The incidence and prevalence of psychiatric disorders in multiple sclerosis: A systematic review
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: Psychiatric comorbidity is associated with lower quality of life, more fatigue, and reduced adherence to disease-modifying therapy in multiple sclerosis (MS). OBJECTIVES: The objectives of this review are to estimate the incidence and prevalence of selected comorbid psychiatric disorders in MS and evaluate the quality of included studies. METHODS: We searched the PubMed, PsychInfo, SCOPUS, and Web of Knowledge databases and reference lists of retrieved articles. Abstracts were screened for relevance by two independent reviewers, followed by full-text review. Data were abstracted by one reviewer, and verified by a second reviewer. Study quality was evaluated using a standardized tool. For population-based studies we assessed heterogeneity quantitatively using the I² statistic, and conducted meta-analyses. RESULTS: We included 118 studies in this review. Among population-based studies, the prevalence of anxiety was 21.9% (95% CI: 8.76%-35.0%), while it was 14.8% for alcohol abuse, 5.83% for bipolar disorder, 23.7% (95% CI: 17.4%-30.0%) for depression, 2.5% for substance abuse, and 4.3% (95% CI: 0%-10.3%) for psychosis. CONCLUSION: This review confirms that psychiatric comorbidity, particularly depression and anxiety, is common in MS. However, the incidence of psychiatric comorbidity remains understudied. Future comparisons across studies would be enhanced by developing a consistent approach to measuring psychiatric comorbidity, and reporting of age-, sex-, and ethnicity-specific estimates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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