seeking to receive explicit responses for its survey research must mention that it will be confidential.

Survey research design

Researchers implement a survey research design in cases where there is a limited cost involved and there is a need to access details easily. This method is often used by small and large organizations to understand and analyze new trends, market demands, and opinions. Collecting information through tactfully designed survey research can be much more effective and productive than a casually conducted survey.

There are five stages of survey research design:

• Decide an aim of the research:  There can be multiple reasons for a researcher to conduct a survey, but they need to decide a purpose for the research. This is the primary stage of survey research as it can mold the entire path of a survey, impacting its results.
• Filter the sample from target population:  Who to target? is an essential question that a researcher should answer and keep in mind while conducting research. The precision of the results is driven by who the members of a sample are and how useful their opinions are. The quality of respondents in a sample is essential for the results received for research and not the quantity. If a researcher seeks to understand whether a product feature will work well with their target market, he/she can conduct survey research with a group of market experts for that product or technology.
• Zero-in on a survey method:  Many qualitative and quantitative research methods can be discussed and decided. Focus groups, online interviews, surveys, polls, questionnaires, etc. can be carried out with a pre-decided sample of individuals.
• Design the questionnaire:  What will the content of the survey be? A researcher is required to answer this question to be able to design it effectively. What will the content of the cover letter be? Or what are the survey questions of this questionnaire? Understand the target market thoroughly to create a questionnaire that targets a sample to gain insights about a survey research topic.
• Send out surveys and analyze results:  Once the researcher decides on which questions to include in a study, they can send it across to the selected sample . Answers obtained from this survey can be analyzed to make product-related or marketing-related decisions.

Survey examples: 10 tips to design the perfect research survey

Picking the right survey design can be the key to gaining the information you need to make crucial decisions for all your research. It is essential to choose the right topic, choose the right question types, and pick a corresponding design. If this is your first time creating a survey, it can seem like an intimidating task. But with QuestionPro, each step of the process is made simple and easy.

Below are 10 Tips To Design The Perfect Research Survey:

• Set your SMART goals:  Before conducting any market research or creating a particular plan, set your SMART Goals . What is that you want to achieve with the survey? How will you measure it promptly, and what are the results you are expecting?
• Choose the right questions:  Designing a survey can be a tricky task. Asking the right questions may help you get the answers you are looking for and ease the task of analyzing. So, always choose those specific questions – relevant to your research.
• Begin your survey with a generalized question:  Preferably, start your survey with a general question to understand whether the respondent uses the product or not. That also provides an excellent base and intro for your survey.
• Enhance your survey:  Choose the best, most relevant, 15-20 questions. Frame each question as a different question type based on the kind of answer you would like to gather from each. Create a survey using different types of questions such as multiple-choice, rating scale, open-ended, etc. Look at more survey examples and four measurement scales every researcher should remember.
• Prepare yes/no questions:  You may also want to use yes/no questions to separate people or branch them into groups of those who “have purchased” and those who “have not yet purchased” your products or services. Once you separate them, you can ask them different questions.
• Test all electronic devices:  It becomes effortless to distribute your surveys if respondents can answer them on different electronic devices like mobiles, tablets, etc. Once you have created your survey, it’s time to TEST. You can also make any corrections if needed at this stage.
• Distribute your survey:  Once your survey is ready, it is time to share and distribute it to the right audience. You can share handouts and share them via email, social media, and other industry-related offline/online communities.
• Collect and analyze responses:  After distributing your survey, it is time to gather all responses. Make sure you store your results in a particular document or an Excel sheet with all the necessary categories mentioned so that you don’t lose your data. Remember, this is the most crucial stage. Segregate your responses based on demographics, psychographics, and behavior. This is because, as a researcher, you must know where your responses are coming from. It will help you to analyze, predict decisions, and help write the summary report.
• Prepare your summary report:  Now is the time to share your analysis. At this stage, you should mention all the responses gathered from a survey in a fixed format. Also, the reader/customer must get clarity about your goal, which you were trying to gain from the study. Questions such as – whether the product or service has been used/preferred or not. Do respondents prefer some other product to another? Any recommendations?

Having a tool that helps you carry out all the necessary steps to carry out this type of study is a vital part of any project. At QuestionPro, we have helped more than 10,000 clients around the world to carry out data collection in a simple and effective way, in addition to offering a wide range of solutions to take advantage of this data in the best possible way.

From dashboards, advanced analysis tools, automation, and dedicated functions, in QuestionPro, you will find everything you need to execute your research projects effectively. Uncover insights that matter the most!

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• Research article
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• Published: 12 September 2013

A survey study of the association between mobile phone use and daytime sleepiness in California high school students

• Nila Nathan 1 &
• Jamie Zeitzer 2 , 3  

BMC Public Health volume  13 , Article number:  840 ( 2013 ) Cite this article

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36 Citations

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Mobile phone use is near ubiquitous in teenagers. Paralleling the rise in mobile phone use is an equally rapid decline in the amount of time teenagers are spending asleep at night. Prior research indicates that there might be a relationship between daytime sleepiness and nocturnal mobile phone use in teenagers in a variety of countries. As such, the aim of this study was to see if there was an association between mobile phone use, especially at night, and sleepiness in a group of U.S. teenagers.

A questionnaire containing an Epworth Sleepiness Scale (ESS) modified for use in teens and questions about qualitative and quantitative use of the mobile phone was completed by students attending Mountain View High School in Mountain View, California (n = 211).

Multivariate regression analysis indicated that ESS score was significantly associated with being female, feeling a need to be accessible by mobile phone all of the time, and a past attempt to reduce mobile phone use. The number of daily texts or phone calls was not directly associated with ESS. Those individuals who felt they needed to be accessible and those who had attempted to reduce mobile phone use were also ones who stayed up later to use the mobile phone and were awakened more often at night by the mobile phone.

Conclusions

The relationship between daytime sleepiness and mobile phone use was not directly related to the volume of texting but may be related to the temporal pattern of mobile phone use.

Peer Review reports

Mobile phone use has drastically increased in recent years, fueled by new technology such as ‘smart phones’. In 2012, it was estimated that 78% of all Americans aged 12–17 years had a mobile phone and 37% had a smart phone [ 1 ]. Despite the growing number of adolescent mobile phone users, there has been limited examination of the behavioral effects of mobile phone usage on adolescents and their sleep and subsequent daytime sleepiness.

Mobile phone use in teens likely compounds the biological causes of sleep loss. With the onset of puberty, there are changes in innate circadian rhythms that lead to a delay in the habitual timing of sleep onset [ 2 ]. As school start times are not correspondingly later, this leads to a reduction in the time available for sleep and is consequently thought to contribute to the endemic sleepiness of teenagers. The use of mobile phones may compound this sleepiness by extending the waking hours further into the night. Munezawa and colleagues [ 3 ] analyzed 94,777 responses to questionnaires sent out to junior and senior high school students in Japan and found that the use of mobile phones for calling or sending text messages after they went to bed was associated with sleep disturbances such as short sleep duration, subjective poor sleep quality, excessive daytime sleepiness and insomnia symptoms. Soderqvist et al. in their study of Swedish adolescents aged 15–19 years, found that regular users of mobile phones reported health symptoms such as tiredness, stress, headache, anxiety, concentration difficulties and sleep disturbances more often than less frequent users [ 4 ]. Van der Bulck studied 1,656 school children in Belgium and found that prevalent mobile phone use in adolescents was related to increased levels of daytime tiredness [ 5 ]. Punamaki et al. studied Finnish teens and found that intensive mobile phone use lead to more health complaints and musculoskeletal symptoms in girls both directly and through deteriorated sleep, as well as increased daytime tiredness [ 6 ]. In one prospective study of young Swedish adults, aged 20–24, those who were high volume mobile phone users and male, but not female, were at greater risk for developing sleep disturbances a year later [ 7 ]. The association of mobile phone utilization and either sleep or sleepiness in teens in the United States has only been described by a telephone poll. In the 2011 National Sleep Foundation poll, 20% of those under the age of 30 reported that they were awakened by a phone call, text or e-mail message at least a few nights a week [ 8 ]. This type of nocturnal awakening was self-reported more frequently by those who also reported that they drove while drowsy.

As there has been limited examination of how mobile phone usage affects the behavior of young children and adolescents, none of which have addressed the effects of such usage on daytime sleepiness in U.S. teens, it seemed worthwhile to attempt a cross-sectional study of sleep and mobile phone utilization in a U.S. high school. As such, it was the purpose of this study to examine the association of mobile phone utilization and sleepiness patterns in a sample of U.S. teens. We hypothesized that an increased number of calls would be associated with increased sleepiness.

