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Cognitive decline in Alzheimer disease

2007· article· en· W2086822026 on OpenAlexaff
Yakir Kaufman, David Anaki, Malcolm A. Binns, Morris Freedman

Bibliographic record

VenueNeurology · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsReligiositySpiritualityCognitive declineQuality of life (healthcare)PsychologyCognitionClinical psychologyDiseaseGerontologyMedicineDemographyInternal medicinePsychiatryDementiaPathologySocial psychologyPsychotherapistSociology

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess effects of quality of life (QOL), spirituality, and religiosity on rate of progression of cognitive decline in Alzheimer disease (AD). METHODS: In this longitudinal study, we recruited 70 patients with probable AD. The Mini-Mental State Examination was used to monitor the rate of cognitive decline. Religiosity and spirituality were measured using standardized scales that assess spirituality, religiosity, and organizational and private religious practices. We conducted a simultaneous multiple linear regression analysis for factors contributing to rate of cognitive decline. RESULTS: After controlling for baseline level of cognition, age, sex, and education, a slower rate of cognitive decline was associated with higher levels of spirituality (p < 0.05) and private religious practices (p < 0.005). These variables accounted for 17% of the total variance [F(11,58) = 2.24, p < 0.05]. There was no correlation between rate of cognitive decline and QOL. CONCLUSION: Higher levels of spirituality and private religious practices, but not quality of life, are associated with slower progression of Alzheimer disease.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
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 integrity0.0000.001
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 head0.056
GPT teacher head0.399
Teacher spread0.343 · 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

Citations109
Published2007
Admission routes1
Has abstractyes

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