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Article

Effects of a 12-Week Semi-Immersion Virtual Reality-Based Multicomponent Intervention on the Functional Capacity of Older Adults in Different Age Groups: A Randomized Control Trial

by
Li-Ting Wang
1,†,
Yung Liao
2,†,
Shao-Hsi Chang
3,*,† and
Jong-Hwan Park
4,*,†
1
Department of Leisure and Recreation Management, Taipei City University of Science & Technology, Taipei 11202, Taiwan
2
Graduate Institute of Sport, Leisure and Hospitality Management, National Taiwan Normal University, Taipei 10610, Taiwan
3
Department of Physical Education and Sport Sciences, National Taiwan Normal University, Taipei 10610, Taiwan
4
Health Convergence Medicine Laboratory, Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Republic of Korea
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Multimodal Technol. Interact. 2024, 8(8), 67; https://doi.org/10.3390/mti8080067
Submission received: 3 June 2024 / Revised: 6 July 2024 / Accepted: 16 July 2024 / Published: 1 August 2024
Browse Figures
Versions Notes

Abstract

:
Virtual reality (VR) exercise has been used as a strategy to promote physical health in older adults. Studies have revealed that the effects of exercise interventions vary across age groups. This study aimed to investigate the effects of a 12-week semi-immersion VR-based multicomponent exercise program on the functional fitness of young-old (65–73 years) and middle-old (74–85 years) adults. This study recruited two age groups (young-old adults, n = 49; middle-old adults, n = 37) and randomly assigned them to the experimental (EG) and control (CG) groups. EG participants performed a 75–90-min semi-immersion VR exercise routine twice weekly for 12 weeks, whereas CG participants maintained their original lifestyles without any alterations. The Senior Fitness Test was used to measure functional fitness by assessing upper- and lower-limb flexibility and muscle strength, cardiorespiratory fitness, and balance. EG participants exhibited greater improvements than their CG counterparts in certain functional fitness tests, specifically the Back Scratch, Arm Curl, 2-Minute Step, and 8-Foot Up-and-Go Tests. On comparing the age groups, a difference was exclusively noted in the effects of the Chair Sit-and-Reach Test. In the EG, the intervention significantly improved lower-body flexibility in young-old adults but elicited no such improvement in middle-old adults. Semi-immersion VR exercise improved the functional fitness of young-old and middle-old adults in the EG, with superior results in the former. Elucidating the impact of age-specific exercise interventions on functional capacity will help practitioners design age-specific exercise training content that enhances functional fitness in older adults of different ages.

1. Introduction

The global proportion of older adults is growing and is expected to increase by 20% by 2050 [1]. By 2026, Taiwan is projected to have become a super-aged society, aging faster than Europe, the United States, and Japan [2]. The extension of life expectancy is one of mankind’s crowning achievements. However, aging and age-related diseases pose an increasing challenge to society and the healthcare system [3,4,5].
The healthy aging and frailty perspective suggests that regular physical activity is safe for older adults and can help mitigate the risks of cardiovascular disease, obesity, falls, and muscle weakness [6]. The important goals of maintaining older adults’ fitness are to prevent physical frailty and improve functional mobility [7]. Multicomponent exercise programs are important for maintaining functional fitness in this population [8]. However, the average values for individual functional capacity decrease significantly with age [9]. Jones and Rikli developed and validated a functional fitness assessment tool for older adults [10]. Functional fitness tests assess older adults’ physical functioning and ability to live independently [11]. They are recommended when measuring functional ability in older adults aged 60–90 years and have been used in many clinical trials and exercise interventions [12,13,14].
According to a study in Hong Kong, ages 70 and 75 are considered turning points for various functional health components, with most of these components exhibiting aging-related deterioration [15]. Older adults commonly engage in exercise to maintain functional capacity. However, their participation in traditional multicomponent exercise training interventions has yielded inconsistent findings across different age groups. Toraman, Erman [16] conducted 9 weeks of multicomponent exercise training and found significant post-intervention improvements in all health tests in the 60–73- and 74–86-year age groups. Seco, Abecia [17] found 9 months of exercise training to improve flexibility, strength, cardiorespiratory fitness, and balance in 65–74-year-old adults. Over the age of 74, the intervention’s overall effect was less pronounced. Therefore, elucidating the effectiveness of interventions targeting different older-adult age groups will help tailor training programs that improve functional performance in this population.
Technology-related exercise interventions have long been key approaches toward health promotion in the information age [18]. Virtual reality (VR) is a promising intervention strategy. A previous study reviewed its role in improving the physical and mental health of older adults [19]. Moreover, studies applying various VR to exercise interventions have also established that VR-based fitness helps improve functional capacity in adults aged ≥ 65 years [20,21,22]. However, these studies did not investigate the different effects of exercise interventions across various age groups. Moreover, they had certain limitations, such as yielding significant improvements only in upper-body flexibility [20], exclusively targeting a single sex [21], and focusing more on post-detraining follow-up [22]. Few research projects involving VR have explored age differences and physical function outcomes. One systematic evaluation recommended that the impact of this technology on healthy older adults should be assessed in further detail using larger samples and measurements of function capacity [23]. To fill this research gap, it is thus beneficial to study the subject of semi-immersion VR exercise intervention.
Relative to the previous work mentioned, this paper makes the following novel contributions: First, this is the first study examining age-related differences in older adults participating in a multicomponent exercise program involving technology-based sports. Second, the present study provided a comprehensive assessment of the functional capacity of older adults stratified by age following their participation in a technology-based exercise intervention.
The following sections will detail the experimental design of the study and its findings. Section 2 gives an overview of the study methods. Section 3 presents the results of the study. Section 4 discusses the findings and the significance of the results. Section 5 summarizes the findings of this study and provides direction for future studies.

