The term “Gerontechnology” was first coined by Graafmans and Brouwers (1989) and refers to the mixing of the scientific fields of gerontology and technological engineering. The word itself is a blend of “gerontology” (i.e., the study of aging) and “technology” (i.e., the creation and supply of technological products, services, and environments) (Fozard et al., 2000). It can be defined as the development and use of technology for the benefit of aging and older adults (Fozard et al., 2000). In Bouma and others’ (2009) review, gerontechnology is described as an essential determinant to the healthy aging and quality of life of older adults. Bouma et al. (2009) discusses how the field of gerontology often overlooks: 1) the environment of aging people, 2) proactive prevention-based solutions, instead seeking out disease countering strategies, and 3) active participation of older adults as their own agents of change in the healthy aging process. The impact and ability of technology to change the environment in which people age is highlighted as a key utility of using gerontechnology as a prevention-based intervention to promote holistic, healthy aging (Bouma et al., 2009). Fozard et al. (2000)’s seminal review highlights six key areas where gerontechnology has the potential to improve the aging process of older adults: 1) housing; 2) communication; 3) personal mobility and transportation; 4) health; 5); work; and 6) recreation and self-fulfillment. Of particular relevance, gerontechnology is posited to help with the healthy aging of older adults, for instance by preventing or postponing health problems through nonmedical interventions that help to counteract deterioration in psychological and physiological functioning, which is often linked to aging (Fozard et al., 2000). Additionally, Fozard and others (2000) points to the potential utility of computer games and visual arts-based computer programs as an under-tapped resource for self-fulfillment and well-being in older adults.

However, in order for gerontechnology to be successfully implemented, it needs to be perceived as acceptable by its primary target, namely, older adults. According to Davis’s (1989) technology acceptance model (TAM), two primary components effect an individual’s acceptance of technology: 1) perceived usefulness of the technology, and 2) perceived ease of use. That is, potential use of technology is often predicted by the extent that individuals believe it will be helpful to them. However, even if potential technology users think that a specific technology is useful, they may also think that it is too challenging to use, and that the effort involved in using the technology outweighs its benefits (Davis, 1989). Therefore, based on the TAM, effective gerontechnology should be clearly beneficial to its users, while also being developed and presented in a way that is easy for users to engage with. This hypothesis has been empirically supported through a meta-analysis conducted by Zhou and others (2020), where it was found that perceived usefulness and perceived ease of use had significant positive impacts on older adults’ attitudes and behavioral intentions related to gerontechnology.

The global impact of the aging society is further compounded by another major societal change: the technological revolution. In particular, these transformations raise questions for researchers, policymakers, and practitioners as to whether computer-based technologies will further widen the divide of age segregation, amplifying the isolation of older people, or instead break down generational barriers (Rowe & Kahn, 2015). Despite common perceptions, a growing body of research is beginning to highlight the potential acceptability of technology for older adults as evidenced by its increased integration into their daily life routines (Wootton, 2012; Calvo & Peters, 2013; Lattanzio et al., 2014; Bercovitz & Pagnini, 2016). For instance, in higher income countries, adults over 65 years of age appear to be increasingly Internet and tech-savvy (Wagner & Wagner, 2003; Crabb et al., 2012; Reardon 2012; Cangelosi and Sorrel, 2014). Estimates of older adults in the USA indicate that over 50% use email or the Internet, with around 70% of this population using them every day (Reardon, 2012). Additionally, approximately 11% of older adults own a smartphone (Reardon, 2012).

While the Internet, email, and text messaging are, at this time, the most widespread and accessible types of computer-based technology for older adults, more advanced forms of technology (e.g., patient portals, smartphone applications) that help older adults manage acute and chronic health-based conditions also appear to be acceptable, based on findings from recent scientific studies (for e.g., see Chang & Im, 2014; McMahon et al., 2014; Taha et al., 2014; Wong et al., 2014). Gerontechology is currently applied in a wide range of health-based domains such as physical activity and mobility, home care experience, and overall wellness. For example, technology has been used to assist with medication adherence in home care settings (Lapane et al., 2012; Reeder et al., 2013). Pedometer-based technology used to help with flexibility and frequency of exercise has been implemented in older adult populations through DVD-based exercise programs, tablet computers, and software applications (Bickmore et al., 2013; McAuley et al., 2013; Silveira et al., 2013). Information technology has been used to augment knowledge of and adherence to practices that improve general wellness (Cocosila et al., 2009; Thompson et al., 2011; Xie, 2011); for instance, focusing on improving mental health by reducing isolation and loneliness (McCausland & Falk, 2012). Furthermore, VR headsets have become more accessible and immersive for older adults with tools such as head-mounted display (HMD) and the cave automatic virtual environment (CAVE) that facilitate increased interaction with virtual environments, thereby improving engagement and motivation to use technological interventions (Tuena et al., 2020). The development of mobile application technology with visors and/or tracking systems (e.g., Google Cardboard) allows for further options that are accessible and provide relatively immersive virtual environments (Fang et al., 2017; Tuena et al., 2020). These VR technologies allow for the development of tailored exercises that can be meaningfully manipulated and controlled to virtual environments, enabling effective rehabilitation interventions (Winstein et al., 2016). However, the current gerontechnology research-base is heavily weighted towards biomedical and physical health interventions, often overlooking the potential for gerontechnology as a psychological intervention (Vailati-Riboni et al., 2020a). Kwon (2016)’s review of current gerontechnology applications highlights this gap in the research, noting that there is a dearth of research examining assistive technology geared towards cognitive and psychological needs, with most gerontechnology research focusing on heart disease and diabetes, as evidenced by a systematic review by Barlow and others (2007). Of the research examining gerontechnology to support psychological well-being and quality-of-life, the available technology-based interventions appear to fall into six main categories: 1) Telemedicine; 2) Smartphone applications; 3) Software; 4) Videogames; 5) Robots; and 6) VR. For a more detailed review of the psychological applications of gerontechnology, see Vailati-Riboni et al. (2020a).

