Ethics of task shifting in the health workforce: exploring the role of community health workers in HIV service delivery in low- and middle-income countries
Bibliographic record
Abstract
BACKGROUND: Task shifting is increasingly used to address human resource shortages impacting HIV service delivery in low- and middle-income countries. By shifting basic tasks from higher- to lower-trained cadres, such as Community Health Workers (CHWs), task shifting can reduce overhead costs, improve community outreach, and provide efficient scale-up of essential treatments like antiretroviral therapies. Although there is rich evidence outlining positive outcomes that CHWs bring into HIV programs, important questions remain over their place in service delivery. These challenges often reflect concerns over whether CHWs can mitigate HIV through a means that does not overlook the ethical and practical constraints that undergird their work. Ethical and practical guidance thus needs to become the cornerstone of CHW deployment. This paper analyzes such challenges through the lens of Ethical Principlism. METHODS: We examined papers identifying substantive and ethical challenges impacting CHWs as they provide HIV services in low- and middle-income contexts. To do this, we analyzed papers written in English and published from year 2000 or later. These articles were identified using MEDLINE, Cochrane Database of Systematic Reviews, and Google Scholar databases. In total, 465 articles were identified, 78 of which met our inclusion criteria. Article reference lists and grey literature were also examined. RESULTS: CHWs experience specific challenges while carrying out their duties, such as conducting emotionally- and physically-demanding tasks with often inadequate training, supervision and compensation. CHWs have also been poorly integrated into health systems, which not only impacts quality of care, but can hinder their prospects for promotion and lead to CHW disempowerment. As we argue, these challenges can be addressed if a set of ethical principles is prioritized, which specifically entail the principles of respect for persons, justice, beneficence, proportionality and cultural humility. CONCLUSIONS: CHWs play a crucial role in HIV service delivery, yet the ethical challenges that can accompany their work cannot be overlooked. By prioritizing ethical principles, policymakers and program implementers can better ensure that CHWs are combatting HIV through a means that does not exploit or take their critical role within service delivery for granted.
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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 | 0.083 | 0.182 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".