Differentiating adolescent suicidal and nonsuicidal self-harm with artificial intelligence: Beyond suicidal intent and capability for suicide

Clinical differentiation between adolescent suicidal self-harm (SSH) and nonsuicidal self-harm (NSSH) is a significant challenge for mental health professionals, and its feasibility is controversial. The aim of the present study was to determine whether adolescent SSH can be differentiated from NSSH based on a holistic multimodel domain analysis (HMDA) of individual, psychological, sociodemographic, and environmental data without relying on intent and acquired capability for suicide. The study also sought to compare the compatibility of the HMDA result with four theories of suicide: the interpersonal theory of suicide, the three-steps theory, the integrated motivational-volitional model, and the theory of adolescent suicidality and self-destruction. This cross-sectional study analyzed data from a nationwide survey conducted from 2017 to 2019 in Norway. The sample included 26,904 adolescents (mean age = 15.01; 29.9 % males), who self-reported suicidal and nonsuicidal self-harm. The meta-learner classification model reached an AUC of 77.0 % and a 70.0 % for both sensitivity and specificity in differentiating the two conditions. Exploratory factor analysis suggested eight factors for clustering the important risk and protective indicators: 1) disordered eating and future orientation, 2) sleep disturbance, 3) orientation toward affects and self, 4) risk-taking behavior, 5) peer relationships, 6) victimization, safety, and security, 7) family relationships, and 8) substance use. These factors emphasize that domains central to adolescent physical, personal, social, and expected future well-being provide invaluable information about risk of suicidal and self-destructive behavior. The results also indicated that despite their high comorbidity, adolescent SSH and NSSH are multifaceted and can be differentiated without relying on suicide-related information. These findings fully supported the theory of adolescent suicidality and self-destruction and partially supported the ideation-to-action theories.

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Publication Details

Journal
Journal of Affective Disorders
Published
2025-02-13
DOI
https://doi.org/10.1016/j.jad.2025.02.015
Citations
6
Primary Topic
Suicide and Self-Harm Studies
Type
article
Field-Weighted Citation Impact
13.84
Controls
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article

Differentiating adolescent suicidal and nonsuicidal self-harm with artificial intelligence: Beyond suicidal intent and capability for suicide

E. F. Haghish
6 citations
Journal of Affective Disorders
Suicide and Self-Harm Studies
13.84
article

Differentiating adolescent suicidal and nonsuicidal self-harm with artificial intelligence: Beyond suicidal intent and capability for suicide

E. F. Haghish
article en
6 citations

Abstract

Clinical differentiation between adolescent suicidal self-harm (SSH) and nonsuicidal self-harm (NSSH) is a significant challenge for mental health professionals, and its feasibility is controversial. The aim of the present study was to determine whether adolescent SSH can be differentiated from NSSH based on a holistic multimodel domain analysis (HMDA) of individual, psychological, sociodemographic, and environmental data without relying on intent and acquired capability for suicide. The study also sought to compare the compatibility of the HMDA result with four theories of suicide: the interpersonal theory of suicide, the three-steps theory, the integrated motivational-volitional model, and the theory of adolescent suicidality and self-destruction. This cross-sectional study analyzed data from a nationwide survey conducted from 2017 to 2019 in Norway. The sample included 26,904 adolescents (mean age = 15.01; 29.9 % males), who self-reported suicidal and nonsuicidal self-harm. The meta-learner classification model reached an AUC of 77.0 % and a 70.0 % for both sensitivity and specificity in differentiating the two conditions. Exploratory factor analysis suggested eight factors for clustering the important risk and protective indicators: 1) disordered eating and future orientation, 2) sleep disturbance, 3) orientation toward affects and self, 4) risk-taking behavior, 5) peer relationships, 6) victimization, safety, and security, 7) family relationships, and 8) substance use. These factors emphasize that domains central to adolescent physical, personal, social, and expected future well-being provide invaluable information about risk of suicidal and self-destructive behavior. The results also indicated that despite their high comorbidity, adolescent SSH and NSSH are multifaceted and can be differentiated without relying on suicide-related information. These findings fully supported the theory of adolescent suicidality and self-destruction and partially supported the ideation-to-action theories.

Journal of Affective DisordersVol. 378
University of Oslo (NO)
Gender equality
Openalex Percentile: Top 1%
Suicide and Self-Harm Studies
13.84
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