As outlined above, gerontechnology can be used as a psychological intervention in a variety of ways. Encouragingly, research with varying levels of vigor has highlighted the potential benefits for mental health and well-being linked to gerontechnological interventions (for review, see Baker et al., 2018; Buyl et al., 2020; Chen & Schulz, 2016; Lampit et al., 2014; Piau et al., 2014; Vailati-Riboni et al., 2020a). While a full review of the benefits of gerontechnology is beyond the scope of this paper, a growing body of literature points to its potential benefits for social isolation (e.g., Fokkema & Knipscheer, 2007; Tsai et al., 2010; Kahlbaugh et al., 2011; Tsai & Tsai, 2011; Cotten et al., 2013; Aarts et al., 2015), cognitive performance (e.g., Ball et al., 2002; Shatil et al., 2014; Ballesteros et al., 2015; Kim et al., 2015), depression (e.g., Spek et al., 2007; Tsai & Tsai, 2011; Preschl et al., 2012; Dear et al., 2015a; Jøranson et al., 2015; Titov et al., 2015; Firth et al., 2017a), anxiety (e.g., Zou et al., 2012; Mewton et al., 2013; Dear et al., 2015a; Dear et al., 2015b; Firth et al., 2017b), quality of life (Moyle et al., 2013; Broadbent et al., 2014; Vailati-Riboni, 2018; Vailati-Riboni et al., 2020b), and well-being (Cocosila et al., 2009; Thompson et al., 2011; Xie, 2011; Silva et al., 2015). Table 1 provides an overview of findings from a selection of existing reviews evaluating the efficacy of gerontechnology for well-being and mental health.

Gerontechnology is predicted to improve the aging process for older adults; however, its implementation is not without concerns and drawbacks (Kim et al., 2017). Of key importance, despite its potential for improving various aspects of older adults’ lives (e.g., social engagement, cognitive engagement, functional independence), this age group continues to show reluctance to engage with technology (Millward, 2003). Older adults’ lack of technology uptake is even more pronounced when compared with younger populations, a phenomenon referred to as the “grey digital divide” (Millward, 2003; Nielsen, 2014). Several barriers to gerontechnology use have been identified in the literature. For example, in a study by the Pew Research Center, it was found that skeptical attitudes regarding the benefits of technology use, difficulties learning to use technologies, and physical challenges were among some of the most frequently cited barriers (Smith, 2014). In a review by Kang and others (2010), obstacles to technology uptake included the tendency for many older adults to feel uncomfortable with new technology, stigma (for e.g., viewing technology as a confession of dependence) and financial concerns. In a focus group study by Vaportzis and others (2017) examining the acceptability of technology and computer tablet use, older adults expressed concerns related to three main categories: 1) barriers, such as lack of instructions, low confidence, health-related drawbacks, and cost; 2) disadvantages, such as technology that is too complex or too prolific, feelings of inadequacy, comparison with younger generations, or lack of in-person social interaction, and 3) skepticism about technology use, in general. Importantly, in a recent review on effective implementation of digital mental health interventions for older adults by Seifert and others (2019), five risks for barriers to gerontechnology use were identified: 1) lack of experience, social support, and access to digital technology increasing the risk that older adults perceive technology to be exclusionary; 2) lower use of digital technologies amongst older adults; 3) retired older adults are not required to use new technologies for their work, potentially reducing their motivation to try new technologies; 4) lower levels of socialization to technology; and 5) aging-related increases in cognitive, physical, social, and financial vulnerability leading to greater effort needed to learn to use new technologies. Given the commonly expressed challenges and barriers to gerontechnology use found in the research, effective technologies should be designed to be easily usable by older adults, provide avenues for increased social contact, be easy to fit into the user’s daily routine, and provide opportunities for rapid and/or frequent interactions with health providers (Jimison et al., 2008; Kang et al., 2010; Seifert et al., 2019). Finally, and of crucial importance, gerontechnology should be perceived as beneficial by users (Jimison et al., 2008).

VR appears to have strong therapeutic potential for use as an intervention for older adults and offers substantial advantages when compared to conventional treatments with respect to accessibility (e.g., to a wider number of clinical stimuli), functionality (i.e., by improving capacity to provide interactions with and tests of “real-life” skills), patient interaction with therapeutic stimuli, standardization of experimental treatments, possibilities for treatment-related virtual environment manipulation, and safety conditions for patients (Cherniack, 2011). Additionally, systematic review evidence suggests that VR may be as effective as traditional treatment methods but may achieve results in shorter periods of time (Mohr et al., 2013; Montana et al., 2020). Notably, preliminary research indicates that VR applications in mental health practice show increased acceptability by older adult patients, as measured via the Technology Acceptance Model (Davis, 1989; Benham et al., 2019).

