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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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What is survey research.

15 min read Find out everything you need to know about survey research, from what it is and how it works to the different methods and tools you can use to ensure you’re successful.

Survey research is the process of collecting data from a predefined group (e.g. customers or potential customers) with the ultimate goal of uncovering insights about your products, services, or brand overall .

As a quantitative data collection method, survey research can provide you with a goldmine of information that can inform crucial business and product decisions. But survey research needs careful planning and execution to get the results you want.

So if you’re thinking about using surveys to carry out research, read on.

Get started with our free survey maker tool

Types of survey research

Calling these methods ‘survey research’ slightly underplays the complexity of this type of information gathering. From the expertise required to carry out each activity to the analysis of the data and its eventual application, a considerable amount of effort is required.

As for how you can carry out your research, there are several options to choose from — face-to-face interviews, telephone surveys, focus groups (though more interviews than surveys), online surveys , and panel surveys.

Typically, the survey method you choose will largely be guided by who you want to survey, the size of your sample , your budget, and the type of information you’re hoping to gather.

Here are a few of the most-used survey types:

Face-to-face interviews

Before technology made it possible to conduct research using online surveys, telephone, and mail were the most popular methods for survey research. However face-to-face interviews were considered the gold standard — the only reason they weren’t as popular was due to their highly prohibitive costs.

When it came to face-to-face interviews, organizations would use highly trained researchers who knew when to probe or follow up on vague or problematic answers. They also knew when to offer assistance to respondents when they seemed to be struggling. The result was that these interviewers could get sample members to participate and engage in surveys in the most effective way possible, leading to higher response rates and better quality data.

Telephone surveys

While phone surveys have been popular in the past, particularly for measuring general consumer behavior or beliefs, response rates have been declining since the 1990s .

Phone surveys are usually conducted using a random dialing system and software that a researcher can use to record responses.

This method is beneficial when you want to survey a large population but don’t have the resources to conduct face-to-face research surveys or run focus groups, or want to ask multiple-choice and open-ended questions .

The downsides are they can: take a long time to complete depending on the response rate, and you may have to do a lot of cold-calling to get the information you need.

You also run the risk of respondents not being completely honest . Instead, they’ll answer your survey questions quickly just to get off the phone.

Focus groups (interviews — not surveys)

Focus groups are a separate qualitative methodology rather than surveys — even though they’re often bunched together. They’re normally used for survey pretesting and designing , but they’re also a great way to generate opinions and data from a diverse range of people.

Focus groups involve putting a cohort of demographically or socially diverse people in a room with a moderator and engaging them in a discussion on a particular topic, such as your product, brand, or service.

They remain a highly popular method for market research , but they’re expensive and require a lot of administration to conduct and analyze the data properly.

You also run the risk of more dominant members of the group taking over the discussion and swaying the opinions of other people — potentially providing you with unreliable data.

Online surveys

Online surveys have become one of the most popular survey methods due to being cost-effective, enabling researchers to accurately survey a large population quickly.

Online surveys can essentially be used by anyone for any research purpose – we’ve all seen the increasing popularity of polls on social media (although these are not scientific).

Using an online survey allows you to ask a series of different question types and collect data instantly that’s easy to analyze with the right software.

There are also several methods for running and distributing online surveys that allow you to get your questionnaire in front of a large population at a fraction of the cost of face-to-face interviews or focus groups.

This is particularly true when it comes to mobile surveys as most people with a smartphone can access them online.

However, you have to be aware of the potential dangers of using online surveys, particularly when it comes to the survey respondents. The biggest risk is because online surveys require access to a computer or mobile device to complete, they could exclude elderly members of the population who don’t have access to the technology — or don’t know how to use it.

It could also exclude those from poorer socio-economic backgrounds who can’t afford a computer or consistent internet access. This could mean the data collected is more biased towards a certain group and can lead to less accurate data when you’re looking for a representative population sample.

When it comes to surveys, every voice matters.

Find out how to create more inclusive and representative surveys for your research.

Panel surveys

A panel survey involves recruiting respondents who have specifically signed up to answer questionnaires and who are put on a list by a research company. This could be a workforce of a small company or a major subset of a national population. Usually, these groups are carefully selected so that they represent a sample of your target population — giving you balance across criteria such as age, gender, background, and so on.

Panel surveys give you access to the respondents you need and are usually provided by the research company in question. As a result, it’s much easier to get access to the right audiences as you just need to tell the research company your criteria. They’ll then determine the right panels to use to answer your questionnaire.

However, there are downsides. The main one being that if the research company offers its panels incentives, e.g. discounts, coupons, money — respondents may answer a lot of questionnaires just for the benefits.

This might mean they rush through your survey without providing considered and truthful answers. As a consequence, this can damage the credibility of your data and potentially ruin your analyses.

What are the benefits of using survey research?

Depending on the research method you use, there are lots of benefits to conducting survey research for data collection. Here, we cover a few:

1.   They’re relatively easy to do

Most research surveys are easy to set up, administer and analyze. As long as the planning and survey design is thorough and you target the right audience , the data collection is usually straightforward regardless of which survey type you use.

2.   They can be cost effective

Survey research can be relatively cheap depending on the type of survey you use.

Generally, qualitative research methods that require access to people in person or over the phone are more expensive and require more administration.

Online surveys or mobile surveys are often more cost-effective for market research and can give you access to the global population for a fraction of the cost.

3.   You can collect data from a large sample

Again, depending on the type of survey, you can obtain survey results from an entire population at a relatively low price. You can also administer a large variety of survey types to fit the project you’re running.

4.   You can use survey software to analyze results immediately

Using survey software, you can use advanced statistical analysis techniques to gain insights into your responses immediately.

Analysis can be conducted using a variety of parameters to determine the validity and reliability of your survey data at scale.

5.   Surveys can collect any type of data

While most people view surveys as a quantitative research method, they can just as easily be adapted to gain qualitative information by simply including open-ended questions or conducting interviews face to face.

How to measure concepts with survey questions

While surveys are a great way to obtain data, that data on its own is useless unless it can be analyzed and developed into actionable insights.

The easiest, and most effective way to measure survey results, is to use a dedicated research tool that puts all of your survey results into one place.

When it comes to survey measurement, there are four measurement types to be aware of that will determine how you treat your different survey results:

Nominal scale

With a nominal scale , you can only keep track of how many respondents chose each option from a question, and which response generated the most selections.

An example of this would be simply asking a responder to choose a product or brand from a list.

You could find out which brand was chosen the most but have no insight as to why.

Ordinal scale

Ordinal scales are used to judge an order of preference. They do provide some level of quantitative value because you’re asking responders to choose a preference of one option over another.

Ratio scale

Ratio scales can be used to judge the order and difference between responses. For example, asking respondents how much they spend on their weekly shopping on average.

Interval scale

In an interval scale, values are lined up in order with a meaningful difference between the two values — for example, measuring temperature or measuring a credit score between one value and another.

Step by step: How to conduct surveys and collect data

Conducting a survey and collecting data is relatively straightforward, but it does require some careful planning and design to ensure it results in reliable data.

Step 1 – Define your objectives

What do you want to learn from the survey? How is the data going to help you? Having a hypothesis or series of assumptions about survey responses will allow you to create the right questions to test them.

Step 2 – Create your survey questions

Once you’ve got your hypotheses or assumptions, write out the questions you need answering to test your theories or beliefs. Be wary about framing questions that could lead respondents or inadvertently create biased responses .

Step 3 – Choose your question types

Your survey should include a variety of question types and should aim to obtain quantitative data with some qualitative responses from open-ended questions. Using a mix of questions (simple Yes/ No, multiple-choice, rank in order, etc) not only increases the reliability of your data but also reduces survey fatigue and respondents simply answering questions quickly without thinking.

Find out how to create a survey that’s easy to engage with

Step 4 – Test your questions

Before sending your questionnaire out, you should test it (e.g. have a random internal group do the survey) and carry out A/B tests to ensure you’ll gain accurate responses.

Step 5 – Choose your target and send out the survey

Depending on your objectives, you might want to target the general population with your survey or a specific segment of the population. Once you’ve narrowed down who you want to target, it’s time to send out the survey.

After you’ve deployed the survey, keep an eye on the response rate to ensure you’re getting the number you expected. If your response rate is low, you might need to send the survey out to a second group to obtain a large enough sample — or do some troubleshooting to work out why your response rates are so low. This could be down to your questions, delivery method, selected sample, or otherwise.

Step 6 – Analyze results and draw conclusions

Once you’ve got your results back, it’s time for the fun part.

Break down your survey responses using the parameters you’ve set in your objectives and analyze the data to compare to your original assumptions. At this stage, a research tool or software can make the analysis a lot easier — and that’s somewhere Qualtrics can help.

Get reliable insights with survey software from Qualtrics

Gaining feedback from customers and leads is critical for any business, data gathered from surveys can prove invaluable for understanding your products and your market position, and with survey software from Qualtrics, it couldn’t be easier.

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Get feedback from more than 125 sources on a single platform and view and measure your data in one place to create actionable insights and gain a deeper understanding of your target customers .

Automatically run complex text and statistical analysis to uncover exactly what your survey data is telling you, so you can react in real-time and make smarter decisions.

We can help you with survey management, too. From designing your survey and finding your target respondents to getting your survey in the field and reporting back on the results, we can help you every step of the way.

And for expert market researchers and survey designers, Qualtrics features custom programming to give you total flexibility over question types, survey design, embedded data, and other variables.

No matter what type of survey you want to run, what target audience you want to reach, or what assumptions you want to test or answers you want to uncover, we’ll help you design, deploy and analyze your survey with our team of experts.

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Related resources

Survey bias types 24 min read, post event survey questions 10 min read, best survey software 16 min read, close-ended questions 7 min read, survey vs questionnaire 12 min read, response bias 13 min read, double barreled question 11 min read, request demo.

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7.1 Survey research: What is it and when should it be used?

Learning objectives.