2. Methods

2.1. Study Design

This study was conducted between September 2020 and November 2020 using a single-blinding (outcome assessors), randomized-controlled-trial design. The required sample size was calculated using G* power [24] based on a power (1 − β error probability) of 0.80 at an α error probability of 0.05, assuming an effect size of f = 0.30 [25]. Using multivariate analysis of variance repeated measurements, the power analysis yielded a target total sample size of 126 participants. To account for possible patient dropouts, the total number of participants increased by 5%. Therefore, the target recruitment number was calculated to be 132 older adults. This study was approved by the National Taiwan Normal University (201912HM099) and registered with ClinicalTrials.Gov (NCT05582863). Written informed consent was obtained from all participants. After completing the study, we compensated all eligible participants with 15 USD.

2.2. Participants

We recruited 95 participants from the Daan District of Taipei City, Taiwan, through advertisements and assessed their eligibility. For participation, all older adults were screened for eligibility criteria at the National Taiwan Normal University gym. We included individuals who (1) were aged 65–85 years [26], (2) were able to stand and walk without assistance [26], and (3) did not have any history of illness based on their responses to the Physical Activity Readiness Questionnaire (PAR-Q) [27]. We also considered other special health conditions to ensure their safety when participating in fitness interventions. The exclusion criteria were as follows: (1) having hearing or visual impairment or considered not suitable to engage in physical activities in dark environments (2) any comorbidities that would preclude participation, such as a history of stroke or other acute or unstable chronic conditions.
We excluded individuals who (1) were younger than 65 years (n = 1), (2) had health conditions that precluded their participation in the fitness intervention (as stated in the PAR-Q list) (n = 1), or (3) withdrew owing to health concerns regarding the coronavirus disease 2019 pandemic (n = 1). Participants were categorized into two age groups, as defined in previous studies [26]: (1) young-old (65–73 years) and (2) middle-old (74–85 years). A research assistant, not involved in the recruitment process, randomly assigned the eligible participants to either the experimental (EG) or control (CG) group (Figure 1).

2.3. Semi-Immersive VR Exercise Intervention Design

We used the Uniigym Interactive Somatosensory Fitness program (https://www.uniigym.com/) (accessed on 1 August 2020), which won first place in the 2021 5G Innovative Application Competition in Taiwan, as the intervention tool. Uniigym provides a wide array of exercise courses. Participants have the option to select the physical fitness indicator they want to focus on, the body part they want to exercise (e.g., full body, upper body, lower body, hand, back, hips, and/or legs), equipment to use (e.g., elastic rope, chairs, and/or dumbbells), and exercise duration (e.g., 20–30 min, 40–50 min, etc.).
Previous research has defined semi-immersive VR to be the use of a large screen as an output device to create a moderately immersive environment [28]. We implemented the Uniigym program using three large projectors (Panasonic PT-VMZ60T Laser Business Projector, New Taipei City, Taiwan) to display the videos on the walls in a wrap-around manner and create a semi-immersive VR exercise environment. Semi-immersive VR environments are more visually appealing than a non-immersive desktop screen or watching exercise videos on a smartphone. When compared to a fully immersive VR experience, the risk of dizziness and disorientation for older adults is lower. To account for the safety of all older adults participating in the exercises, this study was designed to be non-interactive, with no environmental interaction and no additional monitoring of participants’ body positions and movements. All participants received instructions from a virtual instructor on how to perform the multicomponent physical activities (Figure 2).
During the intervention period, EG participants proceeded to the allocated exercise venues at the university. Before the start of each exercise session, all participants had their heart rate and blood pressure measured with the help of a nurse. A nurse was on site throughout the intervention to handle any arising medical needs. The semi-immersion VR exercise intervention comprised twice-weekly training sessions for 12 weeks. The multicomponent exercise program proceeded as follows: (1) yoga or tai chi and stretching exercises to increase upper- and lower-body flexibility [13], (2) strength training such as martial arts and basic muscle exercises to strengthen the upper (biceps, triceps, and back) and lower (thighs and calves) body to prevent the decline of muscle strength [29], (3) aerobic exercises such as dance and basic boxing (i.e., frequent changes in hand and foot movements) to increase cardiorespiratory fitness [30], and (4) balancing exercises using balls or chairs to improve balance capacity and agility [31]. Each exercise type lasted 15–20 min for an overall session duration of 75–90 min. The types and duration of exercises used during the exercise intervention were selected based on the results of previous studies [10,32,33]. The researchers selected and evaluated each exercise type, its intensity, and its difficulty level before the experiment to confirm its suitability for older adults.
The final study sample exclusively included participants with an attendance rate > 80%, taking into account the effects and benefits of VR exercise interventions on functional fitness.

2.4. Functional Fitness Test

The Senior Fitness Test [10] was performed to assess the participants’ functional fitness. Studies have documented the effectiveness and reliability of this tool [11]. All participants underwent testing in a university exercise classroom. The examiner and assessors were blinded from participant group allocation during the tests. The same functional fitness test items were assessed by the same outcome assessor pre- and post-intervention to ensure measurement validity. A schematic diagram of the functional fitness tests performed by the participants [34] is reported in Supplementary Figure S1. The six test items and their measurement methods were as follows:

2.4.1. Back Scratch Test

This test was used to evaluate upper-body flexibility. Participants were asked to reach over the shoulder with one hand and up the middle of the back with the other, and the distance between the two middle fingers was measured.

2.4.2. Chair Sit-and-Reach Test

This test was used to evaluate lower-body flexibility. Participants were requested to sit on a chair, place one leg straight out, stretch their hands as far as possible in the direction of the toe tips, and hold for 2–3 s, and the distance between the fingers and toes was subsequently measured.

2.4.3. Arm Curl Test

This test was used to evaluate upper-body strength. The number of bicep curls performed in 30 s using the selected arm and hand while holding a weight (men 8 lb.; women 5 lb.) was determined.

2.4.4. Chair Stand Test

This test was used to assess lower-body strength. The number of full stands and returns to a seated position within 30 s with the arms folded across the chest was measured.

2.4.5. 2-Min Step Test

This test was used to evaluate cardiorespiratory fitness. Participants raised each knee to a point midway between the patella and iliac crest. The number of raises completed within 2 min was subsequently recorded.

2.4.6. 8-Foot Up-and-Go Test

This test was used to evaluate agility and dynamic balance. Participants stood up from their seats, walked 8 ft (2.44 m), turned, and walked back to their seated position. Two tests were conducted, and the fastest completion time was recorded.

