This study adopted a quasi-experimental design, with participants voluntarily recruited from a pharmacy located in central Taiwan between April 2021 and February 2023. The participants themselves determined allocation to the experimental and control groups. The trial design was registered with ClinicalTrials.gov (identifier: NCT05412251) and followed the CONSORT (Consolidated Standards of Reporting Trials) guidelines (Multimedia Appendix 1). The inclusion criteria for this study were participants (1) aged 65 years or older and (2) fluent in Mandarin (speaking or reading). The study excluded participants who had a history of cognitive impairment, cancer, myocardial infarction, or congestive heart failure. This study used G power software to estimate the sample size. The effect size was calculated based on the pre- and posttest scores of the quality of life of older adults in the intervention group and the control group in a previous study [17]. The effect size was 0.19, the detection power was 0.8, the significance level (α) was .05, and the number of measurements was four times. The results showed that 40 participants were required in each group to ensure that a statistically significant difference in quality of life between the two groups could be detected during the follow-up period. Considering the attrition rate in interventional studies can be as high as 40% [18], at least 56 participants were recruited in each group at baseline. Data were collected at baseline (T0) and 12 weeks, 24 weeks, and 36 weeks postintervention (T1, T2, and T3). The data was collected face-to-face and self-reported by participants.

The design of the multihealth promotion program was based on previous studies. We combined 3 intervention strategies: social activities, physical training, and nutritional support, and used artificial intelligence exercise equipment as an assessment tool to measure physical performance during the exercise process [5,13,19]. For 12 weeks, participants in the experimental group engaged in social and physical activities while receiving nutritional support. (1) Social activities: this was combined with activities held at community base C, such as makeup, reading picture books, art classes, board games, and more, for at least 120 minutes, once a week. (2) Physical training: the utilization of artificial intelligence exercise equipment, suitable for middle-aged and older people’s exercise training and approved by the Food and Drug Administration of the Ministry of Health and Welfare. This was carried out at least 60 minutes, 3 times a week, including 8-10 minutes of warm-up exercise before exercise, after exercise, aerobic exercise, muscle strengthening training, and balance training, each requiring 15-20 minutes. Before each exercise, researchers used the exercise assessment and screening for you (EASY) tool to assess participants’ exercise risks, and the AI-enabled exercise equipment will evaluate participants and provide appropriate exercise prescriptions. Throughout the exercise, the researchers observed the physical condition of the participants constantly. If there were signs of discomfort, participants were asked to stop immediately. (3) Nutritional support: nutritionists screened participants’ nutritional status based on the mini nutrition assessment tool and based on personal wishes, provided free protein nutrition products in this plan. During the entire study period, the control group did not receive the intervention program for social activities, physical activity, or nutritional support. They only took measurements and questionnaires at monitoring time points (baseline, 12, 24, and 36 weeks). The on-site nutritionist was available for any questions from the control group.

The study measured demographic and baseline characteristics, frailty, nutrition status, well-being, and quality of life.

A researcher-made demographic form was prepared based on a literature review. It included age, gender, BMI, education level, lived conditions, and chronic disease.

The Clinical Frailty Scale (CFS) is used to assess frailty in older adults and was developed by Rockwood et al in 2005. This scale was updated to version 2.0 in 2020. The frailty scale ranges from 1 to 9, where level 1 indicates very fit and level 9 indicates terminally ill, corresponding to a survival time of fewer than 6 months [20].

The Mini-Nutritional Assessment-Short Form (MNA-SF) consists of 6 questions that assess key areas of nutritional assessment: decline in food intake, weight loss, mobility, psychological stress or acute disease, neuropsychological problems, and BMI. The total score classifies individuals into 3 categories, normal nutritional status (12-14 points), at-risk of malnutrition (8-11 points), and malnourished (0-7 points). The MNA-SF has been validated in various studies and settings, demonstrating high sensitivity and specificity [21].

The EASY is an exercise screening and assessment tool designed to help older adults choose safe and effective exercise modalities and physical activity programs. There are 6 questions, each of which can be answered with “yes” or “no.” If the answer to one of the questions is “yes,” the participant must find a health care provider to discuss an appropriate exercise plan before exercising [22].

