1. Introduction
By 2050, 16% of the world’s population will be aged above 65 years [1]. Although medical technology has enabled individuals to extend their lives, it does not necessarily maintain a favorable quality of life (QOL) [2]. Health-related QOL is the state of one’s physical, psychological, and social self-perception over time [3]. Longitudinal studies have indicated that increasing age has a significantly negative effect on QOL [4,5]. Another cross-sectional study revealed that QOL deteriorates with age [6]. Furthermore, QOL potentially influences older adults’ daily living conditions and physical and mental health, whose relationship with age is concerning.
Regular physical activity helps improve QOL in older adults and plays an important role in enhancing successful aging [7,8,9]. The impact of physical activity on improving the QOL in older adults has been observed in cross-sectional studies, particularly with regard to age-related differences. For example, Gouveia et al. [6] found the positive correlation between QOL and physical activity to be significantly stronger in old adults than in young-old adults. Similar results have also been found in regular exercise interventions. Oh, Kim [10] revealed the effects of multimodal exercises, such as resistance, flexibility, and walking exercises, on QOL in older adults. They observed improvements in both physiological and psychological QOL parameters, such as mobility, self-care, usual activities, pain or discomfort, and anxiety or depression. Furthermore, women aged 75–84 years who had performed balance exercises displayed improvements in their self-perceived physical health [11]. Similarly, health-related QOL in terms of balance impairments in young-old (65–73 years) and middle-old (74–85 years) adults improved over 12 weeks of supervised physical training [12]. Nonetheless, few exercise intervention studies have investigated the QOL of older adults across diverse age groups, and these studies have primarily focused on balance training alone [11,12] or have exclusively recruited older adults from a single age range [11].
Virtual reality (VR) exercise (e.g., immersive VR, non-immersive VR, interactive VR, etc.) potentially exerts a positive impact on physical and mental health and rehabilitative outcomes compared with traditional exercise [13]. This includes the effectiveness of exergaming-based interventions for mobility and balance performance in older adults with Parkinson’s disease [14]; the impact of VR-supported upper-extremity exercise therapy on the motor rehabilitation of motion in sub-healthy people [15]; and the feasibility of, perceptions regarding, and attitude toward the VR-based exercise system in post-treatment patients [16]. It also includes findings on patients’ QOL after participating in the intervention. For example, patient participation in VR games or VR-based therapies has a slightly positive impact on QOL [17,18]. Evidence corroborating the relationship between rehabilitation and QOL across different ages has also been generated [19]. While the current VR-based interventions have mainly targeted sub-healthy populations, two VR exercise interventions have been observed to improve QOL in healthy older adults. First, a previous study found a 6-week short-term VR program to enhance the QOL of healthy older people [20]. Second, Wang [21] explored older adults’ participation in 12 weeks of semi-immersive VR fitness training and tracked the effects of discontinuing the intervention. Nevertheless, these studies generally focused on changes in QOL among people aged ≥ 65 years.
Engaging in exercise as a strategy to maintain health in older adults’ QOL [22,23]. Studies support the use of concrete physical activity strategies to improve QOL in older adults of various age groups [6]. Considering the prevalence of technological skills in exercise and health, QOL should be prioritized at a later age. Thus, this study aimed to (1) evaluate the effects of a 12-week semi-immersive VR exercise intervention on older adults’ QOL and (2) determine the differences in post-intervention QOL outcomes between two different age groups (65–73 and 74–85 years). It primarily focused on elucidating stratified age-related differences. This study explores age-related differences in self-perceived QOL after participating in technology-based fitness activities. Through a semi-immersive VR exercise intervention, we aim to promote sustainable exercise habits and encourage older adults to adopt digital fitness strategies, ultimately enhancing their QOL.
