Factors Associated with Patient Willingness to Conduct a Remote Video Musculoskeletal Consultation

Document Type : RESEARCH PAPER


1 Dell Medical School Austin, The University of Texas at Austin, TX, USA

2 Leiden University Medical Center, The Netherlands


Background: Remote video consultations on musculoskeletal illness are relatively convenient and accessible,
and use fewer resources. However, there are concerns about technological and privacy issues, the possibility of
missing something important, and equal access to all patients. We measured patient characteristics associated with
willingness to conduct a remote video musculoskeletal upper extremity consultation.
Methods: One hundred and five patients seeking specialty musculoskeletal care completed questionnaires
addressing (1) demographics, (2) access to a device, internet, and space to conduct a remote video consultation,
(3) health literacy, (4) pain intensity, (5) magnitude of limitations of the upper extremity, (6) self-efficacy, and (7)
rated willingness to conduct a remote video musculoskeletal consultation (11-point ordinal scale). A multivariable
linear regression analysis sought factors independently associated with patient willingness to conduct remote video
musculoskeletal upper extremity consultations.
Results: Patient education level (4 years of college) and accessibility to a space suitable for remote video consultations
were independently associated with interest in remote video consultations. Sociodemographic factors, health literacy,
accessibility to a device or internet, and amount of perceived pain and disability were not.
Conclusion: We speculate that education level and suitable space might be surrogates for trust and privacy concerns.
Future research might measure the ability of interventions to gain trust and ensure privacy to increase willingness to
engage in remote video musculoskeletal consultations.
Level of evidence: II


1. Wan AC, Gul Y, Darzi A. Realtime remote consultation
in the outpatient clinic—experience at a teaching
hospital. Journal of Telemedicine and Telecare. 1999;
2. Jayaram PR, Bhattacharyya R, Jenkins PJ, Anthony I,
Rymaszewski LA. A new “virtual” patient pathway for
the management of radial head and neck fractures.
Journal of Shoulder and Elbow Surgery. 2014;
3. Bhattacharyya R, Jayaram PR, Holliday R, Jenkins P,
Anthony I, Rymaszewski L. The virtual fracture clinic:
reducing unnecessary review of clavicle fractures.
Injury. 2017; 48(3):720-3.
4. O’Connor S, Hanlon P, O’Donnell CA, Garcia S, Glanville
J, Mair FS. Understanding factors affecting patient and
public engagement and recruitment to digital health
interventions: a systematic review of qualitative 
studies. BMC medical informatics and decision
making. 2016; 16(1):120.
5. Kontos E, Blake KD, Chou WY, Prestin A. Predictors
of eHealth usage: insights on the digital divide from
the Health Information National Trends Survey
2012. Journal of medical Internet research. 2014;
6. Hesse BW, Nelson DE, Kreps GL, Croyle RT, Arora NK,
Rimer BK, et al. Trust and sources of health information:
the impact of the Internet and its implications for
health care providers: findings from the first Health
Information National Trends Survey. Archives of
internal medicine. 2005; 165(22):2618-24.
7. Weiss BD, Mays MZ, Martz W, Castro KM, DeWalt
DA, Pignone MP, et al. Quick assessment of literacy
in primary care: the newest vital sign. The Annals of
Family Medicine. 2005; 3(6):514-22.
8. Gruber-Baldini AL, Velozo C, Romero S, Shulman LM.
Validation of the PROMIS® measures of self-efficacy
for managing chronic conditions. Quality of Life
Research. 2017; 26(7):1915-24.
9. Kaat AJ, Rothrock NE, Vrahas MS, O’Toole RV, Buono
SK, Zerhusen Jr T, et al. Longitudinal validation of
the PROMIS physical function item bank in upper
extremity trauma. Journal of orthopaedic trauma.
2017; 31(10):e321-6.
10. Spooner KK, Salemi JL, Salihu HM, Zoorob RJ. eHealth
patient-provider communication in the United States:
interest, inequalities, and predictors. Journal of the
American Medical Informatics Association. 2017;
11. Ellison LM, Pinto PA, Kim F, Ong AM, Patriciu A,
Stoianovici D, et al. Telerounding and patient
satisfaction after surgery. Journal of the American
College of Surgeons. 2004; 199(4):523-30.
12. Sharareh B, Schwarzkopf R. Effectiveness of
telemedical applications in postoperative followup
after total joint arthroplasty. The Journal of
arthroplasty. 2014; 29(5):918-22.
13. Ancker JS, Hafeez B, Kaushal R. Socioeconomic
disparities in adoption of personal health records
over time. The American journal of managed care.
2016; 22(8):539.
14. Gordon NP, Hornbrook MC. Differences in access to
and preferences for using patient portals and other
eHealth technologies based on race, ethnicity, and
age: a database and survey study of seniors in a large
health plan. Journal of medical Internet research.
2016; 18(3):e50.
15. Smith SG, O’Conor R, Aitken W, Curtis LM, Wolf MS,
Goel MS. Disparities in registration and use of an
online patient portal among older adults: findings
from the LitCog cohort. Journal of the American
Medical Informatics Association. 2015; 22(4):888-95.
16. Yamin CK, Emani S, Williams DH, Lipsitz SR, Karson
AS, Wald JS, et al. The digital divide in adoption and
use of a personal health record. Archives of internal
medicine. 2011; 171(6):568-74.
17. De Rosis S, Barsanti S. Patient satisfaction, e-health
and the evolution of the patient–general practitioner
relationship: Evidence from an Italian survey. Health
Policy. 2016; 120(11):1279-92.
18. Woods SS, Forsberg CW, Schwartz EC, Nazi KM,
Hibbard JH, Houston TK, et al. The association of
patient factors, digital access, and online behavior on
sustained patient portal use: a prospective cohort of
enrolled users. Journal of medical Internet research.
2017; 19(10):e345.
Volume 8, Issue 6
November and December 2020
Pages 656-660
  • Receive Date: 04 May 2019
  • Revise Date: 03 January 2020
  • Accept Date: 19 January 2020
  • First Publish Date: 01 November 2020