The Well-being Scale for Elders is a 9-item self-report questionnaire, including emotional, psychological, and social well-being. The higher scores indicate better well-being. It has good reliability and construct validity and can be effectively used to measure the happiness of older adults. The Cronbach α is 0.91, and the factor analysis results explain 59.67% of the variation [12]. In this study, Cronbach α is 0.82.

The EQ-5D 3L is a standardized instrument developed by the EuroQol Group to measure general health status. It is widely used in both clinical and economic evaluations to assess health-related quality of life. The EQ-5D index comprises 5 dimensions: mobility, self-care, daily activities, pain or discomfort, and anxiety or depression. Each dimension has 3 levels of severity (no problems, moderate problems, and extreme problems). Higher scores on this index indicate a poorer health-related quality of life. EQ-VAS (European Quality of Life Visual Analogue Scale) is a visual analog scale ranging from 0 to 100, with higher scores indicating a better-perceived quality of life. Respondents evaluate their overall health on a scale from 0, indicating the worst possible health, to 100, indicating the best possible health [23]. The EQ-5D-3L has demonstrated good reliability, validity, and sensitivity for measuring health-related quality of life [24]. In this study, Cronbach α is 0.8.

All data were analyzed using the SPSS software program (version 24; IBM Corp). This research uses descriptive statistics to analyze frequencies, means, and SD. Differences in outcome variables at baseline between the two groups are analyzed using the chi-square test and an independent t test. The Generalized Estimating Equations (GEE) analyze changes over time, group differences, and group-by-time interactions, including body composition, frailty, well-being, and quality of life.

This study was conducted with the utmost ethical considerations and approved by the National University Institutional Review Board (YM110168EF). All participants were respected, and their autonomy was upheld, as they provided written informed consent before enrollment. Participants were fully informed by a research assistant about the study’s purpose, procedure, benefits, and potential risks, ensuring transparency and respect for their rights and welfare. The participant data has been deidentified for privacy concerns.

This study’s findings indicate that an intervention program encompassing exercise, social activities, and nutritional prescriptions significantly improved muscle mass, muscle strength, and QoL in the experimental group. Exercise programs have been demonstrated to enhance physical function, body composition, QoL, and muscle strength in older adults [6,9,10,16]. However, their effects on mental health and subjective QoL are less consistent and warrant further investigation. In this study, the experimental group’s QoL (measured by the EQ-5D index) was significantly higher than the control group at weeks 12 and 24. However, no significant difference was observed in EQ-VAS scores. By week 36, the experimental group showed a trend of improvement in QoL, suggesting that the intervention may have long-term benefits for mental health. These findings align with Marcos-Pardo et al [6,9], who reported that resistance training interventions improved lean body mass, muscle strength, and QoL. In a randomized controlled trial (RCT) by P J Marcos-Pardo et al [6], the experimental group participated in an 8-week outdoor resistance training program involving bi-weekly sessions with weight machines. Results revealed significant increases in lean body mass, reductions in fat mass, and improvements in muscle strength (arm and leg), functional activity, and QoL. At the same time, the control group experienced declines in muscle strength, activity capacity, dynamic balance, and QoL. Another RCT by Marcos-Pardo et al [9] demonstrated that older adults in the experimental group engaging in moderate-to-high intensity resistance circuit training for 12 weeks experienced significant reductions in body weight, fat mass, and BMI, along with significant improvements in lean body mass, functional independence, and upper and lower limb strength. However, no significant changes in body fat or visceral fat were observed in the experimental group during the study period. Chittrakul et al [10] conducted an RCT involving prefrail older adults with a 12-week exercise intervention and a two-year follow-up. The experimental group exhibited significant improvements in muscle strength at week 12, with enhancements in knee extension, balance, and reaction time persisting through week 24. The experimental group’s health-related QoL was significantly higher than the control group at week 12. However, by week 24, despite the control group engaging in thrice-weekly stretching exercises, there was no significant difference in QoL between the groups, contrasting with this study’s sustained improvements in the experimental group beyond week 24. This study also observed a BMI reduction at week 36, differing from previous findings [9], underscoring the need to explore further BMI changes and their relationships with muscle mass and strength.

