The association between mild cognitive impairment and doing housework
Bibliographic record
Abstract
OBJECTIVES: The ability to perform instrumental activities of daily living (IADL) is thought to be relatively intact for people with mild cognitive impairment (MCI). Doing housework as part of IADL is an important skill needed for older people to live independently and successfully. A limited number of studies explore the association between MCI and doing housework. The aim of this study was to assess the association between MCI and doing housework among old people. METHOD: The study employed a community-based, cross-sectional design. A total of 1773 older people residents, aged 60 and over, were randomly recruited in the Suzhou area, and they underwent the Montreal cognitive assessment (MoCA) for screening MCI in 2009. Participants were required to complete a questionnaire, which was comprised of their demographic information, health status, and life style, to evaluate the associations between MCI and these factors. RESULTS: About 13% of the respondents were found to have MCI. People with MCI are found to be less healthy and live unhealthy lifestyles. After adjusting confounding factors, a significant association was observed between MCI and not doing housework (Odds ratio (OR) = 1.64; 95% confidence interval (CI) = 1.17-2.30). CONCLUSIONS: MCI is associated with doing less housework. The deterioration in the ability to do housework is a potentially important indicator of evolving cognitive impairment in some old people.
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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 | 0.001 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".