survey research design types

A Comprehensive Guide to Survey Research Methodologies

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

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

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

What is Survey Research

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

Brief History of Survey Research

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

-       First Era (1930-1960)

-       Second Era (1960-1990)

-       Third Era (1990 onwards)

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

Survey Research Methods & Types

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

Surveys based on Objective

Exploratory survey research.

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

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

Predictive Survey Research

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

Descriptive Survey Research

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

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

Survey Research Types based on Concept Testing

Monadic concept testing.

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

Sequential Monadic Concept Testing

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

Based on Data Source

Primary data.

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

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

Secondary Data

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

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

Based on Research Method

Quantitative research.

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

Qualitative Research

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

Based on Deployment Method

Online surveys.

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

Paper or Print Surveys

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

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

Telephonic Surveys

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

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

One-on-one Surveys

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

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

Based on Distribution

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

Buy Survey Responses

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

Embedding Survey on a Website

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

Post the Survey on Social Media

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

Based on Frequency of Deployment

Cross-sectional studies.

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

Longitudinal Surveys

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

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

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

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

Retrospective Survey

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

Why Should You Conduct Research Surveys?

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

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

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

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

Common Uses of a Survey

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

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

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

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

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

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

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

6 Steps to Conduct Survey Research

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

Step 1: Objective of the Survey

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

Step 2: Number of Questions

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

Step 3: Language and Voice of Questions

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

Step 4: Type of Questions

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

Step 5: User Experience

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

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

Step 6: Survey Logic

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

How to Effectively Use Survey Research with Starlight Analytics

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

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

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

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

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• Survey Research: Types, Examples & Methods

Surveys have been proven to be one of the most effective methods of conducting research. They help you to gather relevant data from a large audience, which helps you to arrive at a valid and objective conclusion. 

Just like other research methods, survey research had to be conducted the right way to be effective. In this article, we’ll dive into the nitty-gritty of survey research and show you how to get the most out of it. 

What is Survey Research? 

Survey research is simply a systematic investigation conducted via a survey. In other words, it is a type of research carried out by administering surveys to respondents. 

Surveys already serve as a great method of opinion sampling and finding out what people think about different contexts and situations. Applying this to research means you can gather first-hand information from persons affected by specific contexts. 

Survey research proves useful in numerous primary research scenarios. Consider the case whereby a restaurant wants to gather feedback from its customers on its new signatory dish. A good way to do this is to conduct survey research on a defined customer demographic. 

By doing this, the restaurant is better able to gather primary data from the customers (respondents) with regards to what they think and feel about the new dish across multiple facets. This means they’d have more valid and objective information to work with. 

Why Conduct Survey Research?  

One of the strongest arguments for survey research is that it helps you gather the most authentic data sets in the systematic investigation. Survey research is a gateway to collecting specific information from defined respondents, first-hand.  

Surveys combine different question types that make it easy for you to collect numerous information from respondents. When you come across a questionnaire for survey research, you’re likely to see a neat blend of close-ended and open-ended questions, together with other survey response scale questions. 

Apart from what we’ve discussed so far, here are some other reasons why survey research is important: 

• It gives you insights into respondents’ behaviors and preferences which is valid in any systematic investigation.
• Many times, survey research is structured in an interactive manner which makes it easier for respondents to communicate their thoughts and experiences. 
• It allows you to gather important data that proves useful for product improvement; especially in market research. 

Characteristics of Survey Research

• Usage : Survey research is mostly deployed in the field of social science; especially to gather information about human behavior in different social contexts. 
• Systematic : Like other research methods, survey research is systematic. This means that it is usually conducted in line with empirical methods and follows specific processes.
• Replicable : In survey research, applying the same methods often translates to achieving similar results. 
• Types : Survey research can be conducted using forms (offline and online) or via structured, semi-structured, and unstructured interviews . 
• Data : The data gathered from survey research is mostly quantitative; although it can be qualitative. 
• Impartial Sampling : The data sample in survey research is random and not subject to unavoidable biases.
• Ecological Validity : Survey research often makes use of data samples obtained from real-world occurrences. 

Types of Survey Research

Survey research can be subdivided into different types based on its objectives, data source, and methodology. 

Types of Survey Research Based on Objective

• Exploratory Survey Research

Exploratory survey research is aimed at finding out more about the research context. Here, the survey research pays attention to discovering new ideas and insights about the research subject(s) or contexts. 

Exploratory survey research is usually made up of open-ended questions that allow respondents to fully communicate their thoughts and varying perspectives on the subject matter. In many cases, systematic investigation kicks off with an exploratory research survey. 

• Predictive Survey Research

This type of research is also referred to as causal survey research because it pays attention to the causative relationship between the variables in the survey research. In other words, predictive survey research pays attention to existing patterns to explain the relationship between two variables. 

It can also be referred to as conclusive research because it allows you to identify causal variables and resultant variables; that is cause and effect. Predictive variables allow you to determine the nature of the relationship between the causal variables and the effect to be predicted. 

• Descriptive Survey Research

Unlike predictive research, descriptive survey research is largely observational. It is ideal for quantitative research because it helps you to gather numeric data. 

The questions listed in descriptive survey research help you to uncover new insights into the actions, thoughts, and feelings of survey respondents. With this data, you can know the extent to which different conditions can be obtained among these subjects. 

Types of Survey Research Based on Data Source

• Secondary Data

Survey research can be designed to collect and process secondary data. Secondary data is a type of data that has been collected from primary sources in the past and is readily available for use. It is the type of data that is already existing.

Since secondary data is gathered from third-party sources, it is mostly generic, unlike primary data that is specific to the research context. Common sources of secondary data in survey research include books, data collected through other surveys, online data, data from government archives, and libraries. 

• Primary Data

This is the type of research data that is collected directly; that is, data collected from first-hand sources. Primary data is usually tailored to a specific research context so that reflects the aims and objectives of the systematic investigation.

One of the strongest points of primary data over its secondary counterpart is validity. Because it is collected directly from first-hand sources, primary data typically results in objective research findings. 

You can collect primary data via interviews, surveys, and questionnaires, and observation methods. 

Types of Survey Research Based on Methodology

• Quantitative Research

Quantitative research is a common research method that is used to gather numerical data in a systematic investigation. It is often deployed in research contexts that require statistical information to arrive at valid results such as in social science or science. 

For instance, as an organization looking to find out how many persons are using your product in a particular location, you can administer survey research to collect useful quantitative data. Other quantitative research methods include polls, face-to-face interviews, and systematic observation. 

• Qualitative Research

This is a method of systematic investigation that is used to collect non-numerical data from research participants. In other words, it is a research method that allows you to gather open-ended information from your target audience. 

Typically, organizations deploy qualitative research methods when they need to gather descriptive data from their customers; for example, when they need to collect customer feedback in product evaluation. Qualitative research methods include one-on-one interviews, observation, case studies, and focus groups. 

Survey Research Scales

• Nominal Scale

This is a type of survey research scale that uses numbers to label the different answer options in a survey. On a nominal scale , the numbers have no value in themselves; they simply serve as labels for qualitative variables in the survey. 

In cases where a nominal scale is used for identification, there is typically a specific one-on-one relationship between the numeric value and the variable it represents. On the other hand, when the variable is used for classification, then each number on the scale serves as a label or a tag. 

Examples of Nominal Scale in Survey Research 

1. How would you describe your complexion? 

2. Have you used this product?

• Ordinal Scale

This is a type of variable measurement scale that arranges answer options in a specific ranking order without necessarily indicating the degree of variation between these options. Ordinal data is qualitative and can be named, ranked, or grouped. 

In an ordinal scale , the different properties of the variables are relatively unknown, and it also identifies, describes, and shows the rank of the different variables. With an ordered scale, it is easier for researchers to measure the degree of agreement and/or disagreement with different variables. 

With ordinal scales, you can measure non-numerical attributes such as the degree of happiness, agreement, or opposition of respondents in specific contexts. Using an ordinal scale makes it easy for you to compare variables and process survey responses accordingly. 

Examples of Ordinal Scale in Survey Research

1. How often do you use this product?

• Prefer not to say

2. How much do you agree with our new policies? 

• Totally agree
• Somewhat agree
• Totally disagree
• Interval Scale

This is a type of survey scale that is used to measure variables existing at equal intervals along a common scale. In some way, it combines the attributes of nominal and ordinal scales since it is used where there is order and there is a meaningful difference between 2 variables. 

With an interval scale, you can quantify the difference in value between two variables in survey research. In addition to this, you can carry out other mathematical processes like calculating the mean and median of research variables. 

Examples of Interval Scale in Survey Research

1. Our customer support team was very effective. 

• Completely agree
• Neither agree nor disagree
• Somewhat disagree
• Completely disagree 

2. I enjoyed using this product.

Another example of an interval scale can be seen in the Net Promoter Score.

• Ratio Scale

Just like the interval scale, the ratio scale is quantitative and it is used when you need to compare intervals or differences in survey research. It is the highest level of measurement and it is made up of bits and pieces of the other survey scales. 

One of the unique features of the ratio scale is it has a true zero and equal intervals between the variables on the scale. This zero indicates an absence of the variable being measured by the scale. Common occurrences of ratio scales can be seen with distance (length), area, and population measurement. 

Examples of Ratio Scale in Survey Research

1. How old are you?

• Below 18 years
• 41 and above

2. How many times do you shop in a week?

• Less than twice
• Three times
• More than four times

Uses of Survey Research

• Health Surveys

Survey research is used by health practitioners to gather useful data from patients in different medical and safety contexts. It helps you to gather primary and secondary data about medical conditions and risk factors of multiple diseases and infections. 

In addition to this, administering health surveys regularly helps you to monitor the overall health status of your population; whether in the workplace, school, or community. This kind of data can be used to help prevent outbreaks and minimize medical emergencies in these contexts. 

Survey research is also useful when conducting polls; whether online or offline. A poll is a data collection tool that helps you to gather public opinion about a particular subject from a well-defined research sample.

By administering survey research, you can gather valid data from a well-defined research sample, and utilize research findings for decision making. For example, during elections, individuals can be asked to choose their preferred leader via questionnaires administered as part of survey research.

• Customer Satisfaction

Customer satisfaction is one of the cores of every organization as it is directly concerned with how well your product or service meets the needs of your clients. Survey research is an effective way to measure customer satisfaction at different intervals. 

As a restaurant, for example, you can send out online surveys to customers immediately when they patronize your business. In these surveys, encourage them to provide feedback on their experience and to provide information on how your service delivery can be improved. 

Survey research makes data collection and analysis easy during a census. With an online survey tool like Formplus , you can seamlessly gather data during a census without moving from a spot. Formplus has multiple sharing options that help you collect information without stress. 

Survey Research Methods

Survey research can be done using different online and offline methods. Let’s examine a few of them here.

• Telephone Surveys

This is a means of conducting survey research via phone calls. In a telephone survey, the researcher places a call to the survey respondents and gathers information from them by asking questions about the research context under consideration. 

A telephone survey is a kind of simulation of the face-to-face survey experience since it involves discussing with respondents to gather and process valid data. However, major challenges with this method include the fact that it is expensive and time-consuming. 

• Online Surveys

An online survey is a data collection tool used to create and administer surveys and questionnaires using data tools like Formplus. Online surveys work better than paper forms and other offline survey methods because you can easily gather and process data from a large sample size with them. 

• Face-to-Face Interviews

Face-to-face interviews for survey research can be structured, semi-structured, or unstructured depending on the research context and the type of data you want to collect. If you want to gather qualitative data , then unstructured and semi-structured interviews are the way to go. 

On the other hand, if you want to collect quantifiable information from your research sample, conducting a structured interview is the best way to go. Face-to-face interviews can also be time-consuming and cost-intensive. Let’s mention here that face-to-face surveys are one of the most widely used methods of survey data collection. 

How to Conduct Research Surveys on Formplus 

With Formplus, you can create forms for survey research without any hassles. Follow this step-by-step guide to create and administer online surveys for research via Formplus. 

1. Sign up at www.formpl.us to create your Formplus account. If you already have a Formplus account, click here to log in.

5. Use the form customization options to change the appearance of your survey. You can add your organization’s logo to the survey, change the form font and layout, and insert preferred background images.

Advantages of Survey Research

• It is inexpensive – with survey research, you can avoid the cost of in-person interviews. It’s also easy to receive data as you can share your surveys online and get responses from a large demographic
• It is the fastest way to get a large amount of first-hand data
• Surveys allow you to compare the results you get through charts and graphs
• It is versatile as it can be used for any research topic
• Surveys are perfect for anonymous respondents in the research 

Disadvantages of Survey Research

• Some questions may not get answers
• People may understand survey questions differently
• It may not be the best option for respondents with visual or hearing impairments as well as a demographic with no literacy levels
• People can provide dishonest answers in a survey research

Conclusion 

In this article, we’ve discussed survey research extensively; touching on different important aspects of this concept. As a researcher, organization, individual, or student, it is important to understand how survey research works to utilize it effectively and get the most from this method of systematic investigation. 