We designed a survey that contained questions concerning sleepiness and mobile phone use (see Additional file 1 ). Sleepiness was assessed using a version of the Epworth Sleepiness Scale (ESS) [ 9 ] modified for use in adolescents [ 10 ]. The modified ESS consists of eight questions that assessed the likelihood of dozing in the following circumstances: sitting and reading, watching TV, sitting inactive in a public place, as a passenger in a car for an hour without a break, lying down to rest in the afternoon when circumstances permit, sitting and talking to someone, sitting quietly after a lunch, in a car while stopped for a few minutes in traffic. Responses were limited to a Likert-like scale using the following: no chance of dozing (0), slight chance of dozing (1), moderate chance of dozing (2), or high chance of dozing (3). This yielded total ESS scores ranging from 0 to 24, with scores over 10 being associated with clinically-significant sleepiness [ 9 ]. We also included a set of modified questions, originally designed by Thomée et al., that assess the subjective impact of mobile phone use [ 7 ]. These included the number of mobile calls made or received each day, the number of texts made or received each day, being awakened by the mobile phone at night (never/occasionally/monthly/weekly/daily), staying up late to use the mobile phone (never/occasionally/monthly/weekly/daily), expectations of accessibility by mobile phone (never/occasionally/daily/all day/around-the-clock), stressfulness of accessibility (not at all/a little bit/rather/very), use mobile phone too much (yes/no), and tried and failed to reduce mobile phone use (yes/no).

An email invitation to complete an electronic form of the survey ( http://www.surveymonkey.com ) was sent to the entire student body of the Mountain View High School, located in Mountain View, California, USA, on April 5, 2012. Out of the approximately 2,000 students attending the school, a total of 211 responded by the collection date of April 23, 2012. Data analyses are described below (OrginPro8, OriginLab, Northampton MA). Summary data are provided as mean ± SD for age and ESS and as median (range) for the number of texts and/or phone calls made or received per day as these were non-normally distributed (p’s <; 0.001, Kolmogorov Smirnov test). To examine the relationship between sleepiness and predictor variables, stepwise multivariate regression analyses were performed. Collinearity in the data was examined by calculating the Variance Inflation Factor (VIF). Post hoc t-tests, ANOVA, Mann–Whitney U tests, and Spearman correlations were used, as appropriate, to examine specific components of the model and their relationship to sleepiness. χ 2 tests were used to examine categorical variables. The study was done within the regulations codified by the Declaration of Helsinki and approved by the administration of Mountain View High School.

Sixty-eight males and 143 females responded to the survey. Most (96.7%) respondents owned a mobile phone. The remainder of the analyses presented herein is on the 202 respondents (64 male, 138 female) who indicated that they owned a mobile phone (Tables  1 and 2 ). The youngest participant in the survey was 14 years old and the oldest was 19 years old (16 ± 1.2 years), representative of the age range of this school. The median number of mobile phone calls made or received per day was 2 and ranged from 0 to 60. The median number of text messages sent or received per day was 22.5 and ranged from 0 to 700. While about half of the respondents (53%) had never been awakened by the mobile phone at night, 35% were occasionally awakened, 5.9% were awakened a few times a month, 5.0% were awakened a few times a week, and 1.0% were awakened almost every night. About one-quarter (27%) of respondents had never stayed awake later than a target bedtime in order to use the mobile phone, however 36% occasionally stayed awake, 19% stayed awake a few times a month, 8.5% stayed awake a few times a week, and 10% stayed awake almost every night in order to use the mobile phone. In regards to feeling an expectation of accessibility, 7.5% reported that they needed to be accessible around the clock, 26% reported that they needed to be accessible all day, 52% reported they needed to be accessible daily, 13% reported that they only needed to be accessible now and then, and 1.0% reported they never needed to be accessible. Nearly half (49%) of the survey participants viewed accessibility via mobile phones to be not at all stressful, 45% found it to be a little bit stressful, 4.5% found it rather stressful, and 1.0% found it very stressful. More than one-third (36%) reported that they or someone close to them thought that they used the mobile phone too much. Few (17%) had tried but were unable to reduce their mobile phone use.

Subjective sleepiness on the ESS ranged from 0 to 18 (6.8 ± 3.5, with higher numbers indicating greater sleepiness), with 25% of participants having ESS scores in the excessively sleepy range (ESS ≥ 10). We examined predictors of subjective sleepiness (ESS score) using stepwise multivariate regression analysis with the following independent variables: age, sex, frequency of nocturnal awakening by the phone, frequency of staying up too late to use the phone, self-perceived accessibility by phone, stressfulness of this accessibility, attempted and failed to reduce phone use, excessive phone use determined by others, number of texts per day, and number of phone calls per day. Only subjects with complete data sets were used in our modeling (n = 191 of 202). Our final model (Table  3 ) indicated that sex, frequency of accessibility, and a failed attempt to reduce mobile phone use were all predictive of daytime sleepiness (F 6,194  = 4.35, p <; 0.001, r 2  = 0.12). These model variables lacked collinearity (VIF’s <; 3.9), indicating that they were not likely to represent the same source of variance. Despite the lack of significance in the multivariate model, given previously published data [ 4 – 6 ], we independently tested if there was a relationship between the number of estimated texts and sleepiness, but found no such correlation (r = 0.13, p = 0.07; Spearman correlation). In examining the final model, it appears that those who felt that they needed to be accessible “around the clock” (ESS = 9.2 ± 2.9) were sleepier than all others (ESS = 6.7 ± 3.4) (p <; 0.01, post hoc t -test). The relationship between sleepiness and reporting having tried, but failed, to reduce mobile phone use was such that those who had tried to reduce phone use were more sleepy (ESS = 8.3 ± 3.6) than those who had not (ESS = 6.5 ± 3.4) (p <; 0.01, post hoc t -test). While more females had tried to reduce their mobile phone use, sex did not modify the relationship between the attempt to reduce mobile phone use and sleepiness (p = 0.32, two-way ANOVA), thus retaining attempt and failure to reduce mobile phone use as an independent modifier of ESS scores.

In an attempt to better understand the relationship between ESS and accessibility, we parsed the population into those who felt that they needed to be accessible around the clock (7.4%) and those who did not (92.6%). The most accessible group, as compared to the less accessible group, had a numerically though not statistically significantly higher texting rate (50 vs. 20 per day; p = 0.07, Mann–Whitney U test), but were awakened more at night by the phone (27% vs. 4%, weekly or daily; p <; 0.05, χ 2 test), and stayed awake later than desired more often (40% vs. 17%, weekly or daily; p <; 0.05, χ 2 test). We did a similar analysis, parsing the population into those who had attempted but failed to reduce their use of their mobile phone (17%) with those who had not (83%). Those who had attempted to reduce their mobile phone use had a higher texting rate (60 vs. 20 per day; p <; 0.01, Mann–Whitney U test) and stayed awake later than desired more often (53% vs. 11%, weekly or daily; p <; 0.01, χ 2 test), but were not awakened more at night by the phone (12% vs. 5%, weekly or daily; p = 0.26, χ 2 test).

Given previous research on the topic, our a priori hypothesis was that teenagers who use their phone more often at night are likely to be more prone to daytime sleepiness. We did not, however, observe this simple relationship in this sample of U.S. teens. We did find that being female, perceived need to be accessible by mobile phone, and having tried but failed to reduce mobile phone usage were all predictive of daytime sleepiness, with the latter two likely being moderated by increased use of the phone at night. Previous work has shown that being female was associated with higher ESS scores [ 11 ]. It may be that adolescent females score higher on the ESS without being objectively sleepier, though this remains to be tested. Our analyses revealed that staying up late to use the mobile phone and being awakened by the mobile phone may be involved in the relationship between increased ESS scores and perceived need to be accessible by mobile phone and a past attempt to decrease mobile phone use. These analyses reveal some of the complexity of assessing daytime sleepiness, which is undoubtedly multifactorial. If the sheer number of text messages being sent per day is directly associated daytime sleepiness, it is likely with a small effect size. Our work, of course, is not without its limitations. Data were collected from a sample of convenience at a single, public high school in California. Only 10% of students responded to the survey and this may have introduced some response bias to the data. The data collected were cross-sectional; a longitudinal collection would have enabled a more precise analysis of moderators and mediators as well as a more accurate interpretation of causal relationships. Also, we did not objectively record the number of texts, so there may be a certain degree of bias or uncertainty associated with self-report of number of texts and calls. Several variables that might influence sleepiness both directly and indirectly through mobile phone use (e.g., socioeconomic status, comorbid sleep disorders, medication use) were not assessed. Future studies on the impact of mobile phone use on sleep and sleepiness should take into account the multifactorial and temporal nature of these behaviors.

