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Sleep disturbance mediates the relationship between depressive symptoms and cognitive function in older adults with mild cognitive impairment

2021· article· en· W3180113277 on OpenAlexaboutno aff
Jie Zhou, Juanjuan Ma, Jing Chang, Yuzhen Qiu, Zexiang Zhuang, Huan Xiao, Li Zeng

Bibliographic record

VenueGeriatric Nursing · 2021
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
FundersHumanities and Social Science Fund of Ministry of Education of ChinaScience, Technology and Innovation Commission of Shenzhen MunicipalityMinistry of Education of the People's Republic of China
KeywordsPittsburgh Sleep Quality IndexCognitionMediationDepression (economics)DementiaSleep disorderGeriatric Depression ScaleClinical psychologyPsychologySleep (system call)Depressive symptomsPopulationPsychiatrySleep qualityMedicineInternal medicine

Abstract

fetched live from OpenAlex

This study examined whether and to what extent sleep disturbance mediates the effects of depressive symptoms on the cognition of individuals with mild cognitive impairment (MCI), who represent a high-risk group for developing dementia. Cross-sectional data were obtained from a sample of 204 Chinese community-dwelling older adults with MCI. MCI subjects were screened using the Montreal Cognitive Assessment, sleep quality was measured using the Pittsburgh Sleep Quality Index, and depressive symptoms were assessed using the Geriatric Depression Scale. Mediation analysis was conducted using the PROCESS macro with 10,000 bootstrap samples. The significant mediating effect of sleep quality on the association between depressive symptoms and cognition (Beta = -0.025; 95% CI, -0.054 to -0.007) explains 26% of the total effect of depressive symptoms on cognition and implies that the timely detection and management of sleep disturbance among the MCI population is highly important, especially for those with depressive symptoms.

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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.266
Teacher spread0.256 · 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

Citations27
Published2021
Admission routes1
Has abstractyes

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