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Abstract

The purpose of this study employed the theory of planned behavior as a research framework to analyze the explanatory power of exercise attitude, subjective norms, and perceived behavioral control on exercise intention among older adults and to obtain insight on exercise behavior among older adults. The study used Ajzen's theory of planning behavior as a basis to compile the “Exercise Behavior Intention Questionnaire of the Older Adults.” Results showed that there were significant differences were detected in the exercise intentions of older adults with different subjective norms and perceived behavioral control. This indicated that older adults of greater age have a greater need for companionship from family members and stronger subjective norms. In addition, exercise attitude, subjective norms, and perceived behavioral control explained the variance in exercise intention among older adults, verifying the positive explanatory power of these variables on exercise intention in older adults. The study concluded that the theory of planned behavior, improving older adults’ exercise attitude alone was insufficient for increasing their exercise behavior intention. In particular, older adults of greater age had greater needs for social support from the main groups, and they required encouragement to enhance their self-efficacy and confidence.

Keywords

Senior learning center theory of planned behavior exercise attitude subjective norms perceived behavioral control

Introduction

Life extension is accompanied by aging and physical activity decline, and physical activity is a critical indicator of aging.¹ The subject of this study was older adults’ exercise behavioral intentions (BI). First, the concepts of physical activity and exercise should be clarified. Physical activity is defined as any bodily movement resulting in energy expenditure generated by the contraction of human skeletal muscles. For example, daily activities such as planting flowers, sweeping, and walking are all included in the range of physical activities.² Exercise is also defined as physical activities that are planned, structured, repetitive, and aimed at improving or maintaining physical fitness. This is what this study refers to as older adult exercise.

According to the exercise survey results of the Sports Administration of Taiwan's Ministry of Education, in 2019, have 41.4% of older adults in Taipei still do not exercise regularly, and 14.2% do not exercise at all. Consequently, it is necessary to continue the study of older adult exercise behaviors in Taipei. Next, related foreign researches on the exercise participation of older adults were discussed. Tomioka et al. studied found that the incidence of men with poor physical activity was 17.1% and that of women was 4.5%.³ This indicates that sex differences exist for physical activity.⁴ In addition, exercise levels gradually decrease with age.⁵ Van Uffelen et al. discovered that women are more motivated to participate in exercise than men.⁶ Because women are more likely to establish regular times for exercise compared with men.^7,8 In particular, family members are the major supporters for improving older adults’ physical activities.^9–13

For understanding BI, the theory of planned behavior (TPB) is recommended first Proposed by Ajzen in 1985,¹⁴ the TPB asserts that attitude (EA), subjective norms (SN), and perceived behavioral control (PBC) together shape an individual's BI and behaviors. The core concept of the TPB is that an individual's behaviors are influenced by BI, and intentions are considered the motivating factors that influence behaviors.¹⁵ In addition, Ajzen proposed that the performance of most behaviors depends to some extent on usable external motivating factors, such as time, money, skill, and assistance from others.^16,17 Various studies are based on the TPB. The three factors of attitude, SN, and PBC are considered to be predictive of BI in all these studies.^18–21 First, when the connection between exercise participation and personal attitude is stronger, the person's exercise behaviors are more obvious.²² Second, the SN that influences exercise behavior intentions refers to the pressure of perceiving the influence of significant others or groups on individuals’ execution of specific behaviors. They are also divided into main group norms and subgroup norms.¹⁸ Third, the TPB is influenced by PBC, and self-efficacy is a premise of behavioral change.²³ Because people's behaviors are strongly influenced by their beliefs, self-efficacy demonstrates individuals’ beliefs and predicts the strength of their BI.²⁴ Inferring from the abovementioned research, it was feasible for this study to adopt the TPB to predict older adults’ exercise BI.

Based on the aforementioned study purposes, the following two research questions were proposed to guide this study's discussion: What are the correlations between the factors and variables of older adults’ BI? What is the explanatory power of the TPB for older adults’ exercise BI? In addition, the following two hypotheses were proposed according to the study questions:

H1: There are significant correlations between the factors and variables of older adults’ BI.

