Smartphone use, health-promoting behaviours and self-rated health among middle-aged and elderly people in rural areas

Smartphone use, health-promoting behaviours and self-rated health among middle-aged and elderly people in rural areas | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Smartphone use, health-promoting behaviours and self-rated health among middle-aged and elderly people in rural areas Xiaomin Gan, Xuefang Liu, Juan Wu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4953641/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective Accounting for the convergence of digitalization and ageing, our study focused on middle-aged and elderly people in rural areas. Moreover, the potential mechanisms by which smartphone use affects the self-rated health and heterogeneity among different groups were explored, and the mediating effects of health-promoting behaviours were explored, with the aim of providing relevant insights and recommendations for improving the health of rural middle-aged and elderly people and actively promoting healthy ageing in rural areas. Methods On the basis of data from the 2020 China Rural Revitalization Survey, we established a multiple linear regression model to assess the direct effects of smartphone use (including whether to use, difficulty of use, and duration of use) on the self-rated health of rural middle-aged and elderly people and examined the heterogeneity among the various groups in terms of sex, age, and education level. In addition, the three-step regression and bootstrap test methods were used to analyse the mediating effect of health-promoting behaviours on the relationship between smartphone use and self-rated health. Results Smartphone use among rural middle-aged and elderly people significantly and positively affected their health-promoting behaviours and self-rated health, and the findings were robust. The positive effects of smartphone use on self-rated health were heterogeneous among rural middle-aged and older adults of different ages, sexes, and education levels. Health-promoting behaviours exerted significant mediating effects, accounting for 91.91%, 95.27% and 90.91% of the total effects, respectively. Conclusion Smartphone use among rural middle-aged and elderly people notably affected the improvement in their self-rated health, and this positive effect differed according to sex, age and education level. The indirect path of encouraging rural middle-aged and elderly people to use smartphones, reducing the difficulty of smartphone use, and prolonging the duration of smartphone use for enhancing health-promoting behaviours could effectively improve their self-rated health. Smartphone use Health-promoting behaviours Self-rated health Rural middle-aged and elderly people Healthy ageing Background At present, demographic transformation in China is accelerating, with a very large elderly population that accounts for a very fast increasing proportion of the total population. It is predicted that in approximately 2035, China will officially become a severely ageing society and will remain so for a long period. We should avoid the series of "grey rhinoceros" risks, such as the risk of disease spread, the uneven distribution of old-age risks, and the risk of insufficient pension security for residents[ 1 , 2 ]. Healthy ageing is considered a means to address population ageing and is associated with the lowest cost and the greatest benefits[ 3 ]. The urban‒rural inversion phenomenon is a typical feature of the population ageing process in China. There are notable differences in the degree of rural ageing and the self-rated health status of elderly people between rural and urban areas, and this phenomenon is exacerbated over time[ 4 , 5 ]. Moreover, the development of the digital economy in China has rapidly progressed, and digital technology has penetrated all aspects of human production and life at an unprecedented speed. However, owing to contact barriers, knowledge ageing, and physical reasons, middle-aged and elderly people are at a disadvantage in terms of network access, digital equipment and the use of digital technologies. They are even aptly referred to as “digital immigrants” and “digital refugees”[ 6 ]. According to the 53rd Statistical Report on Internet Development in China released by the China Internet Network Information Centre, as of December 2023, the number of non-internet users in China reached 317 million individuals, with non-internet users in rural areas accounting for 51.8% of the total number. The elderly group accounted for 39.8% of the total sample, and the terms “rural” and “elderly” are still the two key labels for non-internet users in China[ 7 ]. Therefore, at the convergence of the digital wave and the ageing process, accounting for digital inclusion and the health status of middle-aged and elderly people in rural areas is highly practical. As the internet continues to penetrate middle-aged and elderly populations, more middle-aged and elderly people have begun to access and embrace digital life. Most existing studies emphasize the health dividends resulting from the use of digital technology for middle-aged and elderly people. For example, the use of the internet, smartphones, and mobile applications such as WeChat positively affects the promotion of the healthy lifestyle, the increase in proactive health consciousness, and the improvement in the health levels of middle-aged and elderly people[ 8 – 12 ], and relevant conclusions have also been obtained for middle-aged and elderly people in rural areas[ 13 – 16 ]. In addition, scholars have noted that moderate internet use positively affects healthy ageing and the subjective well-being of middle-aged and elderly people[ 17 ], but excessive and high-frequency use of smartphones and the internet is detrimental to the physical and mental health of elderly people[ 13 , 18 ], as it will make them psychologically dependent and lead to problems such as weakened social network, dysfunctional intergenerational relationships, and reduced sleep quality[ 13 , 19 , 20 ]. Furthermore, other scholars have examined the internal mechanisms of digital technology health empowerment and noted that the use of the internet by elderly people can increase the frequency of exercise and learning, improve social participation and social trust and facilitate their access to formal and informal social support structures. Therefore, their physical and mental health conditions can be improved[ 10 , 21 – 24 ]. In addition, Zhu et al. reported that internet use can improve the physical and mental health of rural residents by promoting their leisure and entertainment, social networking, and knowledge acquisition activities[ 14 ], but some studies have indicated that internet use significantly inhibits the frequency of physical activities among rural residents and that the inhibitory effect is greater for rural residents aged 40 and over than for other age groups[ 25 ]. However, through a literature review, most recent studies are based on comprehensive national survey data and focus on middle-aged and elderly people as a whole, although this research has involved evaluating the heterogeneity in the dichotomous structure between rural and urban areas. However, in general, mechanistic studies on the relationship between digital inclusion and the health of rural middle-aged and elderly people remain very rare, especially mechanistic studies involving the improvement in active health ability levels. National Health Commission of PRC issued the 14th Five-Year Plan for Healthy Aging, which clearly states that elderly individuals should be guided to adopt the goal of “maintaining body functions and the ability to live independently”, establish the awareness that “they are the first person responsible for health”, and promote the development of the health of elderly people. A healthy lifestyle is recommended to improve the health of elderly people[ 26 ]. In summary, this study focused on middle-aged and elderly people in rural areas, and national survey data for rural areas were used to empirically analyse the effects of smartphone use (including whether to use, difficulty of use and duration of use) on the self-rated health of middle-aged and elderly people as well as its heterogeneous performance in different individual characteristics. Therefore, we determined whether health-promoting behaviour exerts a mediating effect, and we examined the corresponding effects on improving the health status of middle-aged and elderly people and actively promoting healthy ageing in rural areas. This study aimed to narrow the health gap between urban and rural areas and provide relevant insights and suggestions for a methodical response to population ageing in China. Data and methods Data sources In this paper, China Rural Revitalization Survey data released by the Institute of Rural Development of the Chinese Academy of Social Sciences were used. The data were derived from the first phase (2020) of the China Rural Revitalization Survey (CRRS). The survey was conducted between August and September 2020. First, provinces were selected via the random sampling method. Second, sample counties, townships (towns) and villages were selected via the equidistant random sampling method on the basis of the per capita gross domestic (GDP). Finally, samples were selected from Guangdong, Zhejiang, Shandong, Anhui, and Henan Provinces, including survey data covering 50 counties (cities) and 156 townships (towns) across China, and more than 3800 farmer household questionnaires were obtained. In this study, on the basis of the research population, samples of middle-aged and elderly people aged 45 years and over were screened, and the individual characteristics of rural households, information use status, health status, and health behaviour were assessed on the basis of the research findings. Outliers and missing values were removed. Notably, middle-aged and elderly people in rural areas were effectively sampled, which yielded database 1 in this paper. Furthermore, the group of individuals who did not use smartphones was excluded to investigate the issues of the difficulty and duration of smartphone use, and a total of 2221 effective samples were obtained, which yielded database 2. Variable selection Dependent variable The self-rated health status was adopted as the dependent variable. Specifically, questions, such as “how is your health status compared with that of your peers? (20 − 5)”, were used to reflect the health status of middle-aged and elderly people in rural areas. This question was scored positively via the Likert five-point scoring method, where a value of 1 indicated “very poor”, and a value of 5 indicated “very good”. Afterwards, the options of the self-rated health part were combined to generate a new three-category dependent variable (i.e., “poor,” “fair” and “good”) for stability testing. Independent variable The use of smartphones was employed as the independent variable. This variable was analysed via questions related to the following three issues: (1) whether to use a smartphone (8 − 3: “do you use a 4G/5G mobile phone?”), where a value of 1 indicated that a 4G/5G mobile phone was used, and a value of 0 indicated the opposite; (2) difficulty of smartphone use (8 − 4: “do you have difficulty using the functions of 4G/5G mobile phones?”), which was treated as an ordinal variable, with values of 1–3 assigned, where a value of 1 indicated no difficulty, a value of 2 indicated some difficulty, and a value of 3 indicated great difficulty (i.e., phones were only used to make and receive calls). Notably, the latter two categories (2 and 3) were combined to indicate that it was “difficult to use smartphones”, which was assigned a value of 1, and the remaining cases were assigned a value of 0, thus generating a new binary variable of the difficulty of smartphone use for robustness testing. (3) The duration of smartphone use (8 − 5: “what is your average duration of 4G/5G mobile phone use per day?”) was treated as a continuous numerical variable, namely, the number of hours indicated by the respondent. Afterwards, the mean duration of smartphone use was calculated. A value higher than the mean was defined as a high usage duration, which was assigned a label of 1. A value lower than the mean was defined as a low usage duration, which was assigned a label of 0. Furthermore, as stability check was performed. Mediating variable Health-promoting behaviour was considered a mediating variable. Drawing on the study of Cao et al[ 27 ], this study focused on investigating the health-promoting behaviours of middle-aged and elderly people in rural areas from the three aspects of exercise, nutrition and health responsibility by asking the following questions: ① 20 − 10: “did you do more than 30 minutes of fitness or exercise activity in the last week”② 20 − 13: “do you consciously control your sugar intake?”; ③ 20 − 14: “do you consciously control your salt intake?”; ④ 20 − 15: “do you consciously control your edible oil intake?”; ⑤ 20 − 16: “do you consume health products in your daily life?”; ⑥ 13 − 8: “do you participate in pension insurance?”; ⑦ 20 − 11: “did you have a medical examination in the past year?”; ⑧ 20 − 9: “do you currently purchase health products or have commercial medical insurance?”; and ⑨ 20 − 12: “did you consciously study health or health preservation knowledge?”