Adverse health behaviours are associated with depression and anxiety in multiple sclerosis: A prospective multisite study
Bibliographic record
Abstract
Background: Depression and anxiety are common among people with multiple sclerosis (MS), as are adverse health behaviours, but the associations between these factors are unclear. Objective: To evaluate the associations between cigarette smoking, alcohol use, and depression and anxiety in MS in a cross-Canada prospective study. Methods: From July 2010 to March 2011 we recruited consecutive MS patients from four MS clinics. At three visits over two years, clinical and demographic information was collected, and participants completed questionnaires regarding health behaviours and mental health. Results: Of 949 participants, 75.2% were women, with a mean age of 48.6 years; most had a relapsing-remitting course (72.4%). Alcohol dependence was associated with increased odds of anxiety (OR: 1.84; 95% CI: 1.32-2.58) and depression (OR: 1.53; 95% CI: 1.05-2.23) adjusting for age, sex, Expanded Disability Status Scale (EDSS), and smoking status. Smoking was associated with increased odds of anxiety (OR: 1.29; 95% CI: 1.02-1.63) and depression (OR: 1.37; 95% CI: 1.04-1.78) adjusting for age, sex, EDSS, and alcohol dependence. Alcohol dependence was associated with an increased incidence of depression but not anxiety. Depression was associated with an increased incidence of alcohol dependence. Conclusion: Alcohol dependence and smoking were associated with anxiety and depression. Awareness of the effects of adverse health behaviours on mental health in MS might help target counselling and support for those 'at risk'.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".