Digital technologies are increasingly central to the future of mental health care. Among them, Virtual Reality (VR) has moved rapidly from experimental settings into real-world clinical settings offering immersive and scalable approaches to supporting wellbeing.
At the same time, demand for mental health support among individuals with attention deficit hyperactivity disorder (ADHD) and autism spectrum condition (ASC) continues to grow (1). Across the NHS, long waiting times for both diagnosis and post-diagnostic support for these populations highlights the need for new approaches that can provide timely, personalised and accessible care (2).
Responding to growing demand via innovative models of mental health support aligns closely with the NHS’s current strategic direction, including the shift towards delivering more care in community settings, focusing on preventative support and making greater use of digital technologies to improve access and efficiency (3). As these trends converge, immersive technologies such as VR are increasingly positioned as part of the solution, with a view that they can deliver flexible, engaging interventions at scale (4).
Early signals from practice support this view. TendVR, an organisation supported by Health Innovation East, delivers mindfulness-based cognitive interventions through VR Meta Quest headsets. Through routine service use, the TendVR team observed that a notable proportion of individuals engaging with their platform identified as neurodivergent.
TendVR is a digital mental health innovator delivering mindfulness-based cognitive therapy through immersive virtual reality headsets, providing users with access to evidence-based therapeutic techniques in a flexible and accessible format. TendVR aims to improve mental wellbeing at scale by increasing access to effective mental health support while reducing the resource demands associated with traditionally delivered therapy.
Such data prompts a deeper line of enquiry. If neurodivergent individuals are engaging disproportionately with immersive technologies, what is it about these environments that resonates with this population? Further, what might this tell us about how mental health support can be better designed for neurodivergent populations?
To explore these questions, Health Innovation East undertook a structured literature review, drawing on the organisation’s evaluation expertise to examine how neurodivergent people experience mental health interventions delivered through virtual reality.
Search terms and inclusion criteria were carefully developed and five major academic databases were searched, followed by a robust screening process including title and abstract review followed by full-text assessment.
Given the rapid growth of digital mental health products and immersive technologies, we expected to uncover a body of qualitative evidence offering insight into how neurodivergent individuals experience VR-based mental health interventions.
While qualitative research on VR and neurodiversity is growing, much of it focuses on educational applications, skills training or simulated social interactions, such as practising everyday conversations or preparing for job interviews. Other studies focused on the pre-emptive design of the VR environments or co-production, with limited follow-up on real-world user experience.
These approaches have merit but do not capture how individuals experience VR-based mental health interventions, nor do they explain the mechanisms through which they may support engagement, emotional regulation or therapeutic benefit. Without this understanding, it becomes difficult to refine existing approaches or design interventions better tailored to neurodivergent populations.
Despite the limited evidence base we uncovered, several useful themes emerged (6,7).
Overall, the findings suggest that VR may be effective not because it delivers therapy differently, but because it changes the conditions under which individuals are able to engage with it. However, while these insights are valuable, they are drawn from an extremely limited evidence base and point to a critical gap in the research that needs to be addressed.
The evidence gap has not emerged by accident, but as a product of how research in this space is currently structured.
Much of the existing evidence is shaped by academic systems, where studies are often conducted by research students operating within fixed timelines. These constraints make it difficult to design, deliver and evaluate VR-based mental health interventions, while also capturing rich qualitative follow-up data. Such data typically require a longer and more resource-intensive analysis phase than quantitative approaches.
Ethical requirements, particularly when working with neurodivergent populations in clinical contexts, are essential. However, they can further constrain recruitment, study duration and the depth of data collected in academic settings.
A broader preference for quantitative evidence has also shaped the field. Outcome measures and effect sizes are often prioritised for their perceived generalisability, while qualitative approaches, which are typically more resource-intensive and complex to analyse, remain comparatively underutilised. However, this has long been recognised as a systemic limitation within healthcare research. Whilst quantitative approaches are invaluable for establishing efficacy and measurable outcomes, they may offer an inherently reductive account of intervention impact when used in isolation. Scholars have argued that overreliance on quantitative metrics can obscure the contextual, experiential, and process-driven insights afforded by qualitative enquiry, despite these factors often being central to understanding how and why interventions succeed in real-world settings (9,10,11).
At the same time, research funding and design have tended to prioritise paediatric populations and measurable clinical outcomes. This has led to a reliance on proxy accounts, such as parental reporting and a focus on evidencing symptom reduction rather than lived experience. While valuable, these approaches offer only a partial view, particularly when exploring how individuals engage with and make meaning from clinical content delivered through experiential environments.
Finally, much VR research has focused on skills training or behaviour change, often oriented towards social performance or adaptation. This emphasis risks overlooking the value of VR as a space for autonomy, regulation and authentic engagement with clinical content for neurodivergent individuals. As a result, we gain insight into whether interventions have an effect, but far less understanding of how or why they work, which is essential for refining interventions and improving outcomes over time.
If VR and other digital technologies are to play a meaningful role in the future of mental health care, we must move beyond asking whether they work and start understanding how and why they work, for whom and in what contexts.
