“Help me to take care”: Professional expectations about using an application in heart failure
Bibliographic record
Abstract
Objective: To understand the expectations of the professionals about the construction and use of an educational and follow-up application to care.Methods: Phenomenological and qualitative study. Convenience and purposive sampling were carried out and in-depth individual interviews with 35 professionals from the multidisciplinary team, between September and October 2020 in Brazil. All interviews were audio-recorded and data analyzed using the hermeneutic circle. The COREQ checklist was employed to report on the current study.Results: Two main units of meaning emerged: (a) The care of the person who lives with heart failure; and (b) The care of the person with heart failure intermediated by an application. Care for the person with the disease brings together elements related to the identification of demands and understanding of their surroundings, with guidance and use of technologies.Conclusions: The professionals were favorable to the development of an application and considered it beneficial. The use of it, would allow the approximation between patients and their family and the multidisciplinary team; respect the patient’s needs and overcome the precariousness of the health system.
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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 | 0.012 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".