Digital media use and the Chinese elderly’s physical activity: Evidence from a national aging social survey

doi:10.21203/rs.3.rs-2534041/v1

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Digital media use and the Chinese elderly’s physical activity: Evidence from a national aging social survey

https://doi.org/10.21203/rs.3.rs-2534041/v1

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Background and Objectives: Constructing a national fitness service system is important in realizing high-quality development. This study analyze the impact and mechanism of digital media use on physical activity (PA) in the elderly.

Research Design and Methods: This study uses the China Longitudinal Aging Social Survey data. At first, we uses the ordinary least square model (OLS) and binary selection modelto test the relationship between digital media use and elderly’s PA.Then, we uses the three-step causal analysis and Bootstrap methods to test whether there is a mediating effect.

Results: The study found that: first, physical activity of the elderly involves multiple difficulties, such as lack of PA venues, PA organizations and PA guidance. Second, the use of digital media such as smartphones and the internet have a positive impact on the elderly’s PA, and this conclusion still holds after using multiple robustness tests. Thirdly, promoting the elderly’s participation in community governance, enhancing interpersonal support of the elderly, and improving positive efficacy of the elderly are mediating mechanisms.

Discussion and Implications: This study highlights the importance of using digital media, upgrading sports public service resources, participating in community governance, and building social support for the elderly.

Earth and environmental sciences/Environmental social sciences

Health sciences/Health care

digital media use

the elderly

social support

positive efficiency

The aging of the population has brought severe challenges to national governance. To effectively deal with the problem of population aging, the Communist Party of China (CPC) has proposed the Healthy China Strategy and emphasizes the development of public services’ supply capabilities. As an essential part of public services, the status of the national fitness service is a significant way to enhance the elderly’s health literacy.

There has been fruitful academic research on the issue of physical activity (PA) for the elderly. These studies mainly focus on the following aspects, including the current status of PA participation by the elderly (Guo et al., 2016), perceptions of exercise (Liu et al., 2015), cohort differentiation of PA participation (Zang & Ng, 2016), the function of exercise motivation (Chen & Tsuchiya, 2016), and so on. The above research inspires us to continue the study of PA in the elderly. However, they ignore the possible impact of the developing digital service construction on the PA of the Chinese elderly.

In the era of digital media, digital information platforms displayed by new media technologies have become an essential channel for the public to obtain and disseminate information. The public can learn the latest news and realize online social needs through mobile devices or the internet. It is known that digital media services have penetrated every aspect of public life. What are the dilemmas faced by the elderly in PA? As users of digital media services, will these services impact the PA of the elderly? Lastly, what is the medium of digital media services? The academic community has not researched this question.

The contribution of this study is two-fold. First, based on China’s context, this study uses national sample survey data and conducts an empirical analysis of the effect and the mechanisms of digital media use on the PA of the elderly, which enriches the understanding of the impact of digital technology use on the public’s behavior. Second, this study shows the dilemmas of the elderly in realtion to PA and improves the existing literature on the status quo of mass’ PA.

Using digital media and the elderly’s PA

The elderly are a group that a country or region will inevitably face in coping with the wave of aging. Existing studies have shown that PA positively affects the health, subjective well-being, and life satisfaction of the elderly (McPhee et al., 2016). Therefore, improving PA for the elderly is important in building a national fitness service system and actively responding to the aging work worldwide.

In terms of factors affecting the PA of the elderly, these can be roughly classified into four types. The first type is the individual physiological characteristics of the elderly, such as physical health (Li et al., 2010), age (Jenkin et al., 2017), chronic disease status (Lin et al., 2011), and their exercise habits (Hagger, 2019). The second is the elderly’s socioeconomic characteristics, such as income (Shuval et al., 2017), socioeconomic deprivation (Qian et al., 2018), and social capital (Fu et al., 2018). The third includes non-sport factors such as the level of economic development (Wang et al., 2017), PA park features (Petrunoff et al., 2022), and environmental quality (Smith et al., 2019). The last are the sports’ factors, such as the development level of the sports’ industry (Kroesen & Wee, 2022), the public sports’ service policy system (Hoekman & Scheerder, 2021). However, the above literature ignores the impact of digital media use on the PA of the elderly.

