Diabetes distress mediates the relationship between depressive symptoms and glycaemic control among adults with type 2 diabetes: Findings from a multi‐site diabetes peer support intervention
Bibliographic record
Abstract
Abstract Aims Diabetes distress is positively associated with HbA 1c and may mediate the relationship between depressive symptoms and HbA 1c . This study examined these relationships in a geographically, socioeconomically, and ethnically diverse sample of adults with type 2 diabetes. Methods Using data from five US sites evaluating peer support for diabetes management ( n = 917), Structural Equation Modeling (SEM) examined whether diabetes distress (four items from Diabetes Distress Scale) mediated the relationship between depressive symptoms (PHQ‐8) and HbA 1c . Sites compared interventions of varying content and duration with control conditions. Time from Baseline Assessment to Final Assessment varied from six to 18 months. Site characteristics were controlled by entering site as a covariate along with age, sex, education, diabetes duration, insulin use, and intervention/control assignment. Results Depressive symptoms, diabetes distress, and HbA 1c were all intercorrelated cross‐sectionally and from Baseline to Final Assessment (rs from 0.10 to 0.57; p s <0.05). In SEM analyses, diabetes distress at Final Assessment mediated the relationship between Baseline depressive symptoms and HbA 1c at Final Assessment (indirect effect: b = 0.031, p < 0.001), controlling for Baseline HbA 1c and covariates. Parallel analysis of whether depressive symptoms mediated the relationship between Baseline diabetes distress and HbA 1c at Final Assessment was not significant. Conclusions In this diverse sample, diabetes distress mediated the influence of depressive symptoms on HbA 1c but the reverse, depressive symptoms mediating the effect of distress, was not found. These findings add to the evidence that diabetes distress is a worthy intervention target to improve clinical status and quality of life among 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".