• Define survey research
• Identify when it is appropriate to employ survey research as a data-collection strategy

Most of you have probably taken a survey at one time or another, so you probably have a pretty good idea of what a survey is.  However, there is more to constructing a good survey than meets the eye. Survey design takes a great deal of thoughtful planning and often a great many rounds of revision. But it is worth the effort. As we’ll learn in this chapter, there are many benefits to choosing survey research as a method of data collection. We’ll take a look at what a survey is exactly, what some of the benefits and drawbacks of this method are, how to construct a survey, and what to do with survey data once it is collected.

Survey research is a quantitative method in which a researcher poses a set of predetermined questions to a sample of individuals. Survey research is an especially useful approach when a researcher aims to describe or explain features of a very large group or groups. This method may also be used as a way of quickly gaining some general details about a population of interest. In this case, a survey may help a researcher identify specific individuals or locations from which to collect additional data.

As is true of all methods of data collection, survey research is better suited to answering some kinds of research questions more than others. In addition, as you’ll recall from Chapter 5, operationalization works differently with different research methods. If your interest is in political activism, for example, you might operationalize that concept differently in a survey than you would for an experimental study of the same topic.

Spotlight on UTA SChool of social work

Diana padilla-medina conducts survey research.

Dr. Diana Padilla-Medina , an assistant professor at the University of Texas at Arlington’s School of Social Work, and a team of researchers (Padilla-Medina, Rodríguez, & Vega, 2019; Padilla-Medina, Rodríguez, Vega & Williams, 2019) are conducting a cross-sectional survey with a sample of urban Puerto Rican adolescents living in Puerto Rico to study the behavioral factors that influence adolescents’ intention to use physical and psychological abusive behaviors in dating and romantic relationships.  The study also explores how gender, development stage, and exposure to family violence influence both behavioral factors and intentions.  A sample of 2000 adolescents between the ages of 13 and 17 years are being recruited from communities across five towns in Puerto Rico using area sampling techniques.  Area sampling is a technique often used in survey research conducted in large geographical settings, such as towns and communities.  When using this technique, the target population is divided into clusters, or geographic areas, and a random sample of the clusters are selected.  Communities served as the geographic area from which adolescents were recruited.  As with any research study involving human subjects, consent and assent was obtained from participants and their parents or caregivers.

An in-person survey in which an interviewer administers the survey is being administered to the adolescents in their homes. For this survey research, an interview schedule (i.e., survey instrument or questionnaire) was developed.  When developing a survey instrument or questionnaire, it is important to consider the audience in order to choose the appropriate form to administer the survey.  In this case, Dr. Padilla-Medina and her team, based on previous pilot qualitative and quantitative studies, determined that Puerto Ricans prefer to be interviewed in person, particularly when the study topic and questions are personal and sensitive.  Additionally, when developing and/or administering a survey instrument it is important to pilot test the instrument to evaluate adequacy, psychometric properties, time, cost, adverse events, and improve upon the instrument prior to using it in a larger sample.  For example, in their previous studies, the researchers used focus groups to learn about the adolescents’ perceptions about the readability and understandability of the instrument.  In addition, the instrument was pilot tested to assess its psychometric properties and ensure it was ready for use in the larger survey research.

Finally, in any type of survey research, there is the potential for social desirability effects.  This means that participants’ report an answer that he or she thinks would be desirable or acceptable by the interviewer, rather than their “true” answer.  These behaviors could bias the study results.  There are several social desirability measures that are used to reduce the possibility of these types of biases.  Considering the sensitive nature of the current study topic and questions, the researchers used a social desirability measure to assess if the adolescents were or not concerned with social approval.

Key Takeaways

• Survey research is often used by researchers who wish to explain trends or features of large groups. It may also be used to assist those planning some more focused, in-depth study.
• Survey research- a quantitative method whereby a researcher poses some set of predetermined questions to a sample

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Foundations of Social Work Research Copyright © 2020 by Rebecca L. Mauldin is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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8.1 Survey Research: What Is It and When Should It Be Used?

Learning objectives.

• Define survey research.
• Identify when it is appropriate to employ survey research as a data-collection strategy.

Most of you have probably taken a survey at one time or another, so you probably have a pretty good idea of what a survey is. Sometimes students in my research methods classes feel that understanding what a survey is and how to write one is so obvious, there’s no need to dedicate any class time to learning about it. This feeling is understandable—surveys are very much a part of our everyday lives—we’ve probably all taken one, we hear about their results in the news, and perhaps we’ve even administered one ourselves. What students quickly learn is that there is more to constructing a good survey than meets the eye. Survey design takes a great deal of thoughtful planning and often a great many rounds of revision. But it is worth the effort. As we’ll learn in this chapter, there are many benefits to choosing survey research as one’s method of data collection. We’ll take a look at what a survey is exactly, what some of the benefits and drawbacks of this method are, how to construct a survey, and what to do with survey data once one has it in hand.

Survey research A quantitative method for which a researcher poses the same set of questions, typically in a written format, to a sample of individuals. is a quantitative method whereby a researcher poses some set of predetermined questions to an entire group, or sample, of individuals. Survey research is an especially useful approach when a researcher aims to describe or explain features of a very large group or groups. This method may also be used as a way of quickly gaining some general details about one’s population of interest to help prepare for a more focused, in-depth study using time-intensive methods such as in-depth interviews or field research. In this case, a survey may help a researcher identify specific individuals or locations from which to collect additional data.

As is true of all methods of data collection, survey research is better suited to answering some kinds of research question more than others. In addition, as you’ll recall from Chapter 6 "Defining and Measuring Concepts" , operationalization works differently with different research methods. If your interest is in political activism, for example, you likely operationalize that concept differently in a survey than you would for a field research study of the same topic.

Key Takeaway

• Survey research is often used by researchers who wish to explain trends or features of large groups. It may also be used to assist those planning some more focused, in-depth study.
• Recall some of the possible research questions you came up with while reading previous chapters of this text. How might you frame those questions so that they could be answered using survey research?

A Comprehensive Guide to Survey Research Methodologies

For decades, researchers and businesses have used survey research to produce statistical data and explore ideas. The survey process is simple, ask questions and analyze the responses to make decisions. Data is what makes the difference between a valid and invalid statement and as the American statistician, W. Edwards Deming said:

“Without data, you’re just another person with an opinion.” - W. Edwards Deming

In this article, we will discuss what survey research is, its brief history, types, common uses, benefits, and the step-by-step process of designing a survey.

What is Survey Research

A survey is a research method that is used to collect data from a group of respondents in order to gain insights and information regarding a particular subject. It’s an excellent method to gather opinions and understand how and why people feel a certain way about different situations and contexts.

Brief History of Survey Research

Survey research may have its roots in the American and English “social surveys” conducted around the turn of the 20th century. The surveys were mainly conducted by researchers and reformers to document the extent of social issues such as poverty. ( 1 ) Despite being a relatively young field to many scientific domains, survey research has experienced three stages of development ( 2 ):

-       First Era (1930-1960)

-       Second Era (1960-1990)

-       Third Era (1990 onwards)

Over the years, survey research adapted to the changing times and technologies. By exploiting the latest technologies, researchers can gain access to the right population from anywhere in the world, analyze the data like never before, and extract useful information.

Survey Research Methods & Types

Survey research can be classified into seven categories based on objective, data sources, methodology, deployment method, and frequency of deployment.

Surveys based on Objective

Exploratory survey research.

Exploratory survey research is aimed at diving deeper into research subjects and finding out more about their context. It’s important for marketing or business strategy and the focus is to discover ideas and insights instead of gathering statistical data.

Generally, exploratory survey research is composed of open-ended questions that allow respondents to express their thoughts and perspectives. The final responses present information from various sources that can lead to fresh initiatives.

Predictive Survey Research

Predictive survey research is also called causal survey research. It’s preplanned, structured, and quantitative in nature. It’s often referred to as conclusive research as it tries to explain the cause-and-effect relationship between different variables. The objective is to understand which variables are causes and which are effects and the nature of the relationship between both variables.

Descriptive Survey Research

Descriptive survey research is largely observational and is ideal for gathering numeric data. Due to its quantitative nature, it’s often compared to exploratory survey research. The difference between the two is that descriptive research is structured and pre-planned.

 The idea behind descriptive research is to describe the mindset and opinion of a particular group of people on a given subject. The questions are every day multiple choices and users must choose from predefined categories. With predefined choices, you don’t get unique insights, rather, statistically inferable data.

Survey Research Types based on Concept Testing

Monadic concept testing.

Monadic testing is a survey research methodology in which the respondents are split into multiple groups and ask each group questions about a separate concept in isolation. Generally, monadic surveys are hyper-focused on a particular concept and shorter in duration. The important thing in monadic surveys is to avoid getting off-topic or exhausting the respondents with too many questions.

Sequential Monadic Concept Testing

Another approach to monadic testing is sequential monadic testing. In sequential monadic surveys, groups of respondents are surveyed in isolation. However, instead of surveying three groups on three different concepts, the researchers survey the same groups of people on three distinct concepts one after another. In a sequential monadic survey, at least two topics are included (in random order), and the same questions are asked for each concept to eliminate bias.

Based on Data Source

Primary data.

Data obtained directly from the source or target population is referred to as primary survey data. When it comes to primary data collection, researchers usually devise a set of questions and invite people with knowledge of the subject to respond. The main sources of primary data are interviews, questionnaires, surveys, and observation methods.

 Compared to secondary data, primary data is gathered from first-hand sources and is more reliable. However, the process of primary data collection is both costly and time-consuming.

Secondary Data

Survey research is generally used to collect first-hand information from a respondent. However, surveys can also be designed to collect and process secondary data. It’s collected from third-party sources or primary sources in the past.

 This type of data is usually generic, readily available, and cheaper than primary data collection. Some common sources of secondary data are books, data collected from older surveys, online data, and data from government archives. Beware that you might compromise the validity of your findings if you end up with irrelevant or inflated data.

Based on Research Method

Quantitative research.