According to the China Internet Network Information Center data, the penetration rate of smartphones and the internet in China has reached 58% and 45.80% in 2021, respectively. Additionally, the number of netizens also soared from 618 million in 2013 to 904 million in 2021. In short, the public has embedded in an era of digital media. The use of digital media not only reduces the cost for the public of understanding or exchanging information but also has an impact on individual social behavior. Different scholars have paid attention to this phenomenon and conducted much research. For example, the use of the internet has a significant impact on the transformation of the rural economy (Ishida, 2015), the gender difference in wage income (Forman et al., 2012), political participation of the public (Lee, 2017). Based on this, this study infers that the use of digital media services such as smartphones or the internet impacts older adults’ PA.

Unlike the existing research on the impact of the internet on an individual’s economic or social behavior, we argue that the effect is complex.

One possible impact is the positive one. The use of digital media helps the elderly learn some knowledge of different types of PA, such as running, fitness, Taichi, etc., and it benefits the PA. Specifically, by using digital media to download various popular sports apps, the elderly may learn the basic requirements of sports and rehabilitation knowledge. Thus, the elderly can communicate with other age groups to make themselves better integrated into digital society. Furthermore, the information transmitted by the digital media breaks the defect of one-way information dissemination. It establishes a bridge for the elderly to communicate with the government and the public, thus forming an incentive for public resocialization. Using the planned behavior theory and the social survey performed in Israel, Zach and Lissitsa (2016) found that individuals who used the internet had a higher odds of engaging in PA than non-internet users. Wang et al. (2022) also confirmed that using digital media positively impacts older adult’s PA in China; more importantly, this effect is more potent than in youth.

However, using digital media services may also harm older adults’ PA. In the context of widespread digital media, the public may face diverse information sources which compete for people’s scarce attention resources. Thus, the most precious resource is attention rather than knowledge. Attention allocation is a social problem, not just a technical one. As the information disseminated on digital media is selective, the use of smartphones or the internet by the elderly has their fixed content preferences, which can lead to new hobbies rather than PA. That is to say, using digital media may crowd out the time commitment to PA. Finally, because the information is not entirely favorable, the theory of media depression holds that the audience is likely to have conflicted feelings if they are exposed to negative news for a long time. In other words, older people may experience a decrease in their PA time through the use of digital media.

Consequently, we propose the competing hypotheses:

H1.1: The use of digital media positively impacts the elderly’s PA.

H1.2: The use of digital media harms the elderly’s PA.

The mechanism analysis framework

How does digital media use affect the PA of the elderly? Researchers from sociology, psychology, and other disciplines have conducted much research on this. Earlier studies focused on attitudes such as loneliness, well-being, and life satisfaction of the elderly (Crombie et al., 2004), while recemt studies focus on psychological attitudes like positive efficacy (Litman et al., 2015). In addition, scholars have also explored some explanatory theories, including detachment theory, self-determination theory, and hierarchy of need theory. The media dependence theory holds that digital media can satisfy the audience’s needs, including social communication, self-determination, self-entertainment, and other psychological needs (Ball-Rokeach, 1998). Overall, digital media meet the audiences’ needs by providing continuous and cumulative information services. This study argues that using digital media may affect the PA of the elderly through external social support, community participation, and positive efficacy.

First, digital media enhances the interaction between the elderly and external social groups, thereby affecting their physical activity. By using digital media, the elderly can share daily life experiences and other local knowledge with members outside the family through online or offline interaction. Thus, they can find common topics with each other to meet their emotional needs. The support of the peer network is an important factor that needs attention. By using the English Longitudinal Study on Aging data, Gilleard et al. (2007) found that the smartphone or internet had significantly improved the social capital of the elderly. Besides, Chopik (2017) found that online chatting can enhance older adults’ social interaction with friends, eventually benefiting their well-being, and reducing loneliness and chronic illness risk.

Second, digital media facilitates the integration of the elderly into residential communities, affecting their likelihood of PA. The Chinese rural community is a society of acquaintances, while the urban community is a society of strangers. In general, PA involves social interaction between acquaintances. With the advancement of urbanization, new community governance affairs have occurred and new members have arrived in the communities where the elderly live. Using digital media encourages the elderly to communicate in online network organizations, which could reduce the psychological distance between community members and encourage them to integrate into the community. Based on the context of COVID-19, Khan et al. (2022) identified that using the internet pushes communication between neighbors on life risk experiences and individual participation in community governance. Through participating in community governance affairs, the elderly expand their localized social network, hence, enhancing the possibility of PA.

