Effects of Integrating Wearable Activity Trackers With a Home-Based Multicomponent Exercise Intervention on Fall-Related Parameters and Physical Function in Older Adults: Randomized Controlled Trial
Bibliographic record
Abstract
Background: Older adults with a history of falling often encounter challenges in participating in group exercise programs. Recent technological advances, such as activity trackers, can potentially enhance home-based exercise programs by providing continuous physical activity monitoring and feedback. Objective: The aim of the study is to explore whether integrating wearable activity trackers with a home-based exercise intervention is effective in reducing fear of falling and improving physical function in older adults. Methods: This was a 12-week, parallel-group, randomized controlled trial involving 30 older adults (≥60 years) with a history of falling. Participants were randomly assigned in a 1:1 ratio to either a group combining an activity tracker with a home-based multicomponent exercise intervention, which included in-person exercise sessions, exercise videos, and objective feedback via phone calls (AT+EX group) or to a group using the activity tracker only for self-monitoring (AT-only group). The primary and secondary outcomes included fall-related parameters (fear of falling assessed by the Activities-Specific Balance Confidence [ABC] and the Falls Efficacy Scale-International [FES-I] scales), depression (Short Geriatric Depression Scale), cognition (Montreal Cognitive Assessment), physical function (grip strength, Short Physical Performance Battery, Timed Up and Go [TUG] test, and 2-Minute Step Test), and body composition. Changes in the average daily step count were monitored and analyzed. Results: Overall, 28 (mean age 74.0, SD 6.4 years; n=23, 77% female) participants completed the 12-week follow-up period (28/30, 93%). In the activity tracker and exercise group (AT+EX group), significant improvements were observed in fear of falling (15.5 points of ABC: P=.002; -5.1 points of FES-I: P=.01). The activity tracker alone group (AT-only group) also showed a significant improvement in FES-I score (-5.5 points: P=.01). Physical function significantly improved in the AT+EX group (1.1 points of Short Physical Performance Battery: P=.004; -1.4 seconds of TUG; P=.008; and 26.7 steps of 2-Minute Step Test: P=.001), whereas the AT-only group showed significant improvement only in the TUG test (-1.3 seconds: P=.002). However, no significant between-group differences were observed in the ABC score, FES-I score, or physical function. Despite no significant increase in daily step counts, both groups maintained close to 10,000 steps per day throughout the 12 weeks. Conclusions: Both groups showed improvements in the FES-I and TUG test scores without significant between-group differences. Wearable technology, with or without an exercise intervention, seems to be an effective tool in reducing the fear of falling and improving physical function in older adults susceptible to falls.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".