Is Motor Function in MCI Related to Caregiver Ratings of Cognition and Everyday Function?
Bibliographic record
Abstract
Abstract Mild cognitive impairment (MCI) often affects daily functioning, which is typically assessed by subjective caregiver ratings. Previous research shows that caregiver ratings may be biased by individual factors, such as caregiver burden and stress. We aimed to extend this work by further examining whether decline in motor function in MCI also influences caregiver perceptions, potentially leading to lower ratings of patients’ cognition and everyday function. A cross-sectional study was conducted with 124 MCI patient-caregiver dyads (patients: age=74.7±6.6 years, 49% female; caregivers: age=65.6±13.3 years, 76% female). Caregivers rated MCI patients’ cognition and daily function using the Everyday Cognition Scale (ECog-39) and Functional Activities Questionnaire (FAQ) and completed the Zarit Burden Interview Short Form (ZBI-12) and NIH Toolbox Perceived Stress Scale (PSS). Patients completed the Montreal Cognitive Assessment (MoCA) and motor assessments (10-meter walk, handgrip strength, and 30-second chair stands). Multiple linear regressions were fitted while controlling for patient (age, sex, education, MoCA) and caregiver (age, sex) covariates. Consistent with the prior work, higher caregiver burden and stress were associated with lower caregiver ratings on ECog-39 (ZBI-12: B = 0.86, p<.001; PSS: B = 0.94, p<.001) and FAQ ratings (ZBI-12: B = 0.03, p<.001; PSS: B = 0.22, p=.026). In contrast, walking speed, grip strength, and chair stands were not associated with ECog-39 and FAQ ratings (all p>.10). Caregivers’ subjective ratings of MCI patients’ cognition and daily functioning were more closely tied to their own burden and stress than to patients’ motor performance. These findings highlight the need to consider caregiver factors when interpreting subjective functional ratings in MCI.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".