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Survey Research | Definition, Examples & Methods

Survey Research | Definition, Examples & Methods

Published on August 20, 2019 by Shona McCombes . Revised on June 22, 2023.

Survey research means collecting information about a group of people by asking them questions and analyzing 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
Analyze the responses
Write up the results

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

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: analyze the survey results, step 6: write up the survey results, other interesting articles, 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 in 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
US college students
Second-generation immigrants in the Netherlands
Customers of a specific company aged 18-24
British transgender women over the age of 50

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

Several common research biases can arise if your survey is not generalizable, particularly sampling bias and selection bias . The presence of these biases have serious repercussions for the validity of your results.

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 college student in the US. 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 generalize 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. Again, beware of various types of sampling bias as you design your sample, particularly self-selection bias , nonresponse bias , undercoverage bias , and survivorship bias .

There are two main types of survey:

A questionnaire , where a list of questions is distributed by mail, 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 mail 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, and at risk for biases like self-selection bias .

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 analyze.
The anonymity and accessibility of online surveys mean you have less control over who responds, which can lead to biases like self-selection bias .

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 mall 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 store’s weekday customers).
The sample size will be smaller, so this method is less suitable for collecting data on broad populations and is at risk for sampling bias .

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 analyzes the results. But they are more commonly used to collect qualitative data : the interviewees’ full responses are transcribed and analyzed 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 analyzed 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. Avoid jargon or industry-specific terminology.

Survey questions are at risk for biases like social desirability bias , the Hawthorne effect , or demand characteristics . It’s critical to use language that respondents will easily understand, and avoid words with vague or ambiguous meanings. Make sure your questions are phrased neutrally, with no indication that you’d prefer a particular answer or emotion.

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 mail, online, or in person.

There are many methods of analyzing 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 clean 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 organizing them into categories or themes. You can also use more qualitative methods, such as thematic analysis , which is especially suitable for analyzing 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 analyzed 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 analyze it. In the results section, you summarize the key results from your analysis.

In the discussion and conclusion , you give your explanations and interpretations of these results, answer your research question, and reflect on the implications and limitations of the research.

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.

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.

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 analyze your data.

The priorities of a research design can vary depending on the field, but you usually have to specify:

Your research questions and/or hypotheses
Your overall approach (e.g., qualitative or quantitative )
The type of design you’re using (e.g., a survey , experiment , or case study )
Your sampling methods or criteria for selecting subjects
Your data collection methods (e.g., questionnaires , observations)
Your data collection procedures (e.g., operationalization , timing and data management)
Your data analysis methods (e.g., statistical tests or thematic analysis )

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Home Market Research

Survey Research: Definition, Examples and Methods

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

LEARN ABOUT: Behavioral Research

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

Survey Research Definition

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

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

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

LEARN ABOUT: Survey Sampling

Survey Research Methods

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

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

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

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

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

LEARN ABOUT: Survey Sample Sizes

The various non-probability sampling techniques are :

Convenience sampling
Snowball sampling
Consecutive sampling
Judgemental sampling
Quota sampling

Process of implementing survey research methods:

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

LEARN ABOUT: System Usability Scale

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

LEARN ABOUT: Testimonial Questions

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

Reasons to conduct survey research

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

LEARN ABOUT: Research Process Steps

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

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

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

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

Survey Research Scales

There are four main scales for the measurement of variables:

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

Benefits of survey research

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

Other benefits of survey research are:

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

Survey research design

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

There are five stages of survey research design:

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

Survey examples: 10 tips to design the perfect research survey

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

Below are 10 Tips To Design The Perfect Research Survey:

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

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

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

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Home » Survey Research – Types, Methods, Examples

Survey Research – Types, Methods, Examples

Table of Contents

Survey Research

Definition:

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

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

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

Survey Research Methods

Survey Research Methods are as follows:

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

Types of Survey Research

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

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

Types Based on Methodology

Based on Methodology Survey are divided into two Types:

Quantitative Survey Research

Qualitative survey research.

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

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

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

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

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

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

Data Analysis Methods

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

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

Applications of Survey Research

Here are some common applications of survey research:

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

Examples of Survey Research

Here are some real-time examples of survey research:

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

Survey Sample

Purpose of survey research.

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

Here are some common purposes of survey research:

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

When to use Survey Research

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

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

How to Conduct Survey Research

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

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

Advantages of Survey Research

There are several advantages to using survey research, including:

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

Limitations of Survey Research

Here are some of the main limitations of survey research:

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

Following is an example of a Survey Sample:

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

1. What is your age?

A) Under 18
G) 65 or older

2. What is your highest level of education completed?

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

3. What is your current employment status?

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

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

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

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

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

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

A) Excellent
E) Very poor

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

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

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

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

10. Any additional comments or suggestions?

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

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

Questionnaire – Definition, Types, and Examples

Case Study – Methods, Examples and Guide

Observational Research – Methods and Guide

Quantitative Research – Methods, Types and...

Qualitative Research Methods

Explanatory Research – Types, Methods, Guide

Quantitative Methods for the Social Sciences pp 23–35 Cite as

A Short Introduction to Survey Research

Daniel Stockemer 2
First Online: 20 November 2018

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This chapter offers a brief introduction into survey research. In the first part of the chapter, students learn about the importance of survey research in the social and behavioral sciences, substantive research areas where survey research is frequently used, and important cross-national survey such as the World Values Survey and the European Social Survey. In the second, I introduce different types of surveys.

Survey Research
Cross-national Survey
Substantive Research Areas
World Values Survey
Comparative Study Of Electoral Systems (CSES)

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In the literature, such reversed causation is often referred to as an endogeneity problem.

Almond, G., & Verba, S. (1963) [1989]. The civic culture: Political attitudes and democracy in five nations. Newbury Park, CA: Sage.

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Applied Survey Research

Almond, G. A., & Verba, S. (1963). The civic culture: Political attitudes and democracy in five nations. Princeton: Princeton University Press. Almond’s and Verba’s masterpiece is a seminal work in survey research measuring citizens’ political and civic attitudes in key Western democracies. The book is also one of the first books that systematically uses survey research to measure political traits.

Inglehart, R., & Welzel, C. (2005). Modernization, cultural change, and democracy: The human development sequence . Cambridge: Cambridge University Press. This is an influential book, which uses data from the World Values Survey to explain modernization as a process that changes individual’s values away from traditional and patriarchal values and toward post-materialist values including environmental protection, minority rights, and gender equality.

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Stockemer, D. (2019). A Short Introduction to Survey Research. In: Quantitative Methods for the Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-99118-4_3

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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 .

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.

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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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.

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.

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.

The content of the survey questions

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 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.

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 .

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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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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5 Approaching Survey Research

What is survey research.

Survey research is a quantitative and qualitative method with two important characteristics. First, the variables of interest are measured using self-reports (using questionnaires or interviews). In essence, survey researchers ask their participants (who are often called respondents in survey research) to report directly on their own thoughts, feelings, and behaviors. Second, considerable attention is paid to the issue of sampling. In particular, survey researchers have a strong preference for large random samples because they provide the most accurate estimates of what is true in the population. Beyond these two characteristics, almost anything goes in survey research. Surveys can be long or short. They can be conducted in person, by telephone, through the mail, or over the Internet. They can be about voting intentions, consumer preferences, social attitudes, health, or anything else that it is possible to ask people about and receive meaningful answers. Although survey data are often analyzed using statistics, there are many questions that lend themselves to more qualitative analysis.

Most survey research is non-experimental. It is used to describe single variables (e.g., the percentage of voters who prefer one presidential candidate or another, the prevalence of schizophrenia in the general population, etc.) and also to assess statistical relationships between variables (e.g., the relationship between income and health). But surveys can also be used within experimental research; as long as there is manipulation of an independent variable (e.g. anger vs. fear) to assess an effect on a dependent variable (e.g. risk judgments).

Chapter 5: Learning Objectives

If your research question(s) center on the experience or perception of a particular phenomenon, process, or practice, utilizing a survey method may help glean useful data. After reading this chapter, you will

Identify the purpose of survey research
Describe the cognitive processes involved in responding to questions
Discuss the importance of context in drafting survey items
Contrast the utility of open and closed ended questions
Describe the BRUSO method of drafting survey questions
Describe the format for survey questionnaires

The heart of any survey research project is the survey itself. Although it is easy to think of interesting questions to ask people, constructing a good survey is not easy at all. The problem is that the answers people give can be influenced in unintended ways by the wording of the items, the order of the items, the response options provided, and many other factors. At best, these influences add noise to the data. At worst, they result in systematic biases and misleading results. In this section, therefore, we consider some principles for constructing surveys to minimize these unintended effects and thereby maximize the reliability and validity of respondents’ answers.

Cognitive Processes of Responses

To best understand how to write a ‘good’ survey question, it is important to frame the act of responding to a survey question as a cognitive process. That is, there are are involuntary mechanisms that take place when someone is asked a question. Sudman, Bradburn, & Schwarz (1996, as cited in Jhangiani et. al, 2012) illustrate this cognitive process here.

Progression of a cognitive response. Fist the respondent must understand the question then retrieve information from memory to formulate a response based on a judgement formed by the information. The respondent must then edit the response, depending on the response options provided by the survey.

Framing the formulation of survey questions in this way is extremely helpful to ensure that the questions posed on your survey glean accurate information.

Example of a Poorly Worded Survey Question

How many alcoholic drinks do you consume in a typical day?

A lot more of average
Somewhat more than average
Average number
Somewhat fewer than average
A lot fewer than average

Although this item at first seems straightforward, it poses several difficulties for respondents. First, they must interpret the question. For example, they must decide whether “alcoholic drinks” include beer and wine (as opposed to just hard liquor) and whether a “typical day” is a typical weekday, typical weekend day, or both. Even though Chang and Krosnick (2003, as cited in Jhangiani et al. 2012) found that asking about “typical” behavior has been shown to be more valid than asking about “past” behavior, their study compared “typical week” to “past week” and may be different when considering typical weekdays or weekend days). Once respondents have interpreted the question, they must retrieve relevant information from memory to answer it. But what information should they retrieve, and how should they go about retrieving it? They might think vaguely about some recent occasions on which they drank alcohol, they might carefully try to recall and count the number of alcoholic drinks they consumed last week, or they might retrieve some existing beliefs that they have about themselves (e.g., “I am not much of a drinker”). Then they must use this information to arrive at a tentative judgment about how many alcoholic drinks they consume in a typical day. For example, this mental calculation might mean dividing the number of alcoholic drinks they consumed last week by seven to come up with an average number per day. Then they must format this tentative answer in terms of the response options actually provided. In this case, the options pose additional problems of interpretation. For example, what does “average” mean, and what would count as “somewhat more” than average? Finally, they must decide whether they want to report the response they have come up with or whether they want to edit it in some way. For example, if they believe that they drink a lot more than average, they might not want to report that for fear of looking bad in the eyes of the researcher, so instead, they may opt to select the “somewhat more than average” response option.

From this perspective, what at first appears to be a simple matter of asking people how much they drink (and receiving a straightforward answer from them) turns out to be much more complex.

Context Effects on Survey Responses

Again, this complexity can lead to unintended influences on respondents’ answers. These are often referred to as context effects because they are not related to the content of the item but to the context in which the item appears (Schwarz & Strack, 1990, as cited in Jhangiani et al. 2012). For example, there is an item-order effect when the order in which the items are presented affects people’s responses. One item can change how participants interpret a later item or change the information that they retrieve to respond to later items. For example, researcher Fritz Strack and his colleagues asked college students about both their general life satisfaction and their dating frequency (Strack, Martin, & Schwarz, 1988, as cited in Jhangiani et al. 2012) . When the life satisfaction item came first, the correlation between the two was only −.12, suggesting that the two variables are only weakly related. But when the dating frequency item came first, the correlation between the two was +.66, suggesting that those who date more have a strong tendency to be more satisfied with their lives. Reporting the dating frequency first made that information more accessible in memory so that they were more likely to base their life satisfaction rating on it.

The response options provided can also have unintended effects on people’s responses (Schwarz, 1999, as cited in Jhangiani et al. 2012) . For example, when people are asked how often they are “really irritated” and given response options ranging from “less than once a year” to “more than once a month,” they tend to think of major irritations and report being irritated infrequently. But when they are given response options ranging from “less than once a day” to “several times a month,” they tend to think of minor irritations and report being irritated frequently. People also tend to assume that middle response options represent what is normal or typical. So if they think of themselves as normal or typical, they tend to choose middle response options. For example, people are likely to report watching more television when the response options are centered on a middle option of 4 hours than when centered on a middle option of 2 hours. To mitigate against order effects, rotate questions and response items when there is no natural order. Counterbalancing or randomizing the order of presentation of the questions in online surveys are good practices for survey questions and can reduce response order effects that show that among undecided voters, the first candidate listed in a ballot receives a 2.5% boost simply by virtue of being listed first!

Writing Survey Items

Types of Items

Questionnaire items can be either open-ended or closed-ended. Open-ended items simply ask a question and allow participants to answer in whatever way they choose. The following are examples of open-ended questionnaire items.

“What is the most important thing to teach children to prepare them for life?”
“Please describe a time when you were discriminated against because of your age.”
“Is there anything else you would like to tell us about?”

Open-ended items are useful when researchers do not know how participants might respond or when they want to avoid influencing their responses. Open-ended items are more qualitative in nature, so they tend to be used when researchers have more vaguely defined research questions—often in the early stages of a research project. Open-ended items are relatively easy to write because there are no response options to worry about. However, they take more time and effort on the part of participants, and they are more difficult for the researcher to analyze because the answers must be transcribed, coded, and submitted to some form of qualitative analysis, such as content analysis. Another disadvantage is that respondents are more likely to skip open-ended items because they take longer to answer. It is best to use open-ended questions when the answer is unsure or for quantities which can easily be converted to categories later in the analysis.

Closed-ended items ask a question and provide a set of response options for participants to choose from.

Examples of Closed-Ended Questions

How old are you?

On a scale of 0 (no pain at all) to 10 (the worst pain ever experienced), how much pain are you in right now?

Closed-ended items are used when researchers have a good idea of the different responses that participants might make. They are more quantitative in nature, so they are also used when researchers are interested in a well-defined variable or construct such as participants’ level of agreement with some statement, perceptions of risk, or frequency of a particular behavior. Closed-ended items are more difficult to write because they must include an appropriate set of response options. However, they are relatively quick and easy for participants to complete. They are also much easier for researchers to analyze because the responses can be easily converted to numbers and entered into a spreadsheet. For these reasons, closed- ended items are much more common.

All closed-ended items include a set of response options from which a participant must choose. For categorical variables like sex, race, or political party preference, the categories are usually listed and participants choose the one (or ones) to which they belong. For quantitative variables, a rating scale is typically provided. A rating scale is an ordered set of responses that participants must choose from.

Likert Scale indicating scaled responses between 1 and 5 to questions. A selection of 1 indicates strongly disagree and a selection of 5 indicates strongly agree

The number of response options on a typical rating scale ranges from three to 11—although five and seven are probably most common. Five-point scales are best for unipolar scales where only one construct is tested, such as frequency (Never, Rarely, Sometimes, Often, Always). Seven- point scales are best for bipolar scales where there is a dichotomous spectrum, such as liking (Like very much, Like somewhat, Like slightly, Neither like nor dislike, Dislike slightly, Dislike somewhat, Dislike very much). For bipolar questions, it is useful to offer an earlier question that branches them into an area of the scale; if asking about liking ice cream, first ask “Do you generally like or dislike ice cream?” Once the respondent chooses like or dislike, refine it by offering them relevant choices from the seven-point scale. Branching improves both reliability and validity (Krosnick & Berent, 1993, as cited in Jhangiani et al. 2012 ) . Although you often see scales with numerical labels, it is best to only present verbal labels to the respondents but convert them to numerical values in the analyses. Avoid partial labels or length or overly specific labels. In some cases, the verbal labels can be supplemented with (or even replaced by) meaningful graphics.

Writing Effective Items

We can now consider some principles of writing questionnaire items that minimize unintended context effects and maximize the reliability and validity of participants’ responses. A rough guideline for writing 9 questionnaire items is provided by the BRUSO model (Peterson, 2000, as cited in Jhangiani et al. 2012 ) . An acronym, BRUSO stands for “brief,” “relevant,” “unambiguous,” “specific,” and “objective.” Effective questionnaire items are brief and to the point. They avoid long, overly technical, or unnecessary words. This brevity makes them easier for respondents to understand and faster for them to complete. Effective questionnaire items are also relevant to the research question. If a respondent’s sexual orientation, marital status, or income is not relevant, then items on them should probably not be included. Again, this makes the questionnaire faster to complete, but it also avoids annoying respondents with what they will rightly perceive as irrelevant or even “nosy” questions. Effective questionnaire items are also unambiguous; they can be interpreted in only one way. Part of the problem with the alcohol item presented earlier in this section is that different respondents might have different ideas about what constitutes “an alcoholic drink” or “a typical day.” Effective questionnaire items are also specific so that it is clear to respondents what their response should be about and clear to researchers what it is about. A common problem here is closed- ended items that are “double barreled .” They ask about two conceptually separate issues but allow only one response.

Example of a “Double Barreled” question

Please rate the extent to which you have been feeling anxious and depressed

Note: The issue in the question itself is that anxiety and depression are two separate items and should likely be separated

Finally, effective questionnaire items are objective in the sense that they do not reveal the researcher’s own opinions or lead participants to answer in a particular way. The best way to know how people interpret the wording of the question is to conduct a pilot test and ask a few people to explain how they interpreted the question.

A description of the BRUSO methodology of writing questions wherein items are brief, relevant, unambiguous, specific, and objective

For closed-ended items, it is also important to create an appropriate response scale. For categorical variables, the categories presented should generally be mutually exclusive and exhaustive. Mutually exclusive categories do not overlap. For a religion item, for example, the categories of Christian and Catholic are not mutually exclusive but Protestant and Catholic are mutually exclusive. Exhaustive categories cover all possible responses. Although Protestant and Catholic are mutually exclusive, they are not exhaustive because there are many other religious categories that a respondent might select: Jewish, Hindu, Buddhist, and so on. In many cases, it is not feasible to include every possible category, in which case an ‘Other’ category, with a space for the respondent to fill in a more specific response, is a good solution. If respondents could belong to more than one category (e.g., race), they should be instructed to choose all categories that apply.

For rating scales, five or seven response options generally allow about as much precision as respondents are capable of. However, numerical scales with more options can sometimes be appropriate. For dimensions such as attractiveness, pain, and likelihood, a 0-to-10 scale will be familiar to many respondents and easy for them to use. Regardless of the number of response options, the most extreme ones should generally be “balanced” around a neutral or modal midpoint.

Example of an unbalanced versus balanced rating scale

Unbalanced rating scale measuring perceived likelihood

Unlikely | Somewhat Likely | Likely | Very Likely | Extremely Likely

Balanced rating scale measuring perceived likelihood

Extremely Unlikely | Somewhat Unlikely | As Likely as Not | Somewhat Likely |Extremely Likely

Note, however, that a middle or neutral response option does not have to be included. Researchers sometimes choose to leave it out because they want to encourage respondents to think more deeply about their response and not simply choose the middle option by default. However, including middle alternatives on bipolar dimensions can be used to allow people to choose an option that is neither.

Formatting the Survey

Writing effective items is only one part of constructing a survey. For one thing, every survey should have a written or spoken introduction that serves two basic functions (Peterson, 2000, as cited by Jhangiani et al. 2012 ). One is to encourage respondents to participate in the survey. In many types of research, such encouragement is not necessary either because participants do not know they are in a study (as in naturalistic observation) or because they are part of a subject pool and have already shown their willingness to participate by signing up and showing up for the study. Survey research usually catches respondents by surprise when they answer their phone, go to their mailbox, or check their e-mail—and the researcher must make a good case for why they should agree to participate. This means that the researcher has only a moment to capture the attention of the respondent and must make it as easy as possible for the respondent to participate . Thus the introduction should briefly explain the purpose of the survey and its importance, provide information about the sponsor of the survey (university-based surveys tend to generate higher response rates), acknowledge the importance of the respondent’s participation, and describe any incentives for participating.

