The expert patient's contribution to the empowerment of people with diabetes mellitus
Bibliographic record
Abstract
Objective: to uncover the contributions of specialist patients to the empowerment of people with diabetes mellitus. Methods: a qualitative study comprising three open virtual communities with public posts in Portuguese, aimed at discussing diabetes mellitus. The nuclei of meaning were identified through a word cloud, with mutual checking between three researchers using content analysis. Results: the interactions showed concern about the clinical dimension of the disease and the welcoming nature of suffering and anguish. It was also observed that living with diabetes provides knowledge about the disease, making these people propagators of knowledge and ensuring their participation in the treatment process. Furthermore, the dialogues provided by the online environment can contribute to health promotion, facilitating understanding of aspects inherent to diabetes. Conclusion: specialist patients are willing to answer questions based on the knowledge they have acquired through the experience of becoming ill, supporting their recommendations in the care and recommendations received during treatment. Contributions to practice: it is hoped that the results can contribute to the recognition and appreciation of new approaches to health promotion and self-care for people with diabetes, such as virtual communities.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".