{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T18:46:01Z","timestamp":1781808361935,"version":"3.54.5"},"reference-count":32,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T00:00:00Z","timestamp":1741219200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81971286"],"award-info":[{"award-number":["81971286"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002865","name":"Chongqing Municipal Science and Technology Bureau","doi-asserted-by":"publisher","award":["CSTC2021-jscx-gksb-N0002"],"award-info":[{"award-number":["CSTC2021-jscx-gksb-N0002"]}],"id":[{"id":"10.13039\/501100002865","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Psychiatry"],"abstract":"<jats:sec><jats:title>Objective<\/jats:title><jats:p>To explore the risk factors that affect adolescents\u2019 suicidal and self-injurious behaviors and to construct a prediction model for adolescents\u2019 suicidal and self-injurious behaviors based on machine learning algorithms.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Stratified cluster sampling was used to select high school students in Chongqing, yielding 3,000 valid questionnaires. Based on whether students had engaged in suicide or self-injury, they were categorized into a suicide\/self-injury group (n=78) and a non-suicide\/self-injury group (n=2,922). Gender, age, insomnia, and mental illness data were compared between the two groups, and a logistic regression model was used to analyze independent risk factors for adolescent suicidal and self-injurious behavior. Six methods\u2014multi-level perceptron, random forest, K-nearest neighbor, support vector machine, logistic regression, and extreme gradient boosting\u2014were used to build predictive models. Various model indicators for suicidal and self-injurious behavior were compared across the six algorithms using a confusion matrix to identify the optimal model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Result<\/jats:title><jats:p>In the self-injury and suicide groups, the proportions of male adolescents, late adolescence, insomnia, and mental illness were significantly higher than in the non-suicide and self-injury groups (<jats:italic>p &amp;lt;<\/jats:italic>0.05). Compared with the non-suicidal self-injury group, this group also showed significantly increased scores in cognitive subscales, impulsivity, psychoticism, introversion\u2013extroversion, neuroticism, interpersonal sensitivity, depression, anxiety, hostility, terror, and paranoia (p &amp;lt;0.05). These statistically significant variables were analyzed in a logistic regression model, revealing that gender, impulsivity, psychoticism, neuroticism, interpersonal sensitivity, depression, and paranoia are independent risk factors for adolescent suicide and self-injury. The logistic regression model achieved the highest sensitivity and specificity in predicting adolescent suicide and self-injury behavior (0.9948 and 0.9981, respectively). Performance of the random forest, multi-level perceptron, and extreme gradient models was acceptable, while the K-nearest neighbor algorithm and support vector machine performed poorly.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The detection rate of suicidal and self-injurious behaviors is higher in women than in men. Adolescents displaying impulsiveness, psychoticism, neuroticism, interpersonal sensitivity, depression, and paranoia have a greater likelihood of engaging in such behaviors. The machine learning model for classifying and predicting adolescent suicide and self-injury risk effectively identifies these behaviors, enabling targeted interventions.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpsyt.2024.1521025","type":"journal-article","created":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T06:52:30Z","timestamp":1741243950000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Research on prediction model of adolescent suicide and self-injury behavior based on machine learning algorithm"],"prefix":"10.3389","volume":"15","author":[{"given":"Yao","family":"Gan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Kuang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao-Ming","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming","family":"Ai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing-Lan","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wo","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Su","family":"Hong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian mei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Cao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,3,6]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e2020020610","DOI":"10.1542\/peds.2020-020610","article-title":"Adolescent risk behavior screening and interventions in hospital settings: A scoping review","volume":"147","author":"Pfaff","year":"2021","journal-title":"Pediatrics"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1016\/j.anpede.2022.11.005","article-title":"Self-injury and suicidal behavior in children and youth populations: Learning from the pandemic","volume":"98","author":"V\u00e1zquez L\u00f3pez","year":"2023","journal-title":"Pediatr (Engl Ed)"},{"key":"B3","doi-asserted-by":"publisher","first-page":"e12452","DOI":"10.1111\/appy.12452","article-title":"Suicide prevention in childhood and adolescence: a narrative review of current knowledge on risk and protective factors and effectiveness of interventions","volume":"13","author":"Wasserman","year":"2021","journal-title":"Asia Pac Psychiatry"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1002\/eat.23880","article-title":"Non-suicidal self-injury, suicidal thoughts and behaviors in individuals with an eating disorder relative to healthy and psychiatric controls: A systematic review and meta-analysis","volume":"56","author":"Sohn","year":"2023","journal-title":"Int J Eat Disord"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1111\/sltb.2018.48.issue-1","article-title":"The relationship between nonsuicidal self-injury age of onset and severity of self-harm","volume":"48","author":"Ammerman","year":"2018","journal-title":"Suicide Life Threat Behav"},{"key":"B6","doi-asserted-by":"publisher","first-page":"741","DOI":"10.1111\/sltb.12747","article-title":"Examining decentering as a moderator in the relation between non-suicidal self-injury and suicide ideation via cognitive-affective factors","volume":"51","author":"Rosario-Williams","year":"2021","journal-title":"Suicide Life Threat Behav"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1038\/s41380-022-01639-y","article-title":"Augmented pain inhibition and higher integration of pain modulatory brain networks in women with self-injury behavior","volume":"27","author":"Lalouni","year":"2022","journal-title":"Mol Psychiatry"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1016\/j.genhosppsych.2021.07.009","article-title":"How common is recent denial of suicidal ideation among ideators, attempters, and suicide decedents? 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