A Mobile App for Promoting Breastfeeding-Friendly Communities in Hong Kong: Design and Development Study
Bibliographic record
Abstract
Background: Breastfeeding is vital for the health and well-being of both mothers and infants, and it is crucial to create supportive environments that promote and maintain breastfeeding practices. Objective: The objective of this paper was to describe the development of a breastfeeding-friendly app called "bfGPS" (HKU TALIC), which provides comprehensive territory-wide information on breastfeeding facilities in Hong Kong, with the goal of fostering a breastfeeding-friendly community. Methods: The development of bfGPS can be categorized into three phases, which are (1) planning, prototype development, and preimplementation evaluation; (2) implementation and updates; and (3) usability evaluation. In phase 1, a meeting was held with experts, including maternal and child health researchers, app developers, breastfeeding individuals, and health professionals, to discuss the focus and functionality of the breastfeeding app. A prototype was developed, and breastfeeding facilities in various public venues in Hong Kong were assessed using a structured checklist. For the preimplementation evaluation, 10 focus groups and 19 one-on-one interviews were conducted between May 2019 and October 2020 with staff working in public premises (n=29) and breastfeeding individuals (n=29). For phase 2, bfGPS was published on iOS (Apple Inc) and Android (Google) platforms in September 2020. App updates were launched in September 2021 and May 2022 based on the suggestions provided by the participants in the preimplementation evaluation. For the usability evaluation, semistructured, in-depth, one-to-one interviews were conducted with breastfeeding individuals (n=30) to understand their experiences of using bfGPS. Content analysis was used to analyze the data. Results: bfGPS is a mobile app that was developed to assist breastfeeding individuals in locating breastfeeding facilities in public venues in Hong Kong. In the preimplementation evaluation, the participants gave comments on the layout and interface of bfGPS, and suggestions were given on incorporating new functions into the app. Based on the suggestions of the participants in the preimplementation evaluation, a few additional functions were added into bfGPS, including allowing the users to rate and upload recent information about breastfeeding facilities and an infant tracker function that encourages users to record infant development. In the usability evaluation, 3 main themes emerged-bfGPS improves the community experience for breastfeeding individuals, facilitates tracking the infant's growth, and provides suggestions for further development. Conclusions: The bfGPS app is the first user-friendly tool designed to assist users in locating breastfeeding facilities within the community. It stands as a guide for similar health care app developments, emphasizing the importance of accurate, current data to ensure user adoption and long-term use. The app's potential lies in the support and reinforcement of breastfeeding practices coupled with self-management strategies.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".