The field of older adult VR is still relatively nascent. However, to-date, scientific research examining the effectiveness of VR interventions for older adults points to various potential benefits for physical, psychological, and social well-being (Hasan and Linger, 2016; Baez et al., 2017; Lee et al., 2019; Montana et al., 2020; Vailati-Riboni et al., 2020). Physical benefits include decreased pain (Benham et al., 2019; Dermody et al., 2020), increased functional strength (Dermody et al., 2020), improved balanced/decreased risk of falls (Bisson et al., 2007; Rendon et al., 2012; Dermody et al., 2020), improved posture (Dermody et al., 2020), and increased physical activity (Miller et al., 2014). Psychological effects include improved cognitive functioning (Optale et al., 2010; Cherniack, 2011; Dermody et al., 2020; Yen & Chiu, 2021), better emotion regulation (Hasan and Linger, 2016; Bornioli et al., 2019; Montana et al., 2020), decreased depression and anxiety (Robert et al., 2016; Yen & Chiu, 2021), creation of positive emotions and enjoyment (Lee et al., 2019), as well as an increased sense of control through environmental mastery and improved capacity to live independently (Lee et al., 2019). While there is less research examining the impact of VR on social outcomes in older adults, it has been hypothesized that VR may have the capability to increase social interaction in this population (Dudley, 2018; Miller et al., 2019). Additionally, VR used as a well-being intervention for older adults appears to have the distinct benefit of meeting more than one health-related need at once, given that VR programs often simultaneously address the physical, psychological, and social needs of the user (Hughes et al., 2017; Dudley, 2018).

Despite the numerous proposed benefits of VR for older adults, the strength of the research base is currently mixed, at best. Meta-analytic and systematic review findings indicate that many study designs are methodologically weak, with high risk for bias (Molina et al., 2014; Lee et al., 2019; Miller et al., 2013; Dermody et al., 2020; Montana et al., 2020; Thach et al., 2020; Skurla et al., 2021; Yen & Chiu, 2021). For example, in a systematic review by Dermody and others (2020) of VR interventions in community dwelling older adults, it was found that all seven of the included studies had small sample sizes (n ≤ 39), affecting the generalizability of the results. Additionally, none of the papers reviewed received a “high” quality rating (Dermody et al., 2020), based on the grading of recommendations, assessment, development, and evaluation (GRADE) approach to assess overall quality of findings (Higgins & Green, 2011). Similar methodological weaknesses were highlighted in the systematic review of 13 randomized controlled trials (RCTs) by Molina et al. (2014), where small and selective samples were a consistent issue for generalizability of results. Furthermore, none of the studies analyzed reported follow-up analyses, limiting the ability to decipher whether gains made during the intervention period would lead to lasting benefits (Molina et al., 2014). In a systematic review of 14 studies by Miller and others (2013) on the feasibility and effectiveness of VR interventions to enable physical activity in older adults, it was found that the evidence was not strong enough to conclude definitively whether interventions were effective, due to weak study quality and high risk of bias. Additionally, feasibility was reported inconsistently (Miller et al., 2014). A review by Montana and others (2020) pointed to the need for more rigorous RCTs in order to achieve an enhanced understanding of VR versus non-VR intervention efficacy. Finally, in the combined meta-analysis and systematic review of RCTs by Yen and Chiu (2021), all 18 studies were found to have moderate risk of bias based on the Cochrane Risk of Bias Rating (Higgins et al., 2011), once again highlighting a need for more rigorous research methodology in the field of VR research.

In addition to methodological limitations, important gaps in study design were identified. Older adults undergo visual and auditory changes as part of the aging process; however, many studies did not consider these age-related changes in their assessments (Dermody et al., 2020). For example, Dermody et al. (2020)’s review of community-based VR interventions for older adult health found that very few studies assessed visual acuity, (Parijat et al., 2014; Parijat et al., 2015) and often excluded participants if they had self-reported or serious visual or sensory impairment (Optale et al., 2010; Parijat et al., 2015; Parijat et al., 2015; Levy et al., 2016). Additionally, none of the studies in their review assessed hearing ability and only three studies measured for cybersickness (Parijat et al., 2015; Parijat et al., 2015; Benham et al., 2019). Furthermore, only one study included a survey question about participants’ perceived acceptability of the VR experience (Benham et al., 2019). Without attention paid to auditory and vision-based capabilities, as well as dexterity, older adults may be less likely to accept VR as an intervention. Therefore, further research examining the impact of developmental capacity on VR engagement, as well as design features in VR programs accounting for audio, visual, and physical challenges, is warranted. Notably, none of the studies reviewed by Dermody et al. (2020) integrated gaming technology in the VR system, which could be a potential way to support user engagement and enhance participant enjoyment (Molina et al., 2014). Finally, most studies reviewed examining VR programs for older adults focused on physical health-related interventions, with far fewer VR interventions incorporating an explicit focus on content related to improving psychological well-being (Molina et al., 2014; Parijat et al., 2015; Lee et al., 2019; Dermody et al., 2020; Yen & Chiu, 2021).