. The answers to the above questions were all regarded as binary variables, where a value of 0 indicated no and where a value of 1 indicated yes. The total score of the health-promoting behaviours of middle-aged and elderly people was calculated via summation. A higher score indicated greater individual health-promoting behaviour. Control variables In addition, in accordance with a previous study[ 28 ], to reduce the effect of systematic bias, six variables, namely, sex, age, education level, body mass index (BMI), ordinary villager status, and chronic diseases, were included as control variables. Notably, sex was treated as a binary variable, with 1 indicating male and 2 indicating female; ordinary villager status was treated as a dichotomous variable, with 1 indicating the status of an ordinary villager and 2 indicating other positions in the village (such as village party secretary, village director, village committee member, and group leader); the occurrence of chronic diseases was treated as a binary variable, with 1 indicating the occurrence of chronic diseases and 0 indicating the absence thereof; age was treated as a continuous numerical variable; and education level was treated as an ordinal variable, thereby assigning values of 1–3, where 1 indicated a primary school education and below, 2 indicated a junior high school education, and 3 indicated a high school education and above. The BMI was calculated by dividing the weight (in kilograms) by the square of the height (in metres). Notably, 18.5 ≤ BMI < 24 indicated a normal weight, which was assigned a value of 1. Values outside this range indicated an abnormal weight, which was assigned a value of 0. Data analysis SPSS 26.0 software was used for statistical analysis. First, a multivariate linear regression model was established to assess the effect of smartphone use on the self-rated health of middle-aged and elderly people in rural areas, and a stability test was performed of the baseline regression results. Previous studies have shown that smartphone use imposes differential effects on the health status of different groups of people[ 29 , 30 ]. Therefore, in this study, heterogeneity analysis was employed to determine whether there are sex, age and education level differences in the effect of smartphone use on self-rated health among middle-aged and elderly people in rural areas. Finally, a three-step regression method was adopted to examine the mediating effect of health-promoting behaviours on the relationship between smartphone use and self-rated health among middle-aged and elderly people, and the bootstrap test was used to analyse whether health-promoting behaviours imposed a mediating effect on the relationship between these two aspects, and to compare the relationship between the indirect effect and the direct effect and its magnitude. Results Descriptive statistics As indicated in Table 1 , the mean age of the 2876 middle-aged and elderly people included in this study was 58.82 ± 8.54 years, with 78.79% males and 21.21% females. In terms of education level, a primary school education and below and a junior high school education accounted for the majority, namely, 41.97% and 44.30%, respectively, whereas a high school education and above accounted for only 13.56% of the total results. According to the survey results, 42.94% of middle-aged and elderly people indicated that they suffered chronic diseases, and the BMI value of 50.42% of middle-aged and elderly people reached the normal level. The self-rated health of middle-aged and elderly people in rural areas was relatively good. A total of 37.97% of middle-aged and elderly people rated their health as “good,” while 16.55% and 29.66% of the considered individuals rated their health as “very good” and “fair,” respectively. Among the 2876 middle-aged and elderly people included in the analysis, 2221 individuals used smartphones, accounting for 77.23% of the total number, indicating that the considered middle-aged and elderly people exhibited a high smartphone usage rate. Among the 2221 people who used smartphones, 43.13% noted that they experienced no difficulty using smartphones, while 42.14% noted that they experienced some difficulty using smartphones. Moreover, the average duration of smartphone use was 2.44 ± 1.86 hours. The average score of the health-promoting behaviour parameter was 4.66 ± 2.14 points, which is slightly higher than the theoretical mean score of 4.5 points, indicating that the health-promoting behaviours of rural middle-aged and elderly people were moderate. Table 1 Descriptive statistics of the samples Variable Database 1 (N = 2876) Database 2 (N = 2221) Frequency/mean a Proportion/variance b Frequency/mean a Proportion/variance b Self-rated health Very poor 82 2.85% 63 2.84% Poor 373 12.97% 255 11.48% Average 853 29.66% 649 29.22% Good 1092 37.97% 874 39.35% Very good 476 16.55% 380 17.11% Smartphone use (yes = 1) 2221 77.23% Difficulty of smartphone use No difficulty 958 43.13% Some difficulty 936 42.14% It is very difficult, and the phone is only used for making and receiving calls 327 14.72% Smartphone use duration 2.44 a 1.86 b Health-promoting behaviour 4.66 a 2.14 b 4.75 a 2.18 b Whether they performed more than 30 minutes of fitness or exercise activities in the past week (yes = 1) 1679 58.40% 1360 38.77% Do they consciously control their sugar intake (yes = 1) 1740 60.50% 1367 61.55% Do they consciously control their salt intake (yes = 1) 1797 62.48% 1418 63.85% Do they consciously control their edible oil intake (yes = 1) 1712 59.53% 1353 60.92% Do they consume health products in their daily life (yes = 1) 403 14.01% 297 13.37% Whether they participate in pension insurance (yes = 1) 2451 85.22% 1910 86.00% Whether they had a medical examination in the last year (yes = 1) 1934 67.25% 1442 64.93% Do they have commercial medical insurance (yes = 1) 401 13.94% 355 15.98% Do they consciously study health or regimen knowledge (yes = 1) 1275 44.33% 1056 47.55% Sex (male = 1) 2266 78.79% 1733 78.03% Age 58.82 a 8.54 b 56.32 a 7.16 b Education level Primary school education and below 1207 41.97% 765 34.44% Junior high school education 1274 44.30% 1093 49.21% High school education and above 390 13.56% 363 16.34% Villager (yes = 1) 2293 79.73% 1686 75.91% BMI (normal = 1) 1450 50.42% 1067 48.04% Chronic diseases (yes = 1) 1235 42.94% 909 40.93% Note : a denotes the mean value; b denotes the variance . Baseline regression results As indicated in Table 2 , Models 1, 3 and 5 captured only the core independent variables, whereas Models 2, 4 and 6 are estimates of the complete regression model with control variables added. The results revealed that smartphone use and the duration of such use consistently and significantly positively promoted the self-rated health of rural middle-aged and elderly people, whereas the difficulty of smartphone use significantly and negatively affected the self-rated health of rural middle-aged and elderly people. In addition, the five control variables of age, education level, ordinary villager status, BMI and chronic diseases were significant in the three models. Age imposed a positive U-shaped effect on the self-rated health of rural middle-aged and elderly people. The self-rated health of rural middle-aged and elderly people with higher education levels, a nonordinary villager status, a normal BMI and no chronic diseases was better. Robustness test Table 3 lists the results of the stability test after replacing the dependent and independent variables. The results indicated that, first, after the dependent variables were replaced, the use of smartphones, the difficulty and duration of smartphone use still significantly affected the self-rated health of middle-aged and elderly people in rural areas. Second, after the independent variables were replaced, the difficulty and duration of smartphone use still significantly affected the self-rated health of middle-aged and elderly people in rural areas, validating the estimation results of the baseline model. Heterogeneity analysis Age heterogeneity analysis With reference to previous studies, the samples were divided into two groups: middle-aged individuals that are 46–59 years old and elderly individuals that are 60 years and older[ 31 ]. According to Table 4 , smartphone use positively affected the self-rated health of the middle-aged population, but the effect was not significant. Notably, smartphone use imposed a significant positive effect on the self-rated health of the elderly population. Moreover, the difficulty of using smartphones imposed a significant negative effect both on the self-rated health of middle-aged people and elderly people, indicating that reducing the difficulty of smartphone use could improve the self-rated health of middle-aged and elderly people in rural areas. In addition, a longer duration of smartphone use significantly improved the self-rated health in the middle-aged population, but the improvement was not significant in the elderly population. Sex heterogeneity analysis The samples were divided into two groups according to sex, namely, male and female, and a heterogeneity test was performed. According to Table 5 , smartphone use imposed a significant positive effect on the self-rated health of males, but the improvement effect on the self-rated health of females was not significant. Moreover, the difficulty of smartphone use significantly restricted the self-rated health of both males and females, whereas the duration of smartphone use significantly improved both the self-rated health of both groups. Education level heterogeneity analysis The education level was divided into three groups for further heterogeneity testing: elementary school education and below, junior high school education, and high school education and above. According to Table 6 , smartphone use imposed a positive and significant effect on the self-rated health of rural middle-aged and elderly people with a junior high school education and a high school education and above, but the improvement effect on the population with a primary school education and below was not significant. Moreover, the difficulty of smartphone use significantly inhibited the self-rated health of rural middle-aged and elderly people with primary school educations and below and junior high school educations, whereas the duration of smartphone use significantly improved the health of only rural middle-aged and elderly people with junior high school educations. Table 2 Baseline regression results Variable Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Smartphone use 0.176*** (0.045) 0.135** (0.051) Difficulty of smartphone use -0.242*** (0.029) -0.169*** (0.030) Smartphone use duration 0.130** (0.041) 0.032** (0.011) Sex -0.068 (0.043) -0.076 (0.048) -0.084* (0.048) Age -0.066** (0.027) -0.069* (0.038) -0.085** (0.038) Age squared 0.001** (0.000) 0.001** (0.000) 0.001** (0.000) Education level 0.074** (0.027) 0.069** (0.030) 0.095** (0.029) Ordinary villager 0.200*** (0.045) 0.177*** (0.046) 0.181*** (0.047) BMI 0.138*** (0.035) 0.164*** (0.039) 0.173*** (0.039) Chronic diseases -0.748*** (0.036) -0.731*** (0.040) -0.758*** (0.040) N 2876 2876 2221 2221 2221 2221 F value 15.639 64.378 67.052 56.649 10.073 54.082 Adjusted R 2 0.005 0.150 0.029 0.168 0.004 0.161 Note: *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively, and the standard errors are listed in parentheses. Table 3 Results of robustness test Variable Self-rated health (three categories) Self-rated health (five categories) Smartphone use 0.123** (0.038) Difficulty of smartphone use -0.123*** (0.022) Smartphone use duration 0.020** (0.008) Difficulty of smartphone use (binary classification) 0.262*** (0.042) Smartphone use duration (binary classification) 0.088** (0.040) Control variables Control Control Control Control Control N 2876 2221 2221 2221 2221 F value 62.694 53.316 50.400 57.747 53.475 Adjusted R 2 0.147 0.159 0.151 0.171 0.159 Note: *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively, and the standard errors are provided in parentheses. Table 4 Results of age heterogeneity analysis Variable Middle-aged people Elderly people Middle-aged people Elderly people Middle-aged people Elderly people Smartphone use 0.097 (0.097) 0.113* (0.058) Difficulty of smartphone use -0.163*** (0.036) -0.160** (0.050) Smartphone use duration 0.031** (0.012) 0.034 (0.022) Control variables Control Control Control Control Control Control N 1672 1204 1572 649 1572 649 F value 53.505 31.367 55.862 19.429 53.059 19.014 Adjusted R 2 0.159 0.132 0.174 0.148 0.166 0.143 Note: *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively, and the standard errors are provided in parentheses. Table 5 Results of sex heterogeneity analysis Variable Male Female Male Female Male Female Smartphone use 0.164** (0.056) 0.013 (0.123) Difficulty of smartphone use -0.133*** (0.033) -0.292*** (0.069) Smartphone use duration 0.022* (0.012) 0.068** (0.025) Control variables Control Control Control Control Control Control N 2266 610 1733 488 1733 488 F value 56.601 16.425 45.901 18.242 44.830 16.358 Adjusted R 2 0.147 0.151 0.54 0.199 0.151 0.181 Note: *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively, and the standard errors are listed in parentheses. Table 6 Results of education level heterogeneity analysis Variable Primary school education and below Junior high school education High school education and above Primary school education and below Junior high school education High school education and above Primary school education and below Junior high school education High school education and above Smartphone use 0.060 (0.070) 0.189** (0.085) 0.692*** (0.191) Difficulty of smartphone use -0.113** (0.051) -0.230*** (0.043) -0.119 (0.073) Smartphone use duration 0.024 (0.021) 0.038** (0.015) 0.030 (0.022) Control variables Control Control Control Control Control Control Control Control Control N 1207 1274 390 763 1091 363 763 1091 363 F value 30.969 30.045 11.231 24.542 29.964 7.709 24.228 26.578 7.945 Adjusted R 2 0.148 0.138 0.155 0.178 0.157 0.116 0.176 0.141 0.118 Note: *, ** and *** indicate significance at the 10%, 5% and 1% levels, respectively; standard errors are provided in parentheses. Mechanism analysis We draw on the basic idea of Baron[ 32 ] on mediating effect analysis, the three-step regression method was used to analyse the mechanism of the effect of smartphone use on the self-rated health of rural middle-aged and elderly people. Regression was performed using health-promoting behaviour and self-rated health as the dependent variables and smartphone use, difficulty of use, and duration of use as the independent variables. According to Table 7 , smartphone use among rural middle-aged and elderly people significantly and positively affected their health-promoting behaviour ( β = 0.390, P < 0.05) and self-rated health ( β = 0.135, P < 0.05); the difficulty of using smartphones among rural middle-aged and elderly people significantly and negatively affected their health-promoting behaviour ( β = -0.377, P < 0.001) and self-rated health ( β = -0.169, P < 0.001); and the duration of smartphone use among rural middle-aged and elderly people significantly and positively affected their health-promoting behaviour ( β = 0.089, P < 0.001) and self-rated health ( β = 0.032, P < 0.05). The study results revealed that rural middle-aged and elderly people who use smartphones exhibit less difficulty using smartphones and longer use times are associated with greater health-promoting behaviours and higher self-rated health levels. Moreover, self-rated health was used as a dependent variable to regress smartphone use, difficulty of use, and duration of use and health-promoting behaviour in the same model, and it was determined that health-promoting behaviour imposed a significant positive effect on the self-rated health ( β = 0.025, P < 0.05; β = 0.021, P < 0.05; β = 0.024, P < 0.05). In summary, the mediating effect test of health-promoting behaviour was passed, namely, the health-promoting behaviour play a mediating role in the relationship between smartphone use, difficulty of use, and duration of use affecting self-rated health among rural middle-aged and elderly people. A bootstrap test was conducted. The number of repeated samples was set to 5000, and the confidence interval was set to 95% to verify the mediating effect of health-promoting behaviour. According to Table 8 , first, the direct effect of smartphone use on the self-rated health of middle-aged and elderly people in rural areas was 0.011, while the indirect effect of health-promoting behaviour was 0.125. Notably, the results were statistically significant, with the indirect effect accounting for 91.91% of the overall variance. Second, the direct effect of the difficulty of smartphone use on the self-rated health of middle-aged and elderly people in rural areas was − 0.008, while the indirect effect of health-promoting behaviour was − 0.161. The results were statistically significant, and the indirect effect accounted for 95.27% of the total variance. Finally, the direct effect of smartphone use time on the self-rated health of middle-aged and elderly people in rural areas was 0.003, while the indirect effect of health-promoting behaviour was 0.030. The obtained results were statistically significant, and the indirect effect accounted for 90.9% of the total variance. Table 7 Estimates of the mediating effect of health-promoting behaviour Variable Health-promoting behaviour Self-rated health (1) (2) (3) (4) (5) (6) (7) (8) (9) Smartphone use 0.390** (0.113) 0.135** (0.051) 0.125* (0.051) Difficulty of smartphone use -0.377*** (0.068) -0.169*** (0.030) -0.161*** (0.030) Smartphone use duration 0.089*** (0.025) 0.032** (0.011) 0.030** (0.011) Health-promoting behaviour 0.025** (0.008) 0.021** (0.009) 0.024** (0.009) Control variables Control Control Control Control Control Control Control Control Control N 2876 2221 2221 2876 2221 2221 2876 2221 2221 F value 28.519 25.654 23.499 64.378 56.649 54.082 58.399 51.009 48.973 Adjusted R 2 0.071 0.082 0.075 0.150 0.168 0.161 0.153 0.169 0.163 Note: *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively. Table 8 Results of bootstrap test Independent variable Effect Path relationship β SE Lower limit Upper limit Effect size Smartphone use Direct effect Smartphone use → self-rated health 0.011** 0.004 0.004 0.021 8.09% Indirect effect Smartphone use → health-promoting behaviour → self-rated health 0.125** 0.052 0.026 0.227 91.91% Total effect 0.136** 0.051 0.038 0.237 100.00% Difficulty of smartphone use Direct effect Difficulty of smartphone use → self-rated health -0.008** 0.004 -0.017 -0.002 4.73% Indirect effect Difficulty of smartphone use → health-promoting behaviour → self-rated health -0.161*** 0.030 -0.221 -0.102 95.27% Total effect -0.169*** 0.030 -0.230 -0.111 100.00% Smartphone use duration Direct effect Duration of smartphone use → self-rated health 0.003** 0.001 0.001 0.006 9.09% Indirect effect Duration of smartphone use → health-promoting behaviour → self-rated health 0.030** 0.011 0.010 0.050 90.91% Total effect 0.033** 0.011 0.013 0.053 100% Note: *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively Discussion Smartphone use among rural middle-aged and elderly people directly reinforces health-promoting behaviour In this study, it was revealed that smartphone use among rural middle-aged and elderly people could directly reinforce health-promoting behaviour. Health-promoting behaviour requires individuals to exert subjective initiative, in which knowledge plays an important role[ 33 ]. With the rapid development of digital technology, many types of health information are presented in electronic form, and the internet has become an important source of health information for people[ 34 ]. Numerous previous studies have shown that smartphones provide channels for middle-aged and elderly people to obtain information and education, and that middle-aged and elderly people can use smartphones to obtain online health information and learn ways and methods to search for and acquire health knowledge, which will be conducive to the accumulation of their health knowledge [ 11 , 35 , 36 ], and that knowledge is one of the important prerequisites for behaviour change, which in turn can guide middle-aged and elderly people to adopt healthier behaviours[ 37 ]. Xavier et al analysed data from 5,900 older people in the English Longitudinal Study of Ageing and found that internet use was associated with weekly moderate to vigorous exercise, more frequent daily consumption of fruit and vegetables and less smoking[ 38 ]. In addition, relevant studies on rural groups have indicated that rural residents who often use smartphones are more inclined to adopt digital tools for health promotion, consider diverse sources of digital health information and explore various digital health-promoting behaviours, such as searching for health information and health status management and tracking improving, to enhance their health levels[ 39 ]. Smartphone use among rural middle-aged and elderly people directly affects their self-rated health The relevant results showed that smartphone use among rural middle-aged and elderly people could directly improve their self-rated health. Similarly, previous studies have shown that smartphone use can effectively sustain the social connections of middle-aged and elderly people with other groups, expand their social networks, and reduce social alienation[ 40 – 42 ], thereby positively affecting their health[ 43 – 45 ]. In addition, Liu and Guo reported that the use of mobile internet applications, including WeChat, WeChat Moments and mobile payments, can effectively promote physical and mental health[ 46 ]. Studies have also demonstrated that middle-aged and elderly people can use smartphones to search for and browse a variety of online health information, obtain medical information, communicate with health care professionals, and perform other health-related tasks, thus positively affecting their health[ 12 , 46 – 48 ]. For the rural population, numerous empirical studies have revealed that internet use can significantly improve the self-rated health level of middle-aged and elderly people in rural areas[ 49 , 50 ] and that the health of Chinese elderly people is affected mainly through social support[ 51 , 52 ]. Moreover, some studies have indicated that watching short videos can positively influence the acquisition of online health information by rural elderly people. As mentioned previously, online health information is an important prefactor influencing the health status[ 53 ]. The effect of smartphone use on the self-rated health varies among rural middle-aged and elderly people of different sexes, ages and education levels Through heterogeneity analysis, we found that sex, age and education level differences exist in the effects of smartphone use on the self-rated health of middle-aged and elderly people in rural areas, which is similar to the conclusions of existing studies[ 8 , 24 , 29 , 50 ]. In terms of gender differences, the effect of smartphone use on the self-rated health of rural elderly males was greater than that on rural elderly females. There is significant gender inequality in rural education opportunities, namely, rural women are at a disadvantage in obtaining educational opportunities, whereas rural men are more likely to obtain better educational opportunities and reach higher educational levels[ 54 ]. In addition, under the influence of traditional cultural thinking, the traditional family division of labour model, in which “males dominate the workplace and females dominate the home,” is still common[ 55 ]. Given the need to maintain social networks, middle-aged and elderly men use smartphones more frequently. Therefore, men face fewer barriers to using smartphones, exhibit greater proficiency in using smartphones, and demonstrate better judgement and differentiation ability in the face of good and bad health information online. From an age perspective, smartphone use exerted a greater promoting effect on the self-rated health of the 46–59-year-old group of middle-aged individuals. Middle-aged people are more accepting of new things and have fewer learning disabilities and technical barriers when using smartphones. Therefore, they use them more frequently to obtain all types of information and to maintain social contacts. However, for elderly people aged 60 years and older, there are certain difficulties in learning how to use smartphones, and they feel rejection and fear in the face of digital technology; therefore, these individuals are more likely to give up trying to integrate into digital life[ 56 ]. Their use of smartphones is more focussed on the basic functions of voice calling and maintaining necessary contact with the outside world[ 57 ], which brings very limited health effects. In addition, the positive effect of smartphone use on the self-rated health of middle-aged and elderly people with higher levels of education was more significant. A previous study revealed that middle-aged and elderly people with higher education levels can more easily cross the digital divide and integrate into the digital age[ 58 ], which is verified in this study. Middle-aged and elderly people with higher education levels possess relatively more abundant social resources and are more likely to fully utilize smartphones for social maintenance and access to health resources, thereby more likely improving their self-rated health. Mediating effect of health-promoting behaviour on the relationship between smartphone use and the self-rated health of rural middle-aged and elderly people It was also revealed that the health-promoting behaviour of rural middle-aged and elderly people exerted an important mediating effect on the relationship between smartphone use and self-rated health, which is similar to the results of previous studies[ 30 , 36 , 59 – 62 ]. This mediating effect can be explained by Andersen's Behavioural Model of Health Services Use[ 63 ]. This model emphasizes that personal propensity characteristics are correlated with health outcomes. Personal propensity characteristics can directly or indirectly affect health outcomes by influencing health behaviour[ 64 ]. In this study, smartphone use can be considered an individual tendency feature. According to this model, middle-aged and elderly people who use smartphones are more likely to actively acquire effective online health resources and online health knowledge through online media, thereby increasing their health management awareness, adopting sound health management behaviours, and improving their health-promoting behaviour, thus enhancing their self-rated health. Using data from a national comprehensive survey in China, Zhou et al. found that Internet use among older adults was positively associated with self-rated health and negatively associated with psychological sub-health, and that Internet use promotes health in older adults by facilitating access to health information, healthy lifestyles, and enhanced social interaction[ 30 ]. Similarly, Guo et al. reported that internet use among elderly people can increase the frequency of physical exercise, thereby improving their physical health[ 60 ]. In addition, numerous rural population-based studies have shown that healthy living habits and behaviours are the key factors for preventing and treating diseases and protecting health; moreover, the lifespan can be increased, and the risk of death can be reduced by shaping healthy lifestyles, such as favouring vegetables, physical activity, reading, etc.