The global demographic shift toward an aging population presents a pressing need to enhance the quality and effectiveness of health care [1]. Aging is typically associated with cognitive inactivity and, thus, cognitive impairment, resulting in escalating care demands and health care costs [2] and reducing daily functioning and quality of life among older adults [3]. As such, there is a need for effective interventions aimed at enhancing cognitive functions, which can mitigate their decline and promote healthy aging [4].

A promising tool with significant potential across various fields is virtual reality (VR), which has been found to be effective in caring for older individuals, both with and without cognitive impairment [5]. By offering immersive digital experiences, VR can provide varying levels of immersion and high immersion can be provided by head-mounted displays (HMDs), which can stimulate multiple sensory modalities [6]. Such heightened immersion enhances the sense of presence, yielding more pronounced behavioral responses [7].

In addition to the general cognitive function, VR-based training programs have shown promise in improving specific cognitive domains, such as short-term memory, orientation, attention, comprehension, naming, constructions, memory, and judgment [8]. Indeed, VR interventions have been found to significantly improve executive function and verbal memory in older adults [9], whereas traditional cognitive training methods may be limited in terms of accessibility, motivation, and ecological validity [10]. VR technology offers a unique opportunity to create immersive and engaging 3D experiences that simulate real-world scenarios and involve multiple sensory modalities [11,12]. Indeed, studies indicate that VR interventions can enhance the effectiveness and engagement of cognitive interventions, resulting in better outcomes among older patients [13]. VR-based training may also have a beneficial influence on physical activity, with research suggesting it can improve balance performance and functional mobility [14]. Additionally, the potential of VR interventions to promote social engagement and combat social isolation has also been studied among older adults [15].

Research has shown that music has many positive effects on human health, including reducing stress and anxiety [16], enhancing mood [7], improving sleep [17], and relieving pain [18], and it can be an excellent motivator for physical activity [19]. Music has previously been integrated into VR experiences among older adults [11] to increase motivation [11], improve mental well-being [20], and support rehabilitation [21].

While studies have examined the use of VR in health care settings, particularly in mental health [22], its application in healthy older adults who can use VR at home is still an emerging area of research [11]. Understanding the benefits and potential limitations of home-based VR interventions is crucial for developing evidence-based strategies to support healthy aging [4]. Further research is still needed to assess the impact of VR interventions on specific cognitive, physical, and social domains and to identify the optimal protocols for therapeutic use.

Currently, existing VR products and services are prohibitively expensive for many home end users, and their use is typically limited to clinics, nursing homes, and rehabilitation centers [23]. However, the most effective strategy for ensuring maintainable health care in the face of aging populations is prevention. As such, there is a need to provide a home-based service that offers scientifically validated, safe, engaging, and personalized content for older adults to enhance their cognitive, physical, and social abilities.

The main aim of the study is to determine the effects of using a VR-based digital therapeutics app to improve the cognitive, social, and physical performance abilities of healthy (high-functioning) older adults.

It is expected that significant relationships will be found between the 2 factors (group × time) for each of the tested cognitive, physical, and social performance scores. Specifically, cognitive, social, and physical performance scores are expected to significantly improve throughout the VR training intervention compared with the start, but only for the experimental group. No such change is expected to be observed for the control group.

The Cognitive, Social, and Physical Effects (CoSoPhy FX) study was designed as a randomized, parallel-group, 2-arm, superiority study with an aimed 1:1 allocation ratio. The protocol was registered with ClinicalTrials.gov (NCT05369897) on June 30, 2022.

Neuropsychological assessment was performed at baseline and after the intervention. The primary outcomes of the initial study comprised the cognitive, social, and physical performance abilities of healthy (high-functioning) older adults. The parameters that were selected are (1) a wide range of cognitive domains: composite memory, verbal memory, visual memory, psychomotor speed, reaction time, complex attention, cognitive flexibility, processing speed, executive function, simple attention, and motor speed (Central Nervous System Vital Signs [CNS-VS] battery) [31]; (2) physical performance across 6 subcomponents: lower body strength, upper body strength, aerobic endurance, lower body flexibility, upper body flexibility, and dynamic balance or agility (Senior Fitness Test); (3) standard grip strength (using a dynamometer); (4) the sense of loneliness (De Jong Gierveld Loneliness Short Form); (5) the quality of life and perceived well-being (World Health Organization [WHO]–5 Well-Being Index); (6) the health-related quality of life (EQ-5D-5L); (7) satisfaction with participation in social roles and ability to participate in social roles and activities (Patient-Reported Outcomes Measurement Information System Short Form 8a); and (8) the severity of anxiety symptoms (General Anxiety Disorder 7-item questionnaire [GAD-7]) [32].