Keeping in mind the potential barriers to VR usage in older adult populations, one potential avenue for improved mental health and well-being is to design VR programs that incorporate scenes of nature. Exposure to natural settings, as well as perceived connection with nature, have both been shown to be associated with numerous improved psychological health outcomes (for review, see Aerts et al., 2018; Capaldi et al., 2014; Hartig et al., 2014, McMahan & Estes, 2015). The notion that natural settings are imperative for human thriving has been explored in the literature for decades (Orians, 1980). For instance, the Biophilia Hypothesis (Wilson, 1984), which is a seminal theory in environmental psychology, posits that human health and well-being is related to connection with our natural environment. Wilson (1984) theorizes that human affiliation with life forms and life-like processes is due to millennia of human evolution in natural surroundings, and the necessity for humans to be in contact with life-like processes in order to survive. Attention Restoration Theory (ART; Kaplan & Kaplan, 1989; Kaplan 1995) provides a theoretical framework to clarify the underlying mechanisms through which nature connection may improve mental health. ART hypothesizes that directed attention is a finite resource that can be restored through exposure and appreciation towards nature via “soft fascination”; that is, the attention directed towards interesting stimuli requiring minimal cognitive exertion (Kaplan, 1995). Furthermore, gerontechnology has been theoretically and empirically connected to the impact of the natural environment on healthy aging. For example, through developing appropriate technological interventions that consider the influence of the natural physical environment on well-being as one ages (Fozard, 2012). These hypotheses have been corroborated by a variety of studies (for e.g., Mayer et al., 2009; Nisbet et al., 2011; Roe & Aspinall, 2011; Sadowski et al., 2020; van den Berg et al., 2003; Zelenski & Nisbet, 2014) and reviews (Thompson Coon et al., 2011; Capaldi et al., 2014; Hartig et al., 2014; McMahan & Estes, 2015; Aerts et al., 2018) investigating the relationship between connection with nature and well-being.

One way proposed to utilize VR 360-degree video technology most effectively is through the incorporation of natural settings in the VR experience (Depledge et al., 2011; Smith, 2015; Browning et al., 2020). Despite the numerous benefits offered from exposure to in vivo nature, many people do not feel comfortable going into natural or “wild” environments, even if they have convenient access to them (Bixler & Floyd, 1999; Browning et al., 2017). It is important to develop and examine technologies, such as VR, that enable frequent, realistic interactions with nature, particularly in the context of older adult health promotion, given that nature may not always be accessible due to mobility restrictions and care needs related to aging, (Depledge et al., 2011; Van Houwelingen-Snippe et al., 2021). VR programs using 360-degree videos of nature are both a convenient and inexpensive way to provide access to nature (Depledge et al., 2011; Smith, 2015). This is particularly important given findings that many of the benefits of nature exposure can be achieved through VR headsets providing visual and auditory sensory information (Browning et al., 2020). Preliminary research comparing interaction with real-life nature to VR-based nature shows evidence that VR nature may provide similar benefits, although there is a lack of clarity to the extent that this comparison holds true, with some studies showing that the impacts of VR-based nature may be less beneficial for mood (Kjellgren & Buhrkall, 2010; Annerstedt et al., 2013; Calogiuri et al., 2018; Browning et al., 2020).

While the research field examining the impacts of VR-based natural environments is still relatively new, a growing body of literature points to the therapeutic efficacy of 360-degree nature videos (Valtchanov, 2010; Maples-Keller et al., 2017; Jerdan et al., 2018; White et al., 2018). For example, nature-based VR videos have been evidenced to rapidly improve mood in experimental studies of healthy, community-based young and middle-aged adults (Anderson et al., 2017) and university students (Valtchanov, 2010; Schutte et al., 2017; Yu et al., 2018). Anderson and others’ (2017) study of 18 young to middle-aged adults found that VR nature scenes 15-min in length improved both objective (electrodermal activity and heart-rate variability) and subjective (Positive and Negative Affect Schedule; Watson et al., 1988) affect. Yu et al. (2018) corroborated these findings in their study of psychological responses to 9-min VR nature videos in 30 healthy young adults, but did not find significant effects for physiological responses. Both Schutte et al. (2017) and Valtchanov (2010) reported that university student responses to short immersive VR-based nature videos indicated benefits for subjective psychological mood levels. Valtchanov (2010) also found objective improvements to relaxation via skin-conductance and heart rate.

The benefits to well-being conferred from 360-nature videos appear to extend to improvements in cognitive functioning (Gerber et al., 2017; Chung et al., 2018) and reductions in physiological levels of stress (Gerber et al., 2017; Hedblom et al., 2019). In Chung and others (2018) study of 40 healthy young adults, preliminary support was provided for the capability of 360-degree nature videos to restore attention, through subjective (Perceived Restorativeness Scale; Hartig et al., 1997) and objective measures (via event-related potential). Hedblom and others (2019) experimental study compared the effects of 360-degree virtual visual stimuli of urban environments, forests, and parks, with congruent olfactory stimuli (i.e., city and nature odors) and auditory stimuli (i.e., noise and bird songs) on physiological stress levels in 154 healthy young adults. Their findings indicated that the virtual park and forest provided significant stress reductions, but not the urban area (Hedblom et al., 2019). In addition to community settings, 360-degree VR nature videos show potential for improving attentional capacity and reducing physiological measures of stress in intensive care unit (ICU) settings, based on findings from 37 healthy younger and older adults with ages ranging from 20 to 85 (Gerber et al., 2017).

Despite preliminary support for VR-based nature videos on psychological well-being, several methodological and design limitations in the current scientific literature should be mentioned. The vast majority of reviewed studies examined healthy, younger or middle-aged adults with fairly small sample sizes. This significantly impacts the ability to generalize the results of these studies and it remains unclear whether the effects found would be the same in exclusively older adult or clinical populations. Many studies investigated both physiological and psychological outcomes, which was a methodological strength. However, most studies did not assess longitudinal outcomes of nature-based VR inductions and interventions, instead relying on single-time point evidence. Further studies are needed to clarify the durability of affective, cognitive and stress level improvements associated with 360-degree VR nature videos.

