The prospective association between positive psychological well-being and diabetes.
Bibliographic record
Abstract
OBJECTIVE: Positive psychological well-being has protective associations with cardiovascular outcomes, but no studies have considered its association with diabetes. This study investigated links between well-being and incident diabetes. METHODS: At study baseline (1991-1994), 7,800 middle-aged British men and women without diabetes indicated their life satisfaction, emotional vitality, and optimism. Diabetes status was determined by self-reported physician diagnosis and oral glucose tolerance test (screen detection) at baseline and through 2002-2004. Incident diabetes was defined by physician-diagnosed and screen-detected cases combined and separately. Logistic regression estimated the odds of developing diabetes controlling for relevant covariates (e.g., demographics, depressive symptoms). Models were also stratified by gender and weight status. RESULTS: There were 562 combined cases of incident diabetes during follow-up (up to 13 years). Well-being was not associated with incident diabetes for combined physician-diagnosed and screen-detected cases. However, when examining the 288 physician-diagnosed cases, life satisfaction and emotional vitality were associated with up to a 15% decrease in the odds of physician-diagnosed diabetes, controlling for demographics (results were similar with other covariates). Optimism was not associated with physician-diagnosed diabetes, and no well-being indicator was associated with screen-detected diabetes. Gender and weight status were not moderators. CONCLUSIONS: Life satisfaction and emotional vitality, but not optimism, were associated with reduced risk of physician-diagnosed diabetes. These findings suggest that well-being may contribute to reducing risk of a prevalent and burdensome condition, although intervention studies are needed to confirm this. It is unclear why findings differed for physician-diagnosed versus study-screened diabetes. (PsycINFO Database Record
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".