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Extended reality and healthcare practitioner well-being: scoping review

Published online by Cambridge University Press:  24 September 2025

Holly Mould
Affiliation:
Aintree University Hospital, NHS University Hospitals of Liverpool Group, Liverpool, UK ExR Solutions Ltd, London, UK
Jonathan R. Abbas
Affiliation:
ExR Solutions Ltd, London, UK
Michael Loizou
Affiliation:
Centre for Health Technology, University of Plymouth, Plymouth, UK
Nick Culley
Affiliation:
ExR Solutions Ltd, London, UK
Sheena Asthana
Affiliation:
Centre for Health Technology, University of Plymouth, Plymouth, UK
Rohit Shankar
Affiliation:
Plymouth Medical School, University of Plymouth, Plymouth, UK Cornwall Intellectual Disability Equitable Research, Cornwall Partnership NHS Foundation Trust, Truro, UK
John Downey*
Affiliation:
Centre for Health Technology, University of Plymouth, Plymouth, UK
*
Correspondence: John Downey. Email: john.downey@plymouth.ac.uk
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Abstract

Background

Extended reality may offer a convenient and effective method of increasing well-being within the wider healthcare workforce and particularly for those working in the mental health sector who are subject to high levels of stress because of increased workload, high levels of staff turnover and limited resources.

Aims

This scoping review aims to identify and assimilate relevant literature pertaining to the use of extended reality to improve healthcare practitioners’ well-being.

Method

Databases (MEDLINE, CINAHL, Cochrane and PubMed) and grey literature were searched for relevant articles using established methodology and reported as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews.

Results

A total of 280 articles were yielded by the search strategy, with 13 relevant articles selected by two independent reviewers in a blinded process. Studies demonstrated a heterogenous pool of outcome measurement modalities, intervention modalities and duration and frequency of the interventions. Of all the studies, 85% note a positive impact on healthcare practitioner well-being but studies have limited comparability because of heterogeneity. Interventions were engaging but the practicality of implementing such technologies into a finance- and time-limited healthcare environment will be a challenge.

Conclusions

Whilst extended reality is a promising well-being intervention, there is a paucity of literature relating to its effect on mental health practitioners’ well-being, and further studies in this area are required.

Information

Type
Review
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of Royal College of Psychiatrists

Current staff shortages within the healthcare sector are higher than the national average for other sectors in England. 1 In particular, there is a shortfall in the capacity of the mental health workforce 1,Reference Brooker and Coid2 in a climate of rising numbers of mental health presentations to healthcare providers in the UK. 3 The mental health workforce experience high levels of work-related stress while having limited resources, Reference O’Connor, Muller Neff and Pitman4 coupled with high levels of staff turnover. Reference Shembavnekar and Kelly5 Indeed, high workloads, hindered quality of care, poor commitment to the organisation, lack of investment and feeling unable to contribute to organisational agendas precede staff departures. Reference Long, Ohlsen, Senek, Booth, Weich and Wood6

Workplace stress and staff burnout negatively affect the health of employees and patient safety, satisfaction and the quality of care. Reference Jun, Ojemeni, Kalamani, Tong and Crecelius7 Mental health workers undertake ‘psychologically hazardous’ work, Reference Walsh Sue8 and have higher levels of emotional exhaustion than other healthcare practitioners. Reference O’Connor, Muller Neff and Pitman4 The burnout experienced by mental health employees contributes to higher healthcare costs, with one in three mental health nurses experiencing burnout Reference O’Connor, Muller Neff and Pitman4 and staff burnout alone costing the National Health Service (NHS) up to £400 million annually. Reference Ravalier, McVicar and Boichat9 Community mental health employees experience greater levels of burnout than other specialities, Reference O’Connor, Muller Neff and Pitman4,Reference la Fuente GA, Vargas, San Luis, García, Cañadas and De la Fuente10 potentially because of longer hours on shift Reference Dall’ora, Ejebu, Ball and Griffiths11 or isolated working in the community. Reference O’Connor, Muller Neff and Pitman4

There is a body of evidence that interventions can support the well-being of staff, Reference Cohen, Pignata, Bezak, Tie and Childs12 but the implementation, heterogeneity, measurement of impact and theoretical underpinning are lacking. Practical, accessible and standardised approaches that can be translated into routine care easily are needed.

