Anxiety and depression affect performance on the symbol digit modalities test over time in MS and other immune disorders
Bibliographic record
Abstract
Background: Longitudinal studies assessing depression and anxiety effects on cognition in multiple sclerosis (MS) are limited. Objective: We tested whether within-person fluctuations in symptoms of depression or anxiety over time affect cognition in persons with MS, inflammatory bowel disease (IBD), rheumatoid arthritis (RA), and a lifetime history of depression/anxiety disorders (DEP/ANX) but without an immune-mediated inflammatory diseases (IMID). Methods: We followed participants (MS: 255, IBD: 247, RA: 154, and DEP/ANX: 306) for 3 years. Annually, they completed the hospital anxiety and depression scale (HADS) and cognitive tests including the symbol digit modalities test (SDMT). We evaluated associations of elevated symptoms (scores ⩾ 11) of anxiety (HADS-A) and depression (HADS-D) with SDMT z-scores using multivariable linear models—estimating between-person and within-person effects. Results: Participants with MS performed worse on the SDMT than participants in the DEP/ANX cohort (β = −0.68; 95% CI: −0.88, −0.48). Participants with elevated HADS-A scores performed worse on the SDMT than those without elevated scores (β = −0.43; 95% CI: −0.65, −0.21), particularly those with RA. Time-varying within-person elevations in depressive symptoms were associated with worse SDMT performance (β = −0.12; 95% CI: −0.21, −0.021). Conclusions: Across persons, elevated symptoms of anxiety adversely affected information processing. Elevated symptoms of depression within-persons over time were associated with declines in information processing speed.
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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 | 0.001 | 0.002 |
| 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) | 0.000 | 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".