Psychometric assessment of social cognitive tasks

Abstract

Although there has been a marked increase in interest in social cognition (SC) in recent years, psychometric data relating to many tasks used to measure its components remain limited in healthy populations with only five articles published to date. It is accordingly premature to speak of a consensus concerning the specific components, or best tests of the components, and possible cultural differences. The present study sought to partially fill that gap, examining the psychometric properties of a battery of SC tasks in a sample of 100 healthy adults aged 18–85 years old. Initially, nine tasks assessing four SC components were selected: emotion recognition, theory of mind, attributional bias, and social judgment. Construct validity and criterion-related validity were assessed using factor and correlational analyses. Performance across age and sex groups was also investigated. Reliability was assessed through internal consistency, interrater and intercoder agreement. Results indicated satisfactory properties for the Ambiguous Intentions Hostility Questionnaire-blame score, the Social Judgment Task, the Facial Emotions Recognition Test, and a modified version of the Strange Stories Task. Statistically significant differences were found between the groups with regard to age and sex after accounting for demographic and cognitive factors. However, the correlations of these measures with relationship quality were mostly very low, raising questions about their concomitant validity. Other tasks showed sub-optimal properties, suggesting that some frequently used tests require further validation or modifications to ensure the quality of research findings. Based on the results, recommended measures for future studies and limitations are discussed.

Keywords:

• Emotion recognition
• psychometric
• social cognition
• social judgment
• theory of mind

Acknowledgments

The authors would like to express their sincere gratitude to Dr. F. Happé for the opportunity to use and adapt the Strange Stories Task, as well as Dr. D. L. Penn, Dr. P. Kinderman, Dr. R. Langdon, Dr. M. Davis, Mr. B. Gaudelus, Dr. E. Brunet-Gouet, Dr. R. Vallerand, and Dr. S. Baron-Cohen (Autism Research Centre) for the access to the tests. Also, the authors would like to thank Francis Germain (Université du Québec à Montréal) for his contribution to data collection.

Disclosure statement

Authors declare that they have no conflicts of interest concerning this article.