Effectiveness of 3D virtual reality motionless imagery exercise through an avatar for mental health in older people: A randomized controlled trial

Abstract

Objective

This study developed a 3D virtual reality (VR)–based Mental Imagery Exercise with Avatars (MIEA) and evaluated its effectiveness in improving cognitive, emotional, and physical outcomes in older adults.

Methods

The experiment involved 38 older adults aged between 65 and 84 years. The study subjects were divided into experimental and control groups, with 19 individuals in each group. Both groups engaged in the VR intervention for 20 minutes, three times a week, for six weeks. The experimental group selected an avatar matching their gender and engaged in virtual exercise using a jogging track, while the control group performed virtual exercise on the same jogging track without an avatar.

Results

Most cognitive assessments showed significant improvements over time, except for the Stop Signal Task. Significant time-by-group interactions were observed in the Stroop Test, immediate and delayed recall in the K-AVLT, working memory in the Digit Span Task, and semantic fluency in the COWAT. Emotional well-being analysis showed a significant improvement in physical self-efficacy over time, along with a time-by-group interaction. Group differences were significant for stress, positive affect, and negative affect. Electromyography (EMG) data from the left gastrocnemius indicated significant time effects and time-by-group interaction, suggesting physiological changes associated with the intervention.

Conclusions

The results indicated that 3D MIEA provides certain psychological benefits associated with exercise and 3D MIEA may offer potential utility for individuals who are unable to engage in physical exercise.

Keywords

3D virtual reality mental health older people cognitive function emotional well-being imagery training

Introduction

In humans, the cognitive function undergoes progressive changes due to aging and various disease processes, illustrating its inherent plasticity and susceptibility to external and internal influences.¹ Cognitive decline in older people increases the risk of mild cognitive impairment and dementia, and decreased cognitive function restricts functional activities in daily living.^2,3 This may be alleviated by interventions involving physical exercise, which are known to have a psychological impact and improve cognitive and emotional functioning.^4–6 Physical activity contributes positively to psychophysiological health by promoting physical well-being, enhancing life satisfaction, providing opportunities for social interaction, fostering self-belief and physical confidence, and improving the skills and functional abilities necessary for autonomous living.⁷ Furthermore, exercise has been shown to exert a beneficial influence on the memory and emotional state of older people, thereby helping to mitigate cognitive decline.⁸ Thus, while participation in exercise primarily focuses on physical improvements in this population, it is often oriented toward enhancing cognitive function and emotional well-being.⁹ The integration of aerobic exercise with cognitive stimulation has been shown to improve brain function, particularly in individuals with Alzheimer’s disease and other cognitive impairments.^10–12 Based on these findings, promoting exercise participation in older adults is essential to prevent dementia and enhance cognitive health.

Although the significance of physical activity in promoting health among older adults is well-established, this population frequently faces considerable obstacles to engaging in regular exercise. These barriers stem from both physiological and psychological factors, including age-related sarcopenia, heightened susceptibility to falls and fractures, reduced physical self-efficacy, and diminished intrinsic motivation for physical activity.^13,14 This issue is particularly pronounced among hospitalized older adults who are subjected to prolonged bed rest, with empirical evidence indicating that approximately 86% of their hospital stay is characterized by inactivity, despite only 5% of this period being medically warranted.¹⁵ Such behavioral patterns not only compromise physical and psychological well-being, but also substantially elevate the risk of functional dependence and long-term disability.¹⁶ Prolonged physical inactivity has been documented to adversely affect multiple physiological systems, including the cardiovascular, endocrine, immune, gastrointestinal, vestibular, and cognitive domains.^17–22 Moreover, sustained immobilization and static postural maintenance during bed rest have been shown to exert direct effects on brain function, as demonstrated through electrophysiological (EEG) and functional magnetic resonance imaging (fMRI) studies.²³ Collectively, these findings underscore the fact that the neurocognitive consequences of prolonged bed rest may not only manifest during periods of immobility but may also persist well after the cessation of bed rest and resumption of mobility, indicating delayed and potentially prolonged recovery trajectories. Given the aforementioned barriers, it is imperative to explore alternative approaches to facilitate exercise engagement among older adults. One such method involves motor imagery, wherein individuals visualize themselves performing physical movements without actual execution.²⁴ While this technique may not elicit substantial physiological adaptations in older populations, it is believed to have significant clinical relevance due to its potential to enhance cognitive and emotional functioning.

With continuous advancements in cognitive neuroscience, insights into the diverse physiological and psychological effects of exercise on humans are being integrated into a new scientific paradigm.²⁵ This focuses on embodied cognitive concepts, which consider the external environment, body, and brain as a unified unit. Exercise methods based on this approach can be referred to as mental imagery exercises. Mental imagery exercises involve training by mobilizing brain-based imagination without physical movement, thereby inducing indirect sensory experiences of movement tasks through mental visualization.^26–28 In essence, cognition and behavior interact dynamically through functional neural activity in the brain’s networks, influencing aging, diseases, health, and more.^29–32

Mental imagery exercises are utilized as cognitive intervention techniques that promote neural plasticity through the relearning of motor skills or motor imitation. Recent evidence also demonstrates that motor imagery can induce motor-related neural activation similar to real movement and facilitate neuroplastic adaptations with repeated practice.³³ However, the application of these techniques on untrained individuals remains challenging.^34–36 These limitations may be addressed by integrating body swapping, a manifestation of body ownership, with virtual reality (VR) paradigms.³⁷