As we’ve already stated, conducting survey research online is one of the most effective methods of data collection as it allows you to gather valid data from a large group of respondents. If you’re looking to kick off your survey research, you can start by signing up for a Formplus account here. 

Connect to Formplus, Get Started Now - It's Free!

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Survey Research — Types, Methods and Example Questions

Survey research The world of research is vast and complex, but with the right tools and understanding, it's an open field of discovery. Welcome to a journey into the heart of survey research. What is survey research? Survey research is the lens through which we view the opinions, behaviors, and experiences of a population. Think of it as the research world's detective, cleverly sleuthing out the truths hidden beneath layers of human complexity. Why is survey research important? Survey research is a Swiss Army Knife in a researcher's toolbox. It’s adaptable, reliable, and incredibly versatile, but its real power? It gives voice to the silent majority. Whether it's understanding customer preferences or assessing the impact of a social policy, survey research is the bridge between unanswered questions and insightful data. Let's embark on this exploration, armed with the spirit of openness, a sprinkle of curiosity, and the thirst for making knowledge accessible. As we journey further into the realm of survey research, we'll delve deeper into the diverse types of surveys, innovative data collection methods, and the rewards and challenges that come with them. Types of survey research Survey research is like an artist's palette, offering a variety of types to suit your unique research needs. Each type paints a different picture, giving us fascinating insights into the world around us. Cross-Sectional Surveys: Capture a snapshot of a population at a specific moment in time. They're your trusty Polaroid camera, freezing a moment for analysis and understanding. Longitudinal Surveys: Track changes over time, much like a time-lapse video. They help to identify trends and patterns, offering a dynamic perspective of your subject. Descriptive Surveys: Draw a detailed picture of the current state of affairs. They're your magnifying glass, examining the prevalence of a phenomenon or attitudes within a group. Analytical Surveys: Deep dive into the reasons behind certain outcomes. They're the research world's version of Sherlock Holmes, unraveling the complex web of cause and effect. But, what method should you choose for data collection? The plot thickens, doesn't it? Let's unravel this mystery in our next section. Survey research and data collection methods Data collection in survey research is an art form, and there's no one-size-fits-all method. Think of it as your paintbrush, each stroke represents a different way of capturing data. Online Surveys: In the digital age, online surveys have surged in popularity. They're fast, cost-effective, and can reach a global audience. But like a mysterious online acquaintance, respondents may not always be who they say they are. Mail Surveys: Like a postcard from a distant friend, mail surveys have a certain charm. They're great for reaching respondents without internet access. However, they’re slower and have lower response rates. They’re a test of patience and persistence. Telephone Surveys: With the sound of a ringing phone, the human element enters the picture. Great for reaching a diverse audience, they bring a touch of personal connection. But, remember, not all are fans of unsolicited calls. Face-to-Face Surveys: These are the heart-to-heart conversations of the survey world. While they require more resources, they're the gold standard for in-depth, high-quality data. As we journey further, let’s weigh the pros and cons of survey research. Advantages and disadvantages of survey research Every hero has its strengths and weaknesses, and survey research is no exception. Let's unwrap the gift box of survey research to see what lies inside. Advantages: Versatility: Like a superhero with multiple powers, surveys can be adapted to different topics, audiences, and research needs. Accessibility: With online surveys, geographical boundaries dissolve. We can reach out to the world from our living room. Anonymity: Like a confessional booth, surveys allow respondents to share their views without fear of judgment. Disadvantages: Response Bias: Ever met someone who says what you want to hear? Survey respondents can be like that too. Limited Depth: Like a puddle after a rainstorm, some surveys only skim the surface of complex issues. Nonresponse: Sometimes, potential respondents play hard to get, skewing the data. Survey research may have its challenges, but it also presents opportunities to learn and grow. As we forge ahead on our journey, we dive into the design process of survey research. Limitations of survey research Every research method has its limitations, like bumps on the road to discovery. But don't worry, with the right approach, these challenges become opportunities for growth. Misinterpretation: Sometimes, respondents might misunderstand your questions, like a badly translated novel. To overcome this, keep your questions simple and clear. Social Desirability Bias: People often want to present themselves in the best light. They might answer questions in a way that portrays them positively, even if it's not entirely accurate. Overcome this by ensuring anonymity and emphasizing honesty. Sample Representation: If your survey sample isn't representative of the population you're studying, it can skew your results. Aiming for a diverse sample can mitigate this. Now that we're aware of the limitations let's delve into the world of survey design. {loadmoduleid 430} Survey research design Designing a survey is like crafting a roadmap to discovery. It's an intricate process that involves careful planning, innovative strategies, and a deep understanding of your research goals. Let's get started. Approach and Strategy Your approach and strategy are the compasses guiding your survey research. Clear objectives, defined research questions, and an understanding of your target audience lay the foundation for a successful survey. Panel The panel is the heartbeat of your survey, the respondents who breathe life into your research. Selecting a representative panel ensures your research is accurate and inclusive. 9 Tips on Building the Perfect Survey Research Questionnaire Keep It Simple: Clear and straightforward questions lead to accurate responses. Make It Relevant: Ensure every question ties back to your research objectives. Order Matters: Start with easy questions to build rapport and save sensitive ones for later. Avoid Double-Barreled Questions: Stick to one idea per question. Offer a Balanced Scale: For rating scales, provide an equal number of positive and negative options. Provide a ‘Don't Know’ Option: This prevents guessing and keeps your data accurate. Pretest Your Survey: A pilot run helps you spot any issues before the final launch. Keep It Short: Respect your respondents' time. Make It Engaging: Keep your respondents interested with a mix of question types. Survey research examples and questions Examples serve as a bridge connecting theoretical concepts to real-world scenarios. Let's consider a few practical examples of survey research across various domains. User Experience (UX) Imagine being a UX designer at a budding tech start-up. Your app is gaining traction, but to keep your user base growing and engaged, you must ensure that your app's UX is top-notch. In this case, a well-designed survey could be a beacon, guiding you toward understanding user behavior, preferences, and pain points. Here's an example of how such a survey could look: "On a scale of 1 to 10, how would you rate the ease of navigating our app?" "How often do you encounter difficulties while using our app?" "What features do you use most frequently in our app?" "What improvements would you suggest for our app?" "What features would you like to see in future updates?" This line of questioning, while straightforward, provides invaluable insights. It enables the UX designer to identify strengths to capitalize on and weaknesses to improve, ultimately leading to a product that resonates with users. Psychology and Ethics in survey research The realm of survey research is not just about data and numbers, but it's also about understanding human behavior and treating respondents ethically. Psychology: In-depth understanding of cognitive biases and social dynamics can profoundly influence survey design. Let's take the 'Recency Effect,' a psychological principle stating that people tend to remember recent events more vividly than those in the past. While framing questions about user experiences, this insight could be invaluable. For example, a question like "Can you recall an instance in the past week when our customer service exceeded your expectations?" is likely to fetch more accurate responses than asking about an event several months ago. Ethics: On the other hand, maintaining privacy, confidentiality, and informed consent is more than ethical - it's fundamental to the integrity of the research process. Imagine conducting a sensitive survey about workplace culture. Ensuring respondents that their responses will remain confidential and anonymous can encourage more honest responses. An introductory note stating these assurances, along with a clear outline of the survey's purpose, can help build trust with your respondents. Survey research software In the age of digital information, survey research software has become a trusted ally for researchers. It simplifies complex processes like data collection, analysis, and visualization, democratizing research and making it more accessible to a broad audience. LimeSurvey, our innovative, user-friendly tool, brings this vision to life. It stands at the crossroads of simplicity and power, embodying the essence of accessible survey research. Whether you're a freelancer exploring new market trends, a psychology student curious about human behavior, or an HR officer aiming to improve company culture, LimeSurvey empowers you to conduct efficient, effective research. Its suite of features and intuitive design matches your research pace, allowing your curiosity to take the front seat. For instance, consider you're a researcher studying consumer behavior across different demographics. With LimeSurvey, you can easily design demographic-specific questions, distribute your survey across various channels, collect responses in real-time, and visualize your data through intuitive dashboards. This synergy of tools and functionalities makes LimeSurvey a perfect ally in your quest for knowledge. Conclusion If you've come this far, we can sense your spark of curiosity. Are you eager to take the reins and conduct your own survey research? Are you ready to embrace the simple yet powerful tool that LimeSurvey offers? If so, we can't wait to see where your journey takes you next! In the world of survey research, there's always more to explore, more to learn and more to discover. So, keep your curiosity alive, stay open to new ideas, and remember, your exploration is just beginning! We hope that our exploration has been as enlightening for you as it was exciting for us. Remember, the journey doesn't end here. With the power of knowledge and the right tools in your hands, there's no limit to what you can achieve. So, let your curiosity be your guide and dive into the fascinating world of survey research with LimeSurvey! Try it out for free now! Happy surveying! {loadmoduleid 429}

Table Content

Survey research.

The world of research is vast and complex, but with the right tools and understanding, it's an open field of discovery. Welcome to a journey into the heart of survey research.

What is survey research?

Survey research is the lens through which we view the opinions, behaviors, and experiences of a population. Think of it as the research world's detective, cleverly sleuthing out the truths hidden beneath layers of human complexity.

Why is survey research important?

Survey research is a Swiss Army Knife in a researcher's toolbox. It’s adaptable, reliable, and incredibly versatile, but its real power? It gives voice to the silent majority. Whether it's understanding customer preferences or assessing the impact of a social policy, survey research is the bridge between unanswered questions and insightful data.

Let's embark on this exploration, armed with the spirit of openness, a sprinkle of curiosity, and the thirst for making knowledge accessible. As we journey further into the realm of survey research, we'll delve deeper into the diverse types of surveys, innovative data collection methods, and the rewards and challenges that come with them.

Types of survey research

Survey research is like an artist's palette, offering a variety of types to suit your unique research needs. Each type paints a different picture, giving us fascinating insights into the world around us.

• Cross-Sectional Surveys: Capture a snapshot of a population at a specific moment in time. They're your trusty Polaroid camera, freezing a moment for analysis and understanding.
• Longitudinal Surveys: Track changes over time, much like a time-lapse video. They help to identify trends and patterns, offering a dynamic perspective of your subject.
• Descriptive Surveys: Draw a detailed picture of the current state of affairs. They're your magnifying glass, examining the prevalence of a phenomenon or attitudes within a group.
• Analytical Surveys: Deep dive into the reasons behind certain outcomes. They're the research world's version of Sherlock Holmes, unraveling the complex web of cause and effect.

But, what method should you choose for data collection? The plot thickens, doesn't it? Let's unravel this mystery in our next section.

Survey research and data collection methods

Data collection in survey research is an art form, and there's no one-size-fits-all method. Think of it as your paintbrush, each stroke represents a different way of capturing data.

• Online Surveys: In the digital age, online surveys have surged in popularity. They're fast, cost-effective, and can reach a global audience. But like a mysterious online acquaintance, respondents may not always be who they say they are.
• Mail Surveys: Like a postcard from a distant friend, mail surveys have a certain charm. They're great for reaching respondents without internet access. However, they’re slower and have lower response rates. They’re a test of patience and persistence.
• Telephone Surveys: With the sound of a ringing phone, the human element enters the picture. Great for reaching a diverse audience, they bring a touch of personal connection. But, remember, not all are fans of unsolicited calls.
• Face-to-Face Surveys: These are the heart-to-heart conversations of the survey world. While they require more resources, they're the gold standard for in-depth, high-quality data.

As we journey further, let’s weigh the pros and cons of survey research.

Advantages and disadvantages of survey research

Every hero has its strengths and weaknesses, and survey research is no exception. Let's unwrap the gift box of survey research to see what lies inside.

Advantages:

• Versatility: Like a superhero with multiple powers, surveys can be adapted to different topics, audiences, and research needs.
• Accessibility: With online surveys, geographical boundaries dissolve. We can reach out to the world from our living room.
• Anonymity: Like a confessional booth, surveys allow respondents to share their views without fear of judgment.

Disadvantages:

• Response Bias: Ever met someone who says what you want to hear? Survey respondents can be like that too.
• Limited Depth: Like a puddle after a rainstorm, some surveys only skim the surface of complex issues.
• Nonresponse: Sometimes, potential respondents play hard to get, skewing the data.

Survey research may have its challenges, but it also presents opportunities to learn and grow. As we forge ahead on our journey, we dive into the design process of survey research.

Limitations of survey research

Every research method has its limitations, like bumps on the road to discovery. But don't worry, with the right approach, these challenges become opportunities for growth.

