Patient education program for Brazilians living with diabetes and prediabetes: findings from a development study
Bibliographic record
Abstract
BACKGROUND: Globally, the incidence of diabetes is increasing and strategies to reach a comprehensive approach of care are needed, including education in self-management. This is particularly true in low and middle-income countries where the number of people living with diabetes is higher than in the high-income ones. This article describes the development of a structured patient education program for Brazilians living with diabetes or prediabetes. METHODS: These steps were undertaken: 1) a 4-phase needs assessment (literature search of local diabetes guidelines, environmental scan, evaluation of information needs of patients identified by diabetes experts, and patient focus groups); and, 2) the translation and cultural adaptation of the patient guide (preparation, translation, back-translation, back-translation review, harmonization, and proofreading). RESULTS: Four of the seven guidelines identified include educational aspects of diabetes management. No structured education program was reported from the environmental scan. Regarding the information needs, 15 diabetes experts identified their patients' needs, who referred that they have high information needs for topics related to their health condition. Finally, results from six patient focus groups were clustered into six themes (self-management, physical activity, eating habits, diabetes medication, psychosocial being, and sleep), all embedded into the new education program. Constructive theory, adult learning principles, and the Health Action Process Approach model were used in program development and will be used in delivery. The developed program consists of 18 educational sessions strategically mapped and sequenced to support the program learning outcomes and a patient guide with 17 chapters organized into five sections, matched with weekly lectures. CONCLUSIONS: This program is a sequential and theoretical strategic intervention that can reach programs in Brazil to support diabetes and prediabetes patient education.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".