[ 65 , 66 ]. Policy implications Against the background of the convergence of digitalization and the ageing process, in this study, the relationships among smartphone use, health-promoting behaviour, and self-rated health of rural middle-aged and elderly people were analysed. The relevant conclusions have important policy implications for improving the health of rural middle-aged and elderly people and actively promoting healthy ageing in rural areas. First, the construction of mobile networks in rural areas should be strengthened, and a suitable digital access environment should be created for elderly individuals. Compared with that in urban areas, mobile network infrastructure in rural areas is relatively underdeveloped, and the popularity of smartphones among middle-aged and elderly people in rural areas should be improved. It is recommended that the government implement a digital countryside construction strategy, increase infrastructure construction of rural mobile networks, create a favourable digital access environment for the use of smartphones by middle-aged and elderly people in rural areas, drive them to better integrate into digital life, and mitigate the deterioration of the health status of middle-aged and elderly people caused by the digital divide. Second, smartphone education for middle-aged and elderly people in rural areas should be strengthened to establish an age-friendly digital society. Owing to the flat information characteristics of the digital age, smartphone use and internet access could compensate for the lack of health information acquisition abilities among middle-aged and elderly people in rural areas. To this end, the provision of internet education to rural middle-aged and elderly individuals should be strengthened to cultivate their basic digital abilities, such as network connections, information searches, and digital communications, so that they can use smartphones to obtain and understand more comprehensive health information and thus improve their health status and promote the development of healthy ageing in rural areas. Third, we should focus on group differences and revealed the differentiated uses of smartphones by middle-aged and elderly individuals. While the smartphone penetration rate among middle-aged and elderly people in rural areas has steadily increased, a “targeted support” policy is recommended to provide differentiated digital resource services, with a focus on precise help for rural women, elderly people above a certain age, and disadvantaged middle-aged and elderly groups with low education levels. In addition, in the process of ageing-appropriate construction, internet-related companies are encouraged to customize the research and development of smartphone-related functions on the basis of sex, age, and education level of middle-aged and elderly people to create differentiated ageing-appropriate products to meet their smartphone needs. Limitations Although this paper provides a certain theoretical basis for the investigation of relevant variables, due to data limitations, only cross-sectional data from the 2020 CRRS were analysed. There is a lack of longitudinal observation data, and the time-varying pattern of the influence mechanism of smartphone use cannot be comprehensively captured. The second phase of the CRRS survey was completed in 2022. After the release of relevant data, the existing database can be expanded to form a panel dataset, which can improve the study of relevant mechanisms. Second, this study focused only on the self-rated health of middle-aged and elderly people. Currently, the understanding of healthy ageing is continuously increasing. Thais et al. proposed that healthy ageing includes physical health as well as other aspects, such as physical function, cognitive ability, and mental health dimensions[ 67 ]. Therefore, future measurements of health can be expanded, and studies can be performed in greater depth to enrich the research results related to healthy ageing. Abbreviations CRRS：China Rural Revitalization Survey Declarations Acknowledgments We are very grateful the Rural Development Institute Chinese Academy of Social Sciences for the approval to use the 2022 CRRS data. We also thank the anonymous reviewers for their valuable comments. Authors’ contributions Theme: X.G and X.L. Methodology: X.G and X.L. Software: X.G and J.W. Data Curation: X.G and X.L. Original draft: X.G. Review and editing: X.G and J.W. Supervision and funding acquisition: J.W. All authors have read and agreed to the published version of the manuscript. Funding This work was funded by the Ministry of Education Humanities and Social Sciences Youth Project (Grant number 22YJCZH188) and Anhui Provincial Colleges and Universities Outstanding Youth Scientific Research Project (Grant number 2023AH030062) Availability of data and materials The data presented in this study are publicly available via the China Rural Revitalization Survey (CRRS) database. Access data online via http://rdi.cass.cn/ggl/202210/t20221024_5551642.shtml. Further queries can be directed to the authors. Ethics approval and consent to participate All experimental protocols of this study were approved by the Ethics Committee of Anhui Medical University and all methods were conducted according to the guidelines of the Declaration of Helsinki and relevant Chinese laws and regulations. This study confirms that informed consent was obtained from all participants and/or their legal guardians. Written informed consent was obtained from all participants before administering any study procedures. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. References Lu J, Lin J. Demographic Characteristics, Risk Identification and Strategic Responses in Heavily Aging Society. Studies on Socialism with Chinese Characteristics. 2023;59–68. Luo Y, Su B, Zheng X. 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Abud T, Kounidas G, Martin KR, Werth M, Cooper K, Myint PK. Determinants of healthy ageing: a systematic review of contemporary literature. Aging Clin Exp Res. 2022;34:1215–23. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4953641","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":353716022,"identity":"ce236284-7373-4bbd-b9de-4d5864b035ea","order_by":0,"name":"Xiaomin Gan","email":"","orcid":"","institution":"Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaomin","middleName":"","lastName":"Gan","suffix":""},{"id":353716023,"identity":"79a186ac-6c39-48c9-ae03-e728278a90b2","order_by":1,"name":"Xuefang Liu","email":"","orcid":"","institution":"Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xuefang","middleName":"","lastName":"Liu","suffix":""},{"id":353716024,"identity":"90f9192b-7257-4623-b3bc-68f1ae89d014","order_by":2,"name":"Juan Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYBACfmbGxsc/DCR4+BkOH2CGiCXg1yLZ3nzYmKHCRk6y8VgCcVoMzhxLk2Y4k2ZscPiMAXFaGG7kGBsXth1ObDh25uPnwpzDDPzsOQYMP3fg1sE4I8fw8Uyglsaes5ulZ247zCDZ88aAsfcMbi3MEjnGBrxALc0SZzdI8wK1GNzIMWBmbMOthU0ix0wCpKVN/s3j3yAt9oS08PAAvc8D9D4Pwxk2iC0SBLRIsDcfNpwBDGQJhmNm1rzb0nkkzjwrONiLR4v9YcbGBx+AUWl/4PDj27zbrOX425M3PviJRwumS0HEARI0jIJRMApGwSjAAgAGdFdip/HCIAAAAABJRU5ErkJggg==","orcid":"","institution":"Anhui Medical University","correspondingAuthor":true,"prefix":"","firstName":"Juan","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2024-08-21 19:25:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4953641/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4953641/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105739340,"identity":"9373f002-a01d-41fc-92f4-4955b73848a9","added_by":"auto","created_at":"2026-03-30 12:43:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2558641,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4953641/v1/0d2825d5-5bb1-41be-98e5-d25eecf060bb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Smartphone use, health-promoting behaviours and self-rated health among middle-aged and elderly people in rural areas","fulltext":[{"header":"Background","content":"\u003cp\u003eAt present, demographic transformation in China is accelerating, with a very large elderly population that accounts for a very fast increasing proportion of the total population. It is predicted that in approximately 2035, China will officially become a severely ageing society and will remain so for a long period. We should avoid the series of \"grey rhinoceros\" risks, such as the risk of disease spread, the uneven distribution of old-age risks, and the risk of insufficient pension security for residents[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Healthy ageing is considered a means to address population ageing and is associated with the lowest cost and the greatest benefits[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe urban‒rural inversion phenomenon is a typical feature of the population ageing process in China. There are notable differences in the degree of rural ageing and the self-rated health status of elderly people between rural and urban areas, and this phenomenon is exacerbated over time[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Moreover, the development of the digital economy in China has rapidly progressed, and digital technology has penetrated all aspects of human production and life at an unprecedented speed. However, owing to contact barriers, knowledge ageing, and physical reasons, middle-aged and elderly people are at a disadvantage in terms of network access, digital equipment and the use of digital technologies. They are even aptly referred to as \u0026ldquo;digital immigrants\u0026rdquo; and \u0026ldquo;digital refugees\u0026rdquo;[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. According to the 53rd Statistical Report on Internet Development in China released by the China Internet Network Information Centre, as of December 2023, the number of non-internet users in China reached 317\u0026nbsp;million individuals, with non-internet users in rural areas accounting for 51.8% of the total number. The elderly group accounted for 39.8% of the total sample, and the terms \u0026ldquo;rural\u0026rdquo; and \u0026ldquo;elderly\u0026rdquo; are still the two key labels for non-internet users in China[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, at the convergence of the digital wave and the ageing process, accounting for digital inclusion and the health status of middle-aged and elderly people in rural areas is highly practical.\u003c/p\u003e \u003cp\u003eAs the internet continues to penetrate middle-aged and elderly populations, more middle-aged and elderly people have begun to access and embrace digital life. Most existing studies emphasize the health dividends resulting from the use of digital technology for middle-aged and elderly people. For example, the use of the internet, smartphones, and mobile applications such as WeChat positively affects the promotion of the healthy lifestyle, the increase in proactive health consciousness, and the improvement in the health levels of middle-aged and elderly people[\u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and relevant conclusions have also been obtained for middle-aged and elderly people in rural areas[\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In addition, scholars have noted that moderate internet use positively affects healthy ageing and the subjective well-being of middle-aged and elderly people[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], but excessive and high-frequency use of smartphones and the internet is detrimental to the physical and mental health of elderly people[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], as it will make them psychologically dependent and lead to problems such as weakened social network, dysfunctional intergenerational relationships, and reduced sleep quality[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Furthermore, other scholars have examined the internal mechanisms of digital technology health empowerment and noted that the use of the internet by elderly people can increase the frequency of exercise and learning, improve social participation and social trust and facilitate their access to formal and informal social support structures. Therefore, their physical and mental health conditions can be improved[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In addition, Zhu et al. reported that internet use can improve the physical and mental health of rural residents by promoting their leisure and entertainment, social networking, and knowledge acquisition activities[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], but some studies have indicated that internet use significantly inhibits the frequency of physical activities among rural residents and that the inhibitory effect is greater for rural residents aged 40 and over than for other age groups[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, through a literature review, most recent studies are based on comprehensive national survey data and focus on middle-aged and elderly people as a whole, although this research has involved evaluating the heterogeneity in the dichotomous structure between rural and urban areas. However, in general, mechanistic studies on the relationship between digital inclusion and the health of rural middle-aged and elderly people remain very rare, especially mechanistic studies involving the improvement in active health ability levels. National Health Commission of PRC issued the 14th Five-Year Plan for Healthy Aging, which clearly states that elderly individuals should be guided to adopt the goal of \u0026ldquo;maintaining body functions and the ability to live independently\u0026rdquo;, establish the awareness that \u0026ldquo;they are the first person responsible for health\u0026rdquo;, and promote the development of the health of elderly people. A healthy lifestyle is recommended to improve the health of elderly people[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn summary, this study focused on middle-aged and elderly people in rural areas, and national survey data for rural areas were used to empirically analyse the effects of smartphone use (including whether to use, difficulty of use and duration of use) on the self-rated health of middle-aged and elderly people as well as its heterogeneous performance in different individual characteristics. Therefore, we determined whether health-promoting behaviour exerts a mediating effect, and we examined the corresponding effects on improving the health status of middle-aged and elderly people and actively promoting healthy ageing in rural areas. This study aimed to narrow the health gap between urban and rural areas and provide relevant insights and suggestions for a methodical response to population ageing in China.