Background
Immersive virtual reality (IVR) presents new possibilities for application in health care. Health care professionals can now immerse their patients in environments to achieve exposure to a specific scene or experience, evoke targeted emotional responses, inspire, or distract from an experience occurring in reality.
Objective
This review aimed to identify patient-focused applications for head-mounted IVR for acute treatment of health conditions and determine the technical specifications of the systems used.
Methods
A systematic review was conducted by searching medical and engineering peer-reviewed literature databases in 2018. The databases included PubMed, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Association for Computing Machinery, Institute of Electrical and Electronics Engineers, Scopus, and Web of Science. Search terms relating to health and IVR were used. To be included, studies had to investigate the effectiveness of IVR for acute treatment of a specific health condition. IVR was defined as a head-mounted platform that provides virtual and auditory immersion for the participant and includes a minimum of 3 degrees of orientation tracking. Once identified, data were extracted from articles and aggregated in a narrative review format.
Results
A total of 58 studies were conducted in 19 countries. The studies reported IVR use for 5 main clinical areas: neurological and development (n=10), pain reduction through distraction (n=20), exposure therapy for phobias (n=9), psychological applications (n=14), and others (n=5). Studies were primarily feasibility studies exploring systems and general user acceptance (n=29) and efficacy studies testing clinical effect (n=28).
Conclusions
IVR has a promising future in health care, both in research and commercial realms. As many of the studies examined are still exploring the feasibility of IVR for acute treatment of health conditions, evidence for the effectiveness of IVR is still developing.
This brief editorial describes an emerging area of machine learning technology called large language models (LLMs). LLMs, such as ChatGPT, are the technological disruptor of this decade. They are going to be integrated into search engines (Bing and Google) and into Microsoft products in the coming months. They will therefore fundamentally change the way patients and clinicians access and receive information. It is essential that telehealth clinicians are aware of LLMs and appreciate their capabilities and limitations.
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