Quantitative research is a popular research methodology that is used to collect numeric data in a systematic investigation. It’s frequently used in research contexts where statistical data is required, such as sciences or social sciences. Quantitative research methods include polls, systematic observations, and face-to-face interviews.

Qualitative Research

Qualitative research is a research methodology where you collect non-numeric data from research participants. In this context, the participants are not restricted to a specific system and provide open-ended information. Some common qualitative research methods include focus groups, one-on-one interviews, observations, and case studies.

Based on Deployment Method

Online surveys.

With technology advancing rapidly, the most popular method of survey research is an online survey. With the internet, you can not only reach a broader audience but also design and customize a survey and deploy it from anywhere. Online surveys have outperformed offline survey methods as they are less expensive and allow researchers to easily collect and analyze data from a large sample.

Paper or Print Surveys

As the name suggests, paper or print surveys use the traditional paper and pencil approach to collect data. Before the invention of computers, paper surveys were the survey method of choice.

Though many would assume that surveys are no longer conducted on paper, it's still a reliable method of collecting information during field research and data collection. However, unlike online surveys, paper surveys are expensive and require extra human resources.

Telephonic Surveys

Telephonic surveys are conducted over telephones where a researcher asks a series of questions to the respondent on the other end. Contacting respondents over a telephone requires less effort, human resources, and is less expensive.

What makes telephonic surveys debatable is that people are often reluctant in giving information over a phone call. Additionally, the success of such surveys depends largely on whether people are willing to invest their time on a phone call answering questions.

One-on-one Surveys

One-on-one surveys also known as face-to-face surveys are interviews where the researcher and respondent. Interacting directly with the respondent introduces the human factor into the survey.

Face-to-face interviews are useful when the researcher wants to discuss something personal with the respondent. The response rates in such surveys are always higher as the interview is being conducted in person. However, these surveys are quite expensive and the success of these depends on the knowledge and experience of the researcher.

Based on Distribution

The easiest and most common way of conducting online surveys is sending out an email. Sending out surveys via emails has a higher response rate as your target audience already knows about your brand and is likely to engage.

Buy Survey Responses

Purchasing survey responses also yields higher responses as the responders signed up for the survey. Businesses often purchase survey samples to conduct extensive research. Here, the target audience is often pre-screened to check if they're qualified to take part in the research.

Embedding Survey on a Website

Embedding surveys on a website is another excellent way to collect information. It allows your website visitors to take part in a survey without ever leaving the website and can be done while a person is entering or exiting the website.

Post the Survey on Social Media

Social media is an excellent medium to reach abroad range of audiences. You can publish your survey as a link on social media and people who are following the brand can take part and answer questions.

Based on Frequency of Deployment

Cross-sectional studies.

Cross-sectional studies are administered to a small sample from a large population within a short period of time. This provides researchers a peek into what the respondents are thinking at a given time. The surveys are usually short, precise, and specific to a particular situation.

Longitudinal Surveys

Longitudinal surveys are an extension of cross-sectional studies where researchers make an observation and collect data over extended periods of time. This type of survey can be further divided into three types:

-       Trend surveys are employed to allow researchers to understand the change in the thought process of the respondents over some time.

-       Panel surveys are administered to the same group of people over multiple years. These are usually expensive and researchers must stick to their panel to gather unbiased opinions.

-       In cohort surveys, researchers identify a specific category of people and regularly survey them. Unlike panel surveys, the same people do not need to take part over the years, but each individual must fall into the researcher’s primary interest category.

Retrospective Survey

Retrospective surveys allow researchers to ask questions to gather data about past events and beliefs of the respondents. Since retrospective surveys also require years of data, they are similar to the longitudinal survey, except retrospective surveys are shorter and less expensive.

Why Should You Conduct Research Surveys?

“In God we trust. All others must bring data” - W. Edwards Deming

 In the information age, survey research is of utmost importance and essential for understanding the opinion of your target population. Whether you’re launching a new product or conducting a social survey, the tool can be used to collect specific information from a defined set of respondents. The data collected via surveys can be further used by organizations to make informed decisions.

Furthermore, compared to other research methods, surveys are relatively inexpensive even if you’re giving out incentives. Compared to the older methods such as telephonic or paper surveys, online surveys have a smaller cost and the number of responses is higher.

 What makes surveys useful is that they describe the characteristics of a large population. With a larger sample size , you can rely on getting more accurate results. However, you also need honest and open answers for accurate results. Since surveys are also anonymous and the responses remain confidential, respondents provide candid and accurate answers.

Common Uses of a Survey

Surveys are widely used in many sectors, but the most common uses of the survey research include:

-       Market research : surveying a potential market to understand customer needs, preferences, and market demand.

-       Customer Satisfaction: finding out your customer’s opinions about your services, products, or companies .

-       Social research: investigating the characteristics and experiences of various social groups.

-       Health research: collecting data about patients’ symptoms and treatments.

-       Politics: evaluating public opinion regarding policies and political parties.

-       Psychology: exploring personality traits, behaviors, and preferences.

6 Steps to Conduct Survey Research

An organization, person, or company conducts a survey when they need the information to make a decision but have insufficient data on hand. Following are six simple steps that can help you design a great survey.

Step 1: Objective of the Survey

The first step in survey research is defining an objective. The objective helps you define your target population and samples. The target population is the specific group of people you want to collect data from and since it’s rarely possible to survey the entire population, we target a specific sample from it. Defining a survey objective also benefits your respondents by helping them understand the reason behind the survey.

Step 2: Number of Questions

The number of questions or the size of the survey depends on the survey objective. However, it’s important to ensure that there are no redundant queries and the questions are in a logical order. Rephrased and repeated questions in a survey are almost as frustrating as in real life. For a higher completion rate, keep the questionnaire small so that the respondents stay engaged to the very end. The ideal length of an interview is less than 15 minutes. ( 2 )

Step 3: Language and Voice of Questions

While designing a survey, you may feel compelled to use fancy language. However, remember that difficult language is associated with higher survey dropout rates. You need to speak to the respondent in a clear, concise, and neutral manner, and ask simple questions. If your survey respondents are bilingual, then adding an option to translate your questions into another language can also prove beneficial.

Step 4: Type of Questions

In a survey, you can include any type of questions and even both closed-ended or open-ended questions. However, opt for the question types that are the easiest to understand for the respondents, and offer the most value. For example, compared to open-ended questions, people prefer to answer close-ended questions such as MCQs (multiple choice questions)and NPS (net promoter score) questions.

Step 5: User Experience

Designing a great survey is about more than just questions. A lot of researchers underestimate the importance of user experience and how it affects their response and completion rates. An inconsistent, difficult-to-navigate survey with technical errors and poor color choice is unappealing for the respondents. Make sure that your survey is easy to navigate for everyone and if you’re using rating scales, they remain consistent throughout the research study.

Additionally, don’t forget to design a good survey experience for both mobile and desktop users. According to Pew Research Center, nearly half of the smartphone users access the internet mainly from their mobile phones and 14 percent of American adults are smartphone-only internet users. ( 3 )

Step 6: Survey Logic

Last but not least, logic is another critical aspect of the survey design. If the survey logic is flawed, respondents may not continue in the right direction. Make sure to test the logic to ensure that selecting one answer leads to the next logical question instead of a series of unrelated queries.

How to Effectively Use Survey Research with Starlight Analytics

Designing and conducting a survey is almost as much science as it is an art. To craft great survey research, you need technical skills, consider the psychological elements, and have a broad understanding of marketing.

The ultimate goal of the survey is to ask the right questions in the right manner to acquire the right results.

Bringing a new product to the market is a long process and requires a lot of research and analysis. In your journey to gather information or ideas for your business, Starlight Analytics can be an excellent guide. Starlight Analytics' product concept testing helps you measure your product's market demand and refine product features and benefits so you can launch with confidence. The process starts with custom research to design the survey according to your needs, execute the survey, and deliver the key insights on time.

• Survey research in the United States: roots and emergence, 1890-1960 https://searchworks.stanford.edu/view/10733873    
• How to create a survey questionnaire that gets great responses https://luc.id/knowledgehub/how-to-create-a-survey-questionnaire-that-gets-great-responses/    
• Internet/broadband fact sheet https://www.pewresearch.org/internet/fact-sheet/internet-broadband/    

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9 Survey research

Survey research is a research method involving the use of standardised questionnaires or interviews to collect data about people and their preferences, thoughts, and behaviours in a systematic manner. Although census surveys were conducted as early as Ancient Egypt, survey as a formal research method was pioneered in the 1930–40s by sociologist Paul Lazarsfeld to examine the effects of the radio on political opinion formation of the United States. This method has since become a very popular method for quantitative research in the social sciences.

The survey method can be used for descriptive, exploratory, or explanatory research. This method is best suited for studies that have individual people as the unit of analysis. Although other units of analysis, such as groups, organisations or dyads—pairs of organisations, such as buyers and sellers—are also studied using surveys, such studies often use a specific person from each unit as a ‘key informant’ or a ‘proxy’ for that unit. Consequently, such surveys may be subject to respondent bias if the chosen informant does not have adequate knowledge or has a biased opinion about the phenomenon of interest. For instance, Chief Executive Officers may not adequately know employees’ perceptions or teamwork in their own companies, and may therefore be the wrong informant for studies of team dynamics or employee self-esteem.

Survey research has several inherent strengths compared to other research methods. First, surveys are an excellent vehicle for measuring a wide variety of unobservable data, such as people’s preferences (e.g., political orientation), traits (e.g., self-esteem), attitudes (e.g., toward immigrants), beliefs (e.g., about a new law), behaviours (e.g., smoking or drinking habits), or factual information (e.g., income). Second, survey research is also ideally suited for remotely collecting data about a population that is too large to observe directly. A large area—such as an entire country—can be covered by postal, email, or telephone surveys using meticulous sampling to ensure that the population is adequately represented in a small sample. Third, due to their unobtrusive nature and the ability to respond at one’s convenience, questionnaire surveys are preferred by some respondents. Fourth, interviews may be the only way of reaching certain population groups such as the homeless or illegal immigrants for which there is no sampling frame available. Fifth, large sample surveys may allow detection of small effects even while analysing multiple variables, and depending on the survey design, may also allow comparative analysis of population subgroups (i.e., within-group and between-group analysis). Sixth, survey research is more economical in terms of researcher time, effort and cost than other methods such as experimental research and case research. At the same time, survey research also has some unique disadvantages. It is subject to a large number of biases such as non-response bias, sampling bias, social desirability bias, and recall bias, as discussed at the end of this chapter.