H2: TPB has explanatory power for older adults’ exercise BI.

Materials and methods

Research structure

The TPB can be used as a behavioral prediction model. Specifically, it can be used to measure the BI of the exercise field, and BI are the levels of explanation for behaviors. According to the related literature mentioned in the introduction, the intensions of the factors of the TPB model in this study (EA, SN, PBC, and BI) were the same. The latent variables included the cognition, emotions, and behaviors of older adult exercise; norms of the main group and subgroup; self-efficacy; and behavioral control of facility convenience. In this study, the abovementioned latent variables were all called variables. In addition, the researcher for targeting older adults in senior learning centers in Taipei. The centers are free and thus cost does not influence individuals’ economic conditions, and all of the older adults live in the city. Therefore, the adults’ economic conditions and living environment were not listed as background variables for the discussion. The variables of loneliness, disease, and individual former sports injuries were listed as control variables.²⁵ The final confirmed study structure is presented in Figure 1. The differences in EA, SN, PBC, and BI for older adults with different backgrounds were discussed. This study used three factors to explain older adults’ exercise BI and discussed how to promote older adults’ exercise behaviors.

Figure 1.

Research architecture diagram.

Participants

The study population was older adults in Taipei City. Twelve administrative districts’ senior learning centers in Taipei were sampled, and 35 older adults were randomly sampled in each center. A total of 420 questionnaires were distributed, and 408 were retrieved; 8 questionnaires with incomplete answers were excluded for a total of 400 valid questionnaires. They were used to discuss the explanatory power of older adults’ EA, SN, and PBC for exercise BI.

Measures

The measurement tool was designed based on Ajzen's TPB, and related literature was referenced.^18,24 The first draft of the “Older Adult Exercise Behavioral Intention Questionnaire” was made to conform to older adults’ EA, SN, PBC, and BI. The questionnaire had five parts. The first part on EA included the three variables of cognition, emotion, and behavior, with a total of 14 items in the first draft. The second part on SN included two variables of main group opinion and subgroup opinion, with a total of six items in the first draft. The third part on PBC included the two variables of self-efficacy and convenient condition, with a total of six items in the first draft. The fourth part on BI was modified according to the study subjects, with a total of five items in the first draft. Finally, the fifth part collected background information, which was diverse among these older adults. The background variables that were easy to answer while protecting personal health privacy were captured for the questionnaire according to relevant literature.^4,11,13,26 A Likert five-point scale was adopted for the measurements.

Procedures

Once the first draft of the questionnaire had been produced, questions were evaluated and selected for their adequacy by professors in the field of exercise. Then, 200 male and female older adults who exercised in parks in Taipei were randomly selected for a pretest. The pretest questionnaires were retrieved, and after 7 questionnaires with incomplete answers were excluded, there were 193 valid questionnaires. After the pretest questionnaires were complete, the correlations and critical ratios of the items with the total scores were adopted for item analysis. Critical ratios are the differences in the mean scores of an item of the high-score group and the low-score group. The higher the ratio, the greater the discrimination of the item. The items could only be used if their correlation coefficient was over 0.30 and the critical ratio was over 3.5 with the total score. The total cumulated explained variance of the questionnaire reached 78.21%; therefore, it possessed construct validity. Reliability analysis was performed to understand the consistency and stability of the questionnaire. Cronbach's α was adopted for the internal consistency analysis of the questions with the same factors. They were measured if they conformed to the general reliability examination demands. The Cronbach's α should be at least 0.7. The reliability analysis results revealed that the internal consistency of the questionnaire was high, and therefore, no item was deleted. For the overall analysis of EA, the Cronbach's α was 0.826. For the overall analysis of SN, the Cronbach's α was 0.792. For the overall analysis of PBC, the Cronbach's α was 0.806. For the overall analysis of older adults’ exercise BI, the Cronbach's α was 0.841. The Cronbach's α of the entire scale was 0.812.