The second function of the introduction is to establish informed consent. Remember that this involves describing to respondents everything that might affect their decision to participate. This includes the topics covered by the survey, the amount of time it is likely to take, the respondent’s option to withdraw at any time, confidentiality issues, and so on. Written consent forms are not always used in survey research (when the research is of minimal risk and completion of the survey instrument is often accepted by the IRB as evidence of consent to participate), so it is important that this part of the introduction be well documented and presented clearly and in its entirety to every respondent.

The introduction should be followed by the substantive questionnaire items. But first, it is important to present clear instructions for completing the questionnaire, including examples of how to use any unusual response scales. Remember that the introduction is the point at which respondents are usually most interested and least fatigued, so it is good practice to start with the most important items for purposes of the research and proceed to less important items. Items should also be grouped by topic or by type. For example, items using the same rating scale (e.g., a 5-point agreement scale) should be grouped together if possible to make things faster and easier for respondents. Demographic items are often presented last because they are least interesting to participants but also easy to answer in the event respondents have become tired or bored. Of course, any survey should end with an expression of appreciation to the respondent.

Coding your survey responses

Once you’ve closed your survey, you’ll need to identify how to quantify the data you’ve collected. Much of this can be done in ways similar to methods described in the previous two chapters. Although there are several ways by which to do this, here are some general tips:

Transfer data : Transfer your data to a program which will allow you to organize and ‘clean’ the data. If you’ve used an online tool to gather data, you should be able to download the survey results into a format appropriate for working the data. If you’ve collected responses by hand, you’ll need to input the data manually.
Save: ALWAYS save a copy of your original data. Save changes you make to the data under a different name or version in case you need to refer back to the original data.
De-identify: This step will depend on the overall approach that you’ve taken to answer your research question and may not be appropriate for your project.
Name the variables: Again, there is no ‘right’ way to do this; however, as you move forward, you will want to be sure you can easily identify what data you are extracting. Many times, when you transfer your data the program will automatically associate data collected with the question asked. It is a good idea to name the variable something associated with the data, rather than the question
Code the attributes : Each variable will likely have several different attributes, or layers. You’ll need to come up with a coding method to distinguish the different responses. As discussed in previous chapters, each attribute should have a numeric code associated so that you can quantify the data and use descriptive and/or inferential statistical methods to either describe or explore relationships within the dataset.

Most online survey tools will download data into a spreadsheet-type program and organize that data in association with the question asked. Naming the variables so that you can easily identify the information will be helpful as you proceed to analysis.

This is relatively simple to accomplish with closed-ended questions. Because you’ve ‘forced’ the respondent to pick a concrete answer, you can create a code that is associated with each answer. In the picture above, respondents were asked to identify their region and given a list of geographical regions and in structed to pick one. The researcher then created a code for the regions. In this case, 1= West; 2= Midwest; 3= Northeast; 4= Southeast; and 5= Southwest. If you’re working to quantify data that is somewhat qualitative in nature (i.e. open ended questions) the process is a little more complicated. You’ll need to either create themes or categories, classify types or similar responses, and then assign codes to those themes or categories.

6. Create a codebook : This.is.essential. Once you begin to code the data, you will have somewhat disconnected yourself from the data by translating the data from a language that we understand to a language which a computer understands. Af ter you run your statistical methods, you’ll translate it back to the native language and share findings. To stay organized and accurate, it is important that you keep a record of how the data has been translated.

7. Analyze: Once you have the data inputted, cleaned, and coded, you should be ready to analyze your data using either descriptive or inferential methods, depend. ing on your approach and overarching goal.

Key Takeaways

Surveys are a great method to identify information about perceptions and experiences
Question items must be carefully crafted to elicit an appropriate response
Surveys are often a mixed-methods approach to research
Both descriptive and inferential statistical approaches can be applied to the data gleaned through survey responses
Surveys utilize both open and closed ended questions; identifying which types of questions will yield specific data will be helpful as you plan your approach to analysis
Most surveys will need to include a method of informed consent, and an introduction. The introduction should clearly delineate the purpose of the survey and how the results will be utilized
Pilot tests of your survey can save you a lot of time and heartache. Pilot testing helps to catch issues in the development of item, accessibility, and type of information derived prior to initiating the survey on a larger scale
Survey data can be analyzed much like other types of data; following a systematic approach to coding will help ensure you get the answers you’re looking for
This section is attributed to Research Methods in Psychology by Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted. ↵
The majority of content in these sections can be attributed to Research Methods in Psychology by Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted. ↵

A mixed methods approach using self-reports of respondents who are sampled using stringent methods

A type of survey question that allows the respondent to insert their own response; typically qualitative in nature

A type of survey question which forces a respondent to select a response; no subjectivity.

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What is a survey?
Survey Research

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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.

Used by more than 13,000 brands and supporting more than 1 billion surveys a year, Qualtrics empowers everyone in your organization to gather insights and take action. No coding required — and your data is housed in one system.

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.

Ready to find out more about Qualtrics CoreXM?

Get started with our free survey maker tool today

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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Conducting Survey Research

Surveys represent one of the most common types of quantitative, social science research. In survey research, the researcher selects a sample of respondents from a population and administers a standardized questionnaire to them. The questionnaire, or survey, can be a written document that is completed by the person being surveyed, an online questionnaire, a face-to-face interview, or a telephone interview. Using surveys, it is possible to collect data from large or small populations (sometimes referred to as the universe of a study).

Different types of surveys are actually composed of several research techniques, developed by a variety of disciplines. For instance, interview began as a tool primarily for psychologists and anthropologists, while sampling got its start in the field of agricultural economics (Angus and Katona, 1953, p. 15).

Survey research does not belong to any one field and it can be employed by almost any discipline. According to Angus and Katona, "It is this capacity for wide application and broad coverage which gives the survey technique its great usefulness..." (p. 16).

Types of Surveys

Surveys come in a wide range of forms and can be distributed using a variety of media.

Mail Surveys

Group administered questionnaires, drop-off surveys, oral surveys, electronic surveys.

An Example Survey

Example Survey

General Instructions: We are interested in your writing and computing experiences and attitudes. Please take a few minutes to complete this survey. In general, when you are presented with a scale next to a question, please put an X over the number that best corresponds to your answer. For example, if you strongly agreed with the following question, you might put an X through the number 5. If you agreed moderately, you might put an X through number 4, if you neither agreed nor disagreed, you might put an X through number 3.

Example Question:

As is the case with all of the information we are collecting for our study, we will keep all the information you provide to us completely confidential. Your teacher will not be made aware of any of your responses. Thanks for your help.

Your Name: ___________________________________________________________

Your Instructor's Name: __________________________________________________

Written Surveys

Imagine that you are interested in exploring the attitudes college students have about writing. Since it would be impossible to interview every student on campus, choosing the mail-out survey as your method would enable you to choose a large sample of college students. You might choose to limit your research to your own college or university, or you might extend your survey to several different institutions. If your research question demands it, the mail survey allows you to sample a very broad group of subjects at small cost.

Strengths and Weaknesses of Mail Surveys

Cost: Mail surveys are low in cost compared to other methods of surveying. This type of survey can cost up to 50% less than the self-administered survey, and almost 75% less than a face-to-face survey (Bourque and Fielder 9). Mail surveys are also substantially less expensive than drop-off and group-administered surveys.

Convenience: Since many of these types of surveys are conducted through a mail-in process, the participants are able to work on the surveys at their leisure.

Bias: Because the mail survey does not allow for personal contact between the researcher and the respondent, there is little chance for personal bias based on first impressions to alter the responses to the survey. This is an advantage because if the interviewer is not likeable, the survey results will be unfavorably affected. However, this could be a disadvantage as well.

Sampling--internal link: It is possible to reach a greater population and have a larger universe (sample of respondents) with this type of survey because it does not require personal contact between the researcher and the respondents.

Low Response Rate: One of the biggest drawbacks to written survey, especially as it relates to the mail-in, self-administered method, is the low response rate. Compared to a telephone survey or a face-to-face survey, the mail-in written survey has a response rate of just over 20%.

Ability of Respondent to Answer Survey: Another problem with self-administered surveys is three-fold: assumptions about the physical ability, literacy level and language ability of the respondents. Because most surveys pull the participants from a random sampling, it is impossible to control for such variables. Many of those who belong to a survey group have a different primary language than that of the survey. They may also be illiterate or have a low reading level and therefore might not be able to accurately answer the questions. Along those same lines, persons with conditions that cause them to have trouble reading, such as dyslexia, visual impairment or old age, may not have the capabilities necessary to complete the survey.

Imagine that you are interested in finding out how instructors who teach composition in computer classrooms at your university feel about the advantages of teaching in a computer classroom over a traditional classroom. You have a very specific population in mind, and so a mail-out survey would probably not be your best option. You might try an oral survey, but if you are doing this research alone this might be too time consuming. The group administered questionnaire would allow you to get your survey results in one space of time and would ensure a very high response rate (higher than if you stuck a survey into each instructor's mailbox). Your challenge would be to get everyone together. Perhaps your department holds monthly technology support meetings that most of your chosen sample would attend. Your challenge at this point would be to get permission to use part of the weekly meeting time to administer the survey, or to convince the instructors to stay to fill it out after the meeting. Despite the challenges, this type of survey might be the most efficient for your specific purposes.

Strengths and Weaknesses of Group Administered Questionnaires

Rate of Response: This second type of written survey is generally administered to a sample of respondents in a group setting, guaranteeing a high response rate.

Specificity: This type of written survey can be very versatile, allowing for a spectrum of open and closed ended types of questions and can serve a variety of specific purposes, particularly if you are trying to survey a very specific group of people.

Weaknesses of Group Administered Questionnaires

Sampling: This method requires a small sample, and as a result is not the best method for surveys that would benefit from a large sample. This method is only useful in cases that call for very specific information from specific groups.

Scheduling: Since this method requires a group of respondents to answer the survey together, this method requires a slot of time that is convenient for all respondents.

Imagine that you would like to find out about how the dorm dwellers at your university feel about the lack of availability of vegetarian cuisine in their dorm dining halls. You have prepared a questionnaire that requires quite a few long answers, and since you suspect that the students in the dorms may not have the motivation to take the time to respond, you might want a chance to tell them about your research, the benefits that might come from their responses, and to answer their questions about your survey. To ensure the highest response rate, you would probably pick a time of the day when you are sure that the majority of the dorm residents are home, and then work your way from door to door. If you don't have time to interview the number of students you need in your sample, but you don't trust the response rate of mail surveys, the drop-off survey might be the best option for you.

Strengths and Weaknesses of Drop-off Surveys

Convenience: Like the mail survey, the drop-off survey allows the respondents to answer the survey at their own convenience.

Response Rates: The response rates for the drop-off survey are better than the mail survey because it allows the interviewer to make personal contact with the respondent, to explain the importance of the survey, and to answer any questions or concerns the respondent might have.

Time: Because of the personal contact this method requires, this method takes considerably more time than the mail survey.

Sampling: Because of the time it takes to make personal contact with the respondents, the universe of this kind of survey will be considerably smaller than the mail survey pool of respondents.

Response: The response rate for this type of survey, although considerably better than the mail survey, is still not as high as the response rate you will achieve with an oral survey.

Oral surveys are considered more personal forms of survey than the written or electronic methods. Oral surveys are generally used to get thorough opinions and impressions from the respondents.

Oral surveys can be administered in several different ways. For instance, in a group interview, as opposed to a group administered written survey, each respondent is not given an instrument (an individual questionnaire). Instead, the respondents work in groups to answer the questions together while one person takes notes for the whole group. Another more familiar form of oral survey is the phone survey. Phone surveys can be used to get short one word answers (yes/no), as well as longer answers.

Strengths and Weaknesses of Oral Surveys

Personal Contact: Oral surveys conducted either on the telephone or in person give the interviewer the ability to answer questions from the participant. If the participant, for example, does not understand a question or needs further explanation on a particular issue, it is possible to converse with the participant. According to Glastonbury and MacKean, "interviewing offers the flexibility to react to the respondent's situation, probe for more detail, seek more reflective replies and ask questions which are complex or personally intrusive" (p. 228).

Response Rate: Although obtaining a certain number of respondents who are willing to take the time to do an interview is difficult, the researcher has more control over the response rate in oral survey research than with other types of survey research. As opposed to mail surveys where the researcher must wait to see how many respondents actually answer and send back the survey, a researcher using oral surveys can, if the time and money are available, interview respondents until the required sample has been achieved.

Cost: The most obvious disadvantage of face-to-face and telephone survey is the cost. It takes time to collect enough data for a complete survey, and time translates into payroll costs and sometimes payment for the participants.

Bias: Using face-to-face interview for your survey may also introduce bias, from either the interviewer or the interviewee.

Types of Questions Possible: Certain types of questions are not convenient for this type of survey, particularly for phone surveys where the respondent does not have a chance to look at the questionnaire. For instance, if you want to offer the respondent a choice of 5 different answers, it will be very difficult for respondents to remember all of the choices, as well as the question, without a visual reminder. This problem requires the researcher to take special care in constructing questions to be read aloud.

Attitude: Anyone who has ever been interrupted during dinner by a phone interviewer is aware of the negative feelings many people have about answering a phone survey. Upon receiving these calls, many potential respondents will simply hang up.

With the growth of the Internet (and in particular the World Wide Web) and the expanded use of electronic mail for business communication, the electronic survey is becoming a more widely used survey method. Electronic surveys can take many forms. They can be distributed as electronic mail messages sent to potential respondents. They can be posted as World Wide Web forms on the Internet. And they can be distributed via publicly available computers in high-traffic areas such as libraries and shopping malls. In many cases, electronic surveys are placed on laptops and respondents fill out a survey on a laptop computer rather than on paper.

Strengths and Weaknesses of Electronic Surveys

Cost-savings: It is less expensive to send questionnaires online than to pay for postage or for interviewers.

Ease of Editing/Analysis: It is easier to make changes to questionnaire, and to copy and sort data.

Faster Transmission Time: Questionnaires can be delivered to recipients in seconds, rather than in days as with traditional mail.

Easy Use of Preletters: You may send invitations and receive responses in a very short time and thus receive participation level estimates.

Higher Response Rate: Research shows that response rates on private networks are higher with electronic surveys than with paper surveys or interviews.

More Candid Responses: Research shows that respondents may answer more honestly with electronic surveys than with paper surveys or interviews.

Potentially Quicker Response Time with Wider Magnitude of Coverage: Due to the speed of online networks, participants can answer in minutes or hours, and coverage can be global.

Sample Demographic Limitations: Population and sample limited to those with access to computer and online network.

Lower Levels of Confidentiality: Due to the open nature of most online networks, it is difficult to guarantee anonymity and confidentiality.

Layout and Presentation issues: Constructing the format of a computer questionnaire can be more difficult the first few times, due to a researcher's lack of experience.

Additional Orientation/Instructions: More instruction and orientation to the computer online systems may be necessary for respondents to complete the questionnaire.

Potential Technical Problems with Hardware and Software: As most of us (perhaps all of us) know all too well, computers have a much greater likelihood of "glitches" than oral or written forms of communication.

Response Rate: Even though research shows that e-mail response rates are higher, Opermann (1995) warns that most of these studies found response rates higher only during the first few days; thereafter, the rates were not significantly higher.

Designing Surveys

Initial planning of the survey design and survey questions is extremely important in conducting survey research. Once surveying has begun, it is difficult or impossible to adjust the basic research questions under consideration or the tool used to address them since the instrument must remain stable in order to standardize the data set. This section provides information needed to construct an instrument that will satisfy basic validity and reliability issues. It also offers information about the important decisions you need to make concerning the types of questions you are going to use, as well as the content, wording, order and format of your survey questionnaire.

Overall Design Issues

Four key issues should be considered when designing a survey or questionnaire: respondent attitude, the nature of the items (or questions) on the survey, the cost of conducting the survey, and the suitability of the survey to your research questions.

Respondent attitude: When developing your survey instrument, it is important to try to put yourself into your target population's shoes. Think about how you might react when approached by a pollster while out shopping or when receiving a phone call from a pollster while you are sitting down to dinner. Think about how easy it is to throw away a response survey that you've received in the mail. When developing your instrument, it is important to choose the method you think will work for your research, but also one in which you have confidence. Ask yourself what kind of survey you, as a respondent, would be most apt to answer.

Nature of questions: It is important to consider the relationship between the medium that you use and the questions that you ask. For instance, certain types of questions are difficult to answer over the telephone. Think of the problems you would have in attempting to record Likert scale responses, as in closed-ended questions, over the telephone--especially if a scale of more than five points is used. Responses to open-ended questions would also be difficult to record and report in telephone interviews.

Cost: Along with decisions about the nature of the questions you ask, expense issues also enter into your decision making when planning a survey. The population under consideration, the geographic distribution of this sample population, and the type of questionnaire used all affect costs.

Ability of instrument to meet needs of research question: Finally, there needs to be a logical link between your survey instrument and your research questions. If it is important to get a large number of responses from a broad sample of the population, you obviously will not choose to do a drop-off written survey or an in-person oral survey. Because of the size of the needed sample, you will need to choose a survey instrument that meets this need, such as a phone or mail survey. If you are interested in getting thorough information that might need a large amount of interaction between the interviewer and respondent, you will probably pick in-person oral survey with a smaller sample of respondents. Your questions, then, will need to reflect both your research goals and your choice of medium.

Creating Questionnaire Questions

Developing well-crafted questionnaires is more difficult than it might seem. Researchers should carefully consider the type, content, wording, and order of the questions that they include. In this section, we discuss the steps involved in questionnaire development and the advantages and disadvantages of various techniques.

Open-ended vs. Closed-ended Questions

All researchers must make two basic decisions when designing a survey--they must decide: 1) whether they are going to employ an oral, written, or electronic method, and 2) whether they are going to choose questions that are open or close-ended.

Closed-Ended Questions: Closed-ended questions limit respondents' answers to the survey. The participants are allowed to choose from either a pre-existing set of dichotomous answers, such as yes/no, true/false, or multiple choice with an option for "other" to be filled in, or ranking scale response options. The most common of the ranking scale questions is called the Likert scale question. This kind of question asks the respondents to look at a statement (such as "The most important education issue facing our nation in the year 2000 is that all third graders should be able to read") and then "rank" this statement according to the degree to which they agree ("I strongly agree, I somewhat agree, I have no opinion, I somewhat disagree, I strongly disagree").

Open-Ended Questions: Open-ended questions do not give respondents answers to choose from, but rather are phrased so that the respondents are encouraged to explain their answers and reactions to the question with a sentence, a paragraph, or even a page or more, depending on the survey. If you wish to find information on the same topic as asked above (the future of elementary education), but would like to find out what respondents would come up with on their own, you might choose an open-ended question like "What do you think is the most important educational issue facing our nation in the year 2000?" rather than the Likert scale question. Or, if you would like to focus on reading as the topic, but would still not like to limit the participants' responses, you might pose the question this way: "Do you think that the most important issue facing education is literacy? Explain your answer below."

Note: Keep in mind that you do not have to use close-ended or open-ended questions exclusively. Many researchers use a combination of closed and open questions; often researchers use close-ended questions in the beginning of their survey, then allow for more expansive answers once the respondent has some background on the issue and is "warmed-up."

Rating scales: ask respondents to rate something like an idea, concept, individual, program, product, etc. based on a closed ended scale format, usually on a five-point scale. For example, a Likert scale presents respondents with a series of statements rather than questions, and the respondents are asked to which degree they disagree or agree.

Ranking scales: ask respondents to rank a set of ideas or things, etc. For example, a researcher can provide respondents with a list of ice cream flavors, and then ask them to rank these flavors in order of which they like best, with the rank of "one" representing their favorite. These are more difficult to use than rating scales. They will take more time, and they cannot easily be used for phone surveys since they often require visual aids. However, since ranking scales are more difficult, they may actually increase appropriate effort from respondents.

