Chronic musculoskeletal pain is associated with significant psychosocial difficulties. Unfortunately, patients and medical providers find it difficult to discuss psychosocial factors, and these often remain unaddressed during the medical visit. The goal of the proposed application is to develop next-generation Virtual Human-assisted therapeutic interviews that can be integrated in current pain practice to engage patients in a conversation about psychosocial problems associated with their chronic pain. Virtual Humans (VHs) are computer-animated characters that mimic the appearance and behavior of a real person and that can be used as virtual interviewers. This novel technology also makes it possible to implement different experimental conditions with a great degree of standardization, thereby enhancing internal validity and reproducibility, while maintaining a high level of authenticity. Our team?s existing VH prototype has been successfully used to elicit self-disclosure. We propose to adapt our VH for use in patients with chronic pain in preparation for a subsequent large-scale clinical trial. In Phase 1 of the application, we will develop VH-assisted psychosocial interviews specifically for chronic pain. They will address two theoretically important yet divergent targets of communication: (1) psychosocial consequences resulting from the experience of chronic pain (e.g., depression, relationship disruption); and (2) possible psychosocial contributors that may trigger, exacerbate, or maintain chronic pain (e.g., background stressful events, pain attributions). Development of the VH-assisted psychosocial interviews will be guided by prior research on emotion-focused treatment, our extensive clinical expertise, and qualitative feedback from patient stakeholders. In Phase 2, we will bring our VH into the clinic and conduct preliminary feasibility and efficacy testing. Patients will be randomly assigned to one of four experimental conditions in a 2 x 2 factorial design, in which the VH will address (a) psychosocial consequences of chronic pain, (b) psychosocial contributors to chronic pain, (c) a combination of both, or (d) neither (attention control group). All patients will engage in a single VH interview session before their initial medical consultation. Feasibility will be established through participation rates, potential patient concerns about discussing psychosocial stressors with the VH, clinic flow, and stakeholder satisfaction. Based on existing theoretical frameworks, we expect that the VH sessions will impact patient outcomes through improved patient emotion regulation, working memory, and patient-provider relations; shifts in pain attitudes, and increased motivation for behavioral pain management. The pilot data collected in this application will provide essential preliminary information on the therapeutic mechanisms and patient health benefits of the VH-assisted communication approaches. This proposal is expected to be impactful because it 1) utilizes novel yet promising next-generation VH methodology; 2) tests theories and advances practice about how patients? psychosocial problems related to pain should be addressed in pain management; and 3) examines the feasibility and clinical utility of integrating VHs into pain care.

Public Health Relevance

/Relevance Chronic musculoskeletal pain is associated with significant psychosocial difficulties that often remain unaddressed in routine clinical care. The proposed application will develop next-generation Virtual Human (VH) interviewers to talk with patients about psychosocial problems associated with their chronic pain and pilot test whether it is feasible and clinically helpful to integrate VHs in chronic pain management for patients? disclosure of stress and negative emotion.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21AR074020-02
Application #
9776205
Study Section
Behavioral Medicine, Interventions and Outcomes Study Section (BMIO)
Program Officer
Wang, Yan Z
Project Start
2018-09-07
Project End
2021-06-30
Budget Start
2019-07-01
Budget End
2021-06-30
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Southern California
Department
Social Sciences
Type
Schools of Arts and Sciences
DUNS #
072933393
City
Los Angeles
State
CA
Country
United States
Zip Code
90089