Body swapping refers to a phenomenon in virtual environments wherein participants perceive avatars or virtual bodies as extensions of their own physical bodies.³⁸ This approach offers the advantage of facilitating synchronization between the movements and cognitive states of the virtual body and those of the participant. Furthermore, studies have reported that the provision of a virtual body significantly enhances the body-swapping experience.³⁹ Extending this line of evidence, emerging findings indicate that VR-induced embodiment can enhance cognitive processing by facilitating the integration of perceived bodily states with higher-order cognitive functions, highlighting the therapeutic relevance of avatar-based interventions.⁴⁰ Empirical investigations utilizing such mechanisms have demonstrated that in patients subjected to prolonged immobilization due to extended hospitalization, multisensory stimulation, particularly through VR technologies encompassing visual and auditory modalities, exerts a beneficial influence on functional neuroplasticity and aids in the amelioration of cognitive impairment.⁴¹ This evidence underscores the potential of enriched environments, such as VR-generated illusions of bodily movement, to facilitate the activation of motor-related cortical regions, thereby promoting desirable neuroplastic adaptations through the targeted engagement of specific neural pathways.⁴²

These findings suggest that leveraging VR technologies to deliver avatar representations of bodily movements can amplify the effectiveness of mental imagery interventions. The application of VR not only increases immersion but also enhances the efficacy of mental imagery exercises. Consequently, VR-assisted interventions may offer therapeutic benefits, particularly for vulnerable populations, such as older people or patients with physical limitations who are unable to engage in conventional physical exercise.

Recent evidence further supports the cognitive benefits of VR-based interventions in aging populations. For example, immersive VR cognitive stimulation has been reported to significantly enhance executive function and overall cognitive performance in older adults.⁴³

In a pilot experiment of a VR mental imagery exercise program conducted by our research team, improvement in cognitive function was observed in young adults.³⁴ Research has demonstrated that mental imagery exercises, although not equivalent to actual physical exercise, can have significant effects. They are actively utilized in the treatment of patients with disabilities who are immobile or in chronic pain.^44–46

A review of studies using virtual reality (VR) in stroke patients with motor impairments revealed that applying VR exercise programs resulted in significant improvements in upper limb function.⁴⁷ Additionally, a study targeting hemodialysis patients reported that a VR exercise program increased the sympathetic nervous system activity, thereby reducing stress.⁴⁸ Furthermore, immersive VR-based cognitive stimulation has been shown to significantly improve cognitive performance in older adults, further highlighting the potential of VR as an effective intervention for age-related cognitive decline.⁴⁹

Therefore, using VR on elderly individuals to induce the integration of varied sensory information within the virtual environment, allowing perception and control of the virtual body, may demonstrate effects akin to therapeutic exercise through VR.

However, existing studies have predominantly focused on the effects of VR that involve actual dynamic movements and emphasize improvements in physical function. Such dynamic movements pose limitations for elderly individuals with mobility difficulties or those who have difficulty executing actual movements. Therefore, it is important to develop VR exercise programs based on mental imagery exercises to complement the limitations of traditional VR exercise programs. Validating the effects of mental imagery exercises using only visual images in VR without actual dynamic movements of the body is crucial. Additionally, multidimensional research on the cognitive and emotional effects of VR exercise programs is currently lacking.^50,51

Therefore, in this study, we aimed to verify the effects of a VR program based on mental imagery exercises on the physiological, cognitive, and emotional functions of older people. Through this research, our goal was to provide fundamental treatment methods in the field of medical and exercise rehabilitation and popularize VR mental imagery exercise programs.

Method

Participants

The study was designed as a randomized controlled trial and was conducted at a senior center in Busan, Republic of Korea. Participant recruitment began on November 15, 2019, and all experimental procedures were completed by March 31, 2020. The determination of the number of research participants was based on the statistical program G-power (latest ver. 3.1; Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany), using an effect size of f = .26, α = .05, and 1–β = .95, resulting in a calculated total sample size of 40 individuals.

Although 40 participants were initially recruited in accordance with the G*Power calculation. 2 datasets were excluded due to severe artifacts and measurement errors. As a result, the final analysis included 38 participants. A post hoc power estimation indicated that this reduction decreased the statistical power from approximately 0.361 to 0.345 (a 1.6% absolute reduction), which is minimal but should be considered a methodological limitation.

For this study, participants were selected from older adults aged 65 to 84 years. Those who scored 24 or higher on the Korean Mini-Mental State Examination (MMSE-K) cognitive assessment and were physically and neurologically healthy, and had no restrictions in physical activity, were included. Forty subjects were enrolled in this study. All 40 randomized participants attended all 18 scheduled sessions throughout the 6-week intervention, showing consistently high adherence. This strong engagement was supported by conducting the intervention at a senior center where participants regularly gathered, which facilitated stable attendance and minimized attrition. No participant missed a session, and all scheduled sessions were fully completed. The only exclusions occurred prior to the analysis due to severe artifacts in physiological recordings. Of the two excluded datasets, one belonged to the experimental group and one to the control group, resulting in 19 participants per group included in the final analysis (N = 38).