Virtual reality can be defined as ‘a three-dimensional computer-generated simulated environment, which attempts to replicate real world or imaginary environments and interactions, thereby supporting work, education, recreation, and health’. Reference Abbas, O.’Connor, Ganapathy, Isba, Payton and McGrath13 Extended reality may be used as an overarching term to encompass virtual reality, augmented reality and mixed reality. Reference Goldsworthy, Chawla, Baumann, Birt and Gough14 Augmented reality layers computer-generated objects over real physical objects, allowing the participant to interact with them. Reference Hantono, Nugroho and Santosa15 Mixed reality can be thought of more broadly as a blend of the real and virtual worlds. Reference O’Shiel16 Virtual reality and extended reality applications are emerging as a potential effective well-being strategy for employees. Reference Riches, Taylor, Jeyarajaguru, Veling and Valmaggia17 Applications of extended reality have proven to be effective in decreasing stress and increasing relaxation in the nascent literature. Reference Riches, Azevedo, Bird, Pisani and Valmaggia18,Reference Valmaggia, Latif, Kempton and Rus-Calafell19 Virtual reality applications are accessible, cheap and could be integrated into busy environments more easily than other interventions that involve greater resource and organisational burden, Reference Riches, Taylor, Jeyarajaguru, Veling and Valmaggia17,Reference Lee, Heo, Kim, Park, Jung and Ji20,Reference Weitzman, Wong, Worrall, Park, McKee and Tufts21 such as talking therapies or a timetabled well-being programme.

Previous systematic reviews have sought to evaluate the role of virtual reality and extended reality in workplace well-being more widely but have not focused specifically on mental health practitioners. Reference Riches, Taylor, Jeyarajaguru, Veling and Valmaggia17,Reference Lee, Heo, Kim, Park, Jung and Ji20,Reference Weitzman, Wong, Worrall, Park, McKee and Tufts21 This scoping review identifies and analyses the literature relevant to extended reality interventions to improve mental health professionals’ well-being. Because of the emerging nature of the extended reality well-being literature generally, diverse study designs and immature application for healthcare workers, a scoping review was conducted to identify the current knowledge base and map the field. Reference Munn, Peters, Stern, Tufanaru, McArthur and Aromataris22

Method

A scoping review was performed in five steps, in accordance with the methodology described by Arksey and O’Malley. Reference Arksey and O’Malley23

Identifying the research questions

First, the research questions were identified and formulated as follows:

  1. (a) What peer-reviewed research literature exists that examines the impact of virtual reality and extended reality on healthcare workers?

  2. (b) Which common themes can be derived from these studies?

  3. (c) To what extent is this research applicable to mental health practitioners?

  4. (d) What are the implications of these findings for next steps?

Identifying the relevant studies

Peer-reviewed articles containing the following terms in their title or abstract were included:

(wellbeing OR well-being OR well being OR quality of life OR wellness OR mental) AND (healthcare workers OR nurs* OR medical workers OR healthcare professionals OR staff) AND (virtual reality OR vr OR augmented reality OR extended reality OR gamification)

Given mixed reality has a broad definition, the authors elected not to include this in the search string because of the risk of inclusion of a wide variety of non-virtual interventions, which would be outside the remit of this scoping review.

Further inclusion criteria were formulated using the population, intervention, comparator and outcomes (PICO) framework, 24 whereby the population included healthcare professionals, the intervention was the use of extended reality and the outcome was a domain related to well-being, mood or stress. There was no comparator.

Exclusion criteria were articles not written in the English language, opinion pieces, studies in which technology was used for healthcare training purposes or with patients or students in the intervention group.

Articles were identified by searching the literature databases MEDLINE, CINAHL, Cochrane and PubMed. Grey literature was identified by searching these terms on Google Scholar and the King’s fund websites. To ensure that only the most recent advances in technology were included in the search, articles were excluded if they were older than ten years. Grey sources were used to identify peer-reviewed work that may have been missed within core databases, but did not include non-peer-reviewed work.

