[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124487-en":3,"doc-seo-124487-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124487,13056703020460,"Valentina","https://ap-avatar.wpscdn.com/avatar/be000253dac470eee5d?_k=1778207105932848923",8,"Research & Report","Psychopathology profiles and longitudinal correlates of nonsuicidal self-injury in youth - a machine-learning approach","Nonsuicidal self-injury (NSSI) in youth is clinically heterogeneous. This study aimed to identify distinct psychopathology-based profiles among children and adolescents reporting NSSI and to determine longitudinal correlates. A Brazilian High-Risk Cohort provided 1,345 participants assessed from ages 6–14, with follow-ups at ages 9–18 and 13–23. Unsupervised learning (self-organizing maps, k-means) defined two profiles with high versus low psychopathology, and longitudinal predictors were evaluated using logistic regression, elastic net, and random forest.","Translational [Psychiatry](Psychiatry www.nature.com/tp)[ www.nature.com/tp](Psychiatry www.nature.com/tp)  \nARTICLE OPEN   \nPsychopathology profiles and longitudinal correlates of nonsuicidal self-injury in youth: a machine-learning approach  \nMarcos S. Croci 1,2,3,15 ✉, Marcelo J.A.A. Brañas 1,2,3,15, Ellen F. Finch4, Boyu Ren5,6, Stepheni Uh7, Edwin S. Dalmaijer 8  \n,  \nArthur Caye 2,3,9, Giovanni A. Salum3,9,10, Luis Augusto Paim Rohde3,9,11,12, Euripedes Constantino Miguel 2,3, Pedro Mario Pan 3,13 and Lois W. Choi-Kain5,14  \n© The Author(s) 2026  \n\n|  | Nonsuicidal self-injury (NSSI) in youth is clinically heterogeneous. We aimed to identify distinct psychopathology-based profiles among children and adolescents reporting NSSI and their longitudinal correlates. Participants (N = 1 345) were drawn from the Brazilian High-Risk Cohort Study, which conducted extensive phenotypic assessments at baseline (ages 6–14 years) and across two follow-up waves (ages 9–18 and 13–23 years) . First, we applied unsupervised machine-learning algorithms (Self-Organizing Maps and k-means clustering) to identify distinct psychopathology-based profiles among youth reporting NSSI at the second follow-up. We then employed three models to identify longitudinal predictors of these profiles: logistic regression, elastic net, and random forest. Analyses revealed two distinct profiles of youth reporting NSSI, characterized by high and low psychopathology. The high psychopathology profile (n = 117) was associated with factors identifiable earlier in life and characterized by persistent psychiatric symptoms and significant social adversity throughout development (e.g., family problems and bullying). The low psychopathology profile (n = 127) was marked by lower overall psychopathology and experienced mental health problems only later in development, with less severe challenges over time, such as school suspension and milder depressive symptoms. While the logistic regression did not provide overall significant performance, the elastic net (AUC = 0.72 95% CI 0.65–0.77) and random forest (AUC = 0.73 95% CI 0.67–0.78) did. The present study identified two distinct psychopathology-based profiles among youth reporting NSSI and their longitudinal correlates, using machine learning approaches. Early identification of youth in higher-risk |  |\n| --- | --- | --- |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n| profiles can inform early intervention strategies. |  |  |\n|  | Translational Psychiatry (2026)16:99; [https://doi.org/10.1038/s41398-026-03832-x](https://doi.org/10.1038/s41398-026-03832-x) |  |\n|  |  |  |\n\nINTRODUCTION  \nNonsuicidal self-injury (NSSI) refers to deliberate self-inflicted bodily damage without the intention to die [1] . NSSI is prevalent among youth, with observed rates of 17.4 and 13.4% in adolescents (10–18 years) and young adults (18–24 years), respectively [2]. This causes serious concern for clinicians, families, and policymakers as those who self-injure are more likely to engage in suicidal behavior [3], which is one of the leading causes of mortality among youth, and to develop poor mental health outcomes, such as depression and substance abuse [4, 5] . Given these strong associations and the early emergence of NSSI, these behaviors can serve as an early signal of the youth most in need of interventions to curb the development of complex psychopathology and suicidality during a sensitive period of brain development [6, 7] . Therefore, it is essential to study the correlates and  \npredictors of NSSI to identify at-risk populations and inform early intervention measures.  \nSystematic reviews and meta-analyses have identified various risk factors for self-harm that span multiple domains: demographic (e.g., female sex), psychological (e.g., perfectionism), psychopathological (e.g., depression), behavioral (e.g., substance use), and environmental (","cbCaikEU6YQ2CeYY","https://ap.wps.com/l/cbCaikEU6YQ2CeYY","pdf",1040669,1,14,"English","en",105,"# Introduction\n## Background and prevalence of NSSI in youth\n## Risk and protective factors\n## Study rationale and theoretical models","[{\"question\":\"What was the main goal of the study on nonsuicidal self-injury (NSSI) in youth?\",\"answer\":\"To identify distinct psychopathology-based profiles among youth reporting NSSI and to determine longitudinal correlates for these profiles.\"},{\"question\":\"How were the psychopathology profiles derived in this research?\",\"answer\":\"The study used unsupervised machine-learning methods, including self-organizing maps and k-means clustering, to define profiles at the second follow-up.\"},{\"question\":\"What distinguishes the two identified NSSI profiles?\",\"answer\":\"One profile showed higher psychopathology with persistent psychiatric symptoms and social adversity across development, while the other showed lower overall psychopathology with mental health problems emerging later.\"}]","Psychopathology profiles and longitudinal correlates of nonsuicidal self-injury in youth - a machine-learning approach | PDF",1785822733,35,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"psychopathology-profiles-and-longitudinal-correlates-of-nonsuicidal-self-injury-in-youth-a-machine-learning-approach","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/psychopathology-profiles-and-longitudinal-correlates-of-nonsuicidal-self-injury-in-youth-a-machine-learning-approach/124487/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What was the main goal of the study on nonsuicidal self-injury (NSSI) in youth?","Question",{"text":75,"@type":76},"To identify distinct psychopathology-based profiles among youth reporting NSSI and to determine longitudinal correlates for these profiles.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How were the psychopathology profiles derived in this research?",{"text":80,"@type":76},"The study used unsupervised machine-learning methods, including self-organizing maps and k-means clustering, to define profiles at the second follow-up.",{"name":82,"@type":73,"acceptedAnswer":83},"What distinguishes the two identified NSSI profiles?",{"text":84,"@type":76},"One profile showed higher psychopathology with persistent psychiatric symptoms and social adversity across development, while the other showed lower overall psychopathology with mental health problems emerging later.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]