Predictors of Medication Adherence in Inflammatory Bowel Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND AND AIMS: This study reports cross-sectional medication adherence data from year 1 of the Manitoba Inflammatory Bowel Disease (IBD) Cohort Study, a longitudinal, population-based study of multiple determinants of health outcomes in IBD in those diagnosed within 7 yr. METHODS: A total of 326 participants completed a validated multi-item self-report measure of adherence, which assesses a range of adherence behaviors. Demographic, clinical, and psycho-social characteristics were also assessed by survey. Adherence was initially considered as a continuous variable and then categorized as high or low adherence for logistic regression analysis to determine predictors of adherence behavior. RESULTS: Using the cutoff score of 20/25 on the Medication Adherence Report Scale, high adherence was reported by 73% of men and 63% of women. For men, predictors of low adherence included diagnosis (UC: OR 4.42, 95% CI 1.66-11.75) and employment status (employed: OR 11.27, 95% CI 2.05-62.08). For women, predictors of low adherence included younger age (under 30 versus over 50 OR 3.64, 95% CI 1.41-9.43; under 30 vs. 40-49 yr: OR 2.62, 95% CI 1.07-6.42). High scores on the Obstacles to Medication Use Scale strongly related to low adherence for both men (OR 4.05, 95% CI 1.40-11.70) and women (OR 3.89, 95% CI 1.90-7.99). 5-ASA use (oral or rectal) was not related to adherence. For women, immunosuppressant use versus no use was associated with high adherence (OR 4.49, 95% CI 1.58-12.76). Low trait agreeableness was associated with low adherence (OR 2.03, 95% CI 1.12-3.66). CONCLUSIONS: Approximately one-third of IBD patients were low adherers. Predictors of adherence differed markedly between genders, although obstacles such as medication cost were relevant for both men and women.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it