Study selection

Duplicates were removed with the use of Mendeley referencing software version 1.19.5 for Windows (Elsevier, London, UK; see https://www.mendeley.com), and the remaining articles underwent blind screening for relevance by two independent reviewers (H.M. and J.D.). Titles and abstracts were pasted into Windows Microsoft 365 Excel spreadsheets and the two reviewers independently gave a yes/no/maybe label and made a memo describing the decision. The respective Excel spreadsheets were then shared to check for agreement. The level of agreement was 82%, with four manuscripts leading to a conflict and three needing a further discussion, because of one reviewer having a ‘maybe’ decision. Conflicts were resolved by meeting to discuss the paper and cross-checking it with the inclusion criteria. Resolution was as followed: three papers were excluded as they were not about extended reality, one was excluded as the cohort was not relevant and one was a protocol design. One conflict was initially included, as upon discussion it met the criteria. A third reviewer was available (M.L.) if a mediator was needed, but this was not the case.

Charting the data

The lead author developed a data extraction framework and shared it with the team for feedback. A single data extraction process took place whereby prudent information from the included manuscripts were summarised in an Excel spreadsheet. As is suggested from guidance, where one scoping reviewer does the extraction, a proportion (50%) of the outputs were cross-checked by a second reviewer. Reference Robson, Pham, Hwee, Thomas, Rios and Page25 Included articles and their contents (authors, location, year, population, methods and sample results) are charted in Table 1.

Table 1 Descriptive information of the included articles

NHS, National Health Service.

Collating, summarising and reporting the results

Articles were collated and common themes were identified using content analysis by hand (H.M.). A deductive approach was undertaken where data from prudent mapping domains were used as categories of interest. Descriptive summaries were generated for the included papers and content was packaged together where similar or contrasting data were noted within the included manuscripts.

Results

A total of 280 articles were identified using the methodology above (see Fig. 1). As demonstrated in Fig. 1, duplicates (n = 107) were removed, and the remaining abstracts (n = 173) were screened for relevance. A total of seven relevant articles were identified, with a further two articles found through grey literature searches and four articles from snowballing. Therefore, a total of 13 studies describing primary research met the criteria for inclusion. Studies included healthcare professionals from a variety of countries and were based in a range of settings, with only one being specific to mental health settings. Reference Williams and Riches26 All studies examined the impact of extended reality interventions on healthcare professionals’ well-being; however, the intervention and outcome measurement modalities differed widely between studies. Two papers were not retrieved, and authors were not contacted as a means to source the papers.

Fig. 1 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart demonstrating the search strategy.

The common themes of these studies included the efficacy, feasibility and acceptability of interventions, alongside the associated financial and logistical considerations that should be considered to increase the engagement and impact of such interventions.

Intervention modality

Interventions took a variety of forms. Virtual reality was used as a standalone head-mounted device, Reference Williams and Riches26Reference Tarrant, Jackson and Viczko36 or with a smartphone placed on to the headset. Reference Weitzman, Wong, Worrall, Park, McKee and Tufts21 Virtual reality interventions included simulations, Reference Williams and Riches26,Reference Gaggioli, Pallavicini, Morganti, Serino, Scaratti and Briguglio31,Reference Adhyaru and Kemp32,Reference Michael, Villarreal, Ferguson, Wiler, Zane and Flarity37 360-degree videos, Reference Hayakawa, Barrows, See and Schomberg27,Reference Beverly, Hommema, Coates, Duncan, Gable and Gutman33,Reference Muir, Webb-Jones, Farish, Barker, Miller-Davis and Galloway34 or a combination of the two. Reference Pascual, Fredman, Naum, Patil and Sikka28,Reference Nijland, Veling, Lestestuiver and Van Driel35,Reference Tarrant, Jackson and Viczko36 The 360-degree videos were generally peaceful settings and included footage of beaches, mountains and forests Reference Hayakawa, Barrows, See and Schomberg27,Reference Pascual, Fredman, Naum, Patil and Sikka28,Reference Beverly, Hommema, Coates, Duncan, Gable and Gutman33Reference Tarrant, Jackson and Viczko36 ; they were accessed via a specific application Reference Beverly, Hommema, Coates, Duncan, Gable and Gutman33,Reference Nijland, Veling, Lestestuiver and Van Driel35,Reference Tarrant, Jackson and Viczko36 or through YouTube. Reference Muir, Webb-Jones, Farish, Barker, Miller-Davis and Galloway34 Three studies included virtual reality interventions that had some element of interaction, for example participants being able to plant trees Reference Adhyaru and Kemp32 or pop bubbles. Reference Williams and Riches26,Reference Nijland, Veling, Lestestuiver and Van Driel35 Two studies fed participants’ biodata into the simulation, which altered the appearance of the simulation. Reference Gaggioli, Pallavicini, Morganti, Serino, Scaratti and Briguglio31,Reference Tarrant, Jackson and Viczko36 Electroencephalogram (EEG) measurements correlating to brain activity were mapped onto a simulated firefly model, which moved below a threshold when the participant was thinking or stressed, and as such reminded participants to attempt to modulate their thoughts. Reference Tarrant, Jackson and Viczko36 Another study mapped heart rate to the intensity of the campfire, with the fire eventually extinguishing if the participant was sufficiently relaxed. Reference Gaggioli, Pallavicini, Morganti, Serino, Scaratti and Briguglio31