Depending on how the data is collected, survey research can be divided into two broad categories: questionnaire surveys (which may be postal, group-administered, or online surveys), and interview surveys (which may be personal, telephone, or focus group interviews). Questionnaires are instruments that are completed in writing by respondents, while interviews are completed by the interviewer based on verbal responses provided by respondents. As discussed below, each type has its own strengths and weaknesses in terms of their costs, coverage of the target population, and researcher’s flexibility in asking questions.

Questionnaire surveys

Invented by Sir Francis Galton, a questionnaire is a research instrument consisting of a set of questions (items) intended to capture responses from respondents in a standardised manner. Questions may be unstructured or structured. Unstructured questions ask respondents to provide a response in their own words, while structured questions ask respondents to select an answer from a given set of choices. Subjects’ responses to individual questions (items) on a structured questionnaire may be aggregated into a composite scale or index for statistical analysis. Questions should be designed in such a way that respondents are able to read, understand, and respond to them in a meaningful way, and hence the survey method may not be appropriate or practical for certain demographic groups such as children or the illiterate.

Most questionnaire surveys tend to be self-administered postal surveys , where the same questionnaire is posted to a large number of people, and willing respondents can complete the survey at their convenience and return it in prepaid envelopes. Postal surveys are advantageous in that they are unobtrusive and inexpensive to administer, since bulk postage is cheap in most countries. However, response rates from postal surveys tend to be quite low since most people ignore survey requests. There may also be long delays (several months) in respondents’ completing and returning the survey, or they may even simply lose it. Hence, the researcher must continuously monitor responses as they are being returned, track and send non-respondents repeated reminders (two or three reminders at intervals of one to one and a half months is ideal). Questionnaire surveys are also not well-suited for issues that require clarification on the part of the respondent or those that require detailed written responses. Longitudinal designs can be used to survey the same set of respondents at different times, but response rates tend to fall precipitously from one survey to the next.

A second type of survey is a group-administered questionnaire . A sample of respondents is brought together at a common place and time, and each respondent is asked to complete the survey questionnaire while in that room. Respondents enter their responses independently without interacting with one another. This format is convenient for the researcher, and a high response rate is assured. If respondents do not understand any specific question, they can ask for clarification. In many organisations, it is relatively easy to assemble a group of employees in a conference room or lunch room, especially if the survey is approved by corporate executives.

A more recent type of questionnaire survey is an online or web survey. These surveys are administered over the Internet using interactive forms. Respondents may receive an email request for participation in the survey with a link to a website where the survey may be completed. Alternatively, the survey may be embedded into an email, and can be completed and returned via email. These surveys are very inexpensive to administer, results are instantly recorded in an online database, and the survey can be easily modified if needed. However, if the survey website is not password-protected or designed to prevent multiple submissions, the responses can be easily compromised. Furthermore, sampling bias may be a significant issue since the survey cannot reach people who do not have computer or Internet access, such as many of the poor, senior, and minority groups, and the respondent sample is skewed toward a younger demographic who are online much of the time and have the time and ability to complete such surveys. Computing the response rate may be problematic if the survey link is posted on LISTSERVs or bulletin boards instead of being emailed directly to targeted respondents. For these reasons, many researchers prefer dual-media surveys (e.g., postal survey and online survey), allowing respondents to select their preferred method of response.

Constructing a survey questionnaire is an art. Numerous decisions must be made about the content of questions, their wording, format, and sequencing, all of which can have important consequences for the survey responses.

Response formats. Survey questions may be structured or unstructured. Responses to structured questions are captured using one of the following response formats:

Dichotomous response , where respondents are asked to select one of two possible choices, such as true/false, yes/no, or agree/disagree. An example of such a question is: Do you think that the death penalty is justified under some circumstances? (circle one): yes / no.

Nominal response , where respondents are presented with more than two unordered options, such as: What is your industry of employment?: manufacturing / consumer services / retail / education / healthcare / tourism and hospitality / other.

Ordinal response , where respondents have more than two ordered options, such as: What is your highest level of education?: high school / bachelor’s degree / postgraduate degree.

Interval-level response , where respondents are presented with a 5-point or 7-point Likert scale, semantic differential scale, or Guttman scale. Each of these scale types were discussed in a previous chapter.

Continuous response , where respondents enter a continuous (ratio-scaled) value with a meaningful zero point, such as their age or tenure in a firm. These responses generally tend to be of the fill-in-the blanks type.

Question content and wording. Responses obtained in survey research are very sensitive to the types of questions asked. Poorly framed or ambiguous questions will likely result in meaningless responses with very little value. Dillman (1978) [1] recommends several rules for creating good survey questions. Every single question in a survey should be carefully scrutinised for the following issues:

Is the question clear and understandable ?: Survey questions should be stated in very simple language, preferably in active voice, and without complicated words or jargon that may not be understood by a typical respondent. All questions in the questionnaire should be worded in a similar manner to make it easy for respondents to read and understand them. The only exception is if your survey is targeted at a specialised group of respondents, such as doctors, lawyers and researchers, who use such jargon in their everyday environment. Is the question worded in a negative manner ?: Negatively worded questions such as ‘Should your local government not raise taxes?’ tend to confuse many respondents and lead to inaccurate responses. Double-negatives should be avoided when designing survey questions.

Is the question ambiguous ?: Survey questions should not use words or expressions that may be interpreted differently by different respondents (e.g., words like ‘any’ or ‘just’). For instance, if you ask a respondent, ‘What is your annual income?’, it is unclear whether you are referring to salary/wages, or also dividend, rental, and other income, whether you are referring to personal income, family income (including spouse’s wages), or personal and business income. Different interpretation by different respondents will lead to incomparable responses that cannot be interpreted correctly.

Does the question have biased or value-laden words ?: Bias refers to any property of a question that encourages subjects to answer in a certain way. Kenneth Rasinky (1989) [2] examined several studies on people’s attitude toward government spending, and observed that respondents tend to indicate stronger support for ‘assistance to the poor’ and less for ‘welfare’, even though both terms had the same meaning. In this study, more support was also observed for ‘halting rising crime rate’ and less for ‘law enforcement’, more for ‘solving problems of big cities’ and less for ‘assistance to big cities’, and more for ‘dealing with drug addiction’ and less for ‘drug rehabilitation’. A biased language or tone tends to skew observed responses. It is often difficult to anticipate in advance the biasing wording, but to the greatest extent possible, survey questions should be carefully scrutinised to avoid biased language.

Is the question double-barrelled ?: Double-barrelled questions are those that can have multiple answers. For example, ‘Are you satisfied with the hardware and software provided for your work?’. In this example, how should a respondent answer if they are satisfied with the hardware, but not with the software, or vice versa? It is always advisable to separate double-barrelled questions into separate questions: ‘Are you satisfied with the hardware provided for your work?’, and ’Are you satisfied with the software provided for your work?’. Another example: ‘Does your family favour public television?’. Some people may favour public TV for themselves, but favour certain cable TV programs such as Sesame Street for their children.

Is the question too general ?: Sometimes, questions that are too general may not accurately convey respondents’ perceptions. If you asked someone how they liked a certain book and provided a response scale ranging from ‘not at all’ to ‘extremely well’, if that person selected ‘extremely well’, what do they mean? Instead, ask more specific behavioural questions, such as, ‘Will you recommend this book to others, or do you plan to read other books by the same author?’. Likewise, instead of asking, ‘How big is your firm?’ (which may be interpreted differently by respondents), ask, ‘How many people work for your firm?’, and/or ‘What is the annual revenue of your firm?’, which are both measures of firm size.

Is the question too detailed ?: Avoid unnecessarily detailed questions that serve no specific research purpose. For instance, do you need the age of each child in a household, or is just the number of children in the household acceptable? However, if unsure, it is better to err on the side of details than generality.

Is the question presumptuous ?: If you ask, ‘What do you see as the benefits of a tax cut?’, you are presuming that the respondent sees the tax cut as beneficial. Many people may not view tax cuts as being beneficial, because tax cuts generally lead to lesser funding for public schools, larger class sizes, and fewer public services such as police, ambulance, and fire services. Avoid questions with built-in presumptions.

Is the question imaginary ?: A popular question in many television game shows is, ‘If you win a million dollars on this show, how will you spend it?’. Most respondents have never been faced with such an amount of money before and have never thought about it—they may not even know that after taxes, they will get only about $640,000 or so in the United States, and in many cases, that amount is spread over a 20-year period—and so their answers tend to be quite random, such as take a tour around the world, buy a restaurant or bar, spend on education, save for retirement, help parents or children, or have a lavish wedding. Imaginary questions have imaginary answers, which cannot be used for making scientific inferences.

Do respondents have the information needed to correctly answer the question ?: Oftentimes, we assume that subjects have the necessary information to answer a question, when in reality, they do not. Even if a response is obtained, these responses tend to be inaccurate given the subjects’ lack of knowledge about the question being asked. For instance, we should not ask the CEO of a company about day-to-day operational details that they may not be aware of, or ask teachers about how much their students are learning, or ask high-schoolers, ‘Do you think the US Government acted appropriately in the Bay of Pigs crisis?’.

Question sequencing. In general, questions should flow logically from one to the next. To achieve the best response rates, questions should flow from the least sensitive to the most sensitive, from the factual and behavioural to the attitudinal, and from the more general to the more specific. Some general rules for question sequencing:

Start with easy non-threatening questions that can be easily recalled. Good options are demographics (age, gender, education level) for individual-level surveys and firmographics (employee count, annual revenues, industry) for firm-level surveys.

Never start with an open ended question.

