Mobilising various levers of team commitment: the experience of a quality contest in Burundi
Bibliographic record
Abstract
Issue The quality of care is both a strategical and a complex issue that requires the commitment of all field-based staff. The Quality Contest (QC) in Burundi was built on a gamification approach addressing various levers. Extrinsic motivation was nurtured by a positive (‘sportive’) competition with team rewards but moreover by social recognition, team building and strengthening of a professional identity. Intrinsic motivation was developed through capacity building, professional autonomy, satisfaction and explicit values (quality, equity, trust…). Methodology A Quali-Quanti approach is used in an evaluation of the implementation (intensity and fidelity) and the outcomes of the intervention. The design was based on a stepwedge cluster RCT. Data were collected before, during and after the entire cycle of the first QC (2014-16) that involved 62 voluntary health centers (HC) and about 1000 agents workers. Results Process There was a high level of compliance to the intervention by health workers. Initial adherence was linked with the competitive facet and a close coaching, including all staff, provided a steady source of motivation and commitment. Coaches promoted team spirit, capacity for self-management and skill building by offering support, feed-back and a trusting attitude. Impact The range of improvements was limited by financial and time constraints. The most significant changes were the teams’ commitment and the strengthening of professional identities, especially for the agents with the lowest level of training. For the second cycle of the QC, almost all the HS enrolled again. Lessons Both underestimating the importance of human motivation and overestimating the real effects of extrinsic motivator approaches are traps in the way to healthcare quality. Gamification and close coaching are powerful techniques to support motivation and commitment. By combining different motivational strategies, interventions can become more adequate to a complex reality. Key messages: Gamification and close coaching are powerful techniques to support motivation and commitment. By combining different motivational strategies, interventions can become more adequate to a complex reality.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".