ArticleChild psychiatry and human development2026
Identifying Adolescents at Risk for Emotional Disorders with Latent Profile Analysis: A Personalized, Transdiagnostic Preventive Intervention.
Article in Child psychiatry and human development, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Evaluation of the effectiveness of Reframe-IT + to prevent suicidal ideation and other mental health outcomes among adolescents in Chile: 3-month, 6-month and 10-month follow-up.BMC psychology · 2026Trial
- Association of physical activity domains and television time with mental health profiles in Brazilian adolescents: a latent class analysis.Cadernos de saude publica · 2026Article
- How Does Booster Work? A Mediation Analysis of the Effects of Booster Sessions in a Transdiagnostic, Selective, Personalised, Preventive Intervention for At-Risk Youth.Research on child and adolescent psychopathology · 2025Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
It can be challenging to assign patients to the appropriate intervention programs, as risk and protective factors for developing emotional disorders are multiple and shared across disorders. This study aimed to provide a theoretical and empirical approach to identify and categorise adolescents into different levels of severity. The risk of developing emotional symptoms was assessed in 1425 Spanish adolescents (M = 14.34, SD = 1.76; 59.9% women). Latent Profile Analysis (LPA) was conducted to identify subgroups based on their emotional symptom severity, risk, and resilience factors. Results revealed four profiles: at low risk (emotionally healthy), moderate risk (for selective interventions), high risk (for indicated interventions), and severe risk (for clinical referral). Older age and especially female gender were predictors of higher risk clusters, and there were differences in the levels of psychopathology and health-related quality of life across clusters. Identification of at-risk adolescents for emotional disorders by means of LPA may contribute to designing personalised and tailored prevention programs that match adolescents' specific needs.
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