To-date, empirical research on nature-based VR interventions for older-adult well-being is extremely limited with only ten published articles found when conducting the literature search for this review. However, of these 10, only eight specifically focus on nature-based VR experiences for older adults (Banos et al., 2012; Bruun-Pedersen et al., 2014; Bruun-Pedersen et al., 2016; Bornioli et al., 2018; Moyle et al., 2018; Reynolds et al., 2018; Bornioli et al., 2019; Ludden et al., 2019), with the remaining two including older adults in their samples, but not exclusively studying this age group (Bornioli et al., 2018; Bornioli et al., 2019). Most studies focus on healthy, non-clinical samples (Banos et al., 2012; Bruun-Pedersen et al., 2014; Bruun-Pedersen et al., 2016; Bornioli et al., 2018; Bornioli et al., 2019), but three focused on older adults with symptoms of cognitive decline or dementia (Moyle et al., 2018; Reynolds et al., 2018; Ludden et al., 2019). Study findings are presented in Table 2 according to reference, sample, VR technology, VR environment, aims, design, measures, and results.

For example, in a study by Banos et al. (2012) the ability of VR-based nature walks to enhance feelings of positive mood and relaxation in 18 healthy older adults was explored. It was found that the virtual environments provided significant increases in joy and relaxation, and significant decreases in sadness and anxiety (Banos et al., 2012). Additionally, participants reported low difficulty of use along with high levels of satisfaction and sense of presence (Banos et al., 2012). However, this study used a small sample size with a non-clinical population, limiting generalizability of findings. Furthermore, the study examined only two sessions with the VR environment. In order to draw more robust conclusions, studies examining multiple nature-based VR sessions should be conducted, as it is likely that this will improve older adults’ comfortability with the VR interface, further clarifying the impact of the intervention itself on mood (Banos et al., 2012).

The impact of interactive screens with virtual nature scenes attached to exercise bicycles has been examined for potential benefits for enjoyment and self-efficacy in healthy older adults living in retirement homes (Bruun-Pedersen et al., 2014; Bruun-Pedersen et al., 2016). Results indicated that participants exercised for longer, experienced more excitement and felt an increased sense of control regarding their ability to engage in exercise (Bruun-Pedersen et al., 2014). However, these studies had small sample sizes (n ≤ 15), were conducted with healthy older adults, and did not use control groups, making findings challenging to generalize (Bruun-Pedersen et al., 2014; Bruun-Pedersen et al., 2016).

In an example of a study examining the potential use of VR-based nature videos for older adults with dementia, Ludden et al. (2019) conducted a series of case studies based at a residential care home in Sweden. Preliminary feedback from study participants and care home staff indicated acceptability and beneficial effects for mood and relaxation. However, due to the study design, the findings are once again challenging to replicate or generalize due to small sample size and lack of experimental design.

Taken together, there is clearly much work to be done to build the quality of evidence examining the impacts of VR-based nature environments for older adult well-being. While the quality of the empirical evidence is currently weak, qualitative findings indicate strong potential for clinical and practical benefits of VR-based nature interventions for the successful aging of older adults. This is particularly promising given the challenges that older adults may be faced with when trying to access nature in real life. Further research with longitudinal RCTs in both clinical and non-clinical populations is warranted to elucidate the feasibility, level of efficacy and mechanisms through which these interventions operate.

There are numerous definitions and frameworks for understanding mindfulness (for in-depth reviews of prevailing conceptualizations, see: Bodhi, 2011; Dunne, 2015; Gethin, 2011; Hart et al., 2013; Khoury et al., 2017). As a construct, the origins of mindfulness are derived from Buddhist tradition, where mindfulness is described as both the ability to remember past experiences in order to facilitate a deeper sense of purpose and awareness (Anālayo, 2003; Bodhi, 2011) and the capability to comprehend what is occurring the present moment (Brown et al., 2007; Bodhi, 2011). In recent years, mindfulness has been increasingly researched within the context of Western science, as is evidenced by growth in the number of mindfulness-related publications during the past four decades (Google Scholar, 2021). Perhaps the most prevalent westernized understanding of mindfulness is Kabat-Zinn’s (1994) conceptualization, where mindfulness is described as a non-judgmental, intentional awareness of the present moment. Mindfulness has also been theorized to be a socio-cognitive ability that allows individuals to notice and draw novel distinctions between objects, people, feelings, thoughts, or experiences and is described as the opposite of “mindlessness” (Langer, 1989; Langer and Moldoveaunu, 2000). Mindlessness is conceptualized as the state of being stuck in previously developed cognitive categories which prevents us from fully engaging with the experience at hand (Langer, 1989). Langer’s mindfulness paradigm is particularly interesting in the context of gerontechnology given the many barriers that older adults may face when attempting to use or integrate technology into their daily routines. A final important western conceptualization of mindfulness, which has been developed in more recent years as a way to reconcile different conceptual approaches, is that of embodied mindfulness (Khoury et al., 2017). Embodied mindfulness is embedded in both Buddhist philosophy and neurobiology and considers mindful consciousness as an interaction between the mind, body, and outside world (Khoury et al., 2017). The notion of embodied mindfulness becomes increasingly relevant in the context of immersive VR given the overlap between effectiveness of VR technology due to the concept of presence (i.e., the feeling of “being there” in one’s body) and the notion of embodied mindfulness as a skill or ability that includes elements of attention, awareness, and acceptance of the mind, body, and mind-body connections (Slater et al., 1994; Khoury et al., 2017). The concepts of embodied mindfulness and presence also connect to general design considerations in gerontechnology, because technologies that incorporate understanding of older adult users’ intentions and perceptions (e.g., understandability of a game or training structure, graphic realism, engaging storytelling) are generally experienced as more acceptable and easier to integrate into daily life (Triberti and Riva, 2016; Tuena et al., 2020). It is likely that the sense of mindful presence that these design elements facilitate allows for more potent gerontechnology interventions, such as VR (Tuena et al., 2020).