Intervention duration varied from 3 min Reference Beverly, Hommema, Coates, Duncan, Gable and Gutman33 to at least 10 min and details varied in the hardware used. Reference Weitzman, Wong, Worrall, Park, McKee and Tufts21,Reference Soh, Ong, Fan, Seah, Henderson and Doshi29,Reference Adhyaru and Kemp32,Reference Nijland, Veling, Lestestuiver and Van Driel35 Some studies allowed participants to engage with the intervention for as long as they saw fit, Reference Williams and Riches26,Reference Muir, Webb-Jones, Farish, Barker, Miller-Davis and Galloway34 whilst some interventions were given as one-off sessions. Reference Williams and Riches26,Reference Soh, Ong, Fan, Seah, Henderson and Doshi29,Reference Bodet-Contentin, Letourneur and Ehrmann30,Reference Beverly, Hommema, Coates, Duncan, Gable and Gutman33,Reference Nijland, Veling, Lestestuiver and Van Driel35,Reference Tarrant, Jackson and Viczko36 Alternatively, others were delivered at frequent intervals over a longer period of weeks or months. Reference Weitzman, Wong, Worrall, Park, McKee and Tufts21,Reference Hayakawa, Barrows, See and Schomberg27,Reference Pascual, Fredman, Naum, Patil and Sikka28,Reference Gaggioli, Pallavicini, Morganti, Serino, Scaratti and Briguglio31,Reference Adhyaru and Kemp32 Interventions were delivered in specific sessions, Reference Weitzman, Wong, Worrall, Park, McKee and Tufts21,Reference Williams and Riches26,Reference Soh, Ong, Fan, Seah, Henderson and Doshi29,Reference Gaggioli, Pallavicini, Morganti, Serino, Scaratti and Briguglio31,Reference Beverly, Hommema, Coates, Duncan, Gable and Gutman33,Reference Nijland, Veling, Lestestuiver and Van Driel35,Reference Tarrant, Jackson and Viczko36 during normal work breaks, Reference Hayakawa, Barrows, See and Schomberg27,Reference Bodet-Contentin, Letourneur and Ehrmann30,Reference Adhyaru and Kemp32 or were left in designated spaces for access whenever staff were available. Reference Pascual, Fredman, Naum, Patil and Sikka28,Reference Muir, Webb-Jones, Farish, Barker, Miller-Davis and Galloway34,Reference Michael, Villarreal, Ferguson, Wiler, Zane and Flarity37

Outcome measurement modalities

There are a wide variety of metrics used to measure well-being, stress, resilience, anxiety and depression, as shown in Fig. 2. Domains assessed by studies included resilience, burnout, depression, anxiety, stress, quality of life, mindfulness and quality of work. Metrics ranged from a simple scale where the participant indicated how far along the scale they agree with a sentiment in the Visual Analogue Scale (VAS) Reference Lesage and Berjot38,Reference Lesage, Berjot and Deschamps39 to the 22-item Maslach Burnout Inventory. Reference Maslach, Jackson, Leiter, Zalaquett and Wood40 In most articles, more than one metric was used to give a more rounded sense of participant well-being.

Fig. 2 Outcome measures of participant well-being used in the articles.