Third, using digital media increases the positive efficacy of the elderly, affecting their PA. Due to the lower human capital, it is difficult for some elderly to resocialize. They think they are out of touch with a new culture and cannot integrate into the rapidly developing society. However, with the deepening of digital media, the elderly can obtain necessary information from the internet at a low cost and increase the opportunities for lifelong learning. Thus, using digital media promotes resocialization and the positive efficacy of the elderly. Cotten et al. (2014) demonstrated that using the internet contributes to American older adults’ mental well-being and reduces symptoms of depression. Another study shows that the positive efficacy significantly impacts their daily PA (Al-Ghafri et al., 2017).

Hence, we propose the mechanism hypothesis:

H2: Using digital media services affects the elderly’s PA through external social support, community participation, and positive efficacy.

Data Collection

This paper uses the China Longitudinal Aging Social Survey data (CLASS). This was designed and implemented by the Renmin University of China. The CLASS survey was a nationwide and continuous large-scale social survey covering more than 30 provincial units across the country. It collected information about the elderly’s lifestyle, physical and mental health, PA, family care, external support, and so forth. The first wave of the nationwide baseline survey was in 2014, and the latest survey data released was that of 2018. Thus, this study used the 2018 CLASS data. After deleting missing and outlier values, we obtained valid analysis samples of 9084 people. Furthermore, we also matched the Chinese Statistical Yearbook data (2018).

Measures

Dependent variables

PA and PA frequency (PAfreq). Questions were: (1) Have you participated in PA in the past year? The options were: 1 = yes, 0 = no; (2) How often do you participate in PA? Options are 1 = average less than one time per month, 2 = average less than one time per week, 3 = once per week, 4 = two times per week, 5 = three times per week, 6 = four times per week, 7 =f ive times per week, 8 = six times per week, 9 = seven times per week and above. It can be seen that the former variable is a dichotomous variable, and the latter is a continuous variable. We combined the two items into a continuous variable with a score of from zero to nine. The higher the score, the higher the frequency of PA.

Independent variables

Using digital media. The CLASS interviewed the elderly about their habit of using digital media, including: (1) Do you use a smartphone now? The options were 1 = yes, 0 = no. (2) Do you often surf the internet? The options were 1 = yes, 0 = no. (3) How often did you use the internet in the past three months? (4) How often do you use your smartphone? The options for questions (3) and (4) were 1= never, 2 = rarely, 3 = sometimes, 4 = often, 5 = always. Thus, we operationalized the concept of using digital media into four variables: whether using smartphones (Umar), whether using the internet (Uint), and the frequency of using smartphones (Umarfreq), and the frequency of using the internet (Uintfreq).

Mediating variables

The mediating variables were as follows: community participation (Compar), positive efficacy (Poseff), and external social support (Socsup). First, the Compar was: Have you participated in community activities in the past three months. There were eight choices: community security, caring for other elderly, environmental action, addressing disputes, accompanying chat, volunteer experience, caring for other’s grandchildren, and other community affairs. We summed these up to form a continuous variable of community participation with a score of from zero to eight. The larger the value, the higher the community participation. Second, the CLASS survey inquired about the positive efficacy of the elderly, with items such as: “I often want to do something for society again”, “I like to study”, “I think I am still a useful person to the society”, “I am willing to participate in the work of the village committee”, the options are 1 = completely inconsistent, 2 = relatively inconsistent, 3 = general, 4 = relatively consistent, 5 = fully consistent. We summed up the four items and then averaged them to obtain a variable of positive efficacy of the elderly with a score of from one to four. Third, the question of external social support was: How many friends can you meet or contact at least per month? The options were 0=none, 1=one friend, 2=two friends, 3=three to four friends, 4=five to eight friends, 5=more than nine friends. The higher the value, the stronger the social support of the elderly.

Control variables

Based on existing studies, the control variables in this research included the elderly’s gender, age, hukou, marital status, and other demographic characteristics (Table 1).

