Community Mobilization and Community Incentivization (CoMIC) Strategy for Child Health in a Rural Setting of Pakistan: Study Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
Despite the decline in under-five mortality by over 60% in the last three decades, majority of child mortality is still attributable to communicable and infectious diseases that are not only preventable, but they are also treatable. We evaluated the potential impact of a participatory community engagement and innovative community incentivization (C3I) strategy for improving the coverage of child health interventions in a rural setting in Pakistan. We first undertook formative research to assess community knowledge and the likelihood of collective community strategy and conditional incentives for improving existing preventive and care-seeking practices for childhood diarrhea and pneumonia. We developed options for community incentivization and improving group practices, taking local norms and customs into account in the design of the community mobilization strategies and messages. These interventions were then formally evaluated prospectively in a three-arm cluster randomized controlled trial. Clusters were randomly assigned by a computer algorithm using restricted randomization by an external statistician (1:1:1) into three groups: community mobilization and incentivization (CMI); community mobilization only using an enhanced communication package (CM); and control group. The C3I was an innovative strategy as it involved serial incremental targets of collective improvement in community behavior related to improvement in the coverage of a composite indicator of fully immunized children (FIC), oral rehydration salt (ORS), and the sanitation index (SI). The evaluation was done by an independent data collection and analysis team at baseline and end line (after 24 months).
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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 | 0.024 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".