Montreal Cognitive Assessment: Exploring the impact of demographic variables, internal consistency reliability and discriminant validity in a South African sample
Bibliographic record
Abstract
The Montreal Cognitive Assessment (MoCA) is widely used to screen for cognitive impairment and has shown a good capacity to identify cognitive impairment. However, its psychometric properties have not been sufficiently studied in the South African context. Therefore, this study aimed to investigate (1) the influence of demographic variables (age, years of education, and gender) on total MoCA scores; (2) the internal consistency reliability of the test and (3) the discriminant validity of the total MoCA score. This study analysed secondary quantitative data, utilising a cross-sectional, between-subjects design. All participants completed the English MoCA version 8.1. The control sample (n = 89) included healthy South African adults who speak English as a second or third language and who have been educated in public schools. The clinical sample (n = 83) included patients with human immunodeficiency virus (HIV) and a comorbid disorder, either psychiatric (n = 70) or neurocognitive (n = 13). Total MoCA scores were significantly correlated with years of education (p 0.001) and age (p = 0.007) but not gender. Cronbach’s alpha was 0.64 revealing moderate internal consistency. The total MoCA score was not a significant predictor of diagnostic status, indicating poor discriminant validity of the MoCA in this sample. The MoCA appears not to be a useful screening or diagnostic tool in samples with similar characteristics.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".