Developing a VR Training Program for Geriatric Patients with Chronic Back Pain: A Process Analysis

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Abstract

Back pain is increasing with age. Current studies have shown positive effects of virtual reality (VR) interventions for patients with neuropsychiatric diseases such as anxiety and chronic pain. However, little is known about the use of VR by geriatric patients with chronic back pain. This study was conducted as part of the research project “ViRST” (virtual reality for pain therapy). This approach intends to provide a new non-pharmacological therapy concept. The aim of this study was to learn more about the administrative efforts and business goals of physiotherapeutic and psychotherapeutic institutions. Additionally, we wanted to identify daily strategies of geriatric patients for dealing with their back pain to identify current therapies and possible training programs for VR. A process analysis with two physiotherapists and two psychotherapists in an executive position of a hospital and rehabilitation center was conducted. All interviews were performed according to a semi-structured guideline. The data were analyzed to the principles of systematic structured content analysis by Mayring using a data analysis program. Regarding multimorbidity and in contrast to the psychotherapists, the physiotherapists recommended an individual therapy for back pain at patients’ homes. Regardless, the VR system should support geriatric users by complementing long-term postural correction and muscular strengthening to prevent fear-avoidance behavior. In terms of everyday practice, interventions for the VR treatment of back pain problems in geriatric patients are rarely implemented. Nevertheless, for most of the interviewees the back pain training via VR under the instruction of competent therapists was conceivable at patients’ homes.

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Dahms, R., Stamm, O., & Müller-Werdan, U. (2019). Developing a VR Training Program for Geriatric Patients with Chronic Back Pain: A Process Analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11575 LNCS, pp. 243–255). Springer Verlag. https://doi.org/10.1007/978-3-030-21565-1_16

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