Childhood temperament as a predictor of adolescent nonsuicidal self-injury.

Previous cross-sectional work has consistently found associations between neuroticism and impulsivity and nonsuicidal self-injury (NSSI). However, there are few longitudinal studies of personality risk factors for NSSI. In this study, we examined associations between individual differences in temperament at age 3 and NSSI from ages 9 to 15. At age 3, 559 preschool-aged children (54% male; Mage = 42.2 months [SD = 3.10]) completed laboratory assessments of temperament. Parents also completed questionnaires about their child's temperament. Children completed a diagnostic interview assessing NSSI engagement at ages 9, 12, and 15. By the age 15 assessment, 12.4% of adolescents reported engaging in NSSI. In univariate models, we found that higher levels of observed sadness and maternal-reported sadness and anger were associated with increased risk for NSSI. In multivariate models, female sex and maternal-reported anger were significantly associated with greater likelihood of NSSI. Laboratory observed sadness and impulsivity were associated with a higher likelihood of NSSI. This work extends the literature on personality risk factors associated with NSSI by finding longitudinal associations between early childhood negative affect and later NSSI engagement during adolescence.

Enhancing the Psychometric Properties of the Iowa Gambling Task Using Full Generative Modeling.

Poor psychometrics, particularly low test-retest reliability, pose a major challenge for using behavioral tasks in individual differences research. Here, we demonstrate that full generative modeling of the Iowa Gambling Task (IGT) substantially improves test-retest reliability and may also enhance the IGT's validity for use in characterizing internalizing pathology, compared to the traditional analytic approach. IGT data (n=50) was collected across two sessions, one month apart. Our full generative model incorporated (1) the Outcome Representation Learning (ORL) computational model at the person-level and (2) a group-level model that explicitly modeled test-retest reliability, along with other group-level effects. Compared to the traditional 'summary score' (proportion good decks selected), the ORL model provides a theoretically rich set of performance metrics (Reward Learning Rate (A+), Punishment Learning Rate (A-), Win Frequency Sensitivity (ßf), Perseveration Tendency (ßp), Memory Decay (K)), capturing distinct psychological processes. While test-retest reliability for the traditional summary score was only moderate (r=.37, BCa 95% CI [.04, .63]), test-retest reliabilities for ORL performance metrics produced by the full generative model were substantially improved, with test-retest correlations ranging between r=.64-.82 for the five ORL parameters. Further, while summary scores showed no substantial associations with internalizing symptoms, ORL parameters were significantly associated with internalizing symptoms. Specifically, Punishment Learning Rate was associated with higher self-reported depression and Perseveration Tendency was associated with lower self-reported anhedonia. Generative modeling offers promise for advancing individual differences research using the IGT, and behavioral tasks more generally, through enhancing task psychometrics.