Assessing the acceptability and feasibility of proactive community case management: A qualitative study in Chadiza District, Zambia
Bibliographic record
Abstract
Abstract Zambia has implemented passive malaria community case management (CCM), during which symptomatic people seek care at a community health worker’s (CHW) abode, since 2011. In 2021, the National Malaria Elimination Program implemented a two-arm cluster-randomized controlled trial to measure the impact of proactive CCM (ProCCM) compared to routine passive CCM on malaria incidence and prevalence in Chadiza District, Eastern Province. ProCCM is a strategy of regular visits by CHWs to all households in a community to identify people with malaria symptoms, provide rapid diagnostic testing, and treat those with malaria with artemisinin combination therapy. We conducted a qualitative midline assessment of this trial to describe the feasibility and acceptability of ProCCM. Key informant interviews (KIIs) were conducted with CHWs provincial and district staff, health facility staff, and community leaders, while focus group discussions were conducted with community members from six ProCCM and six passive CCM clusters. All respondent groups preferred ProCCM to passive CCM, reporting that it reduces distance travelled to seek care and provides care to people with challenges accessing it. Most CHWs and health facility staff perceived the ProCCM arm to have less malaria compared to the passive arm. Six provincial, district, and health facility staff and five CHWs felt that ProCCM was onerous for CHWs, necessitating compensation. Four health facility staff reported supervising ProCCM CHWs more frequently than before the trial, which two saw as an additional, albeit manageable, time commitment. District and health facility staff noted an increase in commodities consumption due to ProCCM. Other challenges included long distances covered by CHWs during visits and the impact of the farming cycle on both households’ and CHWs’ availability for visits. The findings suggest that ProCCM is both feasible to implement and acceptable to communities but requires additional time and travel for CHWs.
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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 | 0.022 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".