2. Methods
2.1. Study Design
This study followed a block randomization design for a randomized controlled trial. The trial was single-blinded (outcome assessors) and registered with
2.2. Participants
Participants were recruited from the Taipei City, Taiwan, and nearby communities. Eligible participants were recruited based on the following criteria: (1) 65–85 years of age; (2) ability to live independently; (3) no history of or ongoing medical conditions, as revealed through the Physical Activity Readiness Questionnaire (PAR-Q); (4) no previous experience of playing sports on large screens or other digital platforms or no previous interest in VR-based fitness; and (5) willingness to participate in fitness sessions conducted in a dark environment. The present study refers to [12] for the definition of age group ranges, categorizing young-old adults as those aged 65–73 years and middle-old adults as those aged 74–85 years in the context of exercise interventions. This study was designed as a mixed (4 × 2) repeated measures analysis of variance (ANOVA) test (comparing the pre- and post-test results between the experimental group [EG] and control group [CG] in the two different age groups). Therefore, multivariate ANOVA (MANOVA) was used to calculate sample size, while the power for input parameters was referenced from previous studies [24,25]. The optimal total sample size for older adults was estimated to be 126 at a power of 0.80 (1−β), a significance level of 0.05, and an effect size of 0.3. The total required sample size was estimated using G* Power (version 3.1.7) [26].
2.3. Recruitment
Initially, 108 older adults were recruited. Those who were younger than 65 years (n = 1), older than 85 years (n = 8), or not sufficiently healthy to perform the required exercises (as revealed by the PAR-Q; n = 2) were excluded. After excluding ineligible participants, 97 participants were finally enrolled in the study. An assistant not involved in the study assigned all the participants to two age groups. Specifically, 48 and 49 participants were randomly assigned to the EG and CG, respectively. To inform the participants of their specific group allocation, a research assistant contacted them via telephone and email. After the intervention, seven participants were excluded owing to personal reasons (n = 3), medical problems unrelated to the study (n = 1), or incomplete attendance (i.e., missing ≥ 20% of the intervention; n = 3). Therefore, 90 participants completed the randomized controlled trial (EG: n = 45 [young-old adults, n = 26; middle-old adults, n = 19]; CG: n = 45 [young-old adults, n = 24; middle-old adults, n = 21]). Figure 1 provides a flowchart describing the participant enrollment and assessment process.
2.4. Semi-Immersive VR-Based Exercise Training Program
Uniigym (
All the EG participants undertook their sessions in a university exercise classroom. The duration, type, and difficulty of the exercises shown in the videos were evaluated by the researchers before the intervention and confirmed to be suitable for older adults [28,29,30]. The structure of the weekly exercise program remained the same. The training protocol is outlined in Table 1. A nurse was available on site to help during the intervention if required. The final analysis only included the participants with a total attendance rate ≥ 80%. The CG participants were instructed to follow their regular activities and required to participate in pre- and post-tests. All the participants completed the QOL questionnaire one week before the intervention and at the end of week 12.
2.5. QOL Measurement
The World Health Organization’s QOL Instrument-Older Adults Module (WHOQOL-OLD) is widely used to assess the psychological QOL of older adults [31]. In this study, the participant QOL was assessed using the Taiwanese version of this questionnaire, which has demonstrated favorable reliability and validity, with a Cronbach’s alpha (α) ranging from 0.71 to 0.86 and correlation coefficient (r) between the questionnaire and questions ranging from 0.62 to 0.88 [32]. The WHOQOL-OLD assesses six QOL dimensions: sensory abilities; autonomy; past, present, and future activities; social participation/isolation; death and dying; and intimacy. Each dimension is assessed using four questions, yielding a total of 24 questions. Each question is rated on a 5-point Likert scale, ranging from 1 (not at all) to 5 (an extreme amount). The scores of the responses to the questions in a dimension are summed to obtain the score for that dimension, and those for the six dimensions are subsequently summed to obtain the overall score. After a negative transformation, a higher score indicates a better QOL. All the participants arrived at the classroom at the prescribed time to complete the questionnaire. An assistant not involved in the study assisted in recycling the questionnaire. The assistant was blinded from the participant group allocation during the tests.
2.6. Descriptive Variables
The participants’ basic demographic characteristics (sex, age, body mass index (BMI) [33], and physical activity) were recorded before the intervention. The Taiwanese version of the International Physical Activity Questionnaire-Long Version was used in pre-intervention investigations. The participants’ physical activity data were collected using a self-reported questionnaire. The scale exhibited excellent stability and retest reliability (Spearman’s ρ = 0.67) [34].
