An exploratory study of two measures of free-living physical activity for people with multiple sclerosis
Bibliographic record
Abstract
OBJECTIVE: To examine the ability of two measures of physical activity (tri-axial accelerometer and activity diary) to discriminate among groups of inactive, moderately active and active individuals with multiple sclerosis and to explore the relationship between these two measures. DESIGN: Exploratory, descriptive study. SUBJECTS: Thirty individuals with multiple sclerosis and nine controls. PROTOCOL: Individuals with multiple sclerosis were recruited to inactive, moderately active and active groups as defined by Adjusted Activity Scores from the Human Activity Profile. Control participants were recruited to an active group. Free-living physical activity was recorded over four consecutive days. MAIN MEASURES: A TriTrac RT3 accelerometer and a self-report physical activity diary were used to measure activity. RESULTS: Thirty-six participants completed data collection. For the participants with multiple sclerosis, both the accelerometer (P = 0.004) and the diary (P = 0.006) detected significant differences between inactive and active groups. The accelerometer also detected a significant difference between moderately active and active groups (P = 0.04). In contrast, the diary detected a significant difference between inactive and moderately active groups (P = 0.05). Accelerometer and diary scores were significantly correlated (r = 0.59). Accelerometer scores were significantly correlated with neurological status (r(s) = -0.64). CONCLUSIONS: Both measures readily differentiated least active from most active groups. The accelerometer also differentiated moderately active from active groups, suggesting suitability for use in detecting change in more active client groups, while the diary differentiated inactive from moderately active groups, suggesting suitability for use in detecting change in less active groups.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".