Development and evaluation of a predictive algorithm and telehealth intervention to reduce suicidal behavior among university students

Suicidal behaviors are prevalent among college students; however, students remain reluctant to seek support. We developed a predictive algorithm to identify students at risk of suicidal behavior and used telehealth to reduce subsequent risk. Data come from everal waves of a prospective cohort study...

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Bibliographic Details
Published in:	Psychological medicine Vol. 54; no. 5; pp. 971 - 979
Main Authors:	Hasking, Penelope A., Robinson, Kealagh, McEvoy, Peter, Melvin, Glenn, Bruffaerts, Ronny, Boyes, Mark E., Auerbach, Randy P., Hendrie, Delia, Nock, Matthew K., Preece, David A., Rees, Clare, Kessler, Ronald C.
Format:	Journal Article
Language:	English
Published:	England Cambridge University Press 01.04.2024
Subjects:	Algorithms At risk populations At risk students Behavior Cohort analysis College students Colleges & universities Female High risk Humans Intervention Male Medical technology Mental health Predictions Prevention programs Probability Prospective Studies Response rates Risk Risk Factors Risk groups Risk reduction Safety Self destructive behavior Sex crimes Students Suicidal behavior Suicidal Ideation Suicide Suicide prevention Suicides & suicide attempts Telecommunications Telemedicine Telephone surveys Universities Volunteers retrospective cohort trial tertiary education suicide prevention predictive risk treatment access algorithm
ISSN:	0033-2917, 1469-8978, 1469-8978
Online Access:	Get full text
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