2.7. Data Analysis
All the statistical analyses were conducted using SPSS for Windows 22.0 (IBM, Inc., Armonk, NY, USA) with significance set at p = 0.05. Data normality was verified using the Shapiro–Wilk test. Descriptive statistics were used to describe the basic demographic information of the two age groups. The chi-square test was used to compare the descriptive variables by sex in the two age groups. Furthermore, an independent sample t-test was used to compare the ages and physical activity of the participants. The study measured the functional capacity of the older adults during the intervention [35], which helps avoid the fact that exercise intervention has only a placebo effect on QOL improvements.
The effects of the intervention on the QOL of the older adults across different ages were assessed. First, a two-way repeated measures ANOVA was used to compare data in terms of group (EG and CG) × time (pre-test vs. post-test). Second, a mixed (4 × 2) repeated measures ANOVA was used to compare data in terms of age range (65–73 and 74–85) × group (EG and CG) × time (pre-test vs. post-test). Pre-test data for all the dimensions were analyzed using Levene’s test for equality of variances. Greenhouse–Geisser correction was applied in the analysis if unequal variances were found. Please refer to Supplementary Table S1.
Where significant interaction main effects were observed, a post hoc analysis for unidirectional effects was performed using an independent t-test and a paired t-test for between-group and within-group analyses. Least Significant Difference tests were also used to compare the results of multiple comparisons between the different age groups. The effect size was indicated by the magnitude of the partial eta-squared (η2p) of the ANOVA as follows: ≥ 0.01 (small effect), ≥ 0.06 (medium effect), and ≥ 0.14 (large effect).
To preserve the spirit of random sampling, and based on the results, this study conducted intention-to-treat analyses. An additional analysis demonstrated the effectiveness of the exercise intervention (missed ≥ 20%) for all the participants initially included in the program.
3. Results
3.1. Characteristics of the Two Participant Age Groups
The young-old and middle-old groups included 50 (EG: 26, CG: 24) and 40 (EG: 19, CG: 21) participants, respectively. In the EG’s young-old subgroup, 73.1% were women, and the mean age was 69.23 (standard deviation [SD] = 1.70) years. In the EG’s middle-old subgroup, 78.9% were women, and the mean age was 76.05 (SD = 2.17) years. No significant differences in sex, level of vigorous physical activity, or level of moderate physical activity were noted between the young-old and middle-old adults. However, significant differences were observed in age, total leisure-time physical activity, and leisure-time walking. The participants’ characteristics are detailed in Table 2.
3.2. Effects of the Intervention on Older Adults’ QOL
We noted significant main effects of group on sensory abilities (F1, 88 = 6.29, p = 0.014, and η2p = 0.07) as well as those of time on sensory abilities (F1, 88 = 16.13, p < 0.001, and η2p = 0.16), death and dying (F1, 88 = 4.25, p = 0.042, and η2p = 0.05), intimacy (F1, 88 = 4.53, p = 0.036, and η2p = 0.05), and overall QOL (F1, 88 = 15.11, p < 0.001, and η2p = 0.15). Furthermore, we also observed significant group × time interaction effects on sensory abilities (F1, 88 = 26.91, p < 0.001, and η2p = 0.23), autonomy (F1, 88 = 11.66, p = 0.001, and η2p = 0.12), social participation/isolation (F1, 88 = 7.08, p = 0.009, and η2p = 0.07), death and dying (F1, 88 = 7.56, p = 0.007, and η2p = 0.08), and overall QOL (F1, 88 = 32.92, p < 0.001, and η2p = 0.27). Sensory abilities and overall QOL revealed a large effect size. Autonomy, social participation/isolation, and death and dying displayed a medium effect size. (See Table 3 for details).
The post hoc analyses of the simple main effects indicated that the EG yielded better post-test results than the CG in sensory abilities (EG: 12.64 ± 2.09 vs. CG: 10.04 ± 2.76, p < 0.001), autonomy (EG: 15.62 ± 2.53 vs. CG: 14.36 ± 2.10, p = 0.011), death and dying (EG: 16.07 ± 3.00 vs. CG: 14.22 ± 4.11, p = 0.017), and overall QOL (EG: 89.84 ± 10.43 vs. CG: 82.29 ± 10.13, p = 0.001). In addition, the EG demonstrated significant improvements from pre-test to post-test in sensory abilities (change: 23.92%, p < 0.001), autonomy (change: 7.65%, p = 0.016), social participation/isolation (change: 4.80%, p = 0.024), death and dying (change: 7.28%, p = 0.002), and overall QOL (change: 7.61%, p < 0.001). Moreover, the CG exhibited significant decreases from pre-test to post-test in autonomy (change: –4.01%, p = 0.015) and overall QOL (change: –1.46%, p = 0.017) (Figure 3).
