Process evaluation for the delivery of a water, sanitation and hygiene mobile health program: findings from the randomised controlled trial of the CHoBI7 mobile health program
Bibliographic record
Abstract
OBJECTIVE: The Cholera-Hospital-Based Intervention for 7-days (CHoBI7) mobile health (mHealth) program delivers mobile messages to diarrhoea patient households promoting water treatment and handwashing with soap. The randomised controlled trial (RCT) of the CHoBI7 mHealth program demonstrated this intervention was effective in significantly reducing diarrhoea and stunting amoung young children. The objective of this study was to assess the implementation of the CHoBI7 mHealth program in delivering mHealth messages during this RCT. METHODS: 517 diarrhoea patient households with 1777 participants received weekly text, voice and interactive voice response (IVR) messages from the CHoBI7 mHealth program over the 12-month program period. The program process evaluation indicators were the following: the percentage of CHoBI7 mHealth messages received and fully listened to by program households (program fidelity and dose), and household members reporting receiving and sharing an mHealth message from the program in the past two weeks (program reach). RESULTS: Ninety two percent of text messages were received by program households. Eighty three percent of voice and 86% of IVR messages sent were fully listened to by at least one household member. Eighty one percent of IVR quiz responses from households were answered correctly. Program households reported receiving a CHoBI7 mHealth message in the past two weeks at 79% of monthly household visits during the 12-month program. Seventy seven percent of participants reported sharing a program message with a spouse, 55% with a neighbour and 49% with a child during the program period. CONCLUSION: There was high fidelity, dose and reach of mobile messages delivered for the CHoBI7 mHealth program. This study presents an approach for process evaluation that can be implemented to evaluate future mHealth programs.
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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 | 0.036 | 0.082 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".