Associations between coping strategies and mental health in individuals with type 2 diabetes: Prospective analyses.
Bibliographic record
Abstract
OBJECTIVE: Individuals with type 2 diabetes are at greater risk of developing a number of mental health conditions, including depression, anxiety, and diabetes-related distress, than individuals without type 2 diabetes. Cross-sectional studies suggest that some coping strategies may increase the risk of mental health conditions in individuals with diabetes, whereas others may be protective. This study extends the cross-sectional evidence base with a prospective study. METHODS: Data were collected annually for 2 years from a community sample of 1,742 adults with type 2 diabetes. Coping strategies were measured at baseline and mental health conditions were assessed at each time point with self-report symptom measures. For comparison, cross-sectional and prospective analyses were conducted. RESULTS: Cross-sectional analyses demonstrated that task-oriented coping was negatively associated with the likelihood of each of the mental health conditions, emotion-oriented coping was positively associated with the likelihood of each condition, and avoidance-oriented coping showed no association. Prospective analyses revealed that among individuals who did not have elevated depressive symptoms at baseline, only emotion-oriented coping predicted the likelihood of developing major depression syndrome during follow-up. Similar patterns of results were observed for elevated anxiety symptoms and diabetes-related distress. CONCLUSIONS: Cross-sectional results differed from prospective results. Only emotion-oriented coping appears to play a role in the development of depressive symptoms, anxiety symptoms, and diabetes-related distress. Results underscore the importance of examining prospective associations and suggest that interventions targeting specific coping strategies might alleviate mental health problems in individuals with type 2 diabetes.
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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 | 0.001 | 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".