Factors Associated with Stress, Anxiety, and Depression Among Management School Students in Senegal
Bibliographic record
Abstract
Mental health among students in Senegal remains an under-explored area, with limited research and prevention efforts. At the African Center for Higher Studies in Management (CESAG), students face high academic demands, highlighting the importance of investigating stress, anxiety, and depression within this population. This study aimed to identify factors associated with anxiety-depressive states, specifically stress, anxiety and depression, among CESAG students. A cross-sectional, observational, descriptive, and analytical study was conducted from July 22 to August 23, 2024. Data were collected through an electronic questionnaire. Stress, anxiety, and depression were assessed using the Perceived Stress Scale (PSS), the Generalized Anxiety Disorder-7 (GAD-7) score, and the Patient Health Questionnaire-9 (PHQ-9) score, respectively. Data analysis was performed using RStudio (version 2024.12.1.563). Informed and voluntary consent of the participants was ensured. A total of 426 students completed the online questionnaire. The mean age was 23.4 years. Stress was observed in 45.6% of students, anxiety in 21.4%, and depression in 35.4%. Risk factors for stress included belonging to the [20-25 years[ age group (ORa = 5.68, 95%CI [1.67-19.31]) or the ≥30 years group (ORa = 8.8, 95%CI [1.5-51.64]), poor sleep quality (ORa = 7.05, 95%CI [2.32-21.44]), low financial income (ORa = 11.23, 95%CI [4.34-29.06]), low self-esteem (ORa = 15.13, 95%CI [3.18-72.13]) or moderate self-esteem (ORa = 7.96, 95%CI [2.83-22.4]), a negative emotional state (ORa = 4.7, 95%CI [1.64-13.46]), and the absence of physical activity (ORa = 5.03, 95%CI [1.88-13.49]). Living alone was a protective factor against anxiety among students (ORa = 0.16, 95%CI [0.09-0.29]). Depression was associated with several risk factors: poor sleep quality (ORa = 8.07, 95%CI [2.72-23.88]), low financial income (ORa = 4.38, 95%CI [1.42-13.48]), living alone (ORa = 3.53, 95%CI [1.1-11.34]), poor diet (ORa = 13.03, 95%CI [3.84-44.18]), low self-esteem (ORa = 18.21; 95%CI [2.62-126.41]) or moderate self-esteem (ORa = 9.19, 95%CI [1.66-51.01]), and a negative emotional state (ORa = 5.54, 95%CI [1.64-18.71]). A passive coping style was found to be protective (ORa = 0.25, 95%CI [0.08-0.8]). These findings emphasize the importance of preventive strategies to promote CESAG students’ mental health and well-being. Targeted awareness campaigns and psychological support are essential to achieving this goal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".