Magnitude estimation scales: ask respondents to provide numeric estimation of answers. For example, respondents might be asked: "Since your least favorite ice cream flavor is vanilla, we'll give it a score of 10. If you like another ice cream 20 times more than vanilla, you'll give it a score of 200, and so on. So, compared to vanilla at a score of ten, how much do you like rocky road?" These scales are obviously very difficult for respondents. However, these scales have been found to help increase variance explanations over ordinal scaling.

Split or unfolding questions: begin by asking respondents a general question, and then follow up with clarifying questions.

Funneling questions: guide respondents through complex issues or concepts by using a series of questions that progressively narrow to a specific question. For example, researchers can start asking general, open-ended questions, and then move to asking specific, closed-ended, forced-choice questions.

Inverted funneling questions: ask respondents a series of questions that move from specific issues to more general issues. For example, researchers can ask respondents specific, closed-ended questions first and then ask more general, open-ended questions. This technique works well when respondents are not expected to be knowledgeable about a content area or when they are not expected to have an articulate opinion regarding an issue.

Factorial questions: use stories or vignettes to study judgment and decision-making processes. For example, a researcher could ask respondents: "You're in a dangerous, rapidly burning building. Do you exit the building immediately or go upstairs to wake up the other inhabitants?" Converse and Presser (1986) warn that little is known about how this survey question technique compares with other techniques.

The wording of survey questions is a tricky endeavor. It is difficult to develop shared meanings or definitions between researchers and the respondents, and among respondents.

In The Practice of Social Research , Keith Crew, a professor of Sociology at the University of Kentucky, cites a famous example of a survey gone awry because of wording problems. An interview survey that included Likert-type questions ranging from "very much" to "very little" was given in a small rural town. Although it would seem that these items would accurately record most respondents' opinions, in the colloquial language of the region the word "very" apparently has an idiomatic usage which is closer to what we mean by "fairly" or even "poorly." You can just imagine what this difference in definition did to the survey results (p. 271).

This, however, is an extreme case. Even small changes in wording can shift the answers of many respondents. The best thing researchers can do to avoid problems with wording is to pretest their questions. However, researchers can also follow some suggestions to help them write more effective survey questions.

To write effective questions, researchers need to keep in mind these four important techniques: directness, simplicity, specificity, and discreteness.

Questions should be written in a straightforward, direct language that is not caught up in complex rhetoric or syntax, or in a discipline's slang or lingo. Questions should be specifically tailored for a group of respondents.
Questions should be kept short and simple. Respondents should not be expected to learn new, complex information in order to answer questions.
Specific questions are for the most part better than general ones. Research shows that the more general a question is the wider the range of interpretation among respondents. To keep specific questions brief, researchers can sometimes use longer introductions that make the context, background, and purpose of the survey clear so that this information is not necessary to include in the actual questions.
Avoid questions that are overly personal or direct, especially when dealing with sensitive issues.

When considering the content of your questionnaire, obviously the most important consideration is whether the content of the questions will elicit the kinds of questions necessary to answer your initial research question. You can gauge the appropriateness of your questions by pretesting your survey, but you should also consider the following questions as you are creating your initial questionnaire:

Does your choice of open or close-ended questions lead to the types of answers you would like to get from your respondents?
Is every question in your survey integral to your intent? Superfluous questions that have already been addressed or are not relevant to your study will waste the time of both the respondents and the researcher.
Does one topic warrant more than one question?
Do you give enough prior information/context for each set of questions? Sometimes lead-in questions are useful to help the respondent become familiar and comfortable with the topic.
Are the questions both general enough (they are both standardized and relevant to your entire sample), and specific enough (avoid vague generalizations and ambiguousness)?
Is each question as succinct as it can be without leaving out essential information?
Finally, and most importantly, try to put yourself in your respondents' shoes. Write a survey that you would be willing to answer yourself, and be polite, courteous, and sensitive. Thank the responder for participating both at the beginning and the end of the survey.

Order of Questions

Although there are no general rules for ordering survey questions, there are still a few suggestions researchers can follow when setting up a questionnaire.

Pretesting can help determine if the ordering of questions is effective.
Which topics should start the survey off, and which should wait until the end of the survey?
What kind of preparation do my respondents need for each question?
Do the questions move logically from one to the next, and do the topics lead up to each other?

The following general guidelines for ordering survey questions can address these questions:

Use warm-up questions. Easier questions will ease the respondent into the survey and will set the tone and the topic of the survey.
Sensitive questions should not appear at the beginning of the survey. Try to put the responder at ease before addressing uncomfortable issues. You may also prepare the reader for these sensitive questions with some sort of written preface.
Consider transition questions that make logical links.
Try not to mix topics. Topics can easily be placed into "sets" of questions.
Try not to put the most important questions last. Respondents may become bored or tired before they get to the end of the survey.
Be careful with contingency questions ("If you answered yes to the previous question . . . etc.").
If you are using a combination of open and close-ended questions, try not to start your survey with open-ended questions. Respondents will be more likely to answer the survey if they are allowed the ease of closed-questions first.

Borrowing Questions

Before developing a survey questionnaire, Converse and Presser (1986) recommend that researchers consult published compilations of survey questions, like those published by the National Opinion Research Center and the Gallup Poll. This will not only give you some ideas on how to develop your questionnaire, but you can even borrow questions from surveys that reflect your own research. Since these questions and questionnaires have already been tested and used effectively, you will save both time and effort. However, you will need to take care to only use questions that are relevant to your study, and you will usually have to develop some questions on your own.

Advantages of Closed-Ended Questions

Closed-ended questions are more easily analyzed. Every answer can be given a number or value so that a statistical interpretation can be assessed. Closed-ended questions are also better suited for computer analysis. If open-ended questions are analyzed quantitatively, the qualitative information is reduced to coding and answers tend to lose some of their initial meaning. Because of the simplicity of closed-ended questions, this kind of loss is not a problem.
Closed-ended questions can be more specific, thus more likely to communicate similar meanings. Because open-ended questions allow respondents to use their own words, it is difficult to compare the meanings of the responses.
In large-scale surveys, closed-ended questions take less time from the interviewer, the participant and the researcher, and so is a less expensive survey method. The response rate is higher with surveys that use closed-ended question than with those that use open-ended questions.

Advantages of Open-Ended Questions

Open-ended questions allow respondents to include more information, including feelings, attitudes and understanding of the subject. This allows researchers to better access the respondents' true feelings on an issue. Closed-ended questions, because of the simplicity and limit of the answers, may not offer the respondents choices that actually reflect their real feelings. Closed-ended questions also do not allow the respondent to explain that they do not understand the question or do not have an opinion on the issue.
Open-ended questions cut down on two types of response error; respondents are not likely to forget the answers they have to choose from if they are given the chance to respond freely, and open-ended questions simply do not allow respondents to disregard reading the questions and just "fill in" the survey with all the same answers (such as filling in the "no" box on every question).
Because they allow for obtaining extra information from the respondent, such as demographic information (current employment, age, gender, etc.), surveys that use open-ended questions can be used more readily for secondary analysis by other researchers than can surveys that do not provide contextual information about the survey population.

Potential Problems with Survey Questions

While designing questions for a survey, researchers should to be aware of a few problems and how to avoid them:

"Everyone has an opinion": It is incorrect to assume that each respondent has an opinion regarding every question. Therefore, you might offer a "no opinion" option to avoid this assumption. Filters can also be created. For example, researchers can ask respondents if they have any thoughts on an issue, to which they have the option to say "no."

Agree and disagree statements: according to Converse and Presser (1986), these statements suffer from "acquiescence" or the tendency of respondents to agree despite question content (p.35). Researchers can avoid this problem by using forced-choice questions with these statements.

Response order bias: this occurs when a respondent loses track of all options and picks one that comes easily to mind rather than the most accurate. Typically, the respondent chooses the last or first response option. This problem might occur if researchers use long lists and/or rating scales.

Response set: this problem can occur when using a close-ended question format with response options like yes/no or agree/disagree. Sometimes respondents do not consider each question and just answer no or disagree to all questions.

Telescoping: occurs when respondents report that an event took place more recently than it actually did. To avoid this problem, Frey and Mertens (1995) say researchers can use "aided recall"-using a reference point or landmark, or list of events or behaviors (p. 101).

Forward telescoping: occurs when respondents include events that have actually happened before the time frame established. This results in overreporting. According to Converse and Presser (1986), researchers can use "bounded recall" to avoid this problem (p.21). Bounded recall is when researchers interview respondents several months or so after the initial interview to inquire about events that have happened since then. This technique, however, requires more resources. Converse and Presser said that researchers can also just try to narrow the reference points used, which has been shown to reduce this problem too.

Fatigue effect: happens when respondents grow bored or tired during the interview. To avoid this problem, Frey and Mertens (1995) say researchers can use transitions, vary questions and response options, and they can put easy to answer questions at the end of the questionnaire.

Types of Questions to Avoid

Double-barreled questions- force respondents to make two decisions in one. For example, a question like: "Do you think women and children should be given the first available flu shots?" does not allow the responder to choose whether women or children should be given the first shots.
Double negative questions-for example: "Please tell me whether or not you agree or disagree with this statement. Graduate teaching assistants should not be required to help students outside of class." Respondents may confuse the meaning of the disagree option.
Hypothetical questions- are typically too difficult for respondents since they require more scrutiny. For example, "If there were a cure for cancer, would you still support euthanasia?"
Ambiguous questions- respondents might not understand the question.
Biased questions- For example, "Don't you think that suffering terminal cancer patients should be allowed to be released from their pain?" Researchers should never try to make one response option look more suitable than another.
Questions with long lists-these questions may tire respondents or respondents may lose track of the question.

Pretesting the Questionnaire

Ultimately, designing the perfect survey questionnaire is impossible. However, researchers can still create effective surveys. To determine the effectiveness of your survey questionnaire, it is necessary to pretest it before actually using it. Pretesting can help you determine the strengths and weaknesses of your survey concerning question format, wording and order.

There are two types of survey pretests: participating and undeclared .

Participating pretests dictate that you tell respondents that the pretest is a practice run; rather than asking the respondents to simply fill out the questionnaire, participating pretests usually involve an interview setting where respondents are asked to explain reactions to question form, wording and order. This kind of pretest will help you determine whether the questionnaire is understandable.
When conducting an undeclared pretest , you do not tell respondents that it is a pretest. The survey is given just as you intend to conduct it for real. This type of pretest allows you to check your choice of analysis and the standardization of your survey. According to Converse and Presser (1986), if researchers have the resources to do more than one pretest, it might be best to use a participatory pretest first, then an undeclared test.

General Applications of Pretesting:

Whether or not you use a participating or undeclared pretest, pretesting should ideally also test specifically for question variation, meaning, task difficulty, and respondent interest and attention. Your pretests should also include any questions you borrowed from other similar surveys, even if they have already been pretested, because meaning can be affected by the particular context of your survey. Researchers can also pretest the following: flow, order, skip patterns, timing, and overall respondent well-being.

Pretesting for reliability and validity:

Researchers might also want to pretest the reliability and validity of the survey questions. To be reliable, a survey question must be answered by respondents the same way each time. According to Weisberg et. al (1989), researchers can assess reliability by comparing the answers respondents give in one pretest with answers in another pretest. Then, a survey question's validity is determined by how well it measures the concept(s) it is intended to measure. Both convergent validity and divergent validity can be determined by first comparing answers to another question measuring the same concept, then by measuring this answer to the participant's response to a question that asks for the exact opposite answer.

For instance, you might include questions in your pretest that explicitly test for validity: if a respondent answers "yes" to the question, "Do you think that the next president should be a Republican?" then you might ask "What party do you think you might vote for in the next presidential election?" to check for convergent validity, then "Do you think that you will vote Democrat in the next election?" to check the answer for divergent validity.

Conducting Surveys

Once you have constructed a questionnaire, you'll need to make a plan that outlines how and to whom you will administer it. There are a number of options available in order to find a relevant sample group amongst your survey population. In addition, there are various considerations involved with administering the survey itself.

Administering a Survey

This section attempts to answer the question: "How do I go about getting my questionnaire answered?"

For all types of surveys, some basic practicalities need to be considered before the surveying begins. For instance, you need to find the most convenient time to carry out the data collection (this becomes particularly important in interview surveying and group-administered surveys), how long the data collection is likely to take. Finally, you need to make practical arrangements for administering the survey. Pretesting your survey will help you determine the time it takes to administer, process, and analyze your survey, and will also help you clear out some of the bugs.

Administering Written Surveys

Written surveys can be handled in several different ways. A research worker can deliver the questionnaires to the homes of the sample respondents, explain the study, and then pick the questionnaires up on a later date (or, alternately, ask the respondent to mail the survey back when completed). Another option is mailing questionnaires directly to homes and having researchers pick up and check the questionnaires for completeness in person. This method has proven to have higher response rates than straightforward mail surveys, although it tends to take more time and money to administer.

It is important to put yourself into the role of respondent when deciding how to administer your survey. Most of us have received and thrown away a mail survey, and so it may be useful to think back to the reasons you had for not filling it out and returning it. Here are some ideas for boosting your response rate:

Include in each questionnaire a letter of introduction and explanation, and a self-addressed, stamped envelope for returning the questionnaire.
Oftentimes, when it fits the study's budget, the envelope might also include a monetary "reward" (usually a dollar to five dollars) as an incentive to fill out the survey.
Another method for saving the responder time is to create a self-mailing questionnaire that requires no envelope but folds easily so that the return address appears on the outside. The easier you make the process of completing and returning the survey, the better your survey results will be.
Follow up mailings are an important part of administering mail surveys. Nonrespondents can be sent letters of additional encouragement to participate. Even better, a new copy of the survey can be sent to nonresponders. Methodological literature suggests that three follow up letters are adequate, and two to three weeks should be allowed between each mailing.

Administering Oral Surveys

Face-To-Face Surveys

Oftentimes conducting oral surveys requires a staff of interviewers; to control this variable as much as possible, the presentation and preparation of the interviewer is an important consideration.

In any face-to-face interview, the appearance of the interviewer is important. Since the success of any survey relies on the interest of the participants to respond to the survey, the interviewer should take care to dress and act in such a way that would not offend the general sample population.
Of equal importance is the preparedness of the interviewer. The interviewer should be well acquainted with the questions, and have ample practice administering the survey with mock interviews. If several interviewers will be used, they should be trained as a group to ensure standardization and control. Interviewers also need to carry a letter of identification/authentication to present at in-person surveys.

When actually administering the survey, you need to make decisions about how much of the participants' responses need to be recorded, how much the interviewer will need to "probe" for responses, and how much the interviewer will need to account for context (what is the respondent's age, race, gender, reaction to the study, etc.) If you are administering a close-ended question survey, these may not be considerations. On the other hand, when recording more open-ended responses, the researcher needs to decide beforehand on each of these factors:

It depends on the purpose of the study whether the interview should be recorded word for word, or whether the interviewer should record general impressions and opinions. However, for the sake of precision, the former approach is preferred. More information is always better than less when it comes to analyzing the results.
Sometimes respondents will respond to a question with an inappropriate answer; this can happen with both open and close-question surveys. Even if you give the participant structured choices like "I agree" or "I disagree," they might respond "I think that is true," which might require the interviewer to probe for an appropriate answer. In an open-question survey, this probing becomes more challenging. The interviewer might come with a set of potential questions if the respondent does not elaborate enough or strays from the subject. The nature of these probes, however, need to be constructed by the researcher rather than ad-libbed by the interviewers, and should be carefully controlled so that they do not lead the respondent to change answers.

Phone Surveys

Phone surveys certainly involve all of the preparedness of the face-to-face surveys, but encounter new problems because of their reputation. It is much easier to hang-up on a phone surveyor than it is to slam the door in someone's face, and so the sheer number of calls needed to complete a survey can be baffling. Computer innovation has tempered this problem a bit by allowing more for quick and random number dialing and the ability for interviewers to type answers programs that automatically set up the data for analysis. Systems like CATI (Computer-assisted survey interview) have made phone surveys a more cost and time effective method, and therefore a popular one, although respondents are getting more and more reluctant to answer phone surveys because of the increase in telemarketing.

Before conducting a survey, you must choose a relevant survey population. And, unless a survey population is very small, it is usually impossible to survey the entire relevant population. Therefore, researchers usually just survey a sample of a population from an actual list of the relevant population, which in turn is called a sampling frame . With a carefully selected sample, researchers can make estimations or generalizations regarding an entire population's opinions, attitudes or beliefs on a particular topic.

Sampling Procedures and Methods

There are two different types of sampling procedures-- probability and nonprobability . Probability sampling methods ensure that there is a possibility for each person in a sample population to be selected, whereas nonprobability methods target specific individuals. Nonprobability sampling methods include the following:

Purposive samples: to purposely select individuals to survey.
Volunteer subjects: to ask for volunteers to survey.
Haphazard sampling: to survey individuals who can be easily reached.
Quota sampling: to select individuals based on a set quota. For example, if a census indicates that more than half of the population is female, then the sample will be adjusted accordingly.

Clearly, there can be an inherent bias in nonprobability methods. Therefore, according to Weisberg, Krosnick, and Bowen (1989), it is not surprising that most survey researchers prefer probability sampling methods. Some commonly used probability sampling methods for surveys are:

Simple random sample: a sample is drawn randomly from a list of individuals in a population.
Systematic selection procedure sample: a variant of a simple random sample in which a random number is chosen to select the first individual and so on from there.
Stratified sample: dividing up the population into smaller groups, and randomly sampling from each group.
Cluster sample: dividing up a population into smaller groups, and then only sampling from one of the groups. Cluster sampling is " according to Lee, Forthofer, and Lorimer (1989), is considered a more practical approach to surveys because it samples by groups or clusters of elements rather than by individual elements" (p. 12). It also reduces interview costs. However, Weisberg et. al (1989) said accuracy declines when using this sampling method.
Multistage sampling: first, sampling a set of geographic areas. Then, sampling a subset of areas within those areas, and so on.

Sampling and Nonsampling Errors

Directly related to sample size are the concepts of sampling and nonsampling errors. According to Fox and Tracy (1986), surveys are subject to both sampling errors and nonsampling errors.

A sampling error arises from the fact that inevitably samples differ from their populations. Therefore, survey sample results should be seen only as estimations. Weisberg et. al. (1989) said sampling errors cannot be calculated for nonprobability samples, but they can be determined for probability samples. First, to determine sample error, look at the sample size. Then, look at the sampling fraction--the percentage of the population that is being surveyed. Thus, the more people surveyed, the smaller the error. This error can also be reduced, according to Fox and Tracy (1986), by increasing the representativeness of the sample.

Then, there are two different kinds of nonsampling error--random and nonrandom errors. Fox and Tracy (1986) said random errors decrease the reliability of measurements. These errors can be reduced through repeated measurements. Nonrandom errors result from a bias in survey data, which is connected to response and nonresponse bias.

Confidence Level and Interval

Any statement of sampling error must contain two essential components: the confidence level and the confidence interval. These two components are used together to express the accuracy of the sample's statistics in terms of the level of confidence that the statistics fall within a specified interval from the true population parameter. For example, a researcher may be "95 percent confident" that the sample statistic (that 50 percent favor candidate X) is within plus or minus 5 percentage points of the population parameter. In other words, the researcher is 95 percent confident that between 45 and 55 percent of the total population favor candidate X.

Lauer and Asher (1988) provide a table that gives the confidence interval limits for percentages based upon sample size (p. 58):

Sample Size and Confidence Interval Limits

(95% confidence intervals based on a population incidence of 50% and a large population relative to sample size.)

Confidence Limits and Sample Size

When selecting a sample size, one can consider that a higher number of individuals surveyed from a target group yields a tighter measurement, a lower number yields a looser range of confidence limits. The confidence limits may need to be corrected if, according to Lauer and Asher (1988), "the sample size starts to approach the population size" or if "the variable under scrutiny is known to have a much [original emphasis] smaller or larger occurrence than 50% in the whole population" (p. 59). For smaller populations, Singleton (1988) said the standard error or confidence interval should be multiplied by a correction factor equal to sqrt(1 - f), where "f" is the sampling fraction, or proportion of the population included in the sample.

Lauer and Asher (1988) give a table of correction factors for confidence limits where sample size is an important part of population size (p. 60) and also a table of correction factors for where the percentage incidence of the parameter in the population is not 50% (p. 61).

