Implementation Research for the Evaluation of the Child Health Education and Surveillance Tool Application
Bibliographic record
Abstract
Abstract Community health agent programs and modern information and communication technology can greatly improve knowledge of healthy childrearing practices by caregivers in low resource settings, if implemented effectively. Improved knowledge by caregivers can lead to better sanitation, diet, and child development practices. A digital health tool (CHEST App) was developed and deployed in a community health agent program in the Amazon of Peru to improve community health agent performance and ultimately improve early childhood development in the communities. This study presents the results of and evaluation of the implementation and clinical outcomes of the program. METHODS The CHEST App intervention was evaluated using a Hybrid Type II evaluation study design. The effectiveness of the intervention was determined by conducted a paired t-test analysis to compare the mean differences in knowledge scores, hemoglobin levels, early childhood development (ECD) scores, and incidence of diarrhea. The evaluation of the implementation outcomes was conducted with a mixed method approach to identify the extent to which the intervention was successfully installed into the local CHA program. The results of the study are presented within the framework of the Implementation Research Logic Model. RESULTS The CHEST App intervention is associated with improvements in knowledge scores, hemoglobin levels, ECD scores, and decreased diarrhea. However, the evaluation could not isolate the effect of the intervention due to reduction in sample size from COVID-19 closures. The implementation of the CHEST App intervention was effective with high degrees of acceptability, adoption, and fidelity. Adoption and fidelity of the surveillance function of the CHEST App by program coordinators was not achieved. CONCLUSION The CHEST App intervention is a promising tool to improve the performance of CHAs during their home visits, to accomplish their objective of teaching caregivers healthy childrearing practices and improving child health and development in their communities. Trial Registration Trial registered on 11/29/2018 at ISRCTN43591826.
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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 | 0.157 | 0.119 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".