Designing an eHealth Breastfeeding Resource With Young Mothers Using a Participatory Design
Bibliographic record
Abstract
INTRODUCTION: Breastfeeding rates among young mothers are low and do not meet recommendations from health authorities, putting the health of young mothers and their infants at risk. Young mothers require breastfeeding support that meets their learning needs and preferred mode for accessing information. The objective of this study was to work collaboratively with young mothers in order to cocreate an eHealth breastfeeding resource. METHODOLOGY: A three-phase exploratory study was conducted in Ontario, Canada. In Phases I and II, young mothers and health care providers (HCPs) were recruited and preferences for an eHealth breastfeeding resource were explored. In Phase III, feedback from young mothers and HCPs about the new resource was collected. RESULTS: Participants found the breastfeeding eHealth resource visually appealing, engaging, and informative. DISCUSSION: Cocreating a tailored breastfeeding eHealth resource with young mothers and HCPs using a participatory approach ensured that the resource design and content met the learning needs of young mothers.
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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 | 0.030 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".