Association Between Objective Sleep and Clinical Outcomes in Older Adults With Low Back Pain Receiving Physical Therapy Care: A Secondary Analysis of a Responsiveness Study
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Sleep seems to be associated with worse low back pain (LBP) outcomes in older adults; however, studies investigating the association of objective sleep with future changes in LBP outcomes are lacking. The objectives of this study are as follows: (a) to investigate the association between objectively measured sleep with changes in clinical outcomes in older adults with LBP receiving physical therapy care and (b) to examine the cross-sectional association between sleep and pain catastrophizing. METHODS: This was a prospective cohort study. We recruited older adults (≥60 years old) with chronic LBP undergoing physical therapy treatment. At baseline, we assessed participants' sleep (actigraphy for 10-14 days), pain intensity, disability, pain catastrophizing, and covariates. After 8 weeks, we reassessed pain intensity, disability, and self-perceived recovery. We ran linear regression models and Spearman coefficient tests. RESULTS: Fifty-eight participants were included, and 51 completed follow-up assessments (60.8% women; mean age 70.1 ± 5.6 years). We found no associations between sleep quantity and efficiency with changes in pain intensity, disability, and self-perceived recovery after 8 weeks of physical therapy care. We found a correlation between sleep fragmentation and pain catastrophizing (r = .30; 95% confidence interval: [.03, .54]). CONCLUSION: Objective sleep quantity and efficiency may not be associated with changes in LBP outcomes after physical therapy care in older adults. Among the sleep domains evaluated, sleep fragmentation may be the sleep domain with the strongest association with pain catastrophizing. Significance/Implications: Objectively measured sleep might not be a prognostic factor for LBP improvement in older adults. Future studies should explore the association between sleep fragmentation and pain catastrophizing.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| 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".