Accepted Manuscript Title: Individualized feedback-based virtual reality exercise improves older women’s self-perceived health: a randomized controlled trial Author: Minyoung Lee Jaebum Son Jungjin Kim BumChul Yoon PII: DOI: Reference:

S0167-4943(15)30014-5 http://dx.doi.org/doi:10.1016/j.archger.2015.06.010 AGG 3179

To appear in:

Archives of Gerontology and Geriatrics

Received date: Revised date: Accepted date:

28-10-2014 12-6-2015 17-6-2015

Please cite this article as: Lee, Minyoung, Son, Jaebum, Kim, Jungjin, Yoon, BumChul, Individualized feedback-based virtual reality exercise improves older women’s selfperceived health: a randomized controlled trial.Archives of Gerontology and Geriatrics http://dx.doi.org/10.1016/j.archger.2015.06.010 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Individualized feedback-based virtual reality exercise improves older women’s self-perceived health: a randomized controlled trial Minyoung Leea Jaebum Son b Jungjin Kim a BumChul Yoon a,* [email protected] a

Department of Physical Therapy, College of Health Science, Korea University, Seoul, South Korea

Department of Physical Therapy, College of Health Science, Korea University, Seoul, South Korea b

Department of Biomedical Engineering, University of Los Andes, Bogotá, Colombia

Department of Biomedical Engineering, University of Los Andes, Bogotá, Colombia *

Corresponding author at: Department of Physical Therapy, College of Health Sciences, Korea University, 161 Jeongneungro, Sungbuk-Gu, Seoul 136-703, Republic of Korea. Tel: +8229402833; Fax: +8229402830. Highlights 

We studied the effect of virtual reality exercise on older women’s self-perceived health.



Participants’ health-related quality of life was significantly improved.



Physical fitness was also improved.



Therefore, it is recommendable to older women as a self-management strategy.

ABSTRACT Objectives: Individualized feedback-based virtual reality (IFVR) exercise is gaining attention as a cost-effective self-management strategy, however little is known about whether older adults themselves perceive IFVR exercise effective in improving their health. Therefore, we studied the effect of IFVR exercise on health-related quality of life (HRQoL) in older women.

Methods: Fifty-four older women aged ≥ 65 years were randomized to either IFVR exercise group (IFVRG, n = 26) or group-based exercise group (GG, n = 28). Both groups received a 60-minute intervention three times a week for eight weeks. The Short-Form Health Survey (SF-36) was administered. To identify the possible placebo effect, 30-Second Chair Stand Test (30SCST), 8-Foot Upand-Go Test (8FUGT), and 2-Minute Step Test (2MST) were also administered. Results: intention-to-treat analysis with adjustment for baseline levels revealed that IFVRG showed greater improvement in mental health (p = 0.029) and lower body strength (p = 0.042), compared to GG. Within-group analysis for HRQoL revealed that IFVRG showed an increase in role-physical (p = 0.015), bodily pain (p = 0.017), general health (p = 0.004), vitality (p = 0.010), roleemotional (p = 0.007), and mental health (p < 0.001), whereas GG showed an increase in role-physical (p = 0.022), general health (p = 0.023), and social functioning (p = 0.023). Both groups showed an increase in 30SCST, 2MST and 8FUGT (all p < 0.001). Conclusion: IFVR exercise improved HRQoL in older women, in addition to improving physical fitness. Therefore, it might be recommended to older women as an effective self-management strategy.

Keywords: Virtual reality, Quality of life, Mental health, Physical fitness, Older adult 1. Introduction Individualized feedback-based virtual reality (IFVR) is an immersive form of interactive media, incorporating individualized visual and auditory feedback (Sherry, 2004). IFVR technology reflects individuals’ movements onscreen with visual and auditory feedback and thus allows individuals to recognize their own level of performance and adjust their posture or center of gravity for

