<p>Relationship Between Self-Care Behavior and Cognitive Function in Hospitalized Adult Patients with Type 2 Diabetes: A Cross-Sectional Study</p>
Bibliographic record
Abstract
Purpose: To investigate the relationship between diabetes self-care behavior and cognitive function of hospitalized young and middle-aged Chinese patients with type 2 diabetes mellitus (T2DM). Patients and Methods: In this cross-sectional study, young and middle-aged T2DM patients (age range, 35– 65 years) were recruited at 4 tertiary hospitals between July 2016 and January 2017. Data pertaining to self-care behavior and cognitive function were collected using two questionnaires (the Summary of Diabetes Self-care Activities [SDSCA] and the Montreal Cognitive Assessment [MoCA], respectively). Multivariate linear regression analysis was performed to assess the correlation between cognitive function and self-care activities. Results: A total of 140 patients with diabetes were enrolled (mean age, 53.79± 7.96 years). The mean duration of T2DM was 10.83± 6.76 years. Regarding SDSCA performance, the mean scores for foot care and blood glucose monitoring were 2.20± 2.57 and 1.98± 2.45, respectively, which were the worst; scores for exercise (4.01± 2.58) and diet (3.16± 1.89) were better, while scores for medication administration (5.26± 2.79) were the best. The prevalence of cognitive impairment was 37.9% (53 patients). After variables adjustment, delayed recall showed a significant correlation with blood sugar monitoring behavior ( B =0.224, P=0.019); visual space and executive function ( B =0.255, P =0.009) and abstraction ( B =− 0.337, P =0.001) showed a correlation with foot care behavior. Conclusion: Cognitive ability affects the self-care behavior of patients with T2DM. Assessment of cognitive function may help inform patient education interventions to improve the self-care behavior of these patients. Keywords: young and middle-aged, cognitive impairment, self-care behaviors, type 2 diabetes mellitus
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".