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12 Reasons Why The 5-Point Likert Scale is a Universal Sentiment Measurement

You know those standardized COVID screening questions greeters (or security) ask at building entrances — the ones with only two possible answers?  Well, unlike those sorts of binary “yes or no” questions, few employee survey questions can be answered so affirmatively. Enter the 5-point Likert scale. 

We all have opinions of varying degrees. Bi-polar answer options that range from one extreme to another with a neutral midpoint choice for those “undecided” have made Likert’s original 5-point scale one of the most common tools in the scientific and academic community’s research toolkit for sentiment measurement.

5-point likert scale - woman on phone

About Likert Scales   

Early in his career, American social psychologist Rensis Likert saw a need to be able to measure peoples’ attitudes towards various issues. In 1932 as part of his Ph.D., he devised a way to identify a person’s perceptions and opinions and the factors that influence them. His research led him to develop a method of determining attitudes by presenting a statement and asking respondents to choose from a continuum of options to indicate the degree to which they agree. For example:

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1 = strongly disagree

2 = disagree

3 = neutral

4 = agree

5 = strongly agree

A numerical value assigned to each option adds an extra measure of quantitative insight.

5-point likert scale - man working in suit

Why The 5-Point Scale is so Broadly Used 

Likert scales can consist of any number of response options (or points). WorkTango’s survey platform can accommodate a 3-point to 10-point scale. A word of advice though: if your organization historically uses a Likert scale outside of the 5-point, you may want to consider the implications before changing. Continuity is king because you want to be able to compare previous benchmarks apples-to-apples in order to flag future trends, gaps, and opportunities. With that said, the industry standard 5-point is recommended for a variety of reasons:

  1. The 5-point Likert scale is simple to understand and use for survey administrators and respondents alike
  2. It takes less time and effort to complete than higher-point scales
  3. Fits mobile device screens better than higher-point scales
  4. Respondents have choices without becoming overwhelmed
  5. Gives respondents an option to be neutral (rather than having to choose an alternative that doesn’t reflect their thinking)
  6. Allows for a lower margin of error; any scale without a neutral option can distort results and bring the validity of survey results into question
  7. Delivers deeper insight into what people are thinking and feeling
  8. Produces reliable quantitative data that can be analyzed with relative ease
  9. Because the 5-point scale is the common (universal) method of collecting data, the format aligns with a vast library of scientifically vetted questions and comparative external benchmark data
  10. Although the 7-point scale is slightly more accurate than the 5-point, it’s not by much (and according to MeasuringU founder Jeff Saur, the author of over 15 peer-reviewed research articles and several books on statistics and the user experience: “the 7-point scale only realizes benefits if you have fewer response items (less than 10) and you use very large sample sizes.”
  11. It’s ideal for larger questionnaires with multiple items (questions/statements) – because of its accuracy and quick fill-out time
  12. A multiple-item questionnaire with a point-scale higher than 5 can make it difficult for respondents to reliably identify themselves, causing frustration, lower response rates, and unreliable results

 

Of course, the 5-point Likert scale has drawbacks too:

  • Results may not be objective
  • The 5-point scale can’t measure all opinions (which is where open-ended comments have a part to play)
  • Some respondents will lean toward a neutral opinion or evaluation
  • Others will skew towards choosing the most extreme option

But, as user-experience quantifying pioneer Saur writes: “Errors in statistics have a way of cancelling themselves out. It is likely that many responses that are “forced” into higher numbers will be cancelled out by those forced into lower numbers.”

Whatever you do when it comes to the design of your questionnaire, focus first and foremost on asking the right questions in the right way so that you can compare results from one survey to the next, and from one organization or geographic location or division or team to the next.

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