Related Experiment Video
Updated: Jun 25, 2026

Movement Retraining using Real-time Feedback of Performance
Published on: January 17, 2013
Shared Strides: Community-based, high-throughput biomechanics data collection in knee osteoarthritis
Jenna M Qualter1, Ryan C McCloskey2, Kathryn A Stofer3
1Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA.
Objective:
This analysis assessed the acceptability and recruitment implications of a high-throughput, community-based biomechanics protocol among individuals with knee osteoarthritis (OA).
Design:
During the Shared Strides Study, high-throughput markerless biomechanics assessment was conducted at community sites to help facilitate research engagement in the OA population. In this cross-sectional study, biomechanics data during a set of activities of daily living (ADLs) and questionnaire data were collected. Adults aged 40 years or older with knee OA participated at one of four sites across Gainesville, FL-two on-campus and two community-based. Eligible individuals were either screened over the phone and scheduled for a specific date and time or screened on site for potential same-day participation. Participant acceptability of the community-based biomechanics data collection approach was assessed using a 15-item custom questionnaire. Recruitment characteristics and participant preferences were compared across sites.
Results:
The high-throughput community-based data collection approach was well received. Compared with on-campus sites, community-based sites had higher engagement from walk-in participants and new research participants (40% of the sample). Familiarity with, and distance to, a data collection site were important factors in research engagement in this population. No differences in demographic characteristics existed between sites (p > 0.05), but recruitment resulted in a large sample size (n = 85) likely representative of the communities surrounding the selected sites.
Conclusions:
Integrating markerless motion capture with a community-based research approach may enhance the participant experience and facilitate larger, more heterogeneous sample sizes, ultimately reducing bias and homogeneity in current OA biomechanics research.

