Self-reported cognitive function mediates the relationship between employment status and cognitive functioning in persons with multiple sclerosis
Bibliographic record
Abstract
Background Cognitive impairment (CI) is common in people with MS (PwMS). Evidence is lacking for the self-reported CI's mediation effect on employment status and objective cognitive performance. Self-reported CI was found to be unreliable and seemed to be more associated with depression rather than formal cognitive performance. We hypothesized that the link between subjective and objective assessments of cognitive functions, mood, and employment status may be more complex in PwMS than previously reported. Objective The aims of this study are the following: (Romero-Pinel et al., 2022) to determine whether employment status could affect performance in cognitive function testing and (Rao et al., 1991) whether their relationship may be mediated by self-reported CI; and (Deluca et al., 2013) to determine whether self-reported depression interacts with self-reported CI in influencing performance in various cognitive domains in PwMS. Methodology A retrospective study was performed involving PwMS who completed the self-report Multiple Sclerosis Neuropsychological Questionnaire (MSNQ), Hospital Anxiety and Depression Scale-depression scale (HADS-D), Minimal Assessment of Cognitive Function in MS (MACFIMS) and had data regarding employment status. Included PwMS were classified as employed or unemployed. A structural equation modeling (SEM) approach was taken due to the advantage of examining multiple cognitive outcomes simultaneously while accounting for shared associations. First, a latent factor of memory and executive functioning modeled the error-free associations between both factors and a processing speed task (SDMT). Next, the model tested for the indirect effect of self-reported cognition (MSNQ) on employment status differences in each outcome (memory, speed, and executive functioning). Finally, we tested interactions between MSNQ and HADS-D on each of the outcomes. Results We included 590 PwMS: 72.5% female, mean age 44.2 years (SD = 10.5), mean disease duration 8.6 years (SD 9.0). The majority (n = 455, 77.1%) had relapsing MS; 357 (60.5%) were employed. About half (n = 301, 51%) did not report CI on the MSNQ; of those, 213 (70.8%) were employed. The mean MSNQ for employed PwMS was 24.5 (SD = 10.7) and 29.8 (SD = 11.2) for unemployed PwMS. Employed PwMS had significantly better memory (β = .16, p < .05), executive functioning (β = .25, p < .05), and processing speed (β = .22, p < .05). MSNQ partially indirectly mediated the effect of employment status on memory (Δβ = .03, p < .05) and executive functioning (Δβ = .03, p < .05) and processing speed (Δβ = .04, p < .05), indicating that self-report CI partially explains the influence of employment status on these cognitive domains. The association between MSNQ with both memory and executive functioning was moderated by depression, meaning that in PwMS with high HADS-D scores, MSNQ was more strongly related to worse memory and executive functioning. The final model was an acceptable fit to the data (χ 2 (87) = 465.07, p < .05; CFI=.90, RMSEA=.08, 90% CI [.06, .09], SRMR=.05) explaining 41.20%, 38.50% and 33.40% of the variability in memory, executive functioning, and processing speed, respectively. Conclusion Self-reported CI partially explains the associations between employment status and objective cognitive assessment in PwMS. Depression may moderate the relationship between self-reported cognitive assessment and objective cognitive performance. Thus, employment status and mood may guide the interpretation of self-reported CI.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".