It has been theorized that some of the effectiveness of VR interventions is due to enhancing perceptions of mindfulness. For instance, through immersive VR’s capacity to capture participants’ attention and provide users the illusion of “being there” in the 3D computer generated environment, VR interventions may be particularly effective at incorporating mindfulness-based activities (Slater et al., 1994). By providing users with an interesting and engaging setting to practice mindfulness (e.g., simulated natural settings), limiting distractions from the real world, and increasing a sense of presence, VR may facilitate mindfulness practice (Navarro-Haro et al., 2017). As previously described, in the context of VR, “immersion” refers to the capability of a technical system to deliver an encompassing and convincing environment that a user is able to interact with, whereas the concept of “presence” refers to the experience of feeling and behaving as if one is actually in the virtual environment (Sanchez-Vives & Slater, 2005). Both of these sensations appear to have considerable overlap with elements of mindfulness in that they require the user to be present in the here and now and pay some level of attention to both their bodily sensations and environmental perceptions. Research demonstrates that the more immersive a VR intervention is, the more likely that users will endorse acceptability of the VR experience and report benefits (Riva et al., 2016). Additionally, if the VR experience is immersive enough, the VR user may have the perception that they are present in the virtual world or virtual body due to the alternation of cognitive factors that regulate the experience of body and physical space via perceptual information. In the context of VR this perception can also be referred to as “embodiment” (for a more detailed review of this theory, see Riva et al., 2015). Thus, it appears that mindfulness and immersive VR have the potential to operate in a bi-directional pathway, with increased mindfulness leading to augmented awareness and attention to the VR experience, and enhanced immersion in VR experiences leading to increased levels of mindfulness. Given the potential for mindfulness to enable older adults to approach technology with curiosity and openness to explore the unknown, improve engagement (Bercovitz & Pagnini, 2016), and the potential for VR to activate mindful experiences, VR applications that incorporate elements of mindfulness might be particularly useful in the context of gerontechnology interventions to support older-adult mental health and well-being.

Mindfulness-based interventions (MBIs) are behavioral interventions that teach mindfulness, following a mind-body medicine view of health by integrating physical, cognitive-affective, behavioral, and social components (Kabat-Zinn, 2013; Khoury et al., 2017; Khoury, 2018). MBIs have demonstrated efficacy for improving psychological well-being and reducing stress in non-clinical populations, as well as for a large range of psychological and physical disorders in clinical populations (for more in-depth review, see Carletto et al., 2020; Carrière et al., 2018; Goldberg et al., 2018; Hofmann et al., 2010; Howarth et al., 2019; Khoury et al., 2013; Khoury et al., 2015; Poissant et al., 2019).

Comparable to mindfulness, there are many differing conceptualizations of self-compassion from both eastern and western perspectives (Khoury, 2019). As a practice, self-compassion originates from Buddhist traditions (Shonin et al., 2014) and was introduced to western psychology and research by clinical psychologist Paul Gilbert and research psychologist Kristin Neff (Neff, 2003; Neff, 2004; Gilbert, 2006). There is much debate regarding the definition and measurement of self-compassion (Muris et al., 2016; Cleare et al., 2018; Coroiu et al., 2018) and issues regarding a lack of a conceptualization that includes both the eastern Buddhist origins and western definitions (Davidson et al., 2002; Muris et al., 2016; Strauss et al., 2016; Zeng et al., 2016). While a full review of self-compassion and its Buddhist and westernized conceptualizations is beyond this paper, it is important to be aware of the influence that Buddhist concepts have had on the interpretation of self-compassion in western psychological science. Following a westernized conceptualization, self-compassion can be described as relating to oneself with a kind and forgiving attitude (Neff & Vonk, 2009) and involves noticing distress, as well as building understanding that one’s suffering is part of the human condition (Neff, 2003).