Data analyses

In this study, the Chinese version of SPSS 23.0 was used for the statistical analysis, and the significance level was set as α = 0.05. The adopted statistical methods included frequency distribution, t-test, one-way analysis of variance (ANOVA), Pearson's product–moment correlation, and multiple linear regression analysis.

Results

Analysis of respondents’ basic information

In this study, the respondents were older adults in 12 administrative districts’ senior learning centers in Taipei City. Regarding the formal questionnaires, 420 were distributed and 413 were retrieved; 13 invalid questionnaires were eliminated, meaning that 400 valid questionnaires were collected. The valid questionnaire ratio was 95.24%, and the retrieval rate was high. For the study results, the background variables are presented with a frequency distribution table and percentages as follows: Regarding sex, there were 197 men, accounting for 49.3% of the sample, and 203 women, accounting for 50.8% of the sample. Regarding age, 110 people (27.5%) were aged 65–69 years; 104 people (26.0%) were aged 70–74 years; 101 people (25.3%) were aged 75–79 years; 61 people (15.3%) were aged 80–84 years; and 24 people (6.0%) were aged over 85 years. Thus, older adults who participated in exercise were mainly distributed in the 65–79 age range. Regarding companionship, 26 people (6.5%) exercised alone; 194 people (48.5%) exercised with family; 94 people (23.5%) exercised with spouses; and 86 people (21.5%) exercised with friends. Thus, the companions of older adults participating in exercise were mainly family, spouses, and friends, accounting for 93.5% of the sample. In addition, Table 1 presents the means and standard variations of different factors and variables according to respondents’ questionnaire answers.

Table 1.

Older adults’ exercise behavioral intention questionnaire analysis.

Factor Variable		Issue	M(SD)	M(SD)	M(SD)
EA	Cognition	Exercise is good for health.Exercise can improve stamina.Exercise can maintain muscle endurance.Exercise can relax one's mood.Exercise can help me make friends.Exercise can help perspiration.	4.16 (1.05)3.54 (1.36)3.58 (1.37)3.56 (1.33)3.58 (1.30)3.62 (1.31)	3.69(1.31)
	Cognition			3.69(1.31)	3.57(1.37)
	Emotion	Exercise makes me happy.Exercise makes my life regular.Exercise makes me feel satisfied.Exercise makes me energetic.Exercise gives me purpose in life.	3.74 (1.28)3.84 (1.19)3.72 (1.33)4.02 (1.14)3.11 (1.58)	3.67(1.35)
	Behavior	I spend money on exercise.I arrange time for exercise.Include exercise in my daily.	3.18 (1.38)3.19 (1.49)3.15 (1.45)	3.17(1.44)
SN	Main group	Influenced by family.Influenced by friends.Influenced by doctors.	2.88 (1.44)2.82 (1.45)2.76 (1.47)	2.73(1.45)	2.72(1.47)
SN	Subgroup	Influenced by advertisements.Influenced by social clubs.Influenced by newspapers.	2.60 (1.49)2.70 (1.54)2.56 (1.43)	2.71(1.50)	2.72(1.47)
PBC	Self-efficacy	Confidence to participate in exercise.Ability to participate in exercise.	3.54 (1.38)3.15 (1.44)	3.35(1.42)	3.26(1.45)
	Self-efficacy	I arrange a fixed time for exercise.I can afford the fees for exercise.Space and equipment are sufficient.I can participate freely at any time.	3.28 (1.43)3.21 (1.49)3.16 (1.49)3.22 (1.45)	3.22(1.46)
	Convenience		3.28 (1.43)3.21 (1.49)3.16 (1.49)3.22 (1.45)	3.22(1.46)
BI		Willing to promote its advantages.Willing to recommend to my friends.Everybody encourages each other.Can continue to participate.Can spend more time on participating.	2.87 (1.53)3.19 (1.45)3.62 (1.25)3.16 (1.49)3.05 (1.51)	–	3.18(1.47)

Pearson product–moment correlation analysis of the different factors and variables of exercise BI.