3.3. Effects of the Intervention on Older Adults’ QOL According to Age
No significant group main effects were noted between the different age ranges in each QOL dimension and overall QOL. However, significant time main effects on death and dying (F3, 86 = 6.80, p = 0.011, and η2p = 0.07) were identified. Furthermore, significant group × time interaction effects on past, present, and future activities (F3, 86 = 4.48, p = 0.037, and η2p = 0.05) were noted. Past, present, and future activities exhibited a small effect size. (Detailed results are provided in Table 4).
The post hoc analyses of simple main effects displayed a significant decrease from pre-test to post-test in past, present, and future activities (change: –2.75%, p = 0.009) exclusively in the CG young-old adults (Figure 4).
3.4. Additional Analysis
This inclusion did not alter the results, indicating that the EG exclusively demonstrated significant improvements in sensory abilities (p < 0.001), autonomy (p = 0.016), social participation/isolation (p = 0.034), death and dying (p = 0.002), and overall QOL (p < 0.001) from pre-test to post-test. The analysis results from pre-test to post-test also revealed no change in the past, present, and future activity dimension (p = 0.175 and p = 0.866) in both the EG young-old and middle-old adults.
4. Discussion
This study aimed to investigate the effects of a 12-week semi-immersive VR-based intervention program on the QOL of young-old and middle-old adults. In general, the effects of the intervention on the older adults’ QOL revealed that the EG exhibited significant improvements in the QOL dimensions of sensory abilities, autonomy, social participation/isolation, death and dying, and overall QOL compared with the CG. The semi-immersive nature of VR exercise in creating specific atmospheres is an important factor in improving the older adults’ QOL. We believe this intervention stimulated sensory functions in the older adults, and our friendly training environment elicited improvements in autonomy and freedom. In addition, our group activities in the local community helped expand their social interactions [36]. Post-exercise relaxation also increased their self-confidence and rendered them less fearful of pessimistic problems [37]. Our results are congruent with those of the effects of traditional face-to-face exercise on the QOL of older adults of different ages [11,12,38,39] and also consistent with the impact of previous VR fitness interventions on the QOL of adults aged ≥ 65 years [20,40]. Recent studies support the application of technology-based interventions in enhancing the QOL of sub-healthy older individuals across various age groups. Mao, Jiang [19] implemented a 12-week rehabilitation therapy through a mobility application combined with smart dumbbells and found significant differences in QOL between the EG and CG, with no significant age-related differences. Our results are similar to a previous study. Therefore, technology-based exercise training is a potential strategy for maintaining QOL in sub-healthy and healthy older adults of different ages.
Notably, significant decreases in autonomy and overall QOL were observed in the CG older adults. Additionally, significant decreases in past, present, and future activities were noted in the CG young-old adults. A longitudinal study revealed the importance of physical activity in predicting QOL [4]. After retirement, young-old adults tended to reduce their physical activity and worry about their health within 2–4 years [41]. Retirement is often associated with a loss of identity and affects mental health [42]. Physical activity potentially helps older adults regain purpose in daily life, while participation in group activities can afford them a sense of belonging [43]. Consequently, older individuals are able to acquire autonomy and effectively manage their lives by engaging in or maintaining physical activity. Regardless of age, the promotion of consistent physical activity among retired older individuals will contribute to the preservation of QOL and promotion of mental health in later life.
Additionally, no significant increase in the past, present, and future activity dimension was noted in the EG older adults. Intimacy also did not improve as a result of the exercise intervention. This study involved a dynamic exercise intervention. Although the older adults exercised together, they did not interact with each other. However, when exploring specific deep inner feelings, static interventions and accompanied collaboration can improve QOL and more effectively support the psychological feelings of older adults. For example, a 9-week three-dimensional (3D) VR-based intervention combined with aromatherapy with assistance from a facilitator significantly improved life satisfaction in older adults [44]. Another 8-week 3D VR-based intervention combined with hands-on horticultural therapy significantly improved their perceptual abilities and achievement motivation [45].
