ArticleBMC psychiatry2025
Subgroups of suicidal ideation and simulated intervention responses among left-behind children with depression risk: an Ising computational network model.
Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Machine learning-based predictive factor analysis of depression among Chinese adolescents.Frontiers in psychiatry · 2026Article
- The impact of parent-child interaction and adolescent deviant behavior: the sequential mediation of depression and deviant peer affiliation.Frontiers in psychology · 2025Article
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6 authors.
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Abstract
backgroundLeft-behind children (LBC) with depression risk exhibit a higher suicide risk than their peers. To better understand the psychological mechanisms contributing to elevated suicide risk, this study employed a person-centered approach to systematically identify latent subgroups of suicidal ideation, with a particular focus on the roles of positive and negative suicidal ideation, and to investigated their differential responses to simulated interventions.
methodsFrom the Psychological Healthcare Guard Children and Adolescents Project of China cohort, 10,852 left-behind children with depression risk were selected. Using self-reported demographic data, depressive symptoms, and positive and negative suicidal ideation, we conducted latent profile analysis, network analysis, and computational simulation to evaluate the effects of key intervention targets.
resultsLatent profile analysis identified three suicidal ideation subgroups-low, moderate, and high (40%, 39%, and 21%, respectively)-with significant differences in depression levels across groups. The Ising network model revealed that the most influential node in the overall sample was the negative suicidal ideation (SN08: Frustrated in life), whereas positive suicidal ideation nodes (SP03: Satisfied with life and SP06: Confident about the future) dominated in all subgroups. Simulated interventions showed that positive ideation nodes had the greatest impact on suicidal ideation risk, particularly in the high-risk group, where risk scores increased by 1.9 points under the aggravation intervention, highlighting the pivotal role of positive emotion-focused interventions.
conclusionsThis study offers novel insights into suicidal ideation among left-behind children with depression risk, from an individual-centered level, demonstrating that positive suicidal ideation plays a more important role than negative ideation in both aggravation and alleviation intervention effects, with key targets varying across subgroups. Targeted interventions prioritizing positive ideation in high-risk groups are recommended to optimize prevention and treatment strategies.
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