Poster Session C - Mental Health Sciences 1.
Abstract
Introduction: The Mental Affectivity Scale (MAS), developed by Greenberg et al. in 2017, is based on an integrated theory of mentalization and emotion regulation and measures the three main domains of mentalized emotions: emotion recognition, processing and expression. It assumes mental work with emotions and includes reflection on past experiences. The original version of the scale is based on self-report, contains 60 items and has a three-factor structure. The questionnaire has also been validated on an Italian sample, the researchers kept 35 items, grouped in 5 subscales. The questionnaire has been translated into several languages and used to measure mental emotion regulation. Experience to date suggests that it is well suited for measuring both normal and clinical populations. The authors have also produced a shortened version of scale.
Aims: To validate the scale on a Hungarian sample, to verify its psychometric properties and to explore the possible factor structure after translation according to the specifications. As well as convergent validation with other measures.
Methods: Data were collected through an online questionnaire using a snowball sampling method. The psychometric properties of the scale are examined (reverse item counting, Cr-alpha, sum, CFA with the original 3-factor structure and the Italian 5-factor version, and PCA). Convergent validation is performed with the Mentalization Need Questionnaire (MI), the Emotion Regulation Questionnaire (ERQ) and the Satisfaction with Life Scale (SWLS-H).
Results: In this poster, we present the revealed psychometric properties of the MAS-H, its factor structure, its internal validity, and its associations with demographic data.
Conclusion: Our results indicate that the scale measuring the mentalized affectivity construct, which has a strong empirical background, is a well-usable tool in Hungarian as well. We also recommend its application to a Hungarian sample.
Funding: The research was not supported by fundings.