Psychometric Properties of the Chinese Version of the ElectroConvulsive Therapy Cognitive Assessment
Bibliographic record
Abstract
OBJECTIVES: Electroconvulsive therapy (ECT) is an effective somatic treatment, but it may be limited by cognitive adverse effects. The existing cognitive screening instruments often lack specificity to ECT-associated cognitive deficits. The ElectroConvulsive Therapy Cognitive Assessment was developed and validated in a clinical setting, but the reliability and validity of the Chinese version of ElectroConvulsive Therapy Cognitive Assessment (ECCA-C) have not been studied in a large clinical sample. METHODS: The ECCA-C and the Montreal Cognitive Assessment (MoCA) were administered to patients with major depressive disorder (MDD) undergoing ECT at 3 time points: pretreatment (baseline), before the fifth treatment, and 1 week posttreatment. The instruments were also administered to a sample of healthy subjects. RESULTS: Sixty-five patients with MDD and 50 age- and sex-matched healthy controls were recruited in this study. Overall, the patient group had statistically significantly lower MoCA and ECCA-C scores than the control group (both P values <0.001). The Cronbach α of the ECCA-C was 0.88 at baseline. Statistically significant decreases over time were observed in ECCA-C: pre-ECT (23.9 ± 4.0) > mid-ECT (21.3 ± 3.4) > post-ECT (18.7 ± 4.8) (all P values <0.001), whereas no statistically significant changes in MoCA scores were found at these 3 time points ( F = 1.86, P = 0.165). A cutoff score of 26.5 on the ECCA-C was found to best differentiate between MDD patients and healthy controls. CONCLUSIONS: The ECCA-C showed satisfactory psychometric properties and may be a more sensitive instrument than the MoCA to assess cognitive impairment associated with ECT.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 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".