Cited by 372Virtual Reality Applications and ImpactsDigital Mental Health InterventionsStatistical Methods in Clinical Trials

Recommendations for Methodology of Virtual Reality Clinical Trials in Health Care by an International Working Group: Iterative Study

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Birckhead, Brandon, Khalil, Carine, Liu, Xiaoyu, Conovitz, Samuel, Rizzo, Albert, Danovitch, Itai, Bullock, Kim, Spiegel, Brennan·2019·JMIR Mental Health

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Abstract

BACKGROUND: Therapeutic virtual reality (VR) has emerged as an efficacious treatment modality for a wide range of health conditions. However, despite encouraging outcomes from early stage research, a consensus for the best way to develop and evaluate VR treatments within a scientific framework is needed. OBJECTIVE: We aimed to develop a methodological framework with input from an international working group in order to guide the design, implementation, analysis, interpretation, and communication of trials that develop and test VR treatments. METHODS: A group of 21 international experts was recruited based on their contributions to the VR literature. The resulting Virtual Reality Clinical Outcomes Research Experts held iterative meetings to seek consensus on best practices for the development and testing of VR treatments. RESULTS: The interactions were transcribed, and key themes were identified to develop a scientific framework in order to support best practices in methodology of clinical VR trials. Using the Food and Drug Administration Phase I-III pharmacotherapy model as guidance, a framework emerged to support three phases of VR clinical study designs-VR1, VR2, and VR3. VR1 studies focus on content development by working with patients and providers through the principles of human-centered design. VR2 trials conduct early testing with a focus on feasibility, acceptability, tolerability, and initial clinical efficacy. VR3 trials are randomized, controlled studies that evaluate efficacy against a control condition. Best practice recommendations for each trial were provided. CONCLUSIONS: Patients, providers, payers, and regulators should consider this best practice framework when assessing the validity of VR treatments.

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  • These frameworks ensure coherency and effectiveness by addressing the methodological heterogeneity described by Birckhead.

    “These frameworks ensure more than just the coherency and effectiveness of the systems developed by addressing the current methodological Wild West, as Birckhead refers to the subjective role of researchers pursuing the same outcomes in very different ways [134].”
  • Their application in IMT research is essential for producing reliable and applicable results, particularly in mental health.

    “Their application in IMT research is essential for producing reliable and applicable results, particularly in the intricate mental health field [56].”

    From Immersive technologies for depression care: scoping review (2024) · cites this paper as [56]

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Authors
Birckhead, B., Khalil, C., Liu, X., Conovitz, S., Rizzo, A., Danovitch, I., Bullock, K., & Spiegel, B.
Affiliations
  • Cedars-Sinai Medical Center (US)
  • University of Southern California (US)
  • Stanford Medicine (US)
Corresponding author
Spiegel, Brennan
Venue
JMIR Mental Health
Published
2019-01-31
Volume
6
Issue
1
Pages
e11973
ISSN
2368-7959 (ISSN-L)
OpenAlex
W2896422961
Cited by
372
References
85
Citations by year
2026: 49 · 2025: 68 · 2024: 67 · 2023: 50 · 2022: 49 · 2021: 48 · 2020: 30 · 2019: 11
FWCI
22.13
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR Mental Health (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Human-Computer Interaction › Virtual Reality Applications and Impacts
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Keywords
clinical trial design, human-centered design, feasibility and acceptability, randomized controlled trials, expert consensus

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