Patient empowerment through mobile health: Case study with a Brazilian application for pregnancy support
Bibliographic record
Abstract
Abstract This paper analyzes how mobile health applications contribute to the empowerment of health service users. The theoretical foundation includes m‐health, user empowerment, and value co‐creation. Quantitative and qualitative methods were used to investigate the Kangaroo application (Canguru, in Portuguese), which targets Brazilian pregnant women and seeks to make women empowered for a healthy pregnancy. The free app is a healthcare social network designed by a health‐tech startup and a reference Brazilian hospital. It has already supported 350,000 pregnant women, and more than 200 health professionals. The data collection effort comprised application log analysis of 6 months of records of 99,709 users, mobile‐based survey with 429 women and 16 interviews. The results showed that the functionalities of the personal and social dimensions mapped in the application explain 85.5% of the user empowerment. The app social features impacted 2.4 more than the personal functionalities. The quantitative analysis concluded that there was no moderating effect of styles of value co‐creation practices on the relationship between empowerment and its dimensions. The theoretical contribution is associated with the discussion of the influence of personal and social dimensions of m‐health to the user empowerment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".