Feasibility and Utility of a Fitbit Tracker Among Ambulatory Children and Youth With Disabilities
Bibliographic record
Abstract
PURPOSE: To examine the feasibility and utility of the Fitbit Charge HR to estimate physical activity among ambulatory children and youth with disabilities. METHOD: Participants (4-17 y old) with disabilities were recruited and asked to wear a Fitbit for 28 days. Feasibility was assessed as the number of participants who adhered to the 28-day protocol. Heat maps were generated to visually examine variability in step count by age, gender, and disability group. Between-group differences for wear time and step counts by age, gender, and disability type were assessed by independent sample t tests for gender and disability group, and a 1-way analysis of variance for age group. RESULTS: Participants (N = 157; median age = 10 y; 71% boys; 71% nonphysical disabilities) averaged 21 valid days of wear time. Wear time was higher in girls than boys (mean difference = 18.0; 95% confidence interval [CI], 6.8 to 29.1), and in preadolescents (mean difference = 27.6; 95% CI, 15.5 to 39.7) and adolescents (mean difference = -21.2; 95% CI, -33.6 to -8.7) than children. More daily steps were taken by boys than girls (mean difference = -1040; 95% CI, -1465 to -615) and individuals with a nonphysical disability than a physical disability (mean difference = -1120; 95% CI, -1474 to -765). The heat maps showed peaks in physical activity on weekdays before school, at recess, lunchtime, and after school. CONCLUSION: The Fitbit is a feasible tool for monitoring physical activity among ambulatory children and youth with disabilities and may be useful for population-level surveillance and intervention.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".