2.5. Baseline Measurements

Baseline demographic characteristics, such as sex, age, height, and weight, were obtained. The body mass index (BMI) was calculated by dividing weight in kilograms (kg) by height in meters squared (m2) [35].

2.6. Data Analyses

Measurement data were analyzed using SPSS (version 22.0; IBM, Corp., Armonk, NY, USA). Demographic data, such as sex, age, height, weight, and BMI, are expressed as numbers, percentages, and/or mean values (standard deviation [SD]), as appropriate. Between-group differences in baseline characteristics were evaluated using the chi-square (χ2) test and independent t-test for categorical and continuous data, respectively.
To assess the effects of the intervention on the participants’ functional capacity, a two-way repeated measures analysis of variance (ANOVA) test was used to compare the data in terms of group (EG and CG) × time (pre-test vs. post-test). A mixed (4 × 2) repeated measures ANOVA test was used to compare the data in terms of age range group (young-old adults: 65–73 years and middle-old adults: 74–85 years) × group (EG and CG) × time (pre-test vs. post-test). Where significant interactions or main effects were observed, the independent Student’s t-test, paired Student’s t-test, and least significant difference test were applied to a post hoc analysis of the unidirectional effects of between-group and within-group differences. The effect size was computed as partial eta-squared values (η2p: ≥0.01, small; ≥0.06, medium; ≥0.14, large) [36]. Statistical significance was set at p < 0.05.

3. Results

3.1. Participant Characteristics

We removed the data of six enrolled participants who withdrew from the study during the 12-week intervention period. Specifically, four of them (one from the EG and three from the CG) withdrew because of injury and illness, while the other two (both from the EG) withdrew owing to their inability to perform ≥20% of the sessions. Therefore, we exclusively analyzed the data of the remaining 86 participants, including 49 in the young-old group (26 in the EG and 23 in the CG) and 37 in the middle-old group (18 in the EG and 19 in the CG).
Of the young-old adults in the EG, 76.9% were women, with a mean age of 69.11 (SD: 1.97) years, mean height of 157.49 (8.69) cm, mean weight of 56.32 (10.85) kg, and mean BMI of 22.58 (2.99) kg/m2. Of the middle-old adults in the EG, 83.3% were women, with a mean age of 76.11 (2.59) years, mean height of 155.69 (6.59) cm, mean weight of 57.84 (8.57) kg, and mean BMI of 23.81 (2.79) kg/m2. At baseline, no significant differences in sex, height, or weight were noted between young-old and middle-old adults. However, significant age and BMI differences emerged. The participants’ characteristics are shown in Table 1.

3.2. Effects of Semi-Immersive VR Exercise on the Functional Fitness of Older Adults

Table 2 presents the results of the EG and CG. Significant group × time interaction effects were noted in the Back Scratch (F(1, 84) = 9.82, p = 0.002, η2p = 0.11), Arm Curl (F(1, 84) = 21.08, p < 0.001, η2p = 0.20), 2-Minute Step (F(1, 84) = 14.21, p < 0.001, η2p = 0.15), and 8-Foot Up-and-Go (F(1, 84) = 21.54, p < 0.001, η2p = 0.20) Tests. All the functional fitness tests with statistical interaction effects had a large effect size. Furthermore, time had significant main effects on the Back Scratch (F(1, 84) = 16.54, p < 0.001, η2p = 0.17), Chair Sit-and-Reach (F(1, 84) = 9.34, p = 0.003, η2p = 0.10), Arm Curl (F(1, 84) = 18.10, p < 0.001, η2p = 0.17), 2-Minute Step (F(1, 84) = 30.52, p < 0.001, η2p = 0.27), and 8-Foot Up-and-Go (F(1, 84) = 44.03, p < 0.001, η2p = 0.34) Tests.
Post-hoc analyses of the simple main effects indicated that the EG performed better post-test than the CG in the Arm Curl (EG: 22.68 ± 4.97 times, CG: 20.45 ± 3.12 times; t [84] = −2.48, p = 0.015) and 8-Foot Up-and-Go (EG: 5.24 ± 0.86 s, CG: 5.66 ± 0.96 s; t [84] = 2.13, p = 0.037) Tests. In the EG only, the analyses also revealed significant post-test improvements in the Back Scratch (change = 694.59%; t [43] = −5.60, p < 0.001), Arm Curl (change = 12.39%; t [43] = −5.23, p < 0.001), 2-Minute Step (change = 6.33%; t [43] = −5.37, p < 0.001), and 8-Foot Up-and-Go (change = −8.23%; t [43] = 9.06, p < 0.001) Tests (Figure 3).

3.3. Age-Related Effects of Semi-Immersive VR Exercise on Older Adults’ Functional Fitness

Table 3 presents the results of the two groups according to age range. Significant group × time interaction effects between the age groups were exclusively observed in the Chair Sit-and-Reach Test (F(3, 82) = 4.94, p = 0.029, η2p = 0.06). The Chair Sit-and-Reach Test exhibited medium effect sizes, while time exerted significant main effects on the Chair Sit-and-Reach (F(3, 82) = 3.96, p = 0.050, η2p = 0.05), 2-Minute Step (F(3, 82) = 4.70, p = 0.033, η2p = 0.05), and 8-Foot Up-and-Go (F(3, 82) = 13.75, p < 0.001, η2p = 0.15) Tests.
Post hoc analyses indicated no significant pre-test (p = 0.53) and post-test (p = 0.40) differences between age groups in the Chair Sit-and-Reach Test. Additionally, post hoc analyses of the simple main effects indicated that young-old adults in the EG (change = 27.13%; t [25] = −3.31, p = 0.003) and middle-old adults in the CG (change = 10.18%; t [18] = −3.92, p = 0.001) exhibited significant pre- to post-test improvements in the Chair Sit-and-Reach Test (Figure 4).