Misinterpretation: Sometimes, respondents might misunderstand your questions, like a badly translated novel. To overcome this, keep your questions simple and clear.

Social Desirability Bias: People often want to present themselves in the best light. They might answer questions in a way that portrays them positively, even if it's not entirely accurate. Overcome this by ensuring anonymity and emphasizing honesty.

Sample Representation: If your survey sample isn't representative of the population you're studying, it can skew your results. Aiming for a diverse sample can mitigate this.

Now that we're aware of the limitations let's delve into the world of survey design.

•   Create surveys in 40+ languages
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•   Ready-to-go survey templates
•   So much more...

Survey research design

Designing a survey is like crafting a roadmap to discovery. It's an intricate process that involves careful planning, innovative strategies, and a deep understanding of your research goals. Let's get started.

Approach and Strategy

Your approach and strategy are the compasses guiding your survey research. Clear objectives, defined research questions, and an understanding of your target audience lay the foundation for a successful survey.

The panel is the heartbeat of your survey, the respondents who breathe life into your research. Selecting a representative panel ensures your research is accurate and inclusive.

9 Tips on Building the Perfect Survey Research Questionnaire

• Keep It Simple: Clear and straightforward questions lead to accurate responses.
• Make It Relevant: Ensure every question ties back to your research objectives.
• Order Matters: Start with easy questions to build rapport and save sensitive ones for later.
• Avoid Double-Barreled Questions: Stick to one idea per question.
• Offer a Balanced Scale: For rating scales, provide an equal number of positive and negative options.
• Provide a ‘Don't Know’ Option: This prevents guessing and keeps your data accurate.
• Pretest Your Survey: A pilot run helps you spot any issues before the final launch.
• Keep It Short: Respect your respondents' time.
• Make It Engaging: Keep your respondents interested with a mix of question types.

Survey research examples and questions

Examples serve as a bridge connecting theoretical concepts to real-world scenarios. Let's consider a few practical examples of survey research across various domains.

User Experience (UX)

Imagine being a UX designer at a budding tech start-up. Your app is gaining traction, but to keep your user base growing and engaged, you must ensure that your app's UX is top-notch. In this case, a well-designed survey could be a beacon, guiding you toward understanding user behavior, preferences, and pain points.

Here's an example of how such a survey could look:

• "On a scale of 1 to 10, how would you rate the ease of navigating our app?"
• "How often do you encounter difficulties while using our app?"
• "What features do you use most frequently in our app?"
• "What improvements would you suggest for our app?"
• "What features would you like to see in future updates?"

This line of questioning, while straightforward, provides invaluable insights. It enables the UX designer to identify strengths to capitalize on and weaknesses to improve, ultimately leading to a product that resonates with users.

Psychology and Ethics in survey research

The realm of survey research is not just about data and numbers, but it's also about understanding human behavior and treating respondents ethically.

Psychology: In-depth understanding of cognitive biases and social dynamics can profoundly influence survey design. Let's take the 'Recency Effect,' a psychological principle stating that people tend to remember recent events more vividly than those in the past. While framing questions about user experiences, this insight could be invaluable.

For example, a question like "Can you recall an instance in the past week when our customer service exceeded your expectations?" is likely to fetch more accurate responses than asking about an event several months ago.

Ethics: On the other hand, maintaining privacy, confidentiality, and informed consent is more than ethical - it's fundamental to the integrity of the research process.

Imagine conducting a sensitive survey about workplace culture. Ensuring respondents that their responses will remain confidential and anonymous can encourage more honest responses. An introductory note stating these assurances, along with a clear outline of the survey's purpose, can help build trust with your respondents.

Survey research software

In the age of digital information, survey research software has become a trusted ally for researchers. It simplifies complex processes like data collection, analysis, and visualization, democratizing research and making it more accessible to a broad audience.

LimeSurvey, our innovative, user-friendly tool, brings this vision to life. It stands at the crossroads of simplicity and power, embodying the essence of accessible survey research.

Whether you're a freelancer exploring new market trends, a psychology student curious about human behavior, or an HR officer aiming to improve company culture, LimeSurvey empowers you to conduct efficient, effective research. Its suite of features and intuitive design matches your research pace, allowing your curiosity to take the front seat.

For instance, consider you're a researcher studying consumer behavior across different demographics. With LimeSurvey, you can easily design demographic-specific questions, distribute your survey across various channels, collect responses in real-time, and visualize your data through intuitive dashboards. This synergy of tools and functionalities makes LimeSurvey a perfect ally in your quest for knowledge.

If you've come this far, we can sense your spark of curiosity. Are you eager to take the reins and conduct your own survey research? Are you ready to embrace the simple yet powerful tool that LimeSurvey offers? If so, we can't wait to see where your journey takes you next!

In the world of survey research, there's always more to explore, more to learn and more to discover. So, keep your curiosity alive, stay open to new ideas, and remember, your exploration is just beginning!

We hope that our exploration has been as enlightening for you as it was exciting for us. Remember, the journey doesn't end here. With the power of knowledge and the right tools in your hands, there's no limit to what you can achieve. So, let your curiosity be your guide and dive into the fascinating world of survey research with LimeSurvey! Try it out for free now!

Happy surveying!

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

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

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

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

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

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

Table of contents

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

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

Common uses of survey research include:

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

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

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

Populations

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

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

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

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

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

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

There are two main types of survey:

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

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

Questionnaires

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

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

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

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

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

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

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

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

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

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

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

Open-ended vs closed-ended questions

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

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

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

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

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

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

The content of the survey questions

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

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

Phrasing the survey questions

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

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

Ordering the survey questions

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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What is survey research.

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

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

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

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

Get started with our free survey maker tool

Types of survey research

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

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

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

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

Face-to-face interviews

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

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

Telephone surveys

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

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

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

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

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

Focus groups (interviews — not surveys)

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

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

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

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

Online surveys

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

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

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

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

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

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

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

When it comes to surveys, every voice matters.

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

Panel surveys

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

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

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

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

What are the benefits of using survey research?

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

1.   They’re relatively easy to do

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

2.   They can be cost effective

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

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

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

3.   You can collect data from a large sample

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

4.   You can use survey software to analyze results immediately

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

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

5.   Surveys can collect any type of data

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

How to measure concepts with survey questions

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

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

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

Nominal scale

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

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

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

Ordinal scale

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

Ratio scale

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

Interval scale

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

Step by step: How to conduct surveys and collect data

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

Step 1 – Define your objectives

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

Step 2 – Create your survey questions

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

Step 3 – Choose your question types

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

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

Step 4 – Test your questions

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

Step 5 – Choose your target and send out the survey

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

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

Step 6 – Analyze results and draw conclusions

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

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

Get reliable insights with survey software from Qualtrics

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

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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Types of research design: Choosing the right methods for your study

There are many ways to design your study, but some will answer your research question better than others. By choosing the right research design, you can minimize your margin of error and get more accurate and useful results. It all starts with the aim of your study, which will help you determine the best approach to take when it comes to your research design. 

What is research design? 

Research design is the methods and procedures of a study, which vary depending on the type of study, research question, variables, and hypothesis.

While there isn’t a clear consensus on how to categorize the many different types of research design, most survey research can be categorized as either exploratory, descriptive, correlational, or experimental.

Exploratory research design

Exploratory research aims to uncover new ideas and insights from participants who have some familiarity with your research subject. This type of research study design can yield powerful insights but has limited applications. As the name implies, exploratory research focuses on exploration and belongs at the beginning of your research project. The insights you get will help define the direction for the rest of your research, rather than provide conclusive answers.

Exploratory research is all about qualitative, not quantitative data . An exploratory research survey includes open-ended questions, where respondents can share impressions and ideas in an open format. While these responses can’t be quantified (except maybe with a word cloud ), there are some helpful methods for collecting and analyzing open-ended data that you can apply to exploratory research. 

Descriptive research design

Descriptive research sheds light on the current characteristics of a research subject by collecting, analyzing, and presenting feedback from those familiar with the subject. This type of transparent research design asks participants to give their thoughts and opinions on the research subject, so that the researcher can describe the state of the subject with more detail and accuracy. The focus of descriptive research is always on “what” rather than “why.”

This type of research study design leans on both qualitative and quantitative data. For example, a descriptive research survey might collect qualitative data with open-ended questions, while also collecting quantitative metrics with multiple choice, rating scale, ranking, or demographic questions . Both types of data will help you paint a clearer picture of your research subject. 

Customer satisfaction surveys and case studies are examples of descriptive research designs. If your research question asks about the current state of your subject, look to the methods and procedures of these types of studies for tips on how to minimize your margin of error. 

Correlational research design

Correlational research looks at whether or not variables in the study are correlated with each other. It’s a non-experimental type of research study design that uses factor analysis to determine whether, for example, the way respondents answer one question in your survey is related to the way they answer another question. Correlational research can help you develop models that predict things like medical conditions and consumer behavior.

Many observational studies use correlational research designs, particularly if the goal is to construct a predictive model. These studies use quantitative data derived from multiple choice, rating scale, ranking, or demographic questions to calculate the correlation coefficients between two variables .

Experimental research design

Experimental research (or causal research ) aims to establish a causal relationship between two variables by changing an independent variable to see what effect it has on a dependent variable. Experimental research design is ideal for very specific and practical research questions. An experimental research survey might, for example, examine how price affects purchase intention by testing people’s willingness to buy a new product at different price points.

Controlled experiments, field experiments, and natural experiments all utilize experimental research design. To be valid, these experiments must adhere to strict research methods and procedures that ensure the integrity of the experiment. 

Exploratory, descriptive, correlational, and experimental studies each have their own research methods and procedures—and the approach that’s right for you will depend on what you’re seeking to learn. Think about the purpose of your study, and follow best practices for every type of survey design.

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• What is survey design: Definition, methods & good examples

Surveys are a common way to collect data across various industries . They are a wise choice if you want to learn more about a group of people's traits, interests, viewpoints, or beliefs . The number of survey participants is significant in this respect. You can increase the number of survey participants with a good survey design. 

You can gain more profound knowledge of consumer behavior in the market with the help of a customized and well-designed survey. It is feasible to acquire the information you need to make a better decision , avert issues , and keep the organization improving with a good survey research design.

The success of your initiatives may depend on how well your surveys are designed . This article will explain the definition of survey design, types of survey research design, best question types to use in your survey design, and survey design methodology with all details.

• First things first: What is survey design?

Survey design is the creation of questions or other survey items, placing them in a logical order, and selecting acceptable response alternatives . The survey design process is done to gain as much insight as possible from survey research. We can better comprehend consumer behavior in the market using a customized survey.

The definition of survey design

By making the survey easy to read and complete , survey designers want to get precise and essential data from respondents. For a survey design to be effective, it is necessary to understand the research topic or objective , the target population , and the best data-gathering method. 

• Survey design types

The effectiveness of survey research depends on how closely responses to survey questions reflect their thoughts and behaviors. A good survey design helps you get good survey results . Here are the valuable types of survey designs:

Types of survey design

Cross-sectional survey design

An example of an observational study design is the cross-sectional study design. In a cross-sectional study, the researcher simultaneously assesses the participants' exposures and outcomes. The survey research design frequently gathers information at a particular moment with a representative sample . 

Mixed survey design

Research using mixed methods collects and analyzes data using quantitative and qualitative approaches . These methodologies can each address a particular topic; thus, combining them can yield more detailed results. 

Panel survey design

A panel survey is a long-term research that tracks people’s behavior over time , including their thoughts , feelings , and emotions . The survey is repeated over time and involves the same people being polled or interviewed. 

Longitudinal survey design

A longitudinal study is an observational one , just as a cross-sectional study. In a longitudinal study, researchers observe the same participants repeatedly and sometimes for several years . A sample is followed over time in this survey study, usually with many data-collecting sites. 

Prospective survey design

Prospective survey research examines trends, forecasts, and results by starting in the present and following participants into the future . It is a survey that gathers information on upcoming experiences or events. 

Cohort survey design

One longitudinal study is the cohort study, which involves keeping track of research subjects across time . It tracks a specific group or cohort of individuals over time . 

Qualitative surveys design

Qualitative surveys use open-ended questions to generate lengthy written or typed responses . The purpose of the questions is to elicit viewpoints , experiences , narratives , or stories . As they aid in identifying early themes or concerns to be explored more profoundly in the study subsequently, surveys are frequently a helpful intro to interviews or focus groups. 

Experimental survey design

Experimental research utilizes two sets of variables and a scientific methodology . A style of survey research design in which one variable is changed to see how it affects another, the dependent variable. 

Cross-cultural survey design

Study design for cross-cultural surveys compares data from various countries and cultures . Participants from two or more cultures had psychological variables evaluated , and the results were compared . 

Retrospective survey design

Retrospective research examines the past and evaluates things that have already happened . When the study begins, the researchers are already aware of the results for each subject. Researchers use pre-existing records to gather data while employing retrospective approaches. 