If following a historical sequence of events, follow a chronological order from earliest to latest.

Ask about one topic at a time. When switching topics, use a transition, such as, ‘The next section examines your opinions about…’

Use filter or contingency questions as needed, such as, ‘If you answered “yes” to question 5, please proceed to Section 2. If you answered “no” go to Section 3′.

Other golden rules . Do unto your respondents what you would have them do unto you. Be attentive and appreciative of respondents’ time, attention, trust, and confidentiality of personal information. Always practice the following strategies for all survey research:

People’s time is valuable. Be respectful of their time. Keep your survey as short as possible and limit it to what is absolutely necessary. Respondents do not like spending more than 10-15 minutes on any survey, no matter how important it is. Longer surveys tend to dramatically lower response rates.

Always assure respondents about the confidentiality of their responses, and how you will use their data (e.g., for academic research) and how the results will be reported (usually, in the aggregate).

For organisational surveys, assure respondents that you will send them a copy of the final results, and make sure that you follow up with your promise.

Thank your respondents for their participation in your study.

Finally, always pretest your questionnaire, at least using a convenience sample, before administering it to respondents in a field setting. Such pretesting may uncover ambiguity, lack of clarity, or biases in question wording, which should be eliminated before administering to the intended sample.

Interview survey

Interviews are a more personalised data collection method than questionnaires, and are conducted by trained interviewers using the same research protocol as questionnaire surveys (i.e., a standardised set of questions). However, unlike a questionnaire, the interview script may contain special instructions for the interviewer that are not seen by respondents, and may include space for the interviewer to record personal observations and comments. In addition, unlike postal surveys, the interviewer has the opportunity to clarify any issues raised by the respondent or ask probing or follow-up questions. However, interviews are time-consuming and resource-intensive. Interviewers need special interviewing skills as they are considered to be part of the measurement instrument, and must proactively strive not to artificially bias the observed responses.

The most typical form of interview is a personal or face-to-face interview , where the interviewer works directly with the respondent to ask questions and record their responses. Personal interviews may be conducted at the respondent’s home or office location. This approach may even be favoured by some respondents, while others may feel uncomfortable allowing a stranger into their homes. However, skilled interviewers can persuade respondents to co-operate, dramatically improving response rates.

A variation of the personal interview is a group interview, also called a focus group . In this technique, a small group of respondents (usually 6–10 respondents) are interviewed together in a common location. The interviewer is essentially a facilitator whose job is to lead the discussion, and ensure that every person has an opportunity to respond. Focus groups allow deeper examination of complex issues than other forms of survey research, because when people hear others talk, it often triggers responses or ideas that they did not think about before. However, focus group discussion may be dominated by a dominant personality, and some individuals may be reluctant to voice their opinions in front of their peers or superiors, especially while dealing with a sensitive issue such as employee underperformance or office politics. Because of their small sample size, focus groups are usually used for exploratory research rather than descriptive or explanatory research.

A third type of interview survey is a telephone interview . In this technique, interviewers contact potential respondents over the phone, typically based on a random selection of people from a telephone directory, to ask a standard set of survey questions. A more recent and technologically advanced approach is computer-assisted telephone interviewing (CATI). This is increasing being used by academic, government, and commercial survey researchers. Here the interviewer is a telephone operator who is guided through the interview process by a computer program displaying instructions and questions to be asked. The system also selects respondents randomly using a random digit dialling technique, and records responses using voice capture technology. Once respondents are on the phone, higher response rates can be obtained. This technique is not ideal for rural areas where telephone density is low, and also cannot be used for communicating non-audio information such as graphics or product demonstrations.

Role of interviewer. The interviewer has a complex and multi-faceted role in the interview process, which includes the following tasks:

Prepare for the interview: Since the interviewer is in the forefront of the data collection effort, the quality of data collected depends heavily on how well the interviewer is trained to do the job. The interviewer must be trained in the interview process and the survey method, and also be familiar with the purpose of the study, how responses will be stored and used, and sources of interviewer bias. They should also rehearse and time the interview prior to the formal study.

Locate and enlist the co-operation of respondents: Particularly in personal, in-home surveys, the interviewer must locate specific addresses, and work around respondents’ schedules at sometimes undesirable times such as during weekends. They should also be like a salesperson, selling the idea of participating in the study.

Motivate respondents: Respondents often feed off the motivation of the interviewer. If the interviewer is disinterested or inattentive, respondents will not be motivated to provide useful or informative responses either. The interviewer must demonstrate enthusiasm about the study, communicate the importance of the research to respondents, and be attentive to respondents’ needs throughout the interview.

Clarify any confusion or concerns: Interviewers must be able to think on their feet and address unanticipated concerns or objections raised by respondents to the respondents’ satisfaction. Additionally, they should ask probing questions as necessary even if such questions are not in the script.

Observe quality of response: The interviewer is in the best position to judge the quality of information collected, and may supplement responses obtained using personal observations of gestures or body language as appropriate.

Conducting the interview. Before the interview, the interviewer should prepare a kit to carry to the interview session, consisting of a cover letter from the principal investigator or sponsor, adequate copies of the survey instrument, photo identification, and a telephone number for respondents to call to verify the interviewer’s authenticity. The interviewer should also try to call respondents ahead of time to set up an appointment if possible. To start the interview, they should speak in an imperative and confident tone, such as, ‘I’d like to take a few minutes of your time to interview you for a very important study’, instead of, ‘May I come in to do an interview?’. They should introduce themself, present personal credentials, explain the purpose of the study in one to two sentences, and assure respondents that their participation is voluntary, and their comments are confidential, all in less than a minute. No big words or jargon should be used, and no details should be provided unless specifically requested. If the interviewer wishes to record the interview, they should ask for respondents’ explicit permission before doing so. Even if the interview is recorded, the interviewer must take notes on key issues, probes, or verbatim phrases

During the interview, the interviewer should follow the questionnaire script and ask questions exactly as written, and not change the words to make the question sound friendlier. They should also not change the order of questions or skip any question that may have been answered earlier. Any issues with the questions should be discussed during rehearsal prior to the actual interview sessions. The interviewer should not finish the respondent’s sentences. If the respondent gives a brief cursory answer, the interviewer should probe the respondent to elicit a more thoughtful, thorough response. Some useful probing techniques are:

The silent probe: Just pausing and waiting without going into the next question may suggest to respondents that the interviewer is waiting for more detailed response.

Overt encouragement: An occasional ‘uh-huh’ or ‘okay’ may encourage the respondent to go into greater details. However, the interviewer must not express approval or disapproval of what the respondent says.

Ask for elaboration: Such as, ‘Can you elaborate on that?’ or ‘A minute ago, you were talking about an experience you had in high school. Can you tell me more about that?’.

Reflection: The interviewer can try the psychotherapist’s trick of repeating what the respondent said. For instance, ‘What I’m hearing is that you found that experience very traumatic’ and then pause and wait for the respondent to elaborate.

After the interview is completed, the interviewer should thank respondents for their time, tell them when to expect the results, and not leave hastily. Immediately after leaving, they should write down any notes or key observations that may help interpret the respondent’s comments better.

Biases in survey research

Despite all of its strengths and advantages, survey research is often tainted with systematic biases that may invalidate some of the inferences derived from such surveys. Five such biases are the non-response bias, sampling bias, social desirability bias, recall bias, and common method bias.

Non-response bias. Survey research is generally notorious for its low response rates. A response rate of 15-20 per cent is typical in a postal survey, even after two or three reminders. If the majority of the targeted respondents fail to respond to a survey, this may indicate a systematic reason for the low response rate, which may in turn raise questions about the validity of the study’s results. For instance, dissatisfied customers tend to be more vocal about their experience than satisfied customers, and are therefore more likely to respond to questionnaire surveys or interview requests than satisfied customers. Hence, any respondent sample is likely to have a higher proportion of dissatisfied customers than the underlying population from which it is drawn. In this instance, not only will the results lack generalisability, but the observed outcomes may also be an artefact of the biased sample. Several strategies may be employed to improve response rates:

Advance notification: Sending a short letter to the targeted respondents soliciting their participation in an upcoming survey can prepare them in advance and improve their propensity to respond. The letter should state the purpose and importance of the study, mode of data collection (e.g., via a phone call, a survey form in the mail, etc.), and appreciation for their co-operation. A variation of this technique may be to ask the respondent to return a prepaid postcard indicating whether or not they are willing to participate in the study.

Relevance of content: People are more likely to respond to surveys examining issues of relevance or importance to them.

Respondent-friendly questionnaire: Shorter survey questionnaires tend to elicit higher response rates than longer questionnaires. Furthermore, questions that are clear, non-offensive, and easy to respond tend to attract higher response rates.

Endorsement: For organisational surveys, it helps to gain endorsement from a senior executive attesting to the importance of the study to the organisation. Such endorsement can be in the form of a cover letter or a letter of introduction, which can improve the researcher’s credibility in the eyes of the respondents.

Follow-up requests: Multiple follow-up requests may coax some non-respondents to respond, even if their responses are late.

Interviewer training: Response rates for interviews can be improved with skilled interviewers trained in how to request interviews, use computerised dialling techniques to identify potential respondents, and schedule call-backs for respondents who could not be reached.

Incentives : Incentives in the form of cash or gift cards, giveaways such as pens or stress balls, entry into a lottery, draw or contest, discount coupons, promise of contribution to charity, and so forth may increase response rates.

Non-monetary incentives: Businesses, in particular, are more prone to respond to non-monetary incentives than financial incentives. An example of such a non-monetary incentive is a benchmarking report comparing the business’s individual response against the aggregate of all responses to a survey.

