Socioeconomic status and glycemic control in adult patients with type 2 diabetes: a mediation analysis
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study is to examine the contribution of health behaviors (self-management and coping), quality of care, and individual characteristics (depressive symptoms, self-efficacy, illness representations) as mediators in the relationship between socioeconomic status (SES) and glycemic control. METHODS: A sample of 295 adult patients with type 2 diabetes was recruited at the end of a diabetes education course. Glycemic control was evaluated through glycosylated hemoglobin (HbA1c). Living in poverty and education level were used as indicators of SES. RESULTS: Bootstrapping analysis showed that the significant effects of poverty and education level on HbA1c were mediated by avoidance coping and depressive symptoms. The representation that diabetes is unpredictable significantly mediated the relationship between living in poverty and HbA1c, while healthy diet mediated the relationship between education level and HbA1c. CONCLUSIONS: To improve glycemic control among patients with low SES, professionals should regularly screen for depression, offering treatment when needed, and pay attention to patients' illness representations and coping strategies for handling stress related to their chronic disease. They should also support patients in improving their self-management skills for a healthy diet.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".