Adapting an Evidence-Based, Early Childhood Parenting Programme for Integration into Government Primary Health Care Services in Rural Bangladesh
Bibliographic record
Abstract
This paper describes the process of adapting an early childhood development programme, with proven effectiveness in Bangladesh, for integration into government health services in rural Bangladesh. Through a three-stage process, we adapted an evidence-based, home-visiting, programme (Reach-Up and Learn) for delivery in government health clinics by government health staff as part of their regular duties. Stage one involved preparing an initial draft of two parenting interventions for use with: (1) pairs of mother/child dyads, and (2) small groups of mother/child dyads. In stage two, we piloted the adapted interventions in nine clinics with a total of twenty-seven health staff and 357 mother/child dyads. We used data from mothers' attendance, feedback from participating mothers and health staff and observations of parenting sessions by the research team to revise the interventions. Stage three involved piloting the revised interventions in six clinics with eighteen health staff and 162 mother/child dyads. We gathered additional data on mothers' attendance and used observations by the research team to finalize the interventions. Through this three-stage process, adaptations were made to the intervention content, process of delivery, materials, and engagement strategies used. The largest challenges were related to incorporating the parenting programme into health staff's existing workload and promoting mothers' engagement in the programme. We also simplified the content and structure of the curriculum to make it easier for health staff to deliver and to ensure mothers understood the activities introduced. This iterative piloting was used prior to implementing and evaluating the interventions through an effectiveness trial.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".