Montreal Cognitive Assessment Hearing Impairment (MoCA-H) in Brazilian Portuguese: criterion and construct validity
Bibliographic record
Abstract
ABSTRACT Purpose To find evidence of criterion and construct validity for the Montreal Cognitive Assessment Hearing Impairment (MoCA-H) protocol in Brazilian Portuguese. Methods The sample consisted of 70 elderly people divided into two groups: Group 1-50 subjects with hearing loss and no cognitive decline; Group 2-20 subjects with hearing loss and cognitive decline. Criterion validity was obtained by comparing Group 1 and 2 considering the overall score and the eight domains assessed in the MoCA-H. The data were analyzed using the Mann-Whitney U-test and Student's T-test, respecting the characteristics of the data collected. To verify construct validity, the correlation between the total scores of the Mini-Mental State Examination (MMSE) and the MoCA-H obtained by Group 2 was analyzed. Spearman's Correlation Test was used for this purpose. Results The analysis of criterion validity showed a difference between the groups with and without decline in naming, attention, language, abstraction, memory and delayed recall skills, as well as the MoCA-H total score, indicating significantly higher performance of Group 1. The construct validity correlation analysis was weak and non-significant (Rho=0.384; p=0.095) between the MoCA-H and MMSE scores. Conclusion The MoCA-H protocol showed good criterion validity for this specific population, making it a reliable tool for screening mild cognitive decline. However, it did not show satisfactory construct validity, indicating the need for further studies with this instrument using another protocol as a reference.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 source (direct Gemma or distilled Codex), 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".