The endemic sleepiness found in adolescents is multifactorial with both intrinsic and extrinsic factors. Mobile phone use has been assumed to be one source of increased daytime sleepiness in adolescents. Our analyses revealed that use or perceived need of use of the mobile phone during normal sleeping hours may contribute to daytime sleepiness. As overall number of text messages did not significantly contribute to daytime sleepiness, it is possible that a temporal rearrangement of phone use (e.g., limiting phone use during prescribed sleeping hours) might help in alleviating some degree of daytime sleepiness.

Abbreviations

Epworth sleepiness scale

Standard deviation

Analysis of variance.

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The authors wish to thank the students of Mountain View High School (Mountain View, California) for participating in this study.

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Nila Nathan

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Jamie Zeitzer

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Nathan, N., Zeitzer, J. A survey study of the association between mobile phone use and daytime sleepiness in California high school students. BMC Public Health 13 , 840 (2013). https://doi.org/10.1186/1471-2458-13-840

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How to Write a Survey Paper: Brief Overview

Every student wishes there was a shortcut to learning about a subject. Writing a survey paper can be an effective tool for synthesizing and consolidating information on a particular topic to gain mastery over it.

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At this point, you have already undertaken half of the job. Maybe even more since collecting and analyzing the literature is often the most challenging part of writing a survey paper. Now it's time to organize and structure your paper. Follow the well-established outline, give a thorough review, and compose compelling body paragraphs. Don't forget to include detailed methodology and highlight key findings and revolutionary ideas.

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• Conclusion - a summary of the research conducted and its significance, along with suggestions for further work in this area.
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Title - You need to come up with a clear and concise title that reflects the main objective of your research question.

Survey paper example title: 'The analysis of recommender systems in E-commerce.'

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Introduction - This section is a crucial element of an academic essay and should be intriguing and provide background information on the topic, feeding the readers' curiosity.

Literature with benefits and limitations - This section dives into the existing literature on the research question, including relevant studies and their analyses. When reviewing the literature, it is important to highlight both benefits and limitations of existing studies to identify gaps for future research.

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Future Research Direction - You can either give this a separate section or include it in a conclusion, but you can never overlook the importance of a future research direction. Distinctly point out areas of limitations and suggest possible avenues for future research.

References - Finally, be sure to include a list of all the sources/references you've used in your research. Without a list of references, your work will lose all its credibility and can no longer be beneficial to other researchers.

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After mastering the basics of how to write a good survey paper, there are a few tips to keep in mind. They will help you advance your writing and ensure your survey paper stands out among others.

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When conducting research, one can easily get carried away and start hoarding all available literature, which may not necessarily be relevant to your research question. Make sure to stay within the scope of your topic. Clearly articulate your research question, and then select only literature that directly addresses the research question. A few initial readings might not reveal the relevance, so you need a systematic review and filter of the literature that is directly related to the research question.

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Our team suggests only using up-to-date material that was published within the last 5 years. Additional sources may be used if they contribute significantly to the research question, but it is important to prioritize current literature.

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Having a short and to-the-point research question not only helps the audience understand the direction of your paper but also helps you stay focused on a clear goal. With a clear research question, you will have an easier time selecting the relevant literature, avoiding unnecessary information, and maintaining the structure of your paper.

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• Survey of Evolution and Challenges of Electronic Search Engines
• A Comprehensive Survey Paper on Machine Learning Algorithms
• Survey of Leaf Image Analysis for Plant Species Recognition
• Advances in Natural Language Processing for Sentiment Analysis
• Emerging Trends in Cybersecurity Threat Detection
• A Comprehensive Survey of Techniques in Big Data Analytics in Healthcare
• A Survey of Advances in Digital Art and Virtual Reality
• A Systematic Review of the Impact of Social Media Marketing Strategies on Consumer Behavior
• A Survey of AI Systems in Artistic Expression
• Exploring New Research Methods and Ethical Considerations in Anthropology
• Exploring Data-driven Approaches for Performance Analysis and Decision Making in Sports
• A Survey of Benefits of Optimizing Performance through Diet and Supplementation
• A Critical Review of Existing Research on The Impact of Climate Change on Biodiversity Conservation Strategies
• Investigating the Future of Blockchain Technology for Secure Data Sharing
• A Critical Review of the Literature on Mental Health and Innovation in the Workplace

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Home » Survey Research – Types, Methods, Examples

Survey Research – Types, Methods, Examples

Table of Contents

Survey Research

Definition:

Survey Research is a quantitative research method that involves collecting standardized data from a sample of individuals or groups through the use of structured questionnaires or interviews. The data collected is then analyzed statistically to identify patterns and relationships between variables, and to draw conclusions about the population being studied.

Survey research can be used to answer a variety of questions, including:

• What are people’s opinions about a certain topic?
• What are people’s experiences with a certain product or service?
• What are people’s beliefs about a certain issue?

Survey Research Methods

Survey Research Methods are as follows:

• Telephone surveys: A survey research method where questions are administered to respondents over the phone, often used in market research or political polling.
• Face-to-face surveys: A survey research method where questions are administered to respondents in person, often used in social or health research.
• Mail surveys: A survey research method where questionnaires are sent to respondents through mail, often used in customer satisfaction or opinion surveys.
• Online surveys: A survey research method where questions are administered to respondents through online platforms, often used in market research or customer feedback.
• Email surveys: A survey research method where questionnaires are sent to respondents through email, often used in customer satisfaction or opinion surveys.
• Mixed-mode surveys: A survey research method that combines two or more survey modes, often used to increase response rates or reach diverse populations.
• Computer-assisted surveys: A survey research method that uses computer technology to administer or collect survey data, often used in large-scale surveys or data collection.
• Interactive voice response surveys: A survey research method where respondents answer questions through a touch-tone telephone system, often used in automated customer satisfaction or opinion surveys.
• Mobile surveys: A survey research method where questions are administered to respondents through mobile devices, often used in market research or customer feedback.
• Group-administered surveys: A survey research method where questions are administered to a group of respondents simultaneously, often used in education or training evaluation.
• Web-intercept surveys: A survey research method where questions are administered to website visitors, often used in website or user experience research.
• In-app surveys: A survey research method where questions are administered to users of a mobile application, often used in mobile app or user experience research.
• Social media surveys: A survey research method where questions are administered to respondents through social media platforms, often used in social media or brand awareness research.
• SMS surveys: A survey research method where questions are administered to respondents through text messaging, often used in customer feedback or opinion surveys.
• IVR surveys: A survey research method where questions are administered to respondents through an interactive voice response system, often used in automated customer feedback or opinion surveys.
• Mixed-method surveys: A survey research method that combines both qualitative and quantitative data collection methods, often used in exploratory or mixed-method research.
• Drop-off surveys: A survey research method where respondents are provided with a survey questionnaire and asked to return it at a later time or through a designated drop-off location.
• Intercept surveys: A survey research method where respondents are approached in public places and asked to participate in a survey, often used in market research or customer feedback.
• Hybrid surveys: A survey research method that combines two or more survey modes, data sources, or research methods, often used in complex or multi-dimensional research questions.

Types of Survey Research

There are several types of survey research that can be used to collect data from a sample of individuals or groups. following are Types of Survey Research:

• Cross-sectional survey: A type of survey research that gathers data from a sample of individuals at a specific point in time, providing a snapshot of the population being studied.
• Longitudinal survey: A type of survey research that gathers data from the same sample of individuals over an extended period of time, allowing researchers to track changes or trends in the population being studied.
• Panel survey: A type of longitudinal survey research that tracks the same sample of individuals over time, typically collecting data at multiple points in time.
• Epidemiological survey: A type of survey research that studies the distribution and determinants of health and disease in a population, often used to identify risk factors and inform public health interventions.
• Observational survey: A type of survey research that collects data through direct observation of individuals or groups, often used in behavioral or social research.
• Correlational survey: A type of survey research that measures the degree of association or relationship between two or more variables, often used to identify patterns or trends in data.
• Experimental survey: A type of survey research that involves manipulating one or more variables to observe the effect on an outcome, often used to test causal hypotheses.
• Descriptive survey: A type of survey research that describes the characteristics or attributes of a population or phenomenon, often used in exploratory research or to summarize existing data.
• Diagnostic survey: A type of survey research that assesses the current state or condition of an individual or system, often used in health or organizational research.
• Explanatory survey: A type of survey research that seeks to explain or understand the causes or mechanisms behind a phenomenon, often used in social or psychological research.
• Process evaluation survey: A type of survey research that measures the implementation and outcomes of a program or intervention, often used in program evaluation or quality improvement.
• Impact evaluation survey: A type of survey research that assesses the effectiveness or impact of a program or intervention, often used to inform policy or decision-making.
• Customer satisfaction survey: A type of survey research that measures the satisfaction or dissatisfaction of customers with a product, service, or experience, often used in marketing or customer service research.
• Market research survey: A type of survey research that collects data on consumer preferences, behaviors, or attitudes, often used in market research or product development.
• Public opinion survey: A type of survey research that measures the attitudes, beliefs, or opinions of a population on a specific issue or topic, often used in political or social research.
• Behavioral survey: A type of survey research that measures actual behavior or actions of individuals, often used in health or social research.
• Attitude survey: A type of survey research that measures the attitudes, beliefs, or opinions of individuals, often used in social or psychological research.
• Opinion poll: A type of survey research that measures the opinions or preferences of a population on a specific issue or topic, often used in political or media research.
• Ad hoc survey: A type of survey research that is conducted for a specific purpose or research question, often used in exploratory research or to answer a specific research question.