• Essential terms in survey design

A survey is one of the best methods for quickly getting consumer input and determining their motivations. The information required to develop a more effective decision-making approach may be gathered with the help of a well-designed survey. Here are essential terms in survey design:

• Target Population: The whole group about whom you wish to make conclusions is called a target population . When your research issue calls for or allows you access to data from every member of the population, populations are utilized. 
• Response rate: The percentage of respondents that completed your survey from your sample is known as the survey response rate. It is the proportion of respondents to the poll out of all those asked to participate.
• Demographics: A demographic survey gathers information on the group's fundamental traits. Collecting demographic data to understand better a target market or client segment is standard practice. 
• Survey sampling: A statistical technique that includes choosing and polling people from a particular group. The population you decide to sample could depend on a variety of factors.
• Survey bias: Survey bias is an error in the feedback from the surveyor and the respondents' specific factors. How objective feedback and insights may depend in part on sampling bias.
• Reliability: The degree of reproducibility of study findings when conducted again under the same circumstances is known as reliability—the accuracy and reliability of survey findings over time and across various sample groups. 
• Validity: Validity is about the accuracy of the measurement . It is the degree to which a survey collects the data it purports to contain. Asking questions that capture what you want to capture is critical.
• Questionnaire: A questionnaire is a list of inquiries intended to learn more about survey participants’ experiences, beliefs, and actions . 
• Best practices to follow in survey design

The initial step in conducting a survey is to develop questions to gauge respondents’ attitudes and actions. If the data is acquired using biased questions, response rates will be squandered. Writing appropriate questions and implementing a practical layout is essential to get quality feedback. Here are the survey design best practices:

1  - Establish your survey goals: Before beginning the survey design, clearly state the survey’s objectives and aims . By establishing your survey goals, you can be confident that you are gathering information that will be accurate and helpful to your study. 🎯

2  - Use precise language in your survey: Using language is crucial while creating a survey. Your goal must be to make your survey easy for respondents to complete. Use clear, succinct language, and make sure queries are straightforward. Avoid acronyms, technical jargon, and other unusual phrases that might mislead readers . 💬

3  - Keep your survey brief and concise: Your survey should be brief and precise. Due to respondents’ short attention spans and the risk of survey fatigue and dropouts, the quality of your data may be compromised. You will receive higher completion rates and more thoughtful answers to the questions you decide to include. ✍🏻

4  - Avoid double-barreled questions: Respondents frequently pause when faced with double-barreled questions as they struggle to formulate the right answer. The simplest way to avoid a double-barreled question is to divide the question into two halves. 🤔

5  - Avoid biased questions in your survey: It is simple to add skewed or misleading questions to your survey unintentionally. Scrutinize your survey questions for any bias that can impact the integrity and validity of your findings . Stay away from leading questions that sway respondents' responses and double-barreled inquiries that pose many questions at once. ↖️

6  - Think of incorporating a survey incentive: An incentive may be helpful if you are interested in receiving many answers. If responders answer all of your questions, you may offer them a gift card or enter them in sweepstakes drawing as incentives. 🎁

7  - Keep your survey anonymous: Ensure your replies are anonymous to promote truthful responses. Respondents feel more comfortable , so they tend to give more truthful replies when they believe their answers are confidential. 🎭

8  - Use images and videos: It might not be sufficient to communicate the idea in words if you want to ask participants how they would feel about a new product. Include an image for participants to examine instead of providing a lengthy explanation. 🖼️🎞️

9  - Check it out before sending your survey: Make sure to examine it to avoid design errors. Even better, distribute it to others so they can spot any mistakes you might miss. 🧩

• Best question types to use in your survey design

Think about how you want to use the survey respondents' responses before you jump into crafting the survey’s questions. To get answers from people, survey questions can either be closed-ended questions or open-ended questions. About survey design, this means selecting the appropriate respondents and timing for your inquiries. Here are the question types to use in your survey design: 

• Multiple choice questions

Multiple-choice questions are a staple of surveys because they provide respondents with a range of response alternatives. Multiple-choice questions are divided into two subgroups:

Single selection: A single selection question type allows respondents to select one answer from a wide range of options . This question type helps gather information on readily measurable information since it gives respondents a list of alternatives. 

Multiple selection: Respondents may select from a wide range of possibilities when answering questions with multiple choice and multiple responses . Multiple selections question type collects information that is simple to evaluate and provides in-depth insights.

A multiple-choice question sample

• Open-ended questions

Open-ended survey questions don’t offer pre-determined answer selections and ask respondents to input their responses into a comment box. Respondents can freely and without regard to specified categories express their thoughts, ideas, and experiences with this inquiry. This kind of inquiry is helpful for thoroughly examining novel subjects. 

You can ask demographic questions in the open-ended questions. Depending on their characteristics and activities, you may further analyze your data using demographic questions to classify your audience . 

An open-ended question sample

• Likert scales

To assess respondents’ attitudes and emotions, Likert scale questions are employed. Respondents to this question type are given various statements to which they can indicate how much they agree or disagree.

A Likert scale question sample

• Rating scales

A scale of response alternatives from any range is displayed in rating scale inquiries. The respondent chooses the numeric response that most closely matches their opinion. Questions using a rating scale are an excellent example of the Net Promoter Score . 

A rating scale question sample

• Matrix questions

This question type asks the same questions on various qualities or variables with identical response alternatives. Assessing the correlation between variables is made easier with this strategy.

A matrix question sample

• Image choice questions

Including images in online surveys may enhance user experience and make respondents' answers easier. Respondents can choose from a variety of images in image choice questions. You can add images to both questions and answer options on forms.app. 

An image choice question sample

• Frequently asked questions about survey design

Your respondents will provide truthful responses in a well-designed survey, as they won’t be biased in favor of either side. Below are answers to frequently asked questions about design, such as why survey design is essential and where to prepare a well-designed survey.

Why is survey design important?

Researchers can use surveys to get trustworthy, valuable primary data to help them make business decisions. The survey design is crucial because it ensures the validity and reliability of the information or data gathered. Data that is erroneous or skewed might result from poorly constructed questionnaires.

Where can a well-designed survey be prepared?

Surveys can be prepared manually or online. There are many tools for designing online surveys. The features in those applications are vital for you to schedule a better survey. One of the best survey creation tools is forms.app. forms.app offers many features to its users. Using these unique features, you can create a beautifully designed survey.

Why is it crucial to protect survey participants' privacy and confidentiality?

Ensuring survey participants' anonymity and confidentiality promotes truthful and accurate replies. While gathering, analyzing, and reporting participant-related data, human research participants' privacy is protected through anonymity and confidentiality procedures.

What should the order of the questions in the survey be?

The questions should be asked in a sensible order. Before going on to more complicated queries, start with simpler ones. It is possible to gather demographic data at the start or end of the survey. Avoiding prejudicial questions is also essential.

• Final words

In conclusion, developing and organizing a survey or questionnaire to collect information from a specific audience or group is called survey design. A survey's design must guarantee that the questions are precise and unambiguous and that the data gathered will be accurate and trustworthy.

The ultimate goal of survey design is to produce precise, significant, and pertinent data that may be used for a particular research issue or to assist in decision-making . This article has explained the definition of survey design, essential question types to use in your survey design, and practical terms in survey design with all details.

Sena is a content writer at forms.app. She likes to read and write articles on different topics. Sena also likes to learn about different cultures and travel. She likes to study and learn different languages. Her specialty is linguistics, surveys, survey questions, and sampling methods.

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Home Surveys

Types of Survey: What It Is with Examples

Technically, a  survey is a method of gathering and compiling information from a group of people, more often known as the sample, to gain knowledge by organizations, businesses, or institutions. This information or opinion collected from the sample is more often a generalization of what a large population thinks.

Different types of survey helps provide important or critical information in the form of meaningful data, which is further used by businesses or organizations to make informed and sound decisions. The collected data offers good insights only when the administered questionnaire is carefully designed to promote response rates and includes both open-ended questions and closed-ended questions and answers options. There is much variety when it comes to surveys, and we can identify their types based on the frequency of their administration or the way of deployment.

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Types of Survey

Now that we know what a survey is and why do we need to survey people, let’s explore its types. These can be classified in different ways, as mentioned earlier, depending upon the frequency of administration or deployment and how the distribution/deployment occurs. There are other types of surveys like random sample surveys (to understand public opinion or attitude) and self-selected type of studies.

LEARN ABOUT: Candidate Experience Survey

Types of a survey based on deployment methods:

1. online surveys:.

One of the most popular types is an online survey . With technology advancing many folds with each passing day, an online survey is becoming more popular. This survey consists of  survey questions that can be easily deployed to the respondents online via email, or they can access the survey if they have an internet connection. These surveys are easy to design and simple to deploy. Respondents are given ample time and space to the respondent to answer these surveys, so researchers can expect unbiased responses. They are less expensive, and data can be collected and analyzed quickly.

LEARN ABOUT: Event Surveys

2. Paper surveys:

As the name suggests, this survey uses the traditional paper and pencil approach. Many would believe that paper surveys are a thing of the past. However, they are quite handy when it comes to field research and data collection. These surveys can go where computers, laptops or other handheld devices cannot go.

There is a flip side to it too. This survey type is the most expensive method of data collection. It includes deploying a large number of human resources, along with time and money.

LEARN ABOUT: course evaluation survey examples

3. Telephonic Surveys:

Researchers conduct these over telephones. Respondents need to answer questions related to the research topic by the researcher. These surveys are time-consuming and sometimes non-conclusive. The success of these depends on how many people answer the phone and want to invest their time answering questions over the telephone.

4. One-to-One interviews:

The one-to-one interview helps researchers gather information or data directly from a respondent. It’s a qualitative research method  and depends on the knowledge and experience of a researcher to frame and ask relevant questions one after the other to collect meaningful insights from the  interview . These interviews can last from 30 minutes up to a few hours.

Types of a survey based on the frequency of deployment

1. cross-sectional studies.

These surveys are administered to a small sample from a larger population within a small time frame. This type offers a researcher a quick summary or analysis of what respondents think at that given time. These surveys are short and ready to answer and can measure opinion in one particular situation.

Consider hypothetically, an organization conducts a study related to breast cancer in America, and they choose a sample to obtain cross-sectional data. This data indicated that breast cancer was most prevalent in women of African-American origin. The information is from one point in time. Now, if the researcher wants to dwell more in-depth into the research, he/she can deploy a longitudinal survey.

Learn more: Cross-sectional Study

2. Longitudinal surveys:

Longitudinal surveys are those surveys that help researchers to make an observation and collect data over an extended period. There are three main types of longitudinal studies: trend surveys, panel surveys, and cohort surveys.

Trend surveys are deployed by researchers to understand the shift or transformation in the thought process of respondents over some time. They use these surveys to understand how people’s inclination change with time.

Another longitudinal survey type is  a panel survey . Researchers administer these surveys to the same set or group of people over the years. Panel surveys are expensive in nature, and researchers try to stick to their panel to gather unbiased opinions.

The third type of longitudinal survey is the cohort survey. In this type, categories of people that meet specific similar criteria and characteristics form the target audience. The same people don’t need to create a group. However, people forming a group should have certain similarities.

Learn more: Longitudinal Study

3. Retrospective survey:

A retrospective survey is a type of study in which respondents answer questions to report on events from the past. By deploying this kind of survey, researchers can gather data based on past experiences and beliefs of people. This way, unlike a longitudinal survey, they can save the cost and time required.

Learn more: Cross-sectional vs Longitudinal Study

Random public opinion/attitude type of survey research:

When an agency needs reliable, projectable data about the attitudes and opinions of its citizens or a select group of its citizens, it is essential to conduct a valid, random sample survey. Telephone interview surveys are considerably more common than in-person interviews because they are far less expensive to administer and act as a standard tool for gathering information.

There is a margin of error based on the sample size (generally, a minimum population sample of 200 is the industry standard for reliable data about any population segment). Overall, random sample telephone interview surveys provide reasonably accurate information about the population.

While there is a statistical  margin of error (the sample of 200 provides an error range of +/- 7% with a 95% confidence), this type of survey is the most democratic and reliable process for learning about the opinions of an entire community.

A random sample survey is inappropriate for educating people about an issue or assessing what people will do at some future point (i.e., “Will you vote for this bond issue?”). But, the results provide a reasonably accurate portrait of the person’s opinions in the present moment (i.e., a person’s feelings or attitudes about the issues relating to the need to approve a bond). Questions in the past and present tense provide a reasonable degree of accuracy about a person’s usage and habit patterns.

If you are trying to calculate the ideal margin of error for your research, you can use tools like our margin of error calculator .

