Psychosocial predictors of patient adherence to disease-modifying therapies for multiple sclerosis
Bibliographic record
Abstract
OBJECTIVES: Our aim was to identify the impact of psychosocial predictors, specifically relationship style, depressive symptoms, anxiety symptoms, cognitive impairment, and culture-specific disease beliefs, on treatment adherence for multiple sclerosis (MS) patients. METHODS: In this cross-sectional observational study, patients from two MS clinics in Saudi Arabia completed self-reported questionnaires focused on MS treatment adherence, physical symptom burden, relationship style, cultural beliefs, depressive symptoms, anxiety, and cognitive impairment. RESULTS: A total of 163 MS patients participated, 81.6% of them were female, and the mean age of the patients was 31.6 years. Mean patient-reported adherence to their MS treatment regimen was 79.47%±25.26%. Multivariate linear regression analysis only identified patients' belief that their MS was due to "supernatural" forces as being significantly negatively associated with MS medication adherence. CONCLUSION: This study demonstrates the importance of cultural interpretations to MS medication adherence in comparison to psychosocial factors. Education and family involvement in the treatment planning may address this issue and warrant further research.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".