{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T04:04:50Z","timestamp":1790913890261,"version":"4.1.0"},"reference-count":62,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2025,6,6]],"date-time":"2025-06-06T00:00:00Z","timestamp":1749168000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000025","name":"National Institute of Mental Health","doi-asserted-by":"publisher","award":["R21MH123916, K23MH120437"],"award-info":[{"award-number":["R21MH123916, K23MH120437"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,7,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Hypothesis<\/jats:title>\n                    <jats:p>Suicide attempt is a complex behavior influenced by a combination of factors including clinical, neurocognitive, and environmental. We aimed to leverage multimodal data collected during pre\/early adolescence in research settings to predict self-report of suicide attempts by mid-late adolescence reported in pediatric settings. We hypothesized that different data types contribute to suicide attempt prediction and that clinical features would be most predictive of future suicide attempts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Study Design<\/jats:title>\n                    <jats:p>We applied machine learning methods to clinical, neurocognitive, and geocoded neighborhood environmental data from the Philadelphia Neurodevelopmental Cohort study (Mean age [SD]\u2005=\u200511.1 [2.2], 53.3% female, 51.4% Black participants) to predict suicide attempt reported ~5 years later in two independent pediatric settings: primary care (n\u2005=\u2005922, 5.3% suicide attempt) or emergency department (n\u2005=\u2005497, 8.2% suicide attempt). We tested prediction performance using all data versus using subsets of features identified by three feature selection algorithms (Lasso, Relief, Random Forest).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Study Results<\/jats:title>\n                    <jats:p>In the primary care sample, suicide attempt prediction using subsets of selected features (predictors) was good, achieving AUC\u2005=\u20050.75, sensitivity\/specificity 0.76\/0.77. The use of highest-ranking features yielded similar prediction performance in external validation using the independent emergency department sample with AUC\u2005=\u20050.74, sensitivity\/specificity 0.66\/0.70. Different algorithms identified different high-ranking features, but overall multiple data domains were represented among the highest-ranking features. Besides suicidal ideation, the highest-ranking clinical predictive symptoms were from psychosis or mania spectrum.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Results suggest that data collected at a single timepoint during preadolescence can inform suicide attempt prediction during mid-late adolescence, in different clinical settings. Findings encourage incorporation of multiple data types including neurocognitive and geocoded data, alongside clinical data, in machine learning suicide attempt prediction pipelines.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/schbul\/sbaf064","type":"journal-article","created":{"date-parts":[[2025,4,18]],"date-time":"2025-04-18T07:52:09Z","timestamp":1744962729000},"page":"895-905","source":"Crossref","is-referenced-by-count":3,"title":["Prediction of Adolescent Suicide Attempt by Integrating Clinical, Neurocognitive and Geocoded Neighborhood Environment Data"],"prefix":"10.1093","volume":"51","author":[{"given":"Elina","family":"Visoki","sequence":"first","affiliation":[{"name":"Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children\u2019s Hospital of Philadelphia (CHOP) , Philadelphia, PA ,","place":["United States"]},{"name":"Lifespan Brain Institute of CHOP and Penn Medicine , Philadelphia, PA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tyler M","family":"Moore","sequence":"additional","affiliation":[{"name":"Lifespan Brain Institute of CHOP and Penn Medicine , Philadelphia, PA ,","place":["United States"]},{"name":"Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Victor M","family":"Ruiz","sequence":"additional","affiliation":[{"name":"Department of Biomedical and Health Informatics, Children\u2019s Hospital of Philadelphia , Philadelphia, Pennsylvania, PA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joel A","family":"Fein","sequence":"additional","affiliation":[{"name":"Emergency Medicine, Children\u2019s Hospital of Philadelphia (CHOP) , Philadelphia, PA ,","place":["United 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and Adolescent Psychiatry and Behavioral Sciences, Children\u2019s Hospital of Philadelphia (CHOP) , Philadelphia, PA ,","place":["United States"]},{"name":"Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raquel E","family":"Gur","sequence":"additional","affiliation":[{"name":"Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children\u2019s Hospital of Philadelphia (CHOP) , Philadelphia, PA ,","place":["United States"]},{"name":"Lifespan Brain Institute of CHOP and Penn Medicine , Philadelphia, PA ,","place":["United States"]},{"name":"Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania , Philadelphia, PA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fuchiang R","family":"Tsui","sequence":"additional","affiliation":[{"name":"Department of 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