The metrics related to resilience and burnout were as follows: Connor–Davidson Resiliency Scale (measures resilience and ability to cope with stress); Reference Connor and Davidson41 Maslach Burnout Index (assesses burnout levels, concentrating on emotional exhaustion, depersonalisation and personal achievement); Reference Maslach, Jackson, Leiter, Zalaquett and Wood40 and the Coping Orientation to Problems Experienced (evaluates coping strategies used as a stress response). Reference Carver, Scheier and Weintraub42

Measurements of anxiety and depression utilised in the studies were as follows: the State-Trait Anxiety Inventory (this differentiates between temporary state anxiety and chronic trait anxiety); Reference Spielberger, Gorsuch, Lushene, Vagg and Jacobs43 Profile of Mood States (assesses anxiety and its impact on daily functioning); Reference Grove and Prapavessis44 Depression Anxiety and Stress Scales-21 (measures levels of depression, anxiety and stress); Reference Lovibond and Lovibond45 Brunel Mood Scale (evaluates various domains of mood); Reference Lane, Soós and Leibinger46 and Anxiety Short Form 8a. Reference Recklitis, Blackmon, Chevalier and Chang47

Stress measurements used were VASs (linear measures for self-reported stress levels; Reference Lesage and Berjot38,Reference Lesage, Berjot and Deschamps39 initial, resting and variability of heart rate variability (a physiological marker of stress); Reference Tang, Ma, Fan, Feng, Wang and Feng48,Reference Ditto, Eclache and Goldman49 the Perceived Stress Inventory (measures the perception of stress in daily life); Reference Cohen, Kamarck and Mermelstein50 and the Psychological Stress Measure (evaluates the psychological impact of stressors). Reference Lemyre and Tessier51

Metrics used to assess quality of life were as follows: Professional Quality of Life (ProQOL – measures positive and negative aspects of helping others, including compassion satisfaction and burnout); Reference Stamm52 and the Satisfaction with Life Scale (assesses overall satisfaction with life). Reference Diener, Emmons, Larsen and Griffin53

Quality of work was assessed in some studies using the following metrics: the Caring Ability Inventory (measures the caring ability of individuals in healthcare settings); Reference Ngozi and Sitzman Jean54 self-reported days off work; and self-rated mean work performance (evaluates perceived effectiveness and productivity at work).

Mindfulness was measured by some studies using the following tools: the Practice Quality Mindfulness Questionnaire (evaluates the quality of mindfulness practices); and the igroup Presence Questionnaire (assesses the sense of presence in virtual environments, which can relate to mindfulness).

Efficacy of interventions

In general, interventions to increase practitioner well-being using extended reality were effective, with 11 out of 13 studies (85%) noting a positive effect on participants. Interventions decreased stress, Reference Williams and Riches26,Reference Hayakawa, Barrows, See and Schomberg27,Reference Gaggioli, Pallavicini, Morganti, Serino, Scaratti and Briguglio31,Reference Beverly, Hommema, Coates, Duncan, Gable and Gutman33,Reference Nijland, Veling, Lestestuiver and Van Driel35 reduced anxiety Reference Williams and Riches26Reference Pascual, Fredman, Naum, Patil and Sikka28,Reference Gaggioli, Pallavicini, Morganti, Serino, Scaratti and Briguglio31,Reference Adhyaru and Kemp32 and increased relaxation. Reference Williams and Riches26,Reference Gaggioli, Pallavicini, Morganti, Serino, Scaratti and Briguglio31,Reference Adhyaru and Kemp32 Metrics relating to job performance were also affected by the interventions, with burnout reduced and compassion increased. Reference Hayakawa, Barrows, See and Schomberg27 Two studies found that increased use of the intervention correlated with participants feeling more relaxed, with Pascual et al. finding that heart rate variability increased with more virtual reality sessions, Reference Pascual, Fredman, Naum, Patil and Sikka28 and Gaggioli et al. finding that with increased virtual reality scenario and therapy exposure there was increased relaxation, as assessed by biomarkers. Reference Gaggioli, Pallavicini, Morganti, Serino, Scaratti and Briguglio31

There were mixed findings relating to fatigue experienced by participants – Soh et al. found that 25% of participants felt fatigued by the virtual reality guided meditation, Reference Soh, Ong, Fan, Seah, Henderson and Doshi29 whilst Bodet-Contentin et al. and Tarrant et al. found decreased fatigue using their respective metrics Reference Tarrant, Jackson and Viczko36 immediately after their virtual reality relaxation sessions.

