THE JOURNEY FROM CONTROLLED TO AUTOMATIC: LEARING EMOTION REGULATION ACROSS PERSONALITY DOMAINS

This thesis examines the possibility of automating the emotion regulation (ER) strategy cognitive reappraisal and its relationship with personality, as defined by the Big Five model. ER is a key component of psychological well-being that enables individuals to modify emotional responses. Reappraisal, though efficient, often requires conscious cognitive effort. The study explores whether reappraisal can be learned to function more automatically using classical conditioning principles. A within-subjects experimental design was employed, including 30 participants aged 23–38 years, predominantly psychology students. Participants were trained to reappraise emotional stimuli and tested using visual cues (square vs. triangle) to differentiate reappraisal from a counting control task. Emotional arousal was measured using self-reported Likert scales before and after exposure to stimuli. The Big Five Inventory 2-S (BFI-2-S) assessed personality dimensions. The results showed significant reductions in emotional arousal for both stimuli. Furthermore, there was a significantly higher reduction in arousal for the reappraisal cues compared to the control condition, indicating that reappraisal can indeed become more automatic. However, no significant correlations were found between personality traits and ability to learn reappraisal automatically, suggesting that personality may not constrain the ability to learn this strategy. These findings imply potential for widespread application of automatic reappraisal training in clinical interventions, independent of personality differences. Limitations related to sample size, homogeneity, and experimental design are acknowledged, and future studies are encouraged to explore long-term effects and diverse populations. Keywords: emotion regulation, reappraisal, personality traits, Big Five model, classical conditioning.