[Table 1 near here]

Model Design

As there were two types of dependent variables, binary variables and continuous variables, we used the ordinary least square model (OLS) and binary selection model, and the equations setting forms were:

OLS model: ${exercise}_{i}={\alpha }_{0}+{\beta }_{1}\times {use}_{i}+{\beta }_{2}\times {X}_{i}+{\mu }_{i}$ (1)

Probit model: $\text{P}（{exercis}_{ij}=1｜{x}_{ij},{\beta },{u}_{ij}）={\Lambda }\left({x}_{ij}^{\prime }\text{*}{\beta }+{u}_{ij}\right)=\frac{{e}^{{x}_{ij}^{\prime }\text{*}{\beta }+{u}_{ij}}}{1+{e}^{{x}_{ij}^{\prime }\text{*}{\beta }+{u}_{ij}}}$ (2)

In the OLS model, ${exercise}_{ij}$ is the PA frequency of the elderly I in J province; in the Probit model, the variable ${exercise}_{ij}$ is the binary variable of whether the elderly I in J province does PA. The variable ${use}_{i}$ stands for older people I using a smartphone or the internet, and the frequency of usage. The ${\beta }_{1}$ represents digital media use’s effect on the elderly’s PA. ${X}_{i}$ is the control variable. Lastly, the ${u}_{ij}$ is the random disturbance.

Second, this paper uses the three-step causal analysis and Bootstrap methods to test whether there is a mediating effect. The three-step analysis model is as follows:

$${M}_{ij}{=\alpha }_{1}+{{\gamma }}_{1}\text{*}{use}_{ij}+{\gamma }_{2}*{X}_{ij}+{\mu }_{ij}$$

$${Exercise}_{ij}={{\alpha }}_{0}^{{\prime }}+{\beta }_{1}^{{\prime }}{*use}_{ij}+{\gamma }_{1}^{{\prime }}*{M}_{ij}{+\beta }_{2}^{{\prime }}*{X}_{ij}+{\mu }_{ij}^{{\prime }}$$

In Eq. (3), ${M}_{i}$ represents the mediating variables such as community participation, positive efficacy, and social support. In Eq. (4), ${Exercise}_{ij}$ represents the PA of the elderly, ${\gamma }_{1}^{{\prime }}$ represents the effect of the mediating variable on the dependent variable, ${\beta }_{1}^{{\prime }}$ means the net effect of digital media use on older adults’ PA. ${X}_{i}$ and ${\mu }_{ij}^{{\prime }}$represent the control variables and random disturbance, respectively.

Descriptive statistics

Table 2 reports the descriptive statistics. Overall, 16.4% of the elderly had the habit of engaging in PA. The ratio of the elderly who used smartphones and the internet was 18.6% and 12.4%, respectively. However, the frequency of PA, and using smartphones or the internet were relatively low. Of the interviewed elderly, 50.7% were women, the mean age of the elderly was 67.5, 46.1% had urban hukou, and 71.9% had a spouse. The average cognitive ability of the elderly was 13.31, 41.8% had retirement benefits, but 11.8% were still engaged in paid work. Regadding location, 65.1% lived in cities. Furthermore, the elderly’s self-rated health score was 3.376. However, the mental health score was only 5.149 points, which is moderate, and 60.3% of the elderly suffered from chronic diseases.

[Table2 near here]

Furthermore, the social support score of the elderly was 2.908. That is, the elderly can meet and communicate with three to four friends per month. The value of the elderly’s positive efficacy was 3.199, indicating that the elderly’s effectiveness was positive. The score for community participation was 0.168, which means that the elderly were less involved in community governance affairs.

The current status of the elderly’s PA

Then, we analyzed the current situation of PA of the elderly, including PA venues, PA tyPAs, PA organizers, and PA instructors.

[Table 3 near here]

Table 3 presents the satisfaction of the elderly with PA behavior in the PA venue. Overall, 60 % of the elderly used the open space near their residence as the main venue for PA, followed by parks or squares, roadsides, indoors, or courtyards. Regarding usage frequency, the highest frequently used value of the elderly was the open space near their residence, and nearly once in four days. Regarding meeting demand, the elderly were most satisfied with PA in parks or squares, reaching 54 %. Lastly, some elderly used the roadsides for PA, while paid stadiums, free public stadiums, and unit stadiums faced the phenomenon of low use ratio and low satisfaction, which reflects the dilemma of difficulty in PA venues.

[Figure 1 near here]

The CLASS survey investigated the primary forms of exercise of the elderly and listed 18 types of PA, including walking, running, swimming, cycling, table tennis, badminton, tennis, football, basketball, volleyball, square dance, fitness exercise, martial arts, boxing, Qigong, Tai chi, and yoga. Figure 1 reports the top three PA choices that older adults frequently used. It can be seen that the first preferred PA items were walking, followed by square dancing and running. Among the second choice, the top three items were running, walking, and fitness exercise. Regarding the third choice, the elderly preferred fitness exercise, Tai chi, and swimming. In conclusion, the elderly mainly focused on moderate and light exercise such as walking, square dance, running, etc.