4. Discussion

This study aimed to investigate the effects of a 12-week VR-based multicomponent exercise program on the functional capacity of young-old and middle-old adults. We established significant increases in upper-body flexibility and strength, cardiorespiratory fitness, and agility/dynamic balance in EG participants compared with those in their CG counterparts. A comparison between the two groups revealed that only the effects on lower-body flexibility varied with age. In the EG, young-old adults exhibited significant improvements in lower-body flexibility; however, their middle-old counterparts did not yield similar results.
This study demonstrated that semi-immersion VR fitness can improve upper-body strength in older adults. Previous research did not examine the effects of VR exercise interventions on upper-body strength in older adults [20,21]. Upper-limb muscle strength is a predictive factor for disability and mortality in older adults [37,38]. Older adults with greater upper-body strength have less fear of falling than those with lesser upper-body strength [39]. A study that focused on home-based martial arts training detected significant improvements in upper-body muscle strength in older adults [40]. This result supports our finding wherein VR semi-immersive exercise interventions, including basic boxing and martial arts content, sufficiently increased upper-body workout opportunities in young-old and middle-old adults. An 8-week Facebook live-streamed exercise program improved cardiorespiratory fitness in older adults [41]. Our results are consistent with those of previous studies. Moreover, our study revealed that VR multicomponent exercise improves balance in older adults. Although our study’s intervention time was relatively short (i.e., 12 weeks), it still yielded similar results to traditional exercise (i.e., 9 months), according to Seco [17]. This demonstrates the positive effects of VR-based exercise on improving cardiorespiratory fitness and balance.
In this study, the semi-immersive VR exercise intervention used an appropriate intervention period and exercise time to enhance functional fitness in young-old and middle-old adults [42,43]. Semi-immersive VR visual feedback technology enhances the context of the fitness moment, rendering the exercise process lively and more engaging for older adults. In addition, a screen with bright colors and lively rhythmic guidance further motivates older adults to exercise. Nevertheless, no significant differences in upper-body muscle strength, cardiorespiratory fitness, or balance were noted between the age groups after the exercise intervention. However, functional capacity declined with age [15]. Therefore, elucidating age-group differences remains important.
In another study, a 6-week VR exercise program exerted positive effects on upper-body flexibility in older adults, broadly aligning with our findings [20]. However, at the end of the 12-week VR exercise program, significant improvements in lower-body flexibility were exclusively detected in young-old participants of the EG, whereas no significant changes were observed in their middle-old counterparts. This study revealed a difference in lower-body flexibility between young-old and middle-old adults after the semi-immersive VR exercise intervention. This result may have crucial implications. Nonetheless, post hoc analysis revealed a significant pre- to post-test improvement in the Chair Sit-and-Reach Test in middle-old adults of the CG, a phenomenon potentially emanating from familiarity with the test. A previous study on participants aged 55–85 years demonstrated that joint flexibility significantly declines after the age of 70 [44], and mobility decreases with age [44,45]. Stretching has been the focus of other studies on exercise programs [46,47], demonstrating a more effective improvement in the flexibility of the knee flexors and extensors in older adults. Furthermore, basic daily activities like walking, cleaning, and gardening require lower-body flexibility, underscoring the need for older adults to maintain this flexibility. Therefore, for middle-old adults, increasing the duration or frequency of lower-body stretching is recommended in future exercise interventions to improve lower-body functional capacity.
We detected no significant improvements in the lower-body strength of any of the participants. According to previous studies, 65-year-old participants who underwent an 8-week, individualized VR program [21] and those who participated in live-streaming-guided exercises [41] demonstrated increased lower-body muscle performance, exhibiting inconsistency with our findings. This evidence indicates that individualized and guided exercises [21,41] may surpass semi-immersive VR exercises in increasing muscular strength in older adults. However, all the participants in our EG outperformed those in a large Taiwanese study [48] in terms of post-test scores of lower-body strength. Therefore, we recommend that future research include additional instruction or equipment to improve and maintain lower-body muscle strength in older adults.
Age potentially affects physical activity levels and functional fitness [49,50,51] and contributes to a decline in overall physical health. Similar short-term VR exercise intervention studies do not provide a detailed understanding of different age groups [20,21,22]. This study is the first to compare functional fitness in healthy older adults across different age ranges using a technology-based program. However, the present study has its limitations. Six of the initial 92 participants did not complete the exercise intervention owing to personal reasons, yielding an adherence rate of 93% (86/92). The study population falls within a reasonable range to yield statistically meaningful results. Since this study was designed to be conducted in a dark exercise space, the sample size of our middle-old adults was relatively small out of consideration of participant safety. It was calculated based on a previous study [52], and an appropriate sample size was achieved. However, this study’s sample distribution ratio suggests that we should interpret the observed enhanced functional fitness between age groups cautiously. Nevertheless, we believe that this study’s findings still hold value for understanding the positive effects of semi-immersion VR exercise on older adults of different ages.

5. Conclusions

This study explored the effects of a 12-week virtual reality-based multicomponent intervention on the functional capacity of older adults in different age groups. Our program improved the functional capacity of young-old and middle-old adults in upper-body flexibility and strength, cardiorespiratory fitness, and agility/dynamic balance. However, only young-old adults exhibited significant improvements in lower-body flexibility. Our findings offer valuable insights for semi-immersion VR technology-based exercise interventions for different age groups. The findings of this study can support future product developers in designing age-specific exercise training programs. A wider availability of such programs may increase the likelihood of older adults of different ages participating in these programs, therefore enhancing their functional capacity. This study can also serve as a reference for relevant health departments and community units that aim to promote sports technology geared toward enhancing the functional health of older adults.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/mti8080067/s1. Supplementary Figure S1. Schematic of the functional fitness tests (A) Back Scratch Test. (B) Chair Sit-and-Reach Test. (C) Arm Curl Test. (D) Chair Stand Test. (E) 2-Minute Step Test. (F) 8-Foot Up-and-Go Test.

Author Contributions

Study concept and design: L.-T.W. and S.-H.C.; Acquisition of data: L.-T.W.; Analysis and interpretation of data: L.-T.W. and S.-H.C.; Drafting of the manuscript: L.-T.W. and S.-H.C.; Critical revision of the manuscript for important intellectual content: Y.L. and J.-H.P. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by a grant from the National Science and Technology Council of Taiwan (NSTC 109-2410-H-003-035-) as well as a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2022M3E8A1077761). All authors have no relevant financial or non-financial interests to disclose.