\u003c/p\u003e"},{"header":"Data and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData sources\u003c/h2\u003e \u003cp\u003eIn this paper, China Rural Revitalization Survey data released by the Institute of Rural Development of the Chinese Academy of Social Sciences were used. The data were derived from the first phase (2020) of the China Rural Revitalization Survey (CRRS). The survey was conducted between August and September 2020. First, provinces were selected via the random sampling method. Second, sample counties, townships (towns) and villages were selected via the equidistant random sampling method on the basis of the per capita gross domestic (GDP). Finally, samples were selected from Guangdong, Zhejiang, Shandong, Anhui, and Henan Provinces, including survey data covering 50 counties (cities) and 156 townships (towns) across China, and more than 3800 farmer household questionnaires were obtained. In this study, on the basis of the research population, samples of middle-aged and elderly people aged 45 years and over were screened, and the individual characteristics of rural households, information use status, health status, and health behaviour were assessed on the basis of the research findings. Outliers and missing values were removed. Notably, middle-aged and elderly people in rural areas were effectively sampled, which yielded database 1 in this paper. Furthermore, the group of individuals who did not use smartphones was excluded to investigate the issues of the difficulty and duration of smartphone use, and a total of 2221 effective samples were obtained, which yielded database 2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eVariable selection\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eDependent variable\u003c/h2\u003e \u003cp\u003eThe self-rated health status was adopted as the dependent variable. Specifically, questions, such as \u0026ldquo;how is your health status compared with that of your peers? (20\u0026thinsp;\u0026minus;\u0026thinsp;5)\u0026rdquo;, were used to reflect the health status of middle-aged and elderly people in rural areas. This question was scored positively via the Likert five-point scoring method, where a value of 1 indicated \u0026ldquo;very poor\u0026rdquo;, and a value of 5 indicated \u0026ldquo;very good\u0026rdquo;. Afterwards, the options of the self-rated health part were combined to generate a new three-category dependent variable (i.e., \u0026ldquo;poor,\u0026rdquo; \u0026ldquo;fair\u0026rdquo; and \u0026ldquo;good\u0026rdquo;) for stability testing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eIndependent variable\u003c/h2\u003e \u003cp\u003eThe use of smartphones was employed as the independent variable. This variable was analysed via questions related to the following three issues: (1) whether to use a smartphone (8\u0026thinsp;\u0026minus;\u0026thinsp;3: \u0026ldquo;do you use a 4G/5G mobile phone?\u0026rdquo;), where a value of 1 indicated that a 4G/5G mobile phone was used, and a value of 0 indicated the opposite; (2) difficulty of smartphone use (8\u0026thinsp;\u0026minus;\u0026thinsp;4: \u0026ldquo;do you have difficulty using the functions of 4G/5G mobile phones?\u0026rdquo;), which was treated as an ordinal variable, with values of 1\u0026ndash;3 assigned, where a value of 1 indicated no difficulty, a value of 2 indicated some difficulty, and a value of 3 indicated great difficulty (i.e., phones were only used to make and receive calls). Notably, the latter two categories (2 and 3) were combined to indicate that it was \u0026ldquo;difficult to use smartphones\u0026rdquo;, which was assigned a value of 1, and the remaining cases were assigned a value of 0, thus generating a new binary variable of the difficulty of smartphone use for robustness testing. (3) The duration of smartphone use (8\u0026thinsp;\u0026minus;\u0026thinsp;5: \u0026ldquo;what is your average duration of 4G/5G mobile phone use per day?\u0026rdquo;) was treated as a continuous numerical variable, namely, the number of hours indicated by the respondent. Afterwards, the mean duration of smartphone use was calculated. A value higher than the mean was defined as a high usage duration, which was assigned a label of 1. A value lower than the mean was defined as a low usage duration, which was assigned a label of 0. Furthermore, as stability check was performed.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMediating variable\u003c/h2\u003e \u003cp\u003eHealth-promoting behaviour was considered a mediating variable. Drawing on the study of Cao et al[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], this study focused on investigating the health-promoting behaviours of middle-aged and elderly people in rural areas from the three aspects of exercise, nutrition and health responsibility by asking the following questions: ① 20\u0026thinsp;\u0026minus;\u0026thinsp;10: \u0026ldquo;did you do more than 30 minutes of fitness or exercise activity in the last week\u0026rdquo;② 20\u0026thinsp;\u0026minus;\u0026thinsp;13: \u0026ldquo;do you consciously control your sugar intake?\u0026rdquo;; ③ 20\u0026thinsp;\u0026minus;\u0026thinsp;14: \u0026ldquo;do you consciously control your salt intake?\u0026rdquo;; ④ 20\u0026thinsp;\u0026minus;\u0026thinsp;15: \u0026ldquo;do you consciously control your edible oil intake?\u0026rdquo;; ⑤ 20\u0026thinsp;\u0026minus;\u0026thinsp;16: \u0026ldquo;do you consume health products in your daily life?\u0026rdquo;; ⑥ 13\u0026thinsp;\u0026minus;\u0026thinsp;8: \u0026ldquo;do you participate in pension insurance?\u0026rdquo;; ⑦ 20\u0026thinsp;\u0026minus;\u0026thinsp;11: \u0026ldquo;did you have a medical examination in the past year?\u0026rdquo;; ⑧ 20\u0026thinsp;\u0026minus;\u0026thinsp;9: \u0026ldquo;do you currently purchase health products or have commercial medical insurance?\u0026rdquo;; and ⑨ 20\u0026thinsp;\u0026minus;\u0026thinsp;12: \u0026ldquo;did you consciously study health or health preservation knowledge?\u0026rdquo;. The answers to the above questions were all regarded as binary variables, where a value of 0 indicated no and where a value of 1 indicated yes. The total score of the health-promoting behaviours of middle-aged and elderly people was calculated via summation. A higher score indicated greater individual health-promoting behaviour.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eControl variables\u003c/h2\u003e \u003cp\u003eIn addition, in accordance with a previous study[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], to reduce the effect of systematic bias, six variables, namely, sex, age, education level, body mass index (BMI), ordinary villager status, and chronic diseases, were included as control variables. Notably, sex was treated as a binary variable, with 1 indicating male and 2 indicating female; ordinary villager status was treated as a dichotomous variable, with 1 indicating the status of an ordinary villager and 2 indicating other positions in the village (such as village party secretary, village director, village committee member, and group leader); the occurrence of chronic diseases was treated as a binary variable, with 1 indicating the occurrence of chronic diseases and 0 indicating the absence thereof; age was treated as a continuous numerical variable; and education level was treated as an ordinal variable, thereby assigning values of 1\u0026ndash;3, where 1 indicated a primary school education and below, 2 indicated a junior high school education, and 3 indicated a high school education and above. The BMI was calculated by dividing the weight (in kilograms) by the square of the height (in metres). Notably, 18.5\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;24 indicated a normal weight, which was assigned a value of 1. Values outside this range indicated an abnormal weight, which was assigned a value of 0.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eSPSS 26.0 software was used for statistical analysis. First, a multivariate linear regression model was established to assess the effect of smartphone use on the self-rated health of middle-aged and elderly people in rural areas, and a stability test was performed of the baseline regression results. Previous studies have shown that smartphone use imposes differential effects on the health status of different groups of people[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Therefore, in this study, heterogeneity analysis was employed to determine whether there are sex, age and education level differences in the effect of smartphone use on self-rated health among middle-aged and elderly people in rural areas. Finally, a three-step regression method was adopted to examine the mediating effect of health-promoting behaviours on the relationship between smartphone use and self-rated health among middle-aged and elderly people, and the bootstrap test was used to analyse whether health-promoting behaviours imposed a mediating effect on the relationship between these two aspects, and to compare the relationship between the indirect effect and the direct effect and its magnitude.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDescriptive statistics\u003c/h2\u003e \u003cp\u003eAs indicated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the mean age of the 2876 middle-aged and elderly people included in this study was 58.82\u0026thinsp;\u0026plusmn;\u0026thinsp;8.54 years, with 78.79% males and 21.21% females. In terms of education level, a primary school education and below and a junior high school education accounted for the majority, namely, 41.97% and 44.30%, respectively, whereas a high school education and above accounted for only 13.56% of the total results. According to the survey results, 42.94% of middle-aged and elderly people indicated that they suffered chronic diseases, and the BMI value of 50.42% of middle-aged and elderly people reached the normal level. The self-rated health of middle-aged and elderly people in rural areas was relatively good. A total of 37.97% of middle-aged and elderly people rated their health as \u0026ldquo;good,\u0026rdquo; while 16.55% and 29.66% of the considered individuals rated their health as \u0026ldquo;very good\u0026rdquo; and \u0026ldquo;fair,\u0026rdquo; respectively.\u003c/p\u003e \u003cp\u003eAmong the 2876 middle-aged and elderly people included in the analysis, 2221 individuals used smartphones, accounting for 77.23% of the total number, indicating that the considered middle-aged and elderly people exhibited a high smartphone usage rate. Among the 2221 people who used smartphones, 43.13% noted that they experienced no difficulty using smartphones, while 42.14% noted that they experienced some difficulty using smartphones. Moreover, the average duration of smartphone use was 2.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86 hours. The average score of the health-promoting behaviour parameter was 4.66\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14 points, which is slightly higher than the theoretical mean score of 4.5 points, indicating that the health-promoting behaviours of rural middle-aged and elderly people were moderate.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of the samples\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eDatabase 1 (N\u0026thinsp;=\u0026thinsp;2876)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eDatabase 2\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;2221)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFrequency/mean\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eProportion/variance\u003c/b\u003e \u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eFrequency/mean\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eProportion/variance\u003c/b\u003e \u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSelf-rated health\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery poor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.85%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.84%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.97%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.48%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.66%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.22%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.97%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39.35%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.11%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use\u003c/b\u003e (yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.23%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty of smartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo difficulty\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43.13%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome difficulty\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42.14%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIt is very difficult, and the phone is only used for making and receiving calls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.72%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.44\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.86\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth-promoting behaviour\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.66\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.14\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.75\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.18\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhether they performed more than 30 minutes of fitness or exercise activities in the past week (yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.77%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo they consciously control their sugar intake (yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61.55%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo they consciously control their salt intake (yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63.85%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo they consciously control their edible oil intake (yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.53%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.92%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo they consume health products in their daily life (yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.01%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.37%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhether they participate in pension insurance (yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e86.