Device-Measured Walking and Standing are Associated with Improved Quality of Life, Mental Health, and Biochemical Markers in Patients with Ulcerative Colitis: A Pilot Study
Bibliographic record
Abstract
Background: Device-measured daily steps/step cadence and other prominent behaviours occurring throughout the 24-hour day (i.e., sitting, lying, standing) have not been examined in patients with ulcerative colitis (UC).The degree to which these behaviours are associated with mental health, quality of life and clinical outcomes in this population is unknown.Aims: To explore the associations between device-based walking, step cadence, and sedentary time and clinical outcomes among UC patients.Methods: Patients with UC wore an activPAL TM accelerometer for 7 days to measure daily steps, step cadence, lying, standing, and sitting time.Outcomes included total Mayo score (TMS), risk of depression (PHQ-8), risk of anxiety (GAD-7), and health-related quality of life [HRQoL (SF-12)] which included mental composite scores (MCS) and physical composite scores (PCS).Blood and stool samples were used to measure C-reactive protein (CRP) and fecal calprotectin (FCP).Results: Of 30 participants, thirteen (43.3%) had moderate to severe UC symptoms.The percentage of patients with moderate to severe depression and anxiety symptoms were 25.0% and 57.1%, respectively.Average daily steps were 7,869 3339.Step cadence ≥ 100 steps/min was positively associated with mental HRQoL and TMS, and inversely associated with FCP.Standing time was positively associated with TMS and inversely associated with depression, anxiety, and FCP.Faster walking was negatively correlated with CRP.Conclusion: This study identifies potential associations between device-measured brisk walking/running and periods of standing with HRQoL, mental health, and clinical outcomes.This study should be replicated in a larger sample to determine if these associations remain.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".