Psychometric properties of screening tools for mild cognitive impairment in older adults based on COSMIN guidelines: a systematic review
Bibliographic record
Abstract
BACKGROUND: The prevalence of mild cognitive impairment in older adults is understood to be as high as 40%, and early screening for MCI may slow the progression of Alzheimer's disease. However, no systematic review has summarized the psychometric properties of instruments. OBJECTIVE: This systematic review aimed to assess the psychometric properties of existing scales for screening older adults for mild cognitive impairment and to provide an evidence-based basis for selecting the most appropriate assessment tool for older adults. DESIGN: This study systematically reviewed the measurement properties using the consensus-based Criteria for the Selection of Instruments for Measuring Health (COSMIN) method. METHODS: Eight electronic databases (PubMed, Embase, Web of Science, Scopus, Cochrane, CNKI, Wanfang, and Proquest) were systematically searched from inception up to October 26, 2024. Methodological quality was assessed using the COSMIN risk of bias checklist, and psychometric properties were summarized and evaluated using the COSMIN criteria. RESULTS: Thirty-one studies reported 30 different versions of screening instruments, with 15 studies examining more than 5 psychometric properties. Limited information on construct validity and reliability was found. No data were found on cross-cultural validity/measurement invariance, measurement error, or responsiveness. The final three instruments, AV-MoCA, HKBC, and Qmci-G, received class A recommendations and were recommended for use. The TICS-M study had insufficient psychometric properties and received a class C recommendation; thus, it was not recommended for use. The other 26 instruments were class B recommendations, indicating potential for use, although further research is needed to assess their psychometric properties. CONCLUSION: The AV-MoCA, HKBC, and Qmci-G can be used to screen older adults for MCI. Future research is needed to further validate the cross-cultural applicability of these instruments and to fully assess their psychometric properties.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| 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".