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Abstract

The purpose of this study was to use the aerobic exercise program as an intervention to understand exercise awareness and exercise behavior in older adults and to predict health promotion. This study recruited 120 healthy older adults (60 males and 60 females) over 65 years old (average male age 72.15 ± 3.53 years, female average age 71.64 ± 3.97 years), males and females were randomly assigned to the experimental group, and the control group (30 males, 30 females). The experimental group underwent an “aerobic fitness exercise program” for 8 week, while the control group underwent 8 weeks of daily life. All participants were first surveyed on background variables. At the beginning and end of the experiment, the experimental group and control group of males and females had to undergo the senior fitness test (SFT), the Elderly Exercise Awareness and Exercise Behavior Scale (EAEBI) and the Elderly Health Promotion Inventory (HPI) survey. The results of the study showed that male Cohen’s d = .326, and female Cohen’s d = .371, both showed small effects; related power analysis male effect size (es) = 0.2, female effect size (es) = 0.1, showed that the participants were homogeneous, the mean ages of males and females of the Q-Q plot showed normality. The SFT analysis of the experimental group and the control group found that Int-2, Int-1, Con-1, and Con-2 were significantly different between males and females. The EAEBI scale analysis found that the male experimental group had the largest difference in awareness effect (F = 9.47, p < .05), and the female experimental group had the largest difference in exercise cognition (F = 11.35, p < .05). HPI scale analysis found that the male experimental group had the largest difference in physical activity (F = 14.83, p < .05), and the female experimental group had the largest difference in social support (F = 13.19, p < .05). Finally, the intervention measures of aerobic fitness exercise program could positively affect the exercise perceived and exercise behavior of the older adults, and had positive effects on health promotion. This study has practical significance for an aging society. Promoting health through regular exercise can also reduce medical resources, which is the subject of effective preventive medicine.

Plain language summary

The purpose of this study was to use the aerobic exercise program as an intervention to understand exercise awareness and exercise behavior in older adults and to predict health promotion. This study recruited 120 healthy older adults over 65 years old, males and females were randomly assigned to the experimental group and the control group (30 males, 30 females). The experimental group underwent an “aerobic fitness exercise program” for 8 weeks, while the control group underwent 8 weeks of daily life. All participants were first surveyed on background variables. At the beginning and end of the experiment, the experimental group and control group of males and females had to undergo the senior fitness test (SFT), the Elderly Exercise Awareness and Exercise Behavior Scale (EAEBI), and the Elderly Health Promotion Inventory (HPI) survey. The results of the study showed that the participants were homogeneous, and the mean ages of males and females of the Q-Q plot showed normality. The EAEBI scale analysis found that the male experimental group had the largest difference in awareness effect, and the female experimental group had the largest difference in exercise cognition. HPI scale analysis found that the male experimental group had the largest difference in physical activity, and the female experimental group had the largest difference in social support. Finally, the intervention measures of aerobic fitness exercise programs could positively affect the exercise perceived and exercise behavior of the older adults, and have positive effects on health promotion. This study has practical significance for an aging society. Promoting health through regular exercise can also reduce medical resources, which is the subject of effective preventive medicine.

Keywords

senior fitness test exercise awareness exercise behavior exercise adherence health promotion

Introduction

Noncommunicable diseases (NCDs) pointed out that physical inactivity was the fourth most significant risk factor for poor health globally, and it was also considered a risk-modifying factor for noncommunicable diseases. It also pointed out that physical activity was essential for healthy aging (NCD, 2016). The World Health Organization (WHO, 2022) pointed out that despite people’s awareness of the health risks of physical sedentary and the benefits of physical activity, physical inactivity is still prevalent worldwide. The Centers for Disease Control and Prevention (CDC) reported that about a quarter of adults in the United States physical inactivity (Ali, 2022), especially the physical activity of older adults did not meet the physical activity guidelines in the United States (Izquierdo et al., 2021). According to the regular exercise population survey in Taiwan 2019, only 33.6% of adults have regular exercise habits (Hong, 2020). Studies also point to regular physical activity as one of the essential things that older adults could do for their health, preventing or delaying aging (Füzéki et al., 2017; Macera et al., 2017; WHO, 2018).

The so-called awareness was the state or ability to perceive, feel, or be aware of events, objects, or sensory patterns. At this level of awareness, the observer could confirm the sensory data without implying understanding. More broadly, awareness is the human or animal perceptual and cognitive responses to conditions or events (Vaara et al., 2019). Langer (2009) proposed that mindfulness versus adjusting awareness could improve health. However, exercise awareness refers to using of psychological phenomena such as sensation, perception, thinking, and memory to perceive the preferences, habits, and values of the individual’s internal and external physical and mental states for these exercises (Godino et al., 2014). Moreover, positive exercise awareness refers to setting exercise goals, formulating exercise plans, and setting the intensity and duration of each exercise (Chang et al., 2017; Locke & Brawley, 2018). Langer proposed that the brain’s exercise awareness is as important as participating in the exercise. At the same time, it proved that with positive exercise awareness, older adults could more easily achieve health and improve their fitness levels (Langer, 2009). It was known from the above that improving exercise awareness can help improve the exercise behavior of older adults. However, there were few studies, and this was the primary motivation for this study.

The so-called exercise behavior refers to a planned, structured, repetitive, and purposeful physical activity to improve or maintain one or even several elements of physical fitness (Parry, 2023). This study defines exercise behavior as planned, with intensity and duration. According to WHO (2022), the definition of older adults (over 65 years old) exercise behavior should have at least 150 to 300 minutes of moderate-intensity exercise per week, or at least 75 to 150 minutes of high-intensity exercise, or a combination of moderate- intensity and high-intensity activities throughout the week, and weekly be physically active on three or more days. In addition, this study designed a multi-content aerobic exercise program, adopted group exercise, and specially assigned personnel to teach and master exercise intensity (Dorgo et al., 2009) and monitor attendance rate (Sullivan-Marx et al., 2011), which was beneficial to the older adults to develop exercise adherence (Hawley-Hague et al., 2016). According to the Ottawa Charter adopted by the World Health Organization in 1984, health promotion was broadly defined as the process of enabling people to strengthen their control and improve their health to promote people to have positive health. This study narrows the scope of the definition and defines health promotion as the effect of improving the health of older adults through exercise intervention. Evidence has shown that the ability of older adults to remain physically active is the most critical factor in health-promoting activities (Rababa et al., 2021).

