Capitalizing on Community Groups to Improve Women’s Resilience to Maternal and Child Health Challenges: Protocol for a Human-Centered Design Study in Tanzania
Bibliographic record
Abstract
BACKGROUND: Maternal and neonatal deaths remain a major public health issue worldwide. Income Generation Associations (IGAs) could form a critical entry point to addressing poverty-related contributors. However, there have been limited practical interventions to leverage the power of IGAs in addressing the challenges associated with maternal care and childcare. OBJECTIVE: This study aims to co-design an intervention package with women in IGAs to improve their readiness and resilience to address maternal and child health (MCH) challenges using a human-centered design approach. METHODS: The study will use a qualitative descriptive design with purposefully selected women in IGAs and key MCH stakeholders in the Shinyanga and Arusha Regions of Tanzania. A 4-step adaptation of the human-centered design process will be used involving (1) mapping of IGAs and exploring their activities, level of women's engagement, and MCH challenges faced; (2) co-designing of the intervention package to address identified MCH challenges or needs considering the perceived acceptability, feasibility, and sustainability; (3) validation of the emerging intervention package through gathering insights of women in IGAs who did not take part in initial steps; and (4) refinement of the intervention package with MCH stakeholders based on the validation findings. RESULTS: The participants, procedures, and findings of each co-design step will be presented. More specifically, MCH challenges facing women in IGAs, a list of potential solutions proposed, and the emerging prototype will be presented. As of August 2024, we have completed the co-design of the intervention package and are preparing validation. The findings from the validation of the emerging prototype with a new group of women in IGAs and its refinement through multistakeholder engagement will be presented. A final co-designed intervention package with the potential to improve women's resilience and readiness to handle MCH challenges will be generated. CONCLUSIONS: The emerging intervention package will be discussed given relevant literature on the topic. We believe that subsequent testing and refinement of the package could form the basis for scaling up to broader settings and that the package could then be promoted as one of the key strategies in addressing MCH challenges facing women in low- and middle-income countries. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54323.
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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 | 0.062 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.046 | 0.008 |
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".