The inclusion criteria for participation were as follows: (1) No neurological or psychiatric disorders and no medical, neurological, or psychiatric history; (2) No ongoing rehabilitation program for cognitive or emotional disorders; (3) No frequent episodes of nausea, dizziness, or history of vestibular disorders such as Meniere’s disease; (4) Not participating in any other experimental studies; (5) Able to understand the details of the study without difficulty; (6) No visual or auditory abnormalities or skin diseases; and (7) Not currently participating in individual physical activity.

The participants were instructed not to engage in additional physical activities and to Physiological Responses changes throughout the study. Table 1 lists the participants’ demographics.

Table 1.

Demographic information of subjects. IQR=lower limit 25% and upper limit 75%.

Variables		Experimental group (n=19)		Control group (n=19)
Characteristic	Categorize	Frequency	Percentage	Frequency	Percentage
Age, years	M(IQR)	69.20 (67.5, 73.5)		69.90 (66.5, 75)
Sex	Male	9	45	10	55
Sex	Female	10	55	9	45

The objectives and research methods were explained to the participants before participating in the study (Table 1). Those who participated in the study and completed it received a reward of about US $80.

Ethics declaration

This study was reviewed and approved by the Pusan National University Institutional Review Board (IRB), Republic of Korea (Approval No. PNU IRB 2018-84-HR). All participants received a verbal explanation of the study procedures and provided written informed consent prior to participation. All procedures were conducted in accordance with the Declaration of Helsinki and its later amendments. Furthermore, this study was prospectively registered with the Clinical Research Information Service (CRIS), Republic of Korea (Registration No. KCT0010653).

Procedures

The study participants were assessed for eligibility based on the inclusion and exclusion criteria, which were outlined in a telephone interview and checklist. Forty participants were selected for the study. The participants were divided into two groups using a randomized controlled trial design: an experimental group (n=20) who performed a Mental Imagery Exercise with Avatars in 3D virtual reality (3D VR MIEA) and a control group (n=20) who performed exercises a 3D VR program without an Avatar. The study was conducted using a single-blind design. Participants were unaware of group allocation, but the experimenter had to operate the VR system, making full blinding of the experimenter impossible. Participants were randomly assigned to groups using an Excel-generated randomization table, balancing group size and sex, by the principal investigator, who did not participate in subsequent experimental sessions. Pre- and post-assessments of emotional and cognitive outcomes were conducted by three licensed clinical psychologists, who were randomly assigned to participants to ensure blinding of outcome assessors. Physical responses were collected by the experimenter to standardize procedures and minimize variability. While the single-blind design was unavoidable, this potential source of bias should be considered when interpreting the results.

The exercise program was conducted three times a week, for 20 minutes per session, totaling 18 sessions over six weeks. All exercise sessions were conducted by the researchers onsite at a senior center because of the mobility limitations of the elderly participants. Prior to the experiment, all subjects were requested to freely participate in a VR program for 10-20 minutes to check if they could experience VR without discomfort, such as motion sickness, and adapt to participate in a 3D VR experience.

In the experimental group, participants learned and practiced using avatars provided in the VR to embody themselves. The participants in the experimental group were instructed to focus their gaze on the legs of avatar before running began. They were instructed to synchronize their leg movements with the sound of footsteps, inducing a heightened sense of leg movement embodiment. The participants in the experimental group were able to control the speed of the avatar running in real-time through a controller. The participants did not engage in any physical movements while participating in the 3D VR MIEA.

The control group was instructed only to experience the VR comfortably without specific instructions, such as exercising or thinking that they were moving on their own. The control condition therefore involved passive VR exposure, in which participants experienced the same virtual environment as the intervention group, including identical backgrounds and the track-based video. However, no avatar was provided for embodiment, and no instructions for imagined movement or task performance were given. Participants also could not control the speed of the VR experience. Thus, while the visual and environmental context was comparable to the intervention condition, the control group did not engage in interactive or goal-directed activity, making it a non-interactive active control. A no-treatment control group was not included because, due to the nature of VR, even passive exposure can elicit physiological and emotional responses. This design allowed us to specifically examine the additional effects of avatar embodiment and imagined motor activity beyond those produced by simple VR exposure.

Content development

For this study, a 20-minute running program designed for older people was developed using the Unity platform, a VR development program. In the experimental group, avatars were provided to match the participants’ gender, and the participants could adjust the running speed within the running track. The sounds of the footsteps were synchronized with the running speed. In addition, to minimize motion sickness and exclude emotional elements that the environment could evoke, the virtual environment was designed with basic elements, such as mountains and trees, offering a monotonous yet suitable environment to verify the exercise effects. The purpose of these designs was to focus on evaluating the exercise effects while minimizing the potential emotional factors that could influence the outcomes of the VR experience.

In the control group, a track was designed wherein participants could move at a constant speed and view the scenery without avatars being provided. This was done to ensure that both groups experienced similar aspects of the virtual environment, except for the presence of avatars and the ability to control running speed, which was specific to the experimental group. (Figures 1–3).

Figure 1.

CONSORT flow diagram of participant recruitment, randomization, and analysis.

Figure 2.

Study flow chart.

Figure 3.

Experiment setting of 3D Virtual Reality Motionless Imagery Exercise through Avatar.