Physical activity interventions positively impacted health promotion, especially in the quality of life of older adults (Chia et al., 2023). Many studies focus on people’s mental health. There was evidence that exercise could relieve stress (Y. Zhang et al., 2020), reduce anxiety levels (Cho & Kim, 2020), reduce the breadth and depth of depression (Huang et al., 2022), and promote mental health (P. Wang et al., 2023). However, the functional decline of older adults and their spouses, the high risk of cognitive decline, and the lack of social activities and support from group partners could easily cause the psychological pressure of loneliness and helplessness in older adults. Therefore, this study used the intervention of an aerobic exercise program to make older adults aware of the importance of physical activity, create an opportunity for group exercise, establish exercise adherence (Picorelli et al., 2014), and then achieve regular exercise behavior. In addition, this study uses older adults, males, and females, as participants, which may cause research interference due to gender differences. However, anti-aging is one of the purposes for older adults males and females, to participate in exercise (Luo & Cai, 2009); some researchers have pointed out that the older adults of males and females, the higher the rate of regular exercise (S. F. Shaw & Chen, 2003) because most males want to build a strong body, females want to maintain a slim body (Huang et al., 2022). Some studies have pointed out no significant difference in the probability of regular exercise between males and females (Hong, 2020). Therefore, the older adults of males and females were all participants in this study, and factors such as age, previous exercise experience, and current living conditions were all background variables that affect the exercise of older adults (Boyette et al., 2002; Janke et al., 2006; McKee et al., 2015; Pettee et al., 2006).

The global population is rapidly aging and the average life expectancy is gradually increasing. Maintaining or improving their physical health and daily life ability by improving the exercise behavior of the older adults is a problem worthy of attention. Although the effect of exercise on maintaining or improving the health of the older adult is well known, studies have pointed out that to develop autonomous exercise behavior in the older adult, one should first understand the background factors and exercise awareness of the older adult (Huang & Wu, 2021; Pienaar et al., 2004; Tsuji et al., 2022). Therefore, focusing on the purpose of this study, exercise intervention was used to improve older adult’s exercise awareness and the benefits of exercise behavior for health promotion. Based on this, this study proposed the following assumptions and tested them step by step. Hypothesis 1: The benefits of an aerobic fitness program intervention on changing exercise awareness and exercise behavior for older adults. Hypothesis 2: Exercise awareness and exercise behavior after aerobic fitness program intervention could effectively predict t health promotion for older adults.

Materials and Methods

Research Framework

The experimental group was implemented in the gymnasium and gymnasium of the community college, and the research team taught the “aerobic fitness exercise program” for 8 weeks (Monday to Friday, 2 hours a day). The control group was implemented in the community public leisure center, guided by on-site service volunteers, such as daily life or going to the community public leisure center to read, watch videos, play chess, or chat casually during the 8 weeks. All participants established a “LINE group”, followed the research plan from the beginning to the end of the study, and used the “LINE group” at any time to post messages for the next day or for participants to take leave.

The experimental group and the control group were first investigated on background variables. Before and after the 8-week experiment, all participants implemented the “Senior Fitness Test (SFT)” and the “Exercise Awareness and Exercise Behavior Inventory (EAEBI),”“Health-Promoting Inventory (HPI)” survey. Finally, understand the explanatory power of exercise cognition, exercise self-discipline, awareness effect exercise behavior, and other factors for the health promotion of older adults, Based on these viewpoints, the framework of this study was established, as shown in Figure 1.

Figure 1.

Research framework.

Participants

This study takes healthy older adults over 65 in Taipei as the population (Rudnicka et al., 2020). It promotes it through posters in the physical fitness center of the college (including QR code link registration information, online registration, and community service center placing paper registration brochures). Open recruitment of 60 males and 60 females in the community of Taipei City, a total of 120. This sampling was conducive to the research team recruiting research objects efficiently. However, it was not an entirely randomly selected sample, but for this study, the convenience sampling can be selected eligible participants for the study. The recruited participants were randomly assigned to the experimental and the control groups according to their wishes, with 30 males and 30 females.

All participants excluded those unable to participate because of age, mental or physical condition, or vulnerability to undue influence and coercion, or who were unable to participate because of circumstances, status, or social and economic conditions, and who were able to make decisions of their own volition. Participants recruited had to complete a survey of background variables, including gender, age, previous athletic experience, and current residential status. All participants in this study signed the informed consent form, which complies with scientific and ethical principles (contents include: no orthopedic disease or heart disease, and no usual exercise program). This study was approved by the Human Trials Review Meeting at Tri-Service General Hospital, National Defense Medical College, approval number C202305014.

Research Materials

The intervention measures correspond to the part of the experimental group in this study. Since the participants were recruited, the ages of the experimental group and the control group were t-tested, and it was found that there was no significant difference in the age of males or females, showing homogeneity. Since the control group still adopted a daily lifestyle or went to the community public center for static activities, the experimental group adopted the intervention measures of an aerobic fitness exercise program, and the data collected were differed from the daily lifestyle.

According to the Physical Activity Guidelines for Americans (PAGA) (Piercy et al., 2018) formulated an exercise prescription for an aerobic fitness program, and the experimental group experienced a total of 8 weeks of exercise intervention, as shown in Table 1. This study’s type of exercise prescription includes three parts: aerobic exercise, endurance training, and flexibility training. The principles of exercise prescription include exercise frequency, intensity, type, time, and progressive load (Rooney et al., 2023). In this study, the Borg CR-10 scale was used to measure the exercise intensity, which was set at 4 to 5 points of moderately strenuous aerobic exercise intensity to ensure the perceived safety intensity of the participants (Morishita et al., 2018; Shariat et al., 2018). An aerobic fitness program strengthens the heart and lungs through cardiorespiratory endurance training, making the muscles more efficient at using oxygen and increasing cardiac output (Harveson et al., 2016).

Table 1.

Exercise Prescription for a One-Week Aerobic Fitness Exercise Program.

Week	Prescription	Content
Week	Prescription	[Frequency and time, intensity, progressive load]
Mon. & Thu.	Aerobic training for walking	20 to 60 minutes/day (continuous or intermittent) or complete 8,000 steps a day. Moderate intensity (Borg CR-10): 4 to 5 points (You can talk while exercising). Start at a low intensity, slowly increase the time, and then try to increase the intensity.
Mon. & Thu.	Aerobic training for walking	[Content]Walking (400 m oval runway outside the school, at a speed of 6 km/hour, for 30 minutes).
Tue. & Fri.	Flexibility training	Upper and lower body flexibility exercise, each movement 10 to 30 seconds. It is advisable to feel slight discomfort, but not to the extent of pain. Slowly progress from static stretches to dynamic stretches, gradually reducing the degree of support from other objects.
Tue. & Fri.	Flexibility training	[Content]Upper body stretches1. Shoulder and upper back stretch2. Shoulder rolls3. Neck side stretch4.Neck rotation5. Shoulder circles6. Shoulder stretch7. Chest stretch8. Overhead reach9. Reach back10. Triceps stretch11. Hand stretch12. Arm raises	[Content]Lower body flexibility exercise1. Seated lifts2. Standing quadriceps stretch3. Backstretch4. Inner thigh stretch5. Calf stretch6. Hip side stretch7. Hip rotation stretch8. Soleus stretch9. Ankle circles10. Hamstring stretch11. Knee to chest12. Ankle stretch
Wed.	Resistance training	Eight kinds of resistance training, 15 times for each movement, repeated three rounds. Medium-to-high intensity (Borg CR-10): 4 to 5 points. Start with low intensity. If you feel a little difficult but acceptable, you can increase the load.
		[Content]1. Chair squats: 15 (times) × 3 (set): Place a chair behind you, and start the standing position; squat down and raise your hands horizontally, and then squat down and touch the chair with your buttocks and immediately rise into a standing position. Do this once.
		2. Pistol squat: 10 (times) × 3 (set): Stand on one foot and leave the other foot off the ground (you can hold a support), and perform 10 deep squats on the left and right feet.
		3. Standing lunges: 20 (times) × 3 (set): Start in a standing position; put your feet together. Step on one foot (with a stride of more than 60 cm), retract the leg that has stepped out, and step out with the other foot. Repeat the motion with your left and right feet 20 times.
		4. Walk in place with high legs: 20 (times) × 3 (set): Start a standing position, raise the leg in place up to thigh-level, and repeat the operation with the left and right feet 20 times.
		5. Dumbbell arm curls: 12 (times) × 3 (set): Stand vertically with dumbbells in your hands, and abduct your hands to a horizontal level at the same time. (Female 6-pound/Male use 8-pound dumbbell)
		6. Dumbbell flyers: 12 (times) × 3 (set): Stand vertically with dumbbells in your hands and abduct your hands to a horizontal level at the same time (Female 6 lb/Male use 8 lb dumbbell).
		7. Dumbbell shoulder raises: 12 (times) × 3 (set): Hold the dumbbells at shoulder height as the starting point, raise both hands vertically at the same time, and then return to the starting point. (Female 6-pound/Male use 8-pound dumbbell)
		8. Step-ups: 20 (times) × 3 (set): 30 cm high steps; go up the steps with one foot, stand with both feet together, go down the steps with one foot, stand with both feet together, and repeat.