Tables for Calculating Confidence Limits vs. Sample Size

Correction Factors for Confidence Limits When Sample Size (n) Is an Important Part of Population Size (N >= 100)

(For n over 70% of N, take all of N)

From Lauer and Asher (1988, p. 60)

Correction Factors for Rare and Common Percentage of Variables

From Lauer and Asher (1988, p. 61)

Analyzing Survey Results

After creating and conducting your survey, you must now process and analyze the results. These steps require strict attention to detail and, in some cases, knowledge of statistics and computer software packages. How you conduct these steps will depend on the scope of your study, your own capabilities, and the audience to whom you wish to direct the work.

Processing the Results

It is clearly important to keep careful records of survey data in order to do effective work. Most researchers recommend using a computer to help sort and organize the data. Additionally, Glastonbury and MacKean point out that once the data has been filtered though the computer, it is possible to do an unlimited amount of analysis (p. 243).

Jolliffe (1986) believes that editing should be the first step to processing this data. He writes, "The obvious reason for this is to ensure that the data analyzed are correct and complete . At the same time, editing can reduce the bias, increase the precision and achieve consistency between the tables [regarding those produced by social science computer software] (p. 100). Of course, editing may not always be necessary, if for example you are doing a qualitative analysis of open-ended questions, or the survey is part of a larger project and gets distributed to other agencies for analysis. However, editing could be as simple as checking the information input into the computer.

All of this information should be used to test for statistical significance. See our guide on Statistics for more on this topic.

Information may be recorded in any number of ways. Charts and graphs are clear, visual ways to record findings in many cases. For instance, in a mail-out survey where response rate is an issue, you might use a response rate graph to make the process easier. The day the surveys are mailed out should be recorded first. Then, every day thereafter, the number of returned questionnaires should be logged on the graph. Be sure to record both the number returned each day, and the cumulative number, or percentage. Also, as each completed questionnaire is returned, each should be opened, scanned and assigned an identification number.

Analyzing the Results

Before actually beginning the survey the researcher should know how they want to analyze the data. As stated in the Processing the Results section, if you are collecting quantifiable data, a code book is needed for interpreting your data and should be established prior to collecting the survey data. This is important because there are many different formulas needed in order to properly analyze the survey research and obtain statistical significance. Since computer programs have made the process of analyzing data vastly easier than it was, it would be sensible to choose this route. Be sure to pick your program before you design your survey - - some programs require the data to be laid out in different ways.

After the survey is conducted and the data collected, the results must be assembled in some useable format that allows comparison within the survey group, between groups, or both. The results could be analyzed in a number of ways. A T-test may be used to determine if scores of two groups differ on a single variable--whether writing ability differs among students in two classrooms, for instance. A matched T-Test could also be applied to determine if scores of the same participants in a study differ under different conditions or over time. An ANOVA could be applied if the study compares multiple groups on one or more variables. Correlation measurements could also be constructed to compare the results of two interacting variables within the data set.

Secondary Analysis

Secondary analysis of survey data is an accepted methodology which applies previously collected survey data to new research questions. This methodology is particularly useful to researchers who do not have the time or money to conduct an extensive survey, but may be looking at questions for which some large survey has already collected relevant data. A number of books and chapters have been written about this methodology, some of which are listed in the annotated bibliography under "Secondary Analysis."

Advantages and Disadvantages of Using Secondary Analysis

Considerably cheaper and faster than doing original studies
You can benefit from the research from some of the top scholars in your field, which for the most part ensures quality data.
If you have limited funds and time, other surveys may have the advantage of samples drawn from larger populations.
How much you use previously collected data is flexible; you might only extract a few figures from a table, you might use the data in a subsidiary role in your research, or even in a central role.
A network of data archives in which survey data files are collected and distributed is readily available, making research for secondary analysis easily accessible.

Disadvantages

Since many surveys deal with national populations, if you are interested in studying a well-defined minority subgroup you will have a difficult time finding relevant data.
Secondary analysis can be used in irresponsible ways. If variables aren't exactly those you want, data can be manipulated and transformed in a way that might lessen the validity of the original research.
Much research, particularly of large samples, can involve large data files and difficult statistical packages.

Data-entry Packages Available for Survey Data Analysis

SNAP: Offers simple survey analysis, is able to help with the survey from start to finish, including the designing of questions and questionnaires.

SPSS: Statistical package for social sciences; can cope with most kinds of data.

SAS: A flexible general purpose statistical analysis system.

MINITAB: A very easy-to-use and fairly limited general purpose package for "beginners."

STATGRAPHS: General interactive statistical package with good graphics but not very flexible.

Reporting Survey Results

The final stage of the survey is to report your results. There is not an established format for reporting a survey's results. The report may follow a pattern similar to formal experimental write-ups, or the analysis may show up in pitches to advertising agencies--as with Arbitron data--or the analysis may be presented in departmental meetings to aid curriculum arguments. A formal report might contain contextual information, a literature review, a presentation of the research question under investigation, information on survey participants, a section explaining how the survey was conducted, the survey instrument itself, a presentation of the quantified results, and a discussion of the results.

You can choose to graphically represent your data for easier interpretation by others outside your research project. You can use, for example, bar graphs, histograms, frequency polygrams, pie charts and consistency tables.

Commentary on Survey Research

In this section, we present several commentaries on survey research.

Strengths and Weaknesses of Surveys

Surveys are relatively inexpensive (especially self-administered surveys).
Surveys are useful in describing the characteristics of a large population. No other method of observation can provide this general capability.
They can be administered from remote locations using mail, email or telephone.
Consequently, very large samples are feasible, making the results statistically significant even when analyzing multiple variables.
Many questions can be asked about a given topic giving considerable flexibility to the analysis.
There is flexibilty at the creation phase in deciding how the questions will be administered: as face-to-face interviews, by telephone, as group administered written or oral survey, or by electonic means.
Standardized questions make measurement more precise by enforcing uniform definitions upon the participants.
Standardization ensures that similar data can be collected from groups then interpreted comparatively (between-group study).
Usually, high reliability is easy to obtain--by presenting all subjects with a standardized stimulus, observer subjectivity is greatly eliminated.

Weaknesses:

A methodology relying on standardization forces the researcher to develop questions general enough to be minimally appropriate for all respondents, possibly missing what is most appropriate to many respondents.
Surveys are inflexible in that they require the initial study design (the tool and administration of the tool) to remain unchanged throughout the data collection.
The researcher must ensure that a large number of the selected sample will reply.
It may be hard for participants to recall information or to tell the truth about a controversial question.
As opposed to direct observation, survey research (excluding some interview approaches) can seldom deal with "context."

Reliability and Validity

Surveys tend to be weak on validity and strong on reliability. The artificiality of the survey format puts a strain on validity. Since people's real feelings are hard to grasp in terms of such dichotomies as "agree/disagree," "support/oppose," "like/dislike," etc., these are only approximate indicators of what we have in mind when we create the questions. Reliability, on the other hand, is a clearer matter. Survey research presents all subjects with a standardized stimulus, and so goes a long way toward eliminating unreliability in the researcher's observations. Careful wording, format, content, etc. can reduce significantly the subject's own unreliability.

Ethical Considerations of Using Electronic Surveys

Because electronic mail is rapidly becoming such a large part of our communications system, this survey method deserves special attention. In particular, there are four basic ethical issues researchers should consider if they choose to use email surveys.

Sample Representatives: Since researchers who choose to do surveys have an ethical obligation to use population samples that are inclusive of race, gender, educational and income levels, etc., if you choose to utilize e-mail to administer your survey you face some serious problems. Individuals who have access to personal computers, modems and the Internet are not necessarily representative of a population. Therefore, it is suggested that researchers not use an e-mail survey when a more inclusive research method is available. However, if you do choose to do an e-mail survey because of its other advantages, you might consider including as part of your survey write up a reminder of the limitations of sample representativeness when using this method.

Data Analysis: Even though e-mail surveys tend to have greater response rates, researchers still do not necessarily know exactly who has responded. For example, some e-mail accounts are screened by an unintended viewer before they reach the intended viewer. This issue challenges the external validity of the study. According to Goree and Marszalek (1995), because of this challenge, "researchers should avoid using inferential analysis for electronic surveys" (p. 78).

Confidentiality versus Anonymity: An electronic response is never truly anonymous, since researchers know the respondents' e-mail addresses. According to Goree and Marszalek (1995), researchers are ethically required to guard the confidentiality of their respondents and to assure respondents that they will do so.

Responsible Quotation: It is considered acceptable for researchers to correct typographical or grammatical errors before quoting respondents since respondents do not have the ability to edit their responses. According to Goree and Marszalek (1995), researchers are also faced with the problem of "casual language" use common to electronic communication (p. 78). Casual language responses may be difficult to report within the formal language used in journal articles.

Response Rate Issues

Each year, nonresponse and response rates are becoming more and more important issues in survey research. According to Weisberg, Krosnick and Bowen (1989), in the 1950s it was not unusual for survey researchers to obtain response rates of 90 percent. Now, however, people are not as trusting of interviewers and response rates are much lower--typically 70 percent or less. Today, even when survey researchers obtain high response rates, they still have to deal with many potential respondent problems.

Nonresponse Issues

Nonresponse Errors Nonresponse is usually considered a source of bias in a survey, aptly called nonresponse bias . Nonresponse bias is a problem for almost every survey as it arises from the fact that there are usually differences between the ideal sample pool of respondents and the sample that actually responds to a survey. According to Fox and Tracy (1986), "when these differences are related to criterion measures, the results may be misleading or even erroneous" (p. 9). For example, a response rate of only 40 or 50 percent creates problems of bias since the results may reflect an inordinate percentage of a particular demographic portion of the sample. Thus, variance estimates and confidence intervals become greater as the sample size is reduced, and it becomes more difficult to construct confidence limits.

Nonresponse bias usually cannot be avoided and so inevitably negatively affects most survey research by creating errors in a statistical measurement. Researchers must therefore account for nonresponse either during the planning of their survey or during the analysis of their survey results. If you create a larger sample during the planning stage, confidence limits may be based on the actual number of responses themselves.

Household-Level Determinants of Nonresponse

According to Couper and Groves (1996), reductions in nonresponse and its errors should be based on a theory of survey participation. This theory of survey participation argues that a person's decision to participate in a survey generally occurs during the first moments of interaction with an interviewer or the text. According to Couper and Groves, four types of influences affect a potential respondent's decision of whether or not to cooperate in a survey. First, potential respondents are influenced by two factors that the researcher cannot control: by their social environments and by their immediate households. Second, potential respondents are influenced by two factors the researcher can control: the survey design and the interviewer.

To minimize nonresponse, Couper and Groves suggest that researchers manipulate the two factors they can control--the survey design and the interviewer.

Response Issues

Not only do survey researchers have to be concerned about nonresponse rate errors, but they also have to be concerned about the following potential response rate errors:

Response bias occurs when respondents deliberately falsify their responses. This error greatly jeopardizes the validity of a survey's measurements.
Response order bias occurs when a respondent loses track of all options and picks one that comes easily to mind rather than the most accurate.
Response set bias occurs when respondents do not consider each question and just answer all the questions with the same response. For example, they answer "disagree" or "no" to all questions.

These response errors can seriously distort a survey's results. Unfortunately, according to Fox and Tracy (1986), response bias is difficult to eliminate; even if the same respondent is questioned repeatedly, he or she may continue to falsify responses. Response order bias and response set errors, however, can be reduced through careful development of the survey questionnaire.

Satisficing

Related to the issue of response errors, especially response order bias and response bias, is the issue of satisficing. According to Krosnick, Narayan, and Smith (1996) satisficing is the notion that certain survey response patterns occur as respondents "shortcut the cognitive processes necessary for generating optimal answers" (p. 29). This theoretical perspective arises from the belief that most respondents are not highly motivated to answer a survey's questions, as reflected in the declining response rates in recent years. Since many people are reluctant to be interviewed, it is presumptuous to assume that respondents will devote a lot of effort to answering a survey.

The theoretical notion of satisficing can be further understood by considering what respondents must do to provide optimal answers. According to Krosnick et. al. (1996), "respondents must carefully interpret the meaning of each question, search their memories extensively for all relevant information, integrate that information carefully into summary judgments, and respond in ways that convey those judgments' meanings as clearly and precisely as possible"(p. 31). Therefore, satisficing occurs when one or more of these cognitive steps is compromised.

Satisficing takes two forms: weak and strong . Weak satisficing occurs when respondents go through all of the cognitive steps necessary to provide optimal answers, but are not as thorough in their cognitive processing. For example, respondents can answer a question with the first response that seems acceptable instead of generating an optimal answer. Strong satisficing, on the other hand, occurs when respondents omit the steps of judgment and retrieval altogether.

Even though they believe that not enough is known yet to offer suggestions on how to increase optimal respondent answers, Krosnick et. al. (1996) argue that satisficing can be reduced by maximizing "respondent motivation" and by "minimizing task difficulty" in the survey questionnaire (p. 43).

Annotated Bibliography

General Survey Information:

Allan, Graham, & Skinner, Chris (eds.) (1991). Handbook for Research Students in the Social Sciences. The Falmer Press: London.

This book is an excellent resource for anyone studying in the social sciences. It is not only well-written, but it is clear and concise with pertinent research information.

Alreck, P. L., & Settle, R. B. (1995 ). The survey research handbook: Guidelines and strategies for conducting a survey (2nd). Burr Ridge, IL: Irwin.

Provides thorough, effective survey research guidelines and strategies for sponsors, information seekers, and researchers. In a very accessible, but comprehensive, format, this handbook includes checklists and guidelists within the text, bringing together all the different techniques and principles, skills and activities to do a "really effective survey."

Babbie, E.R. (1973). Survey research methods . Belmont, CA: Wadsworth.

A comprehensive overview of survey methods. Solid basic textbook on the subject.

Babbie, E.R. (1995). The practice of social research (7th). Belmont, CA: Wadsworth.

The reference of choice for many social science courses. An excellent overview of question construction, sampling, and survey methodology. Includes a fairly detailed critique of an example questionnaire. Also includes a good overview of statistics related to sampling.

Belson, W.A. (1986). Validity in survey research . Brookvield, VT: Gower.

Emphasis on construction of survey instrument to account for validity.

Bourque, Linda B. & Fiedler, Eve P. (1995). How to Conduct Self-Administered and Mail Surveys. Sage Publications: Thousand Oaks.

Contains current information on both self-administered and mail surveys. It is a great resource if you want to design your own survey; there are step-by-step methods for conducting these two types of surveys.

Bradburn, N.M., & Sudman, S. (1979). Improving interview method and questionnaire design . San Francisco: Jossey-Bass Publishers.

A good overview of polling. Includes setting up questionnaires and survey techniques.

Bradburn, N. M., & Sudman, S. (1988). Polls and Surveys: Understanding What They Tell Us. San Francisco: Jossey-Bass Publishers.

These veteran survey researchers answer questions about survey research that are commonly asked by the general public.

Campbell, Angus, A., &and; Katona, Georgia. (1953). The Sample Survey: A Technique for Social Science Research. In Newcomb, Theodore M. (Ed). Research Methods in the Behavioral Sciences. The Dryden Press: New York. p 14-55.

Includes information on all aspects of social science research. Some chapters in this book are outdated.

Converse, J. M., & Presser, S. (1986). Survey questions: Handcrafting the standardized questionnaire . Newbury Park, CA: Sage.

A very helpful little publication that addresses the key issues in question construction.

Dillman, D.A. (1978). Mail and telephone surveys: The total design method . New York: John Wiley & Sons.

An overview of conducting telephone surveys.

Frey, James H., & Oishi, Sabine Mertens. (1995). How To Conduct Interviews By Telephone and In Person. Sage Publications: Thousand Oaks.

This book has a step-by-step breakdown of how to conduct and design telephone and in person interview surveys.

Fowler, Floyd J., Jr. (1993). Survey Research Methods (2nd.). Newbury Park, CA: Sage.

An overview of survey research methods.

Fowler, F. J. Jr., & Mangione, T. W. (1990). Standardized survey interviewing: Minimizing interviewer-related error . Newbury Park, CA: Sage.

Another aspect of validity/reliability--interviewer error.

Fox, J. & Tracy, P. (1986). Randomized Response: A Method for Sensitive Surveys . Beverly Hills, CA: Sage.

Authors provide a good discussion of response issues and methods of random response, especially for surveys with sensitive questions.

Frey, J. H. (1989). Survey research by telephone (2nd). Newbury Park, CA: Sage.

General overview to telephone polling.

Glock, Charles (ed.) (1967). Survey Research in the Social Sciences. New York: Russell Sage Foundation.

Although fairly outdated, this collection of essays is useful in illustrating the somewhat different ways in which different disciplines regard and use survey research.

Hoinville, G. & Jowell, R. (1978). Survey research practice . London: Heinemann.

Practical overview of the methods and procedures of survey research, particularly discussing problems which may arise.

Hyman, H. H. (1972). Secondary Analysis of Sample Surveys. New York: John Wiley & Sons.

This source is particularly useful for anyone attempting to do secondary analysis. It offers a comprehensive overview of this research method, and couches it within the broader context of social scientific research.

Hyman, H. H. (1955). Survey design and analysis: Principles, cases, and procedures . Glencoe, IL: Free Press.

According to Babbie, an oldie but goodie--a classic.

Jones, R. (1985). Research methods in the social and behavioral sciences . Sunderland, MA: Sinauer.

General introduction to methodology. Helpful section on survey research, especially the discussion on sampling.

Kalton, G. (1983). Compensating for missing survey data . Ann Arbor, MI: Survey Research Center, Institute for Social Research, the University of Michigan.

Addresses a problem often encountered in survey methodology.

Kish, L. (1965). Survey sampling . New York: John Wiley & Sons.

Classic text on sampling theories and procedures.

Lake, C.C., & Harper, P. C. (1987). Public opinion polling: A handbook for public interest and citizen advocacy groups . Washington, D.C.: Island Press.

Clearly written easy to read and follow guide for planning, conducting and analyzing public surveys. Presents material in a step-by-step fashion, including checklists, potential pitfalls and real-world examples and samples.

Lauer, J.M., & Asher, J. W. (1988). Composition research: Empirical designs . New York: Oxford UP.

Excellent overview of a number of research methodologies applicable to composition studies. Includes a chapter on "Sampling and Surveys" and appendices on basic statistical methods and considerations.

Monette, D. R., Sullivan, T. J, & DeJong, C. R. (1990). Applied Social Research: Tool for the Human Services (2nd). Fort Worth, TX: Holt.

A good basic general research textbook which also includes sections on minority issues when doing research and the analysis of "available" or secondary data..

Rea, L. M., & Parker, R. A. (1992). Designing and conducting survey research: A comprehensive guide . San Francisco: Jossey-Bass.

Written for the social and behavioral sciences, public administration, and management.

Rossi, P.H., Wright, J.D., & Anderson, A.B. (eds.) (1983). Handbook of survey research . New York: Academic Press.

Handbook of quantitative studies in social relations.

Salant, P., & Dillman, D. A. (1994). How to conduct your own survey . New York: Wiley.,

A how-to book written for the social sciences.

Sayer, Andrew. (1992). Methods In Social Science: A Realist Approach. Routledge: London and New York.

Gives a different perspective on social science research.

Schuldt, Barbara A., & Totter, Jeff W. (1994, Winter). Electronic Mail vs. Mail Survey Response Rates. Marketing Research, 6. 36-39.

An article with specific information for electronic and mail surveys. Mainly a technical resource.

Schuman, H. & Presser, S. (1981). Questions and answers in attitude surveys . New York: Academic Press.

Detailed analysis of research question wording and question order effects on respondents.

Schwartz, N. & Seymour, S. (1996) Answering Questions: Methodology for Determining Cognitive and Communication Processes in Survey Research. San Francisco: Josey-Bass.

Authors provide a summary of the latest research methods used for analyzing interpretive cognitive and communication processes in answering survey questions.

Seymour, S., Bradburn, N. & Schwartz, N. (1996) Thinking About Answers: The Application of Cognitive Processes to Survey Methodology. San Francisco: Josey-Bass.