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhether they had a medical examination in the last year (yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64.93%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo they have commercial medical insurance (yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.94%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.98%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDo they consciously study health or regimen knowledge (yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47.55%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e (male\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.79%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78.03%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.82\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.54\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56.32\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.16\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school education and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.97%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.44%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior high school education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49.21%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school education and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.56%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.34%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVillager\u003c/b\u003e (yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.73%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75.91%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e (normal\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.42%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48.04%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic diseases\u003c/b\u003e\u0026nbsp;(yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.94%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.93%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eNote\u003c/b\u003e: \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e \u003cb\u003edenotes the mean value;\u003c/b\u003e \u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e \u003cb\u003edenotes the variance\u003c/b\u003e.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eBaseline regression results\u003c/h2\u003e \u003cp\u003eAs indicated in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Models 1, 3 and 5 captured only the core independent variables, whereas Models 2, 4 and 6 are estimates of the complete regression model with control variables added. The results revealed that smartphone use and the duration of such use consistently and significantly positively promoted the self-rated health of rural middle-aged and elderly people, whereas the difficulty of smartphone use significantly and negatively affected the self-rated health of rural middle-aged and elderly people. In addition, the five control variables of age, education level, ordinary villager status, BMI and chronic diseases were significant in the three models. Age imposed a positive U-shaped effect on the self-rated health of rural middle-aged and elderly people. The self-rated health of rural middle-aged and elderly people with higher education levels, a nonordinary villager status, a normal BMI and no chronic diseases was better.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRobustness test\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e lists the results of the stability test after replacing the dependent and independent variables. The results indicated that, first, after the dependent variables were replaced, the use of smartphones, the difficulty and duration of smartphone use still significantly affected the self-rated health of middle-aged and elderly people in rural areas. Second, after the independent variables were replaced, the difficulty and duration of smartphone use still significantly affected the self-rated health of middle-aged and elderly people in rural areas, validating the estimation results of the baseline model.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eHeterogeneity analysis\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003eAge heterogeneity analysis\u003c/h2\u003e \u003cp\u003eWith reference to previous studies, the samples were divided into two groups: middle-aged individuals that are 46\u0026ndash;59 years old and elderly individuals that are 60 years and older[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. According to Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, smartphone use positively affected the self-rated health of the middle-aged population, but the effect was not significant. Notably, smartphone use imposed a significant positive effect on the self-rated health of the elderly population. Moreover, the difficulty of using smartphones imposed a significant negative effect both on the self-rated health of middle-aged people and elderly people, indicating that reducing the difficulty of smartphone use could improve the self-rated health of middle-aged and elderly people in rural areas. In addition, a longer duration of smartphone use significantly improved the self-rated health in the middle-aged population, but the improvement was not significant in the elderly population.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSex heterogeneity analysis\u003c/h2\u003e \u003cp\u003eThe samples were divided into two groups according to sex, namely, male and female, and a heterogeneity test was performed. According to Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, smartphone use imposed a significant positive effect on the self-rated health of males, but the improvement effect on the self-rated health of females was not significant. Moreover, the difficulty of smartphone use significantly restricted the self-rated health of both males and females, whereas the duration of smartphone use significantly improved both the self-rated health of both groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eEducation level heterogeneity analysis\u003c/h2\u003e \u003cp\u003eThe education level was divided into three groups for further heterogeneity testing: elementary school education and below, junior high school education, and high school education and above. According to Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, smartphone use imposed a positive and significant effect on the self-rated health of rural middle-aged and elderly people with a junior high school education and a high school education and above, but the improvement effect on the population with a primary school education and below was not significant. Moreover, the difficulty of smartphone use significantly inhibited the self-rated health of rural middle-aged and elderly people with primary school educations and below and junior high school educations, whereas the duration of smartphone use significantly improved the health of only rural middle-aged and elderly people with junior high school educations.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline regression results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel 4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModel 5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModel 6\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.176*** (0.045)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.135** (0.051)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty of smartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.242*** (0.029)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.169*** (0.030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.130** (0.041)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.032** (0.011)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.068 (0.043)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.076 (0.048)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.084* (0.048)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.066** (0.027)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.069* (0.038)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.085** (0.038)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge squared\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001** (0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001** (0.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001** (0.000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.074** (0.027)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.069** (0.030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.095** (0.029)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOrdinary villager\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.200*** (0.045)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.177*** (0.046)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.181*** (0.047)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.138*** (0.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.164*** (0.039)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.173*** (0.039)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic diseases\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.748*** (0.036)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.731*** (0.040)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.758*** (0.040)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56.649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54.082\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdjusted R\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eNote: *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively, and the standard errors are listed in parentheses.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of robustness test\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eSelf-rated health (three categories)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eSelf-rated health (five categories)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.123** (0.038)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty of smartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.123*** (0.022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.020** (0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty of smartphone use (binary classification)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.262*** (0.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use duration (binary classification)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.088** (0.040)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eControl variables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57.747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.475\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdjusted R\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eNote: *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively, and the standard errors are provided in parentheses.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of age heterogeneity analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiddle-aged\u003c/p\u003e \u003cp\u003epeople\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eElderly\u003c/p\u003e \u003cp\u003epeople\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMiddle-aged people\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eElderly people\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMiddle-aged people\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eElderly people\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.097 (0.097)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.113* (0.058)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty of smartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.163*** (0.036)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.160** (0.050)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.031** (0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.034 (0.022)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eControl variables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e649\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdjusted R\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eNote: *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively, and the standard errors are provided in parentheses.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of sex heterogeneity analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.164** (0.056)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.013 (0.123)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty of smartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.133*** (0.033)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.292*** (0.069)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.022* (0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.068** (0.025)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eControl variables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.358\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdjusted R\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eNote: *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively, and the standard errors are listed in parentheses.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of education level heterogeneity analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary school education and below\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJunior high school education\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh school education and above\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePrimary school education and below\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJunior high school education\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHigh school education and above\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePrimary school education and below\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eJunior high school education\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHigh school education and above\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.060 (0.070)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.189** (0.085)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.692*** (0.191)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty of smartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.113** (0.051)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.230*** (0.043)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.119 (0.073)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.024 (0.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.038** (0.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.030 (0.022)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eControl variables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e363\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.969\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.964\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e24.