Apparatus

The HTC Vive VR equipment (HTC Corporation, New Taipei City, Taiwan) was utilized for the study. The equipment consisted of a head-mounted display (HMD) and two hand controllers. The VR implementation software was developed using the Steam VR Unity plugin. The Procomp Infiniti equipment (Think Technology Ltd., Montreal, Canada) was used to measure the electrophysiological responses.

Measurements

Cognition

The Stroop Test was performed to evaluate the cognitive processing speed and inhibition by assessing the interference in naming the color of a word when the word itself spelled out a different color.⁵² The Controlled Oral Word Association Test (COWAT) measured executive functions through verbal fluency tasks using the Seoul Neuropsychological Screening Battery (SNSB).⁵³ The K-AVLT Test assessed memory recall abilities.⁵⁴ The Digit Span Task, using the Korean-Wechsler Adult Intelligence Scale-Fourth Edition (K-WAIS-IV) assessed short-term memory and attention.⁵⁵ The Stop Signal Task (Millisecond Software, 2008) evaluated inhibitory control and response inhibition. The Korean-Mini Mental State Examination (MMSE-K) was also performed.⁵⁶

Emotional well-being

The State-Trait Anxiety Inventory (STAI) first assessed the participants’ anxiety tendencies.⁵⁷ The reliability of the STAI scale was evaluated, and it was found to be reliable, with Cronbach’s α=0.905. The Physical Self-Efficacy Scale (PSE) developed by Ryckman, Robbins, Thornton, and Cantrell based on a questionnaire and adapted to a Korean version was used to assess the participants’ perception of their physical self-efficacy.⁵⁸ The PSE Scale was found to be reliable and yielded suitable results with Cronbach’s α=0.913. The Stress Response Inventory (SRI) was used to evaluate participants’ stress responses.⁵⁹ The stress scale was found to be reliable and suitable, with Cronbach’s α=0.880. The Positive and Negative Affect Schedule (PANAS) measured the participants’ positive and negative affective states.⁶⁰ The positive and negative scale was found to yield a reliable and suitable result with Cronbach’s α=0.771.

Physiological response

The electrophysiological changes during the virtual environment experience were measured by collecting data from eight channels. The electrocardiogram (ECG) recorded the electrical activity of the heart. A photoplethysmogram (PPG) monitored the heart rate through changes in the blood volume in the skin. The Galvanic Skin Response (GSR) measured the changes in skin conductance caused by emotional arousal. Respiration (RESP) was measured to assess the changes in breathing patterns. An electromyogram (EMG) recorded muscle activity. The skin resistance for surface electrodes was reduced by disinfecting the attachment sites with alcohol and using disposable electrodes (Electrode2237, 3M, USA) made of silver (Ag)/silver chloride (AgCl).

A standardized preprocessing procedure was applied to ensure physiological signal quality. The skin was cleaned with alcohol before electrode placement to reduce impedance, and the electrodes and cables were secured with medical tape to minimize movement artifacts. A high-pass filter (10–20 Hz) and a 50/60 Hz notch filter were used to remove baseline drift and electrical interference. For EMG, Ag/AgCl electrodes were positioned along the muscle fiber direction and maintained below 10kΩ impedance. During post-processing, band-pass filtering (30-400Hz), visual inspection, and RMS (root mean square) computation were used to exclude noisy segments and extract meaningful signals.

Data analysis

The statistical analyses were performed using IBM SPSS Statistics for Windows, version 22.0 (SPSS Inc., Chicago, IL, USA). Descriptive statistics (mean and standard error) were calculated for all measurements and demographic variables. To examine the effects of the 3D VR MIEA intervention compared with the control condition, a 2 (Group: experimental vs. control; between-subjects) × 2 (Time: pre vs. post; within-subjects) Two-way repeated-measures ANOVA was conducted. This approach accounts for the dependency of repeated observations within individuals and allows for the examination of the main effects of Group and Time, as well as the Group × Time interaction effect.

The assumption of normality was assessed using the Shapiro–Wilk test on the difference scores (post − pre). In addition, Q–Q plots and histograms were visually inspected to evaluate the distribution of the data, and potential outliers were examined. The Q–Q plots showed approximately linear patterns and the histograms indicated roughly bell-shaped distributions, with no extreme outliers identified. Because the group sizes were balanced (n = 20 per group) and no missing data were present, repeated-measures ANOVA was considered robust to moderate violations of the normality assumption.

The assumption of sphericity was not evaluated because the within-subject factor (Time) consisted of only two levels (pre and post), for which the sphericity assumption is automatically satisfied.

Effect sizes were reported using partial eta squared (ηp²), and exact p-values were reported for all main effects and interaction effects. Statistical significance was set at α = .05. Post hoc comparisons were conducted within each domain (physiological, emotional, and cognitive), and Bonferroni correction was applied to control for multiple comparisons.

Results

Cognition

Various tools were used to assess changes in cognitive function, including the MMSE-K for dementia screening, the Stroop test, and Stop Signal Task for evaluating the response inhibition, the Korean Auditory Verbal Learning Test (K-AVLT) for memory testing (immediate recall, delayed recall, delayed recognition), Digit-span task for assessing short term memory and attention, and COWAT (semantic fluency, phonemic fluency) for evaluating the frontal lobe function.