Confidentiality and privacy: Finally, assurances that respondents’ private data or responses will not fall into the hands of any third party may help improve response rates

Sampling bias. Telephone surveys conducted by calling a random sample of publicly available telephone numbers will systematically exclude people with unlisted telephone numbers, mobile phone numbers, and people who are unable to answer the phone when the survey is being conducted—for instance, if they are at work—and will include a disproportionate number of respondents who have landline telephone services with listed phone numbers and people who are home during the day, such as the unemployed, the disabled, and the elderly. Likewise, online surveys tend to include a disproportionate number of students and younger people who are constantly on the Internet, and systematically exclude people with limited or no access to computers or the Internet, such as the poor and the elderly. Similarly, questionnaire surveys tend to exclude children and the illiterate, who are unable to read, understand, or meaningfully respond to the questionnaire. A different kind of sampling bias relates to sampling the wrong population, such as asking teachers (or parents) about their students’ (or children’s) academic learning, or asking CEOs about operational details in their company. Such biases make the respondent sample unrepresentative of the intended population and hurt generalisability claims about inferences drawn from the biased sample.

Social desirability bias . Many respondents tend to avoid negative opinions or embarrassing comments about themselves, their employers, family, or friends. With negative questions such as, ‘Do you think that your project team is dysfunctional?’, ‘Is there a lot of office politics in your workplace?’, ‘Or have you ever illegally downloaded music files from the Internet?’, the researcher may not get truthful responses. This tendency among respondents to ‘spin the truth’ in order to portray themselves in a socially desirable manner is called the ‘social desirability bias’, which hurts the validity of responses obtained from survey research. There is practically no way of overcoming the social desirability bias in a questionnaire survey, but in an interview setting, an astute interviewer may be able to spot inconsistent answers and ask probing questions or use personal observations to supplement respondents’ comments.

Recall bias. Responses to survey questions often depend on subjects’ motivation, memory, and ability to respond. Particularly when dealing with events that happened in the distant past, respondents may not adequately remember their own motivations or behaviours, or perhaps their memory of such events may have evolved with time and no longer be retrievable. For instance, if a respondent is asked to describe his/her utilisation of computer technology one year ago, or even memorable childhood events like birthdays, their response may not be accurate due to difficulties with recall. One possible way of overcoming the recall bias is by anchoring the respondent’s memory in specific events as they happened, rather than asking them to recall their perceptions and motivations from memory.

Common method bias. Common method bias refers to the amount of spurious covariance shared between independent and dependent variables that are measured at the same point in time, such as in a cross-sectional survey, using the same instrument, such as a questionnaire. In such cases, the phenomenon under investigation may not be adequately separated from measurement artefacts. Standard statistical tests are available to test for common method bias, such as Harmon’s single-factor test (Podsakoff, MacKenzie, Lee & Podsakoff, 2003), [3] Lindell and Whitney’s (2001) [4] market variable technique, and so forth. This bias can potentially be avoided if the independent and dependent variables are measured at different points in time using a longitudinal survey design, or if these variables are measured using different methods, such as computerised recording of dependent variable versus questionnaire-based self-rating of independent variables.

• Dillman, D. (1978). Mail and telephone surveys: The total design method . New York: Wiley. ↵
• Rasikski, K. (1989). The effect of question wording on public support for government spending. Public Opinion Quarterly , 53(3), 388–394. ↵
• Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology , 88(5), 879–903. http://dx.doi.org/10.1037/0021-9010.88.5.879. ↵
• Lindell, M. K., & Whitney, D. J. (2001). Accounting for common method variance in cross-sectional research designs. Journal of Applied Psychology , 86(1), 114–121. ↵

Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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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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Methodology

• Questionnaire Design | Methods, Question Types & Examples

Questionnaire Design | Methods, Question Types & Examples

Published on July 15, 2021 by Pritha Bhandari . Revised on June 22, 2023.

A questionnaire is a list of questions or items used to gather data from respondents about their attitudes, experiences, or opinions. Questionnaires can be used to collect quantitative and/or qualitative information.

Questionnaires are commonly used in market research as well as in the social and health sciences. For example, a company may ask for feedback about a recent customer service experience, or psychology researchers may investigate health risk perceptions using questionnaires.

Table of contents

Questionnaires vs. surveys, questionnaire methods, open-ended vs. closed-ended questions, question wording, question order, step-by-step guide to design, other interesting articles, frequently asked questions about questionnaire design.

A survey is a research method where you collect and analyze data from a group of people. A questionnaire is a specific tool or instrument for collecting the data.

Designing a questionnaire means creating valid and reliable questions that address your research objectives , placing them in a useful order, and selecting an appropriate method for administration.

But designing a questionnaire is only one component of survey research. Survey research also involves defining the population you’re interested in, choosing an appropriate sampling method , administering questionnaires, data cleansing and analysis, and interpretation.

Sampling is important in survey research because you’ll often aim to generalize your results to the population. Gather data from a sample that represents the range of views in the population for externally valid results. There will always be some differences between the population and the sample, but minimizing these will help you avoid several types of research bias , including sampling bias , ascertainment bias , and undercoverage bias .

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Questionnaires can be self-administered or researcher-administered . Self-administered questionnaires are more common because they are easy to implement and inexpensive, but researcher-administered questionnaires allow deeper insights.

Self-administered questionnaires

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or through mail. All questions are standardized so that all respondents receive the same questions with identical wording.

Self-administered questionnaires can be:

• cost-effective
• easy to administer for small and large groups
• anonymous and suitable for sensitive topics

But they may also be:

• unsuitable for people with limited literacy or verbal skills
• susceptible to a nonresponse bias (most people invited may not complete the questionnaire)
• biased towards people who volunteer because impersonal survey requests often go ignored.

Researcher-administered questionnaires

Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents.

Researcher-administered questionnaires can:

• help you ensure the respondents are representative of your target audience
• allow clarifications of ambiguous or unclear questions and answers
• have high response rates because it’s harder to refuse an interview when personal attention is given to respondents

But researcher-administered questionnaires can be limiting in terms of resources. They are:

• costly and time-consuming to perform
• more difficult to analyze if you have qualitative responses
• likely to contain experimenter bias or demand characteristics
• likely to encourage social desirability bias in responses because of a lack of anonymity

Your questionnaire can include open-ended or closed-ended questions or a combination of both.

Using closed-ended questions limits your responses, while open-ended questions enable a broad range of answers. You’ll need to balance these considerations with your available time and resources.

Closed-ended questions

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. Closed-ended questions are best for collecting data on categorical or quantitative variables.

Categorical variables can be nominal or ordinal. Quantitative variables can be interval or ratio. Understanding the type of variable and level of measurement means you can perform appropriate statistical analyses for generalizable results.

Examples of closed-ended questions for different variables

Nominal variables include categories that can’t be ranked, such as race or ethnicity. This includes binary or dichotomous categories.

It’s best to include categories that cover all possible answers and are mutually exclusive. There should be no overlap between response items.

In binary or dichotomous questions, you’ll give respondents only two options to choose from.

White Black or African American American Indian or Alaska Native Asian Native Hawaiian or Other Pacific Islander

Ordinal variables include categories that can be ranked. Consider how wide or narrow a range you’ll include in your response items, and their relevance to your respondents.

Likert scale questions collect ordinal data using rating scales with 5 or 7 points.

When you have four or more Likert-type questions, you can treat the composite data as quantitative data on an interval scale . Intelligence tests, psychological scales, and personality inventories use multiple Likert-type questions to collect interval data.

With interval or ratio scales , you can apply strong statistical hypothesis tests to address your research aims.

Pros and cons of closed-ended questions

Well-designed closed-ended questions are easy to understand and can be answered quickly. However, you might still miss important answers that are relevant to respondents. An incomplete set of response items may force some respondents to pick the closest alternative to their true answer. These types of questions may also miss out on valuable detail.

To solve these problems, you can make questions partially closed-ended, and include an open-ended option where respondents can fill in their own answer.

Open-ended questions

Open-ended, or long-form, questions allow respondents to give answers in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered. For example, respondents may want to answer “multiracial” for the question on race rather than selecting from a restricted list.

• How do you feel about open science?
• How would you describe your personality?
• In your opinion, what is the biggest obstacle for productivity in remote work?

Open-ended questions have a few downsides.

They require more time and effort from respondents, which may deter them from completing the questionnaire.

For researchers, understanding and summarizing responses to these questions can take a lot of time and resources. You’ll need to develop a systematic coding scheme to categorize answers, and you may also need to involve other researchers in data analysis for high reliability .

Question wording can influence your respondents’ answers, especially if the language is unclear, ambiguous, or biased. Good questions need to be understood by all respondents in the same way ( reliable ) and measure exactly what you’re interested in ( valid ).

Use clear language

You should design questions with your target audience in mind. Consider their familiarity with your questionnaire topics and language and tailor your questions to them.

For readability and clarity, avoid jargon or overly complex language. Don’t use double negatives because they can be harder to understand.

Use balanced framing

Respondents often answer in different ways depending on the question framing. Positive frames are interpreted as more neutral than negative frames and may encourage more socially desirable answers.

Use a mix of both positive and negative frames to avoid research bias , and ensure that your question wording is balanced wherever possible.

Unbalanced questions focus on only one side of an argument. Respondents may be less likely to oppose the question if it is framed in a particular direction. It’s best practice to provide a counter argument within the question as well.

Avoid leading questions

Leading questions guide respondents towards answering in specific ways, even if that’s not how they truly feel, by explicitly or implicitly providing them with extra information.

It’s best to keep your questions short and specific to your topic of interest.

• The average daily work commute in the US takes 54.2 minutes and costs $29 per day. Since 2020, working from home has saved many employees time and money. Do you favor flexible work-from-home policies even after it’s safe to return to offices?
• Experts agree that a well-balanced diet provides sufficient vitamins and minerals, and multivitamins and supplements are not necessary or effective. Do you agree or disagree that multivitamins are helpful for balanced nutrition?

Keep your questions focused

Ask about only one idea at a time and avoid double-barreled questions. Double-barreled questions ask about more than one item at a time, which can confuse respondents.

This question could be difficult to answer for respondents who feel strongly about the right to clean drinking water but not high-speed internet. They might only answer about the topic they feel passionate about or provide a neutral answer instead – but neither of these options capture their true answers.

Instead, you should ask two separate questions to gauge respondents’ opinions.