EA: Exercise attitude; SN: Subjective norm; PBC: Perceived behavior control; BI: Behavior intention.

Table 2 presents the Pearson product–moment correlation analysis of different factors and variables of older adults’ exercise BI. The correlation coefficient of EA and SN was r = 0.61 and that of EA and PBC was r = 0.62. The correlation coefficient was r = 0.69 for EA and exercise BI, and that of SN and PBC was r = 0.72. The correlation coefficient of SN and exercise BI was r = 0.63, and that of PBC and exercise BI was r = 0.73. They all reached significant correlations (p < 0.05).

Table 2.

Pearson product–moment correlation analysis of different factors and variables of older adults’ exercise behavior intentions.

	A	a1	a2	a3	B	b1	b2	C	c1	c2	D
A	1
a1	0.72*	1
a2	0.60*	0.68*	1
a3	0.58*	0.58*	0.64*	1
B	0.61*	0.66*	0.49*	0.60*	1
b1	0.49*	0.49*	0.42*	0.60*	0.53*	1
b2	0.42*	0.41*	0.54*	0.41*	0.63*	0.73*	1
C	0.62*	0.62*	0.52*	0.45*	0.73*	0.58*	0.69*	1
c1	0.52*	0.52*	0.49*	0.42*	0.47*	0.82*	0.66*	0.79*	1
c2	0.41*	0.60*	0.59*	0.52*	0.61*	0.63*	0.77*	0.76*	0.47*	1
D	0.69*	0.56*	0.48*	0.55*	0.63*	0.72*	0.58*	0.73*	0.70*	0.69*	1

p < 0.05.

Note: A: Exercise attitude (a1: cognition, a2: emotion, a3: behavior); B: Subjective norm (b1: main group, b2: subgroup); C: Perceived behavior control (c1: self-efficacy, c2: convenience); D: Behavior intention.

Explanatory power of exercise attitude, subjective norms, and perceived behavioral control for exercise BI.

All the correlation coefficients of all factors and variables of EA, SN, PBC, and BI were between 0.41 and 0.82. They all had moderate-to-high positive correlations. Among the variables, the main group and self-efficacy variables were highly correlated (r = 0.82). By contrast, the three pairs of EA and convenient condition (r = 0.41), cognition and subgroup (r = 0.41), and behavior and subgroup (r = 0.41) had the lowest correlations, which were only moderate to low. The data revealed that the overall EA of older adults had a low correlation with space and equipment. In addition, older adults’ cognition and behaviors of exercise were hardly influenced by subgroup norms such as television advertisements, newspapers, and magazines. They only had moderate-to-low correlations.

The abovementioned factors and variables reveal that the older adults’ EA was mostly positive and active. For SN, family was the most important promotor of older adult exercise. PBC was used to construct older adults’ confidence in exercise. Therefore, to increase older adults’ exercise BI, families should help construct the social concept of older adults’ participation in exercise. The abovementioned results of the correlation analysis of different factors and variables verified H1, namely that significant correlations exist between the factors and variables of older adults’ BI.

The Pearson product–moment correlation analysis revealed that different factors and latent variables of older adults’ exercise BI all had greater than moderate correlations. Next, multiple linear regression analysis was adopted to understand the explanatory power of the three independent variables of EA, SN, and PBC on the dependent variable of exercise BI. First, the statistical significance of the regression model was verified. Table 3 indicates that the F test results of the dependent variable and three independent variables had significant differences with F = 895.564* (p < 0.05). Finally, the enter method of multiple linear regression (i.e. three independent variables considered in the regression model) was used to determine the explanatory power of the dependent variable (exercise BI). Table 4 reveals that the explanatory powers of the three independent variables of EA (β = 0.280), SN (β = 0.119), and PBC (β = 0.611) for exercise BI all reached the level of significance (p < 0.05). The explained variance was R² = 57.3%. Among the three independent variables, the estimate of PBC (β = 0.611) had the largest influence on older adults’ exercise BI. This was followed by EA (β = 0.280) and SN (β = 0.119). The β values of all three independent variables were positive, which indicated that said variables all had a positive influence on older adults’ exercise BI. The regression equation of older adults’ exercise BI is as follows: BI = 0.280 EA + 0.119 SN + 0.611 PBC.

