An innovative Community Mobilisation and Community Incentivisation for child health in rural Pakistan (CoMIC): a cluster-randomised, controlled trial
Bibliographic record
Abstract
BACKGROUND: Infectious diseases remain the leading cause of death among children younger than 5 years due to disparities in access and acceptance of essential interventions. The Community Mobilisation and Community Incentivisation (CoMIC) trial was designed to evaluate a customised community mobilisation and incentivisation strategy for improving coverage of evidence-based interventions for child health in Pakistan. METHODS: CoMIC was a three-arm cluster-randomised, controlled trial in rural areas of Pakistan. Clusters were formed by grouping villages based on geographical proximity, ethnic consistency, and ensuring a population between 1500 to 3000 per cluster. Clusters were randomly assigned (1:1:1) to either community mobilisation, community mobilisation and incentivisation, or the control arm. Community mobilisation included formation of village committees which conducted awareness activities, while clusters in the community mobilisation and incentivisation group were provided with a novel conditional, collective, community-based incentive (C3I) in addition to community mobilisation. C3I was conditioned on serial incremental targets for collective improvement in coverage at cluster level of three key indicators (primary outcomes): proportion of fully immunised children, use of oral rehydration solution, and sanitation index, assessed at 6 months, 15 months, and 24 months, and village committees decided on non-cash incentives for people in the villages. Data were analysed as intention-to-treat by an independent team masked to study groups. The trial is registered at ClinicalTrials.gov, NCT03594279, and is completed. FINDINGS: Between Oct 1, 2018 and Oct 31, 2020, 21 638 children younger than 5 years from 24 846 households, with a total population of 139 005 in 48 clusters, were included in the study. 16 clusters comprising of 152 villages and 7361 children younger than 5 years were randomly assigned to the community mobilisation and incentivisation group; 16 clusters comprising of 166 villages and 7546 children younger than 5 years were randomly assigned to the community mobilisation group; and 16 clusters comprising of 139 villages and 6731 children younger than 5 years were randomly assigned to the control group. Endline analyses were conducted on 3812 children (1284 in the community mobilisation and incentivisation group, 1276 in the community mobilisation group, and 1252 in the control group). Multivariable analysis indicates improvements in all primary outcomes including a higher proportion of fully immunised children (risk ratio [RR] 1·3 [95% CI 1·0-1·5]), higher total sanitation index (mean difference 1·3 [95% CI 0·6-1·9]), and increased oral rehydration solution use (RR 1·5 [1·0-2·2]) in the community mobilisation and incentivisation group compared with the control group at 24 months. There was no evidence of difference between community mobilisation and control for any of the primary outcomes. INTERPRETATION: Community mobilisation and incentivisation led to enhanced acceptance evidenced by improved community behaviours and increased coverage of essential interventions for child health. These findings have the potential to inform policy and future implementation of programmes targeting behaviour change but would need evaluation for varying outcomes and different contexts. FUNDING: Bill & Melinda Gates Foundation. TRANSLATIONS: For the Sindhi and Urdu translations of the abstract see Supplementary Materials section.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".