Strongly Agree Agree Undecided Disagree Strongly Disagree

Do you agree or disagree that the government should be responsible for providing high-speed internet to everyone?

You can organize the questions logically, with a clear progression from simple to complex. Alternatively, you can randomize the question order between respondents.

Logical flow

Using a logical flow to your question order means starting with simple questions, such as behavioral or opinion questions, and ending with more complex, sensitive, or controversial questions.

The question order that you use can significantly affect the responses by priming them in specific directions. Question order effects, or context effects, occur when earlier questions influence the responses to later questions, reducing the validity of your questionnaire.

While demographic questions are usually unaffected by order effects, questions about opinions and attitudes are more susceptible to them.

• How knowledgeable are you about Joe Biden’s executive orders in his first 100 days?
• Are you satisfied or dissatisfied with the way Joe Biden is managing the economy?
• Do you approve or disapprove of the way Joe Biden is handling his job as president?

It’s important to minimize order effects because they can be a source of systematic error or bias in your study.

Randomization

Randomization involves presenting individual respondents with the same questionnaire but with different question orders.

When you use randomization, order effects will be minimized in your dataset. But a randomized order may also make it harder for respondents to process your questionnaire. Some questions may need more cognitive effort, while others are easier to answer, so a random order could require more time or mental capacity for respondents to switch between questions.

Step 1: Define your goals and objectives

The first step of designing a questionnaire is determining your aims.

• What topics or experiences are you studying?
• What specifically do you want to find out?
• Is a self-report questionnaire an appropriate tool for investigating this topic?

Once you’ve specified your research aims, you can operationalize your variables of interest into questionnaire items. Operationalizing concepts means turning them from abstract ideas into concrete measurements. Every question needs to address a defined need and have a clear purpose.

Step 2: Use questions that are suitable for your sample

Create appropriate questions by taking the perspective of your respondents. Consider their language proficiency and available time and energy when designing your questionnaire.

• Are the respondents familiar with the language and terms used in your questions?
• Would any of the questions insult, confuse, or embarrass them?
• Do the response items for any closed-ended questions capture all possible answers?
• Are the response items mutually exclusive?
• Do the respondents have time to respond to open-ended questions?

Consider all possible options for responses to closed-ended questions. From a respondent’s perspective, a lack of response options reflecting their point of view or true answer may make them feel alienated or excluded. In turn, they’ll become disengaged or inattentive to the rest of the questionnaire.

Step 3: Decide on your questionnaire length and question order

Once you have your questions, make sure that the length and order of your questions are appropriate for your sample.

If respondents are not being incentivized or compensated, keep your questionnaire short and easy to answer. Otherwise, your sample may be biased with only highly motivated respondents completing the questionnaire.

Decide on your question order based on your aims and resources. Use a logical flow if your respondents have limited time or if you cannot randomize questions. Randomizing questions helps you avoid bias, but it can take more complex statistical analysis to interpret your data.

Step 4: Pretest your questionnaire

When you have a complete list of questions, you’ll need to pretest it to make sure what you’re asking is always clear and unambiguous. Pretesting helps you catch any errors or points of confusion before performing your study.

Ask friends, classmates, or members of your target audience to complete your questionnaire using the same method you’ll use for your research. Find out if any questions were particularly difficult to answer or if the directions were unclear or inconsistent, and make changes as necessary.

If you have the resources, running a pilot study will help you test the validity and reliability of your questionnaire. A pilot study is a practice run of the full study, and it includes sampling, data collection , and analysis. You can find out whether your procedures are unfeasible or susceptible to bias and make changes in time, but you can’t test a hypothesis with this type of study because it’s usually statistically underpowered .

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

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Prospective cohort study

Research bias

• Implicit bias
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic
• Social desirability bias

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

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. It is made up of 4 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 5 or 7 possible responses, to capture their degree of agreement.

You can organize the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomization can minimize the bias from order effects.

Questionnaires can be self-administered or researcher-administered.

Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

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Designing, Conducting, and Reporting Survey Studies: A Primer for Researchers

Olena zimba.

1 Department of Clinical Rheumatology and Immunology, University Hospital in Krakow, Krakow, Poland.

2 National Institute of Geriatrics, Rheumatology and Rehabilitation, Warsaw, Poland.

3 Department of Internal Medicine N2, Danylo Halytsky Lviv National Medical University, Lviv, Ukraine.

Armen Yuri Gasparyan

4 Departments of Rheumatology and Research and Development, Dudley Group NHS Foundation Trust (Teaching Trust of the University of Birmingham, UK), Russells Hall Hospital, Dudley, UK.

Survey studies have become instrumental in contributing to the evidence accumulation in rapidly developing medical disciplines such as medical education, public health, and nursing. The global medical community has seen an upsurge of surveys covering the experience and perceptions of health specialists, patients, and public representatives in the peri-pandemic coronavirus disease 2019 period. Currently, surveys can play a central role in increasing research activities in non-mainstream science countries where limited research funding and other barriers hinder science growth. Planning surveys starts with overviewing related reviews and other publications which may help to design questionnaires with comprehensive coverage of all related points. The validity and reliability of questionnaires rely on input from experts and potential responders who may suggest pertinent revisions to prepare forms with attractive designs, easily understandable questions, and correctly ordered points that appeal to target respondents. Currently available numerous online platforms such as Google Forms and Survey Monkey enable moderating online surveys and collecting responses from a large number of responders. Online surveys benefit from disseminating questionnaires via social media and other online platforms which facilitate the survey internationalization and participation of large groups of responders. Survey reporting can be arranged in line with related recommendations and reporting standards all of which have their strengths and limitations. The current article overviews available recommendations and presents pointers on designing, conducting, and reporting surveys.

INTRODUCTION

Surveys are increasingly popular research studies that are aimed at collecting and analyzing opinions of diverse subject groups at certain periods. Initially and predominantly employed for applied social science research, 1 surveys have maintained their social dimension and transformed into indispensable tools for analyzing knowledge, perceptions, prevalence of clinical conditions, and practices in the medical sciences. 2 In rapidly developing disciplines with social dimensions such as medical education, public health, and nursing, online surveys have become essential for monitoring and auditing healthcare and education services 3 , 4 and generating new hypotheses and research questions. 5 In non-mainstream science countries with uninterrupted Internet access, online surveys have also been praised as useful studies for increasing research activities. 6

In 2016, the Medical Subject Headings (MeSH) vocabulary of the US National Library of Medicine introduced "surveys and questionnaires" as a structured keyword, defining survey studies as "collections of data obtained from voluntary subjects" ( https://www.ncbi.nlm.nih.gov/mesh/?term=surveys+and+questionnaires ). Such studies are instrumental in the absence of evidence from randomized controlled trials, systematic reviews, and cohort studies. Tagging survey reports with this MeSH term is advisable for increasing the retrieval of relevant documents while searching through Medline, Scopus, and other global databases.

Surveys are relatively easy to conduct by distributing web-based and non-web-based questionnaires to large groups of potential responders. The ease of conduct primarily depends on the way of approaching potential respondents. Face-to-face interviews, regular postmails, e-mails, phone calls, and social media posts can be employed to reach numerous potential respondents. Digitization and social media popularization have improved the distribution of questionnaires, expanded respondents' engagement, facilitated swift data processing, and globalization of survey studies. 7

SURVEY REPORTING GUIDANCE

Despite the ease of survey studies and their importance for maintaining research activities across academic disciplines, their methodological quality, reproducibility, and implications vary widely. The deficiencies in designing and reporting are the main reason for the inefficiency of some surveys. For instance, systematic analyses of survey methodologies in nephrology, transfusion medicine, and radiology have indicated that less than one-third of related reports provide valid and reliable data. 8 , 9 , 10 Additionally, no discussions of respondents' representativeness, reasons for nonresponse, and generalizability of the results have been pinpointed as drawbacks of some survey reports. The revealed deficiencies have justified the need for survey designing and data processing in line with reporting recommendations, including those listed on the EQUATOR Network website ( https://www.equator-network.org/ ).

Arguably, survey studies lack discipline-specific and globally-acceptable reporting guidance. The diversity of surveyed subjects and populations is perhaps the main confounder. Although most questionnaires contain socio-demographic questions, there are no reporting guidelines specifically tailored to comprehensively inquire specialists across different academic disciplines, patients, and public representatives.

The EQUATOR Network platform currently lists some widely promoted documents with statements on conducting and reporting web-based and non-web-based surveys ( Table 1 ). 11 , 12 , 13 , 14 The oldest published recommendation guides on postal, face-to-face, and telephone interviews. 1 One of its critical points highlights the need to formulate a clear and explicit question/objective to run a focused survey and to design questionnaires with respondent-friendly layout and content. 1 The Checklist for Reporting Results of Internet E-Surveys (CHERRIES) is the most-used document for reporting online surveys. 11 The CHERRIES checklist included points on ensuring the reliability of online surveys and avoiding manipulations with multiple entries by the same users. 11 A specific set of recommendations, listed by the EQUATOR Network, is available for specialists who plan web-based and non-web-based surveys of knowledge, attitude, and practice in clinical medicine. 12 These recommendations help design valid questionnaires, survey representative subjects with clinical knowledge, and complete transparent reporting of the obtained results. 12

COVID-19 = coronavirus disease 2019.