themselves, minimizing the need for supervision by a health care professional (Jorgensen, Laessoe, Hendriksen, Nielsen, & Aagaard, 2013). These characteristics of IFVR have facilitated researchers to explore IFVR-led physical activity in a home setting (Miller et al., 2014). In particular, studies in geriatrics and gerontology have focused on the effects of IFVR exercise on “physical health,” and have shown that IFVR exercise is effective in improving balance and lower body strength in older adults (Agmon, Perry, Phelan, Demiris, & Nguyen, 2011; Duque et al., 2013; Jorgensen et al., 2013; Kim, Son, Ko, & Yoon, 2013; Miller et al., 2014; Rendon et al., 2012; Williams, Doherty, Bender, Mattox, & Tibbs, 2011). However, it is not known whether older adults themselves perceive IFVR as an effective way to improve their health. According to the health belief model, one of the most widely used in the public health theoretical framework, an individual’s self-perceived value of an activity helps to determine the level of self-management, as well as the expected outcomes of the activity (Glanz K, 1997; Rosenstock, Strecher, & Becker, 1988; Shillitoe & Christie, 1989). Therefore, for IFVR to be used as an effective self-management strategy in older adults, it is important to verify if older adults perceive it to be an effective way to improve their health. Meanwhile, older adults seem to regard successful aging as a multidimensional concept, encompassing physical, functional, psychological and social health (Depp, Vahia, & Jeste, 2010; Phelan, Anderson, LaCroix, & Larson, 2004), all of which are important aspects of health-related quality of life (HRQoL) (Pavot & Diener, 1993; Spilker, 1984). Further, subjective HRQoL is regarded as more important than are objective measures of physical health in older adults (Depp et al., 2010; Montross et al., 2006). Hence, knowing the effects of IFVR exercise on HRQoL would help to identify whether older adults perceive IFVR exercise as a meaningful

and effective way to improve their health, and thereby contribute to successful aging. Until now, very few studies have looked at the effect of IFVR exercise on HRQoL (Rosenberg et al., 2010; Studenski et al., 2010), and those have measured HRQoL using only summary scores and lacked a control group, thereby having a high risk of bias. Thus, we performed a randomized controlled trial (RCT) to determine if IFVR exercise is effective in improving HRQoL in older women when compared to group-based exercise. In addition, we examined its effect on physical fitness to identify any possible placebo effects, and to add robust evidence to the results of previous studies that analyzed the effect of IFVR exercise on physical health using case studies (Agmon et al., 2011; Studenski et al., 2010; Williams et al., 2011), or comparisons with non-exercise groups (so had a risk of bias) (Duque et al., 2013; Jorgensen et al., 2013; Kim et al., 2013; Rendon et al., 2012).

2. Methods 2.1. Study design and participants A total of 96 participants were recruited in Seongbuk (Seoul, South Korea) and assessed for their eligibility; this resulted in 42 being excluded from the study, resulting in 54 enrolled participants. The inclusion criteria were: (1) ability to stand independently; (2) scores of >23 on the Mini-Mental State Examination (MMSE) (Crum, Anthony, Bassett, & Folstein, 1993). Based on health condition questionnaire completed by participants, the exclusion criteria were: (1) listening/vision impairments; (2) a history of orthopedic or neurological surgery; (3) suffering from dementia, headaches, or dizziness. Approval for the study was obtained from the Institutional Review Board of Korea University. Written informed consent was obtained from all participants following the declaration of Helsinki.

2.2. Randomization Eligible participants were randomly assigned to either the IFVR group (IFVRG) or the group-based exercise group (GG) by a research assistant who was not involved with participant recruitment. The random assignment schedule was generated using an online random number generator (www.random.org). The research assistant contacted participants by telephone and informed them of their group allocation. 2.3. Apparatus To create an IFVR environment, a motion capture sensor (KINECT, Microsoft Inc, WA, US), a main console (Xbox 360, Microsoft Inc, WA, US), and a 1625.6 mm monitor screen (PN64D8000FF, Samsung Inc, Cheonan, South Korea) were used. The motion capture sensor captured 20 body segments of participants (e.g., head, trunk, shoulder, elbow, wrist, hip, knee and ankle), tracked their movements continuously and translated their movements into on-screen action. Thus, participants could see their own 3dimensional avatar on the monitor screen without any controller.

2.4.

Intervention During the intervention period, participants of each group were asked come to exercise rooms located in different places in the

university, so that they were blinded to each other’s intervention. On the first day of intervention, researchers gave information on the exercise program to each of the two groups. Each IFVRG participant made reservations with researchers so that the individualized

IFVR exercise could be conducted at a convenient time. One research assistant stood by participants to take attendance and prepare for emergencies during the intervention, but did not interact with them. For the GG, exercise classes were held at fixed times and led by a certified physiotherapist with over three years of clinical experience. All participants completed a 60-minute exercise program three times a week for eight weeks, including five-minute warm-up and cool-down exercises. A five-minute break was given 30 minutes into the program. As a detailed description of the IFVRG intervention has been provided elsewhere (Kim et al., 2013), only an overview is outlined here. From the Your Shape Fitness Evolved software (Ubisoft Inc, Surrey, UK), “Zen Energy” was chosen as an exercise program for the IFVRG since the included motions were based on tai chi, and thus were optimized for balance and lower extremity training for older adults (Taylor et al., 2012; Tousignant et al., 2013). The four major motions of this exercise program are as follows: (1) abduction of both arms to shoulder level and simultaneous abduction of one leg to about 35°; (2) abduction of one arm to shoulder level with elbow flexion at about 90° and simultaneous abduction of the ipsilateral leg with knee flexion at about 90°; (3) abduction of both arms to shoulder level and simultaneous both knee flexion to about 90°; (4) both arms crossed in front of the chest in a standing position with the feet splayed outward and both knee flexion to about 90°. The monitor screen showed a 3-dimensional avatar in a wilderness setting (a lake surrounded by mountains). This avatar is zoomed or rotated depending on the participant’s postures, so that the participant can clearly identify her own movements onscreen. Participant follows the movements of the virtual instructor on the left side of the screen, while simultaneously watching her own movements on the right side of the screen. The virtual instructor guides the participant towards more exact movement with visual and

