Twenty four-hour sleep, movement and sedentary activity profiles in adults living with Rheumatoid Arthritis: A cross-sectional latent class analysis
Bibliographic record
Abstract
Abstract Background Rheumatoid Arthritis (RA) is an auto-immune systemic inflammatory disease, affecting more than 17 million people globally. People with RA commonly have other chronic health conditions, have a higher risk for premature mortality, often experience chronic fatigue, pain and disrupted sleep and are less physically active and more sedentary than healthy counterparts. What remains unclear is how people with RA may balance their time sleeping and participating in non-ambulatory or walking activities over 24-hours. Nor is it known how different 24-hour sleep-movement patterns may be associated with common determinants of health in people with RA. Methods We conducted a cross-sectional exploration of objectively measured 24-hour walking, non-ambulatory, and sleep activities in 203 adults with RA. We used Latent Class Analysis to identify 24-hour sleep-movement profiles and examined how different profiles were associated with sleep, sitting and walking quality and meeting published guidelines. We conducted multinomial logistic regression to identify factors associated with likelihood of belonging to individual profiles. Results We identified 4 clusters, including one cluster (26%) with more balanced 24-hour sleep, sitting and walking behaviours. The other three clusters demonstrated progressively less balanced profiles; having either too little (< 7 hrs), too much (> 8 hrs), or enough sleep (7–8 hrs) in respective combination with sitting too much (> 12 hrs), walking to little (< 3 hrs) or both when awake. Age, existing sitting and walking habits and fatigue were associated with the likelihood of belonging to different profiles. More balanced 24-hour behaviour was associated with better metrics for sleep, sitting and walking quality and greater likelihood for meeting benchmarks for daily steps, weekly MVPA and Canadian 24-hour movement guidelines. Discussion For adults living with RA, and potentially other chronic health conditions, it is important to understand the ‘whole person’ and their ‘whole day’ to define who may benefit from support to modify 24-hour sleep-movement behaviours and for tailoring healthy lifestyle messages for which behaviours to modify. Supports should be are informed by an understanding of personal or health related factors that could be acting as barriers or facilitators to behaviour change including exploring how habitually engrained existing sitting or walking behaviours may be. Trial Registrations ClinicalTrials.gov ID NCT02554474 (2015-09-16) and ClinicalTrials.gov ID NCT03404245 (2018-01-11)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".