Prevalence and Determinants of Academic Bullying Among Junior Doctors in Sierra Leone: Cross-Sectional Study
Bibliographic record
Abstract
Background: Academic bullying among junior doctors-characterized by repeated actions that undermine confidence, reputation, and career progression-is associated with adverse consequences for mental health and professional development. Objective: This study aimed to investigate the prevalence and determinants of academic bullying among junior doctors in Sierra Leone. Methods: We conducted a cross-sectional survey of 126 junior doctors at the University of Sierra Leone Teaching Hospitals Complex in Freetown between January 1 and March 30, 2024. Participants were selected through random sampling. Data were collected using a semistructured, self-administered questionnaire and analyzed with descriptive statistics and multivariable logistic regression. Results: Of the 126 participants (n=77, 61.1% male; mean age 31.9, SD 5.05 years), 86 (68.3%) participants reported experiencing academic bullying. Among those, 55.8% (n=48) of participants experienced it occasionally and 36% (n=31) of participants experienced it very frequently. The most common forms were unfair criticism (n=63, 73.3%), verbal aggression (n=57, 66.3%), and derogatory remarks (n=41, 47.7%). Consultants and senior doctors were the main perpetrators, with incidents primarily occurring during ward rounds, clinical meetings, and academic seminars. No statistically significant predictors of bullying were found for gender (odds ratio 2.07, 95% CI 0.92-4.64; P=.08) or less than 2 years of practice (odds ratio 0.30, 95% CI 0.05-1.79; P=.19). Conclusions: Academic bullying is widespread among junior doctors at the University of Sierra Leone Teaching Hospitals Complex. It has serious consequences for their mental health and professional development. There is an urgent need for clear and culturally appropriate policies, targeted training programs, confidential reporting systems, and leadership development. Promoting ethical leadership and fostering a culture of respect can help reduce incivility and burnout, leading to a healthier work environment for junior doctors.
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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 | 0.001 | 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 | 0.000 |
| 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".