Psychological distress among pharmacy students in Ghana and its impact on academic performance
Bibliographic record
Abstract
Background: Mental health encompasses emotional, psychological, and social well-being, shaping cognition, behaviour, and interpersonal relationships across the lifespan. There is a high level of stress, anxiety and depression among students of professional programs such as pharmacy. Academic distress is expected to be associated with high general anxiety. Methods: The study employed a quantitative cross-sectional design and used the depression, anxiety, and stress scale (DASS-21) to measure psychological distress and self-reported grade point average (GPA) for academic performance. A sample of 482 pharmacy students from three pharmacy institutions completed the online survey between April and July 2024. Results: Out of 497 participants, 482 completed the study, yielding a 97% completion rate. Of these, 50.6% were female (n=244) and 49.4% male (n=238). Most students (46.9%) were aged 21-24, about a quarter below 21 years, while the fewest were 30 or older. The majority were Christians (86.3%), followed by Muslims (12%), with a small proportion from other faiths. About 80% (n=386) of respondents reported symptoms of depression, anxiety and stress. Both males and females showed similar levels of anxiety and depression. However, females had a 37% higher likelihood of reporting stress than their male counterparts (OR=0.73, p=0.002). Conclusions: This study revealed a high prevalence of anxiety, depression, and stress among pharmacy students in Ghana, with female students particularly prone to stress. While anxiety and depression correlate positively with higher academic performance, stress shows a negative impact.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".