A two-way repeated-measures ANOVA was conducted to examine the effects of the intervention on cognitive outcomes. Significant Group × Time interactions were observed for the Stroop test F (1, 36) = 17.48, p < .001, ηp² = .327, K-AVLT immediate recall F (1, 36) = 8.34, p = .001, ηp² = .188, K-AVLT delayed recall F (1, 36) = 4.17, p = .019, ηp² = .104, Digit-span task F (1, 36) = 14.27, p < .001, ηp² = .284, and COWAT phonemic fluency F (1, 36) = 7.47, p = .001, ηp² = .172, indicating differential changes between the experimental and control groups over time.

After Bonferroni correction, the interaction effects remained statistically significant for the Stroop test, K-AVLT immediate recall, Digit-span task, and COWAT phonemic fluency.

Significant main effects of Time were also observed for several cognitive measures, including MMSE-K F (1, 36) = 14.93, p < .001, ηp² = .293, Stroop test F (1, 36) = 18.64, p < .001, ηp² = .341, K-AVLT immediate recall F (1, 36) = 23.04, p < .001, ηp² = .390, K-AVLT delayed recall F (1, 36) = 36.80, p < .001, ηp² = .506, K-AVLT delayed recognition F (1, 36) = 15.30, p < .001, ηp² = .298, Digit-span task F (1, 36) = 41.30, p < .001, ηp² = .544, COWAT semantic fluency F (1, 36) = 13.12, p < .001, ηp² = .267), and COWAT phonemic fluency F (1, 36) = 35.55, p < .001, ηp² = .497.

In addition, significant main effects of Group were found for MMSE-K F (1, 36) = 15.45, p < .001, ηp² = .300, Stroop test F (1, 36) = 9.54, p = .004, ηp² = .210, K-AVLT immediate recall F (1, 36) = 5.12, p = .030, ηp² = .125, and COWAT semantic fluency F (1, 36) = 10.71, p = .002, ηp² = .229.

All remaining interaction and main effects were not statistically significant (Table 2).

Table 2.

The results of a repeated measures ANOVA on cognition data.

Variables	Group	Pre –test (95% CI)	Post- test (95% CI)	Repeated measures ANOVA
				Time			Group			T×G
				F	p-	ηp²	F	p-	ηp²	F	p (uncorrected)	p-(Bonferroni-corrected)	ηp²
MMSE-K	Exp	28.42 (27.41, 29.10)	29.21 (28.53, 29.78)	14.93***	0.000	0.293	15.45***	0.000	0.300	1.21	0.30	1.00	0.033
MMSE-K	Con	26.68 (25.95, 27.74)	27.00 (26.29, 28.02)	14.93***	0.000	0.293	15.45***	0.000	0.300	1.21	0.30	1.00	0.033
Stroop Test	Exp	36.21 (28.96, 39.55)	41.74 (35.90, 44.61)	18.64***	0.000	0.341	9.54**	0.004	0.210	17.48***	0.00	0.009	0.327
Stroop Test	Con	52.16 (45.31, 58.05)	52.00 (45.22, 57.93)	18.64***	0.000	0.341	9.54**	0.004	0.210	17.48***	0.00	0.009	0.327
Immediate recall (K-AVLT)	Exp	35.53 (31.19, 39.54)	43.84 (40.59, 46.67)	23.04***	0.000	0.390	5.12*	0.030	0.125	8.34**	0.001	0.009	0.188
Immediate recall (K-AVLT)	Con	34.37 (30.47, 37.20)	36.05 (32.90,38.46)	23.04***	0.000	0.390	5.12*	0.030	0.125	8.34**	0.001	0.009	0.188
Delayed recall (K-AVLT)	Exp	6.37 (5.38, 7.35)	8.37 (7.69, 9.14)	36.80***	0.000	0.506	0.70	0.405	0.019	4.17*	0.019	0.171	0.104
Delayed recall (K-AVLT)	Con	6.63 (5.87, 7.28)	7.47 (6.81, 8.13)	36.80***	0.000	0.506	0.70	0.405	0.019	4.17*	0.019	0.171	0.104
Delayed recognition (K-AVLT)	Exp	10.32 (9.06, 11.66)	11.89 (11.27, 12.40)	15.30***	0.000	0.298	0.34	0.564	0.009	3.13	0.05	0.450	0.080
Delayed recognition (K-AVLT)	Con	10.84 (9.91, 11.44)	11.58 (11.05, 12.10)	15.30***	0.000	0.298	0.34	0.564	0.009	3.13	0.05	0.450	0.080
Stop-Signal Task	Exp	307.26 (224.76, 421.43)	309.13 (285.29, 361.55)	2.51	0.088	0.065	0.89	0.771	0.002	2.43	0.095	0.855	0.063
Stop-Signal Task	Con	370.81 (274.12, 424.53)	254.78 (234.17, 271.79)	2.51	0.088	0.065	0.89	0.771	0.002	2.43	0.095	0.855	0.063
Digit-Span Task	Exp	23.68 (20.89, 26.47)	28.79 (26.54, 31.13)	41.30***	0.000	0.544	2.73	0.107	0.071	14.27***	0.000	0.009	0.284
Digit-Span Task	Con	23.47 (20.37, 25.51)	24.68 (21.55, 26.44)	41.30***	0.000	0.544	2.73	0.107	0.071	14.27***	0.000	0.009	0.284
COWAT (semantic fluency)	Exp	31.89 (28.13, 36.39)	38.53 (33.97, 43.81)	13.12***	0.000	0.267	10.71**	0.002	0.229	2.56	0.084	0.756	0.067
COWAT (semantic fluency)	Con	26.26 (22.85, 28.72)	28.74 (25.30, 30.90)	13.12***	0.000	0.267	10.71**	0.002	0.229	2.56	0.084	0.756	0.067
COWAT (phonemic fluency)	Exp	24.37 (18.59, 30.14)	30.95 (25.07, 35.55)	35.55***	0.000	0.497	1.01	0.321	0.027	7.47**	0.001	0.009	0.172
COWAT (phonemic fluency)	Con	23.79 (18.36, 28.36)	25.63 (20.07, 30.87)	35.55***	0.000	0.497	1.01	0.321	0.027	7.47**	0.001	0.009	0.172