Types Based on Methodology

Based on Methodology Survey are divided into two Types:

Quantitative Survey Research

Qualitative survey research.

Quantitative survey research is a method of collecting numerical data from a sample of participants through the use of standardized surveys or questionnaires. The purpose of quantitative survey research is to gather empirical evidence that can be analyzed statistically to draw conclusions about a particular population or phenomenon.

In quantitative survey research, the questions are structured and pre-determined, often utilizing closed-ended questions, where participants are given a limited set of response options to choose from. This approach allows for efficient data collection and analysis, as well as the ability to generalize the findings to a larger population.

Quantitative survey research is often used in market research, social sciences, public health, and other fields where numerical data is needed to make informed decisions and recommendations.

Qualitative survey research is a method of collecting non-numerical data from a sample of participants through the use of open-ended questions or semi-structured interviews. The purpose of qualitative survey research is to gain a deeper understanding of the experiences, perceptions, and attitudes of participants towards a particular phenomenon or topic.

In qualitative survey research, the questions are open-ended, allowing participants to share their thoughts and experiences in their own words. This approach allows for a rich and nuanced understanding of the topic being studied, and can provide insights that are difficult to capture through quantitative methods alone.

Qualitative survey research is often used in social sciences, education, psychology, and other fields where a deeper understanding of human experiences and perceptions is needed to inform policy, practice, or theory.

Data Analysis Methods

There are several Survey Research Data Analysis Methods that researchers may use, including:

• Descriptive statistics: This method is used to summarize and describe the basic features of the survey data, such as the mean, median, mode, and standard deviation. These statistics can help researchers understand the distribution of responses and identify any trends or patterns.
• Inferential statistics: This method is used to make inferences about the larger population based on the data collected in the survey. Common inferential statistical methods include hypothesis testing, regression analysis, and correlation analysis.
• Factor analysis: This method is used to identify underlying factors or dimensions in the survey data. This can help researchers simplify the data and identify patterns and relationships that may not be immediately apparent.
• Cluster analysis: This method is used to group similar respondents together based on their survey responses. This can help researchers identify subgroups within the larger population and understand how different groups may differ in their attitudes, behaviors, or preferences.
• Structural equation modeling: This method is used to test complex relationships between variables in the survey data. It can help researchers understand how different variables may be related to one another and how they may influence one another.
• Content analysis: This method is used to analyze open-ended responses in the survey data. Researchers may use software to identify themes or categories in the responses, or they may manually review and code the responses.
• Text mining: This method is used to analyze text-based survey data, such as responses to open-ended questions. Researchers may use software to identify patterns and themes in the text, or they may manually review and code the text.

Applications of Survey Research

Here are some common applications of survey research:

• Market Research: Companies use survey research to gather insights about customer needs, preferences, and behavior. These insights are used to create marketing strategies and develop new products.
• Public Opinion Research: Governments and political parties use survey research to understand public opinion on various issues. This information is used to develop policies and make decisions.
• Social Research: Survey research is used in social research to study social trends, attitudes, and behavior. Researchers use survey data to explore topics such as education, health, and social inequality.
• Academic Research: Survey research is used in academic research to study various phenomena. Researchers use survey data to test theories, explore relationships between variables, and draw conclusions.
• Customer Satisfaction Research: Companies use survey research to gather information about customer satisfaction with their products and services. This information is used to improve customer experience and retention.
• Employee Surveys: Employers use survey research to gather feedback from employees about their job satisfaction, working conditions, and organizational culture. This information is used to improve employee retention and productivity.
• Health Research: Survey research is used in health research to study topics such as disease prevalence, health behaviors, and healthcare access. Researchers use survey data to develop interventions and improve healthcare outcomes.

Examples of Survey Research

Here are some real-time examples of survey research:

• COVID-19 Pandemic Surveys: Since the outbreak of the COVID-19 pandemic, surveys have been conducted to gather information about public attitudes, behaviors, and perceptions related to the pandemic. Governments and healthcare organizations have used this data to develop public health strategies and messaging.
• Political Polls During Elections: During election seasons, surveys are used to measure public opinion on political candidates, policies, and issues in real-time. This information is used by political parties to develop campaign strategies and make decisions.
• Customer Feedback Surveys: Companies often use real-time customer feedback surveys to gather insights about customer experience and satisfaction. This information is used to improve products and services quickly.
• Event Surveys: Organizers of events such as conferences and trade shows often use surveys to gather feedback from attendees in real-time. This information can be used to improve future events and make adjustments during the current event.
• Website and App Surveys: Website and app owners use surveys to gather real-time feedback from users about the functionality, user experience, and overall satisfaction with their platforms. This feedback can be used to improve the user experience and retain customers.
• Employee Pulse Surveys: Employers use real-time pulse surveys to gather feedback from employees about their work experience and overall job satisfaction. This feedback is used to make changes in real-time to improve employee retention and productivity.

Survey Sample

Purpose of survey research.

The purpose of survey research is to gather data and insights from a representative sample of individuals. Survey research allows researchers to collect data quickly and efficiently from a large number of people, making it a valuable tool for understanding attitudes, behaviors, and preferences.

Here are some common purposes of survey research:

• Descriptive Research: Survey research is often used to describe characteristics of a population or a phenomenon. For example, a survey could be used to describe the characteristics of a particular demographic group, such as age, gender, or income.
• Exploratory Research: Survey research can be used to explore new topics or areas of research. Exploratory surveys are often used to generate hypotheses or identify potential relationships between variables.
• Explanatory Research: Survey research can be used to explain relationships between variables. For example, a survey could be used to determine whether there is a relationship between educational attainment and income.
• Evaluation Research: Survey research can be used to evaluate the effectiveness of a program or intervention. For example, a survey could be used to evaluate the impact of a health education program on behavior change.
• Monitoring Research: Survey research can be used to monitor trends or changes over time. For example, a survey could be used to monitor changes in attitudes towards climate change or political candidates over time.

When to use Survey Research

there are certain circumstances where survey research is particularly appropriate. Here are some situations where survey research may be useful:

• When the research question involves attitudes, beliefs, or opinions: Survey research is particularly useful for understanding attitudes, beliefs, and opinions on a particular topic. For example, a survey could be used to understand public opinion on a political issue.
• When the research question involves behaviors or experiences: Survey research can also be useful for understanding behaviors and experiences. For example, a survey could be used to understand the prevalence of a particular health behavior.
• When a large sample size is needed: Survey research allows researchers to collect data from a large number of people quickly and efficiently. This makes it a useful method when a large sample size is needed to ensure statistical validity.
• When the research question is time-sensitive: Survey research can be conducted quickly, which makes it a useful method when the research question is time-sensitive. For example, a survey could be used to understand public opinion on a breaking news story.
• When the research question involves a geographically dispersed population: Survey research can be conducted online, which makes it a useful method when the population of interest is geographically dispersed.

How to Conduct Survey Research

Conducting survey research involves several steps that need to be carefully planned and executed. Here is a general overview of the process:

• Define the research question: The first step in conducting survey research is to clearly define the research question. The research question should be specific, measurable, and relevant to the population of interest.
• Develop a survey instrument : The next step is to develop a survey instrument. This can be done using various methods, such as online survey tools or paper surveys. The survey instrument should be designed to elicit the information needed to answer the research question, and should be pre-tested with a small sample of individuals.
• Select a sample : The sample is the group of individuals who will be invited to participate in the survey. The sample should be representative of the population of interest, and the size of the sample should be sufficient to ensure statistical validity.
• Administer the survey: The survey can be administered in various ways, such as online, by mail, or in person. The method of administration should be chosen based on the population of interest and the research question.
• Analyze the data: Once the survey data is collected, it needs to be analyzed. This involves summarizing the data using statistical methods, such as frequency distributions or regression analysis.
• Draw conclusions: The final step is to draw conclusions based on the data analysis. This involves interpreting the results and answering the research question.