Interventions were found to be enjoyable Reference Weitzman, Wong, Worrall, Park, McKee and Tufts21,Reference Adhyaru and Kemp32 and qualitative responses showed the intervention was shown to be ‘great’, ‘amazing’, and ‘really love to be able to do this during my workday’. Reference Adhyaru and Kemp32 Similarly, Weitzman et al. stated that the intervention was very enjoyable (indicated by an average score of 74/100 on the study’s quantitative metric). Reference Weitzman, Wong, Worrall, Park, McKee and Tufts21 Staff said they would recommend interventions to a colleague. Reference Hayakawa, Barrows, See and Schomberg27 Weitzman et al. and Nijland et al. both found their virtual reality interventions were easy to learn, Reference Weitzman, Wong, Worrall, Park, McKee and Tufts21,Reference Nijland, Veling, Lestestuiver and Van Driel35 with those with prior virtual reality experience finding them easier to use. Reference Weitzman, Wong, Worrall, Park, McKee and Tufts21 Interventions that had some elements of interactivity were deemed to be more engaging by participants. Reference Williams and Riches26

Feasibility and acceptability

The complexity of the technology may prove to be a barrier in widespread implementation of extended reality-based interventions, as the technological effort required to use the equipment was ‘high’ or ‘very high’. The areas of difficulty reported related to the pairing of a smartphone with biosensors and reading stress data, rather than specifically use of virtual reality hardware. Reference Gaggioli, Pallavicini, Morganti, Serino, Scaratti and Briguglio31 Williams and Riches found that some technological issues arose during the implementation of the intervention (e.g. freezing of images); however, these were resolved and minimised when a trained facilitator was present. Reference Williams and Riches26

Few studies commented on the negative aspects of the interventions. Soh et al. found that participants made some comments regarding the use of the hardware, with their virtual reality headset being heavy for participants, and images not being sharp enough. Reference Soh, Ong, Fan, Seah, Henderson and Doshi29 Bodet-Contentin et al. found that 22% of virtual reality sessions triggered mild side effects, for example nausea and dizziness, but these were not significant enough for participants to terminate the sessions. Reference Bodet-Contentin, Letourneur and Ehrmann30

Michael et al. provide technical considerations for effective implementation of virtual reality into clinical environments. They note that factors such as maintenance, storage and internet access should all be contemplated before the purchase of hardware and software, and that different headsets and programmes may be more suited to different environments. Indeed, this was the only article to focus on the space requirements for effective virtual reality use, noting that this differs depending on whether the participant is sat or stood. They also state that privacy should be considered, alongside factors that may affect participant comfort, such as ventilation and furniture. Reference Michael, Villarreal, Ferguson, Wiler, Zane and Flarity37

Nijland et al. found that one third of the nurses using their virtual reality intervention felt that they did not have enough time in their working day to use it, and did not feel that they could leave a colleague with their workload to take a break to use the virtual reality. Reference Nijland, Veling, Lestestuiver and Van Driel35 Similarly, in Michael et al.’s study, whilst all participants felt that they had support from a senior colleague to engage with virtual reality well-being activities, they still felt that they would struggle to integrate the interventions into scheduled breaks. Reference Michael, Villarreal, Ferguson, Wiler, Zane and Flarity37

Costs of hardware and software

Weitzman et al. note that virtual reality is ‘cheap and accessible’ technology, Reference Weitzman, Wong, Worrall, Park, McKee and Tufts21 but as with many of the studies included in this review, do not state the costs of their software and hardware. Gaggioli et al. commented on the costs of using virtual reality rather than traditional cognitive behavioural therapy to aid well-being; however, they also noted that there was an 85% decrease in costs of one piece of equipment from the initiation to the end of the study because of rapid technological advancement. Reference Gaggioli, Pallavicini, Morganti, Serino, Scaratti and Briguglio31 Hayakawa et al. state their study equipment was donated, but hardware costs ranged between USD $600 and USD $1300. Reference Hayakawa, Barrows, See and Schomberg27

Discussion

There is limited literature pertaining to the use of extended reality to improve healthcare worker well-being, with only one study examining the use of virtual reality to improve mental health staff well-being. Reference Williams and Riches26 Given the wide variety of technological interventions and metrics used in the literature, the results of studies are difficult to compare. There is a need for further research to be done in this field, given the challenges within the mental health workforce. Although this scoping review has included a heterogenous pool of studies, all were healthcare professionals that work within a stressful and busy clinical environment and, therefore, sentiments of what has been found in this review may be portable to mental health practitioners.

