The use of subjective cognitive complaints for detecting mild cognitive impairment in older adults across cultural and linguistic groups: A comparison of the Cognitive Function Instrument to the Montreal Cognitive Assessment
Bibliographic record
Abstract
INTRODUCTION: This pilot study aims to explore the psychometric properties of the Cognitive Function Instrument (CFI) as a measure of subjective cognitive complaints (SCC) and its performance in distinguishing mild cognitive impairment (MCI) from normal control (NC) compared to an objective cognitive screen (Montreal Cognitive Assessment [MoCA]). METHODS: One hundred ninety-four community-dwelling non-demented older adults with racial/ethnic diversity were included. Unidimensionality and internal consistency of the CFI were examined using factor analysis, Cronbach's alpha, and McDonald's omega. Logistic regression models and receiver operating characteristic (ROC) analysis were used to examine the performance of CFI. RESULTS: The CFI demonstrated adequate internal consistency; however, the fit for a unidimensional model was suboptimal. The CFI distinguished MCI from NC alone or in combination with MoCA. ROC analysis showed comparable performance of the CFI and the MoCA. DISCUSSION: Our findings support the use of CFI as a brief and easy-to-use screen to detect MCI in culturally/linguistically diverse older adults. HIGHLIGHT: What is the key scientific question or problem of central interest of the paper? Subjective cognitive complaints (SCCs) are considered the earliest sign of dementia in older adults. However, it is unclear if SCC are equivalent in different cultures. The Cognitive Function Instrument (CFI) is a 14-item measure of SCC. This study provides pilot data suggesting that CFI is sensitive for detecting mild cognitive impairment in a cohort of older adults with racial/ethnic diversity. Comparing performance, CFI demonstrates comparable sensitivity to the Montreal Cognitive Assessment, an objective cognitive screening test. Overall, SCC may provide a non-invasive, easy-to-use method to flag possible cognitive impairment in both research and clinical settings.
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 | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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".