Burnout, motivation and job satisfaction among community health workers recruited for a depression training in Madhya Pradesh, India: a cross-sectional study
Bibliographic record
Abstract
Introduction Burnout, low motivation and poor job satisfaction among community health workers (CHWs) have negative impacts on health workers and on patients. This study aimed to characterise levels of burnout, motivation and job satisfaction in CHWs in Madhya Pradesh, India and to determine the relation between these levels and participant characteristics. This study can inform efforts to promote well-being and address stress in this population. Methods In this cross-sectional study, we recruited participants via simple random sampling without replacement. We administered two validated questionnaires, the Copenhagen Burnout Inventory and a Motivation and Job Satisfaction Assessment, to CHWs who had enrolled in a training programme to deliver a brief psychological intervention for depression. We calculated mean scores for each questionnaire item, examined the reliability of the measures and analysed associations between participant demographic characteristics and questionnaire scores. Results 339 CHWs completed the questionnaires. The personal burnout domain had the highest mean burnout score (41.08, 95% CI 39.52 to 42.64, scale 0–100) and 33% of participants reported moderate or greater levels of personal burnout. Items that reflected physical exhaustion had the highest item-test correlations. The organisation commitment domain had the highest mean motivation score (mean 3.34, 95% CI 3.28 to 3.40, scale 1–4). Items describing pride in CHWs’ work had the highest item-test correlations. Several pairwise comparisons showed that higher education levels were associated with higher motivation levels (degree or higher vs eighth standard (p=0.0044) and 10th standard (p=0.048) and 12th standard versus eighth standard (p=0.012)). Cronbach’s alpha was 0.82 for the burnout questionnaire and 0.86 for the motivation and job satisfaction questionnaire. Conclusion CHWs report experiencing burnout and feeling physically tired and worn out. A sense of pride in their work appears to contribute to motivation. These findings can inform efforts to address burnout and implement effective task-sharing programmes in low-resource settings.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".