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Record W2076440439 · doi:10.1080/13607863.2013.823376

The association between mild cognitive impairment and doing housework

2013· article· en· W2076440439 on OpenAlexaboutno aff
Changchuan Jiang, Yong Xu

Bibliographic record

VenueAging & Mental Health · 2013
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsConfoundingAssociation (psychology)GerontologyOdds ratioConfidence intervalCognitive impairmentActivities of daily livingCognitionPsychologyOlder peopleMontreal Cognitive AssessmentCross-sectional studyDemographyMedicinePsychiatry

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.340
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations28
Published2013
Admission routes1
Has abstractyes

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