Table 3.

F test abstract table of the multiple linear regression model.

Mode	SS	df	MS	F	p
Regression	2468.223	3	822.741	895.564*	0.000
Residual	1833.695	1996	0.919
Sum	4301.918	1999

p < 0.05.

Note: Independent variables: Exercise attitude, subjective norms, perceptual behavior control. Dependent variable: Behavioral intention.

Table 4.

Abstract table of the multiple linear regression analysis.

	β	R	R ²	R² adjust
EA	0.280*	0.757	0.574	0.573
SN	0.119*
PBC	0.611*

p < 0.05.

Note: Independent variables: Exercise attitude (EA), Subjective norms (SN), Perceptual behavior control (PBC). Dependent variable: Behavioral intention (BI).

The three factors of TPB could explain up to 57.3% of the exercise BI overall. The multiple linear regression equation indicates that older adults had positive exercise BI. For EA, they were mostly influenced by the cognition and emotion variables. Older adults had the cognition that exercise is good for health, maintaining muscle strength, making friends, and helping perspiration (M = 3.69). In terms of emotions, they participated in exercise to feel happy, feel energetic, and have purposes in life (M = 3.67). The behavior variable was the worst (M = 3.17). The abovementioned data reveal that older adults’ EA had an explanatory power of 28.0% on exercise BI. For SN, older adults’ exercise participation was influenced by the variables of the main group (M = 2.73), which are family (M = 2.88), friends (M = 2.82), and doctors (M = 2.76). The support and encouragement of family had an explanatory power of 11.9% for older adults’ exercise BI. For PBC, older adults were mainly influenced by the self-efficacy variable (M = 3.35). Their confidence in exercise participation was the highest (M = 3.54). PBC had an explanatory power of 61.1% for exercise BI. To conclude the multiple linear regression equation above, older adults’ EA, SN, and PBC were all major factors determining exercise BI in this study. This study verified H2, namely that the TPB has explanatory power for older adults’ exercise BI.

Discussion

The TPB is extensively used in research to predict exercise and health topics.^{19,20–22,24} The following discussion is divided into three parts according to the study results.

Older adults’ exercise behavior intentions for different background variables

According to the data, compared with older women, older men were more influenced by the main group of family, spouses, and friends. For PBC, the men's self-efficacy was higher than that of women. For exercise BI, men exhibited more confidence. In addition, compared with women, men were more capable of arranging fixed times for exercise. Older adults of different sexes had no difference in EA. The goal of exercise for both sexes was for health, relaxation, good mood, and energy. These results are consistent with those of Mao et al.4 who asserted that older adults living in a city with spouses or partners are more likely to conduct in regular exercise. For both male and female older adults, happiness is the crucial factor in exercise participation.

In addition, the results indicated that age is related to the prediction of exercise BI and exercise behaviors. Older adults of different ages all had positive EA. However, a positive attitude does not always generate behaviors.¹⁰ Li et al.⁵ indicated that people reduce exercise participation because of declining health conditions or physical abilities with advancing age. On the other hand, Langhammer et al.²⁶ indicated that the older people are, the more they understand the importance of exercise. In addition, the study results indicated that older adults of more advanced age need the company of the main group of family, spouses, and friends more for exercise. Compared with other people of higher age, older adults aged 65–69 years are more confident in exercise with higher self-efficacy. In addition, they are willing to spend more time on and continue to participate in exercise. This result is consistent with the study of Notthoff et al.⁸ who asserted that older adults’ psychological motives and self-efficacy have positive correlations with their physical activities.