Note. Values are M±SD. *p <0.05, **p <0.01, ***p <0.001. T×G: Time×Group Interaction, ηp²: partialetasquared.

Emotional well-being

Table 3 presents the results of the repeated-measures ANOVA for emotional outcomes. A significant Group × Time interaction was observed for physical self-efficacy, F (1, 36) = 11.27, p = .001, ηp² = .224, indicating differential changes between the experimental and control groups over time. After Bonferroni correction, this interaction effect remained statistically significant (p = .006), whereas the interaction effects for the other emotional variables were not significant after correction.

Table 3.

The results of repeated-measures analysis of variance (RM-ANOVA) in emotional states.

Variables	Group	Pre-test (95% CI)	Post-test (95% CI)	RM-ANOVA
				Time			Group			T × G
				F	p	ηp²	F	p-	ηp²	F	p-(uncorrected)	p-(Bonferroni-corrected)	ηp²
State anxiety	Exp	32.00 (27.98, 35.38)	33.21 (29.14, 37.27)	0.139	0.004	0.004	3.58	0.066	0.090	0.894	0.351	1.000	0.024
State anxiety	Con	36.63 (34.65, 38.82)	36.10 (34.88, 37.74)	0.139	0.004	0.004	3.58	0.066	0.090	0.894	0.351	1.000	0.024
Characteristic anxiety	Exp	32.84 (29.64, 36.03)	33.89 (30.70, 37.08)	0.513	0.478	0.014	2.34	0.135	0.061	0.939	0.339	1.000	0.025
Characteristic anxiety	Con	36.05 (34.30, 37.58)	35.89 (34.39, 37.42)	0.513	0.478	0.014	2.34	0.135	0.061	0.939	0.339	1.000	0.025
Physical self-efficacy	Exp	87.33 (80.55, 92.71)	92.22 (84.03, 95.22)	5.87*	0.015	0.140	2.13	0.153	0.058	11.27**	0.001	0.006	0.224
Physical self-efficacy	Con	84.74 (81.26, 91.15)	83.95 (79.85, 90.77)	5.87*	0.015	0.140	2.13	0.153	0.058	11.27**	0.001	0.006	0.224
Stress	Exp	16.94 (10.82, 23.17)	15.26 (11.01, 19.71)	3.43	0.072	0.087	13.52**	0.001	0.273	0.166	0.686	1.000	0.005
Stress	Con	6.84 (3.21, 10.67)	4.21 (2.93, 5.79)	3.43	0.072	0.087	13.52**	0.001	0.273	0.166	0.686	1.000	0.005
Positive affect (PANAS)	Exp	31.15 (27.07, 36.18)	27.68 (24.31, 31.79)	1.23	0.273	0.033	5.74*	0.022	0.138	4.05	0.052	0.312	0.101
Positive affect (PANAS)	Con	27.68 (20.97, 25.96)	24.84 (22.79, 26.78)	1.23	0.273	0.033	5.74*	0.022	0.138	4.05	0.052	0.312	0.101
Negative affect (PANAS)	Exp	12.73 (11.84, 15.09)	11.10 (11.65, 13.92)	1.55	0.221	0.041	6.13*	0.018	0.146	1.55	0.221	1.000	0.041
Negative affect (PANAS)	Con	11.10 (10.03, 12.07)	11.10 (10.17, 11.82)	1.55	0.221	0.041	6.13*	0.018	0.146	1.55	0.221	1.000	0.041

Note. Values are M±SD. *p <0.05, **p <0.01, ***p <0.001. T×G: Time×Group Interaction, ηp²: partialetasquaredElectrophysiological response.

A significant main effect of Time was observed for physical self-efficacy, F (1, 36) = 5.87, p = .015, ηp² = .140, indicating a meaningful change over time. Significant main effects of Group were observed for stress, F (1, 36) = 13.52, p = .001, ηp² = .273, positive affect, F (1, 36) = 5.74, p = .022, ηp² = .138, and negative affect, F (1, 36) = 6.13, p = .018, ηp² = .146, indicating differences between the experimental and control groups. All remaining interaction and main effects were not statistically significant (Table 3).

Electrophysiological response

The results of the repeated-measures ANOVA for electrophysiological responses are presented in Table 4. A significant Group × Time interaction was initially observed for EMG C (left lateral gastrocnemius), F (1, 36) = 5.53, p = .028, ηp² = .121. However, after Bonferroni correction, this interaction effect was no longer statistically significant (p = .196).

Table 4.

Electrophysiological response changes in the experimental and control groups. NOTE. Values are M±SD. *p <0.05, **p <0.01, ***p <0.001. EMG A: left biceps brachii, EMG B: left rectus femoris, EMG C: left lateral gastrocnemius. T×G: Time×Group Interaction, ηp²: partial eta squared.

