Lay Health Workers experience of a tailored knowledge translation intervention to improve job skills and knowledge: a qualitative study in Zomba district Malawi
Bibliographic record
Abstract
BACKGROUND: Like many sub-Saharan African countries, Malawi is facing a critical shortage of skilled healthcare workers. In response to this crisis, a formal cadre of lay health workers (LHW) has been established and now carries out several basic health care services, including outpatient TB care and adherence support. While ongoing training and supervision are recognized as essential to the effectiveness of LHW programs, information is lacking as to how these needs are best addressed. The objective of this qualitative study was to explore LHWs responses to a tailored knowledge translation intervention they received, designed to address a previously identified training and knowledge gap. METHODS: Forty-five interviews were conducted with 36 healthcare workers. Fourteen to sixteen interviews were done at each of 3 evenly spaced time blocks over a one year period, with 6 individuals interviewed more than once to assess for change both within and across individuals overtime. RESULTS: Reported benefits of the intervention included: increased TB, HIV, and job-specific knowledge; improved clinical skills; and increased confidence and satisfaction with their work. Suggestions for improvement were less consistent across participants, but included: increasing the duration of the training, changing to an off-site venue, providing stipends or refreshments as incentives, and adding HIV and drug dosing content. CONCLUSIONS: Despite the significant departure of the study intervention from the traditional approach to training employed in Malawi, the intervention was well received and highly valued by LHW participants. Given the relative low-cost and flexibility of the methods employed, this appears a promising approach to addressing the training needs of LHW programs, particularly in Low- and Middle-income countries where resources are most constrained.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".