Assessing Determinants of Programmatic Performance of Community Management of Malaria, Pneumonia, and Diarrhea in Children in Africa: Protocol and Data Collection for a Mixed Methods Evaluation of Integrated Community Case Management
Bibliographic record
Abstract
BACKGROUND: Integrated community case management (iCCM) is a child health program designed to provide integrated community-based care for children with pneumonia, malaria, or diarrhea in hard-to-reach areas of low- and middle-income countries. The foundation of the intervention is service delivery by community health workers (CHWs) who depend on reliable provision of drugs and supplies, consistent supervision, comprehensive training, and community acceptance and participation to perform optimally. The effectiveness of the program may also depend on a number of other elements, including an enabling policy environment, financing mechanisms from the national to the local level, data transmission systems, and appropriate monitoring and evaluation. The extent to which these factors act upon each other to influence the effectiveness and viability of iCCM is both variable and challenging to assess, especially across different implementation contexts. OBJECTIVE: In this paper, we describe a mixed methods systems-based study protocol to assess the programmatic components of iCCM that are associated with intervention effectiveness and report preliminary results of data collection. METHODS: This protocol uses a mixed qualitative and quantitative study design based on a systems thinking approach within four iCCM programs in Malawi, Democratic Republic of the Congo, and Niger State and Abia State in Nigeria. Routine monitoring data are collected to determine intervention effectiveness, namely testing, treatment, and referral outcomes. Surveys with CHWs, supervisors, and caregivers are performed to collect quantitative data on their demographics, activities, and experiences within the program and how these relate to the areas of intervention effectiveness. Focus group discussions are conducted with these stakeholders as well as local traditional leaders to contextualize these data. Key informant interviews are undertaken with national- and district-level program stakeholders and officers knowledgeable in critical program processes. RESULTS: We performed 3836 surveys and 45 focus group discussions of 379 participants with CHWs, supervisors, caregivers, and traditional leaders, as well as 120 key informant interviews with district- and national-level program managers, health officers, and ministry officials. Policy and program documents were additionally collected for review. CONCLUSIONS: We expect that evidence from this study will inform child health programs and practice in low- and middle-income settings as well as future policy development within the iCCM intervention. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/33076.
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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 | 0.155 | 0.089 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".