TL;DR: UEQ is a 26-item questionnaire that measures reliably the Pragmatic Quality and Hedonic Quality of a product. Five other sub-dimensions have been proposed but literature is torn in their validity. UEQ provides a benchmark for comparing a system scores with normative data for a collection of other systems.
Defining UX has been, and to some extent still is, tricky. In their 2006 publication, Laugwitz, Schrepp, and Held introduced the User Experience Questionnaire (UEQ), originally developed in German (and later adapted into English). As a working definition of UX, the UEQ builds on Hassenzahl’s theory that users perceive a product through Pragmatic and Hedonic qualities. Pragmatic Quality emphasises how well a product supports users in achieving task-related goals with effectiveness and efficiency, whereas Hedonic Quality emphasises the product’s role in psychological well-being, stimulation, and identity expression. UEQ has shown promising psychometric properties, but more research is needed to evaluate the dimensions it is measuring.
Setting up the UEQ
The questions of the UEQ
The UEQ consists of 26 items, presented as pairs of opposite adjectives on a 7-point semantic differential scale ranging from -3 to +3, with 0 representing neutrality. Each item asks participants to rate the product somewhere between two extremes. Some items are positively worded (where higher scores indicate better UX), while others are negatively worded (where higher scores indicate worse UX).
The labels of the 26 semantic differential items are:
- Annoying – Enjoyable
- Not understandable – Understandable
- Creative – Dull
- Easy to learn – Difficult to learn
- Valuable – Inferior
- Boring – Exciting
- Not interesting – Interesting
- Unpredictable – Predictable
- Fast – Slow
- Inventive – Conventional
- Obstructive – Supportive
- Good – Bad
- Complicated – Easy
- Unlikable – Pleasing
- Usual – Leading edge
- Unpleasant – Pleasant
- Secure – Not secure
- Motivating – Demotivating
- Meets expectations – Does not meet expectations
- Inefficient – Efficient
- Clear – Confusing
- Impractical – Practical
- Organized – Cluttered
- Attractive – Unattractive
- Friendly – Unfriendly
- Conservative – Innovative
The translations and some adaptations can be found on the UEQ website.

Calculating the UEQ score
The rules
Positively worded items are:
1, 2, 6, 7, 8, 11, 13, 14, 15, 16, 20, 22, and 26.
Negatively worded items are:
3, 4, 5, 9, 10, 12, 17, 18, 19, 21, 23, 24, and 25.
The overall score of the UEQ (the product’s score)
There is no single “overall UEQ score”. Instead, the questionnaire is interpreted through three overarching qualities and six sub-dimensions. However, if we are really after an overall score we can use the score of the Attractiveness scale, which also should be approximately (Pragmatic + Hedonic) / 2.
We will assume in the calculation formulas below that all replies are in the range of 1 to 7.
The product’s Attractiveness score
To get the Attractiveness score for each participant:
- Add items 1, 14, and 16
- From the number 24, subtract items 12, 24, and 25
- Add the two numbers from the previous steps, divide by 6, and subtract 4
Or in one formula:
\text{participant\_attractiveness\_score} = \frac{item_{1} + item_{14} + item_{16} + 24 - (item_{12} + item_{24} + item_{25})}{6} - 4To get the overall Attractiveness score, calculate the mean of all participants’ scores.
The product’s Pragmatic Quality score
To get the Pragmatic Quality score for each participant:
Or in one formula:
- Add items 2, 8, 11, 13, 20, and 22
- From the number 48, subtract items 4, 9, 17, 19, 21, 23
- Add the two numbers from the previous steps, divide by 12, and subtract 4
To get the overall Pragmatic Quality score, calculate the mean of all participants’ scores.
The product’s Hedonic Quality score
To get the Hedonic Quality score for each participant:
- Add items 6, 7, 15, and 26
- From the number 32, subtract items 3, 5, 10, and 18
- Add the two numbers from the previous steps, divide by 8, and subtract 4
Or in one formula:
\text{participant\_hq\_score} = \frac{item_{6} + item_{7} + item_{15} + item_{26} + 32 - (item_{3} + item_{5} + item_{10} + item_{18})}{8} - 4To get the overall Hedonic Quality score, calculate the mean of all participants’ scores.
The five sub-dimensions of the UEQ
The Pragmatic and Hedonic dimensions are further broken down into 5 sub-dimensions. Even though these dimensions were reported in the initial publications, recent research has shown mixed results in replicating them (e.g. research by Schankin et. al). The five sub-dimensions were introduced to help pin-point which aspects of the product need to be improved, for the time being, we suggest interpreting these dimensions with caution.
Pragmatic Quality dimensions:
Perspicuity (ease of learning and clarity):
To get the Perspicuity score for each participant:
- Add items 2, and 13
- From the number 16, subtract items 4, and 21
- Add the two numbers from the previous steps, divide by 4, and subtract 4
Or in one formula:
\text{participant\_perspicuity\_score} = \frac{item_{2} + item_{13} + 16 - (item_{4} + item_{12})}{4} - 4To get the overall Perspicuity score, calculate the mean of all participants’ scores.
