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GERT

 

Geneva Emotion Recognition Test (GERT and GERT-S)

The Geneva Emotion Recognition Test (GERT; Schlegel, Grandjean, & Scherer, 2014) is a performance-based test to measure individual differences in people's ability to recognize others' emotions in the face, voice, and body. This ability is considered a central component of emotional competence or intelligence.

It consists of 83 short video clips with audio in which ten actors express 14 different emotions (duration 15-20 min). These portrayals were taken from the GEneva Multimodal Emotion Portrayals database (GEMEP). After each clip, participants are asked to choose which of the 14 emotions was expressed by the actor. The GERT takes between 15 and 20 minutes to complete. Good construct and predictive validity has been demonstrated in several studies (publications in preparation).

A short 42-item short version of the GERT (GERT-S, duration about 10 min) is also available.

 

The following features distinguish the GERT from many existing emotion recognition tests:

 

  • The GERT is based exclusively on dynamic, multimodal emotion expressions (i.e., short video clips with sound) in order to measure emotion recognition ability (ERA) in a more ecologically valid fashion
  • The GERT features 14 different emotions, including 6 positive ones, in order to assess ERA more comprehensively than tests relying on basic emotions
  • The GERT was developed and validated based on modern psychometric principles (Item Response Theory, Rasch model)

 

To try out the GERT, please go to our Exploring your EC page.

The GERT has been developed and validated in German, French, Dutch, and English. It is also available in Italian, Hungarian, and Chinese. We thank the following colleagues for translating the GERT into these languages: Dr. Irene Rotondi (Italian), Dr. Dóra Kovácz (Hungarian), Dr. Lingdan Wu (Chinese).

 

Obtaining the GERT and GERT-S for research purposes

The GERT is available as an online test. If you wish to use the GERT for academic research purposes, please follow the instructions below:

  1. Read the User's guide for details about the test and academic use.
  2. Download and print the user agreement form.
  3. Send the completed and signed agreement form together with a brief description of the project (1/2 to 1 page) in which you want to use the GERT to eureca(at)ugent.be. Please cc each additional person (e.g., research assistants) who should get access to the test in your email.
  4. Upon approval of your request, you will get access to your personal online version that you can distribute to your participants.

Publications

Schlegel, K., Fontaine, J. R. J., & Scherer, K. R. (2017). The nomological network of emotion recognition ability: Evidence from the Geneva Emotion Recognition Test. European Journal of Psychological Assessment, 1–12.
 
Schlegel, K., & Scherer, K. R. (2016). Introducing a short version of the Geneva Emotion Recognition Test (GERT-S): Psychometric properties and construct validation. Behavior Research Methods, 48(4), 1383–1392.

Schlegel, K., Grandjean, D., & Scherer, K. R. (2014). Introducing the Geneva Emotion Recognition Test: An example of Rasch-based test development. Psychological Assessment, 26(2), 666-672.
                    Click here to download the Supplementary Material to this article.

Schlegel, K., Grandjean, D., & Scherer, K. R. (2012). Emotion recognition: Unidimensional ability or a set of modality- and emotion-specific skills? Personality and Individual Differences, 53(1), 16–21.
                    Click here to download the Supplementary Material to this article.

 

Additional material

GERT User's guide: Further information about the test, how to obtain it for research purposes, and how to analyze the results.

GERT (83-item long version) SPSS Syntax to analyze Qualtrics data.

GERT (42-item short version) SPSS Syntax to analyze Qualtrics data.

Please note: To use the above SPSS syntax, download the data from Qualtrics in the following way: Data & analysis --> Export & import --> Export data --> Use legacy exporter --> SPSS. Only this file has the correct variable names for the syntax to run.