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J Clin Psychiatry. 2017 Jul;78(7):e828-e836. doi: 10.4088/JCP.17m11485.

A Risk Algorithm for the Persistence of Suicidal Thoughts and Behaviors During College.

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Research Group Psychiatry, Department of Neurosciences, KU Leuven University, Herestraat 49, Leuven, Belgium.
Research Group Psychiatry, Department of Neurosciences, KU Leuven University, Leuven, Belgium.
Department of Psychiatry, Harvard Medical School, Boston; and Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, Massachusetts, USA.
Department of Clinical, Neuro-, and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
School of Education, Boston University, Boston, Massachusetts, USA.
Harvard Medical School, Department of Health Care Policy, Harvard University, Boston, Massachusetts, USA.
Department of Psychology, Harvard University, Cambridge, Massachusetts, USA.



The primary aims of this study are to (a) identify patterns of suicidal thoughts and behaviors (STB) during college among students with lifetime pre-matriculation STB and (b) develop a risk-screening algorithm for persistence of pre-matriculation STB during college.


Data come from the Leuven College Surveys, a series of prospective cohort studies of all incoming KU Leuven University freshmen. In the academic year 2012-2013, 4,889 incoming freshmen (73.2% response rate) provided baseline data on sociodemographic variables, childhood-adolescent traumatic experiences, 12-month stressful experiences, 12-month mental disorders, 12-month STB, and severity markers of pre-matriculation STB. A total of 2,566 students (69.3% conditional response rate) participated in 12- and 24-month follow-up surveys during the first 2 college years.


Thirteen percent (weighted n = 535) of incoming freshmen reported lifetime pre-matriculation STB. Of those, 28.0% reported 12-month STB in 1 follow-up assessment, and another 27.7%, in both follow-up assessments. High persistence of STB (ie, 12-month STB in 2 follow-up assessments) was most strongly associated with severity markers of pre-matriculation STB, with odds ratios in the 2.4-10.3 range and population attributable risk proportions between 9.2% and 50.8%. When the aim was for less than 50% of false-positive cases (positive predictive value = 54.4%), a multivariate predictive risk algorithm (cross-validated area under the curve = 0.79) situated 59.9% of highly persistent cases among the 30% respondents with highest baseline predicted risk.


An individualized web-based screening approach is a promising strategy to identify students at the time of university entrance who may be at high risk for STB persistence during their academic career.

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