Explores the survey as a "social conversation" to investigate what answers mean in relation to how people understand the world and communicate.

Simon, J. (1969). Basic research methods in social science: The art of empirical investigation. New York: Random .

An excellent discussion of survey analysis. The definitions and descriptions begin from a fairly understandable (simple) starting point, then the discussion unfolds to cover some fairly complex interpretive strategies.

Singleton, R. Jr., et. al. (1988). Approaches to social research . New York: Oxford UP.

Has a very accessible chapter on sampling as well as a chapter on survey research.

Smith, Robert B. (Ed.) (1982). A Handbook of Social Science Methods, Volume 3. Prayer: New York.

There is a series of handbooks, each one with specific topics in social science research. A good technical resource, yet slightly dated.

Sul Lee, E., Forthofer, R.N.,& Lorimor, R.J. (1989). Analyzing complex survey data . Newbury Park, CA: Sage Publications.

Details on the statistical analysis of survey data.

Singer, E., & Presser, S., eds. (1989). Survey research methods: A reader . Chicago: U of Chicago P.

The essays in this volume originally appeared in various issues of Public Opinion Quarterly.

Survey Research Center (1983). Interviewer's manual . Ann Arbor, MI: University of Michigan Press.

Very practical, step-by-step guide to conducting a survey and interview with lots of examples to illustrate the process.

Pearson, R.W., &Borouch, R.F. (Eds.) (1986). Survey Research Design: Towards a Better Understanding of Their Costs and Benefits. Springer-Verag: Berlin.

Explains, in a technical fashion, the financial aspects of research design. Somewhat of a cost-analysis book.

Weissberg, H.F., Krosnick , J.A., & Bowen, B.D. (1989). An introduction to survey research and data analysis . Glenview, IL: Scott Foresman.

A good discussion of basic analysis and statistics, particularly what statistical applications are appropriate for particular kinds of data.

Anderson, B., Puur, A., Silver, B., Soova, H., & Voormann, R. (1994). Use of a lottery as an incentive for survey participation: a pilot survey in Estonia. International Journal of Public Opinion Research, 6 , 64-71.

Looks at return results in a study that offers incentives, and recommends incentive use to increase response rates.

Bare, J. (1994). Truth about daily fluctuations in 1992 pre-election polls. Newspaper Research Journal, 15, 73-81.

Comparison of variations between daily poll results of the major polls used during the 1992 American Presidential race.

Chi, S. (1993). Computer knowledge, interests, attitudes, and uses among faculty in two teachers' universities in China. DAI-A, 54/12 , 4412-4623.

Survey indicating a strong link between subject area and computer usage.

Cowans, J. (1994). Wielding the people: Opinion polls and the problem of legitimacy in France since 1944. DAI-A, 54/12 , 4556-5027.

Study looks at how the advent of opinion polling has affected the legitimacy of French governments since World War II.

Crewe, I. (1993). A nation of liars? Opinion polls and the 1992 election. Journal of the Market Research Society, 35 , 341-359.

Poses possible reasons the British polls were so wrong in predicting the outcomes of the 1992 national elections.

Daly, J., & Miller, M. (1975). The empirical development of an instrument to measure writing apprehension. Research in the teaching of English , 9 (3), 242-249.

Discussion of basics in question development and data analysis. Also includes some sample questions.

Daniell, S. (1993). Graduate teaching assistants' attitudes toward and responses to academic dishonesty. DAI-A,54/06, 2065- 2257.

Study explores the ethical and academic responses to cheating, using a large survey tool.

Mittal, B. (1994). Public assessment of TV advertising: Faint praise and harsh criticism. Journal of Advertising Research, 34, 35-53.

Results of a survey of Southern U.S. television viewers' perceptions of television advertisements.

Palmquist, M., & Young, R.E. (1992). Is writing a gift? The impact on students who believe it is. Reading empirical research studies: The rhetoric of research . Hayes et al. eds. Hillsdale NJ: Erlbaum.

This chapter presents results of a study of student beliefs about writing. Includes sample questions and data analysis.

Serow, R. C., & Bitting, P. F. (1995). National service as educational reform: A survey of student attitudes. Journal of research and development in education , 28 (2), 87-90.

This study assessed college students' attitude toward a national service program.

Stouffer, Samuel. (1955). Communism, Conformity, and Civil Liberties. New York: John Wiley & Sons.

This is a famous old survey worth examining. This survey examined the impact of McCarthyism on the attitudes of both the general public and community leaders, a asking whether the repression of the early 1950s affected support for civil liberties.

Wanta, W. & Hu, Y. (1993). The agenda-setting effects of international news coverage: An examination of differing news frames. International Journal of Public Opinion Research, 5, 250-264.

Discusses results of Gallup polls on important problems in relation to the news coverage of international news.

Worcester, R. (1992). The performance of the political opinion polls in the 1992 British general election. Marketing and Research Today, 20, 256-263.

A critique of the use of polls in an attempt to predict voter actions.

Yamada, S, & Synodinos, N. (1994). Public opinion surveys in Japan. International Journal of Public Opinion Research, 6 , 118-138.

Explores trends in opinion poll usage, response rates, and refusals in Japanese polls from 1975 to 1990.

Criticism/Critique/Evaluation:

Bangura, A. K. (1992). The limitations of survey research methods in assessing the problem of minority student retention in higher education . San Francisco: Mellen Research UP.

Case study done at a Maryland university addressing an aspect of validity involving intercultural factors.

Bateson, N. (1984). Data construction in social surveys. London: Allen & Unwin.

Tackles the theory of the method (but not the methods of the method) of data construction. Deals with validity of the data by validizing the process of data construction.

Braverman, M. (1996). Sources of Survey Error: Implications for Evaluation Studies. New Directions for Evaluation: Advances in Survey Research ,70, 17-28.

Looks at how evaluations using surveys can benefit from using survey design methods that reduce various survey errors.

Brehm, J. (1994). Stubbing our toes for a foot in the door? Prior contact, incentives and survey response. International Journal of Public Opinion Research, 6 , 45-63.

Considers whether incentives or the original contact letter lead to increased response rates.

Bulmer, M. (1977). Social-survey research. In M. Bulmer (ed.), Sociological research methods: An introduction . London: Macmillan.

The section includes discussions of pros and cons of survey research findings, inferences and interpreting relationships found in social-survey analysis.

Couper, M. & Groves, R. (1996). Household-Level Determinants of Survey Nonresponse. . New Directions for Evaluation: Advances in Survey Research , 70, 63-80.

Authors discuss their theory of survey participation. They believe that decisions to participate are based on two occurences: interactions with the interviewer, and the sociodemographic characteristics of respondents.

Couto, R. (1987). Participatory research: Methodology and critique. Clinical Sociology Review, 5 , 83-90.

Criticism of survey research. Addresses knowledge/power/change issues through the critique.

Dillman, D., Sangster, R., Tarnai, J., & Rockwood, T. (1996) Understanding Differences in People's Answers to Telephone and Mail Surveys. New Directions for Evaluation: Advances in Survey Research , 70, 45-62.

Explores the issue of differences in respondents' answers in telephone and mail surveys, which can affect a survey's results.

Esaiasson, P. & Granberg, D. (1993). Hidden negativism: Evaluation of Swedish parties and their leaders under different survey methods. International Journal of Public Opinion Research, 5, 265-277.

Compares varying results of mailed questionnaires vs. telephone and personal interviews. Findings indicate methodology affected results.

Guastello, S. & Rieke, M. (1991). A review and critique of honesty test research. Behavioral Sciences and the Law, 9, 501-523.

Looks at the use of honesty, or integrity, testing to predict theft by employees, questioning further use of the tests due to extremely low validity. Social and legal implications are also considered.

Hamilton, R. (1991). Work and leisure: On the reporting of poll results. Public Opinion Quarterly, 55 , 347-356.

Looks at methodology changes that affected reports of results in the Harris poll on American Leisure.

Juster, F. & Stanford, F. (1991). Comment on work and leisure: On reporting of poll results. Public Opinion Quarterly, 55 , 357-359.

Rebuttal of the Hamilton essay, cited above. The rebuttal is based upon statistical interpretation methods used in the cited survey.

Krosnick, J., Narayan, S., & Smith, W. (1996). Satisficing in Surveys: Initial Evidence. New Directions in Evaluation: Advances in Survey Research , 70, 29-44.

Authors discuss "satisficing," a cognitive approach to survey response, which they believe helps researchers understand how survey respondents arrive at their answers.

Lindsey, J.K. (1973). Inferences from sociological survey data: A unified approach . San Francisco: Jossey-Bass.

Examines the statistical analysis of survey data.

Morgan, F. (1990). Judicial standards for survey research: An update and guidelines. Journal of Marketing, 54 , 59-70.

Looks at legal use of survey information as defined and limited in recent cases. Excellent definitions.

Pottick, K. (1990). Testing the underclass concept by surveying attitudes and behavior. Journal of Sociology and Social Welfare, 17, 117-125.

Review of definitional tests constructed to define "underclass."

Rohme, N. (1992). The state of the art of public opinion polling worldwide. Marketing and Research Today, 20, 264-271.

A quick review of the use of polling in several countries, concluding that the use of polling is on the rise worldwide.

Sabatelli, R. (1988). Measurement issues in marital research: A review and critique of contemporary survey instruments. Journal of Marriage and the Family, 55 , 891-915.

Examines issues of methodology.

Schriesheim, C. A.,& Denisi, A. S. (1980). Item Presentation as an Influence on Questionnaire Validity: A Field Experiment. Educational-and-Psychological-Measurement ; 40 (1), 175-82.

Two types of questionnaire formats measuring leadership variables were examined: one with items measuring the same dimensions grouped together and the second with items measuring the same dimensions distributed randomly. The random condition showed superior validity.

Smith, T. (1990). "A critique of the Kinsey Institute/Roper organization national sex knowledge survey." Public Opinion Quarterly, Vol. 55 , 449-457.

Questions validity of the survey based upon question selection and response interpretations. A rejoinder follows, defending the poll.

Smith, Tom W. (1990). "The First Straw? A Study of the Origins of Election Polls," Public Opinion Quarterly, Vol. 54 (Spring: 21-36).

This article offers a look at the early history of American political polling, with special attention to media reactions to the polls. This is an interesting source for anyone interested in the ethical issues surrounding polling and survey.

Sniderman, P. (1986). Reflections on American racism. Journal of Social Issues, 42 , 173-187.

Rebuttal of critique of racism research. Addresses issues of bias and motive attribution.

Stanfield, J. H. II, & Dennis, R. M., eds (1993). Race and Ethnicity in Research Methods . Newbury Park, CA: Sage.

The contributions in this volume examine the array of methods used in quantitative, qualitative, and comparative and historical research to show how research sensitive to ethnic issues can best be conducted.

Stapel, J. (1993). Public opinion polling: Some perspectives in response to 'critical perspectives.' International Journal of Public Opinion Research, 5, 193-194.

Discussion of the moral power of polling results.

Wentland, E. J., & Smith, K. W. (1993). Survey responses: An evaluation of their validity . San Diego: Academic Press.

Reviews and analyzes data from studies that have, through the use of external criteria, assessed the validity of individuals' responses to questions concerning personal characteristics and behavior in a wide variety of areas.

Williams, R. M., Jr. (1989). "The American Soldier: An Assessment, Several Wars Later." Public Opinion Quarterly. Vol. 53 (Summer: 155-174).

One of the classic studies in the history of survey research is reviewed by one of its authors.

Secondary Analysis:

Jolliffe, F.R. (1986). Survey Design and Analysis. Ellis Horwood Limited: Chichester.

Information about survey design as well as secondary analysis of surveys.

Kiecolt, K. J., & Nathan, L. E. (1985). Secondary analysis of survey data . Beverly Hills, CA: Sage.

Discussion of how to use previously collected survey data to answer a new research question.

Monette, D. R., Sullivan, T. J, & DeJong, C. R. (1990). Analysis of available data. In Applied Social Research: Tool for the Human Services (2nd ed., pp. 202-230). Fort Worth, TX: Holt.

Gives some existing sources for statistical data as well as discussing ways in which to use it.

Rubin, A. (1988). Secondary analyses. In R. M. Grinnell, Jr. (Ed.), Social work research and evaluation. (3rd ed., pp. 323-341). Itasca, IL: Peacock.

Chapter discusses inductive and deductive processes in relation to research designs using secondary data. It also discusses methodological issues and presents a case example.

Dale, A., Arber, S., & Procter, M. (1988). Doing Secondary Analysis . London: Unwin Hyman.

A whole book about how to do secondary analysis.

Electronic Surveys:

Carr, H. H. (1991). Is using computer-based questionnaires better than using paper? Journal of Systems Management September, 19, 37.

Reference from Thach.

Dunnington, Richard A. (1993). New methods and technologies in the organizational survey process. American Behavioral Scientist , 36 (4), 512-30.

Asserts that three decades of technological advancements in communications and computer techhnology have transformed, if not revolutionized, organizational survey use and potential.

Goree, C. & Marszalek, J. (1995). Electronic Surveys: Ethical Issues for Researchers. The College Student Affairs Journal , 15 (1), 75-79.

Explores how the use of electronic surveys challenge existing ethical standards of survey research, and how that researchers need to be aware of these new ethical issues.

Hsu, J. (1995). The Development of Electronic Surveys: A Computer Language-Based Method. The Electronic Library , 13 (3), 195-201.

Discusses the need for a markup language method to properly support the creation of survey questionnaires.

Kiesler, S. & Sproull, L. S. (1986). Response effects in the electronic survey. Public Opinion Quarterly, 50 , 402-13.

Opperman, M. (1995) E-Mail Surveys--Potentials and Pitfalls. Marketing Research, 7 (3), 29-33.

A discussion of the advantages and disadvantages of using E-Mail surveys.

Sproull, L. S. (1986). Using electronic mail for data collection in organizational research. Academy of Management Journal, 29, 159-69.

Synodinos, N. E., & Brennan, J. M. (1988). Computer interactive interviewing in survey research. Psychology & Marketing, 5 (2), 117-137.

Thach, Liz. (1995). Using electronic mail to conduct survey research. Educational Technology, 35, 27-31.

A review of the literature on the topic of survey research via electronic mail concentrating on the key issues in design, implementation, and response using this medium.

Walsh, J. P., Kiesler, S., Sproull, L. S., & Hesse, B. W. (1992). Self-selected and randomly selected respondents in a computer network survey. Public Opinion Quarterly, 56, 241-244.

Further Investigation

Bery, David N., & Smith , Kenwyn K. (eds.) (1988). The Self in Social Inquiry: Researching Methods. Sage Publications: Newbury Park.

Has some ethical issues about the role of researcher in social science research.

Barribeau, Paul, Bonnie Butler, Jeff Corney, Megan Doney, Jennifer Gault, Jane Gordon, Randy Fetzer, Allyson Klein, Cathy Ackerson Rogers, Irene F. Stein, Carroll Steiner, Heather Urschel, Theresa Waggoner, & Mike Palmquist. (2005). Survey Research. Writing@CSU . Colorado State University. https://writing.colostate.edu/guides/guide.cfm?guideid=68

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Survey Research Design: Definition, How to Conduct a Survey & Examples

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Survey research is a quantitative research method that involves collecting data from a sample of individuals using standardized questionnaires or surveys. The goal of survey research is to measure the attitudes, opinions, behaviors, and characteristics of a target population. Surveys can be conducted through various means, including phone, mail, online, or in-person.

If your project involves live interaction with numerous people in order to obtain important data, you should know the basic rules of survey research beforehand. Today we’ll talk about this research type, review the step-by-step guide on how to do a survey research and try to understand main advantages and potential pitfalls. The following important questions will be discussed below:

Purpose and techniques of information collection.
Kinds of responses.
Analysis techniques, assumptions, and conclusions.

Do you wish to learn best practices of survey conducting? Stay with our research paper service and get prepared for some serious reading!

What Is Survey Research: Definition

Let’s define the notion of survey research first. It revolves around surveys you conduct to retrieve certain data from your respondents. The latter is to be carefully selected from some population that for particular reasons possess the data necessary for your research. For example, they can be witnesses of some event that you should investigate. Surveys contain a set of predefined questions, closed- or open-ended. They can be sent to participants who would answer them and thus provide you with data for your research. There are many methods for organizing surveys and processing the obtained information.

Purpose of Survey Research Design

Purpose of survey research is to collect proper data and thus get insights for your research. You should pick participants with relatable experience. It should be done in order to get relevant information from them. Questions in your survey should be formulated in a way that allows getting as much useful data as possible. The format of a survey should be adjusted to the situation. It will ensure your respondents will be ready to give their answers. It can be a questionnaire sent over email or questions asked during a phone call.

Surveys Research Methods

Which survey research method to choose? Let’s review the most popular approaches and when to use them. There are two critical factors that define how a survey will be conducted

Tool to send questions
online: using web forms or email questionnaires.
phone: reaching out to respondents individually. Sometimes using an automated service.
face-to-face: interviewing respondents in the real world. This makes room for more in-depth questions.
Time to conduct research
short-term periods.
long-term periods.

Let’s explore the time-related methods in detail.

Cross-Sectional Survey Design Research

The first type is cross sectional survey research. Design of this survey type includes collecting various insights from an audience within a specific short time period. It is used for descriptive analysis of a subject. The purpose is to provide quick conclusions or assumptions. Which is why this approach relies on fast data gathering and processing techniques. Such surveys are typically implemented in sectors such as retail, education, healthcare etc, where the situation tends to change fast. So it is important to obtain operational results as soon as possible.

Longitudinal Survey Research

Let’s talk about survey research designs . Planning a design beforehand is crucial. It is crucial in case you are pressed on time or have a limited budget. Collecting information using a properly designed survey research is typically more effective and productive compared with a casually conducted study. Preparation of a survey design includes the following major steps:

Understand the aim of your research. So that you can better plan the entire path of a survey and avoid obvious issues.
Pick a good sample from a population. Ensure precision of the results by selecting members who could provide useful insights and opinions.
Review available research methods. Decide about the one most suitable for your specific case.
Prepare a questionnaire. Selection of questions would directly affect the quality of your longitudinal analysis . So make sure to pick good questions. Also, avoid unnecessary ones to save time and counter possible errors.
Analyze results and make conclusions.

Advantages of Survey Research

As a rule, survey research involves getting data from people with first-hand knowledge about the research subject. Therefore, when formulated properly, survey questions should provide some unique insights and thus describe the subject better. Other benefits of this approach include:

Minimum investment. Online and automated call services require very low investment per respondent.
Versatile sources. Data can be collected by numerous means, allowing more flexibility.
Reliable for respondents. Anonymous surveys are secure. Respondents are more likely to answer honestly if they understand it will be confidential.

Types of Survey Research

Let’s review the main types of surveys. It is important to know about most popular templates. So that you wouldn’t have to develop your own ones from scratch for your specific case. Such studies are usually categorized by the following aspects:

Objectives.
Data source.
Methodology.

We’ll examine each of these aspects below, focusing on areas where certain types are used.

Types of Survey Research Depending on Objective

Depending on your objective and the specifics of the subject’s context, the following survey research types can be used:

Predictive This approach foresees asking questions that automatically predict the best possible response options based on how they are formulated. As a result, it is often easier for respondents to provide their answers as they already have helpful suggestions.
Exploratory This approach is focused more on the discovery of new ideas and insights rather than collecting statistically accurate information. The results can be difficult to categorize and analyze. But this approach is very useful for finding a general direction for further research.
Descriptive This approach helps to define and describe your respondents' opinions or behavior more precisely. By predefining certain categories and designing survey questions, you obtain statistical data. This descriptive research approach is often used at later research stages. It is used in order to better understand the meaning of insights obtained at the beginning.

Types of Survey Research Depending on Data Source

The following research survey types can be defined based on which sources you obtain the data from:

Primary In this case, you collect information directly from the original source, e.g., learn about a natural disaster from a survivor. You aren’t using any intermediary instances. And, as a result, don't get any information twisted or lost on its way. This is the way to obtain the most valid and trustworthy results. But at the same time, it is often not so easy to access such sources.
Secondary This involves collecting data from existing research on the same subject that has been published. Such information is easier to access. But at the same time, it is usually too general and not tailored for your specific needs.