LEARN ABOUT: telephone survey

Self-selected type of survey research – Newspapers, mail, Internet, written questionnaires:

When an agency has a political need to create a survey process that allows anyone interested in responding, it can do a self-selected process. A written survey can be distributed in public locations, such as the City Hall or Library, emailed directly, emailed, or published in the city newsletter or the local newspaper.

When reporting data from a self-selected survey, it is essential, to begin with, the understanding and the language, “Of those who chose to respond…..” Most often, those who volunteer to respond to a self-selected survey have a strong opinion (frequently negative) about the issue in question.

A self-selected survey can be an excellent public relations tool and the right way to inform the public. But, it’s crucial to be cautious in drawing any conclusion about what the public, in general, thinks based on the results of a survey when the respondents are volunteers.

Learn more: Research Design

Types of surveys with examples

A researcher must have a proper medium to conduct research and collect meaningful information to make informed decisions. Also, it is essential to have a platform to create and deploy these various types of market research surveys.

LEARN ABOUT: Top 12 Tips to Create A Good Survey

QuestionPro is a platform that helps not only to create but also to deploy different types of surveys. We have 350+ types of survey templates and survey examples, including:

• Customer survey templates: Customers are crucial to success for any business or organization, and so are customer satisfaction surveys. It is essential for organizations or companies to understand their customers and what their needs and preferences are. Use the customer survey template to understand your customers better and work on their feedback to grow and flourish your business.
• Market research & Marketing survey templates : Use marketing survey templates for market research to determine what consumers think about products or services. These are also helpful for a brand to assess whether products are reasonably priced, gather feedback from consumers, measure their level of awareness, and more.
• Community survey templates : Community survey templates can be administered to members of associations or foundations to get feedback regarding the various activities conducted within the association. This helps understand the member’s experiences and collect feedback regarding what kind of programs add value, feedback of previously held events, etc. and more.
• Human Resource survey templates : The human resource survey template can be used by businesses and organizations for employee evaluation, employee satisfaction, employee engagement, and more. Organizations can send these out to employees, and their feedback can be collected and implemented.

LEARN ABOUT:   Workforce Planning Model

• Industrial survey templates : Expertly designed survey templates that are customized for the different industries help to collect in-depth feedback or information from consumers of various industries like event management, hotel industry , fast food industry, transportation, just to name a few. Through these survey templates, the industry player can understand what good they are already doing and what needs more attention from a consumer’s point of view.
• Academic survey templates : Academic survey templates are one of the best ways to understand how students and their parents respond to the efforts taken by your education institution. A online questionnaire designed by industry experts helps to assess the parent/student feedback on a course evaluation, curriculum planning, training sessions, etc.
• Nonprofit survey templates : These Nonprofit survey templates are designed by domain experts to collect targeted information and feedback from various donors, volunteers, stakeholders, and any other participants of a nonprofit’s activities. The questionnaires address various important touchpoints and collect data from event attendees, collect donor survey feedback, or run an internal survey among volunteers.

LEARN ABOUT: best time to send out surveys

One can choose from these existing survey format templates or create a survey of their own, all this just at the click of a button.

Explore: 350+ Free survey templates

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Lau F, Kuziemsky C, editors. Handbook of eHealth Evaluation: An Evidence-based Approach [Internet]. Victoria (BC): University of Victoria; 2017 Feb 27.

Handbook of eHealth Evaluation: An Evidence-based Approach [Internet].

Chapter 13 methods for survey studies.

Francis Lau .

13.1. Introduction

The survey is a popular means of gauging people’s opinion of a particular topic, such as their perception or reported use of an eHealth system. Yet surveying as a scientific approach is often misconstrued. And while a survey seems easy to conduct, ensuring that it is of high quality is much more difficult to achieve. Often the terms “survey” and “questionnaire” are used interchangeably as if they are the same. But strictly speaking, the survey is a research approach where subjective opinions are collected from a sample of subjects and analyzed for some aspects of the study population that they represent. On the other hand, a questionnaire is one of the data collection methods used in the survey approach, where subjects are asked to respond to a predefined set of questions.

The eHealth literature is replete with survey studies conducted in different health settings on a variety of topics, for example the perceived satisfaction of ehr systems by ophthalmologists in the United States ( Chiang et al., 2008 ), and the reported impact of emr adoption in primary care in a Canadian province ( Paré et al., 2013 ). The quality of eHealth survey studies can be highly variable depending on how they are designed, conducted, analyzed and reported. It is important to point out there are different types of survey studies that range in nature from the exploratory to the predictive, involving one or more groups of subjects and an eHealth system over a given time period. There are also various published guidelines on how survey studies should be designed, reported and appraised. Increasingly, survey studies are used by health organizations to learn about provider, patient and public perceptions toward eHealth systems. As a consequence, the types of survey studies and their methodological considerations should be of great interest to those involved with eHealth evaluation.

This chapter describes the types of survey studies used in eHealth evaluation and their methodological considerations. Also included are three case examples to show how these studies are done.

13.2. Types of Survey Studies

There are different types of survey study designs depending on the intended purpose and approach taken. Within a given type of survey design, there are different design options with respect to the time period, respondent group, variable choice, data collection and analytical method involved. These design features are described below ( Williamson & Johanson, 2013 ).

13.2.1. The Purpose of Surveys

There are three broad types of survey studies reported in the eHealth literature: exploratory, descriptive, and explanatory surveys. They are described below.

• Exploratory Surveys – These studies are used to investigate and understand a particular issue or topic area without predetermined notions of the expected responses. The design is mostly qualitative in nature, seeking input from respondents with open-ended questions focused on why and/or how they perceive certain aspects of an eHealth system. An example is the survey by Wells, Rozenblum, Park, Dunn, and Bates (2014) to identify organizational strategies that promote provider and patient uptake of phr s.
• Descriptive Surveys – These studies are used to describe the perception of respondents and the association of their characteristics with an eHealth system. Perception can be the attitudes, behaviours and reported interactions of respondents with the eHealth system. Association refers to an observed correlation between certain respondent characteristics and the system, such as prior eHealth experience. The design is mostly quantitative and involves the use of descriptive statistics such as frequency distributions of Likert scale responses from participants. An example is the survey on change in end user satisfaction with cpoe over time in intensive care ( Hoonakker et al., 2013 ).
• Explanatory Surveys – These studies are used to explain or predict one or more hypothesized relationships between some respondent characteristics and the eHealth system. The design is quantitative, involving the use of inferential statistics such as regression and factor analysis to quantify the extent to which certain respondent characteristics lead to or are associated with specific outcomes. An example is the survey to model certain residential care facility characteristics as predictors of ehr use ( Holup, Dobbs, Meng, & Hyer, 2013 ).

13.2.2. Survey Design Options

Within the three broad types of survey studies one can further distinguish their design by time period, respondent group, variable choice, data collection and analytical method. These survey design options are described below.

• Time Period – Surveys can take on a cross-sectional or longitudinal design based on the time period involved. In cross-sectional design the survey takes place at one point in time giving a snapshot of the participant responses. In longitudinal design the survey is repeated two or more times within a specified period in order to detect changes in participant responses over time.
• Respondent Group – Surveys can involve a single or multiple cohorts of respondents. With multiple cohorts they are typically grouped by some characteristics for comparison such as age, sex, or eHealth use status (e.g., users versus non-users of emr ).
• Variable Choice – In quantitative surveys one needs to define the dependent and independent variables being studied. A dependent variable refers to the perceived outcome that is measured, whereas an independent variable refers to a respondent characteristic that may influence the outcome (such as age). Typically the variables are defined using a scale that can be nominal, ordinal, interval, or ratio in nature ( Layman & Watzlaf, 2009 ). In a nominal scale, a value is assigned to each response such as 1 or F for female and 2 or M for male. In an ordinal scale, the response can be rank ordered such as user satisfaction that starts from 1 for very unsatisfied to 4 for very satisfied. Interval and ratio scales have numerical meaning where the distance between two responses relate to the numerical values assigned. Ratio is different from interval in that it has a natural zero point. Two examples are weight as a ratio scale and temperature as an interval scale.
• Data Collection – Surveys can be conducted by questionnaire or by interview with structured, semi-structured or non-structured questions. Questionnaires can be administered by postal mail, telephone, e-mail, or through a website. Interviews can be conducted in-person or by phone individually or in groups. Pretesting or pilot testing of the instrument should be done with a small number of individuals to ensure its content, flow and instructions are clear, consistent, appropriate and easy to follow. Usually there are one or more follow-up reminders sent to increase the response rate.
• Analytical Method – Survey responses are analyzed in different ways depending on the type of data collected. For textual data such qualitative analyses as content or thematic analysis can be used. Content analysis focuses on classifying words and phrases within the texts into categories based on some initial coding scheme and frequency counts. Thematic analysis focuses on identifying concepts, relationships and patterns from texts as themes. For numeric data, quantitative analysis such as descriptive and inferential statistics can be used. Descriptive statistics involves the use of such measures as mean, range, standard deviation and frequency to summarize the distribution of numeric data. Inferential statistics involve the use of a random sample of data from the study population to make inferences about that population. The inferences are made with parametric and non-parametric tests and multivariate methods. Pearson correlation, t -test and analysis of variance are examples of parametric tests. Sign test, Mann-Witney U test and χ 2 are examples of non-parametric tests. Multiple regression, multivariate analysis of variance, and factor analysis are examples of multivariate methods ( Forza, 2002 ).

13.3. Methodological Considerations

The quality of survey studies is dependent on a number of design parameters. These include population and sample, survey instrument, sources of bias, and adherence to reporting standards. These considerations are described below ( Williamson & Johanson, 2013 ).

13.3.1. Population and Sample

For practical reasons, survey studies are often done on a sample of individuals rather than the entire population. Sampling frame refers to the population of interest from which a representative sample is drawn for the study. The two common strategies used to select the study sample are probability and non-probability sampling. These are described below.

• Probability sampling – This is used in descriptive and explanatory surveys where the sample selected is based on the statistical probability of each individual being included under the assumption of normal distribution. They include such methods as simple random, systematic, stratified, and cluster sampling. The desired confidence level and margin of error are used to determine the required sample size. For example, in a population of 250,000 at 95% confidence level and a ±5% margin of error, a sample of 384 individuals is needed (Research Advisors, n.d.).
• Non-probability sampling – This is used in exploratory surveys where individuals with specific characteristics that can help understand the topic being investigated are selected as the sample. They include such non-statistical methods as convenience, snowball, quota, and purposeful sampling. For example, to study the effects of the Internet on patients with chronic conditions one can employ purposeful sampling where only individuals known to have a chronic disease and access to the Internet are selected for inclusion.

13.3.2. Survey Instrument

The survey instrument is the tool used to collect data from respondents on the topic being investigated. Ideally one should demonstrate that the survey instrument chosen is both valid and reliable for use in the study. Validity refers to whether the items (i.e., predefined questions and responses) in the instrument are accurate in what they intend to measure. Reliability refers to the extent to which the data collected are reproducible when repeated on the same or similar groups of respondents. These two constructs are elaborated below.

• Validity – The four types of validity are known as face, content, criterion, and construct validity. Face and content validity are qualitative assessments of the survey instrument for its clarity, comprehensibility and appropriateness. While face validity is typically assessed informally by non-experts, content validity is done formally by experts in the subject matter under study. Criterion and construct validity are quantitative assessments where the instrument is measured against other schemes. In criterion validity the instrument is compared with another reputable test on the same respondents, or against actual future outcomes for the survey’s predictive ability. In construct validity the instrument is compared with the theoretical concepts that the instrument purports to represent to see how well the two align with each other.
• Reliability – The tests for reliability include test-retest, alternate form and internal consistency. Test-retest reliability correlates results from the same survey instrument administered to the same respondents over two time periods. Alternate form reliability correlates results from different versions of the same instrument on the same or similar individuals. Internal consistency reliability measures how well different items in the same survey that measure the same construct produce similar results.

13.3.3. Sources of Bias

There are four potential sources of bias in survey studies. These are coverage, sampling, non-response, and measurement errors. These potential biases and ways to minimize them are described below.

