Background: Cross-sectional and longitudinal studies have found that problematic mobile phone use, bedtime procrastination, sleep quality, and depressive symptoms are strongly associated. However, studies are inconsistent regarding whether problematic mobile phone use predicts depressive symptoms or vice versa, and sleep factors have been infrequently focused on in this regard. In addition, few studies have examined the longitudinal associations and directions of effects between these factors. Therefore, this study aims to explore the longitudinal relationship among problematic mobile phone use, bedtime procrastination, sleep quality, and depressive symptoms in college students. Methods: Overall, 1181 college students completed questionnaires on problematic mobile phone use, bedtime procrastination, sleep quality, and depressive symptoms at two time points 12 months apart. A cross-lagged model was used to examine the longitudinal relationship between these factors. Results: Cross-lagged analyses showed significant bidirectional relationships of problematic mobile phone use with bedtime procrastination and depressive symptoms. Additionally, there were also significant bidirectional relationships of sleep quality with bedtime procrastination and depressive symptoms. Problematic mobile phone use predicted subsequent sleep quality one-way, and bedtime procrastination predicted subsequent depressive symptoms one-way. Conclusions: This study further expands our understanding of the longitudinal and bidirectional relationships among problematic mobile phone use, bedtime procrastination, sleep quality and depressive symptoms and helps school mental health educators design targeted interventions to reduce problematic mobile phone use, sleep problems, and depressive symptoms among college students.

Myocardial fibrosis represents the primary pathological change associated with diabetic cardiomyopathy and heart failure, and it leads to decreased myocardial compliance with impaired cardiac diastolic and systolic function. Quercetin, an active ingredient in various medicinal plants, exerts therapeutic effects against cardiovascular diseases. Here, we investigate whether SIRT5‐ and IDH2‐related desuccinylation is involved in the underlying mechanism of myocardial fibrosis in heart failure while exploring related therapeutic drugs for mitochondrial quality surveillance. Mouse models of myocardial fibrosis and heart failure, established by transverse aortic constriction (TAC), were administered with quercetin (50 mg/kg) daily for 4 weeks. HL‐1 cells were pretreated with quercetin and treated with high glucose (30 mM) in vitro. Cardiac function, western blotting, quantitative PCR, enzyme‐linked immunosorbent assay, and immunofluorescence analysis were employed to analyze mitochondrial quality surveillance, oxidative stress, and inflammatory response in myocardial cells, whereas IDH2 succinylation levels were detected using immunoprecipitation. Myocardial fibrosis and heart failure incidence increased after TAC, with abnormal cardiac ejection function. Following high‐glucose treatment, HL‐1 cell activity was inhibited, causing excess production of reactive oxygen species and inhibition of mitochondrial respiratory complex I/III activity and mitochondrial antioxidant enzyme activity, as well as increased oxidative stress and inflammatory response, imbalanced mitochondrial quality surveillance and homeostasis, and increased apoptosis. Quercetin inhibited myocardial fibrosis and improved cardiac function by increasing mitochondrial energy metabolism and regulating mitochondrial fusion/fission and mitochondrial biosynthesis while inhibiting the inflammatory response and oxidative stress injury. Additionally, TAC inhibited SIRT5 expression at the mitochondrial level and increased IDH2 succinylation. However, quercetin promoted the desuccinylation of IDH2 by increasing SIRT5 expression. Moreover, treatment with si‐SIRT5 abolished the protective effect of quercetin on cell viability. Hence, quercetin may promote the desuccinylation of IDH2 through SIRT5, maintain mitochondrial homeostasis, protect mouse cardiomyocytes under inflammatory conditions, and improve myocardial fibrosis, thereby reducing the incidence of heart failure.

Purpose: The aim of this study was to examine the association between eHealth literacy and health-related quality of life (HRQoL) and explore whether health-promoting behaviors mediate the association between eHealth literacy and HRQoL among Chinese older adults.Methods: An anonymous cross-sectional survey was conducted among 2300 adults aged 60 or older from Jinan, China. The eHealth Literacy Scale, Short-Form Health-Promoting Lifestyle Profile, and Short-Form Health Survey (SF-12) were used to measure eHealth literacy, health-promoting behaviors, and HRQoL. Multivariate linear regression analyses were conducted to test the association between eHealth literacy, health-promoting behaviors, and HRQoL. The mediation analyses, composed of PROCESS analysis and bootstrapping method, were preformed to test both total (c), direct (c'), and indirect effects (a*b) of eHealth literacy on HRQOL through health-promoting behaviors.Results: Regression analyses indicated that eHealth literacy (B = 0.487,p < 0.001) was significantly positively associated with health-promoting behaviors, and health-promoting behaviors (B = 0.257,p < 0.001) were associated with HRQoL. The mediation analyses indicated that eHealth literacy had a significant direct (c' = 0.183,p < 0.001) and indirect effect on older adults’ HRQoL through health-promoting behaviors (a*b = 0.125, bootstrapped 95% confidence interval (CI) = 0.094–0.157). The indirect effect accounted for 40.6% of the total effect (c = 0.308, bootstrapped 95% CI 0.241–0.376) of eHealth literacy on HRQoL.Conclusions: Health-promoting behaviors mediated the association between eHealth literacy and HRQoL in Chinese older adults. The establishment of interventions focused on health-promoting behavior may be an effective way to help older adults with low eHealth literacy improve their HRQoL.

