Acceptability of Robotic-Assisted Exercise Coaching Among Diverse Youth: Pilot Study
Bibliographic record
Abstract
BACKGROUND: Almost 80% of adolescents do not achieve 60 minutes or more of physical activity each day as recommended by current US national guidelines. There is a need to develop and promote interventions that increase physical activity among adolescents. With increased interest in digital technologies among adolescents, robotic-assisted platforms are a novel and engaging strategy to deliver physical activity interventions. OBJECTIVE: This study sought to assess the potential acceptability of robotic-assisted exercise coaching among diverse youth and to explore demographic factors associated with acceptance. METHODS: This pilot study used a cross-sectional survey design. We recruited adolescents aged 12-17 years at three community-based sites in Rochester, MN. Written informed consent was obtained from participants' parents or guardians and participants gave consent. Participants watched a brief demonstration of the robotic system-human interface (ie, robotic human trainer). The exercise coaching was delivered in real time via an iPad tablet placed atop a mobile robotic wheel base and controlled remotely by the coach using an iOS device or computer. Following the demonstration, participants completed a 28-item survey that assessed sociodemographic information, smoking and depression history, weight, and exercise habits; the survey also included the eight-item Technology Acceptance Scale (TAS), a validated instrument used to assess perceived usefulness and ease of use of new technologies. RESULTS: (SD 4.0). Of note, 18.4% (35/190) experienced depression now or in the past. The mean TAS total score was 32.8 (SD 7.8) out of a possible score of 40, indicating high potential receptivity to the technology. No significant associations were detected between TAS score and gender, age, racial minority status, participant neighborhood, BMI, meeting national recommendations for physical activity levels, or depression history (P>.05 for all). Of interest, 67.8% (129/190) of participants agreed that they and their friends were likely to use the robot to help them exercise. CONCLUSIONS: This preliminary study found that among a racially and socioeconomically diverse group of adolescents, robotic-assisted exercise coaching is likely acceptable. The finding that all demographic groups represented had similarly high receptivity to the robotic human exercise trainer is encouraging for ultimate considerations of intervention scalability and reach among diverse adolescent populations. Next steps will be to evaluate consumer preferences for robotic-assisted exercise coaching (eg, location, duration, supervised or structured, choice of exercise, and/or lifestyle activity focus), develop the treatment protocol, and evaluate feasibility and consumer uptake of the intervention among diverse youth.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".