auditory feedback. The accuracy of a participant’s movements is scored by the software and the score appears in real-time on the upper right side of the screen during exercise. The participant can also review her total score at the end of the exercise. The exercise program for GG was adapted from the exercise program by Donat et al. (Donat & Ozcan, 2007) due to its similarity of motions with those in Zen Energy. This exercise program consisted of postural, balance, functional, lower body coordination, and lower body strength exercises; its effects on balance and lower body strength were verified in a previous study (Donat & Ozcan, 2007). A physiotherapist provided auditory feedback for participants to encourage them or to guide them about correct postures. Feedback was provided on a group basis, in front of the exercise room throughout the duration of the intervention.

2.5. Baseline measurement At baseline, demographic information—age, marital status, cognition, education, and physical activity level—was obtained. Height and weight were measured by a certified physiotherapist, and body mass index (BMI) was calculated using weight in kilograms divided by height in meters squared.

2.6. Outcomes All participants underwent baseline and follow-up tests by two intervention-blinded physiotherapists with over three years of clinical experience.

2.6 .1. HRQoL Primary outcome measures included the Short-Form Health Survey (SF-36) (Mchorney, Ware, & Raczek, 1993), which measures HRQoL across eight subscales: (1) physical functioning; (2) role limitations due to physical health (role-physical); (3) bodily pain; (4) general health; (5) vitality; (6) social functioning; (7) role limitations due to emotional health (role-emotional); (8) mental health (Mchorney et al., 1993). The score of each subscale can range from zero to 100, and a higher score indicates better health. The SF-36 shows high reliability and validity (Brazier et al., 1992), and its Korean version was tested for its conceptual equivalence (Cronbach’s α = .59−.88) (Cho, 2012). The scores of the eight subscales were aggregated into two distinct higher-order summary scores with high reliabilities and validities (Ware et al., 1995; Ware JE, 1994): physical functioning, role-physical, bodily pain and general health were included in the physical component summary (PCS); vitality, social functioning, role-emotional, and mental health were grouped into the mental component summary (MCS).

2.6 .2. Physical fitness Secondary outcome measures included following tests from the Senior Fitness Test (Rikli & Jones, 1999b; C. R. Roberta, and J. Jones, 2001): (1) the 30-Second Chair Stand Test (30SCST) to evaluate lower body strength; (2) the 2-Minute Step Test (2MST) to evaluate aerobic endurance; (3) the 8-Foot Up-and-Go Test (8FUGT) for evaluating dynamic balance. In the 8FUGT, the shorter the time taken to complete the task, the better the dynamic balancing ability. The procedure used for these tests in the current study was described in the Senior Fitness Test Manual (Roberta, Rikli, & Jones, 2001). The SFT has been shown to have high validity and

reliability (Rikli & Jones, 1999a).

2.6 .3. Exercise participation Exercise participation was measured using exercise attendance rates, calculated as the ratio of the number of attended interventions divided by the total number of interventions.

2.7. Data analysis All measurements were analyzed using SPSS version 21.0 (IBM SPSS Inc., Chicago, IL). Differences of the baseline measurements and outcomes at baseline between groups were evaluated with the chi-square (χ2) test for categorical data and independent t-tests for continuous data. The baseline differences between completers and non-completers were also analyzed using independent t-tests to investigate possible effects of dropouts. Between-group differences were analyzed using the analysis of covariance (ANCOVA) with baseline values as covariates. Within-group changes from baseline to follow-up values were analyzed using paired t-tests. The analyses were conducted on an intention-to-treat (ITT) basis using the last observation carried forward imputation method. For sensitivity analysis, the ITT results were compared with results of a per-protocol analysis (PPA), which excluded non-completers. Significance levels were set at p < .05 for all analyses.

3.