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e26.578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.945\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdjusted R\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cb\u003eNote: *, ** and *** indicate significance at the 10%, 5% and 1% levels, respectively; standard errors are provided in parentheses.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eMechanism analysis\u003c/h2\u003e \u003cp\u003eWe draw on the basic idea of Baron[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] on mediating effect analysis, the three-step regression method was used to analyse the mechanism of the effect of smartphone use on the self-rated health of rural middle-aged and elderly people. Regression was performed using health-promoting behaviour and self-rated health as the dependent variables and smartphone use, difficulty of use, and duration of use as the independent variables. According to Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, smartphone use among rural middle-aged and elderly people significantly and positively affected their health-promoting behaviour (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.390, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and self-rated health (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.135, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05); the difficulty of using smartphones among rural middle-aged and elderly people significantly and negatively affected their health-promoting behaviour (\u003cem\u003eβ\u003c/em\u003e = -0.377, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and self-rated health (\u003cem\u003eβ\u003c/em\u003e = -0.169, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001); and the duration of smartphone use among rural middle-aged and elderly people significantly and positively affected their health-promoting behaviour (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.089, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and self-rated health (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.032, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The study results revealed that rural middle-aged and elderly people who use smartphones exhibit less difficulty using smartphones and longer use times are associated with greater health-promoting behaviours and higher self-rated health levels. Moreover, self-rated health was used as a dependent variable to regress smartphone use, difficulty of use, and duration of use and health-promoting behaviour in the same model, and it was determined that health-promoting behaviour imposed a significant positive effect on the self-rated health (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.025, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In summary, the mediating effect test of health-promoting behaviour was passed, namely, the health-promoting behaviour play a mediating role in the relationship between smartphone use, difficulty of use, and duration of use affecting self-rated health among rural middle-aged and elderly people.\u003c/p\u003e \u003cp\u003eA bootstrap test was conducted. The number of repeated samples was set to 5000, and the confidence interval was set to 95% to verify the mediating effect of health-promoting behaviour. According to Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, first, the direct effect of smartphone use on the self-rated health of middle-aged and elderly people in rural areas was 0.011, while the indirect effect of health-promoting behaviour was 0.125. Notably, the results were statistically significant, with the indirect effect accounting for 91.91% of the overall variance. Second, the direct effect of the difficulty of smartphone use on the self-rated health of middle-aged and elderly people in rural areas was \u0026minus;\u0026thinsp;0.008, while the indirect effect of health-promoting behaviour was \u0026minus;\u0026thinsp;0.161. The results were statistically significant, and the indirect effect accounted for 95.27% of the total variance. Finally, the direct effect of smartphone use time on the self-rated health of middle-aged and elderly people in rural areas was 0.003, while the indirect effect of health-promoting behaviour was 0.030. The obtained results were statistically significant, and the indirect effect accounted for 90.9% of the total variance.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimates of the mediating effect of health-promoting behaviour\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eHealth-promoting behaviour\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c11\" namest=\"c6\"\u003e \u003cp\u003eSelf-rated health\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(9)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.390** (0.113)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.135** (0.051)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.125* (0.051)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDifficulty of smartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.377*** (0.068)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.169*** (0.030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.161*** (0.030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.089*** (0.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.032** (0.011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.030** (0.011)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth-promoting behaviour\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.025** (0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.021** (0.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.024** (0.009)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eControl variables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eF value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64.378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56.649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e58.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e51.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e48.973\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdjusted R\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cb\u003eNote: *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of bootstrap test\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEffect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePath relationship\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLower limit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUpper limit\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eEffect size\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDirect effect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSmartphone use \u0026rarr; self-rated health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.011**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.09%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eIndirect effect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSmartphone use \u0026rarr; health-promoting behaviour \u0026rarr; self-rated health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.125**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e91.91%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal effect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.136**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eDifficulty of smartphone use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDirect effect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDifficulty of smartphone use \u0026rarr; self-rated health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.008**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.73%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eIndirect effect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDifficulty of smartphone use \u0026rarr; health-promoting behaviour \u0026rarr; self-rated health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.161***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95.27%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal effect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.169***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eSmartphone use duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDirect effect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDuration of smartphone use \u0026rarr; self-rated health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.09%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eIndirect effect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDuration of smartphone use \u0026rarr; health-promoting behaviour \u0026rarr; self-rated health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.030**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e90.91%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal effect\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.033**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eNote: *, ** and *** denote significance at the 10%, 5% and 1% levels, respectively\u003c/h2\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eSmartphone use among rural middle-aged and elderly people directly reinforces health-promoting behaviour\u003c/h2\u003e \u003cp\u003eIn this study, it was revealed that smartphone use among rural middle-aged and elderly people could directly reinforce health-promoting behaviour. Health-promoting behaviour requires individuals to exert subjective initiative, in which knowledge plays an important role[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. With the rapid development of digital technology, many types of health information are presented in electronic form, and the internet has become an important source of health information for people[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Numerous previous studies have shown that smartphones provide channels for middle-aged and elderly people to obtain information and education, and that middle-aged and elderly people can use smartphones to obtain online health information and learn ways and methods to search for and acquire health knowledge, which will be conducive to the accumulation of their health knowledge [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], and that knowledge is one of the important prerequisites for behaviour change, which in turn can guide middle-aged and elderly people to adopt healthier behaviours[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Xavier et al analysed data from 5,900 older people in the English Longitudinal Study of Ageing and found that internet use was associated with weekly moderate to vigorous exercise, more frequent daily consumption of fruit and vegetables and less smoking[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In addition, relevant studies on rural groups have indicated that rural residents who often use smartphones are more inclined to adopt digital tools for health promotion, consider diverse sources of digital health information and explore various digital health-promoting behaviours, such as searching for health information and health status management and tracking improving, to enhance their health levels[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eSmartphone use among rural middle-aged and elderly people directly affects their self-rated health\u003c/h2\u003e \u003cp\u003eThe relevant results showed that smartphone use among rural middle-aged and elderly people could directly improve their self-rated health. Similarly, previous studies have shown that smartphone use can effectively sustain the social connections of middle-aged and elderly people with other groups, expand their social networks, and reduce social alienation[\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], thereby positively affecting their health[\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. In addition, Liu and Guo reported that the use of mobile internet applications, including WeChat, WeChat Moments and mobile payments, can effectively promote physical and mental health[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Studies have also demonstrated that middle-aged and elderly people can use smartphones to search for and browse a variety of online health information, obtain medical information, communicate with health care professionals, and perform other health-related tasks, thus positively affecting their health[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR47\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. For the rural population, numerous empirical studies have revealed that internet use can significantly improve the self-rated health level of middle-aged and elderly people in rural areas[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] and that the health of Chinese elderly people is affected mainly through social support[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Moreover, some studies have indicated that watching short videos can positively influence the acquisition of online health information by rural elderly people. As mentioned previously, online health information is an important prefactor influencing the health status[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe effect of smartphone use on the self-rated health varies among rural middle-aged and elderly people of different sexes, ages and education levels\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThrough heterogeneity analysis, we found that sex, age and education level differences exist in the effects of smartphone use on the self-rated health of middle-aged and elderly people in rural areas, which is similar to the conclusions of existing studies[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. In terms of gender differences, the effect of smartphone use on the self-rated health of rural elderly males was greater than that on rural elderly females. There is significant gender inequality in rural education opportunities, namely, rural women are at a disadvantage in obtaining educational opportunities, whereas rural men are more likely to obtain better educational opportunities and reach higher educational levels[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. In addition, under the influence of traditional cultural thinking, the traditional family division of labour model, in which \u0026ldquo;males dominate the workplace and females dominate the home,\u0026rdquo; is still common[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Given the need to maintain social networks, middle-aged and elderly men use smartphones more frequently. Therefore, men face fewer barriers to using smartphones, exhibit greater proficiency in using smartphones, and demonstrate better judgement and differentiation ability in the face of good and bad health information online. From an age perspective, smartphone use exerted a greater promoting effect on the self-rated health of the 46\u0026ndash;59-year-old group of middle-aged individuals. Middle-aged people are more accepting of new things and have fewer learning disabilities and technical barriers when using smartphones. Therefore, they use them more frequently to obtain all types of information and to maintain social contacts. However, for elderly people aged 60 years and older, there are certain difficulties in learning how to use smartphones, and they feel rejection and fear in the face of digital technology; therefore, these individuals are more likely to give up trying to integrate into digital life[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Their use of smartphones is more focussed on the basic functions of voice calling and maintaining necessary contact with the outside world[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], which brings very limited health effects. In addition, the positive effect of smartphone use on the self-rated health of middle-aged and elderly people with higher levels of education was more significant. A previous study revealed that middle-aged and elderly people with higher education levels can more easily cross the digital divide and integrate into the digital age[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], which is verified in this study. Middle-aged and elderly people with higher education levels possess relatively more abundant social resources and are more likely to fully utilize smartphones for social maintenance and access to health resources, thereby more likely improving their self-rated health.