Note. Using Borg Category-Ratio 10 (CR-10) scale (Rating=Descriptor): 0 = Rest; 1 = Very, very easy; 2 = Easy; 3 = Moderate; 4 = Somewhat hard; 5 to 6 = Hard; 7 to 9 = Very hard; 10 = Maximal.

Detection Method

Senior Fitness Test (SFT)

We referred to the Senior Fitness Test (SFT) developed by Rikli and Jones (2013), as showed in Table 2. SFT detection items have been applied in many studies, showing that the use of SFT to detect lower limb muscle strength in older adults was effective and reliable (Bhattacharya et al., 2016; Hesseberg et al., 2015; Langhammer & Stanghelle, 2015; J. D. Liu et al., 2019), the test items include 30-second sit-to-stand movement, 30-second dominant arm curl, 8-foot up-and-go (2.44 m), 2-minute step, and single leg (SL) exercises.

Table 2.

Brief Description of the Senior Fitness Test.

Test item	Test description
30 second sit-to-stand	Number of full stands completed in 30 second with arms folded across chest.
30 second dominant arm curl	Number of bicep curls completed in 30 second holding a hand weight (Females used a 6-pound dumb-bell; males used an 8-pound dumb-bell).
2 minute step	Number of full steps completed by raising each knee to a point midway between the patella and iliac crest (Number of times the knee reaches the target) in 2 minute.
Single leg (SL)	Participants had to lift one leg off the ground and maintain their balance while standing.
8-foot up-and-go	Number of seconds required to get up from a seated position, walk 8 ft (2.44 m), turn around, and return to a seated position on the chair.

Note. Description of SFT items, from Rikli and Jones.

Exercise Awareness and Exercise Behavior Inventory (EAEBI)

Based on the “Cognitive Behavioral Physical Activity Questionnaire” (CBPAQ) compiled by Schembre et al. (2015), this study revised and completed the first draft. A total of 16 questions were revised and revised into a five-point Likert scale (Joshi et al., 2015), named the “Exercise Awareness Scale” for older adults. The Exercise Behavior Scale for Older Adults was adapted from Ku et al. “Chinese version of the physical activity scale for older adults.” This Chinese version of the scale was a short and easy-to-score survey assessing physical activity performed over 1-week, for example, leisure time, housework, and occupational work (M. Y. Chen et al., 1997; Joshi et al., 2015; Ku et al., 2013). Since this research focused on the exercise of older adults during their leisure time, the exercise situation during leisure time was intercepted, and issues such as exercise intensity and exercise time were revised and added. A total of five questions were revised and completed, named the “Exercise Behavior Scale” for older adults.

Combined with the above subscales, it was named “Exercise Awareness and Exercise Behavior Inventory” (EAEBI) for older adults. The first draft of the scale was completed, and 100 senior students (average age 75.64 ± 1.85 years old) of the College were sampled for a pre-test. The pre-test data was completed for item analysis, and all the topics were still reserved, with 21 items. Part 1: Exercise awareness consists of 16 items, divided into three factors: exercise cognition, exercise self-discipline, and awareness effect. The reliability analysis of each factor was as follows: exercise cognition (Six items, Questions 1–6, explained variance for 21.37%, Cronbach α = .81), exercise self-discipline (five items, questions 7–11, explained variance for 25.52%, Cronbach α = .79), awareness effect (five items, questions 12–16, explained variance for 23.18%, Cronbach α = .83). This questionnaire used a five-point Likert scale and the response interval for each item: 1 = strongly disagree, 2 = slightly disagree, 3 = slightly agree, 4 = agree, 5 = strongly agree (Joshi et al., 2015). Part II: A total of five items in exercise behavior (questions 17–21, explained variance for 29.46%, Cronbach α = .85). The scale was reliable; Cronbach’s alpha coefficient was between .79 and .85. The “EAEBI Scale for the older adult” quantifies psychometric attributes using a data approach. The scale used a Likert “five-point” scale. For example, the favorable items ranging from strongly agree to strongly disagree were 5, 4, 3, 2, and 1 points respectively (Joshi et al., 2015), as shown in Table 3.

Table 3.

Factors and Items of EAEBI.

Factors and items
Factor 1	Exercise cognition
1	I realize that daily exercise is essential in life.
2	I am aware of maintaining physical function.
3	I realize I get enough exercise every day.
4	I am aware of the intensity of each exercise.
5	I am aware of the length of each exercise.
6	I realize that my body feels better after every exercise.
Factor 2	Exercise self-discipline
7	I often go outdoors for exercise.
8	I always make time to exercise.
9	I am motivated to exercise.
10	I like to exercise in my free time.
11	I demand the intensity with which I sweat or pant during exercise.
Factor 3	Awareness effect
12	Exercise makes my daily life mentally better.
13	Exercise makes me feel good.
14	Exercise can release emotions.
15	Exercise can relieve stress.
16	Exercise makes my mind clearer.
Factor 4	Exercise behavior
17	In the past 7 days, how many days have you been outdoors (exercise, walking, walking the dog, etc.)?
	(1) Never; (2) Rarely (1–2 days); (3) Sometimes (3–4 days); (4) Often (5–6 days); (5) Every day (7 days).
18	For how many hours do you exercise, walk, or walk your dog outdoors?
	(1) Less than 1 hour (2); More than 1 but less than 2 hours (3); More than 2 but less than 3 hours (4); More than 3 but less than 4 hours; (5) More than 4 hours.
19	In the past 7 days, how much moderately strenuous physical activity have you performed (the intensity of chatting, but not singing)?
	(1) Less than 60 minutes; (2) More than 60 minutes but less than 90 minutes; (3) More than 90 minutes but less than 120 minutes; (4) More than 120 minutes but less than 150 minutes; (5) More than 150 minutes.
20	In the past 7 days, how many steps have you walked on average each day?
	(1) Fewer than 2000 steps (2); More than 2000 but fewer than 4,000 steps (3); More than 4,000 but fewer than 6,000 steps (4); More than 6,000 but fewer than 8,000 steps (5); More than 8,000 steps.
21	What is your average walking rate?
	(1) Less than 40 steps per minute; (2) More than 40 but less than 60 steps per minute; (3) More than 60 but less than 80 steps per minute; (4) More than 80 but less than 100 steps per minute; (5) More than 100 steps per minute.