Previous research has demonstrated differences in physical performance between adults and older adults after participating in VR [46,47]. In contrast, few research studies involving VR have explored age differences and psychosocial QOL outcomes. The new contribution of this paper is to understand changes in the self-perceived QOL of older adults of different ages after participating in a multicomponent exercise intervention involving technology-based sports. Our study demonstrates that a 12-week semi-immersive VR exercise intervention significantly enhances the QOL of individuals aged 65 and older, including those aged 74 and above. These findings align with previous research highlighting the positive effects of exercise on enhancing QOL [6,22,23]. Additionally, we observed a decline in QOL among the older adults who did not participate in the exercise intervention, with particular attention needed for the young-old adult group. This research underscores the critical role of regular physical activity in promoting QOL among older adults and supports the use of technology-based exercise strategies to improve self-perceived QOL.
However, our study has certain limitations. First, it exclusively recruited healthy older adults; hence, its results are not suitable for extrapolation to sub-healthy populations. Second, the participants had to be capable of engaging in semi-immersive VR fitness training (i.e., capable of exercising in a dark environment). As such, this study had a small number of middle-old adult participants. The results revealed that 40 middle-old adults were sufficient to achieve a power of 0.8, assuming alpha (α) = 0.05, as referenced from formulas in previous studies [25]. Nevertheless, future research should address the issue of sample size by extending the recruitment period to ensure greater consistency across age groups. Furthermore, the higher proportion of female participants, which is influenced by regional recruitment factors, may limit the generalizability of the findings. Previous studies have shown that gender differences exist in exercise habits and technology acceptance [48], which may also impact the interpretation of the effects of VR exercise on older adults. Gender differences should be a focus of future research to enhance the representativeness of the results. Moreover, older adults’ QOL may be affected by the economy, and stable wealth implies superior QOL [49]. In addition, living alone [50] or falls [51] are also potential factors affecting psychological QOL. Despite the differences in research design and tools used, these factors should be considered in future experiments in order to generate more comprehensive findings. Finally, subjective outcomes may be influenced by behavior and thoughts, and the experimental results may be sensitive. Studies have shown a positive correlation between functional ability and QOL in older adults [52]. Our study has concurrently assessed the participants’ functional capacity [35]. The EG has demonstrated improvements in both functional capacity and QOL after the intervention, providing evidence that the results are attributed to the exercise intervention.
5. Conclusions
This study’s 12-week semi-immersive VR-based fitness training intervention program improved the QOL of young-old and middle-old adults in terms of sensory abilities, autonomy, social participation/isolation, death and dying, and overall QOL. This suggests that the effects of the semi-immersive VR-based exercise programs on QOL were consistent in both age groups. However, a significant decline in QOL was observed in the older adults without exercise intervention, and similar findings were obtained in the young-old adults after age stratification.
This study underscores the importance of age-stratified, technology-based exercise interventions in enhancing QOL. We recommend that older adults maintain regular exercise in their daily lives, especially young-old adults. Moreover, further investigation into gender differences is warranted to address the existing research gaps and provide valuable insights for promoting sports technologies that enhance the QOL of older adults across all age cohorts.
Conceptualization, L.-T.W. and Y.-W.W.; Methodology, L.-T.W.; Software, L.-T.W. and Y.-W.W.; Validation, L.-T.W. and Y.-W.W.; Formal Analysis, L.-T.W.; Data Curation, L.-T.W.; Writing-Original Draft Preparation, L.-T.W.; Writing-Review & Editing, L.-T.W.; Visualization, L.-T.W.; Supervision, Y.-W.W. All authors have read and agreed to the published version of the manuscript.
This study employed a randomized controlled trial design (
Written informed consent has been obtained from the participant(s) to publish this paper.
The data supporting the findings of this study are available from the corresponding authors upon reasonable request.
We would like to thank several district communities in Taipei City, Taiwan, for helping with recruitment and support.
The authors declare that they have no competing interests.
Footnotes
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Enlarge this image.Figure 2. Non-interactive virtual reality-based exercise intervention for older adults.
Enlarge this image.Figure 3. Comparison of pre- to post-test quality of life change between the experimental and control groups of older adults.
Enlarge this image.Figure 4. Comparison of pre- to post-test quality of life change between the experimental and control groups of different age groups.
