Interventions to increase immunisation coverage among children 12–23 months of age in India through participatory learning and community engagement: pilot study for a cluster randomised trial
Bibliographic record
Abstract
OBJECTIVE: With the aim of conducting a future cluster randomised trial to assess intervention impact on child vaccination coverage, we designed a pilot study to assess feasibility and aid in refining methods for the larger study. TRIAL DESIGN: Cluster-randomised design with a 1:1 allocation ratio. METHODS: Clusters were 12 villages in rural Uttar Pradesh. All women residing in a selected village who were mothers of a child 0-23 months of age were eligible; participants were chosen at random. Over 4 months, intervention group (IG) villages received: (1) home visits by volunteers; (2) community mobilisation events to promote immunisation. Control group (CG) villages received community mobilisation to promote nutrition. A toll-free number for immunisation was offered to all IG and CG village residents. Primary outcomes were ex-ante criteria for feasibility of the main study related to processes for recruitment and randomisation (50% of villages would agree to participate and accept randomisation; 30 women could be recruited in 70% of villages), and retention of participants (50% of women retained from baseline to endline). Clusters were assigned to IG or CG using a computer-generated randomisation schedule. Neither participants nor those delivering interventions were blinded, but those assessing outcomes were blinded to group assignment. RESULTS: All villages contacted agreed to participate and accepted randomisation. 36 women were recruited per village; 432 participants were randomised (IG n=216; CG n=216). No clusters were lost to follow-up. The main analysis included 86% (373/432) of participants, 90% (195/216) from the IG and 82% (178/216) from the CG. CONCLUSIONS: Criteria related to feasibility were satisfied, giving us confidence that we can successfully conduct a larger cluster randomised trial. Methodological lessons will inform design of the main study. TRIAL REGISTRATION NUMBER: ISRCTN16703097.
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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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".