Types of Survey Research Depending on Methodology

Finally, let’s review survey research methodologies based on the format of retrieved and processed data. They can be:

Quantitative An approach that focuses on gathering numeric or measurable data from respondents. This provides enough material for statistical analysis. And then leads to some meaningful conclusions. Collection of such data requires properly designed surveys that include numeric options. It is important to take precautions to ensure that the data you’ve gathered is valid.
Qualitative Such surveys rely on opinions, impressions, reflections, and typical reactions of target groups. They should include open-ended questions to allow respondents to give detailed answers. It allows providing information that they consider most relevant. Qualitative research is used to understand, explain or evaluate some ideas or tendencies.

It is essential to differentiate these two kinds of research. That's why we prepared a special blog, which is about quantitative vs qualitative research .

How to Conduct a Survey Research: Main Steps

Now let’s find out how to do a survey step by step. Regardless of methods you use to design and conduct your survey, there are general guidelines that should be followed. The path is quite straightforward:

Assess your goals and options for accessing necessary groups.
Formulate each question in a way that helps you obtain the most valuable data.
Plan and execute the distribution of the questions.
Process the results.

Let’s take a closer look at all these stages.

Step 1. Create a Clear Survey Research Question

Each survey research question should add some potential value to your expected results. Before formulating your questionnaire, it is better to invest some time analyzing your target populations. This will allow you to form proper samples of respondents. Big enough to get some insights from them but not too big at the same time. A good way to prepare questions is by constructing case studies for your subject. Analyzing case study examples in detail will help you understand which information about them is necessary.

Step 2. Choose a Type of Survey Research

As we’ve already learned, there are several different types of survey research. Starting with a close analysis of your subject, goals and available sources will help you understand which kinds of questions are to be distributed. As a researcher, you’ll also need to analyze the features of the selected group of respondents. Pick a type that makes it easier to reach out to them. For example, if you should question a group of elderly people, online forms wouldn’t be efficient compared with interviews.

Step 3. Distribute the Questionnaire for Your Survey Research

The next step of survey research is the most decisive one. Now you should execute the plan you’ve created earlier. And then conduct the questioning of the entire group that was selected. If this is a group assignment, ask your colleagues or peers for help. Especially if you should deal with a big group of respondents. It is important to stick to the initial scenario but leave some room for improvisation in case there are difficulties with reaching out to respondents. After you collect all necessary responses, this data can be processed and analyzed.

Step 4. Analyze the Results of Your Research Survey

The data obtained during the survey research should be processed. So that you can use it for making assumptions and conclusions. If it is qualitative, you should conduct a thematic analysis to find important ideas and insights that could confirm your theories or expand your knowledge of the subject. Quantitative data can be analyzed manually or with the help of some program. Its purpose is to extract dependencies and trends from it to confirm or refute existing assumptions.

Step 5. Save the Results of Your Survey Research

The final step is to compose a survey research paper in order to get your results ordered. This way none of them would be lost especially if you save some copies of the paper. Depending on your assignment and on which stage you are at, it can be a dissertation, a thesis or even an illustrative essay where you explain the subject to your audience. Each survey you’ve conducted must get a special section in your paper where you explain your methods and describe your results.

Survey Research Example

We have got a few research survey examples in case you would need some real world cases to illustrate the guidelines and tips provided above. Below is a sample research case with population and the purposes of researchers defined.

Survey Research: Key Takeaways

Today, we have explored the research survey notion and reviewed the main features of this research activity and its usage in the social sciences topics . Important techniques and tips have been reviewed. A step by step guide for conducting such studies has also been provided.

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Frequently Asked Questions About Survey Research

1. what is a market research survey.

A market research survey can help a company understand several aspects of their target market. It typically involves picking focus groups of customers and asking them questions in order to learn about demand for specific products or services and understand whether it grows. Such feedback would be crucial for a company’s development. It can help it to plan its further strategic steps.

2. How does survey research differ from experimental research methods?

The main difference between experiment and survey research is that the latter means field research, while experiments are typically performed in laboratory conditions. When conducting surveys, researchers don’t have full control on the process and should adapt to the specific traits of their target groups in order to obtain answers from them. Besides, results of a study might be harder to quantify and turn into statistical values.

4. What is the difference between survey research and descriptive research?

The purpose of descriptive studies is to explain what the subject is and which features it has. Survey research may include descriptive information but is not limited by that. Typically it goes beyond descriptive statistics and includes qualitative research or advanced statistical methods used to draw inferences, find dependencies or build trends. On the other hand, descriptive methods don’t necessarily include questioning respondents, obtaining information from other sources.

3. What is good sample size for a survey?

It always depends on a specific case and researcher’s goals. However, there are some general guidelines and best practices for this activity. Good maximum sample size is usually around 10% of the population, as long as this does not exceed 1000 people. In any case, you should be mindful of your time and budget limitations when planning your actions. In case you’ve got a team to help you, it might be possible to process more data.

Collaboration, information literacy, writing process, survey research, develop knowledge that is otherwise unavailable by developing an effective survey..

Surveys are a series of questions, which are usually presented in questionnaire format. Surveys can be distributed face-to-face, over the phone, or over the Internet.

Developing, Designing, and Distributing Surveys

Surveys are usually developed to obtain information that is otherwise unavailable. For example, suppose you feel that nationwide statistics on college-age drinking or cheating fail to adequately represent life on your campus. You could then develop a survey to demonstrate (or not demonstrate) your point of view.

Note: This section presents detailed instructions for developing, designing, and distributing surveys. Because English teachers are primarily concerned with how your survey is written, they may encourage you not to worry about some of the design issues addressed below, such as census, random, and stratified census sampling procedures

Determine your survey design by creating questions with your purpose and audience in mind.

To develop a credible survey, you must first organize a systematic approach to your study. This involves insuring your study sample actually represents the population of interest. For example, if you were conducting a survey of whether or not college students ever plagiarized or cheated on a test, you would not want to submit your survey to teachers or parents; you would want to hear from college students. A well-designed survey will reduce the chances of this type of misuse of the data.

Ask the Right Questions

Surveys most commonly take the form of a questionnaire. However, a questionnaire is not just a collection of questions, it is a set of questions focused on a particular objective or set of objectives. Defining objectives simply demonstrates you know what you are doing before you do it. If you have selected a topic like “The education of the 20-year-old,” you would most likely need to narrow the topic before designing your survey. One way to narrow the topic is to consider the when question. When does the education of the 20-year-old interest us? It could be cave people, residents of Europe during the plagues, or some time in the 20th century. Take your choice, but the application of a single survey to cover all the periods of time is highly unlikely.

Limit the Survey

Limit your focus by restricting a geographical region. You may want to survey 20-year-olds who live within 1,000 miles of the North Pole, or only those who live in Palaski County, Missouri. By establishing a geographical target population you can expect reasonable closure. If you wanted to interview all the subjects in your original category (the education of 20-year-olds), you may never get around to writing your report. Another factor that influences your survey is the extent to which you want to examine your population. Do you want to look at all the 20-year-old-students or can you focus on a specific subgroup (such as 20-year-old-students in trade schools or 2-year vs. 4-year colleges or, perhaps, the 20-year-old-students who are self-directed learners attending no formal institution)? What do you want to know about these people anyway? Are you interested in how they learn, why they learn, what they learn or perhaps, how much they spend?

Define Objectives

Ask yourself: What am I going to do with the information once it is revealed? You may plan to simply report your findings, make comparisons with other information or take the results of your survey to support or reject a whole new social theory. All these considerations should be met before beginning your survey research. A well-defined set of objectives eases the burden on the researcher.

Create a Survey Instrument

Learn to write effective survey questions..

After defining the population, surveyors need to create an instrument if a proven survey instrument does not exist. As discussed in more detail below, survey creation parallels the computer axiom “GIGO”–Garbage In—Garbage Out. A well-designed, accurate survey is an excellent way for researchers to gather information or data about a particular subject of interest. When prepared in an unprofessional manner, surveys can also become an inaccurate, misused, misunderstood conveyer of misinformation. If a researcher has developed an idea or hypothesis and seeks information only to prove that the idea is correct, the process, the ethics, the motivation, and the very essence of the researcher are worthy of rigorous challenge and should, most likely, be rejected.

Writing Survey Questions

A survey is more than a list of questions. Not only should each question relate to a specific part of your objectives, but each question should be written in a concise and precise manner, and the survey population must be able to understand what is being asked.

There are four common question formats, as discussed in detail below.

Demographic Questions

Demographic questions attempt to identify the characteristics of the population or sample completing the survey.

Your English instructors do not expect you to generalize from a small sample to a larger population, so your sample does not need to reflect characteristics in the overall population. However, you will need to talk meaningfully about your sample, so you will want to describe the characteristics of your respondents as specifically as possible. The kinds of characteristics you should identify are determined largely by the purpose of your research. Gender, income, age, and level of education are examples of the sort of demographic characteristics that you may want to account for in your survey.

Demographic Example:

Circle One : Male or Female?

Closed Questions

With the closed question, the survey provides responses and the subject selects the one that is most appropriate. When constructing closed questions, you need to provide choices that will allow you to make meaningful interpretations.

Closed questions allow the researcher to deal with the responses in a more efficient manner than open ended questions. Both forms of questions can produce similar information.

Closed Question Example:

How often do you study?

a. less than 6 hours a week

b. 6-10 hours a week

b. 11-15 hours a week

c. more than 15 hours a week

The closed question allows for greater uniformity of response, and the categories can be easily matched to the areas of interest by the researcher. Whether you select one type or a combination of questions for your survey, each question must be clear, unambiguous, and relate to a specific item in your objectives.

A common error is to create a double-barreled question such as, “Do you walk to school or carry your lunch?” Clearly, this question is attempting to ask two different things and a simple yes or no response won’t really answer the question. The original question should be rewritten as two questions: “Do you walk to school?” “Do you carry your lunch?” Now the respondent can provide you useful data.

Rank-Ordered Questions

When your library research has informed you that your audience is likely to be concerned about several issues, you can determine which concern is most troubling by asking a rank-ordered question. Essentially, as illustrated by the following example, the rank-order question presents respondents with several alternatives and requests that they rank them according to priority:

Rank-Ordered Question:

Please rank your five most important reasons for not contributing to our company’s blood drives. Put a #1 by your most important concern, a #2 by your second most important concern, and so forth.

_____ Lack of time _____ Lack of awareness of former blood drives _____ Perception that the blood bank has plenty of blood _____ Concern about possible pain _____ Concern about infection _____ Concern about fainting _____ Concern about vomiting _____ Concern about bruising _____ Concern about being infected with AIDS _____ Belief company should provide some compensation

Open Questions

An open question requires respondents to answer in their own words, like a short-answer or essay type response. Open questions allow for free-flowing responses and are less restrictive than the closed questions. If you are going to use an open-ended question format for mailed surveys, don’t expect a high response rate. People seem more inclined to circle or mark a response than to write a lengthy response.

Open Question Example:

(Ans)_________________________________

Because open-ended commentaries can enrich your interpretation of the statistics, you would be wise to include a few such questions in all surveys that you conduct. One generic question that you might find useful is “What important item(s) has/have been left out of this survey?” However, because they are difficult to tabulate and because they require time on the part of your respondents, be sure to limit the number of open-ended questions you ask.

How Many Questions?

Of course, when you are freewriting possible questions, you should attempt to generate as many questions as possible. You might also ask friends and colleagues what questions they would ask if pursuing your topic. Consider using questions that other researchers have asked, and base additional questions on the sources you have consulted to develop an informed survey. Ultimately, however, you will need to limit the questions so that you have a better chance of getting the surveys back. Before submitting your survey to your targeted sample, ask a few people to take it and time how long it takes them to complete it. Many people are willing to give 15 minutes to a survey, yet find a survey that takes more than 30 minutes intolerable.

Formatting Guidelines

Your questionnaire should be prepared so that someone will read it and respond. Try to make this process as easy as possible for the respondent. Make the questionnaire look like a questionnaire. Have it neatly organized, with questions in a logical sequence, numbering each question and page. If you mix open-and closed-ended questions, put the open-ended questions at the end of the questionnaire. An open-ended response is more threatening than a “select a, b, c, or d” response. Keep your questionnaire focused and as short as possible. Each page added reduces the number of potential respondents who will complete the survey.

Sample the Population

Understand the basics of census and random sampling techniques..

A critical step in survey research involves sampling the population. Now that you have narrowed your objectives to something achievable, who are you going to sample? For many, this is a rather simple step: Ask the people who are able to answer your questions! If you want to learn about the educational perceptions of 20-year-olds, ask them. If you want to learn about the parental perceptions of the education of 20-year-olds, ask the parents.

Since data collection involving humans can raise legal, ethical, and moral issues, if you chose to survey the 20-year-olds on a particular college campus, find out what procedures are required before distributing your questionnaire or conducting interviews (see Informed Consent).

Surveys and questionnaires may be presented:
In paper format.
Over the phone.
Face to face.
Online, perhaps with results viewable in real time.

Census Sample

A researcher may elect to include all the subjects within the population of interest, otherwise known as a census sample. If one is investigating a particular group of people, such as students enrolled in Composition 1 at 8:00 on Monday morning at a particular university, one would survey all the members of the class. The investigation of all the class members is referred to as a census sample.

Random Sample

If you are seeking information about a statewide issue, you would not attempt to interview everyone in the state. Information is still available if you use a technique that allows a sample from the population of interest to represent the population as a whole. A common technique is to employ the random sample. Random sampling implies that each member of the population has an equal chance of being selected in the sample from the population. As a general rule, the higher the sample size the higher the representativeness. The more representativeness you have in the sample, the more it tends to “look like” the population you are studying. Further study in sampling techniques will show how sample size can be determined to afford the researcher a particular level of confidence in the research outcomes.

Random Sample Techniques

Simple random samples may be made using a variety of techniques. One of the most common techniques is the use of a random number table (see Table 1). If you wanted to select 15 people from a classroom of 60 students, begin by obtaining a class roster of all the students. Assign each student a number from 1 – 60. Now we can use the table. Select a row and column. Any row/ column can serve as a starting point. For instance, if you select row 5, column 7 as your starting point, look at the first two digits (34). This number falls within your population range (1 – 60) and therefore can be used as the first of your required 15 people to be selected. Continue down the column. The next number is 68, but that is outside your range, so you should simply skip it and go to the next number, which is 47. When column 7 is exhausted, go to columns 8, 9, and 10 and if you haven’t accomplished your sample of 15, go to column 1 and continue. Note that column 9, rows 2 and 4 repeat the number 60. Since you have selected 60 the first time, simply skip the second and subsequent times. Using this technique, the 15 people from your class size of 60 are represented by numbers 34, 47, 32, 29, 33, 08, 25, 05, 41, 60, 03, 38, 16, 15, and 28. You have just accomplished a simple random sample. As with many things, once you become familiar with the technique, it is often easier to accomplish than to explain.

Table 1—TABLE OF RANDOM NUMBERS

Stratified-Random Sample

Another method of random sampling is called a stratified-random sample . For instance, one may look at the national census for a particular city or state. By applying percentages of age, ethnicity, or gender within the survey design, the researcher is able to gain representativeness within the survey. If the population of a city under study has a population that is 10% Afro-American, 10% Hispanic, 70% Caucasian, and 10% of other ethnic origins, then the researcher would insure the sample of the population contained 10% Afro-American, 10% Hispanic, and so on. The key to random-stratified sampling is to place the population into various categories, called strata, such as age, gender, ethnicity, income, etc. Then select individuals at random from each category. This technique can be used to identify a highly representative sample using a smaller sample size than a purely random sample.

Transmit the Survey

For the mailed survey there are several tactics you can employ to increase the response rate. Write a letter of transmittal stating the purpose and importance of the study, the reason why the individual was selected to participate, insurance of confidentiality, and an offer of thanks for the individual’s participation. If a separate letter is not appropriate, then consider a survey coversheet that contains similar information. Another technique is to send out a mailing informing intended participants that a questionnaire is forthcoming. Advance notification informing individuals they have been selected for your survey may also spark supportive interest.

Sending the Survey and Following Up

Always pick a date for respondents to reply, and be sure that date is at least a few weeks after the survey is mailed. Otherwise you’ll spend most of your time waiting for a response that will never come. About two weeks after your initial mailing, send a follow-up letter. In the letter thank those who have responded and indicate the necessity of obtaining outstanding surveys. Sometimes a statement like “If you have lost the original survey, please contact (researcher’s name, address, phone/fax number) and a new survey will be sent immediately” may also be helpful.

How many follow-ups are required?

That number is up to the researcher. If you can complete your research with a 20% response rate and your sample represents the population from which it is drawn, then don’t follow up. Do be prepared to explain in your report why you stopped. Some researchers will attempt as many as three times to gain subject participation. Given that you have had a particular number of responses now, ask yourself, “Would my results be different if everyone responded?” If you had a 90% initial response, it is unlikely that the remaining 10% would disrupt your findings. If the initial response was only 10%, then you have a considerable amount of work ahead of you.

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J Korean Med Sci
v.35(45); 2020 Nov 23

Reporting Survey Based Studies – a Primer for Authors

Prithvi sanjeevkumar gaur.

1 Smt. Kashibai Navale Medical College and General Hospital, Pune, India.

Olena Zimba

2 Department of Internal Medicine No. 2, Danylo Halytsky Lviv National Medical University, Lviv, Ukraine.

Vikas Agarwal

3 Department Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.

Latika Gupta

Associated data.

The coronavirus disease 2019 (COVID-19) pandemic has led to a massive rise in survey-based research. The paucity of perspicuous guidelines for conducting surveys may pose a challenge to the conduct of ethical, valid and meticulous research. The aim of this paper is to guide authors aiming to publish in scholarly journals regarding the methods and means to carry out surveys for valid outcomes. The paper outlines the various aspects, from planning, execution and dissemination of surveys followed by the data analysis and choosing target journals. While providing a comprehensive understanding of the scenarios most conducive to carrying out a survey, the role of ethical approval, survey validation and pilot testing, this brief delves deeper into the survey designs, methods of dissemination, the ways to secure and maintain data anonymity, the various analytical approaches, the reporting techniques and the process of choosing the appropriate journal. Further, the authors analyze retracted survey-based studies and the reasons for the same. This review article intends to guide authors to improve the quality of survey-based research by describing the essential tools and means to do the same with the hope to improve the utility of such studies.

Graphical Abstract

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INTRODUCTION

Surveys are the principal method used to address topics that require individual self-report about beliefs, knowledge, attitudes, opinions or satisfaction, which cannot be assessed using other approaches. 1 This research method allows information to be collected by asking a set of questions on a specific topic to a subset of people and generalizing the results to a larger population. Assessment of opinions in a valid and reliable way require clear, structured and precise reporting of results. This is possible with a survey based out of a meticulous design, followed by validation and pilot testing. 2 The aim of this opinion piece is to provide practical advice to conduct survey-based research. It details the ethical and methodological aspects to be undertaken while performing a survey, the online platforms available for distributing survey, and the implications of survey-based research.

Survey-based research is a means to obtain quick data, and such studies are relatively easy to conduct and analyse, and are cost-effective (under a majority of the circumstances). 3 These are also one of the most convenient methods of obtaining data about rare diseases. 4 With major technological advancements and improved global interconnectivity, especially during the coronavirus disease 2019 (COVID-19) pandemic, surveys have surpassed other means of research due to their distinctive advantage of a wider reach, including respondents from various parts of the world having diverse cultures and geographically disparate locations. Moreover, survey-based research allows flexibility to the investigator and respondent alike. 5 While the investigator(s) may tailor the survey dates and duration as per their availability, the respondents are allowed the convenience of responding to the survey at ease, in the comfort of their homes, and at a time when they can answer the questions with greater focus and to the best of their abilities. 6 Respondent biases inherent to environmental stressors can be significantly reduced by this approach. 5 It also allows responses across time-zones, which may be a major impediment to other forms of research or data-collection. This allows distant placement of the investigator from the respondents.