Semi-immersive VR-based exercise training protocol.
| Fitness Type | Training Elements | Frequency | Intensity Level | Approximate | Break |
|---|---|---|---|---|---|
| Warm-up and flexibility | Yoga focuses on stretching and breathing during warm-up to enable upper and lower limb joints and full body muscles to have sufficient mobility. | Twice a week for 12 weeks | Light | 20 min | 5 min |
| Muscle strength and balance training | Martial arts emphasize whole-body muscle stabilization (e.g., straight punch, knife hand, split squat, squat movements, etc.) to enhance muscle strength and body stabilization. | Moderate | 20 min | 5 min | |
| Cardiorespiratory fitness | Aerobic dance uses different fast and slow rhythms, adding some hand movements (e.g., push up, pull down, push forward, etc.) and forward or backward steps to continuously burn calories in the body, thus improving cardiorespiratory fitness. | Moderate | 20 min | 5 min | |
| Cool-down routines | Perform basic upper and lower body stretches to achieve complete relaxation. | Light | 15 min | No |
Characteristics of the two participant age groups.
| Variables | Young-Old Adults | Middle-Old Adults | p | ||
|---|---|---|---|---|---|
| EG | CG | EG | CG | ||
| Sex, male/female, n (%) a | 7 (26.9)/ | 5 (20.8)/ | 4 (21.1)/ | 4 (19.0)/ | 0.424 |
| Age (years), Mean (SD) b | 69.23 | 68.50 | 76.05 | 75.38 | <0.001 |
| Total leisure-time physical activity, Mean (SD) (min/wk) b | 428.65 | 419.17 | 295.00 | 343.10 | 0.031 |
| Vigorous physical activity, Mean (SD) (min/wk) b | 47.89 | 48.75 | 31.58 | 40.24 | 0.216 |
| Moderate physical activity, Mean (SD) (min/wk) b | 54.23 | 78.75 | 56.05 | 79.52 | 0.855 |
| Leisure-time walking, Mean (SD) | 326.54 | 291.67 | 207.37 | 223.33 | 0.035 |
Note: a chi-square test; b independent sample t-test.
Effects of the intervention on older adults’ quality of life.
| Outcome | Older Adults | Two-Way Repeated-Measure ANOVA | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| EG (n = 45) | CG (n = 45) | F-Value, p, (η2p) | ||||||||||
| Mean ± SD | Group | Time | Interaction | |||||||||
| Sensory abilities (score) | Pre | 10.20 ± 2.75 | 10.36 ± 2.85 | 6.29 | 0.014 | (0.07) | 16.13 | <0.001 | (0.16) | 26.91 | <0.001 | (0.23) |
| Post | 12.64 ± 2.09 | 10.04 ± 2.76 | ||||||||||
| Autonomy | Pre | 14.51 ± 2.24 | 14.96 ± 2.06 | 1.06 | 0.307 | (0.01) | 1.04 | 0.311 | (0.01) | 11.66 | 0.001 | (0.12) |
| Post | 15.62 ± 2.53 | 14.36 ± 2.10 | ||||||||||
| Past, present, and future activity (score) | Pre | 14.49 ± 1.67 | 14.56 ± 2.49 | 0.14 | 0.713 | (0.00) | 0.56 | 0.457 | (0.01) | 1.55 | 0.216 | (0.02) |
| Post | 14.84 ± 2.07 | 14.47 ± 2.37 | ||||||||||
| Social participation/isolation (score) | Pre | 14.38 ± 1.99 | 14.69 ± 2.43 | 0.07 | 0.790 | (0.00) | 2.82 | 0.097 | (0.03) | 7.08 | 0.009 | (0.07) |
| Post | 15.07 ± 1.70 | 14.53 ± 2.27 | ||||||||||
| Death and dying (score) | Pre | 14.98 ± 2.97 | 14.38 ± 4.29 | 2.77 | 0.099 | (0.03) | 4.25 | 0.042 | (0.05) | 7.56 | 0.007 | (0.08) |
| Post | 16.07 ± 3.00 | 14.22 ± 4.11 | ||||||||||
| Intimacy | Pre | 14.93 ± 2.73 | 14.58 ± 2.61 | 1.46 | 0.230 | (0.02) | 4.53 | 0.036 | (0.05) | 2.65 | 0.107 | (0.03) |
| Post | 15.60 ± 2.77 | 14.67 ± 2.56 | ||||||||||
| Total quality of life (score) | Pre | 83.49 ± 8.88 | 83.51 ± 10.75 | 3.48 | 0.065 | (0.04) | 15.11 | <0.001 | (0.15) | 32.92 | <0.001 | (0.27) |
| Post | 89.84 ± 10.43 | 82.29 ± 10.13 | ||||||||||
Effects of the intervention on older adults’ quality of life according to age.