Institutional Review Board Statement

This study was approved by the National Taiwan Normal University (201912HM099) and the trial was registered with ClinicalTrials.Gov (NCT05582863).

Informed Consent Statement

All procedures of the study were conducted in accordance with the Declaration of Helsinki. We obtained written and verbal informed consent from all participants.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Acknowledgments

I would like to thank all participants and assistants for their time, support, and dedication.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

  1. World Health Organization. Ageing and Health. 2015. Available online: https://www.who.int/news-room/fact-sheets/detail/ageing-and-health (accessed on 15 January 2023).
  2. National Development Council. Popluation Projections for Republic of China (Taiwan): 2018–2065. 2018. Available online: https://www.ndc.gov.tw/News_Content.aspx?n=114AAE178CD95D4C&sms=DF717169EA26F1A3&s=E1EC042108072B67 (accessed on 23 January 2023).
  3. Nylen, E.S.; Kokkinos, P.; Myers, J.; Faselis, C. Prognostic effect of exercise capacity on mortality in older adults with diabetes mellitus. J. Am. Geriatr. Soc. 2010, 58, 1850–1854. [Google Scholar] [CrossRef] [PubMed]
  4. Fulop, T.; Larbi, A.; Witkowski, J.M.; McElhaney, J.; Loeb, M.; Mitnitski, A.; Pawelec, G. Aging, frailty and age-related diseases. Biogerontology 2010, 11, 547–563. [Google Scholar] [CrossRef] [PubMed]
  5. Lunenfeld, B.; Stratton, P. The clinical consequences of an ageing world and preventive strategies. Best Pract. Res. Clin. Obstet. Gynaecol. 2013, 27, 643–659. [Google Scholar] [CrossRef] [PubMed]
  6. McPhee, J.S.; French, D.P.; Jackson, D.; Nazroo, J.; Pendleton, N.; Degens, H. Physical activity in older age: Perspectives for healthy ageing and frailty. Biogerontology 2016, 17, 567–580. [Google Scholar] [CrossRef]
  7. Jeoung, B.; Pyun, D.Y. Investigating functional fitness of older adults in Korea in the period 2013–2018. Sci. Rep. 2022, 12, 6073. [Google Scholar] [CrossRef]
  8. Haripriya, S.; Kumar, D.; Samuel, S.E.; Soman, A. Effect of a multi-component exercise program on functional mobility, exercise capacity and quality of life in older adults. J. Clin. Diagn. Res. 2018, 12, 1. [Google Scholar] [CrossRef]
  9. Ignasiak, Z.; Sebastjan, A.; Sławińska, T.; Skrzek, A.; Czarny, W.; Król, P.; Rzepko, M.; Duda-Biernacka, B.; Marchewka, A.; Filar-Mierzwa, K. Functional fitness normative values for elderly polish population. BMC Geriatr. 2020, 20, 384. [Google Scholar] [CrossRef] [PubMed]
  10. Rikli, R.E.; Jones, C.J. Development and validation of a functional fitness test for community-residing older adults. J. Aging Phys. Act. 1999, 7, 129–161. [Google Scholar] [CrossRef]
  11. Rikli, R.E.; Jones, C.J. Senior Fitness Test Manual, 2nd ed.; Human Kinetics: Champaign, IL, USA, 2013. [Google Scholar]
  12. Lin, S.F.; Sung, H.C.; Li, T.L.; Hsieh, T.C.; Lan, H.C.; Perng, S.J.; Smith, G.D. The effects of tai-chi in conjunction with thera-band resistance exercise on functional fitness and muscle strength among community-based older people. J. Clin. Nurs. 2015, 24, 1357–1366. [Google Scholar] [CrossRef]
  13. Noradechanunt, C.; Worsley, A.; Groeller, H. Thai Yoga improves physical function and well-being in older adults: A randomised controlled trial. J. Sci. Med. Sport 2017, 20, 494–501. [Google Scholar] [CrossRef]
  14. Rodrigues, F.; Amaro, N.; Matos, R.; Mendes, D.; Monteiro, D.; Morouço, P. The impact of an exercise intervention using low-cost equipment on functional fitness in the community-dwelling older adults: A pilot study. Front. Physiol. 2022, 13, 1039131. [Google Scholar] [CrossRef] [PubMed]
  15. Chung, P.-K.; Zhao, Y.; Liu, J.-D.; Quach, B. Functional fitness norms for community-dwelling older adults in Hong Kong. Arch. Gerontol. Geriatr. 2016, 65, 54–62. [Google Scholar] [CrossRef] [PubMed]
  16. Toraman, N.F.; Erman, A.; Agyar, E. Effects of multicomponent training on functional fitness in older adults. J. Aging Phys. Act. 2004, 12, 538–553. [Google Scholar] [CrossRef] [PubMed]
  17. Seco, J.; Abecia, L.C.; Echevarría, E.; Barbero, I.; Torres-Unda, J.; Rodriguez, V.; Calvo, J.I. A long-term physical activity training program increases strength and flexibility, and improves balance in older adults. Rehabil. Nurs. 2013, 38, 37–47. [Google Scholar] [CrossRef]
  18. Lintonen, T.; Konu, A.; Seedhouse, D. Information technology in health promotion. Health Educ. Res. 2008, 23, 560–566. [Google Scholar] [CrossRef] [PubMed]
  19. Gao, Z.; Lee, J.E.; McDonough, D.J.; Albers, C. Virtual reality exercise as a coping strategy for health and wellness promotion in older adults during the COVID-19 pandemic. J. Clin. Med. 2020, 9, 1986. [Google Scholar] [CrossRef]
  20. Barsasella, D.; Liu, M.F.; Malwade, S.; Galvin, C.J.; Dhar, E.; Chang, C.-C.; Li, Y.-C.J.; Syed-Abdul, S. Effects of virtual reality sessions on the quality of life, happiness, and functional fitness among the older people: A randomized controlled trial from Taiwan. Comput. Methods Programs Biomed. 2021, 200, 105892. [Google Scholar] [CrossRef] [PubMed]