Effects of interventions

Extended reality interventions have a positive effect on healthcare staff well-being, regardless of whether they are used as short one-off interventions or in longer term programmes. Multiple metrics were used to assess well-being, but studies demonstrate that extended reality can reduce stress, increase relaxation and reduce anxiety. This correlates with previous studies demonstrating that pleasant and immersive virtual environments decrease stress and increase relaxation within the general population and those with mental health conditions. Reference Valmaggia, Latif, Kempton and Rus-Calafell19,Reference Riva, Baños, Botella, Mantovani and Gaggioli55,Reference Serrano, Baños and Botella56 Many interventions were one-off interventions with few studies demonstrating the long-term follow-up impact of the interventions. However, as suggested in previous systematic reviews, Reference Rowland, Casey, Ganapathy, Cassimatis and Clough57,Reference Jingili, Oyelere, Nyström and Anyshchenko58 future research should explore ideal duration and frequency of interventions, with long-term effect on well-being also assessed.

There was no consensus on the appropriate length or frequency of well-being interventions, with interventions ranging from 3 min to 12 week programmes. Some studies opted to leave the intervention in situ for many weeks or months, with staff able to access them as desired. Interventions that have scheduled sessions for staff should ensure that each member of staff has equal access, and that their access can be planned for in terms of staffing levels. In addition, these sessions can be supervised by a technician, and as appropriate may include a debrief. Unsupervised sessions increase the availability of such interventions but rely on staff members to take control of their own well-being and find time to undertake such activities, with some indicating a need for accessibility outside traditional working hours. Reference Michael, Villarreal, Ferguson, Wiler, Zane and Flarity37

It must be questioned as to whether some of these measurement modalities are appropriate as a surrogate measure for well-being. Well-being is a complex concept with multiple modalities and measuring one aspect does not confer one’s well-being. For example, heart rate variability may confer stress in the moment but not overall practitioner well-being, and evaluation tools for depression and anxiety may aid in giving a sense of a practitioner’s psychological well-being, but will may not reflect their well-being as a whole. Reference Zhang, Balloo, Hosein and Medland59 A more homogenised measure of well-being is required, which will also aid comparison between the efficacy of interventions in future studies.

Engagement with interventions

Generally, extended reality is viewed as an engaging and novel activity in the broader literature, Reference Alhalabi60,Reference Lau and Lee61 and similarly the healthcare professionals in the studies reviewed indicated participants would recommend extended reality to colleagues, Reference Weitzman, Wong, Worrall, Park, McKee and Tufts21,Reference Hayakawa, Barrows, See and Schomberg27 suggesting they would like to engage with well-being activities as part of their normal working day. Reference Adhyaru and Kemp32 Staff generally engaged well with such well-being interventions, and they are viewed as enjoyable and beneficial.

As with previous research, Reference Nahar and Gurav62 although participants recognise the need for well-being activities, they struggle to find time in the working day to complete them. Even when the intervention was scheduled into rotas with appropriate cross-cover of colleagues, there was still guilt experienced by staff undertaking well-being activities. Reference Nijland, Veling, Lestestuiver and Van Driel35,Reference Michael, Villarreal, Ferguson, Wiler, Zane and Flarity37 To combat this, some studies supplied the intervention for use during rostered breaks, which increased relaxation and happiness and decreasing anxiety, Reference Hayakawa, Barrows, See and Schomberg27,Reference Adhyaru and Kemp32 but limited the time that the intervention could be used for. Indeed, a previous systematic review of well-being strategies for mental health practitioners found that well-being interventions were difficult to implement effectively into scheduled breaks, most often because of poor staffing levels. Reference Gilbody, Cahill, Barkham, Richards, Bee and Glanville63

Feasibility

Although the systematic review by Riches et al. pertains to workplace well-being generally, Reference Riches, Taylor, Jeyarajaguru, Veling and Valmaggia17 rather than specifically a healthcare setting, heaviness of the headset was noted in one study, as was cybersickness in another. Issues with hardware and software are still of note and should be considered when implementing such technology into the clinical environment. Worryingly, a third of doctors state that they do not have the necessary technology to perform their job without disruption – which includes WiFi and broadband. 64 Reliable internet access may therefore prove to be an issue in integrating extended reality software into the clinical environment, and this should be considered when choosing appropriate applications for well-being activities. Applications that can be downloaded and stored may be better suited to the clinical environment than software that requires an active internet connection for streaming content such as videos.

