University students at significant risk for mental health effects of COVID-19 lockdown
University students who experienced lockdowns due to COVID-19 exhibited a high prevalence of mental health issues, according to results of a survey study published in JAMA Network Open.
“In a 2016 national survey of 18,875 French university students, 37% of the participants declared having experienced an episode of depression, and 8% reported having suicidal thoughts in the past 12 months,” Marielle Wathelet, MD, of the department of public health at Lille University Centre Hospital in France, and colleagues wrote. “Furthermore, the COVID-19 pandemic threatens to disrupt the provision of mental health services, and the most at-risk populations — primarily young individuals — are already the least likely to seek help. Finally, quarantine poses social and economic consequences, increasing the usual barriers to seeking care.”
A 2008 study found that young adults aged 16 to 24 years had an especially high risk for mental health issues during previous disease outbreak lockdowns. Moreover, results of a study conducted during the initial stage of the pandemic suggested students in China were at greater risk for stress, anxiety and depression related to COVID-19 than were older adults.
Wathelet and colleagues conducted the current study to determine the prevalence of self-reported mental health symptoms and associated factors, as well as to assess care seeking among 69,054 university students, most of whom were women (72.8%) and first-year students (47%), during France’s COVID-19 quarantine between April 17 and May 4. They asked all French universities to send an email to their students regarding completing an online questionnaire. Main outcomes and measures included rates of self-reported suicidal ideation, severe distress, stress, anxiety and depression according to results of the 22-item Impact of Events Scale-Revised, the 10-item Perceived Stress Scale, the 20-item State Trait Anxiety inventory (State subscale) and the 13-item Beck Depression Inventory, respectively. Sociodemographic characteristics, precariousness indicators, media consumption, information on the social environment and health-related data served as covariates. The researchers also collected data related to care seeking and identified risk factors using multivariable logistic regression analyses.