As previously described, embodiment in the context of VR refers to the illusion that an individual’s real body is the life-sized virtual body that is observable to them in the virtual environment (Slater et al., 2010; Petkova et al., 2011). Embodiment appears to alter physiological and psychological perspectives. For example, shifting an individual’s perception of the size of their body (e.g., adults believing their body is the size of a simulated child’s body) as well as modifying racial attitudes when perceiving embodiment in a simulated body with a different skin color than the VR user’s actual body (Banakou et al., 2013; Peck et al., 2013; Martini et al., 2014; Maister et al., 2015). It is theorized that virtual embodiment may enhance self-compassion in individuals with elevated levels of self-criticism (Falconer et al., 2014) and research is beginning to investigate the effects of embodying virtual adult and child bodies, and interacting compassionately with those bodies, on decreasing self-criticism and depressive symptoms (Baghaei et al., 2019; Falconer et al., 2016; Falconer et al., 2014). Cebolla and others (2019) highlights the importance of imagery skills in self-compassion, as many techniques for increasing compassion in therapeutic settings require mental imagery abilities that induce and train positive mental states (Pearson et al., 2013; Cebolla et al., 2019). If individuals struggle to maintain imagery during meditative compassion-practice this can lead to challenges reaching feelings of compassion and can discourage participants from continuing with the necessary training needed to foster compassion-based skills and positive qualities (Cebolla et al., 2019). To overcome attrition related to lack of ability to sustain mental imagery, VR can be very useful as it enables the construction, maintenance, inspection, and transformation of mental images and can be considered an advanced imagery system that is as effective as reality at inducing emotional, cognitive, and behavioral responses (Day et al., 2004). Self-compassion training via VR programs could be especially useful for aging populations (Tavares et al., 2020). In particular, given research indicating that older adults may respond to gradual deterioration in physical and cognitive resources with self-criticism by blaming themselves for these natural age-related changes, and experiencing elevated levels of regret, rumination, and negative affect (Baltes & Smith, 2003; Laidlaw et al., 2003; Casey, 2012). Conscientious development of gerontechnology interventions is once again crucial here. If done well, technological interventions targeting and developed in partnership with older adults may increase both general levels of compassionate service delivery, as well as users’ self-compassion levels (Fozard, 2012; Schmitter-Edgecombe et al., 2013). Teaching self-compassion in a setting that facilitates easier practice, such as VR, could be beneficial for the adoption of attitudes of kindness towards oneself and the effects of aging.

Self-compassion interventions, or compassion-based interventions (CBIs), can be described as interventions that focus on cultivating compassion towards self and others through psycho-education, training and promotion of practices that enhance compassion (Kirby, 2017). CBIs have been linked to a variety of improvements in psychological health outcomes. Research has found CBIs to be effective at decreasing stress, anxiety, and depression (Kirby et al., 2017), and increasing compassion and empathy (Brito et al., 2018). A meta-analysis by Kirby and others (2017) investigated 21 RCT studies of CBIs and found significant short-term moderate effect sizes for life satisfaction, happiness, and decreased anxiety and depression. Additionally, small-to-moderate effects were found for psychological distress. However, a need for increased rigor in study design, as well as reporting, was identified for future studies of CBIs. Ferrari et al. (2019) conducted a more recent meta-analysis of 27 RCTs regarding the effects of CBIs on psychosocial outcomes and found large effects for rumination and eating behavior, and moderate effects for depression, anxiety, stress, self-criticism, mindfulness and self-compassion. Despite these promising findings, study inclusion criteria were based on a specifically western-lens following Neff’s (2003) model of self-compassion. Future research assessing the efficacy of CBIs based on different models of self-compassion is needed given the debates over its conceptualization and operationalization (Khoury, 2019).

Furthermore, large-scale meta-analyses have linked the construct of self-compassion to enhanced well-being and reduced psychopathology in adults and adolescents (MacBeth & Gumley, 2012; Zessin et al., 2015; Marsh et al., 2018). Additionally, self-compassion shows potential for promoting resilience in the face of significant life stressors such as chronic health issues (e.g., Brion et al., 2014), divorce (e.g., Sbarra et al., 2012), parenting a child with a developmental disorder (e.g., Wong et al., 2016), and combat (e.g., Hiraoka et al., 2015). Notably, in two cross-sectional studies by Allen and others (2012) of adults aged 67–90 years old, self-compassion was found to positively moderate the relationship between physical health and psychological well-being. This moderating effect was particularly strong for older adults in poorer health, indicating that self-compassion may be especially useful for improved quality of life in aging populations with health challenges and could be a crucial component of successful aging (Rowe & Kahn, 1987; Allen et al., 2012; Rowe & Kahn, 2015). In a systematic review and meta-analysis of 11 studies by Brown and others (2019) of the effects of self-compassion on the older adult aging process, it was found that self-compassion was associated with decreased symptoms of depression and anxiety and increased psychological well-being. Meta-analytic findings indicated that self-compassion moderated the relationship between health problems and well-being (Brown et al., 2019), corroborating the findings of Allen et al. (2012). Overall, Brown et al. (2019) concluded that self-compassion is a promising resilience promoter for older adults. However, their search did not include qualitative studies, conference abstracts, or materials that were not published in English, limiting the breadth and depth of their findings, as well as the generalizability. Tavares and others (2020) conducted a scoping review of the self-compassion research base as it relates to psychological well-being of the older adult population. There were no restrictions on study design, or setting, so long as research was conducted with adults aged 60 or older, or with a mean age of 65 or older, and measured self-compassion and psychological adjustment (e.g., life satisfaction, depression or anxiety symptoms). Their review resulted in 12 studies, 1 qualitative and 11 mixed-methods design and found that self-compassion appears to be a valuable resource for older adult psychological adjustment and may promote resilience connected to age related challenges. All studies analyzed were cross-sectional therefore limiting the ability to draw meaningful conclusions from their findings. Another notable weakness of this review was the authors choice to exclude studies with compassion towards others as an outcome. This could limit the validity of the review’s findings, given the considerable theoretical overlap between compassion directed to the self (self-compassion) and compassion directed towards others (compassion).

