Frequency and machine learning predictors of depressive, anxiety, obsessive-compulsive symptoms, and suicidal ideation among university students

Abstract

Introduction Prospective studies on mental health of students showed that young adults enroled in university are affected by poorer mental health than other working peers or adults, and this condition is responsible for a large proportion of disability-adjusted life-years Methods We enrolled 1388 students at the baseline (and 557 completed follow-up after six months) who reported their demographic information and completed self-report questionnaires on depressive, anxiety and obsessive-compulsive symptoms. We applied multiple regression modelling and supervised machine learning to evince associations and predict the risk factors of poorer mental health at baseline and follow-up Results Approximately one out of five students reported severe depressive symptoms and/or suicidal ideation. An association of economic worry with depression was evidenced at the beginning of the study (when there was a high frequency of worry OR = 3.11 [1.88 - 5.15]) and during followup.Supervised machine learning exhibited high accuracy in predicting the students who maintained well-being (balanced accuracy = 0.85) or absence of suicidal ideation, but its performance was almost null in identifying those whose symptoms worsened. Conclusions Students' severe mental health problems are reaching worrying percentages, and few demographic factors can be leveraged to predict poor mental health outcomes. Further research including people with lived experience is crucial to assess students' needs and improve the prediction of those at risk of developing worse symptoms.

The prevalence of depressive and anxiety symptoms and functional constipation, and related risk factors among Chinese university students: a cross-sectional study

“…Furthermore, the distribution of severity of depressive and anxiety symptoms revealed a strati cation of depressive and anxiety symptoms among university students. Our ndings were consistent with those of Piscoya-Tenorio et al and Meda et al in that a decreasing trend in the prevalence of depressive and anxiety symptom severity from mild to severe was observed [58,59]. In contrast, an increasing trend was reported in the study of Rabby et al [60].…”

“…Previous studies have reported that variations in factors such as hormone levels, socio-cultural factors, and stress coping styles among females were signi cantly associated with symptoms of depression and anxiety [59,[61][62][63][64]. Strained or con icted relationships between parents may weaken an individual's social and emotional support system, thus increasing vulnerability to stress and serving as a risk factor for depression and anxiety [65,66].…”

Using a Classifier Ensemble for Preventing Burnout in University Students: A Study Case in Valparaíso

“…Moreover, in our study, female participants are classified as having moderate anxiety and mild anxiety for male participants. Considering both genders, the medians of the BAI scores of this study are higher compared to the medians of both stages in [14]. Also, regarding the distribution of BAI scores, this study's IQR values of both genders are similar to those of female participants of the first stage.…”

“…In [14], Italian university students' mental health was investigated, considering students from different areas (e.g., Arts, Law, Economics, Medicine, Psychology and Mental Health, Neuroscience, and Pharmacy). The study considered two stages, the first one with 1,388 participants, and six months later, 557 persons participated in the second stage.…”