Correlates of psychological care strategies for people with diabetes in the second Diabetes Attitudes, Wishes and Needs (<scp>DAWN</scp>2<sup>™</sup>) study
Bibliographic record
Abstract
AIMS: To assess the ways in which healthcare professionals address psychological problems of adults with diabetes in the second Diabetes Attitudes, Wishes and Needs (DAWN2(™) ) study. METHODS: Approximately 120 primary care physicians, 80 diabetes specialists and 80 nurses and dietitians providing diabetes care participated in each of 17 countries (N=4785). Multiple regression analyses were used to evaluate independent statistically significant associations of respondent attributes concerning psychological care strategies, including assessment of diabetes impact on the patient's life, assessment of depression, provision of psychological assessment and support, and coordination with mental health professionals. RESULTS: Psychological care strategies were positively associated with each other but differed by healthcare practice site and discipline; nurses and dietitians were less likely to assess depression than other healthcare professionals, while primary care physicians were less likely to coordinate with mental health specialists or ask patients how diabetes affects their lives. Psychological care was positively associated with healthcare professionals' beliefs that patients need help dealing with emotional issues and that clinical success depends on doing so, and also with level of psychological care training, multidisciplinary team membership and availability of resources for psychological care. There were significant between-country variations in psychological care strategies, before and after adjustment for individual-level factors, and significant country-by-covariate interactions for almost all individual-level factors investigated. CONCLUSIONS: Improvements in training and resources, recognition and assessment of psychological problems, and increased belief in the efficacy of psychological support may enhance healthcare professionals' efforts to address psychological problems in adults with diabetes.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".