• Coverage bias – This occurs when the sampling frame is not representative of the study population such that certain segments of the population are excluded or under-represented. For instance, the use of the telephone directory to select participants would exclude those with unlisted numbers and mobile devices. To address this error one needs to employ multiple sources to select samples that are more representative of the population. For example, in a telephone survey of consumers on their eHealth attitudes and experience, Ancker, Silver, Miller, and Kaushal (2013) included both landline and cell phone to recruit consumers since young adults, men and minorities tend to be under-represented among those with landlines.
• Sampling bias – This occurs when the sample selected for the study is not representative of the population such that the sample values cannot be generalized to the broader population. For example, in their survey of provider satisfaction and reported usage of cpoe , Lee, Teich, Spurr, and Bates (1996) reported different response rates between physicians and nurses, and between medical and surgical staffs, which could affect the generalizability of the results. To avoid sampling bias one should clearly define the target population and sampling frame, employ systematic methods such as stratified or random sampling to select samples, identify the extent and causes of response differences, and adjust the analysis and interpretation accordingly.
• Non-response bias – This occurs when individuals who responded to the survey have different attributes than those who did not respond to the survey. For example, in their study to model nurses’ acceptance of barcoded medication administration technology, Holden, Brown, Scanlon, and Karsh (2012) acknowledged their less than 50% response rate could have led to non-response bias affecting the accuracy of their prediction model. To address this error one can offer incentives to increase response rate, follow up with non-respondents to find out the reasons for their lack of response, or compare the characteristics of non-respondents with respondents or known external benchmarks for differences ( King & He, 2005 ). Adjustments can then be made when the cause and extent of non-response are known.
• Measurement bias – This occurs when there is a difference between the survey results obtained and the true values in the population. One major cause is deficient instrument design due to ambiguous items, unclear instructions, or poor usability. To reduce measurement bias one should apply good survey design practices, adequate pretesting or pilot testing of the instrument, and formal tests for validity and reliability. An example of good Web-based eHealth survey design guidelines is the Checklist for Reporting Results of Internet E-Surveys ( cherries ) by Eysenbach (2004) . The checklist has eight item categories and 31 individual items that can be used by authors to ensure quality design and reporting of their survey studies.

13.3.4. Adherence to Reporting Standards

Currently there are no universally accepted guidelines or standards for reporting survey studies. In the field of management information systems ( mis ), Grover, Lee, and Durand (1993) published nine ideal survey methodological attributes for analyzing the quality of mis survey research. In their review of ideal survey methodological attributes, Ju, Chen, Sun, and Wu (2006) found two frequent problems in survey studies published in three top mis journals to be the failure to perform statistical tests for non-response errors and not using multiple data collection methods. In healthcare, Kelly, Clark, Brown, and Sitzia (2003) published a checklist of seven key points to be covered when reporting survey studies. They are listed below:

• Explain the purpose of the study with explicit mention of the research question.
• Explain why the research is needed and mention previous work to provide context.
• Provide detail on how study was done that covers: the method and rationale; the instrument with its psychometric properties and references to original development/testing; sample selection and data collection processes.
• Describe and justify the analytical methods used.
• Present the results in a concise and factual manner.
• Interpret and discuss the findings.
• Present conclusions and recommendations.

In eHealth, Bassi, Lau, and Lesperance (2012) published a review of survey-based studies on the perceived impact of emr in physician office practices. In the review they used the 9-item assessment tool developed by Grover and colleagues (1993) to appraise the reporting quality of 19 emr survey studies. Using the 9-item tool a score from 0 to 1 was assigned depending on whether the attribute was present or absent, giving a maximum score of 9. Of the 19 survey studies appraised, the quality scores ranged from 0.5 to 8. Over half of the studies did not include a data collection method, the instrument and its validation with respect to pretesting or pilot testing, and non-respondent testing. Only two studies scored 7 or higher which suggested the reporting of the 19 published emr survey studies was highly variable. The criteria used in the 9-item tool are listed below.

• Report the approach used to randomize or select samples.
• Report a profile of the sample frame.
• Report characteristics of the respondents.
• Use a combination of personal, telephone and mail data collection methods.
• Append the whole or part of the questionnaire in the publication.
• Adopt a validated instrument or perform a validity or reliability analysis.
• Perform an instrument pretest.
• Report on the response rate.
• Perform a statistical test to justify the loss of data from non-respondents.

13.4. Case Examples

13.4.1. clinical informatics governance for ehr in nursing.

Collins, Alexander, and Moss (2015) conducted an exploratory survey study to understand clinical informatics ( ci ) governance for nursing and to propose a governance model with recommended roles, partnerships and councils for ehr adoption and optimization. The study is summarized below.

• Setting – Integrated healthcare systems in the United States with at least one acute care hospital that had pioneered enterprise-wide ehr implementation projects and had reached the Health Information Management Systems Society ( himss ) Analytics’ emr Adoption Model ( emram ) level 6 or greater, or were undergoing enterprise-wide integration, standardization and optimization of existing ehr systems across sites.
• Population and samples – Nursing informatics leaders in the role of an executive in an integrated healthcare system who could offer their perspective and lessons learned in their organization’s clinical and nursing informatics governance structure and its evolution. The sampling frame was the himss Analytics database that contains detailed information on most u.S. healthcare organizations and their health it status.
• Design – A cross-sectional survey conducted through semi-structured telephone interviews with probing questions.
• Measures – The survey had four sections: (a) organizational characteristics; (b) participant characteristics; (c) governance structure; and (d) lessons learned. Questions on governance covered decision-making, committees, collaboration, roles, and facilitators/barriers for success in overall and nursing-specific ci governance.
• Analysis – Grounded theory techniques of open, axial and selective coding were used to identify overlapping themes on governance structures and ci roles. Data were collected until thematic saturation in open coding was reached. The ci structures of each organization were drawn, compared and synthesized into a proposed model of ci roles, partnerships and councils for nursing. Initial coding was independently validated among the researchers and group consensus was used in thematic coding to develop the model.
• Results – Twelve nursing executives (made up of six chief nursing information officers, four directors of nursing informatics, one chief information officer, and one chief ci officer) were interviewed by phone. For analysis 128 open codes were created and organized into 18 axial coding categories where further selective coding led to four high-level themes for the proposed model. The four themes (with lessons learned included) identified as important are: inter-professional partnerships; defining role-based levels of practice and competence; integration into existing clinical infrastructure; and governance as an evolving process.
• Conclusion – The proposed ci governance model can help understand, shape and standardize roles, competencies and structures in ci practices for nursing, as well as be extended to other domains.

13.4.2. Primary Care EMR Adoption, Use and Impacts

Paré et al. (2013) conducted a descriptive survey study to examine the adoption, use and impacts of primary care emr s in a Canadian province. The study is summarized below.

• Setting – Primary care clinics in the Canadian Province of Quebec that had adopted electronic medical records under the provincial government’s emr adoption incentive and accreditation programs.
• Population and samples – The population consisted of family physicians as members of the Quebec Federation of General Practitioners that practice in primary care clinics in the province. The sample had three types of physician respondents that: (a) had not adopted emr (type-1); (b) had emr in their clinic but were not using it to support their practice (type-2); or (c) used emr in their clinic to support their practice (type-3).
• Design – A cross-sectional survey in the form of a pretested online questionnaire in English and French accessible via a secure website. E-mail invitations were sent to all members followed by an e-mail reminder. With a sampling frame of 9,166 active family physicians in Quebec, 370 responses would be needed to obtain a representative sample with a 95% confidence interval and a margin of error of ±5%.
• Measures – For all three respondent types the measures were clinic and socio-demographic profiles and comments. For type-2 and type-3 respondents, the measures were emr brand and year of implementation. For type-1 the measures were barriers and intent to adopt emr . For type-2 the measures were reasons and influencing factors for not using emr , and intent to use emr in future. For type-3 the measures were emr use experience, level and satisfaction, ease of use with advanced emr features, and individual/organizational impacts associated with emr use.
• Analysis – Descriptive statistics in frequencies, per cent and mean Likert scores were used on selected measures. Key analyses included comparison of frequencies by: socio-demographic and clinic profiles; barrier and adoption intent; emr feature availability and use; and comparison of mean Likert scores for satisfaction and individual and organizational impacts. Individual impacts included perceived efficiency, quality of care and work satisfaction. Organizational impacts included effects on clinical staff, the clinic’s financial position, and clients.
• Results – Of 4,845 invited physicians, 780 responded to the survey (16% response rate) that was representative of the population. Just over half of emr users reported the high cost and complexity in emr acquisition and deployment as the main barriers. Half of non-users reported their clinics intended to deploy emr in the next year. emr users made extensive use of basic emr features such as clinical notes, lab results and scheduling, but few used clinical decision support and data sharing features. For work organization, emr s addressed logistical issues with paper systems. For care quality, emr s improved the quality of clinical notes and safety of care provided but not clinical decision-making. For care continuity, emr s had poor ability to transfer clinical data among providers.
• Conclusion – emr impacts related to a physician’s experience where the perceived benefits were tied to the duration of emr use. Health organizations should continue to certify emr products to ensure alignment with the provincial ehr .

13.4.3. Nurses’ Acceptance of Barcoded Medication Administration Technology

Holden and colleagues (2012) conducted an explanatory survey study to identify predictors of nurses’ acceptance of barcoded medication administration ( bcma ) in a u.S. pediatric hospital. The study is summarized below.

• Setting – A 236-bed free standing academic pediatric hospital in the midwestern U.S. that had recently adopted bcma . The hospital also had cpoe , a pharmacy information system and automated medication-dispensing units.
• Population and Sample – The population consisted of registered nurses that worked at least 24 hours per week at the hospital. The sample consisted of nurses from three care units that had used bcma for three or more months.
• Design – A cross-sectional paper survey with reminders was conducted to test the hypothesis that bcma acceptance would be best predicted by a larger set of contextualized variables than the base variables in the Technology Acceptance Model ( tam ). A multi-item scales survey instrument, validated in previous studies with several added items, was used. The psychometric properties of the survey scales were pretested with 16 non-study nurses.
• Measures – Seven bcma -related perceptions: ease of use, usefulness for the job, non-specific social influence, training, technical support, usefulness for patient care, and social influence from patients/families. Responses were 7-point scales from not-at-all to a-great-deal. Also tracked were variables for age in five categories, as well as experience measured as job tenure in years and months. Two bcma acceptance variables: behavioural intention to use and satisfaction.
• Analysis – Regression of all subsets of perceptions to identify the best predictors of bcma acceptance using five goodness-of-fit indicators (i.e., R 2 , root mean square error, Mallow’s Cp statistics, Akaike information criterion, and Bayesian information criterion). An a priori α criterion of 0.05 was used and 95% confidence intervals were computed around parameter estimates.
• Results – Ninety-four of 202 nurses returned a survey (46.5% response rate) but 11 worked less than 24 hours per week and were excluded, leaving a final sample of 83 respondents. Nurses perceived moderate ease of use and low usefulness of bcma . They perceived moderate or higher social influence to use bcma , and were moderately positive about bcma training and technical support. Behavioural intention to use bcma was high but satisfaction was low. Behavioural intention to use bcma was best predicted by perceived ease of use, non-specific social influence and usefulness for patient care (56% variance explained). Satisfaction was best predicted by perceived ease of use, usefulness for patient care and social influence from patients/families (76% variances explained).
• Conclusion – Predicting bcma acceptance benefited from using a larger set of perceptions and adapting variables.

13.5. Summary

This chapter introduced three types of surveys, namely exploratory, descriptive and explanatory surveys. The methodological considerations addressed included population and sample, survey instrument, variable choice and reporting standards. Three case examples were also included to show how eHealth survey studies are done.

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• Bassi J., Lau F., Lesperance M. Perceived impact of electronic medical records in physician office practices: A review of survey-based research. Interactive Journal of Medical Research. 2012; 1 (2):e3.1–e3.23. [ PMC free article : PMC3626136 ] [ PubMed : 23611832 ]
• Chiang M. F., Boland M. V., Margolis J. W., Lum F., Abramoff M. D., Hildbrand L. Adoption and perceptions of electronic health record systems by ophthalmologists: An American Academy of Ophthalmology survey. Ophthalmology. 2008; 115 (9):1591–1597. [ PubMed : 18486218 ]
• Collins S. A., Alexander D., Moss J. Nursing domain of ci governance: recommendations for health it adoption and optimization. Journal of American Medical Informatics Association. 2015; 22 (3):697–706. [ PubMed : 25670752 ]
• Eysenbach G. Improving the quality of web surveys: the checklist for reporting results of Internet e-surveys ( cherries ). Journal of Medical Internet Research. 2004; 6 (3):e34. [ PMC free article : PMC1550605 ] [ PubMed : 15471760 ]
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Home » Research Design – Types, Methods and Examples

Research Design – Types, Methods and Examples

Table of Contents

Research Design

Definition:

Research design refers to the overall strategy or plan for conducting a research study. It outlines the methods and procedures that will be used to collect and analyze data, as well as the goals and objectives of the study. Research design is important because it guides the entire research process and ensures that the study is conducted in a systematic and rigorous manner.

Types of Research Design

Types of Research Design are as follows:

Descriptive Research Design

This type of research design is used to describe a phenomenon or situation. It involves collecting data through surveys, questionnaires, interviews, and observations. The aim of descriptive research is to provide an accurate and detailed portrayal of a particular group, event, or situation. It can be useful in identifying patterns, trends, and relationships in the data.