Variables	Group	Pre-test (95% CI)	Post-test (95% CI)	Repeated measures ANOVA
				Time			Group			T×G
				F	p	ηp²	F	p	ηp²	F	p (uncorrected)	p (Bonferroni-corrected)	ηp²
ECG (beats/min)	Exp	-0.16 (-2.54, 2.24)	1.21 (-2.72, 2.57)	0.341	0.563	0.009	0.010	0.922	0.000	2.582	0.116	0.812	0.064
ECG (beats/min)	Con	1.86 (0.26, 4.85)	-1.09 (-3.47, 1.19)	0.341	0.563	0.009	0.010	0.922	0.000	2.582	0.116	0.812	0.064
EMG A (㎶)	Exp	-3.35 (-8.09, 2.07)	-0.88 (-0.23, 0.87)	0.629	0.433	0.016	2.432	0.127	0.060	1.123	0.296	1.000	0.029
EMG A (㎶)	Con	0.39 (-0.73, 0.63)	0.04 (-0.36, 0.35)	0.629	0.433	0.016	2.432	0.127	0.060	1.123	0.296	1.000	0.029
EMG B (㎶)	Exp	-0.28 (-1.75, 1.21)	0.35 (0.38, 1.31)	0.306	0.584	0.008	0.043	0.837	0.001	0.718	0.402	1.000	0.019
EMG B (㎶)	Con	0.005 (-0.46, 0.49)	-0.13 (-0.33, 0.11)	0.306	0.584	0.008	0.043	0.837	0.001	0.718	0.402	1.000	0.019
EMG C (㎶)	Exp	0.21 (-0.67, 1.10)	1.55 (1.23, 2.03)	8.881	0.005**	0.189	3.690	0.062	0.089	5.5254	0.028*	0.196	0.121
EMG C (㎶)	Con	0.25 (-0.12, 0.56)	0.42 (0.06, 0.81)	8.881	0.005**	0.189	3.690	0.062	0.089	5.5254	0.028*	0.196	0.121
RESP (beats/min)	Exp	0.77 (-0.18, 1.62)	0.32 (-0.37, 0.92)	0.351	0.557	0.009	3.511	0.069	0.085	0.073	0.788	1.000	0.002
RESP (beats/min)	Con	-0.45 (-2.13, 0.95)	-0.62 (-1.93, 0.52)	0.351	0.557	0.009	3.511	0.069	0.085	0.073	0.788	1.000	0.002
SC (㎶)	Exp	-1.18 (-1.88, -0.61)	-0.61 (-0.88, -0.24)	8.973	0.018*	0.139	2.741	0.106	0.067	0.140	0.711	1.000	0.004
SC (㎶)	Con	-0.68 (-1.15, -0.26)	0.08 (-0.92, 1.08)	8.973	0.018*	0.139	2.741	0.106	0.067	0.140	0.711	1.000	0.004
BVP (pulse/min)	Exp	0.87 (-0.28, 2.16)	0.59 (-0.04, 2.32)	0.379	0.542	0.010	0.162	0.690	0.044	0.000	0.993	1.000	0.000
BVP (pulse/min)	Con	1.37 (-0.80, 3.12)	0.53 (-3.43, 4.53)	0.379	0.542	0.010	0.162	0.690	0.044	0.000	0.993	1.000	0.000

Significant main effects of Time were observed for EMG C, F (1, 36) = 8.88, p = .005, ηp² = .189, and skin conductance (SC), F (1, 36) = 8.97, p = .018, ηp² = .139, indicating significant changes over time. All remaining interaction and main effects were not statistically significant (Table 4).

Without correction, several main effects and interactions reached statistical significance. However, when applying Bonferroni correction within each domain, these effects no longer reached the conventional significance threshold (all p > .05). This indicates that the uncorrected findings may reflect increased Type I error, and interpretation should be made with caution.

Discussion

The present study explored the physiological, cognitive, and emotional changes experienced by older people through the application of 3D VR MIEA, grounded in the theory of embodied cognition. The main findings were as follows: (1) Regarding the changes in cognitive function over time, significant effects were observed in the MMSE-K, Stroop test, K-AVLT (immediate recall, delayed recall, delayed recognition), Digit–span task, and COWAT (semantic fluency and phonemic fluency). The group-related changes significantly affected the MMSE-K, Stroop test, K-AVLT (immediate recall), and COWAT (semantic fluency). Moreover, in the interaction between time and group, significant effects were found in the Stroop test, K-AVLT (immediate recall, delayed recall), Digit-span task, and COWAT (phonemic fluency). (2) In terms of emotional well-being, significant effects were observed over time, and for physical self-efficacy, the interactions between time and group were significant. (3) Regarding electrophysiological responses, significant effects were observed over time and in the interaction between time and group for EMG C. Overall, the 3D VR MIEA significantly affected cognitive, emotional, and electrophysiological aspects among older people participants.