Health Promotion Inventory (HPI)

This study revised M. Y. Chen et al. (1997)“Revision of the Chinese version of the Health-Promoting Lifestyle Inventory (HPLI)”. The first draft of the scale was completed, and the same sample as the EAEBI pre-examination will be assisted by the research team assisted on-site in the senior classroom to fill in the explanation (question meaning description). After the pre-test was completed, the internal consistency of the project analysis was high, and the questions not be deleted. The total cumulative explained variance of the scale was 77.46%, which had construct validity. Reliability analysis in order to understand the consistency and stability of the scale, the Cronbach α value was used to analyze the internal consistency of the items with the same factors. The reliability analysis results that the Cronbach α value was between .69 and .75. Factor analysis extracted six factors with a total of 34 items, including health responsibility (five items), physical activity (six items), nutrition (seven items), spiritual growth (five items), social support (six items) and stress management (five items), named “Health Promotion Inventory (HPI)” for older adults. The scale used a Likert “five-point” scale. For example, the favorable items ranging from strongly agree to disagree firmly were 5, 4, 3, 2, and 1 points respectively (Joshi et al., 2015), as shown in the Table 4.

Table 4.

Factors and Items of HPI.

Factors and items
Factor 1 health responsibility
1	I watch TV programs about improving health.
2	I discuss my health concerns with a health professional.
3	I get a second opinion when I suspect advice given by my healthcare professional.
4	I examine my body at least once a month to detect any physical changes.
5	I attend educational programs on healthcare.
Factor 2 physical activity
6	I exercise vigorously for 30 minutes or more at least three times a week (e.g., brisk walking, climbing stairs).
7	I participate in physical activity at a mild to moderate level (e.g., walking continuously for 30–40 minutes five times or more per week).
8	I do stretching exercises at least three times a week.
9	I participate in leisure physical activities (such as swimming pool, spa, dancing, tai chi, and croquet).
10	I exercise while doing daily activities (such as using stairs instead of elevators, walking short distances, cleaning, and shopping).
11	I check my pulse rate while exercising.
Factor 3 nutrition
12	I choose a diet low in fat, saturated fat, and cholesterol.
13	I limit my intake of sugar and foods that contain sugar (sweets).
14	I eat 1.5 to 4 bowls of staple food, including cereals, rice, and noodles, daily.
15	I eat two to four fist-sized pieces of fruit daily.
16	I eat three to five plates of vegetables daily.
17	I drink 350 to 500 mL of dairy daily.
18	I eat 115 to 300 g of meat, chicken, fish, dried beans, eggs, or beans daily.
Factor 4 spiritual growth
19	I get enough sleep.
20	I feel I am growing and changing in a positively way.
21	I believe that my life has a purpose.
22	I look forward to the future.
23	I concentrate on pleasant thoughts before bed.
Factor 5 social support
24	I discuss exercise patterns with my friends.
25	I compliment my friends’ athleticism.
26	I exercise with my friends.
27	I show concern for my friends.
28	Playing sports with my friends makes me happy.
29	I get support from friends while exercising.
Factor 6 stress management
30	I accept things I cannot change in my life.
31	I feel satisfied and calm with myself.
32	Exercise makes me less stressed.
33	I find that every day is exciting and challenging.
34	I calm myself to avoid fatigue.

Control Variable

Healthy older adults were recruited as participants, and the background variables, such as gender, age, previous exercise experience and current residential status, were associated with health promotion (Bartram, 2021; Nielsen et al., 2021). Background variables include many factors, such as education level, previous occupation, residence time, living environment and family income, etc. The study did not consider these factors or potential influencing variables, the main reason was that the participants were all living in the urban-adjacent community (radius 5 km), and the participants were homogeneous through convenience sampling, thus reducing the influence of other factors on the results. In addition, this study focused on the explanatory power of exercise awareness and exercise behavior for health promotion. Exercise awareness was an abstract concept. Understanding the factors in exercise awareness would facilitate follow-up research and reduce the interference of potential factors. The experimental site had diet publicity materials, and the research team had a short three-minute oral diet publicity and health reminders at the end of each course. This was the control method for dietary variables in this study.

Statistical Analysis

First, the Quantile-Quantile (Q-Q) diagram of SPSS was used to judge the normality for 120 participants (Qiu et al., 2022). Cohen’s d was used to confirm the adequacy of the sample size (Cohen, 1988), and then JASP Team (2022) was used to detect the Cohen’s d effect. The recruited participants will be divided into the experimental and the control groups according to the total number of males and females. The samples of this experimental group and the control group were from the same group (the experimental group and the control group have the same number of samples, 30 people each), so power analysis can be performed (Kemal, 2020; Suresh & Chandrashekara, 2012).

The mean (Mean) and standard deviation (Std. Deviation) of all background variables for all participants included: gender, age, previous exercise experience, and current residential status, and a t-test was performed on the background variables of males and females. SFT detection, EAEBI, and HPI surveys, the experimental group intervention start (Int-1), the experimental group intervention end (Int-2), the control group pre-test (Con-1), the control group post-test (Con-2) data, presented in standard deviation (Std. Deviation) and mean (Mean) (Kelley & Rausch, 2006). All “int-1, int-2, con-1, con-2” differences were compared using Repeated Measures ANOVA, and the overall significance level was set at p < .05. Variation analysis (F test) and Durbin-Waston test (the test value is distributed between 0–4, the closer to 2, the greater the possibility that the observed values are independent of each other) between the factors of each scale (Durbin & Watson, 1951). Then, the Pearson product-moment correlation was used to compare the relationship between the factors of the two scales. Finally, multiple regression analysis was used to understand the explanatory power of exercise awareness and exercise behavior on the health promotion of older adults. The data in this study were analyzed using SPSS 20.0 software (IBM^®, Armonk, NY, USA).

Results

Analysis of the Background Variables of Participants

The background variables of 120 participants recruited in this study include gender, age, previous exercise experience, and current residential status, as shown in Table 5.

Table 5.

Analysis of Socio-Demographic Variables of Participants.

	Male (n = 60)	Female (n = 60)	t-value	p-value
Variables	M ± SD	M ± SD	t-value	p-value
Age (years)	72.15 ± 3.53	71.64 ± 3.97	0.86	.34
Previous exercise experience	N (%)	N (%)	t-value	p-value
Never	23 (38.33)	34 (56.67)	−8.92^*	.00
1–3 year	27 (45.00)	20 (33.33)	6.17^*	.00
More than 3 years	10 (16.67)	6 (10.00)	3.84^*	.00
Current residence status
Live alone	8 (13.33)	3 (5.00)	3.76^*	.00
Live with spouse	24 (40.00)	16 (26.67)	7.17^*	.00
Living with spouse and children	17 (28.33)	22 (36.67)	−3.85^*	.00
Living with children	11 (18.33)	19 (31.67)	−6.32^*	.00

Note. Mean ± Std. Deviation was presented as M ± SD.

p < .05.