Growing evidence supports the importance of gerontechnology as an essential determinant to healthy aging and quality of life of older adults (Bouma et al., 2009). Gerontechnology has the potential to facilitate older adults’ active participation in the healthy aging process and may benefit communication, health, mobility, work, housing, recreation, and self-fulfillment (Fozard et al., 2000). However, for its effective uptake, older adults need to perceive gerontechnology to be useful, as well as easy to use (Davis, 1989; Zhou et al., 2020). Therefore, technological solutions need to bridge the generational gap of technology use, instead of widening it. Additionally, further emphasis is needed on the research and development of gerontechnology for mental health, given the bias toward physical health-related technological support. Effective technological interventions for older adults should account for challenges and barriers commonly expressed by older adults and should be designed for easy use, increased social contact, fit with daily routines, and include access to straightforward, regular interactions with health providers, if needed (Jimison et al., 2008; Kang et al., 2010; Seifert et al., 2019). Despite its relatively recent introduction to the mainstream market, VR has the potential to be readily accepted by older adults due to its benefits compared to conventional treatments, such as accessibility, functionality, patient interaction with therapeutic stimuli, quicker positive health impacts, and safety conditions (Cherniack, 2011; Mohr et al., 2013; Robert et al., 2016; Benham et al., 2019; Montana et al., 2020). VR shows promise as a gerontechnology intervention; however, high quality empirical literature is currently limited and further research of its applications, feasibility and efficacy is needed. Additionally, component analyses of the mechanisms through which VR may improve well-being, as well as specific design elements that facilitate better outcomes, are important for clarification of the evidence-base and for the creation of optimally effective interventions.

Taken together, the research base is extremely sparse and sometimes non-existent with respect to VR-based nature interventions, MBIs, or CBIs for older adults, and is even more narrow in the area of older adult mental health and well-being. For instance, based on findings from this review, no study to-date has investigated MBIs or CBIs using VR for older adults and the studies examining nature-based VRs are very few and often methodologically weak. Of the research available, VR for older adults demonstrates potential as an intervention to enhance well-being, but there are significant methodological flaws that must be addressed in order to clarify the evidence base and create effective interventions (e.g., Dermody et al., 2020; Yen & Chiu, 2021). In general populations, nature-based, mindfulness and compassion VR interventions show promise for effectiveness at improving mental health and well-being outcomes (e.g., Falconer et al., 2016; Jerdan et al., 2018; Chandrasiri et al., 2020; Modrego-Alarcón et al., 2021). Currently, no study has investigated a VR-based combined mindfulness-compassion intervention incorporating natural settings for older adults. Given the pathways through which nature, mindfulness, and compassion interventions operate, it is likely that combining these interventions using VR could lead to improved resilience and well-being outcomes, such as mood and quality-of-life, and decreased symptoms of psychopathology. Additionally, a combined nature-mindfulness-compassion program based in VR could further enhance adherence and acceptability of mental health interventions for older adults, given preliminary findings indicating that VR: 1) appears to be an effective method for improving mindfulness, compassion, and nature-based intervention adherence, and 2) shows acceptability for older adults when administered under the right conditions (Zhou et al., 2020). Therefore, there is a need for studies with robust designs explicitly investigating nature interventions, MBIs, and CBIs for older adults, as well as interventions combining these three approaches, in addition to interventions integrating these approaches using VR technology, given their potential to improve quality-of-life and quality-of-care in soon to be the largest proportion of the population. Due to the prospective benefits, further clarification is warranted regarding the mechanisms contributing to the efficacy of VR-based nature interventions, MBIs and CBIs. Additionally, large-scale studies employing rigorous longitudinal RCT designs in cross-cultural and clinical populations are needed to better understand the effectiveness of VR interventions compared to non-VR interventions for mental health and well-being.

Despite the evidence base for older adults still requiring further development, nature, mindfulness, compassion, and VR-based interventions all have support for general population mental health and well-being, in both clinical and non-clinical populations. Key implications for practice with geriatric populations include facilitating access to effective and engaging mental health interventions by clarifying the efficacy of VR-based psychological interventions for older adults, as robust research will be instrumental for effective preventative mental health care for a population in need of this type of programming. Additionally, collecting information on the feasibility, acceptability, and effectiveness of VR for older adults will deliver vital information regarding users’ needs in the burgeoning field of digital therapeutics. Current evidence suggests that both nature-based interventions and MBIs improve emotional well-being and physical health among nonclinical community-dwelling samples of older adults. There is currently not enough research examining the efficacy of CBIs for older adults, but research examining positive associations between self-compassion as a construct and mental health outcomes suggests potential utility for CBIs in geriatric populations. Clearly, further empirical intervention studies are needed in this area. Additionally, mental health support programs that combine nature, mindfulness and compassion show promise given the connections between these constructs and their additive effects on psychological well-being in various older adult populations. Furthermore, despite the early stages of the research base, VR-based interventions appear to be a feasible and effective type of gerontechnology for both physical and psychological outcomes. Limitations to VR access should not be forgotten, there are currently technological, physical, and financial barriers, and a dearth of research examining these specific barriers in VR design and studies. Additionally, given the research focus on WEIRD populations, it is unclear to what extent VR intervention efficacy could be globally generalized. Continuing to find ways to incorporate gerontechnology that promote acceptability amongst older adults is key in order for these interventions to have ecological validity. Whenever possible, gerontechnology interventions should be developed with the input of older adults and specifically targeted to their needs.