Unlike the QoL findings, this study did not detect significant differences in well-being between the experimental and control groups, contrasting with the findings of Lai et al [25] and Jung et al [26]. The quasi-experimental study by Lai et al [25] demonstrated that a 6-day outdoor activity program, including kayaking, rafting, hiking, and camping, significantly improved well-being, self-image, and mental health among older adults, differing from this study’s results. Similarly, Jung et al [26] reported that a 6-week integrated cognitive function improvement program significantly enhanced cognitive function and well-being in the experimental group, with no significant changes observed in the control group. The lack of significant well-being improvements in this study might be attributable to participant characteristics, cultural contexts, or the predominantly indoor nature of the intervention activities. Notably, previous research [27] has highlighted the mediating and moderating roles of outdoor and group exercise in enhancing well-being, emphasizing the psychological benefits of these activities. This underscores the importance of environmental and social factors in promoting well-being. The findings related to well-being suggest that additional intervention components beyond physical and nutritional strategies may be necessary. Factors such as depression risk, social relationships, and leisure activities have been shown to influence well-being [11]. Furthermore, Yang et al [27] emphasized that outdoor environments and group interactions significantly enhance well-being by fostering social connections and providing meaningful engagement. Future studies should consider integrating these elements to maximize the psychological benefits of multicomponent interventions.

Exercise and nutritional interventions have positively affected older adults’ physical function and weight management. Liao et al [19] showed that combining exercise with nutritional support improved grip strength and walking speed despite limited changes in lean body mass. Similarly, in this study, while there were no significant changes in body fat or visceral fat in the experimental group, muscle mass significantly increased at week 24, with effects sustained through week 36. Upper limb strength improved significantly up to week 36, whereas lower limb strength showed significant improvements only at week 12. These findings highlight the need for more targeted designs in future interventions to address lower limb training.

This study underscores the potential of multidisciplinary active aging programs to improve physical function, QoL, and muscle strength among community-dwelling older adults. Such programs have been shown to reduce frailty risk, enhance flexibility, and promote social participation [28]. However, single-component nutritional interventions may have limited effects on individuals without malnutrition or unintentional weight loss [4], consistent with this study’s findings. Clinicians should prioritize integrating physical, nutritional, and social interventions into comprehensive strategies tailored to older adults’ needs. Muscle mass and muscle strength are positively correlated, and increasing muscle mass is key to improving muscle strength in older adults. Muscle mass and body fat percentage are important predictors of muscle strength. With aging, physical fitness declines, and body composition changes (eg, decreased muscle mass and increased obesity) are common [29]. Enhancing muscle strength is critical for clinical health care providers, contributing to improved stability, coordination, flexibility, and balance, ultimately reducing injury risk [30]. As global life expectancy rises and the proportion of older adults increases, promoting healthy aging is not merely a slogan but an urgent priority. However, physical inactivity and nutritional issues are prevalent among older adults [31], and these challenges are closely tied to their health and QoL [3]. While this study did not delve deeply into the influencing factors of QoL, well-being, and nutritional status, the results suggest these areas are important directions for future research.

This study has several limitations that must be noted. First, the quasi-experimental design may introduce selection bias, as participants were not randomized. Second, the predominantly indoor nature of the activities may have limited the potential psychological benefits. Third, this study did not explore the influence of individual variability in adherence and baseline activity levels on the outcomes. Fourth, it was unable to determine the potential for individuals in either the experimental or control group to participate in additional outdoor or physical activities outside of the intervention program, which could have influenced the results. Further studies should address these limitations by employing randomized controlled trial designs, which include outdoor and group-based activities, examining the effects of participant adherence and baseline characteristics, and tracking any additional activities performed outside of the intervention.

In conclusion, this study confirms the beneficial effects of multicomponent intervention programs on older individuals’ physical function and quality of life. However, the limited benefits on well-being underline the importance of more comprehensive solutions that consider psychological and social aspects. Future studies should concentrate on the long-term assessment of nutritional status, quality of life, and well-being and the creation of individualized intervention programs that incorporate outdoor activities to promote active and healthy aging.