Various digital tools are now available for designing surveys ( Table 1 ). 7 Most of these are free with separate premium paid options. The analysis of data can be made simpler and cleaning process almost obsolete by minimising open-ended answer choices. 8 Close-ended answers makes data collection and analysis efficient, by generating an excel which can be directly accessed and analysed. 9 Minimizing the number of questions and making all questions mandatory can further aid this process by bringing uniformity to the responses and analysis simpler. Surveys are arguably also the most engaging form of research, conditional to the skill of the investigator.

Q/t = questions per typeform, A/m = answers per month, Q/s = questions per survey, A/s = answers per survey, NA = not applicable, NPS = net promoter score.

Data protection laws now mandate anonymity while collecting data for most surveys, particularly when they are exempt from ethical review. 10 , 11 Anonymization has the potential to reduce (or at times even eliminate) social desirability bias which gains particular relevance when targeting responses from socially isolated or vulnerable communities (e.g. LGBTQ and low socio-economic strata communities) or minority groups (religious, ethnic and medical) or controversial topics (drug abuse, using language editing software).

Moreover, surveys could be the primary methodology to explore a hypothesis until it evolves into a more sophisticated and partly validated idea after which it can be probed further in a systematic and structured manner using other research methods.

The aim of this paper is to reduce the incorrect reporting of surveys. The paper also intends to inform researchers of the various aspects of survey-based studies and the multiple points that need to be taken under consideration while conducting survey-based research.

SURVEYS IN THE COVID-19 PANDEMIC

The COVID-19 has led to a distinctive rise in survey-based research. 12 The need to socially distance amid widespread lockdowns reduced patient visits to the hospital and brought most other forms of research to a standstill in the early pandemic period. A large number of level-3 bio-safety laboratories are being engaged for research pertaining to COVID-19, thereby limiting the options to conduct laboratory-based research. 13 , 14 Therefore, surveys appear to be the most viable option for researchers to explore hypotheses related to the situation and its impact in such times. 15

LIMITATIONS WHILE CONDUCTING SURVEY-BASED RESEARCH

Designing a fine survey is an arduous task and requires skill even though clear guidelines are available in regard to the same. Survey design requires extensive thoughtfulness on the core questions (based on the hypothesis or the primary research question), with consideration of all possible answers, and the inclusion of open-ended options to allow recording other possibilities. A survey should be robust, in regard to the questions gathered and the answer choices available, it must be validated, and pilot tested. 16 The survey design may be supplanted with answer choices tailored for the convenience of the responder, to reduce the effort while making it more engaging. Survey dissemination and engagement of respondents also requires experience and skill. 17

Furthermore, the absence of an interviewer prevents us from gaining clarification on responses of open-ended questions if any. Internet surveys are also prone to survey fraud by erroneous reporting. Hence, anonymity of surveys is a boon and a bane. The sample sizes are skewed as it lacks representation of population absent on the Internet like the senile or the underprivileged. The illiterate population also lacks representation in survey-based research.

The “Enhancing the QUAlity and Transparency Of health Research” network (EQUATOR) provides two separate guidelines replete with checklists to ensure valid reporting of e-survey methodology. These include “The Checklist for Reporting Results of Internet E-Surveys” (CHERRIES) statement and “ The Journal of Medical Internet Research ” (JMIR) checklist.

COMMON TYPES OF SURVEY-BASED RESEARCH

From a clinician's standpoint, the common survey types include those centered around problems faced by the patients or physicians. 18 Surveys collecting the opinions of various clinicians on a debated clinical topic or feedback forms typically served after attending medical conferences or prescribing a new drug or trying a new method for a given procedure are also surveys. The formulation of clinical practice guidelines entails Delphi exercises using paper surveys, which are yet another form of survey-mediated research.

Size of the survey depends on its intent. They could be large or small surveys. Therefore, identification of the intent behind the survey is essential to allow the investigator to form a hypothesis and then explore it further. Large population-based or provider-based surveys are often done and generate mammoth data over the years. E.g. The National Health and Nutrition Examination Survey, The National Health Interview Survey and the National Ambulatory Medical Care Survey.

SCENARIOS FOR CONDUCTING SURVEY-BASED RESEARCH

Despite all said and done about the convenience of conducting survey-based research, it is prudent to conduct a feasibility check before embarking on one. Certain scenarios may be the key determinants in determining the fate of survey-based research ( Table 2 ).

ETHICS APPROVAL FOR SURVEY-BASED RESEARCH

Approval from the Institutional Review Board should be taken as per requirement according to the CHERRIES checklist. However, rules for approval are different as per the country or nation and therefore, local rules must be checked and followed. For instance, in India, the Indian Council of Medical Research released an article in 2017, stating that the concept of broad consent has been updated which is defined “consent for an unspecified range of future research subject to a few contents and/or process restrictions.” It talks about “the flexibility of Indian ethics committees to review a multicentric study proposal for research involving low or minimal risk, survey or studies using anonymized samples or data or low or minimal risk public health research.” The reporting of approvals received and applied for and the procedure of written, informed consent followed must be clear and transparent. 10 , 19

The use of incentives in surveys is also an ethical concern. 20 The different of incentives that can be used are monetary or non-monetary. Monetary incentives are usually discouraged as these may attract the wrong population due to the temptation of the monetary benefit. However, monetary incentives have been seen to make survey receive greater traction even though this is yet to proven. Monetary incentives are not only provided in terms of cash or cheque but also in the form of free articles, discount coupons, phone cards, e-money or cashback value. 21 These methods though tempting must be seldom used. If used, their use must be disclosed and justified in the report. The use of non-monetary incentives like a meeting with a famous personality or access to restricted and authorized areas. These can also help pique the interest of the respondents.

DESIGNING A SURVEY

As mentioned earlier, the design of a survey is reflective of the skill of the investigator curating it. 22 Survey builders can be used to design an efficient survey. These offer majority of the basic features needed to construct a survey, free of charge. Therefore, surveys can be designed from scratch, using pre-designed templates or by using previous survey designs as inspiration. Taking surveys could be made convenient by using the various aids available ( Table 1 ). Moreover, even the investigator should be mindful of the unintended response effects of ordering and context of survey questions. 23

Surveys using clear, unambiguous, simple and well-articulated language record precise answers. 24 A well-designed survey accounts for the culture, language and convenience of the target demographic. The age, region, country and occupation of the target population is also considered before constructing a survey. Consistency is maintained in the terms used in the survey and abbreviations are avoided to allow the respondents to have a clear understanding of the question being answered. Universal abbreviations or previously indexed abbreviations maintain the unambiguity of the survey.

Surveys beginning with broad, easy and non-specific questions as compared to sensitive, tedious and non-specific ones receive more accurate and complete answers. 25 Questionnaires designed such that the relatively tedious and long questions requiring the respondent to do some nit-picking are placed at the end improves the response rate of the survey. This prevents the respondent to be discouraged to answer the survey at the beginning itself and motivates the respondent to finish the survey at the end. All questions must provide a non-response option and all questions should be made mandatory to increase completeness of the survey. Questions can be framed in close-ended or open-ended fashion. However, close-ended questions are easier to analyze and are less tedious to answer by the respondent and therefore must be the main component in a survey. Open-ended questions have minimal use as they are tedious, take time to answer and require fine articulation of one's thoughts. Also, their minimal use is advocated because the interpretation of such answers requires dedication in terms of time and energy due to the diverse nature of the responses which is difficult to promise owing to the large sample sizes. 26 However, whenever the closed choices do not cover all probabilities, an open answer choice must be added. 27 , 28

Screening questions to meet certain criteria to gain access to the survey in cases where inclusion criteria need to be established to maintain authenticity of target demographic. Similarly, logic function can be used to apply an exclusion. This allows clean and clear record of responses and makes the job of an investigator easier. The respondents can or cannot have the option to return to the previous page or question to alter their answer as per the investigator's preference.

The range of responses received can be reduced in case of questions directed towards the feelings or opinions of people by using slider scales, or a Likert scale. 29 , 30 In questions having multiple answers, check boxes are efficient. When a large number of answers are possible, dropdown menus reduce the arduousness. 31 Matrix scales can be used to answer questions requiring grading or having a similar range of answers for multiple conditions. Maximum respondent participation and complete survey responses can be ensured by reducing the survey time. Quiz mode or weighted modes allow the respondent to shuffle between questions and allows scoring of quizzes and can be used to complement other weighted scoring systems. 32 A flowchart depicting a survey construct is presented as Fig. 1 .

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Survey validation

Validation testing though tedious and meticulous, is worthy effort as the accuracy of a survey is determined by its validity. It is indicative of the of the sample of the survey and the specificity of the questions such that the data acquired is streamlined to answer the questions being posed or to determine a hypothesis. 33 , 34 Face validation determines the mannerism of construction of questions such that necessary data is collected. Content validation determines the relation of the topic being addressed and its related areas with the questions being asked. Internal validation makes sure that the questions being posed are directed towards the outcome of the survey. Finally, Test – retest validation determines the stability of questions over a period of time by testing the questionnaire twice and maintaining a time interval between the two tests. For surveys determining knowledge of respondents pertaining to a certain subject, it is advised to have a panel of experts for undertaking the validation process. 2 , 35

Reliability testing

If the questions in the survey are posed in a manner so as to elicit the same or similar response from the respondents irrespective of the language or construction of the question, the survey is said to be reliable. It is thereby, a marker of the consistency of the survey. This stands to be of considerable importance in knowledge-based researches where recall ability is tested by making the survey available for answering by the same participants at regular intervals. It can also be used to maintain authenticity of the survey, by varying the construction of the questions.

Designing a cover letter

A cover letter is the primary means of communication with the respondent, with the intent to introduce the respondent to the survey. A cover letter should include the purpose of the survey, details of those who are conducting it, including contact details in case clarifications are desired. It should also clearly depict the action required by the respondent. Data anonymization may be crucial to many respondents and is their right. This should be respected in a clear description of the data handling process while disseminating the survey. A good cover letter is the key to building trust with the respondent population and can be the forerunner to better response rates. Imparting a sense of purpose is vital to ideationally incentivize the respondent population. 36 , 37 Adding the credentials of the team conducting the survey may further aid the process. It is seen that an advance intimation of the survey prepares the respondents while improving their compliance.

The design of a cover letter needs much attention. It should be captivating, clear, precise and use a vocabulary and language specific to the target population for the survey. Active voice should be used to make a greater impact. Crowding of the details must be avoided. Using italics, bold fonts or underlining may be used to highlight critical information. the tone ought to be polite, respectful, and grateful in advance. The use of capital letters is at best avoided, as it is surrogate for shouting in verbal speech and may impart a bad taste.

The dates of the survey may be intimated, so the respondents may prepare themselves for taking it at a time conducive to them. While, emailing a closed group in a convenience sampled survey, using the name of the addressee may impart a customized experience and enhance trust building and possibly compliance. Appropriate use of salutations like Mr./Ms./Mrs. may be considered. Various portals such as SurveyMonkey allow the researchers to save an address list on the website. These may then be reached out using an embedded survey link from a verified email address to minimize bouncing back of emails.

The body of the cover letter must be short, crisp and not exceed 2–3 paragraphs under idea circumstances. Ernest efforts to protect confidentiality may go a long way in enhancing response rates. 38 While it is enticing to provide incentives to enhance response, these are best avoided. 38 , 39 In cases when indirect incentives are offered, such as provision of results of the survey, these may be clearly stated in the cover letter. Lastly, a formal closing note with the signatures of the lead investigator are welcome. 38 , 40

Designing questions

Well-constructed questionnaires are essentially the backbone of successful survey-based studies. With this type of research, the primary concern is the adequate promotion and dissemination of the questionnaire to the target population. The careful of selection of sample population, therefore, needs to be with minimal flaws. The method of conducting survey is an essential determinant of the response rate observed. 41 Broadly, surveys are of two types: closed and open. Depending on the sample population the method of conducting the survey must be determined.

Various doctors use their own patients as the target demographic, as it improves compliance. However, this is effective in surveys aiming towards a geographically specific, fairly common disease as the sample size needs to be adequate. Response bias can be identified by the data collected from respondent and non-respondent groups. 42 , 43 Therefore, to choose a target population whose database of baseline characteristics is already known is more efficacious. In cases of surveys focused on patients having a rare group of diseases, online surveys or e-surveys can be conducted. Data can also be gathered from the multiple national organizations and societies all over the world. 44 , 45 Computer generated random selection can be done from this data to choose participants and they can be reached out to using emails or social media platforms like WhatsApp and LinkedIn. In both these scenarios, closed questionnaires can be conducted. These have restricted access either through a URL link or through e-mail.

In surveys targeting an issue faced by a larger demographic (e.g. pandemics like the COVID-19, flu vaccines and socio-political scenarios), open surveys seem like the more viable option as they can be easily accessed by majority of the public and ensures large number of responses, thereby increasing the accuracy of the study. Survey length should be optimal to avoid poor response rates. 25 , 46

SURVEY DISSEMINATION

Uniform distribution of the survey ensures equitable opportunity to the entire target population to access the questionnaire and participate in it. While deciding the target demographic communities should be studied and the process of “lurking” is sometimes practiced. Multiple sampling methods are available ( Fig. 1 ). 47

Distribution of survey to the target demographic could be done using emails. Even though e-mails reach a large proportion of the target population, an unknown sender could be blocked, making the use of personal or a previously used email preferable for correspondence. Adding a cover letter along with the invite adds a personal touch and is hence, advisable. Some platforms allow the sender to link the survey portal with the sender's email after verifying it. Noteworthily, despite repeated email reminders, personal communication over the phone or instant messaging improved responses in the authors' experience. 48 , 49

Distribution of the survey over other social media platforms (SMPs, namely WhatsApp, Facebook, Instagram, Twitter, LinkedIn etc.) is also practiced. 50 , 51 , 52 Surveys distributed on every available platform ensures maximal outreach. 53 Other smartphone apps can also be used for wider survey dissemination. 50 , 54 It is important to be mindful of the target population while choosing the platform for dissemination of the survey as some SMPs such as WhatsApp are more popular in India, while others like WeChat are used more widely in China, and similarly Facebook among the European population. Professional accounts or popular social accounts can be used to promote and increase the outreach for a survey. 55 Incentives such as internet giveaways or meet and greets with their favorite social media influencer have been used to motivate people to participate.

However, social-media platforms do not allow calculation of the denominator of the target population, resulting in inability to gather the accurate response rate. Moreover, this method of collecting data may result in a respondent bias inherent to a community that has a greater online presence. 43 The inability to gather the demographics of the non-respondents (in a bid to identify and prove that they were no different from respondents) can be another challenge in convenience sampling, unlike in cohort-based studies.

Lastly, manually filling of surveys, over the telephone, by narrating the questions and answer choices to the respondents is used as the last-ditch resort to achieve a high desired response rate. 56 Studies reveal that surveys released on Mondays, Fridays, and Sundays receive more traction. Also, reminders set at regular intervals of time help receive more responses. Data collection can be improved in collaborative research by syncing surveys to fill out electronic case record forms. 57 , 58 , 59

Data anonymity refers to the protection of data received as a part of the survey. This data must be stored and handled in accordance with the patient privacy rights/privacy protection laws in reference to surveys. Ethically, the data must be received on a single source file handled by one individual. Sharing or publishing this data on any public platform is considered a breach of the patient's privacy. 11 In convenience sampled surveys conducted by e-mailing a predesignated group, the emails shall remain confidential, as inadvertent sharing of these as supplementary data in the manuscript may amount to a violation of the ethical standards. 60 A completely anonymized e-survey discourages collection of Internet protocol addresses in addition to other patient details such as names and emails.

Data anonymity gives the respondent the confidence to be candid and answer the survey without inhibitions. This is especially apparent in minority groups or communities facing societal bias (sex workers, transgenders, lower caste communities, women). Data anonymity aids in giving the respondents/participants respite regarding their privacy. As the respondents play a primary role in data collection, data anonymity plays a vital role in survey-based research.

DATA HANDLING OF SURVEYS

The data collected from the survey responses are compiled in a .xls, .csv or .xlxs format by the survey tool itself. The data can be viewed during the survey duration or after its completion. To ensure data anonymity, minimal number of people should have access to these results. The data should then be sifted through to invalidate false, incorrect or incomplete data. The relevant and complete data should then be analyzed qualitatively and quantitatively, as per the aim of the study. Statistical aids like pie charts, graphs and data tables can be used to report relative data.

ANALYSIS OF SURVEY DATA

Analysis of the responses recorded is done after the time made available to answer the survey is complete. This ensures that statistical and hypothetical conclusions are established after careful study of the entire database. Incomplete and complete answers can be used to make analysis conditional on the study. Survey-based studies require careful consideration of various aspects of the survey such as the time required to complete the survey. 61 Cut-off points in the time frame allow authentic answers to be recorded and analyzed as compared to disingenuous completed questionnaires. Methods of handling incomplete questionnaires and atypical timestamps must be pre-decided to maintain consistency. Since, surveys are the only way to reach people especially during the COVID-19 pandemic, disingenuous survey practices must not be followed as these will later be used to form a preliminary hypothesis.

REPORTING SURVEY-BASED RESEARCH

Reporting the survey-based research is by far the most challenging part of this method. A well-reported survey-based study is a comprehensive report covering all the aspects of conducting a survey-based research.

The design of the survey mentioning the target demographic, sample size, language, type, methodology of the survey and the inclusion-exclusion criteria followed comprises a descriptive report of a survey-based study. Details regarding the conduction of pilot-testing, validation testing, reliability testing and user-interface testing add value to the report and supports the data and analysis. Measures taken to prevent bias and ensure consistency and precision are key inclusions in a report. The report usually mentions approvals received, if any, along with the written, informed, consent taken from the participants to use the data received for research purposes. It also gives detailed accounts of the different distribution and promotional methods followed.

A detailed account of the data input and collection methods along with tools used to maintain the anonymity of the participants and the steps taken to ensure singular participation from individual respondents indicate a well-structured report. Descriptive information of the website used, visitors received and the externally influencing factors of the survey is included. Detailed reporting of the post-survey analysis including the number of analysts involved, data cleaning required, if any, statistical analysis done and the probable hypothesis concluded is a key feature of a well-reported survey-based research. Methods used to do statistical corrections, if used, should be included in the report. The EQUATOR network has two checklists, “The Checklist for Reporting Results of Internet E-Surveys” (CHERRIES) statement and “ The Journal of Medical Internet Research ” (JMIR) checklist, that can be utilized to construct a well-framed report. 62 , 63 Importantly, self-reporting of biases and errors avoids the carrying forward of false hypothesis as a basis of more advanced research. References should be cited using standard recommendations, and guided by the journal specifications. 64

CHOOSING A TARGET JOURNAL FOR SURVEY-BASED RESEARCH

Surveys can be published as original articles, brief reports or as a letter to the editor. Interestingly, most modern journals do not actively make mention of surveys in the instructions to the author. Thus, depending on the study design, the authors may choose the article category, cohort or case-control interview or survey-based study. It is prudent to mention the type of study in the title. Titles albeit not too long, should not exceed 10–12 words, and may feature the type of study design for clarity after a semicolon for greater citation potential.

While the choice of journal is largely based on the study subject and left to the authors discretion, it may be worthwhile exploring trends in a journal archive before proceeding with submission. 65 Although the article format is similar across most journals, specific rules relevant to the target journal may be followed for drafting the article structure before submission.

RETRACTION OF ARTICLES

Articles that are removed from the publication after being released are retracted articles. These are usually retracted when new discrepancies come to light regarding, the methodology followed, plagiarism, incorrect statistical analysis, inappropriate authorship, fake peer review, fake reporting and such. 66 A sufficient increase in such papers has been noticed. 67

We carried out a search of “surveys” on Retraction Watch on 31st August 2020 and received 81 search results published between November 2006 to June 2020, out of which 3 were repeated. Out of the 78 results, 37 (47.4%) articles were surveys, 23 (29.4%) showed as unknown types and 18 (23.2%) reported other types of research. ( Supplementary Table 1 ). Fig. 2 gives a detailed description of the causes of retraction of the surveys we found and its geographic distribution.