First, JASP Team was used to detect the average age of males and females. The results showed that Cohen’s d = .326 for males and Cohen’s d = .371 for females, both showed small effects (Cohen’s d values between .2–5 are small effects, and .5–8 are medium effect, values higher than .8 have a large effect). The results of power analysis showed that male effect size (es) = 0.2 and female effect size (es) = 0.1, showed no difference between the experimental group and the control group. The average ages of males and females were tested by t-test (t = 0.86, p < .05), and the results showed no significant difference, showed that the participants were homogeneous, and the average ages of males and females were judged to be normal through the Quantile-Quantile diagram (Q-Q plot), as shown in Figure 2.

Figure 2.

Normal distribution of female and male ages Q-Q plot.

Statistics on the previous exercise experience of the participants showed that previous exercise experience referred to the number of years of professional exercise guidance. There was a significant difference in the exercise experience of males and females, with males having the most 1 to 3 years, followed by no professional guidance. Most females had never received professional guidance, followed by 1 to 3 years. In the past 10 years, Taipei City has established a public exercise center to provide free time for older adults (≥65 year old), and built outdoor exercise parks around it to increase the leisure and exercise venues for older adults. Current living status: The living status of males and females was very different, with males mostly “living with their spouses,” followed by “living with their spouses and children.” Females most “live with spouse and children,” followed by “live with children.” The above showed that most of the older adults in the residential communities in Taipei live with their spouses or children.

SFT Analysis of Experimental Group and Control Group

The male and female experimental groups experienced an aerobic fitness exercise program for 8 weeks. According to the Senior Fitness Test (SFT), each test item obtained is presented as mean (Mean) and standard deviation (Std. Deviation), followed by repeated measures ANOVA, and the overall data are shown in Table 6. It showed that Int-2 of males and females has significant difference compared with Int-1, Con-1, Con-2, and found “30 second sit-to-stand, 30 second dominant arm curl, 2 minute step” of Int-2 operations increased significantly, “Single leg (SL)” operation seconds increased significantly. “8-foot up-and-go” operations were significantly faster.

Table 6.

Analysis of SFT.

		Int-1	Int-2	Con-1	Con-2
Gender	Variables	M ± SD	M ± SD	M ± SD	M ± SD	F-value	p-value
Male	30 second sit-to-stand, times	14.15 ± 2.65	19.56 ± 3.11	14.13 ± 2.15	14.22 ± 2.48	5.613	.007
	30 second dominant arm curl, times	21.59 ± 2.41	28.37 ± 2.83	21.45 ± 2.13	21.27 ± 2.29	8.351	.003
	2 minute step, times	105.43 ± 6.17	118.67 ± 5.24	107.31 ± 7.62	106.45 ± 6.21	10.824	.001
	Single left leg, sec	15.72 ± 5.53	19.49 ± 5.16	15.86 ± 4.74	15.36 ± 4.53	3.673	.009
	Single right leg, second	15.31 ± 5.27	18.18 ± 5.09	16.01 ± 3.55	15.94 ± 4.17	3.815	.009
	eight-foot up-and-go, second	6.11 ± 1.56	5.06 ± 0.87	6.08 ± 0.92	6.11 ± 1.23	6.717	.005
Female	30 second sit-to-stand, times	13.13 ± 2.77	18.19 ± 2.56	13.11 ± 2.71	13.15 ± 3.02	5.213	.006
	30 second dominant arm curl, times	19.09 ± 2.34	26.35 ± 2.44	18.92 ± 2.68	19.75 ± 3.16	7.754	.004
	2 minute step, times	101.33 ± 5.89	117.13 ± 5.72	102.35 ± 5.94	101.62 ± 5.48	11.361	.001
	Single left leg, sec	15.21 ± 5.72	18.64 ± 5.65	15.22 ± 5.66	15.18 ± 5.91	3.527	.011
	Single right leg, second	14.17 ± 5.61	17.69 ± 5.83	14.85 ± 6.03	15.01 ± 5.77	3.753	.009
	Eight-foot up-and-go, second	6.26 ± 1.17	5.17 ± 0.85	6.25 ± 1.44	6.48 ± 1.85	5.934	.006

Note. SFT was the abbreviation of the senior fitness test. “Int” represents the intervention in the experimental group, and “Con” represents the control group. Int-1 and Int-2 represent the start and end of the experimental group, and Con-1 and Con-2 represent the start and end of the control group. “Int-1, int-2, con-1, con-2” values were presented as means ± Std. deviation (M ± SD). Repeated measures ANOVA values were presented as F-values.

p < .05.

Analysis of EAEBI Between the Experimental Group and the Control Group

EAEBI’s “int-1, int-2, con-1, con-2” repeated measures ANOVA, the overall data were shown in Table 7. It was found that after 8 week of aerobic fitness exercise program intervention in the male and female experimental groups, the “int-2” of males and females was better than “int-1, con-1, con-2,” and repeated measures ANOVA of “int-2” and “int-1, con-1, con-2” of exercise cognition, exercise self-discipline, awareness effect, and exercise behavior, all reached significant differences (p < .05). In particular, the male experimental group had the greatest difference in awareness effect (F = 9.47, p < .05), and the female experimental group had the most significant difference in exercise cognition (F = 11.35, p < .05).

Table 7.

Repeated Measures ANOVA of int-1, int-2, con-1, con-2 of EAEBI.

Gender	Factors	Int-1	Int-2	Con-1	Con-2	F-value	p-value
		(n = 30)	(n = 30)	(n = 30)	(n = 30)
		M ± SD	M ± SD	M ± SD	M ± SD
Male	Factor 1: Exercise cognition	3.55 ± 0.21	4.13 ± 0.12	3.56 ± 0.19	3.58 ± 0.23	8.18^*	.002
	Factor 2: Exercise self-discipline	3.44 ± 0.25	4.09 ± 0.13	3.45 ± 0.24	3.47 ± 0.21	9.35^*	.001
	Factor 3: Awareness effect	3.53 ± 0.24	4.15 ± 0.11	3.52 ± 0.23	3.54 ± 0.21	9.47^*	.001
	Factor 4: Exercise behavior	3.73 ± 0.20	4.12 ± 0.13	3.74 ± 0.19	3.76 ± 0.20	5.72^*	.005
Female	Factor 1: Exercise cognition	3.41 ± 0.24	4.12 ± 0.10	3.40 ± 0.24	3.43 ± 0.22	11.35^*	.0004
	Factor 2: Exercise self-discipline	3.34 ± 0.25	4.01 ± 0.16	3.35 ± 0.25	3.34 ± 0.27	9.84^*	.001
	Factor 3: Awareness effect	3.47 ± 0.21	4.05 ± 0.13	3.46 ± 0.21	3.45 ± 0.23	8.27^*	.002
	Factor 4: Exercise behavior	3.60 ± 0.19	4.10 ± 0.12	3.62 ± 0.18	3.59 ± 0.20	7.31^*	.003

Note. EAEBI was the abbreviation of Exercise Awareness and Exercise Behavior Inventory. “Int” represents the intervention in the experimental group, and “Con” represents the control group. Int-1 and Int-2 represent the start and end of the experimental group, Con-1 and Con-2 represent the start and end of the control group. “Int-1, int-2, con-1, con-2” values were presented as means ± Std. Deviation (M ± SD). Repeated Measures ANOVA values were presented as F-value. ^*p < .05.