Quantitative measures of clinical effectiveness will remain essential. However, without first-hand qualitative insight into how neurodivergent individuals experience these interventions, we risk scaling solutions without fully understanding the mechanisms that drive engagement, trust, and meaningful change. Addressing this systemic gap in research practice will be critical to designing and implementing interventions capable of delivering meaningful impact at scale.
A step change in qualitative insight requires a shift in how immersive VR mental health interventions are evaluated. Qualitative insight must be embedded alongside clinical outcomes, with greater emphasis on lived experience, co-design and longitudinal follow-up. Each are factors that are particularly critical for adult populations, whose perspectives remain underrepresented.
No single organisation can address this. Innovators, health systems, and research partners must work together to bridge the gap between development and real-world understanding. Partnerships with organisations equipped to deliver robust, experience-led evaluation will be essential.
VR holds significant promise as a scalable, preventative tool. Realising that promise depends on our ability to understand, and not just measure, its impact.
To contribute to the conversation and understand more about Health Innovation East’s work contact evaluation@healthinnovationeast.co.uk
Christopher Chrzanowski, Trainee Clinical Psychologist – Health Innovation East
Oliver Brenton, Psychology graduate placement, Health Innovation East
Dr Sarah Robinson, Director of Health Partnerships and Insights – Health Innovation East
References
(1) Department of Health and Social Care. (2025). Review launched into mental health, ADHD and autism services. UK. https://www.gov.uk/government/news/review-launched-into-mental-health-autism-and-adhd-services.
(2) Maciver D, Roy AS, Johnston L, Boilson M, Curnow E, Johnstone‐Cooke V, et al. Waiting Times and Influencing Factors in Children and Adults Undergoing Assessment for Autism, ADHD, and Other Neurodevelopmental Differences. Autism Res. 2025 Apr;18(4):788–801. doi:10.1002/aur.70011 PubMed PMID: 39994914; PubMed Central PMCID: PMC12015800.
(3) UK Government. UK Government. Fit for the future: 10 year health plan for England. 2025. [Internet]. London: Department of Health and Social Care; 2025 Jun. Report No.: CP 1350. Available from: https://assets.publishing.service.gov.uk/media/6866387fe6557c544c74db7a/fit-for-the-future-10-year-health-plan-for-england.pdf.
(4) Torous J, Linardon J, Goldberg SB, Sun S, Bell I, Nicholas J, et al. The evolving field of digital mental health: current evidence and implementation issues for smartphone apps, generative artificial intelligence, and virtual reality. World Psychiatry. 2025 Jun;24(2):156–74. doi:10.1002/wps.21299 PubMed PMID: 40371757; PubMed Central PMCID: PMC12079407.
(5) Skiers K, Pai YS, Nakagawa M, Minamizawa K, Barbareschi G. Portable Silent Room: Exploring VR Design for Anxiety and Emotion Regulation for Neurodivergent Women and Non-Binary Individuals. IEEE trans vis comput graph. 2025;31(11):9625–35. Located at: Ovid MEDLINE(R). doi:10.1109/TVCG.2025.3616828.
(6) Glaser N. The development and evaluation of a virtual reality intervention for adults with autism: A design-based research study. Dissertation Abstracts International Section A: Humanities and Social Sciences [Internet]. ProQuest Information & Learning; 2021. Located at: APA PsycInfo; 2020-97491-066. Available from: https://research.ebsco.com/plink/5d26b443-dca4-343b-bd52-1619d4e76c61.
(7) Schmidt M, Lu JJ, Glaser N, Gluck MC, Li SE, Weng Y, et al. Aligning XR Research with Autistic Priorities and Lived Experiences: Insights from the Project PHoENIX Study. J Autism Dev Disord. 2025;(7904301, hgw). Located at: Ovid MEDLINE(R) Epub Ahead of Print. doi:10.1007/s10803-025-07023-3.
(8) Adams, D., & Young, K. (2021). A systematic review of the perceived barriers and facilitators to accessing psychological treatment for mental health problems in individuals on the autism spectrum. Review Journal of Autism and Developmental Disorders, 8, 436–453. https://doi.org/10.1007/s40489-020-00226-7.
(9) Green, J., & Britten, N. (1998). Qualitative research and evidence based medicine. BMJ, 316(7139), 1230–1232. https://doi.org/10.1136/bmj.316.7139.1230.
(10) Grypdonck, M. H. F. (2006). Qualitative health research in the era of evidence-based practice. Qualitative Health Research, 16(10), 1371–1385. https://doi.org/10.1177/1049732306294089.
(11) Noyes, J., Booth, A., Cargo, M., Flemming, K., Harden, A., Harris, J., Garside, R., Hannes, K., Pantoja, T., & Thomas, J. (2019). Chapter 21: Qualitative evidence. In J. P. T. Higgins et al. (Eds.), Cochrane handbook for systematic reviews of interventions (2nd ed., pp. 525–545). Wiley.
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