Reliability of Cognitive Measures in Individuals With a Chronic Spinal Cord Injury
Bibliographic record
Abstract
Background Following spinal cord injury (SCI), up to 64% of individuals experience cognitive deficit. However, the reliability of commonly used neuropsychological tests is currently unknown in this population. Objectives To evaluate the test‐retest reliability of cognitive measures in individuals with SCI. Design Cross‐sectional study. Setting Vancouver General Hospital. Participants Individuals with a chronic (>2 years) SCI (n = 22). Methods Across three visits (separated by ~16 days), 22 participants with chronic SCI completed a neuropsychological battery evaluating memory (Rey Auditory‐Verbal Learning Test [RAVLT]), attention/concentration/psychomotor speed (Digit Span Task, Stroop Test), and executive function (Trail Making Test A&B, Symbol Digit Modalities Test, Controlled Oral Word Association Test). Coefficients of variation (CV intra ) and intraclass correlation coefficients (ICCs) were calculated to determine the reliability of each test between visits. Linear regressions were performed to assess the associations between variability (CV intra ) and participant characteristics, such as age or highest education level attained. Repeated‐measures, one‐way analysis of variance (ANOVA) was conducted to determine any significant practice effects, and smallest real differences (SRDs) were calculated. Main Outcome Measurements Repeated scores on aforementioned neuropsychological tests. Results ICCs ranged from 0.77 to 0.93, with the exception of RAVLT recognition score (ICC = 0.27). Age showed a moderate association with CV intra in RAVLT interference recall scores ( r = 0.43, P = .047), but was not a confounding factor for other measures. Education was not associated with CV intra . Significant practice effects were noted for most of the cognitive tests assessed. Conclusions Other than the RAVLT recognition score, these cognitive measures demonstrated good‐to‐excellent reliability. Although this is encouraging, test‐retest variability should be considered when interpreting the efficacy of various cognitive training strategies to mitigate cognitive decline in this population. Thus, the SRD values presented herein will allow researchers and clinicians to identify “true” changes in cognitive function with repeated testing. Level of Evidence III.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".