Evidence map›Paper›PMID 41929332›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Shared Strides: Community-based, high-throughput biomechanics data collection in knee osteoarthritis.

Jenna M Qualter, Ryan C McCloskey, Kathryn A Stofer, Peihua Qiu, Zibo Tian, Heather K Vincent, Kerry E Costello

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jenna M QualterDepartment of Biomedical Engineering, University of Florida, Gainesville, FL, USA.ORCID 0009-0005-3096-899X
Ryan C McCloskeyDepartment of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, USA.ORCID 0009-0007-3563-3704
Kathryn A StoferDepartment of Agricultural Education and Communication, University of Florida, Gainesville, FL, USA.ORCID 0000-0002-3659-490X
Peihua QiuDepartment of Biostatistics, University of Florida, Gainesville, FL, USA.ORCID 0000-0003-4439-9466
Zibo TianDepartment of Biostatistics, University of Florida, Gainesville, FL, USA.ORCID 0000-0003-0826-6498
Heather K VincentUnited States Olympic and Paralympic Committee, Colorado Springs, CO, USA.ORCID 0000-0003-2177-1683
Kerry E CostelloDepartment of Biomedical Engineering, University of Florida, Gainesville, FL, USA.ORCID 0000-0002-5928-1471

Funding

Using social networks to map and evaluate team science across CTSA hubsUL1TR001427 · NCATS · UNIVERSITY OF FLORIDA · PI MITCHELL, DUANE A. · 2015 to 2024
$37.2M
University of Florida Older Americans Independence Center (OAIC)P30AG028740 · NIA · UNIVERSITY OF FLORIDA · PI Stephen D Anton · 2007 to 2026
$22.8M
NCATS NIH HHS UL1 TR001427NIA NIH HHS P30 AG028740
6 · The paper itself

Abstract

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.

Indexed as

acceptabilityactivities of daily livingfirst-time research participantsmarkerless motion captureresearch accessibilitywalk-in recruitment

Identifiers

PMID41929332
PMCPMC13042141

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.