At‐risk mental states and personality traits: A cluster analysis approach on a group of help‐seeking young adults.

Rossi, Chiara; De Salve, Francesca; Biagianti, Bruno; Cavalera, Cesare; Malvini, Lara; Barbera, Simona; Pastelli, Ilaria; Tagliabue, Sofia; Oasi, Osmano; Percudani, Mauro

Introduction: Research on the relationship between personality and psychosis onset is growing, with the goal of preventing or intervening early in patients' vulnerability. The identification of individuals with at‐risk mental states has enabled the development of early intervention strategies, such as Programma 2000, a youth mental health service that was implemented in Milan (Italy). Aims: Focusing on the 18–25 age range—the time window with the highest incidence of psychotic onset—this study aims to identify the personality traits that may characterize the at‐risk mental states and the social functioning of a group of help‐seeking young adults. Methods: The sample includes 169 people (48.5% males and 51.5% females). Data were collected during an initial assessment that comprised the Social and Occupational Functioning Assessment Scale, the Personality Inventory for DSM‐5, the Checklist ERIraos and a clinical session. Results: Results identified a three‐cluster solution based on the Checklist scores: Cluster 1 'Not at psychotic risk'; Cluster 2 'At intermediate risk'; Cluster 3 'With psychotic onset'. The multivariate analysis of the variance of personality traits shows significant differences among the clusters in negative affect, detachment and disinhibition. Higher scores in these traits may distinguish individuals, not at psychotic risk from those at intermediate risk or with psychotic onset. Moreover, social functioning was found to be negatively associated with clusters of psychotic risk. Conclusion: Findings from this study highlighted the need to evaluate personalized interventions targeting such personality traits that could prevent psychotic transition and promote psychological well‐being.

MILAN (Italy); PERSONALITY; YOUNG adults; MENTAL health services; CLUSTER analysis (Statistics); SENSATION seeking; MULTIVARIATE analysis

Early Intervention in Psychiatry, 2023, Vol 17, Issue 11, p1070

1751-7885

Academic Journal

10.1111/eip.13397