Analysis of HPI Between the Experimental Group and the Control Group

HPI’s “int-1, int-2, con-1, con-2” repeated measures ANOVA, and the overall data were shown in Table 8. It was found that after 8 week of aerobic fitness exercise program intervention in the male and female experimental groups, “int-2” was better than “int-1, con-1, con-2” for both males and females. Moreover, the male experimental group had the most significant difference in physical activity (F = 14.83, p < .05), and the female experimental group had the most significant difference in social support (F = 13.19, p < .05). The above results confirmed the acceptance of hypothesis 1: The benefits of an aerobic fitness program intervention on changing exercise awareness and exercise behavior for older adults.

Table 8.

Repeated Measures ANOVA of int-1, int-2, con-1, con-2 of HPI.

Gender	Factors	Int-1	Int-2	Con-1	Con-2	F-value	p-value
		(n = 30)	(n = 30)	(n = 30)	(n = 30)
		M ± SD	M ± SD	M ± SD	M ± SD
Male	Factor 1: Health responsibility	3.59 ± 0.23	4.03 ± 0.18	3.62 ± 0.21	3.60 ± 0.22	5.76^*	.0006
	Factor 2: Physical activity	3.51 ± 0.25	4.25 ± 0.09	3.52 ± 0.24	3.50 ± 0.25	14.83^*	.0001
	Factor 3: Nutrition	3.63 ± 0.21	4.03 ± 0.17	3.66 ± 0.20	3.67 ± 0.20	4.42^*	.0007
	Factor 4: Spiritual growth	3.55 ± 0.23	4.10 ± 0.15	3.54 ± 0.23	3.57 ± 0.22	8.46^*	.0003
	Factor 5: Social support	3.50 ± 0.25	4.21 ± 0.10	3.53 ± 0.23	3.51 ± 0.25	12.95^*	.0001
	Factor 6: Stress management	3.52 ± 0.26	4.16 ± 0.13	3.55 ± 0.23	3.53 ± 0.24	9.21^*	.0002
Female	Factor 1: Health responsibility	3.81 ± 0.17	4.15 ± 0.14	3.83 ± 0.18	3.81 ± 0.20	4.27^*	.0007
	Factor 2: Physical activity	3.55 ± 0.25	4.06 ± 0.17	3.53 ± 0.23	3.55 ± 0.23	6.61^*	.0005
	Factor 3: Nutrition	3.79 ± 0.20	4.03 ± 0.18	3.80 ± 0.20	3.83 ± 0.18	3.85^*	.0008
	Factor 4: Spiritual growth	3.57 ± 0.23	4.11 ± 0.15	3.58 ± 0.24	3.60 ± 0.23	8.63^*	.0003
	Factor 5: Social support	3.50 ± 0.26	4.23 ± 0.10	3.51 ± 0.25	3.52 ± 0.26	13.19^*	.0001
	Factor 6: Stress management	3.52 ± 0.25	4.19 ± 0.11	3.50 ± 0.26	3.53 ± 0.25	9.68^*	.0002

Note. HPI was the abbreviation of Health-Promoting Inventory. “Int” represents the intervention in the experimental group, and “Con” represents the control group. Int-1 and Int-2 represent the start and end of the experimental group, Con-1 and Con-2 represent the start and end of the control group. “Int-1, int-2, con-1, con-2” values were presented as means ± Std. Deviation (M ± SD). Repeated Measures ANOVA values were presented as F-value.

p < .05.

Pearson Product-Moment Correlation Analysis Between EAEBI and HPI at the End of the Experimental Intervention

The intervention end of experimental group (Int-2) correlation analysis between the four factors of EAEBI and the six factors of HPI between males and females; since each factor was on an equidistant scale, this study used Pearson product-moment correlation analysis.

The correlation coefficient between EAEBI and HPI in the male experimental group was between .67 and .91, reached a significant moderate or high correlation, as shown in Table 9. It shows that after 8 week of aerobic fitness exercise program intervention in males, EAEBI was positively correlate with HPI. Among them, the highest correlation coefficient between the “awareness effect” of EAEBI and “physical activity” of HPI was .91 (p < .05). The second was the correlation coefficient between the “exercise behavior” of EAEBI and the “social support” of HPI was .90 (p < .05).

Table 9.

Correlation Analysis Between EAEBI and HPI at the End of Experimental Intervention (Int-2) in Males.

	EAEBI
		Factor 1	Factor 2	Factor 3	Factor 4
		Exercise cognition	Exercise self-discipline	Awareness effect	Exercise behavior
HPI	Factor 1: Health responsibility	.71^*	.73^*	.72^*	.75^*
	Factor 2: Physical activity	.86^*	.83^*	.91^*	.87^*
	Factor 3: Nutrition	.73^*	.67^*	.72^*	.76^*
	Factor 4: Spiritual growth	.76^*	.71^*	.75^*	.86^*
	Factor 5: Social support	.87^*	.82^*	.88^*	.90^*
	Factor 6: Stress management	.84^*	.82^*	.85^*	.88^*

Note. EAEBI was the abbreviation of Exercise Awareness and Exercise Behavior Inventory. HPI was the abbreviation of Health-Promoting Inventory. “Int-2” was the code name for the end of the experimental intervention.

p < .05.

The correlation coefficient between EAEBI and HPI of the female experimental group was between .65 and .92, reached a significant moderate or high correlation, as shown in Table 10. It showed that after 8 week of aerobic fitness exercise program intervention in females, EAEBI was positively correlated with HPI. Among them, the highest correlation coefficient between the “exercise cognition” of EAEBI and “social support” of HPI was .92 (p < .05). The second was the correlation coefficient between EAEBI’s “exercise behavior” and HPI’s “stress management” was .91 (p < .05).

Table 10.

Correlation Analysis Between EAEBI and HPI at the End of Experimental Intervention (Int-2) in Females.

	EAEBI
		Factor 1	Factor 2	Factor 3	Factor 4
		Exercise cognition	Exercise self-discipline	Awareness effect	Exercise behavior
HPI	Factor 1: Health responsibility	.83^*	.67^*	.86^*	.78^*
	Factor 2: Physical activity	.87^*	.82^*	.86^*	.89^*
	Factor 3: Nutrition	.78^*	.73^*	.76^*	.77^*
	Factor 4: Spiritual growth	.77^*	.65^*	.85^*	.88^*
	Factor 5: Social support	.92^*	.86^*	.87^*	.89^*
	Factor 6: Stress management	.89^*	.83^*	.85^*	.91^*

p < .05.

