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Virtual Reality Clinical Research: Promises and Challenges

2018· article· en· 256 citations· W2897877729 on OpenAlex· 10.2196/10839

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
Canadian venueIt was published in a Canadian venue.

Full frame distilled prediction

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.

Candidate categories
none
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Other designConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.865
Threshold uncertainty score
0.406
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

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.

Opus teacher head0.279
GPT teacher head0.454
Teacher spread
0.175 · how far apart the two teachers sit on this one work
Validation status
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

Abstract

BACKGROUND: Virtual reality (VR) therapy has been explored as a novel therapeutic approach for numerous health applications, in which three-dimensional virtual environments can be explored in real time. Studies have found positive outcomes for patients using VR for clinical conditions such as anxiety disorders, addictions, phobias, posttraumatic stress disorder, eating disorders, stroke rehabilitation, and for pain management. OBJECTIVE: This work aims to highlight key issues in the implementation of clinical research for VR technologies. METHODS: A discussion paper was developed from a narrative review of recent clinical research in the field, and the researchers' own experiences in conducting VR clinical research with chronic pain patients. RESULTS: Some of the key issues in implementing clinical VR research include theoretical immaturity, a lack of technical standards, the problems of separating effects of media versus medium, practical in vivo issues, and costs. CONCLUSIONS: Over the last decade, some significant successes have been claimed for the use of VR. Nevertheless, the implementation of clinical VR research outside of the laboratory presents substantial clinical challenges. It is argued that careful attention to addressing these issues in research design and pilot studies are needed in order to make clinical VR research more rigorous and improve the clinical significance of findings.

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.

The record

Venue
JMIR Serious Games
Topic
Virtual Reality Applications and Impacts
Field
Computer Science
Canadian institutions
Simon Fraser UniversityUniversity of British Columbia
Funders
not available
Keywords
Virtual realityPhobiasExposure therapyPsychologyClinical trialClinical researchAnxietyMedicinePsychotherapistComputer sciencePsychiatryHuman–computer interaction
Has abstract in OpenAlex
yes