Impact of a Wearable Activity Tracker on Disease Flares in Spondyloarthritis: A Randomized Controlled Trial
Bibliographic record
Abstract
Objective To evaluate the impact of a wearable activity tracker used to encourage physical activity, on disease flares in patients with spondyloarthritis (SpA). Methods This randomized controlled trial involved randomizing 108 patients with SpA into tracker and nontracker groups. The participants were then subjected to assessments of disease activity, performance (6-minute walk test), and quality of life (QOL; 36-item Short Form Health Survey) at the 12th, 24th, and 36th week. The primary outcome was the change in the frequency of flare episodes (categorized as no flare, flare in ≤ 3 days, and flare in > 3 days) between baseline and 12 weeks. Results The results of the study showed that at the 12th week, the mean change (∆) of the number of flares improved in both groups: −0.32 (95% CI −0.66 to 0.02) and −0.38 (95% CI −0.68 to −0.09) in the tracker and nontracker group, respectively. However, the between-group differences were insignificant (P = 0.87). Performance scores improved in both groups at the 12th, 24th, and 36th week (all P < 0.01). The different dimensions of QOL also improved at the 12th week (P < 0.01). Conversely, moderate flares (P < 0.01) and performance (P < 0.01) improved over time; however, the influence over time of a wearable activity tracker was not significant (P = 0.29 and P = 0.66, respectively). Conclusion The use of a wearable activity tracker did not affect the number of flares, performance, or QOL of patients with SpA. Nevertheless, this study confirmed the benefits of physical activity on flares, disease activity, QOL, and physical performance in patients with SpA. (Move Your Spondyl “Better Live Its Rheumatism With the Physical Activity”; ClinicalTrials.gov : NCT03458026 )
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".