Mood computational mechanisms underlying increased risk behavior in adolescent suicidal patients

Suicidal thoughts and behaviors (STB) are among the leading causes of death worldwide. Although previous research has consistently documented elevated risk-taking in individuals with STB and identified mood disturbances as central features of suicidality, the precise cognitive and affective computational mechanisms underlying this increased risky behavior remain poorly understood. Here, 83 adolescent inpatients with affective disorders, including 58 patients with STB (S+) and 25 without STB (S-), and 118 age- and sex-matched healthy controls (HC) completed a decision-making task involving choices between certain and gamble options, alongside momentary mood ratings. Behavioral analyses showed that S+ exhibited greater risk-taking than both S- and HC. Computational modeling of choice behavior using a prospect-theory framework augmented with value-insensitive approach-avoidance parameters indicated that this increase in risky behavior was specifically driven by an elevated approach parameter in S+. In addition, mood-model analyses revealed reduced sensitivity to certain rewards in S+ relative to S- and HC. Importantly, these computational signatures predicted suicidal symptom severity and showed generalizability in an independent general-population sample (n = 747). In S+, lower mood sensitivity to certain rewards was associated with greater gambling, providing a computational affective account of increased risk-taking in STB. These findings remained robust after adjusting for demographic, clinical, and medication-related variables. Overall, our study identifies cognitive and affective computational mechanisms contributing to elevated risk-taking in STB and highlights their potential relevance for the early identification and prevention of suicidality.