Community-Based Intelligent Blood Glucose Management for Older Adults With Type 2 Diabetes Based on the Health Belief Model: Randomized Controlled Trial
Bibliographic record
Abstract
Background: The number of older patients with type 2 diabetes (T2D) is increasing, and effective self-management is crucial for controlling disease progression and its complications. Objective: We designed a home telemedicine intervention that combines telemedicine with health education based on the Health Belief Model (HBM). This study evaluated its effectiveness on self-management in older patients with T2D. Methods: Between March and April 2022, we recruited 198 community-dwelling patients with T2D aged 65 years and older. Patients were randomly assigned to either a control group, which received a conventional diabetes management program, or an intervention group, which received a home telemedicine intervention with a health education program based on the HBM. The intervention lasted 6 months. The primary outcome measured was glycosylated hemoglobin (HbA1c); secondary outcomes included diabetes self-management capacity, self-efficacy, and health beliefs. We collected outcome metrics at baseline, 3 months, and 6 months. Generalized estimating equations were used to compare changes in outcomes. Results: A total of 96.5% (191/198) of patients completed the study. From baseline to 6 months, HbA1c decreased by mean -0.99% (95% CI -1.60% to -0.60%) in the intervention group and mean -0.42% (95% CI -0.90% to 0.90%) in the control group. The intervention group experienced a significantly greater reduction of 0.42% compared to the control group (95% CI 0.12%-0.73%). Furthermore, compared to the control group, the intervention group showed significant improvements in diabetes self-management skills (mean 5.88, 95% CI 4.98-6.79), self-efficacy (mean 9.40, 95% CI 8.15-10.66), and health beliefs (mean 19.54, 95% CI 17.71-21.36) at both 3 and 6 months. Conclusions: Home telemedicine interventions incorporating health education based on the HBM can provide significant benefits for community-dwelling older patients with T2D, potentially offering new avenues for chronic disease prevention and management. However, future large-scale studies are required to further assess their effectiveness and feasibility.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".