Bibliographic record
Abstract
Abstract: Objective: The study investigates the workplace-related determinants of academic faculty burnout in health professions institutions. Methods: This mixed-methods study employs both quantitative and qualitative approaches. We invited 154 academic faculty members from health professions colleges to participate and measured burnout using the original 22-item Maslach Burnout Inventory (subscales: Emotional Exhaustion, Depersonalization, and Low Personal Accomplishment). A p-value of less than .05 is considered statistically significant. We used a direct content analysis approach to code the interview transcripts after transcription. Results: Out of the 96 participants (62%), 38 (39.6%) reported mild to moderate burnout, while 60.4% experienced significant burnout. Emotional Exhaustion (41.7%) was more prevalent than Personal Accomplishment (38.5%) and Depersonalization (DP) (25%) among most faculty members. A psychometric analysis showed a significant correlation ( p-value = .02) between burnout and education level. Our analysis identified four key factors influencing burnout: (a) workload, (b) lack of integrity in professional competence, (c) workplace stress, and (d) insufficient engagement in professional development activities leading to career dissatisfaction. Conclusion: Faculty members in health professions face high levels of burnout. Preventive measures and corrective programs to reduce burnout and enhance performance are recommended.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".