Using management coaching techniques is feasible and can be beneficial to strengthen health system in Western Kenya
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Background To strengthen the health system in five counties of Western Kenya, the System Enhancement for Transformative Health (SETH) Project provided training on coaching to its officers and coordinators to build their capacity to support health management teams address the challenges they face in their daily work. Health management teams manage entire counties in kenya with limited management training and experience. Following 3 days of training, the project team provided coaching sessions to health management teams and was supervised by a professional coach over a 2-year period. This study aimed to evaluate the feasibility and acceptability of using professional coaching techniques to improve the capacity of project officers to support HMTs in Kenya. Methods (14) Key Informant Interviews (KII) and (5) Group interviews were conducted with all SETH project officers and coordinators trained on coaching and the HMTs members they supported to collect their perceptions on the feasibility and benefits of the intervention components. Respondents were also asked about the sustainability of the project. Results Results show that coaching improved the project officers’ self-reported skills and competencies to provide support to county HMTs. The project offers reported feeling better equipped to help HMTs identify lasting solutions to the challenges faced in their daily work. HMTs also reported having gained knowledge and skills to be used on their daily work thanks to the coaching sessions received. Conclusions The study indicates that integrating coaching in health system strengthening is feasible and appreciated by participants in the intervention. The potential impact of coaching on work performance and on health indicators remains to be evaluated.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it