[Figure 2 near here]

The CLASS survey asked about the organizers of the elderly’s PA. Figure 2 presents the results. It can be seen that the elderly’s PA was unorganized, accounting for 69.80% (=1135/1626), followed by a PA interest group, accounting for 19.19%. However, the ratio of the institutions of an official government authority such as sports’ administrative departments, neighborhood committees, and sports’ associations was low, which shows that the elderly’s PA faces the dilemma of an absence of organizers.

[Figure 3 near here]

Futhermore, the CLASS survey also asked about the instructors of the elderly’s PA. Figure 3 reports the results. It can be seen that the PA of the elderly primarily had no guidance, accounting for 76.33% (=1241/1626). The second was neighbors or friends as instructors, accounting for 14.76%. However, the guidance ratios from the community PA instructors, sports’ volunteers, or school PA teachers were low. Overall, the elderly’s PA faces the dilemma of insufficient professional guidance.

In short, the lack of exercise venues reflects the imbalance between the types of existing sports’ venues, the lack of organizations reflects the poor division of labor within the existing sports’ organizers, and the absence of scientific guidance demonstrates the lack of scientific knowledge and professional guidance in PA for the elderly.

Benchmark regression analysis

Table 4 reports the effects of using smartphones and the internet on older adults’ PA. Model 1 included the independent variables, Model 2 further included the elderly’s characteristic variables, and Model 3 included regional background variables. From the results of Model 3, compared with those who did not use smartphones, the elderly who used smartphones were more likely to have PA Similarly, the netizens had a higher probability of taking PA than non-netizens. Thus, we believe that the use of digital media positively affects the elderly’s PA.

[Table 4 near here]

Furthermore, there was no significant difference in PA among the female and male elderly, the urban and rural hukou, high and low educated elderly, married and non-married individuals, the elderly with a job and those without, and the elderly with high or inadequate mental health. With increasing age, the possibility of PA for the elderly also decreases. The higher cognitive ability, the more likely are the elderly to exercise. Compared with the elderly without retirement benefits, those who own benefits were more likely to engage in PA. This is possibly because the elderly with retirement benefits have better economic conditions, human capital, and lower time costs for PA. The public living in urban areas were more likely to exercise than those who do not. The higher the self-rated health of the elderly, the higher the likelihood of PA. A chronic disease significantly reduced the possibility of PA among older adults With the elderly’s income increasing or the region’s per capita income increasing, the elderly were more likely to exercise. However, the rise of wastewater discharge or the greening rate significantly reduced the PA of the elderly. Overall, hypothesis 1.1 was validated.

Robustness analysis

In reality, many elderly do not have PA habits. That is, the frequency of PA is zero. Therefore, the results in Table 3 have the problem of the sample selection effect. We adopted the truncated estimation method for the robustness test to solve this problem. Then, we concentrated the sample on the group of elderly with PA and deleted the pieces that did not have PA. Model 1 in Table 5 presents the regression results. It can be seen that internet use significantly enhanced PA frequency of the elderly, but there was no significant effect of using smartphones.

Furthermore, the environment is an important factor affecting individual PA behavior. That is, the PA of the elderly is embedded in an outside environment, and the behavior may change with the embedded domain. Therefore, researchers emphasize the nesting effect in research. Hence, we examined the influence of provincial traits and used the hierarchical linear model (HLM) as a robustness test method, in which the first layer model wss the variable of the elderly, and the second layer model was the provincial variables where the elderly lived. Model 2 in Table 5 reports the estimation results of the HLM. It can be seen that the use of smartphones or the internet can significantly enhance the PA frequency of the elderly. The inter-group correlation coefficient was 26.82%, which means that provincial traits can explain 26.82% of the influencing factors of the elderly’s PA behavior in the same province. To sum up, using smartphones or the internet has a significant promoting effect on PA participation of the elderly.

[Table 5 near here]

Mediation effect analysis

The previous results suggest that PA among older adults benefits from smartphone or internet use. Although PA is an individual social behavior, such behavior is often affected by the peer group and community environment in which one lives. When there is a group PA behavior around the elderly, or the positive efficacy is more robust, the elderly are more motivated to PA. Therefore, the theoretical analysis part of this research explained the logic of using digital media to promote elderly’s PA through social interaction and positive efficacy. We adopted a stepwise regression test method to verify whether external social support, positive efficacy, and community participation mediate between digital media use and elderly’s PA. The first step is to regress the independent variable on the dependent variable. If the coefficient is significant, we can perform the second step. That is, regress the independent variable on the mediating variable. The third step is to incorporate the independent and mediating variables into one equation regression on the dependent variable.