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMediating effect of health-promoting behaviour on the relationship between smartphone use and the self-rated health of rural middle-aged and elderly people\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIt was also revealed that the health-promoting behaviour of rural middle-aged and elderly people exerted an important mediating effect on the relationship between smartphone use and self-rated health, which is similar to the results of previous studies[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan additionalcitationids=\"CR60 CR61\" citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. This mediating effect can be explained by Andersen's Behavioural Model of Health Services Use[\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. This model emphasizes that personal propensity characteristics are correlated with health outcomes. Personal propensity characteristics can directly or indirectly affect health outcomes by influencing health behaviour[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. In this study, smartphone use can be considered an individual tendency feature. According to this model, middle-aged and elderly people who use smartphones are more likely to actively acquire effective online health resources and online health knowledge through online media, thereby increasing their health management awareness, adopting sound health management behaviours, and improving their health-promoting behaviour, thus enhancing their self-rated health. Using data from a national comprehensive survey in China, Zhou et al. found that Internet use among older adults was positively associated with self-rated health and negatively associated with psychological sub-health, and that Internet use promotes health in older adults by facilitating access to health information, healthy lifestyles, and enhanced social interaction[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Similarly, Guo et al. reported that internet use among elderly people can increase the frequency of physical exercise, thereby improving their physical health[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. In addition, numerous rural population-based studies have shown that healthy living habits and behaviours are the key factors for preventing and treating diseases and protecting health; moreover, the lifespan can be increased, and the risk of death can be reduced by shaping healthy lifestyles, such as favouring vegetables, physical activity, reading, etc.[\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003ePolicy implications\u003c/h2\u003e \u003cp\u003eAgainst the background of the convergence of digitalization and the ageing process, in this study, the relationships among smartphone use, health-promoting behaviour, and self-rated health of rural middle-aged and elderly people were analysed. The relevant conclusions have important policy implications for improving the health of rural middle-aged and elderly people and actively promoting healthy ageing in rural areas.\u003c/p\u003e \u003cp\u003eFirst, the construction of mobile networks in rural areas should be strengthened, and a suitable digital access environment should be created for elderly individuals. Compared with that in urban areas, mobile network infrastructure in rural areas is relatively underdeveloped, and the popularity of smartphones among middle-aged and elderly people in rural areas should be improved. It is recommended that the government implement a digital countryside construction strategy, increase infrastructure construction of rural mobile networks, create a favourable digital access environment for the use of smartphones by middle-aged and elderly people in rural areas, drive them to better integrate into digital life, and mitigate the deterioration of the health status of middle-aged and elderly people caused by the digital divide.\u003c/p\u003e \u003cp\u003eSecond, smartphone education for middle-aged and elderly people in rural areas should be strengthened to establish an age-friendly digital society. Owing to the flat information characteristics of the digital age, smartphone use and internet access could compensate for the lack of health information acquisition abilities among middle-aged and elderly people in rural areas. To this end, the provision of internet education to rural middle-aged and elderly individuals should be strengthened to cultivate their basic digital abilities, such as network connections, information searches, and digital communications, so that they can use smartphones to obtain and understand more comprehensive health information and thus improve their health status and promote the development of healthy ageing in rural areas.\u003c/p\u003e \u003cp\u003eThird, we should focus on group differences and revealed the differentiated uses of smartphones by middle-aged and elderly individuals. While the smartphone penetration rate among middle-aged and elderly people in rural areas has steadily increased, a \u0026ldquo;targeted support\u0026rdquo; policy is recommended to provide differentiated digital resource services, with a focus on precise help for rural women, elderly people above a certain age, and disadvantaged middle-aged and elderly groups with low education levels. In addition, in the process of ageing-appropriate construction, internet-related companies are encouraged to customize the research and development of smartphone-related functions on the basis of sex, age, and education level of middle-aged and elderly people to create differentiated ageing-appropriate products to meet their smartphone needs.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eAlthough this paper provides a certain theoretical basis for the investigation of relevant variables, due to data limitations, only cross-sectional data from the 2020 CRRS were analysed. There is a lack of longitudinal observation data, and the time-varying pattern of the influence mechanism of smartphone use cannot be comprehensively captured. The second phase of the CRRS survey was completed in 2022. After the release of relevant data, the existing database can be expanded to form a panel dataset, which can improve the study of relevant mechanisms. Second, this study focused only on the self-rated health of middle-aged and elderly people. Currently, the understanding of healthy ageing is continuously increasing. Thais et al. proposed that healthy ageing includes physical health as well as other aspects, such as physical function, cognitive ability, and mental health dimensions[\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Therefore, future measurements of health can be expanded, and studies can be performed in greater depth to enrich the research results related to healthy ageing.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCRRS：China Rural Revitalization Survey\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are very grateful the Rural Development Institute Chinese Academy of Social Sciences for the approval to use the 2022 CRRS data. We also thank the anonymous reviewers for their valuable comments.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTheme: X.G and X.L. Methodology: X.G and X.L. Software: X.G and J.W. Data Curation: X.G and X.L. Original draft: X.G. Review and editing: X.G and J.W. Supervision and funding acquisition: J.W. All authors have read and agreed to the published version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the Ministry of Education Humanities and Social Sciences Youth Project (Grant number 22YJCZH188) and Anhui Provincial Colleges and Universities Outstanding Youth Scientific Research Project (Grant number 2023AH030062)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data presented in this study are publicly available via the China Rural Revitalization Survey (CRRS) database. Access data online via http://rdi.cass.cn/ggl/202210/t20221024_5551642.shtml. Further queries can be directed to the authors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll experimental protocols of this study were approved by the Ethics Committee of Anhui Medical University and all methods were conducted according to the guidelines of the Declaration of Helsinki and relevant Chinese laws and regulations. This study confirms that informed consent was obtained from all participants and/or their legal guardians. Written informed consent was obtained from all participants before administering any study procedures.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eLu J, Lin J. Demographic Characteristics, Risk Identification and Strategic Responses in Heavily Aging Society. Studies on Socialism with Chinese Characteristics. 2023;59\u0026ndash;68.\u003c/li\u003e\n \u003cli\u003eLuo Y, Su B, Zheng X. Trends and Challenges for Population and Health During Population Aging - China, 2015-2050. 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Aging Clin Exp Res. 2022;34:1215\u0026ndash;23.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Smartphone use, Health-promoting behaviours, Self-rated health, Rural middle-aged and elderly people, Healthy ageing","lastPublishedDoi":"10.21203/rs.3.rs-4953641/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4953641/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eAccounting for the convergence of digitalization and ageing, our study focused on middle-aged and elderly people in rural areas. Moreover, the potential mechanisms by which smartphone use affects the self-rated health and heterogeneity among different groups were explored, and the mediating effects of health-promoting behaviours were explored, with the aim of providing relevant insights and recommendations for improving the health of rural middle-aged and elderly people and actively promoting healthy ageing in rural areas.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eOn the basis of data from the 2020 China Rural Revitalization Survey, we established a multiple linear regression model to assess the direct effects of smartphone use (including whether to use, difficulty of use, and duration of use) on the self-rated health of rural middle-aged and elderly people and examined the heterogeneity among the various groups in terms of sex, age, and education level. In addition, the three-step regression and bootstrap test methods were used to analyse the mediating effect of health-promoting behaviours on the relationship between smartphone use and self-rated health.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSmartphone use among rural middle-aged and elderly people significantly and positively affected their health-promoting behaviours and self-rated health, and the findings were robust. The positive effects of smartphone use on self-rated health were heterogeneous among rural middle-aged and older adults of different ages, sexes, and education levels. Health-promoting behaviours exerted significant mediating effects, accounting for 91.91%, 95.27% and 90.91% of the total effects, respectively.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eSmartphone use among rural middle-aged and elderly people notably affected the improvement in their self-rated health, and this positive effect differed according to sex, age and education level. The indirect path of encouraging rural middle-aged and elderly people to use smartphones, reducing the difficulty of smartphone use, and prolonging the duration of smartphone use for enhancing health-promoting behaviours could effectively improve their self-rated health.\u003c/p\u003e","manuscriptTitle":"Smartphone use, health-promoting behaviours and self-rated health among middle-aged and elderly people in rural areas","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-20 09:27:19","doi":"10.21203/rs.3.rs-4953641/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"567a150f-0c44-4999-a44a-f8af265cae07","owner":[],"postedDate":"September 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T12:40:57+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-20 09:27:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4953641","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4953641","identity":"rs-4953641","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}