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A good survey ought to be designed with a clear objective, the design being precise and focused with close-ended questions and all probabilities included. Use of rating scales, multiple choice questions and checkboxes and maintaining a logical question sequence engages the respondent while simplifying data entry and analysis for the investigator. Conducting pilot-testing is vital to identify and rectify deficiencies in the survey design and answer choices. The target demographic should be defined well, and invitations sent accordingly, with periodic reminders as appropriate. While reporting the survey, maintaining transparency in the methods employed and clearly stating the shortcomings and biases to prevent advocating an invalid hypothesis.

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

Author Contributions:

Conceptualization: Gaur PS, Zimba O, Agarwal V, Gupta L.
Visualization: Gaur PS, Zimba O, Agarwal V, Gupta L.
Writing - original draft: Gaur PS, Gupta L.

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Survey Research – Step-by-Step Guide

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Survey research is the method used in data collection from a specific group of people to gain insight into topics of interest. This method involves asking the predefined group of people questions on one or several issues. The following blog contains FAQs about survey research, step-by-step guide on how to conduct a survey and tips that provide you with insight on how an excellent investigation should look like.

Inhaltsverzeichnis

1 Survey Research – FAQ
2 Survey Research: Definition
3 Survey Research: Step-by-Step Guide
4 Five tips for a good Survey Research
5 In a Nutshell

Survey Research – FAQ

Answering the most common questions that students ask about research will help you gain a better understanding of survey research. Some of these questions include:

What are the types of Survey Research?

The diverse types of surveys are categorised according to the method of deployment. This means that the types of survey are named according to how the information is gotten. They include online, paper, telephonic and one-on-one surveys.

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What are the advantages of Survey Research?

Survey research provides some benefits over other types of surveys. Some of these advantages include the following:

They are relatively easy to conduct
Saves time than other methods of data collection
Although the cost is dictated by the method of performance, they are generally cost-effective
Can be performed remotely via online platforms
Ideal for collecting data from a large number of respondents
Provides extensive flexibility by allowing numerous questions to be asked about one or several subjects
A standard survey has very few chances of errors
A broad range of data can be collected regarding various aspects of life including beliefs, behaviour and opinions
Advanced statistical techniques can be used to analyse data thanks to surveying software

What are the two main characteristics of Survey Research?

The two main characteristics of the survey include variables of interest and samples. These are explained as follows:

Variable of Interest : In essence, the variable of interest is the main subject a researcher wants information about and the questions. When asking the questions, the surveyor asks the respondents to report their thoughts, behaviours, beliefs, and feelings.
Samples : Sampling is the action of selecting a subset of elements from a finite population to deduce the results obtained from the research to the readers. The main goal of sampling is to reduce survey costs.

How long should my Survey Research be?

While it’s recommended that you obtain all the relevant information about your target, you should not tire your respondents with too many questions. You ought to ask specific questions that are right on target and will influence the respondents to open up. Ideally, your survey research should have about 20 questions, which will take just five minutes of the respondents’ time. Also, your questions should be clear, concise, and short to ensure that anyone with an 8th-grade reading level can understand and answer your questions.

How long do Survey Research typically take to administer?

Typical survey research can take between two to ten days to be complete. Some of the issues that contribute to the varying duration include:

The sample size
Number of questions in the survey
The target audience
Percentage of the respondents who met your requirements

Survey Research: Definition

This type of study is defined as the process of researching a particular subject through the use of questions. The information collected from the research is consequently analysed to derive a conclusive meaning over the research. Survey research has multiple purposes and can be conducted through several methods depending on the goal of the researcher.

Survey Research: Step-by-Step Guide

As a student, you need to conduct a survey when asked by your professor or when your subject of study demands survey research. The following is a step-by-step guide that will help you perform the study efficiently.

Determine the Purpose of your Survey

The first step in every survey research is to determine a subject of interest. Depending on your research question , you need to identify the target respondents of your survey. This means that you ought to target the specific a specific group of people. This may include college students or customers who frequent a particular mall. Your survey should be generalised to the target audience and should define precisely who you need to get conclusions about.

Create a List of Questions

Survey research can include several types of questions, which include matrix table questions, single or multi-response questions, as well as open and closed questions. In most cases, people like to take part in survey research that has short, concise questions. Ideally, when writing these questions, you need to use simple language and avoid double negations.

Invite Participants

There are numerous ways in which you can invite your correspondents. Depending on your type of survey research, you may send your target audience emails, design a burner, and post it on the school website or board or hand out questionnaires.

Gather your Response

You need to monitor and gather your response, as your final sample size will depend on the number of respondents who completed your survey. Ideally, you may increase the interest and number of participants by providing an incentive. This may include a gift for completion or a lottery.

Analysing the Results

After gathering all the data, you may create charts and graphs to provide a quick reference to your results. You may also utilise text analysis as well as a word cloud on open-ended questions, which will help you pinpoint the common response trends in your survey research. If you are using an online survey, the data will be saved automatically, which means that you can analyse your results right away.

As mentioned earlier, problem-solving can also be viewed as art. Depending on your skill level, you will find that there are numerous ways of laying out a given task. Applying some elegance to this process guarantees that even the uninformed reader will understand what it is that you are trying to do. Furthermore, a problem that has been broken down into constituent sections always appears simple.

Writing a Report

The result you get from your analysis will come in handy in writing a concluding report. This report is meant to explain your findings and state whether they have met your goals. The description should be short and conclusive of the entire data. A successful study should provide you with reliable answers to the subject in question, which should allow you to create a final report.

Five tips for a good Survey Research

Use the following tips to create an excellent survey research that will provide conclusive results.

Define its purpose from the get-go

Ensure that you have a clear objective with your study. The last thing you want is to end up with a set of results that have no real decision or direction.

Use concise and straightforward questions

Most people respond to questions that they can understand. A questionnaire with endless questions will automatically put off potential respondents.

Keep your Survey short and focused

It would help if you kept your study short to attract respondents and ensure completion

Provide an incentive to attract a significant number of responders

An incentive comes in handy in attracting people to respond to your survey and gives them a reason to help you out.

Utilise Response Scale

Response scales show the intensity of your attitude towards the subject in question, which helps provide in-depth feedback.

In a Nutshell

Conducting great survey research is an easy task that you should handle before completing your college or university education
An excellent survey research should provide you with reliable, transparent and actionable insight regarding your quest
The process is easy if you understand it and inexpensive to conduct
The results of a survey research study are essential as they can help you understand vita subjects in life

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Survey research

Affiliation.

1 Ann Arbor, Mich. From the Section of Plastic Surgery, Department of Surgery, The University of Michigan Medical Center; and Division of General Medicine, Department of Internal Medicine, University of Michigan.
PMID: 20885261
DOI: 10.1097/PRS.0b013e3181ea44f9

Survey research is a unique methodology that can provide insight into individuals' perspectives and experiences and can be collected on a large population-based sample. Specifically, in plastic surgery, survey research can provide patients and providers with accurate and reproducible information to assist with medical decision-making. When using survey methods in research, researchers should develop a conceptual model that explains the relationships of the independent and dependent variables. The items of the survey are of primary importance. Collected data are only useful if they accurately measure the concepts of interest. In addition, administration of the survey must follow basic principles to ensure an adequate response rate and representation of the intended target sample. In this article, the authors review some general concepts important for successful survey research and discuss the many advantages this methodology has for obtaining limitless amounts of valuable information.

Publication types

Research Support, Non-U.S. Gov't
Data Collection / methods*
Quality Control
Reproducibility of Results
Research Design
Surgery, Plastic*
Surveys and Questionnaires*
United States

Read our research on: Gun Policy | International Conflict | Election 2024

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Methodology, the american trends panel survey methodology.

The American Trends Panel (ATP), created by Pew Research Center, is a nationally representative panel of randomly selected U.S. adults. Panelists participate via self-administered web surveys. Panelists who do not have internet access at home are provided with a tablet and wireless internet connection. Interviews are conducted in both English and Spanish. The panel is being managed by Ipsos.

Data in this report is drawn from ATP Wave 143, conducted from Feb. 13 to 25, 2024. A total of 12,693 panelists responded out of 14,762 who were sampled, for a response rate of 89% (AAPOR RR3). The survey includes an oversample of 2,051 Jewish and Muslim Americans from Ipsos’ KnowledgePanel, SSRS’s Opinion Panel, and NORC at the University of Chicago’s AmeriSpeak Panel. These oversampled groups are weighted to reflect their correct proportions in the population. The cumulative response rate accounting for nonresponse to the recruitment surveys and attrition is 4%. The break-off rate among panelists who logged on to the survey and completed at least one item is less than 1%. The margin of sampling error for the full sample of 12,693 respondents is plus or minus 1.5 percentage points.

ATP Panel recruitment

The ATP was created in 2014, with the first cohort of panelists invited to join the panel at the end of a large, national, landline and cellphone random-digit-dial survey that was conducted in both English and Spanish. Two additional recruitments were conducted using the same method in 2015 and 2017, respectively. Across these three surveys, a total of 19,718 adults were invited to join the ATP, of whom 9,942 (50%) agreed to participate.

In August 2018, the ATP switched from telephone to address-based sampling (ABS) recruitment. A study cover letter and a pre-incentive are mailed to a stratified, random sample of households selected from the U.S. Postal Service’s Delivery Sequence File. This Postal Service file has been estimated to cover as much as 98% of the population, although some studies suggest that the coverage could be in the low 90% range. 5 Within each sampled household, the adult with the next birthday is asked to participate. Other details of the ABS recruitment protocol have changed over time but are available upon request. 6

Table shows American Trends Panel recruitment surveys

We have recruited a national sample of U.S. adults to the ATP approximately once per year since 2014. In some years, the recruitment has included additional efforts (known as an “oversample”) to boost sample size with underrepresented groups. For example, Hispanic, Black and Asian adults were oversampled in 2019, 2022 and 2023, respectively.

Across the six address-based recruitments, a total of 23,862 adults were invited to join the ATP, of whom 20,917 agreed to join the panel and completed an initial profile survey. Of the 30,859 individuals who have ever joined the ATP, 11,920 remained active panelists and continued to receive survey invitations at the time this survey was conducted.

The American Trends Panel never uses breakout routers or chains that direct respondents to additional surveys.

Sample design

The overall target population for this survey was noninstitutionalized persons ages 18 and older living in the U.S., including Alaska and Hawaii. All active panel members who completed the ATP wave which fielded from July 31 to Aug. 6, 2023 (ATP W132), or panelists who previously identified as Jewish or Muslim, were invited to participate in this wave.

The ATP was supplemented with an oversample of self-identified Jewish and Muslim American panelists from three other probability panels: Ipsos’ KnowledgePanel, SSRS’s Opinion Panel, and NORC at the University of Chicago’s AmeriSpeak panel. All panelists who met the selection criteria were selected with certainty.

Questionnaire development and testing

The questionnaire was developed by Pew Research Center in consultation with Ipsos, SSRS and NORC. The survey for ATP and KP panelists was programmed by Ipsos, while the survey for SSRS and NORC panelists was programmed by SSRS. A small number of SSRS panelists took their survey over the phone with an interviewer. Both web programs were rigorously tested on both PC and mobile devices by the Ipsos, SSRS and NORC project management teams and Pew Research Center researchers. The Ipsos project management team also populated test data that was analyzed in SPSS to ensure the logic and randomizations were working as intended before launching the survey.

All ATP respondents were offered a post-paid incentive for their participation. Respondents could choose to receive the post-paid incentive in the form of a check or a gift code to Amazon.com or could choose to decline the incentive. Incentive amounts ranged from $5 to $20 depending on whether the respondent belongs to a part of the population that is harder or easier to reach. Differential incentive amounts were designed to increase panel survey participation among groups that traditionally have low survey response propensities.

Respondents from the Ipsos KnowledgePanel, SSRS Opinion Panel and AmeriSpeak were offered the cash equivalent of $10 for completing this survey.

Data collection protocol

The data collection field period for this survey was Feb. 13 to 25, 2024. Postcard notifications were mailed to a subset of ATP panelists with a known residential address on Feb. 12. 7

Invitations were sent out in separate launches. Sixty ATP panelists and 300 KP panelists were included in the soft launch, which began with an initial invitation sent on Feb. 13. The ATP and KP panelists chosen for the soft launch were known responders who had completed previous surveys within one day of receiving their invitation. All remaining ATP and KP sampled panelists were included in the full launch and were sent an invitation on Feb. 14.

Table shows Invitation and reminder dates, ATP Wave 143

Overall, 129 SSRS panelists were included in the SSRS soft launch, which began with an initial invitation on Feb. 14. And 110 NORC panelists were included in the NORC soft launch, which began with an initial invitation on Feb. 15. All remaining SSRS and NORC sampled panelists were included together in the full launch and were sent an invitation on Feb. 15.

All panelists with an email address received an email invitation and up to four email reminders if they did not respond to the survey. All ATP panelists who consented to SMS messages received an SMS invitation and up to four SMS reminders.

Data quality checks

To ensure high-quality data, the Center’s researchers performed data quality checks to identify any respondents showing clear patterns of satisficing. This includes checking for whether respondents left questions blank at very high rates or always selected the first or last answer presented. As a result of this checking, six ATP respondents were removed from the survey dataset prior to weighting and analysis.

Table shows American Trends Panel weighting dimensions

The data was weighted in a multistep process that accounts for multiple stages of sampling and nonresponse that occur at different points in the survey process. First, each panelist begins with a base weight that reflects their probability of inclusion in the panel to which they belong. Separately for each of the four panels (ATP, KP, SSRS, NORC), the base weights for Muslim and Jewish respondents were scaled to be proportional to the group’s effective sample size. These weights were then combined and calibrated so that the overall proportions of Jewish and Muslim respondents respectively match the National Public Opinion Reference Survey (NPORS) benchmark.

This weight is then calibrated again to align with the full set of population benchmarks identified in the accompanying table (which also includes the NPORS benchmarks for the shares of Jewish and Muslim adults). In order to reduce the loss in precision stemming from variance in the weights, the weights were trimmed separately among Jewish, Muslim, Hispanic, non-Hispanic Black, and non-Hispanic Asian respondents at the 98th percentile, and among all other respondents at the 99.5th percentile. Sampling errors and tests of statistical significance take into account the effect of weighting.

The following table shows the unweighted sample sizes and the error attributable to sampling that would be expected at the 95% level of confidence for different groups in the survey.

Table shows Sample sizes and margins of error, ATP Wave 143

Sample sizes and sampling errors for other subgroups are available upon request. In addition to sampling error, one should bear in mind that question wording and practical difficulties in conducting surveys can introduce error or bias into the findings of opinion polls.

Dispositions and response rates

Table shows Final dispositions, ATP Wave 143

AAPOR Task Force on Address-based Sampling. 2016. “AAPOR Report: Address-based Sampling.” ↩
Email [email protected] . ↩
Postcard notifications are sent to 1) panelists who have been provided with a tablet to take ATP surveys, 2) panelists who were recruited within the last two years, and 3) panelists recruited prior to the last two years who opt to continue receiving postcard notifications. ↩

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Table of contents, younger americans stand out in their views of the israel-hamas war, how u.s. muslims are experiencing the israel-hamas war, how u.s. jews are experiencing the israel-hamas war, majority in u.s. say israel has valid reasons for fighting; fewer say the same about hamas, how americans view the conflicts between russia and ukraine, israel and hamas, and china and taiwan, most popular.

About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .

COMMENTS

Survey Research
Survey research means collecting information about a group of people by asking them questions and analyzing 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.
Understanding and Evaluating Survey Research
Survey research is defined as "the collection of information from a sample of individuals through their responses to questions" ( Check & Schutt, 2012, p. 160 ). This type of research allows for a variety of methods to recruit participants, collect data, and utilize various methods of instrumentation. Survey research can use quantitative ...
(PDF) Understanding and Evaluating Survey Research
Survey research is deﬁned as. "the collection of information from. a sample of individuals through their. responses to questions" (Check &. Schutt, 2012, p. 160). This type of r e -. search ...
PDF Survey Research
Survey research is a specific type of field study that in- volves the collection of data from a sample of ele- ments (e.g., adult women) drawn from a well-defined population (e.g., all adult women living in the United States) through the use of a questionnaire (for more lengthy discussions, see Babbie, 1990; Fowler, 1988; ...
Survey Research: Definition, Examples and Methods
Survey Research Definition. Survey Research is defined as the process of conducting research using surveys that researchers send to survey respondents. The data collected from surveys is then statistically analyzed to draw meaningful research conclusions. In the 21st century, every organization's eager to understand what their customers think ...
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Survey Research. Definition: Survey Research is a quantitative research method that involves collecting standardized data from a sample of individuals or groups through the use of structured questionnaires or interviews. The data collected is then analyzed statistically to identify patterns and relationships between variables, and to draw conclusions about the population being studied.
Survey Research
Survey research is a popular and powerful means by which to study people and organizations in society. It consists of a rich set of techniques used to obtain information about individual attitudes, values, behaviors, opinions, knowledge, and circumstances. Surveys are also used to study organizations and institutions, for example, assessing ...
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3.3 The Importance of Survey Research in the Social Sciences and Beyond. Survey research is one of the pillars in social science research in the twenty-first century. Surveys are used to measure almost everything from voting behavior to public opinion and to sexual preferences (De Leeuw et al. 2008: 1).
Doing Survey Research
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.
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A review of survey scale types and important definitions and concepts related to survey research is included. A sample conceptual framework that can be used to link research questions, relevant ...
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The heart of any survey research project is the survey itself. Although it is easy to think of interesting questions to ask people, constructing a good survey is not easy at all. The problem is that the answers people give can be influenced in unintended ways by the wording of the items, the order of the items, the response options provided ...
Survey Research: Definition, Examples & Methods
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.
PDF Fundamentals of Survey Research Methodology
The survey is then constructed to test this model against observations of the phenomena. In contrast to survey research, a . survey. is simply a data collection tool for carrying out survey research. Pinsonneault and Kraemer (1993) defined a survey as a "means for gathering information about the characteristics, actions, or opinions of a ...
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Survey Research: Definition, Design, Methods and Examples
Survey research is a quantitative research method that involves collecting data from a sample of individuals using standardized questionnaires or surveys. The goal of survey research is to measure the attitudes, opinions, behaviors, and characteristics of a target population. Surveys can be conducted through various means, including phone, mail ...
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Develop knowledge that is otherwise unavailable by developing an effective survey. Surveys are a series of questions, which are usually presented in questionnaire format. Surveys can be distributed face-to-face, over the phone, or over the Internet. Developing, Designing, and Distributing Surveys Surveys are usually developed to obtain information that is otherwise unavailable. For example ...
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Abstract. The coronavirus disease 2019 (COVID-19) pandemic has led to a massive rise in survey-based research. The paucity of perspicuous guidelines for conducting surveys may pose a challenge to the conduct of ethical, valid and meticulous research. The aim of this paper is to guide authors aiming to publish in scholarly journals regarding the ...
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Fowler is the author or co-author of four textbooks on survey methods, including Survey Research Methods, Improving Survey Questions, Standardized Survey Interviewing (with Mangione), and Survey Methodology (with Groves, Couper, Lepkowski, et. al), as well as numerous research papers and monographs. His recent work has focused on studies of ...
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The following is a step-by-step guide that will help you perform the study efficiently. Determine the Purpose of your Survey. The first step in every survey research is to determine a subject of interest. Depending on your research question, you need to identify the target respondents of your survey. This means that you ought to target the ...
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Surveys provide evidence for the social sciences for knowledge, attitudes, and other behaviors, and, in health care, to quantify qualitative research and to assist in policymaking. A survey-designed research project is about asking questions of individuals, and, from the answers, the researcher can generalize the findings from a sample of ...
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Where Are Your Parents? Exploring Potential Bias in Administrative
This paper examines potential bias in the Census Household Composition Key's (CHCK) probabilistic parent-child linkages. By linking CHCK data to the American Community Survey (ACS), we reveal disparities in parent-child linkages among specific demographic groups and find that characteristics of children that can and cannot be linked to the CHCK vary considerably from the larger population.
Methodology
About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions.

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Survey Research – Types, Methods, Examples

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