Table 6 and Table 7 present the mediating effect results. Model 1 of each table is the regression result of the first step. The PA frequency as the dependent variable, using smartphones or the internet as the independent variable, with the control variables added. The results showed that the use of smartphones or the internet had a significant positive effect on the PA frequency of the elderly. Therefore, we continued to the mediation effect test. In Table 6 and Table 7, Model 2, Model 3, and Model 4 are the estimated results of the third step of the mediation effect.

[Table 6 near here]

Table 6 shows that mediating variables positively affected the PA frequency of the elderly. After adding three mediating variables, the coefficients of the independent variables were significantly reduced, and the reduction degree of Model 4 was the largest. This indicates that external social support, community participation, and positive efficacy were mediating mechanisms for using smartphones to affect the PA frequency of the elderly. In addition, we used the Bootstrap (500 times) method to verify the above results. The coefficient of the Sobel test was significant, and the 95% confidence interval did not include zero, indicating that the mediation effect was valid.

Model 2 in Table 7 shows that the estimated coefficient of using the internet does not decrease significantly after adding the external social support variable, which indicates that external social support is not an effective mediating mechanism. However, the coefficients of using the internet in Model 3 and Model 4 decreased, showing that community participation and the elderly’s positive efficacy were mediating variables that use the internet to affect the PA frequency of the elderly. The results of the Bootstrap method further support the above findings.

[Table 7 near here]

The essence of building a national fitness service system is to meet people’s yearning for a better life. Since the nneteenth National Congress of the CPC, the CPC has clearly stated that China has entered a new era of socialism with Chinese characteristics, and the principal contradiction is that between the people’s growing needs for a better life and unbalanced and inadequate development. In this research, the imbalance between the needs of the elderly for PA and the lack of an elderly fitness service system is a structural obstacle that restricts their fitness. We found that fitness dilemmas manifest in the difficulty with fitness venues, scientific PA guidance, and problems in seeking organizations. In this paper, from the view of the proportion of PA, only 16.4% of the elderly have PA. In other words, the elderly also have difficulty in active fitness.

“Technology + pension + sports” is a new plan to deal with the current aging trend for all countries. This new development path can not only better promote the integration of the elderly into digital society but also vigorously promote the strategy of building a strong PA country supported by science and technology. This paper investigates the PA of the Chinese elderly from the view of using digital media services and finds that using smartphones and the internet has a significant role in encouraging the participation of older adults in sports. Using digital media reflects the new characteristics of social and economic development. How to start from the actual needs of the elderly and to making digital media services better for aging is an effective countermeasure to overcome the digital divide for the elderly.

This paper proposes the following policy recommendations based on the above research findings. First, from the science and technology perspective, government and non-governmental organizations should further strengthen publicity and increase the skills of using digital media. Government departments can encourage technology companies and public service agencies to participate in the development of online sports’ guidelines for the elderly through fiscal policies, tax policies, etc. The use of sports’ knowledge transmitted through digital media promotes the scientific and technological foundation of the national fitness service system. It creates favorable conditions for developing new sports for the elderly. Second, from the point of public sports’ services for the elderly, the government have to vigorously optimize and upgrade the sports’ service resource system. Specifically, this includes: promoting the construction of PA venues for the elderly, pushing the low-cost opening of sports’ venues to the elderly, solving the shortcomings of the lack of exercise venues for the elderly, incorporating the construction of sports and fitness facilities for the elderly into the living environment renovation project, and developing a variety of sports and fitness facilities. Third, to strengthen the guidance and organization of sports’ services for the elderly, the authorities must give full play to the advantages of sports’ associations and sports’ volunteers, improve the construction of grassroots sports’ organizations and grassroots PA instructors, and optimize the service capability of grassroots national fitness.

Building a national fitness service system and promoting its implementation are an essential parts of the development stage for all developing and developed countries. From the perspective of national fitness and mass sports, this study analyzes the dilemmas faced by the elderly in PA and examines the impact and mechanism of using digital media on the PA behavior of the elderly. The findings are as follows. First, the elderly’s PA faces three dilemmas: lack of exercise venues, inadequate exercise organizations and insufficient exercise guidance. Second, using digital media services such as smartphones and the internet significantly enhances the possibility and intensity of the elderly’s PA. After applying multiple robustness tests, these findings remain valid. Third, the elderly’s participation in community governance, external social support, and positive efficacy are mediating mechanisms of using digital media affecting the elderly’s PA.

