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Record W4394884804 · doi:10.1186/s44167-024-00049-5

Twenty-four hour physical activity, sedentary behaviour and sleep profiles in adults living with rheumatoid arthritis: a cross-sectional latent class analysis

2024· article· en· W4394884804 on OpenAlexafffund
Lynne M. Feehan, Hui Xie, Na Lu, Linda Li

Bibliographic record

VenueJournal of Activity Sedentary and Sleep Behaviors · 2024
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsResearch CanadaSimon Fraser UniversityUniversity of British Columbia
FundersArthritis Society
KeywordsLatent class modelSittingMultinomial logistic regressionMedicineRheumatoid arthritisLogistic regressionSleep (system call)Cross-sectional studyPhysical therapySedentary lifestyleDemographyPsychologyGerontologyPhysical activityInternal medicineStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: Rheumatoid Arthritis (RA), an autoimmune systemic inflammatory disease, affects more than 17 million people globally. People with RA have higher risk of premature mortality; often experience chronic fatigue, pain and disrupted sleep; and are less physically active and more sedentary than healthy counterparts. It remains unclear how people with RA may balance sleep and awake movement activities over 24-hours, or how differences in 24-hour behaviours may be associated with determinants of health, or alignment with published activity guidelines. METHODS: Cross-sectional exploration of objective measures of 24-hour sleep-wake activities in 203 people with RA. Latent Class Analysis (LCA) derived classes from time, by tertile, in six sleep-awake activities over 24 h. Comparisons of model fit statistics, class separation and interpretability defined best fit for number of classes. Variations in sleep-awake behaviour across classes and association of profile allocation with determinants of health, quality metrics for sleep, sitting and walking and alignment with published guidelines were explored. Multinomial logistic regression identified factors associated with likelihood of profile allocation. RESULTS: LCA identified 2 to 6 classes and a 4-class model was determined as best fit for 24-hour sleep-awake behaviour profiles. One profile (26%) presented with more balanced 24-hour sleep, sitting and walking behaviours. The other three profiles demonstrated progressively less balanced 24-hour behaviours including: having low (< 7 h), high (> 8 h), or recommended (7-8 h) sleep duration in respective combination with high sitting (> 10 h), limited walking (< 3 h) or both when awake. Age, existing sitting and walking habit strength and fatigue were associated with likelihood of belonging to different profiles. More balanced 24-hour behaviour was aligned with better quality metrics for sleep, sitting and walking and published guidelines. DISCUSSION: For people living with RA it is important to understand the 'whole person' and their 'whole day' to define who may benefit from support to modify 24-hour sleep-awake behaviours and which behaviours to modify. Supports should be informed by an understanding of personal or health-related factors that could act as barriers or facilitators for behavioural change, including exploring existing habitual sitting and walking behaviours. TRIAL REGISTRATIONS: ClinicalTrials.gov ID: NCT02554474 (2015-09-16) and ClinicalTrials.gov ID: NCT03404245 (2018-01-11).

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.013
GPT teacher head0.285
Teacher spread0.273 · 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.

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

Citations3
Published2024
Admission routes2
Has abstractyes

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