PORTUGUESE VERSION OF THE QUICK MILD COGNITIVE IMPAIRMENT (QMCI-P) SCREEN—RESULTS FROM THE IBIS STUDY
Bibliographic record
Abstract
Background: As health professionals and researchers face more and more older adults and limited assessment times, there has been an increasing demand for shorter sensitive, reliable and valid cognitive screening instruments. Objective: To adapt the Qmci for Portuguese-language countries, to explore concurrent validity against most common short cognitive screening instruments - MMSE-P and MoCA-P and to assess correlations with other neurospychological dimensions. Methods: Demographic and clinical data (cognition, personality, depression and functionality) of older adults aged ≥65, attending ten day care centres (n=113) and residents in two long-term care institutions (n=53), were collected and assessed with short screening tools. Results: 148 individuals were screened with Qmci-P - median age of 77 (IQR +/-15); 64% female. 103 participants completed the assessment battery and those scoring ≥21 on GDS (indicating possible active depression) were excluded (n=11). The final sample (n=93) had a median age of 74 (IQR +/-15), significantly younger than all those initially consenting (p=0.03). Internal consistency of the Qmci-P using Cronbach’s Alpha was 0.823, better than with MoCA (0.79) and MMSE (0.54). The median Qmci-P score was 57/100 (IQR +/-26) with a median MoCA of 21/30 (IQR +/-8) and median SMMSE of 27/30 (IQR +/-5). Qmci-P screen scores were strongly, positively and significantly correlated with both MMSE (r=0.61, 95% CI 0.45–0.72, p<0.001) and MoCA (r=0.63, 95% CI 0.36–0.80, p<0.001). Conclusion: The Qmci-P is a valid short cognitive screen. Given the psychometric properties and brevity (3–5 minutes), it may be preferable for use than MMSE (7–8 minutes) and MOCA (10–12 minutes).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".