Results

Of the 54 enrolled participants, seven dropped out at eight weeks. Twenty-two (84.62%) and 25 (89.29%) participants of IFVRG and GG, respectively, completed the follow-up tests (Figure 1). Participants’ baseline measurements and outcomes at baseline were not different between the two groups (Tables 1, 2 and 3). The baseline outcomes between completers and non-completers were not also different.

3.1. HRQoL ANCOVA showed significant difference between the IFVRG and GG in mental health (p = 0.029), when adjusted for the baseline score. Change score in the IFVRG was higher than was that in the GG. Within-group analysis for the SF-36 revealed that the IFVRG showed an increase in role-physical (p = 0.015), bodily pain (p = 0.017), general health (p = 0.004), vitality (p = 0.010), roleemotional (p = 0.007), mental health (p = 0.000), and MCS (p = 0.001) scores, whereas the GG showed an increase in role-physical (p = 0.022), general health (p = 0.023), social functioning (p = 0.023), and PCS (p = 0.003) scores. The adjusted between- and withingroup differences for the subscales of SF-36 are shown in Table 2, and the percentage changes for each of the subscale scores of the SF-36 are shown in Figure 2.

3.2.

Physical fitness ANCOVA showed significant difference between the IFVRG and GG in 30SCST (p = 0.042), when adjusted for the baseline

score. Change score in the IFVRG was higher than was that in the GG. Within-group analysis for the physical fitness revealed that

both groups showed an increase in 30SCST, 2MST, and 8FUGT scores compared to baseline scores (all p < 0.001). The adjusted between- and within-group differences for the 30SCST, 2MST, and 8FUGT are shown in Table 3, and the percentage changes for each of tests are shown in Figure 3.

3.3. Exercise participation The mean attendance rate of completers was 90.24% and 79.70% for IFVRG and GG, respectively. 3.4. Sensitivity analysis As a result of PPA, the overall trend was maintained, except that 30SCST showed no difference between the two groups (p = 0.104), and role-physical in the IFVRG (p = 0.074) and general health in the GG (p = 0.083) showed no significant increases between baseline and follow-up.

4.

Discussion The analysis demonstrated positive effects of IFVR exercise on participants’ self-perceived health using HRQoL. In particular,

IFVR exercise improved mental health more than did group-based exercise, while group-based exercise increased social functioning more. The IFVRG perceived increases in vitality (19.3%), role-emotional (40.9%), and mental health (20.6%) for themselves. The IFVR exercise used an unrealistic 3-dimensional avatar of the participant exercising on a lake, surrounded by mountains, with soft

music, guided by a virtual instructor using visual and auditory feedback. These characteristics of IFVR might increase the emotional and mental health of participants and a previous study suggested that older adults who completed IFVR gaming showed gains in mental health, whereas non-completers did not (Studenski et al., 2010). It was also reported that older adults with impaired balance rated high enjoyment during IFVR gaming (Agmon et al., 2011) and that older adults with subsyndromal depression perceived improvements in mental health after receiving the IFVR intervention (Rosenberg et al., 2010). However, the reduced improvement of social functioning with the IFVRG (4.1%) as compared to the GG (11.7%), though not significant, might indicate a less beneficial effect of IFVR exercise, due to the need for individualized feedback requiring a single participant, without interaction from others. Therefore, a way of supplementing social health needs to be identified to satisfy all dimensions of the HRQoL for older women. Both the IFVRG and GG showed an overall improvement in the physical component of the SF-36. In particular, bodily pain significantly decreased in the current study (16.2%). A previous study supports this result, suggesting that IFVR could promote relaxation and a decrease in pain through visual and auditory feedback for patients with arthritis (Keefe et al., 2012). Physical functioning, however, did not increase in either the IFVRG or the GG. This might be due to a ceiling effect, as most questions in physical functioning scale were related to basic activities of daily living, and most participants were already healthy enough to complete such physical activities at baseline. The exercise content of the current study could be another factor limiting an increase in physical functioning as, according to Sartor-Glittenberg et al. (Sartor-Glittenberg et al., 2014), gait speed is the primary variable contributing to an improved PCS, and the exercise content of this current study concentrated on balance and lower extremity