Correlational Research Design

Correlational research design is used to determine if there is a relationship between two or more variables. This type of research design involves collecting data from participants and analyzing the relationship between the variables using statistical methods. The aim of correlational research is to identify the strength and direction of the relationship between the variables.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This type of research design involves manipulating one variable and measuring the effect on another variable. It usually involves randomly assigning participants to groups and manipulating an independent variable to determine its effect on a dependent variable. The aim of experimental research is to establish causality.

Quasi-experimental Research Design

Quasi-experimental research design is similar to experimental research design, but it lacks one or more of the features of a true experiment. For example, there may not be random assignment to groups or a control group. This type of research design is used when it is not feasible or ethical to conduct a true experiment.

Case Study Research Design

Case study research design is used to investigate a single case or a small number of cases in depth. It involves collecting data through various methods, such as interviews, observations, and document analysis. The aim of case study research is to provide an in-depth understanding of a particular case or situation.

Longitudinal Research Design

Longitudinal research design is used to study changes in a particular phenomenon over time. It involves collecting data at multiple time points and analyzing the changes that occur. The aim of longitudinal research is to provide insights into the development, growth, or decline of a particular phenomenon over time.

Structure of Research Design

The format of a research design typically includes the following sections:

• Introduction : This section provides an overview of the research problem, the research questions, and the importance of the study. It also includes a brief literature review that summarizes previous research on the topic and identifies gaps in the existing knowledge.
• Research Questions or Hypotheses: This section identifies the specific research questions or hypotheses that the study will address. These questions should be clear, specific, and testable.
• Research Methods : This section describes the methods that will be used to collect and analyze data. It includes details about the study design, the sampling strategy, the data collection instruments, and the data analysis techniques.
• Data Collection: This section describes how the data will be collected, including the sample size, data collection procedures, and any ethical considerations.
• Data Analysis: This section describes how the data will be analyzed, including the statistical techniques that will be used to test the research questions or hypotheses.
• Results : This section presents the findings of the study, including descriptive statistics and statistical tests.
• Discussion and Conclusion : This section summarizes the key findings of the study, interprets the results, and discusses the implications of the findings. It also includes recommendations for future research.
• References : This section lists the sources cited in the research design.

Example of Research Design

An Example of Research Design could be:

Research question: Does the use of social media affect the academic performance of high school students?

Research design:

• Research approach : The research approach will be quantitative as it involves collecting numerical data to test the hypothesis.
• Research design : The research design will be a quasi-experimental design, with a pretest-posttest control group design.
• Sample : The sample will be 200 high school students from two schools, with 100 students in the experimental group and 100 students in the control group.
• Data collection : The data will be collected through surveys administered to the students at the beginning and end of the academic year. The surveys will include questions about their social media usage and academic performance.
• Data analysis : The data collected will be analyzed using statistical software. The mean scores of the experimental and control groups will be compared to determine whether there is a significant difference in academic performance between the two groups.
• Limitations : The limitations of the study will be acknowledged, including the fact that social media usage can vary greatly among individuals, and the study only focuses on two schools, which may not be representative of the entire population.
• Ethical considerations: Ethical considerations will be taken into account, such as obtaining informed consent from the participants and ensuring their anonymity and confidentiality.

How to Write Research Design

Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design:

• Define the research question or hypothesis : Before beginning your research design, you should clearly define your research question or hypothesis. This will guide your research design and help you select appropriate methods.
• Select a research design: There are many different research designs to choose from, including experimental, survey, case study, and qualitative designs. Choose a design that best fits your research question and objectives.
• Develop a sampling plan : If your research involves collecting data from a sample, you will need to develop a sampling plan. This should outline how you will select participants and how many participants you will include.
• Define variables: Clearly define the variables you will be measuring or manipulating in your study. This will help ensure that your results are meaningful and relevant to your research question.
• Choose data collection methods : Decide on the data collection methods you will use to gather information. This may include surveys, interviews, observations, experiments, or secondary data sources.
• Create a data analysis plan: Develop a plan for analyzing your data, including the statistical or qualitative techniques you will use.
• Consider ethical concerns : Finally, be sure to consider any ethical concerns related to your research, such as participant confidentiality or potential harm.

When to Write Research Design

Research design should be written before conducting any research study. It is an important planning phase that outlines the research methodology, data collection methods, and data analysis techniques that will be used to investigate a research question or problem. The research design helps to ensure that the research is conducted in a systematic and logical manner, and that the data collected is relevant and reliable.

Ideally, the research design should be developed as early as possible in the research process, before any data is collected. This allows the researcher to carefully consider the research question, identify the most appropriate research methodology, and plan the data collection and analysis procedures in advance. By doing so, the research can be conducted in a more efficient and effective manner, and the results are more likely to be valid and reliable.

Purpose of Research Design

The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection and analysis.

Some of the key purposes of research design include:

• Providing a clear and concise plan of action for the research study.
• Ensuring that the research is conducted ethically and with rigor.
• Maximizing the accuracy and reliability of the research findings.
• Minimizing the possibility of errors, biases, or confounding variables.
• Ensuring that the research is feasible, practical, and cost-effective.
• Determining the appropriate research methodology to answer the research question(s).
• Identifying the sample size, sampling method, and data collection techniques.
• Determining the data analysis method and statistical tests to be used.
• Facilitating the replication of the study by other researchers.
• Enhancing the validity and generalizability of the research findings.

Applications of Research Design

There are numerous applications of research design in various fields, some of which are:

• Social sciences: In fields such as psychology, sociology, and anthropology, research design is used to investigate human behavior and social phenomena. Researchers use various research designs, such as experimental, quasi-experimental, and correlational designs, to study different aspects of social behavior.
• Education : Research design is essential in the field of education to investigate the effectiveness of different teaching methods and learning strategies. Researchers use various designs such as experimental, quasi-experimental, and case study designs to understand how students learn and how to improve teaching practices.
• Health sciences : In the health sciences, research design is used to investigate the causes, prevention, and treatment of diseases. Researchers use various designs, such as randomized controlled trials, cohort studies, and case-control studies, to study different aspects of health and healthcare.
• Business : Research design is used in the field of business to investigate consumer behavior, marketing strategies, and the impact of different business practices. Researchers use various designs, such as survey research, experimental research, and case studies, to study different aspects of the business world.
• Engineering : In the field of engineering, research design is used to investigate the development and implementation of new technologies. Researchers use various designs, such as experimental research and case studies, to study the effectiveness of new technologies and to identify areas for improvement.

Advantages of Research Design

Here are some advantages of research design:

• Systematic and organized approach : A well-designed research plan ensures that the research is conducted in a systematic and organized manner, which makes it easier to manage and analyze the data.
• Clear objectives: The research design helps to clarify the objectives of the study, which makes it easier to identify the variables that need to be measured, and the methods that need to be used to collect and analyze data.
• Minimizes bias: A well-designed research plan minimizes the chances of bias, by ensuring that the data is collected and analyzed objectively, and that the results are not influenced by the researcher’s personal biases or preferences.
• Efficient use of resources: A well-designed research plan helps to ensure that the resources (time, money, and personnel) are used efficiently and effectively, by focusing on the most important variables and methods.
• Replicability: A well-designed research plan makes it easier for other researchers to replicate the study, which enhances the credibility and reliability of the findings.
• Validity: A well-designed research plan helps to ensure that the findings are valid, by ensuring that the methods used to collect and analyze data are appropriate for the research question.
• Generalizability : A well-designed research plan helps to ensure that the findings can be generalized to other populations, settings, or situations, which increases the external validity of the study.

Research Design Vs Research Methodology

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Researcher, Academic Writer, Web developer

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Writing Survey Questions

Perhaps the most important part of the survey process is the creation of questions that accurately measure the opinions, experiences and behaviors of the public. Accurate random sampling will be wasted if the information gathered is built on a shaky foundation of ambiguous or biased questions. Creating good measures involves both writing good questions and organizing them to form the questionnaire.

Questionnaire design is a multistage process that requires attention to many details at once. Designing the questionnaire is complicated because surveys can ask about topics in varying degrees of detail, questions can be asked in different ways, and questions asked earlier in a survey may influence how people respond to later questions. Researchers are also often interested in measuring change over time and therefore must be attentive to how opinions or behaviors have been measured in prior surveys.

Surveyors may conduct pilot tests or focus groups in the early stages of questionnaire development in order to better understand how people think about an issue or comprehend a question. Pretesting a survey is an essential step in the questionnaire design process to evaluate how people respond to the overall questionnaire and specific questions, especially when questions are being introduced for the first time.

For many years, surveyors approached questionnaire design as an art, but substantial research over the past forty years has demonstrated that there is a lot of science involved in crafting a good survey questionnaire. Here, we discuss the pitfalls and best practices of designing questionnaires.

Question development

There are several steps involved in developing a survey questionnaire. The first is identifying what topics will be covered in the survey. For Pew Research Center surveys, this involves thinking about what is happening in our nation and the world and what will be relevant to the public, policymakers and the media. We also track opinion on a variety of issues over time so we often ensure that we update these trends on a regular basis to better understand whether people’s opinions are changing.

At Pew Research Center, questionnaire development is a collaborative and iterative process where staff meet to discuss drafts of the questionnaire several times over the course of its development. We frequently test new survey questions ahead of time through qualitative research methods such as  focus groups , cognitive interviews, pretesting (often using an  online, opt-in sample ), or a combination of these approaches. Researchers use insights from this testing to refine questions before they are asked in a production survey, such as on the ATP.

Measuring change over time

Many surveyors want to track changes over time in people’s attitudes, opinions and behaviors. To measure change, questions are asked at two or more points in time. A cross-sectional design surveys different people in the same population at multiple points in time. A panel, such as the ATP, surveys the same people over time. However, it is common for the set of people in survey panels to change over time as new panelists are added and some prior panelists drop out. Many of the questions in Pew Research Center surveys have been asked in prior polls. Asking the same questions at different points in time allows us to report on changes in the overall views of the general public (or a subset of the public, such as registered voters, men or Black Americans), or what we call “trending the data”.

When measuring change over time, it is important to use the same question wording and to be sensitive to where the question is asked in the questionnaire to maintain a similar context as when the question was asked previously (see  question wording  and  question order  for further information). All of our survey reports include a topline questionnaire that provides the exact question wording and sequencing, along with results from the current survey and previous surveys in which we asked the question.

The Center’s transition from conducting U.S. surveys by live telephone interviewing to an online panel (around 2014 to 2020) complicated some opinion trends, but not others. Opinion trends that ask about sensitive topics (e.g., personal finances or attending religious services ) or that elicited volunteered answers (e.g., “neither” or “don’t know”) over the phone tended to show larger differences than other trends when shifting from phone polls to the online ATP. The Center adopted several strategies for coping with changes to data trends that may be related to this change in methodology. If there is evidence suggesting that a change in a trend stems from switching from phone to online measurement, Center reports flag that possibility for readers to try to head off confusion or erroneous conclusions.

Open- and closed-ended questions

One of the most significant decisions that can affect how people answer questions is whether the question is posed as an open-ended question, where respondents provide a response in their own words, or a closed-ended question, where they are asked to choose from a list of answer choices.

For example, in a poll conducted after the 2008 presidential election, people responded very differently to two versions of the question: “What one issue mattered most to you in deciding how you voted for president?” One was closed-ended and the other open-ended. In the closed-ended version, respondents were provided five options and could volunteer an option not on the list.

When explicitly offered the economy as a response, more than half of respondents (58%) chose this answer; only 35% of those who responded to the open-ended version volunteered the economy. Moreover, among those asked the closed-ended version, fewer than one-in-ten (8%) provided a response other than the five they were read. By contrast, fully 43% of those asked the open-ended version provided a response not listed in the closed-ended version of the question. All of the other issues were chosen at least slightly more often when explicitly offered in the closed-ended version than in the open-ended version. (Also see  “High Marks for the Campaign, a High Bar for Obama”  for more information.)

Researchers will sometimes conduct a pilot study using open-ended questions to discover which answers are most common. They will then develop closed-ended questions based off that pilot study that include the most common responses as answer choices. In this way, the questions may better reflect what the public is thinking, how they view a particular issue, or bring certain issues to light that the researchers may not have been aware of.

When asking closed-ended questions, the choice of options provided, how each option is described, the number of response options offered, and the order in which options are read can all influence how people respond. One example of the impact of how categories are defined can be found in a Pew Research Center poll conducted in January 2002. When half of the sample was asked whether it was “more important for President Bush to focus on domestic policy or foreign policy,” 52% chose domestic policy while only 34% said foreign policy. When the category “foreign policy” was narrowed to a specific aspect – “the war on terrorism” – far more people chose it; only 33% chose domestic policy while 52% chose the war on terrorism.

