Prevalence of Depression and Associated Factors among Medical Students in a Southern Nigerian University
Bibliographic record
Abstract
INTRODUCTION: Medical students may be vulnerable to depression and other psychiatric morbidity. This study sought to assess the prevalence of depression and associated factors among medical students in Niger Delta University, Bayelsa State, Nigeria. METHODS: Using a self-administered, author-developed questionnaire with adaptations from the Patient-rated version of Mini-International Neuropsychiatric Interview (MINI-PR) and the Depression Anxiety Stress Scale (DASS), data including socio-demographic characteristics, alcohol use/abuse, cigarette smoking, features of depression and anxiety were collected from 243 medical students in this descriptive cross-sectional study over a period of 4months. RESULTS: Of the 243 participants, 52.7% were male, mostly aged 18 to 24 years (67.1%). The incidence of depression, suicidal ideation, alcohol use, and psychoactive substance use as defined by the MINI questionnaire was 30.5%, 14.8%, 14.8%, and 9.9%, respectively. As defined by DASS 21, almost a third suffered different levels of anxiety (29.6%), and less than one-fifth reported different levels of stress (17.7%). Female gender and year of study showed a significant association with the diagnosis of depression (X2=15.75;p–0.008). Living arrangement (X2=11.43;p–0.022), perception of accommodation condition (X2=16.35;p–0.001), academic performance (X2=18.02;p–0.001), and experience of academic failure (X2=5.13;p–0.023) all had a significant relationship with depression among the study population. CONCLUSION: Prevalence of depression among medical students is high; its diagnosis showed a significant association with female gender, year of study, and perception of social and academic factors. Several comorbid psychiatric conditions may coexist with depression among medical students; therefore, the approach to their mental health should be holistic with attention paid to associated factors and psychiatric comorbidities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".