  21. Lee, M.; Son, J.; Kim, J.; Yoon, B. Individualized feedback-based virtual reality exercise improves older women’s self-perceived health: A randomized controlled trial. Arch. Gerontol. Geriatr. 2015, 61, 154–160. [Google Scholar] [CrossRef] [PubMed]
  22. Wang, L.-T. Effectiveness of Virtual Reality Exercise for Functional Fitness in Community-Dwelling Older Adults: A 12-Week Follow-Up Study. SAGE Open 2023, 13, 21582440231218515. [Google Scholar] [CrossRef]
  23. Bevilacqua, R.; Maranesi, E.; Riccardi, G.R.; Di Donna, V.; Pelliccioni, P.; Luzi, R.; Lattanzio, F.; Pelliccioni, G. Non-immersive virtual reality for rehabilitation of the older people: A systematic review into efficacy and effectiveness. J. Clin. Med. 2019, 8, 1882. [Google Scholar] [CrossRef]
  24. Buchner, A.; Erdfelder, E.; Faul, F. G*Power: R: Statistical Power Analyses for Mac and Windows. 2001. Available online: https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower (accessed on 23 January 2023).
  25. Cohen, J. Statistical Power Analysis for the Behavioral Sciences, 2nd ed.; Erbaum Press: Hillsdale, NJ, USA, 1988. [Google Scholar]
  26. Gouveia, B.R.; Gouveia, É.R.; Ihle, A.; Jardim, H.G.; Martins, M.M.; Freitas, D.L.; Kliegel, M. The effect of the ProBalance Programme on health-related quality of life of community-dwelling older adults: A randomised controlled trial. Arch. Gerontol. Geriatr. 2018, 74, 26–31. [Google Scholar] [CrossRef] [PubMed]
  27. Shephard, R.J. PAR-Q, Canadian Home Fitness Test and exercise screening alternatives. Sports Med. 1988, 5, 185–195. [Google Scholar] [CrossRef] [PubMed]
  28. Mujber, T.S.; Szecsi, T.; Hashmi, M.S. Virtual reality applications in manufacturing process simulation. J. Mater. Process. Technol. 2004, 155, 1834–1838. [Google Scholar] [CrossRef]
  29. Bates, A.; Donaldson, A.; Lloyd, B.; Castell, S.; Krolik, P.; Coleman, R. Staying alive, staying strong: Pilot evaluation of a once-weekly community-based strength training program for older adults. Health Promot. J. Aust. 2009, 20, 42–47. [Google Scholar] [CrossRef]
  30. Aksović, N.; Bjelica, B.; Joksimović, M.; Skrypchenko, I.; Filipović, S.; Milanović, F.; Pavlović, B.; Ćorluka, B.; Pržulj, R. Effects of aerobic physical activity to cardio-respiratory fitness of the elderly population: Systematic overview. Pedagog. Phys. Cult. Sports 2020, 24, 208–218. [Google Scholar] [CrossRef]
  31. Jacobson, B.H.; Thompson, B.; Wallace, T.; Brown, L.; Rial, C. Independent static balance training contributes to increased stability and functional capacity in community-dwelling elderly people: A randomized controlled trial. Clin. Rehabil. 2011, 25, 549–556. [Google Scholar] [CrossRef] [PubMed]
  32. Chodzko-Zajko, W.J.; Proctor, D.N.; Singh, M.A.F.; Minson, C.T.; Nigg, C.R.; Salem, G.J.; Skinner, J.S. Exercise and Physical Activity for Older Adults. Med. Sci. Sports Exerc. 2009, 41, 1510–1530. [Google Scholar] [CrossRef]
  33. U.S. Department of Health and Human Services. Physical Activity Guidelines for Americans, 2nd ed.; U.S. Department of Health and Human Services: Washington, DC, USA, 2018.
  34. Lin, K.-F.; Chu, C.-Y.; Fu, L.-L.; Liu, J.-C.; Peng, H.-Y. (Eds.) Senior Fitness Test Manual, 2nd ed.; Hua-teng.: Taipei, Taiwan, 2013. [Google Scholar]
  35. Health Promotion Administration. Body Mass Index Test. 2020. Available online: https://health99.hpa.gov.tw/OnlinkHealth/Onlink_BMI.aspx (accessed on 23 January 2023).
  36. Cohen, J. Statistical Power Analysis for the Behavioral Sciences; Routledge: New York, NY, USA, 2013. [Google Scholar]
  37. Bohannon, R.W. Hand-grip dynamometry predicts future outcomes in aging adults. J. Geriatr. Phys. Ther. 2008, 31, 3–10. [Google Scholar] [CrossRef] [PubMed]
  38. Chainani, V.; Shaharyar, S.; Dave, K.; Choksi, V.; Ravindranathan, S.; Hanno, R.; Jamal, O.; Abdo, A.; Abi Rafeh, N. Objective measures of the frailty syndrome (hand grip strength and gait speed) and cardiovascular mortality: A systematic review. Int. J. Cardiol. 2016, 215, 487–493. [Google Scholar] [CrossRef]
  39. Yardimci, B.; Akdeniz, M.; Demir, T. The correlation between fear of falling and upper extremity muscle strength. Saudi Med. J. 2021, 42, 411. [Google Scholar] [CrossRef]
  40. Fong, S.S.; Ng, S.S.; Cheng, Y.T.; Wong, J.Y.; Yu, E.Y.; Chow, G.C.; Chak, Y.T.; Chan, I.K.; Zhang, J.; Macfarlane, D. Effects of Ving Tsun Chinese martial art training on upper extremity muscle strength and eye-hand coordination in community-dwelling middle-aged and older adults: A pilot study. Evid.-Based Complement. Altern. Med. 2016, 2016, 4013989. [Google Scholar] [CrossRef] [PubMed]
  41. Chang, S.-H.; Wang, L.-T.; Chueh, T.-Y.; Hsueh, M.-C.; Hung, T.-M.; Wang, Y.-W. Effectiveness of Facebook Remote Live-Streaming-Guided Exercise for Improving the Functional Fitness of Community-Dwelling Older Adults. Front. Med. 2021, 8, 734812. [Google Scholar] [CrossRef] [PubMed]
