Leveraging Community Health Workers and a Responsive Digital Health System to Improve Vaccination Coverage and Timeliness in Resource-Limited Settings: Protocol for a Cluster Randomized Type 1 Effectiveness-Implementation Hybrid Study
Bibliographic record
Abstract
BACKGROUND: Tanzania is 1 of 20 countries where the majority of unvaccinated and undervaccinated children reside. Prior research identified substantial rural-urban disparities in the coverage and timeliness of childhood vaccinations in Tanzania, with children in rural settings being more likely to receive delayed or no vaccinations. Further research is necessary to identify effective and scalable interventions that can bridge rural-urban gaps in childhood vaccination while accounting for multifaceted barriers to vaccination. OBJECTIVE: This protocol describes a type 1 effectiveness-implementation hybrid study to evaluate Chanjo Kwa Wakati (timely vaccination in Kiswahili), a community-based digital health intervention to improve vaccination timeliness. The intervention combines human resources (community health workers), low-cost digital strategies (electronic communication, digital case management, and task automation), a vaccination knowledge intervention, and insights from behavioral economics (reminders and incentives) to promote timely childhood vaccinations. METHODS: The study will be conducted in 2 predominantly rural regions in Tanzania with large numbers of unvaccinated or undervaccinated children: Shinyanga and Mwanza. Forty rural health facilities and their catchment areas (clusters) will be randomized to an early or delayed onset study arm. From each cluster, 3 cohorts of mother-child dyads (1 retrospective cohort and 2 prospective cohorts) will be enrolled in the study. The timeliness and coverage of all vaccinations recommended during the first year of life will be observed for 1200 children (n=600, 50% intervention group children and n=600, 50% nonintervention group children). The primary effectiveness outcome will be the timeliness of the third dose of the pentavalent vaccine (Penta3). Quantitative surveys, vaccination records, study logs, fidelity checklists, and qualitative interviews with mothers and key informants will inform the 5 constructs of the reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) framework. The results will be used to develop an implementation blueprint to guide future adaptations and scale-up of Chanjo Kwa Wakati. RESULTS: The study was funded in August 2022. Data collection is expected to last from February 2024 to July 2027. CONCLUSIONS: This study will address the lack of rigorous evidence on the effectiveness of community-based digital health interventions for promoting vaccination coverage and timeliness among children from sub-Saharan Africa and identify potential implementation strategies to facilitate the deployment of vaccination promotion interventions in low- and middle-income countries. TRIAL REGISTRATION: ClinicalTrials.gov NCT06024317; https://www.clinicaltrials.gov/study/NCT06024317. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/52523.
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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 | 0.037 | 0.031 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.081 | 0.014 |
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".