TY  - JOUR
PY  - 2023//
TI  - Development and evaluation of a predictive algorithm and telehealth intervention to reduce suicidal behavior among university students
JO  - Psychological medicine
A1  - Hasking, Penelope A.
A1  - Robinson, Kealagh
A1  - McEvoy, Peter
A1  - Melvin, Glenn
A1  - Bruffaerts, Ronny
A1  - Boyes, Mark E.
A1  - Auerbach, Randy P.
A1  - Hendrie, Delia
A1  - Nock, Matthew K.
A1  - Preece, David A.
A1  - Rees, Clare
A1  - Kessler, Ronald C.
SP  - ePub
EP  - ePub
VL  - ePub
IS  - ePub
N2  - BACKGROUND: 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. <br><br>METHODS: Data come from several waves of a prospective cohort study (2016-2022) of college students (n = 5454). All first-year students were invited to participate as volunteers. (Response rates range: 16.00-19.93%). A stepped-care approach was implemented: (i) all students received a comprehensive list of services; (ii) those reporting past 12-month suicidal ideation were directed to a safety planning application; (iii) those identified as high risk of suicidal behavior by the algorithm or reporting 12-month suicide attempt were contacted via telephone within 24-h of survey completion. Intervention focused on support/safety-planning, and referral to services for this high-risk group. <br><br>RESULTS: 5454 students ranging in age from 17-36 (s.d. = 5.346) participated; 65% female. The algorithm identified 77% of students reporting subsequent suicidal behavior in the top 15% of predicted probabilities (Sensitivity = 26.26 [95% CI 17.93-36.07]; Specificity = 97.46 [95% CI 96.21-98.38], PPV = 53.06 [95% CI 40.16-65.56]; AUC range: 0.895 [95% CIs 0.872-0.917] to 0.966 [95% CIs 0.939-0.994]). High-risk students in the Intervention Cohort showed a 41.7% reduction in probability of suicidal behavior at 12-month follow-up compared to high-risk students in the Control Cohort. <br><br>CONCLUSIONS: Predictive risk algorithms embedded into universal screening, coupled with telehealth intervention, offer significant potential as a suicide prevention approach for students.<p />  <p>Language: en</p>
LA  - en
SN  - 0033-2917
UR  - http://dx.doi.org/10.1017/S0033291723002714
ID  - ref1
ER  -