| Outcome | Young-Old Adults | Middle-Old Adults | A Mix (4 × 2) Repeated-Measure ANOVA | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| EG (n = 26) | CG (n = 24) | EG (n = 19) | CG (n = 21) | F-value, p, (η2p) | ||||||||||
| Mean ± SD | Mean ± SD | Group | Time | Interaction | ||||||||||
| Sensory abilities (score) | Pre | 10.31 ± 2.41 | 10.83 ± 2.90 | 10.05 ± 3.05 | 9.81 ± 2.77 | 1.14 | 0.290 | (0.01) | 0.05 | 0.944 | (0.00) | 0.25 | 0.617 | (0.00) |
| Post | 12.65 ± 1.85 | 10.67 ± 2.63 | 12.68 ± 2.32 | 9.33 ± 2.80 | ||||||||||
| Autonomy | Pre | 14.88 ± 1.68 | 15.04 ± 2.24 | 14.18 ± 2.67 | 14.86 ± 1.88 | 1.42 | 0.236 | (0.02) | 0.02 | 0.900 | (0.00) | 0.25 | 0.616 | (0.01) |
| Post | 16.08 ± 2.51 | 14.29 ± 2.33 | 15.00 ± 2.30 | 14.43 ± 1.86 | ||||||||||
| Past, present, and future activity (score) | Pre | 14.54 ± 1.45 | 15.25 ± 2.67 | 14.32 ± 1.91 | 13.76 ± 2.05 | 0.55 | 0.461 | (0.01) | 0.02 | 0.893 | (0.00) | 4.48 | 0.037 | (0.05) |
| Post | 15.23 ± 2.08 | 14.83 ± 2.41 | 14.32 ± 1.97 | 14.05 ± 2.31 | ||||||||||
| Social participation/isolation (score) | Pre | 14.50 ± 1.92 | 15.33 ±2.47 | 14.21 ± 2.12 | 13.95 ± 2.20 | 0.35 | 0.557 | (0.00) | 0.02 | 0.882 | (0.00) | 3.61 | 0.061 | (0.04) |
| Post | 15.42 ± 1.65 | 14.88 ± 2.29 | 14.59 ± 1.62 | 14.14 ± 2.24 | ||||||||||
| Death and dying (score) | Pre | 14.42 ± 2.79 | 15.04 ± 4.55 | 15.82 ± 2.91 | 13.62 ± 3.93 | 2.40 | 0.125 | (0.03) | 6.80 | 0.011 | (0.07) | 1.09 | 0.300 | (0.01) |
| Post | 16.19 ± 2.88 | 15.21 ± 4.16 | 15.95 ± 2.99 | 13.10 ± 3.83 | ||||||||||
| Intimacy | Pre | 15.54 ± 2.12 | 15.33 ± 2.65 | 14.32 ± 3.17 | 13.71 ± 2.33 | 0.08 | 0.783 | (0.00) | 1.14 | 0.290 | (0.01) | 0.82 | 0.775 | (0.00) |
| Post | 16.00 ± 2.24 | 15.29 ± 2.37 | 15.05 ± 3.12 | 13.95 ± 2.64 | ||||||||||
| Total quality of life (score) | Pre | 84.19 ± 7.98 | 86.83 ± 9.99 | 83.00 ± 9.58 | 79.71 ± 10.54 | 0.90 | 0.345 | (0.01) | 0.31 | 0.578 | (0.00) | 1.62 | 0.206 | (0.02) |
| Post | 91.58 ± 9.23 | 85.17 ± 9.95 | 87.64 ± 10.90 | 79.00 ± 9.51 | ||||||||||
Supplementary Materials
The following supporting information can be downloaded at:
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; Yu-Wen, Wang 2 1 Department of Leisure and Recreation Management, Taipei City University of Science & Technology, Taipei 11202, Taiwan
2 Office of Physical Education, Chang Gung University, Taoyuan 33302, Taiwan;