The Explanatory Power of EAEBI of the Experimental Group to HPI

After Pearson product-moment correlation analysis found that the four factors of EAEBI and the six factors of HPI in the male and female experimental groups were all highly correlated, the four factors of EAEBI were used as the independent variable. The dependent variable (HPI), multiple regression analysis would be used to first test the statistical significance of this regression model. The dependent and independent variables of males and females had significant differences after F-test results, males F = 59.637^* (p < .01), and the Durbin-Waston test value was1.604; females F = 64.215^* (p < .01), and the Durbin-Waston test value was 1.658, and the data of the four factors were independent for males and females. Finally, multiple regression was used to analyze the explanatory power of the forced entry method (the independent variable was considered in the regression model) to the HPI of the dependent variable.

The explanatory power of EAEBI for male to HPI reached a significant level, and the explained variation was R² = 65.45% (p < .01). Among the independent variables, the estimated value of awareness effect had the greatest impact on health promotion (β = .613, p < .01), followed by exercise behavior (β = .575, p < .01) and exercise self-discipline (β = .419, p < .01) and exercise cognition (β = .408, p < .01). The four independent variables β were all positive, showed that the independent variables positively impacted the health promotion of male older adult, as shown in Table 11.

Table 11.

Multiple Linear Regression Analysis of Males.

Variables	β	R	R ²	Adjusted R²	p
Exercise cognition	.408^*	.809	0.6545	0.6508	<.005
Exercise self-discipline	.419^*				<.004
Awareness effect	.613^*				<.000
Exercise behavior	.575^*				<.001

Note. Independent variables: Exercise cognition, exercise self-discipline, awareness effect, exercise behavior. Dependent variable: HPI.

p < .01.

The explanatory power of female EAEBI to HPI reached a significant level, and the explained variation was R² = 68.39% (p < .01). Among the independent variables, the estimated value of exercise cognition has the most significant impact on health promotion (β = .648, p < .01), followed by exercise behavior (β = .571, p < .01) and awareness effect (β = .503, p < .01) and exercise self-discipline (β = .475, p < .01). The four independent variables β were all positive, showed that the independent variables positively impacted the health promotion of female older adults, as shown in Table 12. To test and accept hypothesis 2: Exercise awareness and exercise behavior after aerobic fitness program intervention could effectively predict the health promotion for older adults.

Table 12.

Multiple Linear Regression Analysis of Females.

Variables	β	R	R ²	Adjusted R²	p
Exercise cognition	.648^*	0.827	0.6839	0.6814	<.000
Exercise self-discipline	.475^*				<.003
Awareness effect	.503^*				<.002
Exercise behavior	.571^*				<.001

Note. Independent variables: Exercise cognition, exercise self-discipline, awareness effect, exercise behavior. Dependent variable: HPI.

p < .01.

Discussion

Internal and External Validity and Confounding Factors of This Study

In this study, the age distribution of male and female participants was normal and convenience sampling was adopted. All the tests at the end of the experimental group (Int-2) were better than those at the beginning of the experimental group (Int-1), the beginning of the control group (Con-1), and the end of the control group (Con-2), and the research team will guide the participants and be monitored and recorded by a special person during the experiment, which had internal validity. In addition, the results of this experiment could be extrapolated to urban older adults, showed that the research results were generalizable, could be inferred to the representative population (seniors in metropolitan communities), and have external validity, which was consistent with many studies (Andrade, 2018; D. P. Chen et al., 2023; Patino & Ferreira, 2018). Potential confounding factors for the results of this study include diet and partner effects. The experimental group and the control group had different eating habits, and some older adults ate healthy food, which is one of the confounding factors in this study. Another major confounding factor was that the control group used daily life during the experiment. Suppose the participants in the experimental group and the control group were partners. In that case, the participants in the control group may also occasionally go to the community for fitness, which was the effect of the partner effect to achieve social support, and at the same time, produces confounding factors for the research process. This study adopted randomized grouping to assign the research subjects to the experimental group and the control group, and when the random grouping was performed, which group the research subjects were assigned to be determined entirely by a random mechanism, independent of the will and preferences of the researcher or anyone else. Moreover, studies have confirmed that random grouping could ensure that the control group was comparable throughout the study process, thereby minimizing confounding effects in randomized controlled trials (T. Liu et al., 2017; Pourhoseingholi et al., 2012). In addition, the study pointed out that randomization, control group, and multiple regression analysis were the most reliable research designs for the causality of the research population and the most helpful way to control confounding factors (Bhide et al., 2018; Sil et al., 2019), which was also confirmed in this study.

The Effect of Exercise Awareness on Exercise Behavior in the Older Adult

The study found that enhancing the exercise awareness of older adults could start with three factors: exercise cognition, exercise self-discipline, and awareness effect. Improving the awareness of physical activity for older adults and the awareness of the importance of physical activity or exercise were consistent with many studies (Dondzila et al., 2014; Tajima et al., 2018; Vaara et al., 2019). The attendance rates of males and females reached 96% and 98%, respectively, indicating that participation was relatively high. Studies have confirmed that people with high participation may be aware of more details of the environment related to themselves, and through awareness, deep-rooted behaviors in daily life could be changed (Langer, 2009); cited in this study, a high level of engagement among older adults favors changes exercise awareness (Lindsay Smith et al., 2017). In addition, older adults should be made aware that they should maintain physical activity in daily life, make exercise a routine of life, and develop self-disciplined exercise habits (Lachman et al., 2018; J. Zhang et al., 2022). Experts believe that the mindfulness of exercise awareness in older adults could drive internal motivation, achieve self-regulation and produce exercise behavior, which was the effect of exercise awareness (Krieghoff et al., 2011; Rothman et al., 2004). This study on the intervention results of aerobic exercise found that positive exercise awareness could reduce perceived fatigue during exercise. Therefore, studies have confirmed that positive exercise awareness would help individuals’ exercise behavior (Giles et al., 2018; Sin & Lyubomirsky, 2009). In this study, the intervention of aerobic exercise from Monday to Friday gradually made the older adults aware of the necessary process of exercise in daily life. Each exercise should reach a moderate intensity, and each exercise should be more than 30 minutes. The result was similar to many studies (Magutah et al., 2018; WHO, 2022; Zaleski et al., 2016). The study showed that exercise behavior had a close positive relationship with health promotion. This result was consistent with the research of scholars. It was believed that exercise could help emotional stability and stress adjustment (Tao et al., 2023), and reduce memory loss caused by aging problems (Babaei & Azari, 2021). Psychological problems would be accompanied by improvements in physical fitness, which would bring the greatest happiness and spiritual growth (An et al., 2020). Therefore, this study found that the intervention of the aerobic exercise program changed the exercise behavior of the older adult in the experimental group, and many older adults could also reflect, that the exercise behavior changed the older adult’s positive awareness of exercise.

