Prevalence and Associated Factors of Depression in Medical Students in a Northern Thailand University: A Cross-Sectional Study.
Suwatthanachai PhomprasithNuntaporn KarawekpanyawongKanokporn PinyopornpanishWichuda JiraporncharoenBenchalak ManeetonDumnoensun PruksakornSuppachai LawanaskolPublished in: Healthcare (Basel, Switzerland) (2022)
This study was conducted to investigate the prevalence and associated factors of depression in medical students. This cross-sectional study investigated the prevalence and associated factors of depression in medical students from May 2018 to April 2019. Depression was diagnosed using the nine-item Patient Health Questionnaire. We evaluated the following potential predictors: demographic data, stressors, psychiatric comorbidities, emotional intelligence (EI), and perceived social support. The association between potential factors and depression was analyzed using multiple logistic regression analysis. The prevalence of depression was 149 of 706 students with 12.5% suicidality. Second- and fourth-year medical students were high-risk groups. Risk factors identified were insufficient income, physical illness, and previous psychiatric illness. Depression in medical students likely coincides with anxiety, internet addiction, sleep problems, and loneliness. Highly associated stressors were personal relationships, physical health, mental health, difficulties in social relationships, satisfaction with grades, and boredom with medical education. Protective EI factors included emotional self-control, problem-solving abilities, inner peace, and life satisfaction. Up to 21.1% of medical students had depression. In this study, among multiple known risk factors of depression, we found that EI is the novel protective factor against depression among medical students. EI training might be protective intervention for medical students in the future.
Keyphrases
- medical students
- mental health
- depressive symptoms
- risk factors
- sleep quality
- social support
- physical activity
- healthcare
- randomized controlled trial
- public health
- case report
- human health
- health information
- deep learning
- machine learning
- high resolution
- mass spectrometry
- climate change
- psychometric properties
- medical education
- artificial intelligence
- patient reported
- high school