Evidence map›Paper›PMID 39922109›Full record

ArticleJournal of biomechanics2025

Evaluating recruitment methods for selection bias: A large, experimental study of hand biomechanics.

Maximillian T Diaz, Lavanya Durai, Kalyn M Kearney, Erica M Lindbeck, Isaly Tappan, Joel B Harley, Jennifer A Nichols

Abstract read
In one paragraph

Article in Journal of biomechanics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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.

Maximillian T DiazJ. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States.
Lavanya DuraiJ. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States.
Kalyn M KearneyJ. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States.
Erica M LindbeckDepartment of Electrical & Computer Engineering, University of Florida, Gainesville, FL, United States.
Isaly TappanDepartment of Electrical & Computer Engineering, University of Florida, Gainesville, FL, United States.
Joel B HarleyDepartment of Electrical & Computer Engineering, University of Florida, Gainesville, FL, United States.
Jennifer A NicholsJ. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States. Electronic address: jnichols@bme.ufl.edu.

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
A Transfer Learning Framework for Creating Subject-Specific Musculoskeletal Models of the HandR21EB030068 · NIBIB · UNIVERSITY OF FLORIDA · PI NICHOLS, JENNIFER A. · 2020 to 2020
$561k
NCATS NIH HHS UL1 TR001427NIBIB NIH HHS R21 EB030068NSF 1842473
6 · The paper itself

Abstract

Biomechanics studies rely on non-random recruitment methods to obtain study participants. However, the use of common recruitment methods and small sample sizes may influence a given study's generalizability due to selection bias. To improve generalizability, ecological validity, and participant convenience, recent biomechanics studies have moved beyond lab conditions. However, it is unknown if simply leaving the lab space and increasing sample sizes reduces the risks associated with selection bias. Previous studies relied on chart and literature reviews to identify selection bias. Herein, we build upon this work by exploring the potential for and influence of selection bias in three common recruiting methods by performing an experimental, population-level study on hand biomechanics. Hand biomechanics was assessed in the community using a portable lab setup to measure hand function, grip strength, and pinch strength. A total of 642 apparently healthy participants were recruited across 18 locations, with 426 participants selected based on complete data responses and being between the ages of 18 to 35. Sex stratified analysis was performed to see how recruiting only biomechanists, undergraduate students, or university affiliates changed population estimates of hand strength. The presence of selection bias was observed in all three test cases with both male and female biomechanists, graduate students, and non-university affiliates having significant increases in pinch and grip strengths ranging from 6.2% to 19.4% above overall population values. This study quantitively shows how simply leaving the lab and increasing subject recruitment does not eliminate the potential for selection bias in studies of hand biomechanics.

Indexed as

HandPatient SelectionAdolescentAdultBiomechanical PhenomenaFemaleHand StrengthHumansMaleSelection BiasYoung AdultForceGrip strengthLateral pinchSamplingThumb

Identifiers

PMID39922109
PMCPMC12233181

What OpenQuestion holds

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Registered trials

None linked

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.