The Community-Based Child Health Integrated Program in Iran: A Mixed-Methods Process Evaluation
Bibliographic record
Abstract
Objectives: The community-based Child Health Integrated Program (CHIP) was established to improve children’s health status in Iran. The current study was performed to understand how this program was implemented and experienced by the care providers and target group. Methods: A total number of 249 mothers who had children under 5 years (clients) and 70 caregivers (providers) were selected from 42 health care centers of Tabriz city to participate in the study. Quantitative and qualitative data were collected using two separated semi-structured interviews as well as self-developed questionnaires. The mixed-method process evaluation study was examined and reported the exposure and satisfaction status of the clients, and reach, delivery, fidelity rates, and contextual factors toward the CHIP. Results: Overall, low reach (11.2%), moderate-exposure (62.6%), and high satisfaction (80.1%) rates of the clients were reported to the program. The fidelity rate of the program tools was 42.9%, considered as an inadequate rate. Anthropometric measurement and vaccination of the children, as well as face-to-face training sessions for the mothers, were well delivered. However, some parts of the program including follow-up and group training sessions were delivered poorly. Conclusions: This process evaluation study demonstrated that the CHIP is a promising intervention for improving children's health care. However, the barriers identified in this study warrant consideration in subsequent health care needs among children. Further research is required to identify ways to improve the implementation and delivery of this intervention. Practice Implications: There is a dire need to enter some audit and feedback strategies in the form of monthly tracking of process indicators to extent of implementation of intervention components.
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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 | 0.035 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".