From January 2018 to December 2019, three rounds of surveying experts with interest in surveys and questionnaires allowed reaching consensus on a set of points for reporting web-based and non-web-based surveys. 13 The Consensus-Based Checklist for Reporting of Survey Studies included a rating of 19 items of survey reports, from titles to acknowledgments. 13 Finally, rapid recommendations on online surveys amid the coronavirus disease 2019 (COVID-19) pandemic were published to guide the authors on how to choose social media and other online platforms for disseminating questionnaires and targeting representative groups of respondents. 14

Adhering to a combination of these recommendations is advisable to minimize the limitations of each document and increase the transparency of survey reports. For cross-sectional analyses of large sample sizes, additionally consulting the STROBE standard of the EQUATOR Network may further improve the accuracy of reporting respondents' inclusion and exclusion criteria. In fact, there are examples of online survey reports adhering to both CHERRIES and STROBE recommendations. 15 , 16

ETHICS CONSIDERATIONS

Although health research authorities in some countries lack mandates for full ethics review of survey studies, obtaining formal review protocols or ethics waivers is advisable for most surveys involving respondents from more than one country. And following country-based regulations and ethical norms of research are therefore mandatory. 14 , 17

Full ethics review or exemption procedures are important steps for planning and conducting ethically sound surveys. Given the non-interventional origin and absence of immediate health risks for participants, ethics committees may approve survey protocols without a full ethics review. 18 A full ethics review is however required when the informational and psychological harms of surveys increase the risk. 18 Informational harms may result from unauthorized access to respondents' personal data and stigmatization of respondents with leaked information about social diseases. Psychological harms may include anxiety, depression, and exacerbation of underlying psychiatric diseases.

Survey questionnaires submitted for evaluation should indicate how informed consent is obtained from respondents. 13 Additionally, information about confidentiality, anonymity, questionnaire delivery modes, compensations, and mechanisms preventing unauthorized access to questionnaires should be provided. 13 , 14 Ethical considerations and validation are especially important in studies involving vulnerable and marginalized subjects with diminished autonomy and poor social status due to dementia, substance abuse, inappropriate sexual behavior, and certain infections. 18 , 19 , 20 Precautions should be taken to avoid confidentiality breaches and bot activities when surveying via insecure online platforms. 21

Monetary compensation helps attract respondents to fill out lengthy questionnaires. However, such incentives may create mechanisms deceiving the system by surveyees with a primary interest in compensation. 22 Ethics review protocols may include points on recording online responders' IP addresses and blocking duplicate submissions from the same Internet locations. 22 IP addresses are viewed as personal information in the EU, but not in the US. Notably, IP identification may deter some potential responders in the EU. 21

PATIENT KNOWLEDGE AND PERCEPTION SURVEYS

The design of patient knowledge and perception surveys is insufficiently defined and poorly explored. Although such surveys are aimed at consistently covering research questions on clinical presentation, prevention, and treatment, more emphasis is now placed on psychometric aspects of designing related questionnaires. 23 , 24 , 25 Targeting responsive patient groups to collect reliable answers is yet another challenge that can be addressed by distributing questionnaires to patients with good knowledge of their diseases, particularly those registering with university-affiliated clinics and representing patient associations. 26 , 27 , 28

The structure of questionnaires may differ for surveys of patient groups with various age-dependent health issues. Care should be taken when children are targeted since they often report a variety of modifiable conditions such as anxiety and depression, musculoskeletal problems, and pain, affecting their quality of life. 29 Likewise, gender and age differences should be considered in questionnaires addressing the quality of life in association with mental health and social status. 30 Questionnaires for older adults may benefit from including questions about social support and assistance in the context of caring for aging diseases. 31 Finally, addressing the needs of digital technologies and home-care applications may help to ensure the completeness of questionnaires for older adults with sedentary lifestyles and mobility disabilities. 32 , 33

SOCIAL MEDIA FOR QUESTIONNAIRE DISTRIBUTION

The widespread use of social media has made it easier to distribute questionnaires to a large number of potential responders. Employing popular platforms such as Twitter and Facebook has become particularly useful for conducting nationwide surveys on awareness and concerns about global health and pandemic issues. 34 , 35 When various social media platforms are simultaneously employed, participants' sociodemographic factors such as gender, age, and level of education may confound the study results. 36 Knowing targeted groups' preferred online networking and communication sites may better direct the questionnaire distribution. 37 , 38 , 39

Preliminary evidence suggests that distributing survey links via social-media accounts of individual users and organized e-groups with interest in specific health issues may increase their engagement and correctness of responses. 40 , 41

Since surveys employing social media are publicly accessible, related questionnaires should be professionally edited to easily inquire target populations, avoid sensitive and disturbing points, and ensure privacy and confidentiality. 42 , 43 Although counting e-post views is feasible, response rates of social-media distributed questionnaires are practically impossible to record. The latter is an inherent limitation of such surveys.

SURVEY SAMPLING

Establishing connections with target populations and diversifying questionnaire dissemination may increase the rigor of current surveys which are abundantly administered. 44 Sample sizes depend on various factors, including the chosen topic, aim, and sampling strategy (random or non-random). 12 Some topics such as COVID-19 and global health may easily attract the attention of large respondent groups motivated to answer a variety of questionnaire questions. In the beginning of the pandemic, most surveys employed non-random (non-probability) sampling strategies which resulted in analyses of numerous responses without response rate calculations. These qualitative research studies were mainly aimed to analyze opinions of specialists and patients exposed to COVID-19 to develop rapid guidelines and initiate clinical trials.

Outside the pandemic, and beyond hot topics, there is a growing trend of low response rates and inadequate representation of target populations. 45 Such a trend makes it difficult to design and conduct random (probability) surveys. Subsequently, hypotheses of current online surveys often omit points on randomization and sample size calculation, ending up with qualitative analyses and pilot studies. In fact, convenience (non-random or non-probability) sampling can be particularly suitable for previously unexplored and emerging topics when overviewing literature cannot help estimate optimal samples and entirely new questionnaires should be designed and tested. The limitations of convenience sampling minimize the generalizability of the conclusions since the sample representativeness is uncertain. 45

Researchers often employ 'snowball' sampling techniques with initial surveyees forwarding the questionnaires to other interested respondents, thereby maximizing the sample size. Another common technique for obtaining more responses relies on generating regular social media reminders and resending e-mails to interested individuals and groups. Such tactics can increase the study duration but cannot exclude the participation bias and non-response.

Purposive or targeted sampling is perhaps the most precise technique when knowing the target population size and respondents' readiness to correctly fill the questionnaires and ensure an exact estimate of response rate, close to 100%. 46

DESIGNING QUESTIONNAIRES

Correctness, confidentiality, privacy, and anonymity are critical points of inquiry in questionnaires. 47 Correctly worded and convincingly presented survey invitations with consenting options and reassurances of secure data processing may increase response rates and ensure the validity of responses. 47 Online surveys are believed to be more advantageous than offline inquiries for ensuring anonymity and privacy, particularly for targeting socially marginalized and stigmatized subjects. Online study design is indeed optimal for collecting more responses in surveys of sex- and gender-related and otherwise sensitive topics.

Performing comprehensive literature reviews, consultations with subject experts, and Delphi exercises may all help to specify survey objectives, identify questionnaire domains, and formulate pertinent questions. Literature searches are required for in-depth topic coverage and identification of previously published relevant surveys. By analyzing previous questionnaire characteristics, modifications can be made to designing new self-administered surveys. The justification of new studies should correctly acknowledge similar published reports to avoid redundancies.

The initial part of a questionnaire usually includes a short introduction/preamble/cover letter that specifies the objectives, target respondents, potential benefits and risks, and moderators' contact details for further inquiries. This part may motivate potential respondents to consent and answer questions. The specifics, volume, and format of other parts are dependent on revisions in response to pretesting and pilot testing. 48 The pretesting usually involves co-authors and other contributors, colleagues with the subject interest while the pilot testing usually involves 5-10 target respondents who are well familiar with the subject and can swiftly complete the questionnaires. The guidance obtained at the pretesting and pilot testing allows editing, shortening, or expanding questionnaire sections. Although guidance on questionnaire length and question numbers is scarce, some experts empirically consider 5 domains with 5 questions in each as optimal. 12 Lengthy questionnaires may be biased due to respondents' fatigue and inability to answer numerous and complicated questions. 46

Questionnaire revisions are aimed at ensuring the validity and consistency of questions, implying the appeal to relevant responders and accurate covering of all essential points. 45 Valid questionnaires enable reliable and reproducible survey studies that end up with the same responses to variably worded and located questions. 45

Various combinations of open-ended and close-ended questions are advisable to comprehensively cover all pertinent points and enable easy and quick completion of questionnaires. Open-ended questions are usually included in small numbers since these require more time to respond. 46 Also, the interpretation and analysis of responses to open-ended questions hardly contribute to generating robust qualitative data. 49 Close-ended questions with single and multiple-choice answers constitute the main part of a questionnaire, with single answers easier to analyze and report. Questions with single answers can be presented as 3 or more Likert scales (e.g., yes/no/do not know).

Avoiding too simplistic (yes/no) questions and replacing them with Likert-scale items may increase the robustness of questionnaire analyses. 50 Additionally, constructing easily understandable questions, excluding merged items with two or more points, and moving sophisticated questions to the beginning of a questionnaire may add to the quality and feasibility of the study. 50

Survey studies are increasingly conducted by health professionals to swiftly explore opinions on a wide range of topics by diverse groups of specialists, patients, and public representatives. Arguably, quality surveys with generalizable results can be instrumental for guiding health practitioners in times of crises such as the COVID-19 pandemic when clinical trials, systematic reviews, and other evidence-based reports are scarcely available or absent. Online surveys can be particularly valuable for collecting and analyzing specialist, patient, and other subjects' responses in non-mainstream science countries where top evidence-based studies are scarce commodities and research funding is limited. Accumulated expertise in drafting quality questionnaires and conducting robust surveys is valuable for producing new data and generating new hypotheses and research questions.

The main advantages of surveys are related to the ease of conducting such studies with limited or no research funding. The digitization and social media advances have further contributed to the ease of surveying and growing global interest toward surveys among health professionals. Some of the disadvantages of current surveys are perhaps those related to imperfections of digital platforms for disseminating questionnaires and analysing responses.

Although some survey reporting standards and recommendations are available, none of these comprehensively cover all items of questionnaires and steps in surveying. None of the survey reporting standards is based on summarizing guidance of a large number of contributors involved in related research projects. As such, presenting the current guidance with a list of items for survey reports ( Table 2 ) may help better design and publish related articles.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Zimba O.
• Formal analysis: Zimba O, Gasparyan AY.
• Writing - original draft: Zimba O.
• Writing - review & editing: Zimba O, Gasparyan AY.

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