In most circumstances, the number of answer choices should be kept to a relatively small number – just four or perhaps five at most – especially in telephone surveys. Psychological research indicates that people have a hard time keeping more than this number of choices in mind at one time. When the question is asking about an objective fact and/or demographics, such as the religious affiliation of the respondent, more categories can be used. In fact, they are encouraged to ensure inclusivity. For example, Pew Research Center’s standard religion questions include more than 12 different categories, beginning with the most common affiliations (Protestant and Catholic). Most respondents have no trouble with this question because they can expect to see their religious group within that list in a self-administered survey.

In addition to the number and choice of response options offered, the order of answer categories can influence how people respond to closed-ended questions. Research suggests that in telephone surveys respondents more frequently choose items heard later in a list (a “recency effect”), and in self-administered surveys, they tend to choose items at the top of the list (a “primacy” effect).

Because of concerns about the effects of category order on responses to closed-ended questions, many sets of response options in Pew Research Center’s surveys are programmed to be randomized to ensure that the options are not asked in the same order for each respondent. Rotating or randomizing means that questions or items in a list are not asked in the same order to each respondent. Answers to questions are sometimes affected by questions that precede them. By presenting questions in a different order to each respondent, we ensure that each question gets asked in the same context as every other question the same number of times (e.g., first, last or any position in between). This does not eliminate the potential impact of previous questions on the current question, but it does ensure that this bias is spread randomly across all of the questions or items in the list. For instance, in the example discussed above about what issue mattered most in people’s vote, the order of the five issues in the closed-ended version of the question was randomized so that no one issue appeared early or late in the list for all respondents. Randomization of response items does not eliminate order effects, but it does ensure that this type of bias is spread randomly.

Questions with ordinal response categories – those with an underlying order (e.g., excellent, good, only fair, poor OR very favorable, mostly favorable, mostly unfavorable, very unfavorable) – are generally not randomized because the order of the categories conveys important information to help respondents answer the question. Generally, these types of scales should be presented in order so respondents can easily place their responses along the continuum, but the order can be reversed for some respondents. For example, in one of Pew Research Center’s questions about abortion, half of the sample is asked whether abortion should be “legal in all cases, legal in most cases, illegal in most cases, illegal in all cases,” while the other half of the sample is asked the same question with the response categories read in reverse order, starting with “illegal in all cases.” Again, reversing the order does not eliminate the recency effect but distributes it randomly across the population.

Question wording

The choice of words and phrases in a question is critical in expressing the meaning and intent of the question to the respondent and ensuring that all respondents interpret the question the same way. Even small wording differences can substantially affect the answers people provide.

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An example of a wording difference that had a significant impact on responses comes from a January 2003 Pew Research Center survey. When people were asked whether they would “favor or oppose taking military action in Iraq to end Saddam Hussein’s rule,” 68% said they favored military action while 25% said they opposed military action. However, when asked whether they would “favor or oppose taking military action in Iraq to end Saddam Hussein’s rule  even if it meant that U.S. forces might suffer thousands of casualties, ” responses were dramatically different; only 43% said they favored military action, while 48% said they opposed it. The introduction of U.S. casualties altered the context of the question and influenced whether people favored or opposed military action in Iraq.

There has been a substantial amount of research to gauge the impact of different ways of asking questions and how to minimize differences in the way respondents interpret what is being asked. The issues related to question wording are more numerous than can be treated adequately in this short space, but below are a few of the important things to consider:

First, it is important to ask questions that are clear and specific and that each respondent will be able to answer. If a question is open-ended, it should be evident to respondents that they can answer in their own words and what type of response they should provide (an issue or problem, a month, number of days, etc.). Closed-ended questions should include all reasonable responses (i.e., the list of options is exhaustive) and the response categories should not overlap (i.e., response options should be mutually exclusive). Further, it is important to discern when it is best to use forced-choice close-ended questions (often denoted with a radio button in online surveys) versus “select-all-that-apply” lists (or check-all boxes). A 2019 Center study found that forced-choice questions tend to yield more accurate responses, especially for sensitive questions.  Based on that research, the Center generally avoids using select-all-that-apply questions.

It is also important to ask only one question at a time. Questions that ask respondents to evaluate more than one concept (known as double-barreled questions) – such as “How much confidence do you have in President Obama to handle domestic and foreign policy?” – are difficult for respondents to answer and often lead to responses that are difficult to interpret. In this example, it would be more effective to ask two separate questions, one about domestic policy and another about foreign policy.

In general, questions that use simple and concrete language are more easily understood by respondents. It is especially important to consider the education level of the survey population when thinking about how easy it will be for respondents to interpret and answer a question. Double negatives (e.g., do you favor or oppose  not  allowing gays and lesbians to legally marry) or unfamiliar abbreviations or jargon (e.g., ANWR instead of Arctic National Wildlife Refuge) can result in respondent confusion and should be avoided.

Similarly, it is important to consider whether certain words may be viewed as biased or potentially offensive to some respondents, as well as the emotional reaction that some words may provoke. For example, in a 2005 Pew Research Center survey, 51% of respondents said they favored “making it legal for doctors to give terminally ill patients the means to end their lives,” but only 44% said they favored “making it legal for doctors to assist terminally ill patients in committing suicide.” Although both versions of the question are asking about the same thing, the reaction of respondents was different. In another example, respondents have reacted differently to questions using the word “welfare” as opposed to the more generic “assistance to the poor.” Several experiments have shown that there is much greater public support for expanding “assistance to the poor” than for expanding “welfare.”

We often write two versions of a question and ask half of the survey sample one version of the question and the other half the second version. Thus, we say we have two  forms  of the questionnaire. Respondents are assigned randomly to receive either form, so we can assume that the two groups of respondents are essentially identical. On questions where two versions are used, significant differences in the answers between the two forms tell us that the difference is a result of the way we worded the two versions.

One of the most common formats used in survey questions is the “agree-disagree” format. In this type of question, respondents are asked whether they agree or disagree with a particular statement. Research has shown that, compared with the better educated and better informed, less educated and less informed respondents have a greater tendency to agree with such statements. This is sometimes called an “acquiescence bias” (since some kinds of respondents are more likely to acquiesce to the assertion than are others). This behavior is even more pronounced when there’s an interviewer present, rather than when the survey is self-administered. A better practice is to offer respondents a choice between alternative statements. A Pew Research Center experiment with one of its routinely asked values questions illustrates the difference that question format can make. Not only does the forced choice format yield a very different result overall from the agree-disagree format, but the pattern of answers between respondents with more or less formal education also tends to be very different.

One other challenge in developing questionnaires is what is called “social desirability bias.” People have a natural tendency to want to be accepted and liked, and this may lead people to provide inaccurate answers to questions that deal with sensitive subjects. Research has shown that respondents understate alcohol and drug use, tax evasion and racial bias. They also may overstate church attendance, charitable contributions and the likelihood that they will vote in an election. Researchers attempt to account for this potential bias in crafting questions about these topics. For instance, when Pew Research Center surveys ask about past voting behavior, it is important to note that circumstances may have prevented the respondent from voting: “In the 2012 presidential election between Barack Obama and Mitt Romney, did things come up that kept you from voting, or did you happen to vote?” The choice of response options can also make it easier for people to be honest. For example, a question about church attendance might include three of six response options that indicate infrequent attendance. Research has also shown that social desirability bias can be greater when an interviewer is present (e.g., telephone and face-to-face surveys) than when respondents complete the survey themselves (e.g., paper and web surveys).

Lastly, because slight modifications in question wording can affect responses, identical question wording should be used when the intention is to compare results to those from earlier surveys. Similarly, because question wording and responses can vary based on the mode used to survey respondents, researchers should carefully evaluate the likely effects on trend measurements if a different survey mode will be used to assess change in opinion over time.

Question order

Once the survey questions are developed, particular attention should be paid to how they are ordered in the questionnaire. Surveyors must be attentive to how questions early in a questionnaire may have unintended effects on how respondents answer subsequent questions. Researchers have demonstrated that the order in which questions are asked can influence how people respond; earlier questions can unintentionally provide context for the questions that follow (these effects are called “order effects”).

One kind of order effect can be seen in responses to open-ended questions. Pew Research Center surveys generally ask open-ended questions about national problems, opinions about leaders and similar topics near the beginning of the questionnaire. If closed-ended questions that relate to the topic are placed before the open-ended question, respondents are much more likely to mention concepts or considerations raised in those earlier questions when responding to the open-ended question.

For closed-ended opinion questions, there are two main types of order effects: contrast effects ( where the order results in greater differences in responses), and assimilation effects (where responses are more similar as a result of their order).

An example of a contrast effect can be seen in a Pew Research Center poll conducted in October 2003, a dozen years before same-sex marriage was legalized in the U.S. That poll found that people were more likely to favor allowing gays and lesbians to enter into legal agreements that give them the same rights as married couples when this question was asked after one about whether they favored or opposed allowing gays and lesbians to marry (45% favored legal agreements when asked after the marriage question, but 37% favored legal agreements without the immediate preceding context of a question about same-sex marriage). Responses to the question about same-sex marriage, meanwhile, were not significantly affected by its placement before or after the legal agreements question.

Another experiment embedded in a December 2008 Pew Research Center poll also resulted in a contrast effect. When people were asked “All in all, are you satisfied or dissatisfied with the way things are going in this country today?” immediately after having been asked “Do you approve or disapprove of the way George W. Bush is handling his job as president?”; 88% said they were dissatisfied, compared with only 78% without the context of the prior question.

Responses to presidential approval remained relatively unchanged whether national satisfaction was asked before or after it. A similar finding occurred in December 2004 when both satisfaction and presidential approval were much higher (57% were dissatisfied when Bush approval was asked first vs. 51% when general satisfaction was asked first).

Several studies also have shown that asking a more specific question before a more general question (e.g., asking about happiness with one’s marriage before asking about one’s overall happiness) can result in a contrast effect. Although some exceptions have been found, people tend to avoid redundancy by excluding the more specific question from the general rating.

Assimilation effects occur when responses to two questions are more consistent or closer together because of their placement in the questionnaire. We found an example of an assimilation effect in a Pew Research Center poll conducted in November 2008 when we asked whether Republican leaders should work with Obama or stand up to him on important issues and whether Democratic leaders should work with Republican leaders or stand up to them on important issues. People were more likely to say that Republican leaders should work with Obama when the question was preceded by the one asking what Democratic leaders should do in working with Republican leaders (81% vs. 66%). However, when people were first asked about Republican leaders working with Obama, fewer said that Democratic leaders should work with Republican leaders (71% vs. 82%).

The order questions are asked is of particular importance when tracking trends over time. As a result, care should be taken to ensure that the context is similar each time a question is asked. Modifying the context of the question could call into question any observed changes over time (see  measuring change over time  for more information).

A questionnaire, like a conversation, should be grouped by topic and unfold in a logical order. It is often helpful to begin the survey with simple questions that respondents will find interesting and engaging. Throughout the survey, an effort should be made to keep the survey interesting and not overburden respondents with several difficult questions right after one another. Demographic questions such as income, education or age should not be asked near the beginning of a survey unless they are needed to determine eligibility for the survey or for routing respondents through particular sections of the questionnaire. Even then, it is best to precede such items with more interesting and engaging questions. One virtue of survey panels like the ATP is that demographic questions usually only need to be asked once a year, not in each survey.

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ORIGINAL RESEARCH article

Increasing phd student self-awareness and self-confidence through strengths-based professional development submission type: research article provisionally accepted.

• 1 Department of Physiology, Pharmacology, and Toxicology, School of Medicine, West Virginia University, United States
• 2 Health Sciences Center, West Virginia University, United States

The final, formatted version of the article will be published soon.

Strengths-based programs have emerged as asset-based approaches to professional development that promote positive student engagement and success. This paper shares the outcomes of a strengths-based professional development program provided to biomedical and health sciences graduate doctoral students within an academic health center. Program outcomes and changes in participants’ perceived confidence when identifying and applying their strengths in different contexts were evaluated through a mixed methods design that included a Likert-based survey and thematic analysis of qualitative responses. Findings strongly suggest that most participants lacked the self-confidence and/or self-awareness to recognize their own strengths prior to the program. Themes that emerged upon implementation of the program point to the following outcomes: participants gained an increased understanding of their strengths, confidence that the knowledge gained about their strengths would help them learn more effectively in laboratory settings, an increased belief that they possess natural talents and skills that make them good scientists and strong members of their research team, and confidence that applying their strengths will help them to overcome both personal and professional challenges. This program shows promise to strengthen graduate student self-awareness and self-confidence. Further studies are needed to understand and measure how asset-based programs such as this can impact graduate student resilience, science identity, and overall student success.

Keywords: graduate, Strengths, Professional Development, biomedical, Health Sciences, Science identity, stem

Received: 31 Jan 2024; Accepted: 22 Apr 2024.

Copyright: © 2024 Lockman and Ferguson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Julie A. Lockman, West Virginia University, Department of Physiology, Pharmacology, and Toxicology, School of Medicine, Morgantown, United States

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