Objective. As technology continues to improve, it plays an increasingly vital role in the practice of medicine. This study aimed to assess the feasibility of the implementation of virtual reality (VR) in a rheumatology clinic as a platform to administer guided meditation and biofeedback as a means of reducing chronic pain.Methods. Twenty participants were recruited from a rheumatology clinic. These participants included adults with physician-diagnosed autoimmune disorders who were on a stable regimen of medication and had a score of at least 5 on the pain Visual Analog Scale (VAS) for a minimum of 4 days during the prior 30 days. VAS, part of most composite outcome measurements in rheumatology, is an instrument used to assess pain that consists of a straight line with the endpoints ranging from "no pain at all" and "pain as bad as it could be." Patients were randomized into two groups that differed in the order in which they experienced the two VR modules. One module consisted of a guided meditation (GM) environment, whereas the other module consisted of a respiratory biofeedback (BFD) environment. Data on pain and anxiety levels were gathered before, during, and after the two modules.Results. The three most common diagnoses among participants were rheumatoid arthiritis (RA), lupus, and fibromyalgia. There was a significant reduction in VAS scores after BFD and GM (P values = 0.01 and 0.04, respectively). There was a significant reduction in Facial Anxiety Scale after the GM compared with the BFD (P values = 0.02 and 0.08, respectively).Conclusion. This novel study demonstrated that VR could be a feasible solution for the management of pain and anxiety in rheumatology patients. Further trials with varying treatment exposures and durations are required to solidify the viability of VR as a treatment option in rheumatology clinics.
Objective The number of therapies for axial spondyloarthritis (axSpA) is increasing. Thus, it has become more challenging for patients and physicians to navigate the risk‐benefit profiles of the various treatment options. In this study, we used conjoint analysis—a form of trade‐off analysis that elucidates how people make complex decisions by balancing competing factors—to examine patient decision‐making surrounding medication options for axSpA. Methods We conducted an adaptive choice‐based conjoint analysis survey for patients with axSpA to assess the relative importance of medication attributes (eg, chance of symptom improvement, risk of side effects, route of administration, etc) in their decision‐making. We also performed logistic regression to explore whether patient demographics and disease characteristics predicted decision‐making. Results Overall, 397 patients with axSpA completed the conjoint analysis survey. Patients prioritized medication efficacy (importance score 26.8%), cost (26.3%), and route of administration (13.9%) as most important in their decision‐making. These were followed by risk of lymphoma (9.5%), dosing frequency (7.2%), risk of serious infection (6.0%), tolerability of side effects (5.3%), and clinic visit and laboratory test frequency (4.8%). In regression analyses, there were few significant associations between patients’ treatment preferences and sociodemographic and axSpA characteristics. Conclusions Treatment decision‐making in axSpA is highly individualized, and demographics and baseline disease characteristics are poor predictors of individual preferences. This calls for the development of online shared decision‐making tools for patients and providers, with the goal of selecting a treatment that is consistent with patients’ preferences.
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