strength, not gait. Meanwhile, the IFVRG showed a higher attendance rate (90.24%) than did the GG (79.70%). This might be partially due to the “convenient accessibility” of IFVR, whereby, so long as the apparatus is available, people can complete IFVR exercise at their convenience without waiting for a health-care professional or a fixed exercise time. However, even though participants in the IFVRG could choose their exercise time, they would not continue exercise if they were not sufficiently motivated. Hence, we can assume that both the convenient accessibility and the characteristics of the IFVR exercise motivated IFVRG participants enough to produce this high attendance rate. In comparison to the IFVRG, the GG showed a significant increase in social functioning (11.7%) among the mental components, although the increases in role-emotional (1.9%) and mental health (2.8%) were marginal. Meanwhile, the overall percentage changes in physical components for the GG were greater than were those of the IFVRG. Similar to the results of this study, Hand et al. reported that 12 weeks of group-based exercise did not affect role-emotional and mental health in older adults (men = 12, women = 55), although physical fitness did improve (Hand, Cavanaugh, Forbes, Govern, & Cress, 2012). These results implies that group-based exercise might be less engaging and enjoyable than IFVR exercise as it lacks an immersive environment or individualized feedback, though perceived as effective in improving self-perceived physical health or objective physical fitness. For physical fitness, this RCT not only verified that the increases of participants’ self-perceived health were not due to placebo effect, but also added the robust evidence for the effect of FVR exercise on balance, lower body strength and aerobic endurance in older women, by comparing with group-based exercise. Further, we identified that FVR exercise was more effective than group-based

exercise in improving lower body strengthening. This superior effect of FVR on lower body strength might be due to real-time visual and auditory feedback, which guided the participants towards more exact movements, so that participants’ lower body muscles could be correctly and sufficiently activated. This study does have several limitations, the short intervention period and the inclusion of only older women. Another limitation was its relatively small sample size; thus, a large-scale study might be required to confirm the present results. Nevertheless, the strengths of this study are the application of RCT as a robust methodology and the use of a sensitivity analysis, which confirms the robustness of these results.

5.

Conclusion IFVR exercise was effective in improving the HRQoL of older women in addition to their physical fitness. In particular, IFVR

can be used to improve mental health in older women with depression. Therefore, IFVR exercise would be an effective selfmanagement strategy for older women that minimizes supervision from health care professionals. Consequently, IFVR exercise could provide more exercise opportunities for older women to improve HRQoL and physical fitness.

Conflicts of interest statement The authors declare that they have no conflict of interest.

Acknowledgement This work was supported by a grant from the Korean National Rehabilitation Institute. References Agmon, M., Perry, C. K., Phelan, E., Demiris, G., & Nguyen, H. Q. (2011). A Pilot Study of Wii Fit Exergames to Improve Balance in Older Adults. J Geriatr Phys Ther 34(4), 161-167. doi: Doi 10.1519/Jpt.0b013e3182191d98 Brazier, J. E., Harper, R., Jones, N. M. B., Ocathain, A., Thomas, K. J., Usherwood, T., & Westlake, L. (1992). Validating the Sf-36 Health Survey Questionnaire - New Outcome Measure for Primary Care. Brit Med J 305(6846), 160-164. Cho, Sung Myung. (2013). Reliability and Validity Assessment of SF-6D for Measuring the Quality of Life for the General Public, and Comparison with SF-36 and GHQ-12. (Master's thesis), Kangwon University, Seoul. Crum, R. M., Anthony, J. C., Bassett, S. S., & Folstein, M. F. (1993). Population-Based Norms for the Mini-Mental-State-Examination by Age and Educational-Level. JAMA-J Am Med Assoc 269(18), 2386-2391. doi: DOI 10.1001/jama.269.18.2386 Depp, C., Vahia, I. V., & Jeste, D. (2010). Successful Aging: Focus on Cognitive and Emotional Health. Annu Rev Clin Psycho 6, 527550. doi: DOI 10.1146/annurev.clinpsy.121208. 131449 Donat, H., & Ozcan, A. (2007). Comparison of the effectiveness of two programmes on older adults at risk of falling: unsupervised home exercise and supervised group exercise. Clin Rehabil 21(3), 273-283. doi: Doi 10.1177/0269215506069486 Duque, G., Boersma, D., Loza-Diaz, G., Hassan, S., Suarez, H., Geisinger, D., . . . Demontiero, O. (2013). Effects of balance training using a virtual-reality system in older fallers. Clin Interv Aging 8, 257-263. doi: Doi 10.2147/Cia.S41453

Glanz K, L.F., Rimer BK. ( 1997). Health Behavior and Health Education: Theory, Research and Practice. 2nd ed. San Francisco, CA: Jossey-Bass Inc. Hand, B. D., Cavanaugh, S., Forbes, W., Govern, J., & Cress, M. E. (2012). Changes in Health-Related Quality of Life and Functional Fitness With Exercise Training in Older Adults Who Attend Senior Centers. Activ Adapt Aging, 36(1), 29-54. Jorgensen, M. G., Laessoe, U., Hendriksen, C., Nielsen, O. B. F., & Aagaard, P. (2013). Efficacy of Nintendo Wii Training on Mechanical Leg Muscle Function and Postural Balance in Community-Dwelling Older Adults: A Randomized Controlled Trial. J Gerontol A Biol, 68(7), 845-852. doi: DOI 10.1093/gerona/gls222 Keefe, F. J., Huling, D. A., Coggins, M. J., Keefe, D. F., Rosenthal, M. Z., Herr, N. R., & Hoffman, H. G. (2012). Virtual reality for persistent

pain:

A new

direction

for

behavioral

pain

management.

