Response Scale Types 

choosing the best response scale for your survey

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Have you ever taken a survey or filled out a questionnaire and been unsure of how to respond? Response scales, or the set of options provided for participants to answer a question, play a crucial role in collecting accurate and meaningful data. 

However, not all response scales are created equal, and choosing the right one can be a challenge for researchers and survey designers. In this blog post, we’ll explore different types of response scales and their pros and cons, so you can make informed decisions when creating surveys or analyzing data. 

Whether you’re a seasoned researcher or just starting out, understanding the nuances of response scales can help you get more reliable results and make better decisions based on data. So let’s dive in! 

What is a Response Scale?

A response scale is a set of options or categories provided to participants in a survey or questionnaire to choose from when answering a question. It is used to measure the degree to which respondents agree or disagree with a statement, their level of satisfaction with a product, or any other variable of interest.

Response scales can take many different forms, including Likert scales, semantic differential scales, and visual analog scales, among others. The choice of response scale can have a significant impact on the accuracy and quality of the data collected, and it is important to carefully consider the pros and cons of different types of response scales when designing surveys or analyzing data. 

Benefits of Utilizing Response Scales

Response scales provide more specific feedback on how your audience is feeling without using open-ended questions. Using response scales over open-ended questions has several benefits:  


Response scales provide a standardized format for participants to answer a question, which helps ensure that everyone is interpreting and responding to the question in the same way. This can increase the reliability and validity of the data collected. 

For example, if you were to ask your patients the open-ended question: “What was your post-operative pain level?” You may get varying answers such as:  

  • I felt fine for the first six hours until the pain block wore off 
  • Never better
  • It felt different than the last surgery

Which can be very difficult to properly interpret or compare to other responses. 

Ease of Analysis

Responses on a response scale are typically numeric or categorical, which makes them easier to quantify and analyze than open-ended responses. This can save time and resources when it comes to data analysis. 

Greater Range of Responses

Response scales often provide a greater range of responses than open-ended questions, which can allow for more nuanced and detailed data. For example, a Likert scale might provide five or seven response options, allowing participants to indicate degrees of agreement or disagreement. 

Reduced Respondent Burden

Open-ended questions can be time-consuming and mentally taxing for participants, especially if they require a lot of thought or detail. Response scales can reduce respondent burden by providing a set of options to choose from, which can make it quicker and easier for participants to respond. 

While open-ended questions can be valuable in certain contexts, such as when exploring new or complex topics, response scales are often a more efficient and effective way to collect quantitative data. 

Survey Response Scale Types: Understanding Your Options

Conducting surveys is an effective way to gather feedback and insights from your target audience. However, choosing the right response scale type is crucial to obtaining accurate and meaningful results. 

Here are some common survey response scale types: 

Dichotomous or Binary Scale

This scale offers only two response options, such as “Yes/No” or “True/False”. This type of response scale is easy to understand and administer but can lack nuance and detail. 

Nominal Scale

A nominal scale provides several options, but they are not ordered or ranked. Examples include “gender” or “ethnicity”. Nominal scales allow for a larger range of responses than dichotomous scales, but do not provide any indication of the strength or direction of a participant’s opinion. 

Ordinal Scale

An ordinal scale provides options that are ordered or ranked. Examples include “strongly agree, agree, neutral, disagree, strongly disagree”. This type of response scale provides more information than nominal scales but does not provide information about the distance between options. 

Interval Scale

This scale measures the difference between two options but does not have an absolute zero point. 

Ratio Scale

This scale is similar to interval scale but has an absolute zero point, allowing for meaningful comparisons of magnitude. 

Likert Scale

The Likert scale asks respondents to rate their agreement or disagreement with a statement on a 5-point or 7-point scale. Below are some 5 point Likert scale sample response scales for reference.

Choosing the Best Survey Response Scale

Choosing the right response scale type depends on the goals and objectives of your survey. Consider factors such as the complexity of the survey question, the type of data you want to collect, and the demographics of your target audience. 

By using the appropriate survey response scale, you can obtain meaningful insights and take action to improve your products or services. 

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