Perceptions of health stakeholders on task shifting and motivation of community health workers in different socio demographic contexts in Kenya (nomadic, peri-urban and rural agrarian)
Bibliographic record
Abstract
The shortage of health professionals in low income countries is recognized as a crisis. Community health workers are part of a “task-shift” strategy to address this crisis. Task shifting in this paper refers to the delegation of tasks from health professionals to lay, trained volunteers. In Kenya, there is a debate as to whether these volunteers should be compensated, and what motivation strategies would be effective in different socio-demographic contexts, based type of tasks shifted. The purpose of this study was to find out, from stakeholders’ perspectives, the type of tasks to be shifted to community health workers and the appropriate strategies to motivate and retain them. This was an analytical comparative study employing qualitative methods: key informant interviews with health policy makers, managers, and service providers, and focus group discussions with community health workers and service consumers, to explore their perspectives on tasks to be shifted and appropriate motivation strategies. The study found that there were tasks to be shifted and motivation strategies that were common to all three contexts. Common tasks were promotive, preventive, and simple curative services. Common motivation strategies were supportive supervision, means of identification, equitable allocation of resources, training, compensation, recognition, and evidence based community dialogue. Further, in the nomadic and peri-urban sites, community health workers had assumed curative services beyond the range provided for in the Kenyan task shifting policy. This was explained to be influenced by lack of access to care due to distance to health facilities, population movement, and scarcity of health providers in the nomadic setting and the harsh economic realities in peri-urban set up. Therefore, their motivation strategies included training on curative skills, technical support, and resources for curative care. Data collection was viewed as an important task in the rural site, but was not recognized as priority in nomadic and peri-urban sites, where they sought monetary compensation for data collection. The study concluded that inclusion of curative tasks for community health workers, particularly in nomadic contexts, is inevitable but raises the need for accreditation of their training and regulation of their tasks.
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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 | 0.005 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".