Modifiable predictors of suicidal ideation during psychotherapy for late-life major depression. A machine learning approach

Abstract

This study aimed to identify subgroups of depressed older adults with distinct trajectories of suicidal ideation during brief psychotherapy and to detect modifiable predictors of membership to the trajectories of suicidal ideation. Latent growth mixed models were used to identify trajectories of the presence of suicidal ideation in participants to a randomized controlled trial comparing Problem Solving Therapy with “Engage” therapy in older adults with major depression over 9 weeks. Predictors of membership to trajectories of suicidal ideation were identified by the convergence of four machine learning models, i.e., least absolute shrinkage and selection operator logistic regression, random forest, gradient boosting machine, and classification tree. The course of suicidal ideation was best captured by two trajectories, a favorable and an unfavorable trajectory comprising 173 and 76 participants respectively. Members of the favorable trajectory had no suicidal ideation by week 8. In contrast, members of the unfavorable trajectory had a 60% probability of suicidal ideation by treatment end. Convergent findings of the four machine learning models identified hopelessness, neuroticism, and low general self-efficacy as the strongest predictors of membership to the unfavorable trajectory of suicidal ideation during psychotherapy. Assessment of suicide risk should include hopelessness, neuroticism, and general self-efficacy as they are predictors of an unfavorable course of suicidal ideation in depressed older adults receiving psychotherapy. Psychotherapeutic interventions exist for hopelessness, emotional reactivity related to neuroticism, and low self-efficacy, and if used during therapy, may improve the course of suicidal ideation.

Induced optimism to lessen hopelessness-related cognitions among young adults at risk for suicidal thoughts and behavior

“…Contemporary psychological models of suicide suggest that hopelessness about the future plays a fundamental role in the onset of suicidal thoughts (e.g., Van Orden et al, 2010 ; Wenzel & Beck, 2008 ). Hopelessness predicts suicide ideation ( Wolfe et al, 2019 ; Alexopoulos et al, 2021 ; Ribeiro et al, 2018 ; Rosario-Williams et al, 2021 ), suicide attempts ( Ribeiro et al, 2018 ; Liu et al, 2018 ; Miranda-Mendizabal et al, 2019 ), and suicide deaths ( Beck et al, 2006 ; Brown et al, 2000 ; Ribeiro et al, 2018 ), making it a critical target of intervention. Understanding how to modify the hopelessness-related cognitions that give rise to suicidal thoughts may ultimately prevent the transition to suicide attempts and suicide deaths.…”