Immersive Virtual Reality in Health Care: Systematic Review of Technology and Disease States
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it