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Record W2021687825 · doi:10.1159/000355553

Cognitive Activities and Instrumental Activity of Daily Living in Older Adults with Mild Cognitive Impairment

2013· article· en· W2021687825 on OpenAlexaff
Takehiko Doi, Hiroyuki Shimada, Hyuma Makizako, Sang‐Yoon Lee, Hyuntae Park, Kota Tsutsumimoto, Kazuki Uemura, Daisuke Yoshida, Yuya Anan, Takao Suzuki

Bibliographic record

VenueDementia and Geriatric Cognitive Disorders Extra · 2013
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsActivation Laboratories
FundersJapan Society for the Promotion of ScienceNational Center for Geriatrics and Gerontology
KeywordsCognitionActivities of daily livingPsychologyCognitive impairmentCognitive declineGerontologyDementiaMedicineInternal medicinePsychiatryDisease

Abstract

fetched live from OpenAlex

AIMS: This study aimed to identify differences in the implementation of cognitive activities and instrumental activities of daily living (IADLs) between healthy individuals and subjects with mild cognitive impairment (MCI). METHODS: The study included 2,498 cognitively healthy subjects (mean age, 71.2 ± 5.1 years) and 809 MCI subjects (mean age, 71.8 ± 5.4 years). The subjects were interviewed regarding their participation in cognitive activities and the implementation of IADLs. RESULTS: We found a significant association between participation in any cognitive activities (p < 0.001), using a bus or a train (p < 0.001), and MCI. After adjusting for covariates, cognitive activity of any type remained significantly associated with MCI (p < 0.005) but not with the implementation of IADLs. CONCLUSIONS: Our study revealed that greater participation in cognitive activity was associated with lower odds of MCI. Participation in cognitive activities may reflect differences between healthy and MCI subjects. To clarify the causal relationship between cognitive activities and MCI, further studies are required.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.250
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), 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

Citations20
Published2013
Admission routes1
Has abstractyes

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