  42. Liu, M.; Zhou, K.; Chen, Y.; Zhou, L.; Bao, D.; Zhou, J. Is virtual reality training more effective than traditional physical training on balance and functional mobility in healthy older adults? A systematic review and meta-analysis. Front. Hum. Neurosci. 2022, 16, 843481. [Google Scholar] [CrossRef] [PubMed]
  43. Deng, N.; Soh, K.G.; Abdullah, B.B.; Tan, H.; Huang, D. Active video games for improving health-related physical fitness in older adults: A systematic review and meta-analysis. Front. Public Health 2024, 12, 1345244. [Google Scholar] [CrossRef] [PubMed]
  44. Stathokostas, L.; McDonald, M.W.; Little, R.; Paterson, D.H. Flexibility of older adults aged 55–86 years and the influence of physical activity. J. Aging Res. 2013, 2013, 743843. [Google Scholar] [CrossRef] [PubMed]
  45. Nonaka, H.; Mita, K.; Watakabe, M.; Akataki, K.; Suzuki, N.; Okuwa, T.; Yabe, K. Age-related changes in the interactive mobility of the hip and knee joints: A geometrical analysis. Gait Posture 2002, 15, 236–243. [Google Scholar] [CrossRef] [PubMed]
  46. Gallon, D.; Rodacki, A.; Hernandez, S.; Drabovski, B.; Outi, T.; Bittencourt, L.; Gomes, A. The effects of stretching on the flexibility, muscle performance and functionality of institutionalized older women. Braz. J. Med. Biol. Res. 2011, 44, 229–235. [Google Scholar] [CrossRef] [PubMed]
  47. Batista, L.H.; Vilar, A.C.; de Almeida Ferreira, J.J.; Rebelatto, J.R.; Salvini, T.F. Active stretching improves flexibility, joint torque, and functional mobility in older women. Am. J. Phys. Med. Rehabil. 2009, 88, 815–822. [Google Scholar] [CrossRef] [PubMed]
  48. Ho, H.-H.; Fang, I.-Y.; Yu, Y.-C.; Huang, Y.-P.; Kuo, I.-L.; Wang, L.-T.; Tsai, M.-C.; Chang, S.-H.; Hsueh, M.-C. Is functional fitness performance a useful predictor of risk of falls among community-dwelling older adults? Arch. Public Health 2021, 79, 108. [Google Scholar] [CrossRef]
  49. Riebe, D.; Blissmer, B.J.; Greaney, M.L.; Ewing Garber, C.; Lees, F.D.; Clark, P.G. The relationship between obesity, physical activity, and physical function in older adults. J. Aging Health 2009, 21, 1159–1178. [Google Scholar] [CrossRef]
  50. Donat Tuna, H.; Ozcan Edeer, A.; Malkoc, M.; Aksakoglu, G. Effect of age and physical activity level on functional fitness in older adults. Eur. Rev. Aging Phys. Act. 2009, 6, 99–106. [Google Scholar] [CrossRef]
  51. Milanović, Z.; Pantelić, S.; Trajković, N.; Sporiš, G.; Kostić, R.; James, N. Age-related decrease in physical activity and functional fitness among elderly men and women. Clin. Interv. Aging 2013, 8, 549. [Google Scholar] [CrossRef] [PubMed]
  52. Kim, S.-W.; Park, H.-Y.; Jung, W.-S.; Lim, K. Effects of Twenty-Four Weeks of Resistance Exercise Training on Body Composition, Bone Mineral Density, Functional Fitness and Isokinetic Muscle Strength in Obese Older Women: A Randomized Controlled Trial. Int. J. Environ. Res. Public Health 2022, 19, 14554. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. Study flow diagram.
Figure 1. Study flow diagram.
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Figure 2. Semi-immersion Virtual reality (VR)-based exercise intervention (A) Instructor on a virtual exercise conferencing display. (B) Equipment used to project semi-immersion VR exercises. (C) Photograph of participants performing the exercises.
Figure 2. Semi-immersion Virtual reality (VR)-based exercise intervention (A) Instructor on a virtual exercise conferencing display. (B) Equipment used to project semi-immersion VR exercises. (C) Photograph of participants performing the exercises.
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Figure 3. Comparison of pre-to post-test functional capacity change between the experimental and control groups of older adults.
Figure 3. Comparison of pre-to post-test functional capacity change between the experimental and control groups of older adults.
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Figure 4. Comparison of pre-to post-test functional capacity change between the experimental and control groups of different age groups.
Figure 4. Comparison of pre-to post-test functional capacity change between the experimental and control groups of different age groups.
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Table 1. Baseline characteristics of participants in the different age and intervention groups.
Table 1. Baseline characteristics of participants in the different age and intervention groups.
VariableYoung-Old Adults
(65–73 Years)		Middle-Old Adults
(74–85 Years)		p
Experimental
(n = 26)		Control
(n = 23)		Experimental
(n = 18)		Control
(n = 19)
Sex (male/female), n (%) a6 (23.1)/
20 (76.9)		6 (26.1)/
17 (73.9)		3 (16.7)/
15 (83.3)		3 (15.8)/
16 (84.2)		0.25
Age, M (SD) b69.11 (1.97)68.82 (2.48)76.11 (2.59)75.16 (1.21)<0.001 ***
Height (cm), M (SD) b157.49 (8.69)158.52 (6.44)155.69 (6.59)156.95 (4.93)0.26