The CNS-VS is a computerized neurocognitive test battery developed as a routine clinical screening instrument. It comprises 7 tests—verbal and visual memory, finger tapping, symbol digit coding, the Stroop Test, a test of shifting attention, and the continuous performance test. The result includes neurocognitive clinical evaluation domains—composite memory, verbal memory, visual memory, psychomotor speed, reaction time, complex attention, cognitive flexibility, processing speed, executive function, simple attention, and motor speed [31]. The CNS-VS clinical battery is sensitive to subtle cognitive deficits and progressive decline or improvement. Previous research has shown it is validated, reliable, and easy to use [33].

The WHO-5 Well-Being Index is a 5-item measure of well-being with high internal consistency, evidence of a 1D factor structure, and high convergent associations with other measures of well-being [34,35]. The respondent is asked about their well-being in the last 14 days. Each of the 5 items is scored from 5 (all of the time) to 0 (none of the time). The raw score ranges from 0 (absence of well-being) to 25 (maximal well-being) [36].

The EQ-5D-5L is a questionnaire used to assess health-related quality of life. It measures the problems experienced in 5 domains, which are, mobility, self-care, usual activities, pain or discomfort, and anxiety or depression. The questionnaire also includes an overall health scale where individuals rate their health condition from 1 to 100, with 100 representing the best imaginable health. Previous research has found the EQ-5D-5L to be reliable and valid [37].

The GAD-7 was used to measure the severity of anxiety symptoms. Each item considers different anxiety symptoms and is answered on a 4-point Likert-like scale. The total score ranges from 0 to 21, and a rise in the score indicates more severe anxiety. The tool is sensitive to anxiety in nonclinical samples and to changes in the severity of anxiety symptoms.

Grip strength was assessed with a hand-held dynamometer. The method is a reliable measure of the strength of muscles in older adults when using a standardized protocol and instructions [38]. The resulting grip strength data have been reported to predict general muscle strength and physical functioning in the older adult population [39,40].

On September 21, 2021, KB, SS, JK, LM, ES, KN, MMH, and WW prepared the original version of the protocol (version 1.0). During the further development of the VR-based digital therapeutics app, it was decided to eliminate the physical and social aspects of the intervention. On January 10, 2022, the protocol concerning outcome measures was amended (version 2.0); the primary outcomes were redefined as attention and working memory. Secondary outcomes comprised other cognitive domains, quality of life, well-being, anxiety, and standard grip strength. The same authors were involved in making the amendment, and all the changes to the protocol and outcomes were made before participant recruitment. All relevant parties (including the institutional review board and investigators) were informed about the protocol amendments and outcomes. This decision was prompted by several limitations experienced when using the solution at home, such as insufficiently fast internet, which was needed for trouble-free operation, difficulties in connecting to Wi-Fi, a complex setup process, and the risk of falling.

An a priori computation of the required sample size based on the type of test, the expected effect size, the type I and type II error rates, the number of groups, and the number of measurements were performed according to Lu et al [41]. The statistical power analysis was conducted for a mixed model of repeated measures for 2 groups, 1 measure at a time (corresponding to the main cognitive performance scores detailed) with a 0.7 pre-post correlation, a 20% dropout rate, a medium effect size (0.5), a significance level of α=.05, and a statistical power of 1–β=.80. The necessary sample size for these parameters was 77 (n=154) participants per group.

The MUL stored the personal data of the interested and eligible participants on an internal cloud service, protected from external access. The data set for statistical analysis was fully anonymized. All data storage and processing comply with the General Data Protection Regulation (GDPR) and other applicable regulations. Where possible, fully anonymized data may be made publicly available through open-access repositories supporting the Open Science Initiative.

The project received funds from June 1, 2021, to October 31, 2023. The study’s design, management, analysis, and reporting are independent of the funder. The study, from recruitment to completion of follow-up, was planned to take place from January 2022 to May 2023. The recruitment phase was performed from January 2022 to mid-January 2023. As shown in Figure 9, a total of 310 participants were tested for eligibility and 122 were excluded because of not meeting the inclusion criteria. The most common cause of exclusion was the MoCA score being below 26 points, suggesting the presence of objective cognitive impairment. The recruitment rate (61%, 188/310) was acceptable. Following this, 188 participants were allocated to an experimental group (n=100, 53.2%) or a control group (n=88, 46.8%), with an allocation ratio of 1:0.88.

In the experimental group, 20 participants declined to participate before the start of the intervention and withdrew their consent without giving a reason. A total of 12 participants withdrew because they reported somatic and mental health problems unrelated to the intervention. In the experimental group, 68 participants completed the intervention.