Efficiency (task completion and productivity):
To get the Efficiency score for each participant:
- Add items 20, and 22
- From the number 16, subtract items 9, and 23
- Add the two numbers from the previous steps, divide by 4, and subtract 4
Or in one formula:
\text{participant\_efficiency\_score} = \frac{item_{20} + item_{22} + 16 - (item_{9} + item_{23})}{4} - 4To get the overall Efficiency score, calculate the mean of all participants’ scores.
Dependability (predictability, control, and trust):
To get the Dependability score for each participant:
- Add items 8, and 11
- From the number 16, subtract items 17, and 19
- Add the two numbers from the previous steps, divide by 4, and subtract 4
Or in one formula:
\text{participant\_dependability\_score} = \frac{item_{8} + item_{22} + 16 - (item_{17} + item_{19})}{4} - 4To get the overall Dependability score, calculate the mean of all participants’ scores.
Hedonic Quality dimensions:
Stimulation (excitement, motivation, and engagement):
To get the Stimulation score for each participant:
- Add items 6, and 7
- From the number 16, subtract items 5, and 18
- Add the two numbers from the previous steps, divide by 4, and subtract 4
Or in one formula:
\text{participant\_stimulation\_score} = \frac{item_{6} + item_{7} + 16 - (item_{5} + item_{18})}{4} - 4To get the overall Stimulation score, calculate the mean of all participants’ scores.
Novelty (innovation and creativity):
To get the Novelty score for each participant:
- Add items 15, and 26
- From the number 16, subtract items 3, and 10
- Add the two numbers from the previous steps, divide by 4, and subtract 4
Or in one formula:
\text{participant\_novelty\_score} = \frac{item_{15} + item_{26} + 16 - (item_{3} + item_{10})}{4} - 4To get the overall Novelty score, calculate the mean of all participants’ scores.
Understanding the UEQ’s score
Benchmarks
The UEQ provides a benchmark dataset based on 21175 evaluations of 468 products across industries. These benchmarks can be used to compare the results from the product we are evaluating with the products in the dataset and help put a “label” to our numbers. The authors of the UEQ have provided a percentile rank (similar to SUPR-Q) that can be interpreted per subscale as shown on the tables below:
Benchmark for Attractiveness
Percentile | Mean | Label |
---|---|---|
< 25% | – | Bad |
25% | 0.69 | Bellow Average |
50% | 1.18 | Above Average |
75% | 1.58 | Good |
90% | 1.84 | Excellent |
Benchmark for Perspicuity
Percentile | Mean | Label |
---|---|---|
< 25% | – | Bad |
25% | 0.72 | Bellow Average |
50% | 1.2 | Above Average |
75% | 1.73 | Good |
90% | 2 | Excellent |
Benchmark for Efficiency
Percentile | Mean | Label |
---|---|---|
< 25% | – | Bad |
25% | 0.6 | Bellow Average |
50% | 1.05 | Above Average |
75% | 1.5 | Good |
90% | 1.88 | Excellent |
Benchmark for Dependability
Percentile | Mean | Label |
---|---|---|
< 25% | – | Bad |
25% | 0.78 | Bellow Average |
50% | 1.14 | Above Average |
75% | 1.48 | Good |
90% | 1.7 | Excellent |
Benchmark for Stimulation
Percentile | Mean | Label |
---|---|---|
< 25% | – | Bad |
25% | 0.5 | Bellow Average |
50% | 1 | Above Average |
75% | 1.35 | Good |
90% | 1.7 | Excellent |
Benchmark for Novelty
Percentile | Mean | Label |
---|---|---|
< 25% | – | Bad |
25% | 0.16 | Bellow Average |
50% | 0.7 | Above Average |
75% | 1.12 | Good |
90% | 1.6 | Excellent |
For example a product that has an attractiveness score of 1.21, is perceived as having better attractiveness than 50% of the products in the dataset, and worse than 25%. We can label it then as “Above Average” regarding its attractiveness.
The Excel file provided by UEQ can be used both as a shortcut to the calculation and to the benchmarks.
Factors that affect UEQ
Factor | Influence | Studies |
---|---|---|
Gender | Possibly no significant influence | Initial data from Schrepp et al. and initial data for UEQ-S Kollmorgen et al. |
Usage frequency | Possibly some influence on Attractiveness, PQ and HQ | Initial data for UEQ-S from Kollmorgen et al. |
Self-reported knowledge of the product | Possibly some influence on Attractiveness, PQ and HQ | Initial data for UEQ-S from Kollmorgen et al. |
Duration of use | Possibly some influence on Attractiveness, PQ and HQ | Initial data for UEQ-S from Kollmorgen et al. |