Advantages of Survey Research

There are several advantages to using survey research, including:

• Efficient data collection: Survey research allows researchers to collect data quickly and efficiently from a large number of people. This makes it a useful method for gathering information on a wide range of topics.
• Standardized data collection: Surveys are typically standardized, which means that all participants receive the same questions in the same order. This ensures that the data collected is consistent and reliable.
• Cost-effective: Surveys can be conducted online, by mail, or in person, which makes them a cost-effective method of data collection.
• Anonymity: Participants can remain anonymous when responding to a survey. This can encourage participants to be more honest and open in their responses.
• Easy comparison: Surveys allow for easy comparison of data between different groups or over time. This makes it possible to identify trends and patterns in the data.
• Versatility: Surveys can be used to collect data on a wide range of topics, including attitudes, beliefs, behaviors, and preferences.

Limitations of Survey Research

Here are some of the main limitations of survey research:

• Limited depth: Surveys are typically designed to collect quantitative data, which means that they do not provide much depth or detail about people’s experiences or opinions. This can limit the insights that can be gained from the data.
• Potential for bias: Surveys can be affected by various biases, including selection bias, response bias, and social desirability bias. These biases can distort the results and make them less accurate.
• L imited validity: Surveys are only as valid as the questions they ask. If the questions are poorly designed or ambiguous, the results may not accurately reflect the respondents’ attitudes or behaviors.
• Limited generalizability : Survey results are only generalizable to the population from which the sample was drawn. If the sample is not representative of the population, the results may not be generalizable to the larger population.
• Limited ability to capture context: Surveys typically do not capture the context in which attitudes or behaviors occur. This can make it difficult to understand the reasons behind the responses.
• Limited ability to capture complex phenomena: Surveys are not well-suited to capture complex phenomena, such as emotions or the dynamics of interpersonal relationships.

Following is an example of a Survey Sample:

Welcome to our Survey Research Page! We value your opinions and appreciate your participation in this survey. Please answer the questions below as honestly and thoroughly as possible.

1. What is your age?

• A) Under 18
• G) 65 or older

2. What is your highest level of education completed?

• A) Less than high school
• B) High school or equivalent
• C) Some college or technical school
• D) Bachelor’s degree
• E) Graduate or professional degree

3. What is your current employment status?

• A) Employed full-time
• B) Employed part-time
• C) Self-employed
• D) Unemployed

4. How often do you use the internet per day?

•  A) Less than 1 hour
• B) 1-3 hours
• C) 3-5 hours
• D) 5-7 hours
• E) More than 7 hours

5. How often do you engage in social media per day?

6. Have you ever participated in a survey research study before?

7. If you have participated in a survey research study before, how was your experience?

• A) Excellent
• E) Very poor

8. What are some of the topics that you would be interested in participating in a survey research study about?

……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….

9. How often would you be willing to participate in survey research studies?

• A) Once a week
• B) Once a month
• C) Once every 6 months
• D) Once a year

10. Any additional comments or suggestions?

Thank you for taking the time to complete this survey. Your feedback is important to us and will help us improve our survey research efforts.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Best Practices for Survey Research

Below you will find recommendations on how to produce the best survey possible..

Included are suggestions on the design, data collection, and analysis of a quality survey.  For more detailed information on important details to assess rigor of survey methology, see the  AAPOR Transparency Initiative .

To download a pdf of these best practices,  please click here

"The quality of a survey is best judged not by its size, scope, or prominence, but by how much attention is given to [preventing, measuring and] dealing with the many important problems that can arise."

“What is a Survey?”, American Statistical Association

1. Planning Your Survey

Is a survey the best method for answering your research question.

Surveys are an important research tool for learning about the feelings, thoughts, and behaviors of groups of individuals. However, surveys may not always be the best tool for answering your research questions. They may be appropriate when there is not already sufficiently timely or relevant existing data on the topic of study. Researchers should consider the following questions when deciding whether to conduct a survey:

• What are the objectives of the research? Are they unambiguous and specific?
• Have other surveys already collected the necessary data?
• Are other research methods such as focus groups or content analyses more appropriate?
• Is a survey alone enough to answer the research questions, or will you also need to use other types of data (e.g., administrative records)?

Surveys should not be used to produce predetermined results, campaigning, fundraising, or selling. Doing so is a violation of the  AAPOR Code of Professional Ethics .

Should the survey be offered online, by mail, in person, on the phone, or in some combination of these modes?

Once you have decided to conduct a survey, you will need to decide in what mode(s) to offer it. The most common modes are online, on the phone, in person, or by mail.  The choice of mode will depend at least in part on the type of information in your survey frame and the quality of the contact information. Each mode has unique advantages and disadvantages, and the decision should balance the data quality needs of the research alongside practical considerations such as the budget and time requirements.

• Compared with other modes, online surveys can be quickly administered for less cost. However, older respondents, those with lower incomes, or respondents living in rural areas are less likely to have reliable internet access or to be comfortable using computers. Online surveys may work well when the primary way you contact respondents is via email. It also may elicit more honest answers from respondents on sensitive topics because they will not have to disclose sensitive information directly to another person (an interviewer).
• Telephone surveys are often more costly than online surveys because they require the use of interviewers. Well trained interviewers can help guide the respondent through questions that might be hard to understand and encourage them to keep going if they start to lose interest, reducing the number of people who do not complete the survey. Telephone surveys are often used when the sampling frame consists of telephone numbers. Quality standards can be easier to maintain in telephone surveys if interviewers are in one centralized location.
• In-person, or face-to-face, surveys tend to cost the most and generally take more time than either online or telephone surveys.  With an in-person survey, the interviewer can build a rapport with the respondent and help with questions that might be hard to understand. This is particularly relevant for long or complex surveys. In-person surveys are often used when the sampling frame consists of addresses.
• Mailed paper surveys can work well when the mailing addresses of the survey respondents are known. Respondents can complete the survey at their own convenience and do not need to have computer or internet access. Like online surveys, they can work well for surveys on sensitive topics. However, since mail surveys cannot be automated, they work best when the flow of the questionnaire is relatively straightforward. Surveys with complex skip patterns based on prior responses may be confusing to respondents and therefore better suited for other modes.

Some surveys use multiple modes, particularly if a subset of the people in the sample are more reachable via a different mode. Often, a less costly method is employed first or used concurrently with another method, for example offering a choice between online and telephone response, or mailing a paper survey with a telephone follow-up with those who have not yet responded.

2. Designing Your Sample

How to design your sample.

When you run a survey, the people who respond to your survey are called your sample because they are a sample of people from the larger population you are studying, such as adults who live in the U.S. A sampling frame is a list of information that will allow you to contact potential respondents – your sample – from a population. Ultimately, it’s the sampling frame that allows you to draw a sample from the larger population. For a mail-based survey, it’s a list of addresses in the geographic area in which your population is located; for an online panel survey, it’s the people in the panel; for a telephone survey, it’s a list of phone numbers. Thinking through how to design your sample to best match the population of study can help you run a more accurate survey that will require fewer adjustments afterwards to match the population.

One approach is to use multiple sampling frames; for example, in a phone survey, you can combine a sampling frame of people with cell phones and a sampling frame of people with landlines (or both), which is now considered a best practice for phone surveys.

Surveys can be either probability-based or nonprobability-based. For decades, probability samples, often used for telephone surveys, were the gold standard for public opinion polling. In these types of samples, there is a frame that covers all or almost all the population of interest, such as a list of all the phone numbers in the U.S. or all the residential addresses, and individuals are selected using random methods to complete the survey. More recently, nonprobability samples and online surveys have gained popularity due to the rising cost of conducting probability-based surveys. A survey conducted online can use probability samples, such as those recruited using residential addresses, or can use nonprobability samples, such as “opt-in” online panels or participants recruited, through social media or personal networks.  Analyzing and reporting  nonprobability-based survey results often require using special statistical techniques and taking great care to ensure transparency about the methodology.

3. Designing your questionnaire

What are some best practices for writing survey questions.

• Questions should be specific and ask only about one concept at a time. For example, respondents may interpret a question about the role of “government” differently – some may think of the federal government, while others may think of state governments.
• Write questions that are short and simple and use words and concepts that the target audience will understand. Keep in mind that knowledge,  literacy skills , and  English proficiency  vary widely among respondents.
• Keep questions free of bias by avoiding language that pushes respondents to respond in a certain way or that presents only one side of an issue. Also be aware that respondents may tend toward a socially desirable answer or toward saying “yes” or “agree” in an effort to please the interviewer, even if unconsciously.
• Arrange questions in an order that will be logical to respondents but not influence how they answer. Often, it’s better for general questions to come earlier than specific questions about the same concept in the survey. For example, asking respondents whether they favor or oppose certain policy positions of a political leader prior to asking a general question about the favorability of that leader may prime them to weigh those certain policy positions more heavily than they otherwise would in determining how to answer about favorability.
• Choose whether a question should be closed-ended or open-ended. Closed-ended questions, which provide a list of response options to choose from, place less of a burden on respondents to come up with an answer and are easier to interpret, but they are more likely to influence how a respondent answers. Open-ended questions allow respondents to respond in their own words but require coding in order to be interpreted quantitatively.
• Response options for closed-ended questions should be chosen with care. They should be mutually exclusive, include all reasonable options (including, in some cases, options such as “don’t know” or “does not apply” or neutral choices such as “neither agree nor disagree”), and be in a logical order. In some circumstances, response options should be rotated (for example, half the respondents see response options in one order while the other half see it in reverse order) due to an  observed tendency  of respondents to pick the first answer in self-administered surveys and the last answer in interviewer-administered surveys. Randomization allows researchers to check on whether there are order effects.
• Consider what languages you will offer the survey in. Many U.S. residents speak limited or no English. Most nationally representative surveys in the U.S. offer questionnaires in both English and Spanish, with bilingual interviewers available in interviewer-administered modes.
• See AAPOR’s  resources on question wording for more details

How can I measure change over time?