Financial cost of new equipment will be a barrier to integration of new technologies within the NHS. Ways of making interventions cheaper have been demonstrated in some studies, including the use of the participant’s own smartphone with headsets rather than the use of virtual reality head-mounted devices. Reference Soh, Ong, Fan, Seah, Henderson and Doshi29,Reference Michael, Villarreal, Ferguson, Wiler, Zane and Flarity37 There was no consensus among the included articles on the financial viability of extended reality-based interventions. Although initial investment costs for hardware are quoted as being high, Reference Hayakawa, Barrows, See and Schomberg27 balanced with the cost of burnout and work hours lost, effective well-being interventions in the form of extended reality are likely to be cost-effective. For instance, the cost of paying one nurse a day of sick leave because of stress or burnout (£162.84) 65 and hiring an agency nurse to cover their shift (£305.88) 66 is nearly £500 for a single 12 h shift, which is more than the cost of most virtual reality headsets on the market currently (£289.99 for Meta Quest 3S at the time of writing). 67 Indeed, extended reality is now more affordable, Reference Riches, Azevedo, Bird, Pisani and Valmaggia18 even more so on an organisational rather than commercial level. However, there are additional costs to consider when running extended reality interventions, such as the purchase of software, maintenance and cleaning costs and the provision of adequate space in which to run interventions. None of the articles evaluated cost-effectiveness of virtual reality as a well-being intervention. Given that many of these costs are ‘one-off’ software and hardware costs, extended reality-based well-being interventions may prove to be cost-effective, but further research is required to evaluate this fully.

Limitations

Few of the studies included examined long-term effects and outcomes of the technologies, which is common in similar research, and experimental research with robust designs is lacking. Reference Riches, Azevedo, Bird, Pisani and Valmaggia18 Two papers were not retrieved, and only English manuscripts were considered, creating a blind spot within the scoping exercise. In addition, the aim was to map the current literature specifically to the mental health workforce; however, there is a paucity of extended reality well-being research in this setting, limiting transferable learning. There was limited literature pertaining to extended reality well-being interventions other than virtual reality, and thus conclusions regarding virtual reality technologies may not be applicable to wider extended reality technologies.

Implications for practice

Extended reality interventions offer a potential way of increasing well-being within the healthcare workforce, as showcased in this scoping review, reported in line with guidance. Reference Tricco, Lillie, Zarin, O’Brien, Colquhoun and Levac68 They may be cost-effective but require careful consideration of individual software, space requirements and implementation issues, and greater empirical testing is needed to demonstrate the return on investment. A consensus on ideal intervention time and frequency to have the maximal impact on staff well-being is required and homogeneity of outcome measurement modalities needs to be increased in future studies to compare their impact with the current literature.

Data availability

No primary data was collected; however, the Excel spreadsheets used to screen and synthesise the literature are available upon request from the corresponding author.

Author contributions

H.M., J.D., J.R.A. and M.L. shaped the conceptualisation, design and format of the data collection. H.M. performed literature searches and, alongside J.D., screened articles. H.M., J.D., J.R.A., M.L., N.C., S.A. and R.S. played a substantial role in the writing and drafting of the work. All authors approved the final version of the manuscript and agree to be personally accountable for the work.

Funding

This work was supported by the Innovate UK Mindset XR under Grant Number 10103302.

Declaration of interest

N.C. and J.R.A. are co-founders of ExR Solutions Ltd (https://exr.education). J.R.A. is a shareholder of VREvo Ltd and on the advisory board of the Journal of Medical Extended Reality. H.M. was an employee of ExR Solutions Ltd and undertook this work in such capacity. R.S. is a member of editorial board of BJPsych Open. He did not take part in the review or decision-making process of this paper. No other conflicts of interest exist as far as the authors are aware.

Transparency declaration

This manuscript is an honest, accurate and transparent account of the process we undertook. The peer review provided insights to increase the illustration needed for key parts of the work.

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Figure 0

Table 1 Descriptive information of the included articles

Figure 1

Fig. 1 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow chart demonstrating the search strategy.

Figure 2

Fig. 2 Outcome measures of participant well-being used in the articles.

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