Personal Accounts of the Negative and Adaptive Psychosocial Experiences of People With Diabetes in the Second Diabetes Attitudes, Wishes and Needs (DAWN2) Study
Bibliographic record
Abstract
OBJECTIVE: To identify the psychosocial experiences of diabetes, including negative accounts of diabetes and adaptive ways of coping from the perspective of the person with diabetes. RESEARCH DESIGN AND METHODS: Participants were 8,596 adults (1,368 with type 1 diabetes and 7,228 with type 2 diabetes) in the second Diabetes Attitudes, Wishes and Needs (DAWN2) study. Qualitative data were responses to open-ended survey questions about successes, challenges, and wishes for improvement in living with diabetes and about impactful experiences. Emergent coding developed with multinational collaborators identified thematic content about psychosocial aspects. The κ measure of interrater reliability was 0.72. RESULTS: Analysis identified two negative psychosocial themes: 1) anxiety/fear, worry about hypoglycemia and complications of diabetes, depression, and negative moods/hopelessness and 2) discrimination at work and public misunderstanding about diabetes. Two psychosocial themes demonstrated adaptive ways of coping with diabetes: 1) having a positive outlook and sense of resilience in the midst of having diabetes and 2) receiving psychosocial support through caring and compassionate family, friends, health care professionals, and other people with diabetes. CONCLUSIONS: The personal accounts give insight into the psychosocial experiences and coping strategies of people with diabetes and can inform efforts to meet those needs and capitalize on strengths.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".