Sleep quality among undergraduate medical students in Rwanda: a comparative study
Bibliographic record
Abstract
Despite the abundance of literature highlighting poor sleep quality among medical students and its detrimental impact on their mental well-being and academic performance, no study has been conducted to investigate the sleep quality of undergraduate medical students in Rwanda to date. Therefore, this study sought to determine the magnitude of sleep quality of undergraduate medical students in Rwanda and to compare the scores of seven components of sleep quality across classes. This cross-sectional study was conducted among 290 undergraduate medical students aged 18-35 years (mean = 24, SD = 2.9) randomly recruited countrywide from 1st November 2021 to 1st March 2022. The questionnaire was self-administered with 2 sections: characteristics of medical students, and Pittsburgh Sleep Quality Index (PSQI). The Pearson Chi-square test was used to test whether the categories of seven components of sleep quality differ between classes, then ANOVA followed by the post hoc test was used to test if the seven components and global score of Pittsburgh Sleep Quality Index differ between classes. The results revealed that the global PSQI mean score was 7.73 (SD = 2.83), with fifth-year medical students reporting the highest PSQI mean score (M = 8.44, SD = 2.77), followed by first-year (M = 8.15, SD = 3.31). One-way ANOVA showed that the global PSQI score (F = 2.76, p = 0.028), subjective sleep quality (F = 3.35, p = 0.011), habitual sleep efficiency (F = 10.20, p < 0.001), and daytime dysfunction (F = 3.60, p = 0.007) were significantly different across classes. Notably, the post hoc test revealed significant scores differences in the global PSQI score between class II and V (p = 0.026), in subjective sleep quality between class I and II (p = 0.043), and between class I and IV (p = 0.016); habitual sleep efficiency between class V and all other classes (p < 0.001); and daytime dysfunction between class III and IV (p = 0.023). This paper concludes by arguing that poor sleep quality is highly prevalent among medical students in Rwanda, with final and first-year students reporting the poorest sleep quality. There were significant differences across classes in the global PSQI, subjective sleep quality, habitual sleep efficiency, and daytime dysfunction. Intervention approaches such as sleep education, behavioral changes, and relaxing techniques are recommended to address contributing factors and ultimately maximize the academic goals of Rwandan medical students.
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 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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".