Personality and cognitive factors implicated in depression and anxiety in multiple sclerosis: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Depression and anxiety are prevalent among persons living with multiple sclerosis (plwMS) and are linked to negative prognostic outcomes. Cognitive theories posit that personality and cognitive factors confer risk for depression and anxiety. This meta-analytic review aimed to synthesise evidence on personality and cognitive factors related to depression and anxiety in MS and determine whether sociodemographic and clinical variables moderate factor-symptom relations. Methods: This systematic review, meta-analysis and meta-regression was prospectively registered (CRD42020192253). Publications were identified through database searches (Medline, Embase, PsycInfo, WebofScience, Proquest) and considered if they included a sample of individuals with clinically definite MS (age ≥11 years) and a measure of depression or anxiety and a personality or cognitive factor. The Newcastle-Ottawa Scale was applied to assess methodological rigor. Results: A total of 99 studies were included in the narrative synthesis (97 samples; N= 13,609; Mage= 44.20±7.26), with 77 contributing effects on 24 factors for random-effects meta-analyses. The most robust relationships were between depression and anxiety and higher neuroticism, lower extraversion, emotion dysregulation, and illness perceptions of serious MS consequences and a strong MS identity (r's=0.28–0.59). A set of factors exhibited specificity for depression, including psychological inflexibility (r= 0.62) and optimism (r= -0.43). Relationships varied as a function of age, gender, and MS-type. Limitations: Limited data availability prevented evaluation of heterogeneity in all cases, and prospective conclusions. Exclusion criteria in the included studies reduced the generalisability findings. Conclusions: Findings highlight shared and distinct factors implicated in depression and anxiety, offering insights for tailored interventions.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".