MétaCan
Menu
Back to cohort
Record W4393357113 · doi:10.1080/13825585.2024.2333066

Self-reported physical activity and sleep quality is associated with working memory function in middle-aged and older adults during the COVID-19 pandemic

2024· article· en· W4393357113 on OpenAlexaff
Tiago Guardia, Kimberly A. Côté, M. Karl Healey, Kimberley L. Gammage, Karen L. Campbell

Bibliographic record

VenueAging Neuropsychology and Cognition · 2024
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsBrock University
Fundersnot available
KeywordsPsychologySleep (system call)Working memoryPandemicCognitionSleep qualityGerontologyEffects of sleep deprivation on cognitive performanceMemory testDevelopmental psychologyCoronavirus disease 2019 (COVID-19)Clinical psychologyMedicinePsychiatryDisease

Abstract

fetched live from OpenAlex

While previous work has shown a positive relationship between cognitive performance and lifestyle factors in younger adults, evidence for this relationship among middle-aged and older adults has been mixed. The current study aimed to further test the relationship among physical activity, sleep quality, and memory performance in middle-aged and older adults, and to test whether this relationship holds up during the COVID-19 pandemic. Our results showed that physical activity was associated with better sleep quality and better working memory performance, and better sleep quality was associated with better working memory and self-perceptions of everyday memory abilities. Additionally, we found that the effects of physical activity on working memory were partially mediated by sleep quality. While these effects were small and only correlational in nature, they lend further support to the notion that sleep quality and physical activity are beneficial to memory later in life, even during a global pandemic.

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)0.000
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 score0.226
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

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

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 head0.036
GPT teacher head0.311
Teacher spread0.275 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueAging Neuropsychology and CognitionSame topicSleep and related disordersFrench-language works237,207