Pain,

153(11),

2163-2166.

doi: DOI

10.1016/j.pain.2012.05.030 Kim, J., Son, J., Ko, N., & Yoon, B. (2013). Unsupervised Virtual Reality-Based Exercise Program Improves Hip Muscle Strength and Balance Control in Older Adults: A Pilot Study. Arch Phys Med Rehab 94(5), 937-943. doi: DOI 10.1016/j.apmr.2012.12.010 Mchorney, C. A., Ware, J. E., & Raczek, A. E. (1993). The Mos 36-Item Short-Form Health Survey (Sf-36) .2. Psychometric and Clinical-Tests of Validity in Measuring Physical and Mental-Health Constructs. Med Care 31(3), 247-263. doi: Doi 10.1097/00005650-199303000-00006 Miller, K. J., Adair, B. S., Pearce, A. J., Said, C. M., Ozanne, E., & Morris, M. M. (2014). Effectiveness and feasibility of virtual reality and gaming system use at home by older adults for enabling physical activity to improve health-related domains: a

systematic review. Age Ageing 43(2), 188-195. doi: DOI 10.1093/ageing/aft194 Montross, L. P., Depp, C., Daly, J., Reichstadt, J., Golshan, S., Moore, D., . . . Jeste, D. V. (2006). Correlates of self-rated successful aging

among

community-dwelling

older

adults.

Am

J

Geriat

Psychiat

14(1),

43-51.

doi:

Doi

10.1097/01.Jgp.0000192489.43179.31 Pavot, W., & Diener, E. (1993). Review of the Satisfaction With Life Scale. Eur J Psychol Assess 5(2), 164-172. Phelan, E. A., Anderson, L. A., LaCroix, A. Z., & Larson, E. B. (2004). Older adults' views of "successful aging" - How do they compare with researchers' definitions? J Am Geriatr Soc 52(2), 211-216. doi: DOI 10.1111/j.1532-5415.2004.52056.x Rendon, A. A., Lohman, E. B., Thorpe, D., Johnson, E. G., Medina, E., & Bradley, B. (2012). The effect of virtual reality gaming on dynamic balance in older adults. Age Ageing, 41(4), 549-552. doi: DOI 10.1093/ageing/afs053 Rikli, R. E., & Jones, C. J. (1999a). Development and validation of a functional fitness test for community- residing older adults. Journal of Aging and Physical Activity, 7(2), 129-161. Rikli, R. E., & Jones, C. J. (1999b). Development and validation of a functional fitness test for community-residing older adults. J Aging Phys Activ 7(2), 129-161. Roberta, Rikli, C., & Jones, Jessie. (2001). Senior fitness test manual. Champaign, IL: Human Kinetics. Roberta, C. Rikli, and J. Jones. (2001). Senior fitness test manual. Champaign, IL: Human Kinetics. Rosenberg, D., Depp, C. A., Vahia, I. V., Reichstadt, J., Palmer, B. W., Kerr, J., . . . Jeste, D. V. (2010). Exergames for Subsyndromal Depression in Older Adults: A Pilot Study of a Novel Intervention. Am J Geriat Psychiat 18(3), 221-226. doi: Doi

10.1097/Jgp.0b013e3181c534b5 Rosenstock, I. M., Strecher, V. J., & Becker, M. H. (1988). Social-Learning Theory and the Health Belief Model. Health Educ Quart, 15(2), 175-183. doi: Doi 10.1177/109019818801500203 Sartor-Glittenberg, C., Lehmann, S., Okada, M., Rosen, D., Brewer, K., & Bay, R. C. (2014). Variables Explaining Health-Related Quality

of

Life

in

Community-Dwelling

Older

Adults.