If you want to measure change, don’t change the measure.

To accurately measure whether an observed change between surveys taken at two points in time reflects a true shift in public attitudes or behaviors, it is critical to keep the question wording, framing, and methodology of the survey as similar as possible across the two surveys. Changes in question-wording and even the context of other questions before it can influence how respondents answer and make it appear that there has been a change in public opinion even if the only change is in how respondents are interpreting the question (or potentially mask an actual shift in opinion).

Changes in mode, such as comparing a survey conducted over the telephone to one conducted online, can sometimes also mimic a real change because many people respond to certain questions differently when speaking to an interviewer on the phone versus responding in private to a web survey. Questions that are very personal or have a response option that respondents see as socially undesirable, or embarrassing are particularly sensitive to this mode effect.

If changing the measure is necessary — perhaps due to flawed question wording or a desire to switch modes for logistical reasons — the researcher can employ a split-ballot experiment to test whether respondents will be sensitive to the change. This would involve fielding two versions of a survey — one with the previous mode or question wording and one with the new mode or question wording — with all other factors kept as similar as possible across the two versions. If respondents answer both versions similarly, there is evidence that any change over time is likely due to a real shift in attitudes or behaviors rather than an artifact of the change in measurement. If response patterns differ according to which version respondents see, then change over time should be interpreted cautiously if the researcher moves ahead with the change in measurement.

How can I ensure the safety, confidentiality, and comfort of respondents?

• Follow your institution’s guidance and policies on the protection of personal identifiable information and determine whether any data privacy laws apply to the study. If releasing individual responses in a public dataset, keep in mind that demographic information and survey responses may make it possible to identify respondents even if personal identifiable information like names and addresses are removed.
• Consult an  Institutional Review Board  for recommendations on how to mitigate the risk, even if not required by your institution.
• Disclose the sensitive topic at the beginning of the survey, or just before the questions appear in the survey, and  inform respondents  that they can skip the questions if they are not comfortable answering them (and be sure to program an online survey to allow skipping, or instruct interviewers to allow refusals without probing).
• Provide links or hotlines to resources that can help respondents who were affected by the sensitive questions (for example, a hotline that provides help for those suffering from eating disorders if the survey asks about disordered eating behaviors).
• Build rapport with a respondent by beginning with easy and not-too-personal questions and keeping sensitive topics for later in the survey.
• Keep respondent burden low by keeping questionnaires and individual questions short and limiting the number of difficult, sensitive, or open-ended questions.
• Allow respondents to skip a question or provide an explicit “don’t know” or “don’t want to answer” response, especially for difficult or sensitive questions. Requiring an answer increases the risk of respondents choosing to leave the survey early.

4. Fielding Your Survey

If i am using interviewers, how should they be trained.

Interviewers need to undergo training that covers both recruiting respondents into the survey and administering the survey. Recruitment training should cover topics such as contacting sampled respondents and convincing reluctant respondents to participate. Interviewers should be comfortable navigating the hardware and software used to conduct the survey and pronouncing difficult names or terms. They should have familiarity with the concepts the survey questions are asking about and know how to help respondents without influencing their answers. Training should also involve practice interviews to familiarize the interviewers with the variety of situations they are likely to encounter. If the survey is being administered in languages other than English, interviewers should demonstrate language proficiency and cultural awareness. Training should address how to conduct non-English interviews appropriately.

Interviewers should be trained in protocols on how best to protect the health and well-being of themselves and respondents, as needed. As an example, during the COVID-19 pandemic, training in the proper use of personal protective equipment and social distancing would be appropriate for field staff.

What kinds of testing should I do before fielding a survey?

Before fielding a survey, it is important to pretest the questionnaire. This typically consists of conducting cognitive interviews or using another qualitative research method to understand respondents’ thought processes, including their interpretation of the questions and how they came up with their answers. Pretesting should be conducted with respondents who are similar to those who will be in the survey (e.g., students if the survey sample is college students).

Conducting a pilot test to ensure that all survey procedures (e.g., recruiting respondents, administering the survey, cleaning data) work as intended is recommended. If it is unclear what question-wording or survey design choice is best, implementing an experiment during data collection can help systematically compare the effects of two or more alternatives.

What kinds of monitoring or quality checks should I do on my survey?

Checks must be made at every step of the survey life cycle to ensure that the sample is selected properly, the questionnaire is programmed accurately, interviewers do their work properly, information from questionnaires is edited and coded accurately, and proper analyses are used. The data should be monitored while it is being collected by using techniques such as observation of interviewers, replication of some interviews (re-interviews), and monitoring of response and paradata distributions. Odd patterns of responses may reflect a programming error or interviewer training issue that needs to be addressed immediately.

How do I get as many people to respond to the survey as possible?

It is important to monitor responses and attempt to maximize the number of people who respond to your survey. If very few people respond to your survey, there is a risk that you may be missing some types of respondents entirely, and your survey estimates may be biased. There are a variety of ways to incentivize respondents to participate in your survey, including offering monetary or non-monetary incentives, contacting them multiple times in different ways and at different times of the day, and/or using different persuasive messages. Interviewers can also help convince reluctant respondents to participate. Ideally,  reasonable efforts  should be made to convince both respondents who have not acknowledged the survey requests as well as those who refused to participate.

5. Analyzing and reporting the survey results

What are the common methods of analyzing survey data.

Analyzing survey data is, in many ways, similar to data analysis in other fields. However, there are a few details unique to survey data analysis to take note of. It is important to be as transparent as possible, including about any statistical techniques used to adjust the data.

Depending on your survey mode, you may have respondents who answer only part of your survey and then end the survey before finishing it. These are called partial responses, drop offs, or break offs. You should make sure to indicate these responses in your data and use a value to indicate there was no response. Questions with no response should have a different value than answer options such as “none of the above,” “I don’t know,” or “I prefer not to answer.” The same applies if your survey allows respondents to skip questions but continue in the survey.

A common way of reporting on survey data is to show cross-tabulated results, or crosstabs for short. Crosstabs are when you show a table with one question’s answers as the column headers and another question’s answers as the row names. The values in the crosstab can be either counts — the number of respondents who chose those specific answers to those two questions — or percentages. Typically, when showing percentages, the columns total to 100%.

Analyzing survey data allows us to estimate findings about the population under study by using a sample of people from that population. An industry standard is to calculate and report on the margin of sampling error, often shortened to the margin of error. The margin of error is a measurement of confidence in how close the survey results are to the true value in the population. To learn more about the margin of error and the credibility interval, a similar measurement used for nonprobability surveys, please see AAPOR’s  Margin of Error resources.

What is weighting and why is it important?

Ideally, the composition of your sample would match the population under study for all the characteristics that are relevant to the topic of your survey; characteristics such as age, sex, race/ethnicity, location, educational attainment, political party identification, etc. However, this is rarely the case in practice, which can lead to the results of your survey being skewed. Weighting is a statistical technique to adjust the results to adjust the relative contributions of your respondents to match the population characteristics more closely. Learn more about weighting .

What are the common industry standards for transparency in reporting data?

Because there are so many different ways to run surveys, it’s important to be transparent about how a survey was run and analyzed so that people know how to interpret and draw conclusions from it. AAPOR’s Transparency Initiative has established  a list of items to report with your survey results that uphold the industry transparency standards. These items include sample size, margin of sampling error, weighting attributes, the full text of the questions and answer options, the survey mode, the population under study, the way the sample was constructed, recruitment, and several other details of how the survey was run. The list of items to report can vary based on the mode of your survey — online, phone, face-to-face, etc. Organizations that want to commit to upholding these standards can also become members of the Transparency Initiative .

It is important to monitor responses and attempt to maximize the number of people who respond to your survey. If very few people respond to your survey, there is a risk that you may be missing some types of respondents entirely, and your survey estimates may be biased. There are a variety of ways to incentivize respondents to participate in your survey, including offering monetary or non-monetary incentives, contacting them multiple times in different ways and at different times of the day, and/or using different persuasive messages. Interviewers can also help convince reluctant respondents to participate. Ideally, reasonable efforts should be made to convince both respondents who have not acknowledged the survey requests as well as those who refused to participate.

