Impact of cognition on test–retest reliability and concurrent validity of n-back for Chinese stroke patients
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Bibliographic record
Abstract
Objective The objective of this study was the measurement of the test–retest reliability of n-back in Chinese stroke patients.Methods Seventy-five sub-acute stroke patients performed n-back twice in three days. The test–retest reliability of n-back was analyzed by correlation coefficient.Results The n-back had excellent test–retest reliability in stroke patients. Pearson or Spearman coefficients ranged from 0.81 to 0.88. The intra-class correlation coefficients ranged from 0.72 to 0.87. The Chinese version of Montreal Cognitive Assessment-Basic (MoCA-BC) score was significantly correlated with the performance of n-back. MoCA-BC and n-back accuracy were significantly related in the Mild Cognitive Impairment (MCI) group (r = 0.60 in 1-back, p = .002; r = 0.43 in 2-back, p = .040). However, MoCA-BC was correlated with reaction time (RT) in the Cognitively Normal (CN) group (r = –0.44 in 1-back, p = .003; r = –0.36 in 2-back, p = .018). The test–retest reliability of CN group was mostly higher than that of MCI group RT: 0.71–0.76 in MCI, 0.80–0.88 in CN; accuracy: 0.80–0.85 in MCI, 0.75–0.86 in CN). The practice effect was observed in the CN group instead of the MCI group.Conclusions This study indicated that the test–retest reliability of n-back was high in stroke patients. N-back was correlated with cognition. It was preferable to conduct subgroup analyses according to the level of cognitive assessment of patients with stroke.
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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 | 0.000 | 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) | 0.000 | 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