Emerging adulthood and Type 1 diabetes: insights from the DAWN2 Study
Bibliographic record
Abstract
AIMS: To compare clinical, psychological, education and social variables in emerging adults (aged 18-30 years) with Type 1 diabetes with their adult counterparts aged >30 years. METHODS: A single assessment multinational sample was surveyed as part of the larger second Diabetes Attitudes, Wishes and Needs (DAWN2) study. Participants completed a series of surveys incorporating demographic as well as clinical questions (comorbidities, hypoglycaemia) and validated self-report scales concerning psychosocial (health impact, quality of life, beliefs and attitudes, self-management behaviours, healthcare experience and family support) and diabetes education factors. RESULTS: Emerging adults differed from adults aged >30 years with regard to a number of psychosocial variables. Emerging adults reported better overall quality of life, social support and support from their healthcare team compared with adults aged >30 years of age; however, emerging adults experienced greater diabetes-specific distress and were less engaged in self-management. Diabetes education was related to a number of indicators, while experience of discrimination was harmful, but these impacts did not differ between emerging adults and adults aged >30 years. An analysis of geographical regions suggested that emerging adults in North America and Europe had better well-being than older adults, while the opposite was observed in Asia. CONCLUSIONS: Emerging adults, particularly those in the later phase (ages 25-30 years) are especially at risk in terms of diabetes-specific distress. There is a need for novel interventions to meet the needs of these vulnerable emerging adults more effectively.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".