2019 Presidential Address from the 74th Annual Conference

David Dutwin May 2019

“Many of you know me primarily as a methodologist.  But in fact, my path to AAPOR had nothing to do with methodology.  My early papers, in fact, wholly either provided criticism of, or underscored the critical value of, public opinion and public opinion polls.

And so in some respects, this Presidential Address is for me, completes a full circle of thought and passion I have for AAPOR, for today I would like to discuss matters pertaining to the need to reconsider, strengthen, and advance the mission of survey research in democracy.

Historically, there has been much to say on the role of public opinion in democracy.   George Gallup summarized the role of polls quite succinctly when he said,  “Without polls, [elites] would be guided only by letters to congressmen, the lobbying of pressure groups, and the reports of political henchmen.”

Further,  Democratic theory notes the critical, if not the pivotal role, of public opinion and democratic practice.   Storied political scientist V.O Key said:  “The poll furnishes a means for the deflation of the extreme claims of pressure groups and for the testing of their extravagant claims of public sentiment in support of their demands.”

Furthermore, surveys provide a critical check and balance to other claims of what the American public demands in terms of policies and their government.   Without polls, it would be all that much harder to verify and combat claims of public sentiment made by politicians, elites, lobbyists, and interest groups.  [“No policy that does not rest upon some public opinion can be permanently maintained.”- Abe Lincoln; “Public opinion is a thermometer a monarch should constantly consult” – Napoleon]

It is sometimes asked whether leaders do consult polls and whether polls have any impact of policy.   The relationship here is complex, but time and again researchers have found a meaningful and significant effect of public opinion, typically as measured by polling, on public policy. As one example, Page and Shapiro explored trends in American public opinion from the 1930s to the 1980s and found no less than 231 different changes in public policy following shifts in public opinion.

And certainly, in modern times around the world, there is recognition that the loss of public opinion would be, indeed, the loss of democracy itself. [“Where there is no public opinion, there is likely to be bad government, which sooner or later, becomes autocratic government.” – Willian Lyon Mackenzie King]

And yet, not all agree.  Some twist polling to be a tool that works against democratic principles.  [“The polls are just being used as another tool for voter suppression.” – Rush Limbaugh]

And certainly, public opinion itself is imperfect, filled with non-attitudes, the will of the crowd, and can often lead to tyranny of the majority, as Jon Stewart nicely pointed out. [“You have to remember one thing about the will of the people: It wasn’t that long ago that we were swept away by the Macarena.” – Jon Stewart]

If these later quotes were the extent of criticism on the role of public opinion and survey research in liberal democracy, I would not be up here today discussing what soon follows in this address.  Unfortunately, however, we live a world in which many of the institutions of democracy and society are under attack.

It is important to start by recognizing that AAPOR is a scientific organization.  Whether you are a quantitative or qualitative researcher, a political pollster or developer of official statistics, a sociologist or a political scientist, someone who works for a commercial entity or nonprofit, we are all survey scientists, and we come together as a great community of scientists within AAPOR, no matter our differences.

And so we, AAPOR, should be as concerned as any other scientific community regarding the current environment where science is under attack, devalued, and delegitimized.  It is estimated that since the 2016 election, the federal policy has moved to censor, or misrepresent, or curtail and suppress scientific data and discoveries over 200 times, according to the Sabin Center at Columbia University.  Not only is this a concern to AAPOR as a community of scientists, but we should be concerned as well on the impact of these attacks on public opinion itself.

Just as concerning is the attack on democratic information, in general.  Farrell and Schneier argue that there are two key types of knowledge in democracy, common and contested.  And while we should be free to argue and disagree with policy choices, our pick of democratic leaders, and even many of the rules and mores that guide us as a society, what is called contested knowledge, what cannot be up for debate is the common knowledge of democracy, for example, the legitimacy of the electoral process itself, or the validity of data attained by the Census, or even more so, I would argue, that public opinion does not tell us what the public thinks.

As the many quotes I provided earlier attest to, democracy is dependent upon a reliable and nonideological measure of the will of the people.  For more than a half century and beyond, survey research been the principal and predominant vehicle by which such knowledge is generated.

And yet, we are on that doorstep where common knowledge is becoming contested.  We are entering, I fear, a new phase of poll delegitimization.  I am not here to advocate any political ideology and it is critical for pollsters to remain within the confines of science.  Yet there has been a sea change in how polls are discussed by the current administration.  To constantly call out polls for being fake is to delegitimize public opinion itself and is a threat to our profession.

Worse still, many call out polls as mere propaganda (see Joondeph, 2018).  Such statements are more so a direct attack on our science, our field, and frankly, the entire AAPOR community.  And yet even worse is for anyone to actually rig poll results.  Perhaps nothing may undermine the science and legitimacy of polling more.

More pernicious still, we are on the precipice of an age where faking anything is possible.  The technology now exists to fake actual videos of politicians, or anyone for that matter, and to create realistic false statements.  The faking of poll results is merely in lockstep with these developments.

There are, perhaps, many of you in this room who don’t directly connect with this.  You do not do political polling.  You do government statistics.  Sociology.  Research on health, on education, or consumer research.  But we must all realize that polling is the tip of the spear.  It is what the ordinary citizen sees of our trade and our science.  As Andy Kohut once noted, it represents all of survey research. [Political polling is the “most visible expression of the validity of the survey research method.“ – Andrew Kohut]

With attacks on science at an all-time high in the modern age, including attacks on the science of surveys; with denigration of common knowledge, the glue that holds democracy together, including denunciation on the reliability of official statistics; with slander on polling that goes beyond deliberation on the validity of good methods but rather attacks good methods as junk, as propaganda, and as fake news; and worse of all, a future that, by all indications, will if anything include the increased frequency of fake polls, and fake data, well, what are we, AAPOR, to do?

We must respond.  We must react.  And, we must speak out.  What does this mean, exactly?  First, AAPOR must be able to respond.  Specifically, AAPOR must have vehicles and avenues of communication and the tools by which it can communicate.  Second, AAPOR must know how to respond.  That is to say, AAPOR must have effective and timely means of responding.  We are in an every minute of the day news cycle.  AAPOR must adapt to this environment and maximize its impact by speaking effectively within this communication environment.  And third, AAPOR must, quite simply, have the willpower to respond.  AAPOR is a fabulous member organization, providing great service to its members in terms of education, a code of ethics, guidelines for best practices and promotions of transparency and diversity in the field of survey research.  But we have to do more.  We have to learn to professionalize our communication and advocate for our members and our field.  There are no such thing as sidelines anymore.  We must do our part to defend survey science, polling, and the very role of public opinion in a functioning democracy.

This might seem to many of you like a fresh idea, and bold new step for AAPOR.  But in fact, there has been a common and consistent call for improved communication abilities, communicative outreach, and advocacy by many past Presidents, from Diane Colasanto to Nancy Belden to Andy Kohut.

Past President Frank Newport for example was and is a strong supporter of the role of public opinion in democracy, underscoring in his Presidential address that quote, “the collective views of the people…are absolutely vital to the decision-making that ultimately affects them.” He argued in his Presidential address that AAPOR must protect the role of public opinion in society.

A number of Past Presidents have rightly noted that AAPOR must recognize the central role of journalists in this regard, who have the power to frame polling as a positive or negative influence on society.  President Nancy Mathiowetz rightly pointed out that AAPOR must play a role in, and even financially support, endeavors to guarantee that journalists’ support AAPOR’s position on the role of polling in society and journalists’ treatment of polls.  And Nancy’s vision, in fact, launched relationship with Poynter in building a number of resources for journalist education of polling.

Past President Scott Keeter also noted the need for AAPOR to do everything it can to promote public opinion research.  He said that “we all do everything we can to defend high-quality survey research, its producers, and those who distribute it.”  But at the same time, Scott noted clearly that, unfortunately, “At AAPOR we are fighting a mostly defensive war.”

And finally, Past President Cliff Zukin got straight to the point in his Presidential address, noting that, quote “AAPOR needs to increase its organizational capacity to respond and communicate, both internally and externally. We need to communicate our positions and values to the outside world, and we need to diffuse ideas more quickly within our profession.”

AAPOR is a wonderful organization, and in my biased opinion, the best professional organization I know.  How have we responded to the call of past Presidents?  I would say, we responded with vigor, with energy, and with passion.  But we are but a volunteer organization of social scientists.  And so, we make task forces.  We write reports.  These reports are well researched, well written, and at the same time, I would argue, do not work effectively to create impact in the modern communication environment.