Funding:

This work is funded by the Guanghua Talent Project of Southwestern University of Finance and Economics

Compliance of ethical standard statement

This study does not contain any studies with human participants by any authors.

Conflict of interest statement

There are no conflicts of interest with respect to the research to declare.

Informed consent

All authors agree with the current manuscript and publication in Scientific Reports.

Availability of Data

The data that used in the study and support the findings of this study are available from the corresponding author.

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Table 1

The control variables were used.
Control variables	Definition
Gender	Female = 0, male = 1
Age	The age reported by the respondents
Hukou	Rural hukou = 0, urban hukou = 1
Marry	Unmarried, divorced, widowed = 0, married or living together = 1
Cognitive	Sum up the elderly’s scores on calculation, language, and memory questions
Benefits	Have no retirement benefits = 0, have retirement benefits = 1
Education	The highest education level attainment of the elderly, Illiterate = 0, primary school = 1, middle school = 2, high school = 3, college and abolve = 4
Employment	Engaged in a paid job in the last month = 1, no paid job = 0
Living	Living in rural = 0, living in urban = 1
Chronic	Whether the elder has a chronic disease, no = 0, yes = 1
SRH	The self-rated health status of the elderly, very unhealthy = 1, relatively unhealthy = 2, general = 3, relatively healthy = 4, very healthy = 5
Mental	The elderly’s loneliness, powerlessness, and unhappiness feelings in the last week
Income	Annual income reported by the elderly, we takes the natural logarithm form
PerGDP	The provincial GDP divided by the population size of the province in 2017
Waste	Dividing the wastewater discharge (10 000 tons) by the population size of the province where the respondents were live in 2017
Green	Greening rate in the province where the respondents were live in 2017

Table 2

Descriptive statistics of variables (N = 9084).
Variable	Mean	Std	Min	Max
PA	0.164	0.370	0	1
PAfreq	0.964	2.459	0	9
Umar	0.186	0.389	0	1
Uint	0.124	0.330	0	1
Umarfreq	1.114	0.430	1	5
Uintfreq	1.400	0.956	1	5
Gender	0.507	0.500	0	1
Age	67.49	7.048	60	95
Hukou	0.461	0.498	0	1
Marry	0.719	0.450	0	1
Cognitive	13.31	3.139	5	16
Benefits	0.418	0.493	0	1
Education	1.341	1.113	0	4
Employment	0.118	0.322	0	1
Living	0.651	0.477	0	1
SRH	3.376	0.882	1	5
Mental	5.149	2.004	0	9
Chronic	0.603	0.489	0	1
Income	8.950	2.006	0	11.51
PerGDP	56154	25042	19710	118198
Waste	23409	15983	2006	71217
Green	39.49	3.331	29.790	48.400
Socsup	2.908	1.940	0	5
Poseff	3.199	1.312	1	4
Compar	0.168	0.511	0	7
Note: Province variables are 30 categorical variables and not displayed in the table.

Table 3

Satisfaction of the elderly’s PA space.
Venues	Obs.	Have used	Usage frequency	Meeting demand
Open space near a residence	1626	60%	2.000	50%
Park or square	1626	55%	1.650	54%
Roadsides	1626	45%	1.450	34%
Indoor or courtyard	1626	46%	1.710	37%
Community venues	1626	41%	1.350	43%
Paid sports venues	1626	30%	0.220	9%
Committee venues	1626	28%	0.850	31%
Free public sports venues	1626	10%	0.290	14%
Unit sports venues	1626	4%	0.120	9%
Notes: Usage frequency: 0 = not used, 1 = once in 5–7 days, 2 = once in 4 days, 3 = once in 3 days, 4 = once in 2 days, 5 = once per day, 6 = more than once per day.