J

Geriatr

Phys

Ther

37(2),

83-91.

doi:

Doi

10.1519/Jpt.0b013e3182a4791b Sherry, J. L. (2004). Flow and media enjoyment. Commun Theor 14(4), 328-347. doi: Doi 10.1093/Ct/14.4.328 Shillitoe, R. W., & Christie, M. J. (1989). Determinants of self-care: The health belief model. J Interprof Care, 4(1), 3-17. Spilker, B. (1984). Quality of Life Assessments in Clinical Trials. New York: Raven Press Ltd. Studenski, S., Perera, S., Hile, E., Keller, V., Spadola-Bogard, J., & Garcia, J. (2010). Interactive Video Dance Games for Healthy Older Adults. J Nutr Health Aging, 14(10), 850-852. doi: DOI 10.1007/s12603-010-0119-5 Taylor, D., Hale, L., Schluter, P., Waters, D. L., Binns, E. E., McCracken, H., . . . Wolf, S. L. (2012). Effectiveness of Tai Chi as a Community-Based Falls Prevention Intervention: A Randomized Controlled Trial. J Am Geriatr Soc, 60(5), 841-848. doi: DOI 10.1111/j.1532-5415.2012.03928.x Tousignant, M., Corriveau, H., Roy, P. M., Desrosiers, J., Dubuc, N., & Hebert, R. (2013). Efficacy of supervised Tai Chi exercises versus conventional physical therapy exercises in fall prevention for frail older adults: a randomized controlled trial. Disabil Rehabil 35(17), 1429-1435. doi: Doi 10.3109/09638288.2012.737084

Ware, J. E., Kosinski, M., Bayliss, M. S., Mchorney, C. A., Rogers, W. H., & Raczek, A. (1995). Comparison of Methods for the Scoring and Statistical-Analysis of Sf-36 Health Profile and Summary Measures - Summary of Results from the Medical Outcomes Study. Med Care, 33(4), As264-As279. Ware JE, K.M., Keller SD. (1994). SF-36 physical and mental health summary scales: A user's manual. Boston, MA: New England Medical Center, The Health Institute. Williams, B., Doherty, N. L., Bender, A., Mattox, H., & Tibbs, J. R. (2011). The effect of nintendo wii on balance: A pilot study supporting the use of the wii in occupational therapy for the well elderly. Occup Ther Health Care, 25(2-3), 131-139.

Table 1. Baseline demographic and clinical characteristics of participants (n = 54) IFVRG (n = 26)

GG (n = 28)

p-value

Age, mean (SD) (years)

68.77 (4.62)

67.71 (4.31)

< 0.389 a

Height, mean (SD) (cm)

156.07 (4.62)

157.39 (4.21)

< 0.277 a

Weight, mean (SD) (kg)

59.09 (6.27)

56.75 (6.45)

< 0.442 a

BMI, mean (SD) (kg/m2)

23.83 (2.18)

22.92 (2.51)

< 0.162 a

MMSE, mean (SD) (score)

28.00 (1.94)

28.32 (1.94)

< 0.546 a

Physical activity, mean (SD) (min/wk)

46.54 (73.81)

46.29 (59.01)

< 0.989 a

26 (100)

27 (96.43)

< 0.331 b

0 (0)

1 (3.57)

Marital status, married, n (%) Single

Married

26 (100)

27 (96.43)

< 0.623 b

Education level, n (%) Primary school

5 (19.23)

5 (17.86)

Middle school

4 (15.38)

8 (28.57)

High school

13 (50.00)

10 (35.71)

University

4 (15.38)

5 (17.86)

IFVRG, individualized feedback-based virtual reality group; GG, group-based exercise group; SD, standard deviation; BMI, body mass index; MMSE, Mini-Mental State Examination. a Analyzed with independent t-test. b Analyzed with chi-square test. * p < 0.05. Table 2. Baseline and change scores in subscales of SF-36 (n = 54, intention-to-treat population). IFVRG (n = 26)

GG (n = 28)

Baseline

Follow-up

Change

Baseline

Follow-up

Change

Adjusted betweengroup mean difference (95% CI)b

Physical functioning

73.85 (13.95)

75.38 (14.69)

1.35 (13.16)

68.57 (19.48)

69.11 (24.14)

0.54 (17.07)

2.09 (-6.21 to 10.39)

< 0.616

Role-physical

49.04 (33.53)

71.15 (35.14)*

22.12 (43.20)

43.21 (39.04)

62.86 (39.00)*

19.64 (42.69)

6.39 (-13.12 to 25.90)

< 0.514

Bodily pain

65.65 (21.38)

76.31 (19.27)*

10.65 (21.28)

54.36 (24.70)

64.43 (24.77)

10.07 (28.43)

7.71 (-4.00 to 19.42)

< 0.192

General health

49.62 (18.55)

58.81 (18.66)*

9.19 (14.68)

47.98 (16.76)

54.79 (15.17)*

6.81 (14.93)

3.02 (-4.22 to 10.27)

< 0.406

PCS

42.73 (6.67)

44.97 (8.27)

2.24 (7.00)

38.60 (8.85)

42.78 (9.03)*

4.18 (6.78)