In the control group, 22 participants declined to participate before the start of the intervention and withdrew their consent without giving a reason. A total of 4 participants withdrew because they reported somatic and mental health problems unrelated to the intervention. In the control group, 62 participants completed the intervention. There were no missing data.

The data are currently being analyzed, and we plan to publish the results by the end of September 2024.

The study results will be published in scientific journals and presented at appropriate scientific conferences. All materials and papers will be written by the researchers. No services of external copywriters will be used. The study protocol was registered and published on ClinicalTrials.gov.

VR-based interventions can significantly improve the quality of life for healthy older individuals in several ways. First, VR offers a means of mental stimulation and cognitive engagement. By immersing the user in various environments, tasks, and games, VR can delay cognitive decline by enhancing various cognitive abilities such as memory, attention, and problem-solving skills [42,43]. Second, VR interventions can be used to support physical activity and rehabilitation by providing a safe environment for older adults to improve their balance and flexibility and reduce the risk of falls and injuries [14]. Third, VR provides opportunities for social interaction and connectivity, thus combating the isolation and loneliness often experienced by older people. VR meetings and games can promote engagement with family and peers, and exploring VR worlds can offer a sense of adventure and travel without physical limitations [15]. Finally, VR apps can be used to manage anxiety and stress, promote general well-being, and provide leisure opportunities, thus positively impacting quality of life [44].

Several potential risks and challenges are associated with using VR interventions in the older adult population, and these should be taken into consideration to maximize their benefits and minimize any potential harm. First, suboptimal and prolonged use may be associated with physical discomfort or cybersickness, comprising symptoms such as nausea, disorientation, or eyestrain [29]. Second, there can be a significant learning curve for older adults unfamiliar with the technology, and some individuals may find the technology intimidating or stressful, leading to rejection or noncompliance [45]. Third, if the person is unaware of their real-world surroundings while immersed in the VR environment, they may be at risk of falls or accidents. Finally, while the cost of VR hardware has decreased, it can still be expensive, especially for high-quality systems.

One limitation of this study is that it did not determine the degree of function of the participants by an appropriate objective tool; instead, it was evaluated by a research team based on a medical interview during the screening process. While this approach provided some insight into the participants’ functional independence in activities of daily living, it may have introduced subjectivity and potential bias. Objective tools, such as standardized assessments or performance-based measures, could have provided more reliable and valid measures of older adults’ functioning. For instance, widely recognized tools such as the Timed Up and Go (TUG) [46] test for mobility and the Instrumental Activities of Daily Living (IADL) scale [47] for more complex tasks could offer standardized and quantifiable metrics. Future studies should consider incorporating these objective tools to obtain a more comprehensive and accurate assessment of functional ability.

Another potential limitation of the study relates to the occurrence of cybersickness among participants engaging with VR interventions. Cybersickness, a condition characterized by symptoms such as dizziness, nausea, and headache, mirrors the symptoms of motion sickness but is induced by immersive VR environments. The incidence of cybersickness varies among individuals and can significantly impact the user’s ability to engage with VR-based interventions over time [29]. This limitation is particularly relevant as it may affect the participant’s adherence to the intervention, potentially skewing the study’s outcomes. Future research should aim to identify strategies to minimize cybersickness, possibly through the adaptation of VR content, the duration of sessions, or the inclusion of breaks, to enhance the comfort and participation of all users.

Furthermore, the study faced challenges associated with Wi-Fi connectivity, which represents another significant limitation. A reliable Wi-Fi connection is crucial for the seamless delivery of VR content and the uninterrupted participation of subjects in the study. Issues with Wi-Fi connectivity, such as signal instability or bandwidth limitations, can disrupt the VR experience, leading to fragmented sessions or the inability of participants to complete the intervention as planned. This technological constraint not only affects the consistency and quality of the intervention delivery but also potentially impacts the engagement and satisfaction of participants. Addressing Wi-Fi connectivity issues is essential for ensuring the fidelity of VR-based interventions, and future studies may need to consider alternative solutions or backup options to mitigate these challenges, ensuring a smooth and effective implementation of VR technology in research settings.

Previous research found that VR therapy can improve the well-being of older adults in long-term care, rehabilitation hospitals, and older adult care residences, who often experience cognitive decline, reduced mobility, and isolation [22]. We intend to publish our findings in a future study, and we believe that they will provide further information on the effect of immersive VR therapy among healthy, community-dwelling older adults regarding their cognitive performance, tolerance, and technology acceptance. Even so, further research is needed to explore the long-term effects, optimal intervention designs, and specific populations that may benefit most from VR-based interventions.