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The influence of patient race, sex, pain-related body postures, and anxiety status on pain management: a virtual human technology investigation

Authors Clark J, Robinson ME

Received 21 March 2019

Accepted for publication 2 August 2019

Published 30 August 2019 Volume 2019:12 Pages 2637—2650


Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 2

Editor who approved publication: Dr Michael A Überall

Jaylyn Clark, Michael E Robinson

Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA

Correspondence: Michael E Robinson
Department of Clinical and Health Psychology, University of Florida, 101 South Newell Drive, Rm 3151, PO Box 100165, Gainesville, FL 32610-9165, USA
Tel +1 352 273 5220
Fax +1 352 273 6156

Purpose: The purpose of this study was to examine mechanisms underlying disparities in pain management among patients with psychological comorbidities. Studies have consistently shown that health care providers, health care trainees, and laypeople are susceptible to biased assessment and treatment decisions for patients presenting with pain. Further, psychological factors may influence the use of demographic and behavioral cues in pain assessment and treatment decisions. The present study employed innovative virtual human technology to capture decision-making approaches at both the group- and individual-level to better elucidate the influence of psychological factors, demographic cues, and pain-related body postures on pain assessment and treatment decisions.
Patients and methods: One hundred and thirty-two providers and trainees in the areas of nursing, physical therapy, and medicine viewed separate, empirically validated virtual human profiles that systematically varied across pain behaviors, anxiety status, race, and sex. Participants provided pain assessment and treatment ratings using a visual analog scale for each virtual human profile.
Results: Idiographic analyses revealed that participants used patient pain-related body postures most consistently and reliably across ratings. Nomothetic analyses showed anxious virtual humans were identified as having more anxiety and more likely to be recommended anti-anxiety medications, especially by female participants.
Conclusion: This innovative study successfully explored the influence of patient pain-related body postures, anxiety status, and demographic characteristics on pain management decisions with virtual human technology and a Lens model design. Results of this study can be used to better inform clinical practice, research, and education regarding the influence of patient variables on pain assessment and treatment decisions.

Keywords: pain management, disparities, demographic variables

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