The Benefits of Exercise Participation for the Older Adult on Exercise Adherence

The independent variables in this study have passed the Durbin-Waston test (distributed between 0–4), and both males and females were close to 2, which showed that the four factors of males and females’ exercise cognition, exercise self-discipline, awareness effect, and exercise behavior were independent of each other. The results were consistent with scholars’ research (Durbin & Watson, 1951). The experimental group of this study was intervened through the “8-week aerobic fitness program.” This intervention included group exercise, diverse exercise content, and dedicated teaching and monitoring. During the intervention, the older adult established exercise partners and increased social opportunities to build exercise adherence (Hawley-Hague et al., 2014; Killingback et al., 2017; Sullivan-Marx et al., 2011). From the perspective of exercise adherence for older adults, after implementing an aerobic fitness program, it was found that a various exercises aroused the intrinsic motivation of older adults for exercise (Picorelli et al., 2014). The research team implemented exercise teaching and supervision, controlled the exercise intensity of older adults when implementing the plan, established partnerships in exercise, and increased social support through group exercise. This result was consistent with many studies (Hawley-Hague et al., 2016; Rivera-Torres et al., 2019; Room et al., 2017; J. F. Shaw et al., 2022; Valenzuela et al., 2018). Scholars have pointed out that the key to continuous exercise is to make exercise fun and enjoyable (Lakicevic et al., 2020). Some studies pointed out that older adults participate in community fitness courses or parks, and it was an excellent way to meet other sports-loving people (Abdelkarim et al., 2017; Policastro et al., 2018).

The Main Reason Why Social Support Affects the Exercise Behavior of the Older Adult

The experimental group in this study received the intervention results of the aerobic exercise program, which positively affected health behavior. This study found that after the intervention of aerobic exercise program, male older adults were most effective in health-promoting physical activity and social support after an aerobic exercise program intervention and that physical activity was the most agreeable to social support, suggesting that male older adults could take advantage of outdoor physical activity or exercise to meet friends, even had chat partners, to obtain a quality and healthy life, which was consistent with many studies (Böhm et al., 2016; Churchill et al., 2021; Dobarrio-Sanz et al., 2021; Langhammer et al., 2018; Lindsay Smith et al., 2017; Schembre et al., 2015; Sharon-David & Tenenbaum, 2017). Social support for health promotion and stress management was most effective after aerobic exercise program intervention for female older adults because the higher the social support (family, spouse, children, or friends), the more people to talk to in life, and the less loneliness (Czaja et al., 2021), it was easy to move toward positive psychological emotions (J. Chen et al., 2022), and life increased pleasure and reduced stress virtually (Pilcher & Bryant, 2016), which means older adults have more emotional support from family, spouse, children or friends and are more likely to manage stress well. In addition, both male and female older adults think that nutrition was not the main factor for health promotion in the HPI post-test. The participants in this study might have been all healthy older adults, and these participants lived in urban areas, and there was no shortage of material life and diet (Deluga et al., 2018). Thus, nutritional factors were not the focus of the participants. Older adults favored the walking exercise of the aerobic fitness program. Studies have pointed out that regular walking could increase social opportunities and health promotion for older adults (Gardiner et al., 2018; Turcotte et al., 2018). Because walking and chatting with friends or family members would invisibly walk farther, and even walking at a fixed time will often meet friends, which has significant benefits for health promotion for older adults (Han et al., 2021). On the contrary, the main barriers to social support of older adults might be chronic loneliness, and lack of interaction with spouses, friends, peers, and family members, resulting in insufficient social and communication skills (Donovan & Blazer, 2020). According to the research, social support was an important variable affecting older adults’ health promotion. This view was consistent with the literature and confirmed that aerobic exercise programs benefited older adults’ health promotion (Izquierdo et al., 2021; Rivera-Torres et al., 2019; Weber et al., 2018).

Exercise Awareness and Exercise Behavior Could Predict the Effect of Health-Promotion

The experimental group adopted multiple regression analysis, it found that aerobic fitness exercise intervention, exercise awareness, and exercise behavior of older adults significantly and positively affect health promotion, especially the exercise cognition of female older adults was highly correlated with social support for health promotion. In this study, HPI’s social support most correlated with exercise behavior, which was consistent with many empirical pieces of evidence (Huang et al., 2022; Lindsay Smith et al., 2017; Resnick et al., 2002; Zimmer et al., 2023). Because the objects of attachment in old age gradually shift from friends to family members and spouses, the social support for older adults is mainly based on family members or spouses, this result was similar to previous literature (Cui et al., 2022; L. Wang et al., 2020; P. Wang et al., 2023). This study found that exercise intervention could help improve exercise cognition. The reason was that many studies have confirmed that exercise could make more blood flow to the brain and help improve people’s cognitive abilities (Audiffren & André, 2019; Gomez-Pinilla & Hillman, 2013; Mandolesi et al., 2018; Querido & Sheel, 2007). This study adopted moderate-intensity aerobic exercise intervention to improve older adults’ exercise awareness and willingness to exercise behavior, through multiple regression analysis could effectively predict the health promotion of the older adult. These data give practical significance to an aging society. Promoting health through regular exercise can also reduce medical resources, this is the subject of effective preventive medicine.

Research Limitations

This study had several limitations. The outliers in this study occurred in the sampling. The samples belonged to the older adults in the Taipei community. These ethnic groups belong to the metropolitan. From the “current living conditions,” they were different from the rural older adults. This result was difficult to infer from the rural older adults (Baernholdt et al., 2012). Therefore, the extrapolating the obtained data to non-metropolitan communities may cause abnormalities or deviations in the data, which was an important limitation of this study. The study limited broad inferences only to healthy older adults, and future research will design different types of physical activity programs for a more comprehensive age range of chronically ill or mildly disabled individuals. In addition, nutrition education for older adults was only promoted in the classroom, and nutrition leaflets were distributed or broadcast on TV and the Internet. This might cause errors and was one of the limitations of this study. Finally, this study mainly focused on the benefits and explanatory power of exercise awareness and exercise behavior for health promotion in older adults. It was only a cross-sectional study and could not provide clear evidence for the causality of the research variables.

Conclusion

Taiwan will enter a super-aged society by 2025, representing the advancement of life, well-being, and medical technology. How older adults can live healthy and happy is an essential lesson in social public health. The data of this study showed that exercise awareness and behavior positively affected health promotion for older adults, and the intervention of group type and diversity of aerobic exercise was adopted. The research team participates in teaching and controls each attendance rate and exercise intensity. The classroom promoted a shared sense of exercise and a healthy diet. Participants’ 8-week aerobic exercise intervention established peer-interactive interpersonal relationships and also achieved health promotion indicators. In the future, appropriate and moderate exercise interventions are needed for older adults of different ethnic groups (chronic diseases, mildly disabled), which may help more older adults of different ethnic groups to promote health.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest concerning the research,authorship,and/or publication of this article.

Funding

The author(s) received no financial support for the research,authorship,and/or publication of this article.

ORCID iDs

Wei-Yang Huang

Cheng-En Wu

Data Availability Statement

The experimental results used real data obtained from the study participants. The measurement data were obtained after the training program. The participants agreed with the data structure via a confirmation,and this confirmation can be disclosed with reasonable availability. All of the datasets on which the conclusions of the paper rely are available to editors,reviewers,and readers.

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