The social support of different companions is another factor that influences older adults’ exercise BI. Hatefnia et al.²¹ found that encouragement from family influences older women in exercise. For older women, family is more important than friends. Osuka et al.¹³ found that older adults receive the most support from family members for continued exercise. Lindsay Smith et al.¹¹ demonstrated that older adults receive more support from family for exercise, whereas being single (divorced or widowed) creates loneliness and lower exercise levels. They also demonstrated that being alone is negatively correlated with exercise for older adults. Van Uffelen et al.⁶ revealed that older adults’ exercise participation intentions are most influenced by opportunities to get along with others and the motive of making friends. They also verified that older adults who exercise alone have the lowest intentions.

Finally, the background variables selected in this study were based on the study participants, namely older adults in senior learning centers in Taipei City. Because the courses are free, their individual economic conditions are not influenced. In addition, space is sufficient, and older adults who come to learn have the ability to freely move their bodies. Therefore, for the older adult background variables of the questionnaire survey, only the three variables of sex, age, and exercise companions were adopted. The older adults’ latent variables of the psychological state of loneliness, disease, sports injury, and past exercise experience were listed as control variables. In addition, random sampling was adopted to control the factors that would influence this study.

Older adults’ exercise behavior intentions and promotion

In this study, the TPB explained 57.3% of the older adults’ exercise BI. This study's findings are consistent with many other studies.^19,20 Their studies explained 55% and 41% of older adult exercise BI, respectively. Overall, the results of this study are consistent with these theories.^20,22,24,26 This demonstrates that older adults’ EA, SN, and PBC positively influence their exercise BI.

For EA, the 28% explanatory power for BI was compared with the overall explained variance R² = 57.3%. This revealed that EA was not the major factor explaining older adults’ exercise BI. For a deep discussion of the reason, the attitude variables of the cognition (M = 3.67), emotion (M = 3.69), and behavior (M = 3.17) of older adults’ EA of the questionnaire were examined. Older adults’ exercise cognition and behavior attitude were found to have significant differences (t = 16.13*, p < 0.05). They had a moderate correlation (r = 0.58*). The behavior variable of EA and BI had no significant difference (t = −1.18). They had a moderate correlation (r = 0.55*). These results are consistent with the study of Komatsu et al.¹⁰ They believed that attitude is not the only factor influencing older adults’ exercise BI. Although most older adults acknowledge that exercise is beneficial for their body and mind, they still do not take action.

Furthermore, SN had 11.9% explanatory power for BI, which was much lower than the overall explained variance of R² = 57.3%. This indicated that SN had low explanatory power for the older adults’ exercise BI. For a deep discussion of the reason, the questionnaire answers were examined. The main group variable of SN and BI reached a significant difference (t = −12.81*, p < 0.05). The subgroup variable and BI also reached a significant difference (t = −16.38*, p < 0.05). However, the major group variable and BI reached a moderate-to-high correlation (r = 0.72*). The subgroup variable and BI only had a moderate correlation (r = 0.58*). This revealed that for SN, this study mainly focused on the main group variable, which was found to be the main predictor of older adults’ exercise BI. Specifically, family was the main influence on older adult exercise BI. This study result is consistent with various studies,^4,11,13 which have all verified that family is the major support. In addition, related research on the TPB has indicated the importance of norms for intention and behavior change.²²

PBC had 61.1% explanatory power for older adults’ exercise BI. Questionnaire answers were reviewed for a deep discussion of the reason. The self-efficacy variable (M = 3.35) and convenient condition variable (M = 3.22) of older adults’ PBC were found to have significant difference (t = 3.31*, p < 0.05). They had a moderate-to-low correlation (r = 0.41*). The self-efficacy variable and BI reached a significant difference (t = 7.70*, p < 0.05), whereas the convenient condition variable and BI did not reach a significant difference (t = −0.18, p < 0.05). Therefore, the self-efficacy variable of older adults’ PBC was most closely related to BI. If older adults are confident before exercise, they may increase their exercise behaviors. Various studies have indicated that older adults’ PBC is the strong decisive factor for BI.^13,22