Weight (kg), M (SD) b56.32 (10.85)56.74 (11.30)57.84 (8.57)59.59 (9.65)0.32
BMI (kg/m2), M (SD) b22.58 (2.99)22.48 (3.75)23.81 (2.79)24.17 (3.62)0.044 *
Number of people (percentage); BMI, body mass index; M (SD), mean (standard deviation). a Analyzed using the chi-square test; b Analyzed using the independent t-test. * p < 0.05; *** p < 0.001.
Table 2. Effects of semi-immersive VR exercise on the functional fitness of participants.
Table 2. Effects of semi-immersive VR exercise on the functional fitness of participants.
Outcome MeasureOlder Adults
(65–85 Years)		Two-Way Repeated-Measure ANOVA
Experimental
(n = 44)		Control
(n = 42)		F-Value, p (η2p)
PrePostPrePostGroupTimeInteraction
M (SD)M (SD)
Back Scratch Test
(cm)		0.37
(7.25)		2.94
(7.04)		1.71
(5.57)		2.05
(5.95)		0.030.87(0.00)16.54
***		<0.001(0.17)9.82
**		0.002(0.11)
Chair Sit-and-Reach Test (cm)6.58
(7.66)		7.53
(6.97)		5.96
(5.30)		6.36
(5.45)		0.430.52(0.01)9.34
**		0.003(0.10)1.620.21(0.02)
Arm Curl Test
(times)		20.18
(3.14)		22.68 #
(4.97)		20.55
(2.63)		20.45
(3.12)		1.670.20(0.02)18.10
***		<0.001(0.17)21.08
***		<0.001(0.20)
Chair Stand Test
(times)		19.86
(3.76)		20.09
(4.60)		18.57
(3.47)		19.14
(3.59)		2.050.16(0.02)1.710.19(0.02)0.320.57(0.00)
2-Minute Step Test
(times)		101.57
(6.89)		108.00
(9.22)		107.55
(12.08)		108.76
(13.05)		2.420.12(0.03)30.52
***		<0.001(0.27)14.21
***		<0.001(0.15)
8-Foot Up-and-Go Test (s)5.71
(0.79)		5.24 #
(0.86)		5.74
(1.02)		5.66
(0.96)		1.370.25(0.02)44.03
***		<0.001(0.34)21.54
***		<0.001(0.20)
Note. A lower 8-Foot Up-and-Go Test score indicates better performance. M (SD), mean (standard deviation). Significant difference between the experimental and control groups: # p < 0.05; significant interaction or main effect: ** p < 0.01, *** p < 0.001.
Table 3. Age-related effects of semi-immersive VR exercise on functional fitness.
Table 3. Age-related effects of semi-immersive VR exercise on functional fitness.
Outcome MeasureYounger-Old Adults
(65–73 Years)		Middle-Old Adults
(74–85 Years)		A Mix (4 × 2) Repeated-Measure ANOVA
Experimental
(n = 26)		Control
(n = 23)		Experimental
(n = 18)		Control
(n = 19)		F-Value, p (η2p)
PrePostPrePostPrePostPrePostGroupTimeInteraction
M (SD)M (SD)M (SD)M (SD)
Back Scratch Test (cm)1.12
(6.96)		3.80
(6.56)		2.35
(4.83)		3.35
(5.47)		0.71
(7.72)		1.69
(7.69)		0.95
(6.40)		0.47
(6.28)		0.000.95(0.00)1.490.22(0.02)0.670.42(0.01)
Chair Sit-and-Reach Test (cm)6.23
(7.44)		7.92
(7.01)		7.24
(4.44)		7.59
(4.98)		7.08
(8.16)		6.97
(7.08)		4.42
(5.95)		4.87
(5.75)		0.960.33(0.01)3.96
*		0.050(0.05)4.94
*		0.029(0.06)
Arm Curl Test (times)20.73
(3.52)		23.42
(4.67)		20.83
(2.52)		20.78
(3.19)		19.39
(2.38)		21.61
(5.34)		20.21
(2.80)		20.05
(3.06)		0.390.54(0.01)0.260.61(0.00)0.100.76(0.00)
Chair Stand Test (times)20.00
(3.77)		20.85
(4.58)		19.04
(3.83)		19.48
(3.92)		19.67
(3.85)		19.00
(4.54)		18.00
(2.98)		18.74
(3.23)		0.020.91(0.90)0.980.33(0.01)2.200.14(0.03)
2-Minute Step Test (times)102.00
(5.71)		109.85
(8.14)		109.52
(11.31)		111.87
(12.08)		100.95
(8.45)		105.33
(10.25)		105.16
(12.85)		105.00
(13.50)		0.430.51(0.01)4.70
*		0.033(0.05)0.120.73(0.00)
8-Foot Up-and-Go Test (s)5.74
(0.88)		5.11
(0.93)		5.65
(0.94)		5.47
(0.84)		5.66
(0.67)		5.42
(0.73)		5.92
(1.10)		5.94
(1.04)		0.630.43(0.01)13.75
***		<0.001(0.15)1.590.21(0.02)
Note. A lower 8-Foot Up-and-Go Test score indicates better performance. M (SD), mean (standard deviation). Significant interaction or main effect: * p < 0.05, *** p < 0.001.
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Wang, L.-T.; Liao, Y.; Chang, S.-H.; Park, J.-H. Effects of a 12-Week Semi-Immersion Virtual Reality-Based Multicomponent Intervention on the Functional Capacity of Older Adults in Different Age Groups: A Randomized Control Trial. Multimodal Technol. Interact. 2024, 8, 67. https://doi.org/10.3390/mti8080067

AMA Style

Wang L-T, Liao Y, Chang S-H, Park J-H. Effects of a 12-Week Semi-Immersion Virtual Reality-Based Multicomponent Intervention on the Functional Capacity of Older Adults in Different Age Groups: A Randomized Control Trial. Multimodal Technologies and Interaction. 2024; 8(8):67. https://doi.org/10.3390/mti8080067

Chicago/Turabian Style

Wang, Li-Ting, Yung Liao, Shao-Hsi Chang, and Jong-Hwan Park. 2024. "Effects of a 12-Week Semi-Immersion Virtual Reality-Based Multicomponent Intervention on the Functional Capacity of Older Adults in Different Age Groups: A Randomized Control Trial" Multimodal Technologies and Interaction 8, no. 8: 67. https://doi.org/10.3390/mti8080067

APA Style

Wang, L.-T., Liao, Y., Chang, S.-H., & Park, J.-H. (2024). Effects of a 12-Week Semi-Immersion Virtual Reality-Based Multicomponent Intervention on the Functional Capacity of Older Adults in Different Age Groups: A Randomized Control Trial. Multimodal Technologies and Interaction, 8(8), 67. https://doi.org/10.3390/mti8080067

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