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The assessment of emotion reactivity: The Italian validation of the Perth Emotional Reactivity Scale-Short Form (PERS-S).

Festucci FabianaMaria Chiara PinoLorenzo ViselliD' Aurizio GiuliaFederico SalfiAmicucci GiuliaCorigliano DomenicoD' Atri AuroraMichele FerraraDaniela Tempesta
Published in: The European journal of neuroscience (2024)
Emotion reactivity refers to the activation, intensity and duration of emotional responses to internal or external stimuli. It can be differentiated from emotion regulation since the former is the very first response to an emotional trigger, and the latter can be defined as a tool for maintaining one's arousal in a window of tolerance. Since, to date, there are no Italian self-report measures able to evaluate individuals' emotional reactivity, this study aimed to contribute to the Italian validation of the Perth Emotional Reactivity Scale-Short Form (PERS-S). The PERS-S is an 18-item self-report measure answered on a 5-point Likert scale that generates six subscale scores and two composite scores, with higher scores indicating higher levels of reactivity. Data from 768 individuals showed that the PERS-S had good to excellent goodness of fit. The internal consistency was high, with an overall reliability coefficient (Cronbach's α) of .87 and .86 for the negative and positive general scales, respectively. The PERS-S also demonstrated appropriate convergent validity, showing significant correlations with conceptually related measures, and acceptable divergent validity, showing minimal correlations with unrelated constructs. Finally, we evaluated the Test-Retest Reliability by administering the PERS-S to the same sample twice, with a 2-week interval. The significant correlations between the two PERS-S administrations suggest temporal stability. The Italian version of the PERS-S will enrich the repertoire of self-report measures for investigating the development and risk factors of mental health disorders and may have practical applications in clinical settings.
Keyphrases
  • mental health
  • risk factors
  • depressive symptoms
  • autism spectrum disorder
  • randomized controlled trial
  • machine learning
  • high intensity
  • clinical trial
  • magnetic resonance
  • deep learning
  • clinical evaluation