To mitigate this effect, it is good practice to present the Likert scale item...

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Although it is true that respondents may not have a formed opinion on certain issues, supporters of omitting the core value argue that it is often used as a catch-all for those who do not want to spend a lot of time thinking about their answer and that the The presence of only positive or negative values ​​allows them to be forced to express their sincere opinion. You have to mix positive and negative statements Another very common bias that is observed when analyzing survey responses is that participants tend to agree with the statements presented or to indicate a positive attitude ( acquiescence or consent bias ).

by mixing positive and negative statements . The SUS questionnaire , used to measure the perceived usability of an interface or product, is designed in this way, asking participants to indicate their agreement or disagreement about statements such as: “I felt very comfortable using this website” Positive “I find this website very uncomfortable to use” Negative With the same objective of avoiding consent bias, it is advisable to formulate the statements as Brazil Mobile Number List questions rather than statements (to which participants usually agree by default). For example, ask: To what extent are you satisfied with the care you received? (From “very dissatisfied” to “very satisfied”) It is less subject to consent bias than the statement: I am satisfied with the care I received (from “Strongly disagree” to “Strongly agree”) Items must be grouped coherently Let's avoid jumping from one topic to another within the same list of items.



So that respondents can concentrate on their answers, the items on a Likert scale that are displayed together should address different aspects of the same topic. How to analyze data from a Likert scale The data from a Likert scale can be analyzed individually or aggregated, joining the responses of different items that deal with the same aspect. To analyze the data, a numerical value is assigned to the response options that reflects their position on the scale (hence the importance that the distances between the options are the same and as objective as possible). Totally agree (Value ) Agree (Value ) Neither agree nor disagree (Value ) Disagree (Value ) Totally disagree (Value ) The data is then analyzed by adding the values ​​relating to all user responses for each item and dividing it by the number of respondents.