To conclude, most of the older adults in Taipei City had a general cognition of exercise and understood that exercise is of great help to their health. However, data research revealed that there is still great room for improvement for older adults’ EA. Therefore, only improving older adults’ EA may be insufficient for increasing exercise behaviors. Research has found that the social support from family, spouses, and friends of the main group^11,13,21 or the adoption of positive language with encouragement and approval can improve older adults’ mental health first Then, their self-efficacy and confidence can be improved and their exercise behaviors increased. Older adults who live alone can be guided to join a group for exercise participation through the encouragement of community or neighborhood activities.¹⁰

This study had two limitations. First, the data were from older adults in senior learning centers in Taipei City, and 2019 Exercise Survey data of the Sports Administration of Taiwan's Ministry of Education were referenced. A large portion of the population of Taipei moved there from small towns with urbanization. However, the study data may not be applicable to older adults in rural areas. Second, the TPB can only generally explain the prediction of BI. In the TPB, behaviors are assumed to be a linear decision-making model, but in fact, behaviors may change with time. The TPB may be influenced by the factors of older adults’ psychological state, disease, educational level, BMI, activities of daily living, or individual economic condition.^20,25 These factors may also influence older adults’ exercise BI.

Conclusion

The research concluded that the following measures can possibly promote older adults’ exercise behaviors. 1. EA: Health, regimen, and exercise courses should be offered in the 12 districts’ senior learning centers in Taipei. Health consultation volunteers can help older adults with physical fitness examinations and exercise consultations. 2. SN: Older adult exercise clubs should be established in communities and neighborhoods. Family members and spouses can be requested to encourage older adults to collectively participate in exercise through TV promotions. Neighborhood parks or public activity centers can be built as places for older adults to exercise and make friends. 3. PBC: Friendly parks and barrier-free exercise facilities can be built. Older adult exercise facilities should be strengthened for safety. Free exercise periods and discounts for older adults should be provided in the 12 districts’ exercise centers. This research can combine TPB theory with other theories in the future. Alternatively, some of the factors in the TPB can be used with the addition of other behavioral theories. Thus, the TPB can be expanded for deep and comprehensive research on older adults’ exercise BI.

Footnotes

Acknowledgements

I would like to thank the directors and commissioners of the senior learning centers in Taipei City for their assistance with the questionnaire distribution and retrieval. I would also like to thank the professors of the Department of Physical Education of the University of Taipei for their instruction on and revisions of details related to ethics in this study. The revised official questionnaire did not influence the participants’ rights or involve their personal privacy (the questionnaire was anonymous, and the background survey only included sex, age interval, and exercise companions). The survey only targeted the participants’ exercise BI. In addition, thanks to Wallace Academic Editing for completing the English translation and revision. Most importantly, I would like to thank my coauthors for completing this manuscript as well as the members who assisted in the research.

Authors’ contributions

HWY and WCE designed the study and wrote the manuscript, and performed the questionnaire and statistical analysis. Two authors read and approved the final manuscript.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to 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.

Availability of data and materials

The data sets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

ORCID iDs

Wei Yang Huang

Cheng-En Wu

Author biographies

Wei Yang Huang is a doctorate in education from National Taipei University of Education in Taiwan, and received a PhD in exercise science from Soochow University in China. From 2012 until now, has served as an assistant professor at the National Taiwan College of Performing Arts. Since 2012, has been serving as the university's physical education and sports science (sports biomechanics, sports physiology) courses.

Cheng-En Wu is a PhD student from Chung Hua University in Taiwan. My research area is in social science. I currently focus sports and leisure management.

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Predict the exercise behavior intention of the older adults in Taipei City to promote exercise behavior

Abstract

Keywords

Introduction

Materials and methods

Research structure

Participants

Measures

Procedures

Data analyses

Results

Analysis of respondents’ basic information

Discussion

Older adults’ exercise behavior intentions for different background variables

Older adults’ exercise behavior intentions and promotion

Conclusion

Footnotes

Acknowledgements

Authors’ contributions

Declaration of conflicting interests

Funding

Availability of data and materials

ORCID iDs

Author biographies

References