-0.79 (-4.53 to 2.94)

< 0.673

59.81 (23.17)

71.35 (18.03)*

11.54 (21.01)

56.96 (21.79)

62.86 (17.56)

5.89 (23.65)

7.59 (-1.43 to 16.62)

< 0.097

Outcome measure

p-valuec

Physical component

Mental component Vitality

Social functioning

81.25 (21.87)

84.62 (12.90)

3.37 (21.67)

80.36 (18.77)

89.73 (15.61)*

9.38 (20.59)

-5.30 (-12.88 to 2.27)

< 0.166

Role-emotional

56.42 (37.45)

79.49 (34.09)*

23.07 (39.75)

63.09 (37.78)

64.29 (42.49)

1.20 (56.28)

16.40 (-4.72 to 37.51)

< 0.125

Mental health

68.77 (16.36)

82.92 (13.41)**

14.15 (16.17)

71.29 (16.19)

73.29 (17.92)

2.00 (26.18)

9.81 (1.02 to 18.60)

< 0.029*

MCS

47.50 (10.52)

54.58 (8.05)*

7.09 (9.79)

50.16 (7.85)

51.10 (8.99)

0.94 (12.61)

3.95 (-0.74 to 8.64)

< 0.097

SF-36, Short-Form Health Survey; IFVRG, individualized feedback-based virtual reality group; GG, group-based exercise group; CI, confidence interval; PCS, physical component summary; MCS, mental component summary Values are mean scores (standard deviations), unless otherwise indicated. a Subscales of SF-36 are scored on a 0 (worst possible health) to 100 (best possible health) scale. b Between-group mean difference in change scores, calculated as follow-up minus baseline scores, adjusted for baseline score. c Intent-to-treat analysis with missing values imputed using last observation carried forward method, and ANCOVA on change scores adjusted for baseline score. Significance levels were in bold. * p < 0.05, ** p < 0.001. Table 3. Baseline and change scores in physical fitness outcome measures (n = 54, intention-to-treat population). IFVRG (n = 26)

GG (n = 28)

Baseline

Follow-up

Change

Baseline

Follow-up

Change

Adjusted betweengroup mean difference (95% CI)b

30SCST (count)

15.42 (3.62)

22.15 (5.29)**

6.73 (4.77)

16.46 (3.63)

20.14 (4.91)**

3.68 (4.79)

2.66 (0.10 to 5.21)

< 0.042*

2MST (count)

74.08 (17.04)

92.58 (14.33)**

18.50 (21.58)

68.54 (21.35)

95.80 (18.56)**

27.27 (25.70)

-3.88 (-13.08 to 5.34)

< 0.711

6.24 (0.91)

5.38 (0.47)**

-0.86 (0.94)

5.84 (0.70)

5.07 (0.63)**

-0.77 (0.67)

0.22 (-0.08 to 0.52)

< 0.151

Outcome measure

8FUGT (second)a

P-valuec

IFVRG, individualized feedback-based virtual reality group; GG, group-based exercise group; CI, confidence interval; 30SCST, 30Second Chair Stand Test; 2MST, 2-Minute Step Test; 8FUGT, 8-Foot Up-and-Go Test. Values are mean scores (standard deviations), unless otherwise indicated. a Lower scores indicate better performance. b Between-group mean difference in change scores, calculated as follow-up minus baseline scores, adjusted for baseline score. c Intent-to-treat analysis with missing values imputed using last observation carried forward method, and ANCOVA on change scores adjusted for baseline score. Significance levels were in bold. *P < 0.05, **P < 0.001.

Figure 1. Flow chart of the study. IFVRG, individualized feedback-based virtual reality exercise group; GG, group-based exercise group.

Figure 2. Percentage changes for each of the subscale scores of SF-36 over the eight-week study period. IFVRG, individualized feedback-based virtual reality group; GG, group-based exercise group; SF-36, short-form health survey. Note. Each bar indicates the change percentage, which was calculated by subtracting the baseline value from the follow-up value, dividing that change by the baseline value, and then converting it into a percentage. * Significant difference in change score between two groups as a result of ANCOVA.

Figure 3. Percentage changes for tests of physical fitness over the eight-week study period. IFVRG, individualized feedback-based virtual reality group; GG, group-based exercise group; 30SCST, 30-Second Chair Stand Test; 2MST, 2Minute Step Test; 8FUGT, 8-Foot Up-and-Go Test. Each bar indicates the change percentage, which was calculated by subtracting the baseline value from the follow-up value, dividing that change by the baseline value, and then converting it into a percentage. a Lower scores indicate better increases of performance. * Significant difference in change score between two groups as a result of ANCOVA.