626-P: Diab@ease—A Pilot Study on Holistic Mental Health Integration for Diabetes, Cognitive Function, and Physical Frailty
Bibliographic record
Abstract
Introduction and Objective: Diabetes is a chronic condition closely linked to cognitive decline, physical frailty, and mental health issues. This pilot study evaluated the feasibility and preliminary outcomes of a multidisciplinary, patient-centered intervention, providing insights for scaling to a larger study. Methods: Enrolled 53 subjects with type 2 diabetes, aged ≥ 60 years, with duration > 5 years. Each subject was provided with personalized dietary interventions focused on low-glycemic, nutrient-dense foods, tailored physical activity programs and mindfulness-based stress reduction techniques. Baseline assessments included Mini-Mental State Examination [MMSE], Montreal Cognitive Assessment [MoCA]), frailty evaluation (Fried Frailty Index), mental health assessments (PHQ-9, GAD-7) and HbA1c and repeated after 6 months. Feasibility metrics included retention, adherence, and implementation challenges. Results: Of the 53 enrolled, 39 participants (74%) completed the study. Attrition included 9 losses (17%) due to age-related complications and 5 withdrawals (9%) due to mobility constraints, underscoring the need for adaptive strategies in geriatric populations. Cognitive scores improved significantly (MMSE: +2.5, 95% CI: 1.1-3.9; MoCA: +3.1, 95% CI: 2.0-4.2), Frailty scores showed marked reductions (Fried Frailty Index: -1.2, 95% CI: -1.7 to -0.7), Depression (PHQ-9: -4.3, 95% CI: -5.6 to -3.0) and anxiety (GAD-7: -3.7, 95% CI: -4.9 to -2.5) symptoms improved significantly, Glycemic control also improved (HbA1c: -0.7%, 95% CI: -1.1% to -0.3%). Conclusion: This pilot study demonstrated the feasibility of integrating cognitive, physical, and mental health interventions into diabetes care, yielding promising preliminary outcomes. The Diab@ease pilot study underscores the importance of a multidisciplinary approach in diabetes care. Disclosure S. Shaji: None. C. Radhakrishnan: None. S.S. K p: None.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".