Table 4

Benchmark Analysis.
Variables	Model 1	Model 2	Model 3
Umar	0.462^***	0.305^***	0.401^***
	(0.053)	(0.056)	(0.058)
Uint	0.115^*	0.123^*	0.122^*
	(0.062)	(0.064)	(0.068)
Gender		0.063^*	0.002
		(0.035)	(0.036)
Age		-0.013^***	-0.007^***
		(0.003)	(0.003)
Hukou		-0.022	-0.067
		(0.047)	(0.049)
Marry		-0.043	-0.009
		(0.041)	(0.042)
Cognitive		0.016^***	0.022^***
		(0.006)	(0.006)
Benefits		0.203^***	0.129^***
		(0.046)	(0.050)
Education		0.021	0.005
		(0.019)	(0.020)
Employment		0.037	0.060
		(0.051)	(0.054)
Living		0.272^***	0.248^***
		(0.050)	(0.051)
SRH		0.044^**	0.072^***
		(0.022)	(0.023)
Mental		-0.010	-0.011
		(0.009)	(0.009)
Chronic		-0.284^***	-0.291^***
		(0.035)	(0.037)
Income		0.029^***	0.022^**
		(0.010)	(0.010)
PerGDP			0.001^***
			(0.000)
Waste			-0.001 ^***
			(0.000)
Green			-0.078 ^***
			(0.006)
Province	control	control	control
Constant	-1.100^***	-0.329	1.557^***
	(0.018)	(0.261)	(0.356)
Pseudo R²	0.03	0.06	0.11
Obs.	9084	9084	9084
Note: (1) ^* p < 0.10, ^ p < 0.05, ^* p < 0.01; (2) Robust standard errors in brackets.

Table 5

Robustness analysis estimation results.
Estimation method	Truncated Estimation	Estimation method	HLM
	Model 1		Model 2
Umar	-0.046	Umar	0.688^***
	(0.233)		(0.093)
Uint	0.881^***	Uint	0.317^***
	(0.260)		(0.110)
Sigma	2.719^***	Correlation coefficient	26.82%
	(0.060)	LR test	706.50^***
Constant	6.648^***	Constant	5.675^***
	(1.457)		(1.737)
Obs.	1488	Obs.	9084
Note: (1) ^* p < 0.10, ^ p < 0.05, ^* p < 0.01; (2) Robust standard errors in brackets.

Table 6

The mediating effect of using smartphones by the elderly.
	Model 1	Model 2	Model 3	Model 4
Umar	0.840^***	0.827^***	0.825^***	0.792^***
	(0.086)	(0.086)	(0.086)	(0.087)
Socsup		0.061^***
		(0.014)
Compar			0.221^***
			(0.054)
Poseff				0.117^***
				(0.018)
Constant	4.696^***	4.600^***	4.589^***	4.129^***
	(0.560)	(0.558)	(0.561)	(0.566)
R ²	0.103	0.105	0.105	0.106
Bootstrap test method
Sobel test value		0.010^**	0.013^**	0.042^***
		(0.005)	(0.006)	(0.009)
95% confidence interval		[0.002,0.018]	[0.003,0.023]	[0.023,0.059]
Obs.	9084	9084	9084	9084
Note: (1) ^* p < 0.10, ^ p < 0.05, ^* p < 0.01; (2) Robust standard errors in brackets.

Table 7

The mediating effect of using internet by the elderly.
	Model 1	Model 2	Model 3	Model 4
Uint	0.896^***	0.896^***	0.886^***	0.844^***
	(0.105)	(0.104)	(0.104)	(0.105)
Socisup		0.066^***
		(0.014)
Compar			0.232^***
			(0.054)
Poseff				0.121^***
				(0.018)
Constant	4.697^***	4.594^***	4.585^***	4.111^***
	(0.563)	(0.560)	(0.564)	(0.569)
R ²	0.100	0.103	0.102	0.104
Bootstrap test method
Sobel test value		0.000	0.012^**	0.049^***
		(0.004)	(0.006)	(0.009)
95% confidence interval		[-0.007,0.008]	[0.001,0.023]	[0.031,0.068]
Obs.	9084	9084	9084	9084
Note: (1) ^* p < 0.10, ^ p < 0.05, ^* p < 0.01; (2) Robust standard errors in brackets.

No competing interests reported.

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Digital media use and the Chinese elderly’s physical activity: Evidence from a national aging social survey

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Abstract

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Background and Objectives

Theoretical framework and research hypotheses

Using digital media and the elderly’s PA

The mechanism analysis framework

Research Design and Methods

Data Collection

Measures

Dependent variables

Independent variables

Mediating variables

Control variables

Model Design

Results

Descriptive statistics

The current status of the elderly’s PA

Benchmark regression analysis

Robustness analysis

Mediation effect analysis

Discussion and Implications

Conclusion

Declarations

References

Tables

Additional Declarations

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