Diabetes Attitudes, Wishes and Needs second study (DAWN2™): Cross‐national benchmarking of diabetes‐related psychosocial outcomes for people with diabetes
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Bibliographic record
Abstract
AIMS: The second Diabetes Attitudes, Wishes and Needs (DAWN2) study aimed to assess psychosocial outcomes in people with diabetes across countries for benchmarking. METHODS: Surveys included new and adapted questions from validated questionnaires that assess health-related quality of life, self-management, attitudes/beliefs, social support and priorities for improving diabetes care. Questionnaires were conducted online, by telephone or in person. RESULTS: Participants were 8596 adults with diabetes across 17 countries. There were significant between-country differences for all benchmarking indicators; no one country's outcomes were consistently better or worse than others. The proportion with likely depression [WHO-5 Well-Being Index (WHO-5) score ≤ 28] was 13.8% (country range 6.5-24.1%). Diabetes-related distress [Problem Areas in Diabetes Scale 5 (PAID-5) score ≥ 40] was reported by 44.6% of participants (17.2-67.6%). Overall quality of life was rated 'poor' or 'very poor' by 12.2% of participants (7.6-26.1%). Diabetes had a negative impact on all aspects investigated, ranging from 20.5% on relationship with family/friends to 62.2% on physical health. Approximately 40% of participants (18.6-64.9%) reported that their medication interfered with their ability to live a normal life. The availability of person-centred chronic illness care and support for active involvement was rated as low. Following self-care advice for medication and diet was most common, and least common for glucose monitoring and foot examination, with marked country variation. Only 48.8% of respondents had participated in diabetes educational programmes/activities to help manage their diabetes. CONCLUSIONS: Cross-national benchmarking using psychometrically validated indicators can help identify areas for improvement and best practices to drive changes that improve outcomes for people with diabetes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it