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Who attempts suicide among medical students?
Author(s) -
Marcon G.,
Massaro Carneiro Monteiro G.,
Ballester P.,
Cassidy R. M.,
Zimerman A.,
Brui A. R.,
Diemen L.,
Hauck S.,
Passos I. C.
Publication year - 2020
Publication title -
acta psychiatrica scandinavica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.849
H-Index - 146
eISSN - 1600-0447
pISSN - 0001-690X
DOI - 10.1111/acps.13137
Subject(s) - poisson regression , suicide attempt , suicidal ideation , suicide prevention , medicine , clinical psychology , family history , poison control , psychiatry , injury prevention , psychology , demography , medical emergency , environmental health , population , sociology
Objective To identify factors associated with a history of suicide attempt in medical students. Methods A Web‐based survey was sent out to a sample of medical students. A multi‐predictor Poisson regression was performed to identify factors associated with a history of suicide attempt. In addition, an elastic net regularization was used to build a risk calculator to identify students at risk for attempted suicide. Results A total of 4,840 participants were included in the study. Prevalence of suicide attempts in the sample was 8.94%. Risk factors associated with past suicide attempt in the multi‐predictor Poisson regression were as follows: female gender (P < 0.001); homosexuality (P < 0.001); low income (P = 0.026); bullying by university peers (P = 0.006); childhood (P = 0.001) or adult (P = 0.001) trauma; family history of suicide (P = 0.005); suicidal ideation within the last month (P < 0.001); daily tobacco use (P = 0.037); and being at severe risk for alcohol abuse (P = 0.023). Our elastic net model performed well with an AUC of 0.83. Conclusions This study identifies a number of key factors associated with a history of suicide attempts among medical students. Future longitudinal studies should assess the causal relationship between these factors and suicide attempts. Additionally, these results demonstrate that current available data on suicide attempts among medical students can be used to develop an accurate risk algorithm.