The effect of cognitive decline on the medication adherence in patients with type II diabetes mellitus
Bibliographic record
Abstract
Background: Type II Diabetes Mellitus (T2DM) is a risk factor for decreased cognitive function that is rarely recognised by patients, apart from age and other factors. Objective: This study aims to assess the effect of decreased cognitive function on medication adherence in T2DM patients. Method: This study used a cross-sectional design conducted at the Pasar Minggu Community Health Center, Jakarta, Indonesia. Cognitive function was assessed using the validated Indonesian version of the Montreal Cognitive Assessment (MoCA-Ina) questionnaire. Results: One hundred twenty-seven T2DM patients (75.6% female) with a mean age of 58.69 years were recruited. The proportion of T2DM patients with decreased cognitive function was quite high, namely 61%. The proportion of non-adherent patients in the group with decreased cognitive function (70.6%) was greater than in the normal group (29.4%). Decreased cognitive function significantly affected non-adherence in taking medication with aOR 3.744 (95% CI 1.485–9.442), p = 0.005, after controlling for age, education level, HbA1c value, and comorbid dyslipidemia. Conclusion: Patients with decreased cognitive function are 3.7 times more likely to be non-compliant with medication, regardless of age, education level, HbA1c value, and dyslipidemia. Special management is needed for T2DM patients with decreased cognitive function, such as caregiver assistance, education by pharmacists, and simpler drug regimes.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".