Cognitive changes

The study revealed significant enhancements in specific cognitive sub-domains, including response inhibition (Stroop test), working memory, and executive function. This cognitive improvement aligned with previous research suggesting that exercise positively influences memory and executive function among older adults.^61–64 Steinberg et al. reported that exercise participation among older adults positively influences memory and executive function, which is consistent with the study findings.⁶⁵

In addition, VR-based training programs provide a safe environment for older people and can adjust the difficulty levels based on individual abilities, thus enhancing motivation and enjoyment during training. Such programs benefit memory, executive function, and various cognitive domains.^66,67 In the context of this study, the 3D VR MIEA provided cognitive benefits through simulated exercises, which could positively influence cognitive enhancement among older people individuals with limited mobility.

Emotional well-being changes

Although most of the findings associated with emotional well-being were not significant, the experimental group showed emotional improvement compared to the control group with respect to the changes in physical self-efficacy from the pre-experiment to the post-experiment stage. Although many emotional factors tend to decline in older people, including activity levels and the willingness to exercise, this result is significant. The result aligns with studies suggesting that increased physical self-efficacy after exercise is associated with enhanced positive beliefs.⁶⁸ Therefore, an experience of achievement in physical activity can help form strong positive beliefs in individuals.

On the other hand, since the experiment was conducted without actual physical movement, physiological responses required to induce various emotional changes would not have occurred. Furthermore, the monotony of the graphics and composition of the VR content could have been insufficient to trigger various emotional effects. These factors explain the lack of significant emotional effects observed in this study.

Physiological response changes

An analysis of changes in the electrophysiological data between the pre-experiment phase and during 3D VR MIEA indicated significantly greater alterations in the left lateral gastrocnemius in the post-experiment phase compared to the pre-experiment phase. The interaction between time and group also revealed considerable changes in the electrophysiological responses of the left lateral gastrocnemius EMG C. These findings suggest that, despite the absence of actual movement, internal neural stimulation promoted a sense of movement through mental imagery during the exercise regimen. Similarly, Sharma et al. reported that fine muscle activity patterns resembling those during actual movement occurred during imagery exercises.⁶⁹ Hence, utilizing exercise videos or imagining movements can activate muscle responses through neural stimulation, even without physically moving the muscles, which can be explained by psychological and neuromuscular theories.⁷⁰

Although several main effects and interactions were initially significant, some post-hoc comparisons lost statistical significance after applying Bonferroni correction (p > 0.05), reflecting the conservative nature of this method. This is likely due to the modest sample size (n = 20 per group) and the large number of dependent variables, particularly in the memory domain where each test yields multiple outcome measures, which together substantially increased the threshold for significance. Despite the reduction in statistical significance for some comparisons, the pattern of means across groups and time, along with moderate to large effect sizes (partial ηp²), indicates consistent trends. Therefore, the current findings should be regarded as exploratory, and the intervention’s potential influence on physiological, emotional, and cognitive outcomes warrants further investigation in larger samples or using alternative post-hoc methods. These considerations should be taken into account when interpreting the present findings.

Limitations

The feasibility of applying 3D VR MIEA to older people was examined in this study. The significance lies in analyzing the cognitive and emotional effects of imagery exercises using VR. On the other hand, the monotony in the composition and graphics of the VR content used in this study could have limited the emotional benefits of actual physical activity.

This study employed a single-blind design. While participants were unaware of group allocation, the experimenter was required to operate the VR system, making full blinding of the experimenter impossible. In addition, participants were members of the same community. Although they were instructed not to discuss the study with one another, it remains possible that information about the intervention or group assignment was inadvertently shared. These factors may have introduced potential bias or expectancy effects. Future studies may benefit from strategies such as stricter separation of participants or more automated VR administration to further minimize such influences.

Another limitation is that perceived agency, attention, and cognitive engagement were not directly measured. Both groups consisted of older adults who voluntarily participated in the program, and participation was high, with no dropouts across all sessions. Participants appeared generally engaged in the program, suggesting a high level of motivation and positive expectations regarding the intervention. Under these conditions, large differences in perceived agency, attention, or cognitive engagement between groups are less likely to explain the observed effects. However, because these factors were not formally assessed, subtle differences cannot be entirely ruled out. Therefore, the findings should be interpreted within the context of high participant motivation and adherence.

Conclusions

The results of this study suggest that although 3D MIEA does not produce the same level of physiological effects as actual exercise, it may provide some of the psychological benefits associated with exercise. Further research with diverse populations is needed to verify these findings; however, these findings suggest that 3D MIEA could potentially be applied for individuals who experience difficulty engaging in physical exercise.

Footnotes

Acknowledgments

Photograph of Figure 2 used with the participant’s written informed consent. A preliminary version of this work was previously made available as a preprint on an open-access server; however, the preprint has now been officially withdrawn prior to journal submission.

ORCID iD

Myung-Chul Lee

Ethical considerations

This study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board of Pusan National University (IRB No. PNU IRB/2018_84_HR).

Consent to participate

Written informed consent was obtained from all participants prior to participation.

Author contributions

K.H.H., M.C.L., C.H.P. designed the study, K.H.H., M.C.L. performed the experiments, K.H.H., M.C.L. analyzed the data, K.H.H., M.C.L., C.H.P. contributed reagents/materials/analysis tools, K.H.H., M.C.L. wrote the main manuscript text, K.H.H. and M.C.L. prepared the figures. All authors reviewed the manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The Research Project was sponsored by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MIST) (No. NRF-2017R1C1B5018351).

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

All data generated or analyzed during this study is included in this article.*

Trial registration

ClinicalTrials.gov Identifier: KCT0010653.

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