We have taken one small step to ameliorate this, with the report on polling in the 2016 election, which was publicly released via a quite successful live Facebook video event.  But we can still do better.  We need to be more timely for one, as that event occurred 177 days after the election, when far fewer people were listening, and the narrative was largely already written.  And we need to find ways to make such events have greater reach and impact.  And of course, we need more than just one event every four years.

I have been proud to have been a part of, and even be the chair of, a number of excellent task force reports.  But we cannot, I submit, continue to respond only with task force reports.  AAPOR is comprised of the greatest survey researchers in the world.  But it is not comprised of professional communication strategists, plain and simple.  We need help, and we need professional help.

In the growth of many organizations, there comes a time when the next step must be taken.  The ASA many years ago, for example, hired a full time strategic communications firm.  Other organizations, including the NCA, APSA, and others, chose instead to hire their own full time professional communication strategist.

AAPOR has desired to better advocate for itself for decades.  We recognize that we have to get into the fight, that there are again no more things as sidelines.  And we have put forward a commendable effort in this regard, building educational resources for journalists, and writing excellent reports on elections, best practices, sugging and frugging, data falsification, and other issues.  But we need to do more, and in the context of the world outside of us, we need to speak a language that resonates with journalists, political elites, and perhaps most importantly the public.

I want to stop right here and make it clear, that the return on investment on such efforts is not going to be quick.  And the goal here is not to improve response rates, though I would like that very much!  No, it is not likely that any efforts in any near term reverses trends in nonresponse.

It may very well be that our efforts only slow or at best stop the decline. But that would be an important development.  The Washington Post says that democracy dies in darkness.  If I may, I would argue that AAPOR must say, democracy dies in silence, when the vehicle for public opinion, surveys, has been twisted to be distrusted by the very people who need it most, ordinary citizens.  For the most part, AAPOR has been silent.  We can be silent no more.

This year, Executive Council has deliberated the issues outlined in this address, and we have chosen to act.  The road will be long, and at this time, I cannot tell you where it will lead.  But I can tell you our intentions and aspirations.  We have begun to execute a 5 point plan that I present here to you.

First, AAPOR Executive Council developed and released a request for proposals for professional strategic communication services.  Five highly regarded firms responded.  After careful deliberation and in person meetings with the best of these firms, we have chosen Stanton Communications to help AAPOR become a more professionalized association.  Our goals in the short term are as follows.

We desire to become more nimble and effective at responding to attacks on polls, with key AAPOR members serving as spokespersons when needed, but only after professional development of the messages they will promulgate, approved by Council, and professionalized by the firm.  Stanton brings with it a considerable distribution network of journalists and media outlets.  AAPOR, through its professional management firm Kellen, has access to audio and video services of the National Press Club, and will utilize these services when needed to respond to attacks on polls, and for other communications deemed important by AAPOR Executive Council.

Our plan is to begin small.  We are cognizant of the cost that professional communication can entail, and for now, we have set very modest goals. The first step is to be prepared, and have a plan for, the 2020 election, with fast response options of communication during the campaign, and perhaps most importantly, directly thereafter.

The second element of our plan is to re-envision AAPOR’s role in journalism education.  In short, we believe we need to own this space, not farm it out to any other entity.  We need refreshed educational videos, and many more of them, from explaining response rates to the common criticisms made on the use of horserace polling in the media.

We need to travel.  Willing AAPOR members should be funded to travel and present at journalism conferences, to news rooms, and to journalism schools on an annual basis. AAPOR could as well have other live events, for example a forum on the use of polls in journalism.  There should be a consistent applied effort over time.  The media and journalists are AAPOR’s greatest spokespeople.  By and large, much of our image is shaped through them.

The third element looks at the long game.  And that is, for AAPOR to help in developing civics education on public opinion and the role of public opinion in democracy.  With the help of educational experts, and importantly, tipping our hats to our AAPOR’s Got Talent winner last year, Allyson Holbrook, who proposed exactly this kind of strategy, we believe AAPOR can help develop a curriculum and educational materials and engage with educators to push for the inclusion of this curriculum in primary education.  AAPOR can and should develop specific instructional objectives of civics education by grade and develop a communications plan to lobby for the inclusion of this civics curriculum by educators.

The fourth element is for AAPOR to direct the Transparency Initiative to develop a strategic plan for the next ten years.  We recognize that it is not always the case that polls are executed with best practices.  How does AAPOR respond in these instances?  With a plethora of new sampling approaches and modalities, we believe the TI needs to have a full-throated conversation about these challenges and how AAPOR should handle them.  After all, this too is part of the conversation of AAPOR communication.

Finally, AAPOR should, as past President Tim Johnson called for last year, learn as much as it can about the perceptions of polls in society.  We cannot make effective strategic communication plans without knowing first how they will resonate and know to some degree their expected effectiveness.  Such an effort should continue over time, building both a breadth and depth of understanding.

If this sounds a bit like a wish list, well, you would be right.  For now, the immediate goal for AAPOR and its communication firm is to prepare for 2020 and to take some modest steps toward professionalizing AAPOR’s ability to effectively and quickly communicate and advocate.    Looking toward the future, AAPOR Council has authorized the development of the Ad Hoc Committee on Public Opinion.  This committee will be comprised of AAPOR members dedicated to pushing forward this agenda.

We recognize the potential cost of these endeavors in terms of money and labor, and so in each area, there will be mission leaders on the committee whose goal is to push forward with two goals.  The first is funding.  We cannot and should not fund these endeavors alone.  We will be seeking foundational funding for each of these areas, and are developing a proposal for each specifically.  Perhaps only one area attains funding, perhaps all of them.  No matter, the committee will adjust its goals contingent on the means it has available.

A number of members have already asked to be part of these efforts.  But I call on all of you, the AAPOR membership, to reach out and join the effort as well.  We need people experienced in seeking funding, and people passionate in moving the needle with regard to polling journalism, civics education, and the role of public opinion in democracy.  AAPOR’s secret sauce has always been the passion of its members and we call on you to help.  Please go the link below to tell us you want to join the effort.

Friends and colleagues, one of the many excellent AAPOR task forces already, in fact explored this issue, the task force on polling and democracy and leadership.  They argued that “AAPOR should adopt an increased public presence arguing for the importance of public opinion in a democracy and the importance of rigorous, unbiased, scientific research assessing public opinion.”

It is time we strive to realize these aspirations.  For the good of our association, our field, and our very democracy.  If past efforts by AAPOR volunteers are any indication, we anticipate great success and health in the future of our field and our endeavors.

It has been an honor and a privilege serving as your President. Thank you.”

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Correction: Impact of sampling and data collection methods on maternity survey response: a randomised controlled trial of paper and push‑to‑web surveys and a concurrent social media survey

• Siân Harrison 1 ,
• Fiona Alderdice 1 &
• Maria A. Quigley 1  

BMC Medical Research Methodology volume  24 , Article number:  100 ( 2024 ) Cite this article

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The Original Article was published on 12 January 2023

Correction: BMC Med Res Methodol 23, 10 (2023)

https://doi.org/10.1186/s12874-023-01833-8

Following publication of the original article [ 1 ], the authors reported an error in the Fig.  4 : the colours in the pie charts in Fig.  4 do not all correspond with the legend. See the Fig.  4 corrected.

Breakdown of total costs across the surveys

The original article [ 1 ] has been updated.

Harrison S, Alderdice F, Quigley MA. Impact of sampling and data collection methods on maternity survey response: a randomised controlled trial of paper and push-to-web surveys and a concurrent social media survey. BMC Med Res Methodol. 2023;23:10. https://doi.org/10.1186/s12874-023-01833-8 .

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Harrison, S., Alderdice, F. & Quigley, M.A. Correction: Impact of sampling and data collection methods on maternity survey response: a randomised controlled trial of paper and push‑to‑web surveys and a concurrent social media survey. BMC Med Res Methodol 24 , 100 (2024). https://doi.org/10.1186/s12874-024-02216-3

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Title: a survey on the memory mechanism of large language model based agents.

Abstract: Large language model (LLM) based agents have recently attracted much attention from the research and industry communities. Compared with original LLMs, LLM-based agents are featured in their self-evolving capability, which is the basis for solving real-world problems that need long-term and complex agent-environment interactions. The key component to support agent-environment interactions is the memory of the agents. While previous studies have proposed many promising memory mechanisms, they are scattered in different papers, and there lacks a systematical review to summarize and compare these works from a holistic perspective, failing to abstract common and effective designing patterns for inspiring future studies. To bridge this gap, in this paper, we propose a comprehensive survey on the memory mechanism of LLM-based agents. In specific, we first discuss ''what is'' and ''why do we need'' the memory in LLM-based agents. Then, we systematically review previous studies on how to design and evaluate the memory module. In addition, we also present many agent applications, where the memory module plays an important role. At last, we analyze the limitations of existing work and show important future directions. To keep up with the latest advances in this field, we create a repository at \url{ this https URL }.

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