Background: Social capital has been linked to health behaviours, but the underlying mechanism is unclear. Previous studies have found that health literacy played the role of a mediator in the relationships among social capital, individual physical activity and nutrition. But it is not clear whether eHealth literacy mediates the impact of social capital on health behaviours. Therefore, our research aimed to explore the relationships among social capital (structural and cognitive social capital), eHealth literacy, and the health behaviours of elderly people, and to analyse the mediating effect of eHealth literacy, while providing a theoretical basis for a health behaviour intervention for elderly people. Methods: From January to February 2019, we conducted a cross-sectional survey of 1201 Chinese people aged over 60 years using the Chinese Shortened Social Capital Scale (contains two subscales of structural social capital and cognitive social capital), eHealth Literacy Scale, and Health-Promoting Lifestyle Profile. We used structural equation modelling to test a hypothetical mediation model. Results: The mean scores of social capital was 72.07 (SD = 13.03), 17.24 (SD = 9.34) for eHealth literacy, and 112.23 (SD = 23.25) for health behaviours. Social capital and eHealth literacy were significantly correlated with health behaviours, and social capital and structural social capital were significantly correlated with eHealth literacy. Lastly, eHealth literacy mediated the relationship between structural social capital and health behaviours. Conclusions: eHealth literacy was an important mediating factor for elderly people’s structural social capital and health behaviours. Therefore, social capital and eHealth literacy must be considered when designing and implementing health behaviour intervention programmes for elderly people.

Background: Healthy lifestyles and health literacy are strongly associated with cognitive health in older adults, however, it is unclear whether this relationship can be generalized to health-promoting lifestyles and eHealth literacy. To date, no research has examined the interactive effect of health-promoting lifestyles and eHealth literacy on cognitive health. Objective: To examine the associations among health-promoting lifestyles, eHealth literacy, and cognitive health in older adults. Methods: Using a stratified cluster sampling method, we conducted a survey with older adults in four districts and two counties in Jinan (China). Older adults (n = 1201; age ≥ 60 years) completed our survey. We assessed health-promoting lifestyles, eHealth literacy, and cognitive health, and collected participants’ sociodemographic information. Results: Health-promoting lifestyles and eHealth literacy were significantly and positively associated with cognitive health (both p < 0.01). In addition, eHealth literacy was positively associated with health-promoting lifestyles. Moreover, the interaction of health-promoting lifestyle and eHealth literacy negatively predicted cognitive health (β = −0.465, p < 0.01). Conclusions: Health-promoting lifestyles and eHealth literacy were associated with the cognitive health of Chinese older adults, both independently and interactively. Further, eHealth literacy was associated with health-promoting lifestyles in older adults. Therefore, interventions regarding healthy lifestyles and eHealth literacy would benefit older adults.

Objectives: This study aimed to explore the longitudinal associations between eHealth literacy, health-promoting lifestyles, and health-related quality of life (HRQoL) among college students.Methods: From December 2019 (T1) to December 2020 (T2), we administered the eHealth literacy scale, Short-Form Health Survey (SF-12), and Short-Form Health-Promoting Lifestyle Profile Scale to 1,181 college students in Jinan, China. Participants were recruited for 12 months for the two-stage survey.Results: Stable positive correlations were shown between eHealth literacy, health-promoting lifestyles, and HRQoL across time. The cross-lagged analysis showed that eHealth literacy at T1 predicted health-promoting lifestyles at T2 (β = 0.080, P = 0.006); however, health-promoting lifestyles at T1 did not predict eHealth literacy at T2 (β = −0.026, P = 0.499). HRQoL at T1 predicted health-promoting lifestyles at T2 (β = 0.147, P < 0.001); however, similar to the eHealth literacy finding, health-promoting lifestyles at T1 did not predict HRQoL at T2 (β = 0.045, P = 0.142). eHealth literacy was also bi-directionally associated with HRQoL, and the prediction effect of eHealth literacy at T1 to HRQoL at T2 (β = 0.078, P = 0.008) was slightly higher than the prediction effect of HRQoL at T1 to eHealth literacy at T2 (β = 0.074, P = 0.023).Conclusion: eHealth literacy and HRQoL may be antecedents for college students' health-promoting lifestyles. There may be significant bi-directional relationships between eHealth literacy and HRQoL.