Background During the COVID-19 pandemic, the internet has significantly spread information, providing people with knowledge and advice about health protection regarding COVID-19. While a previous study demonstrated that health and eHealth literacy are related to COVID-19 prevention behaviors, few studies have focused on the relationship between health literacy, eHealth literacy, and COVID-19–related health behaviors. The latter includes not only preventative behaviors but also conventional health behaviors. Objective The objective of this study was to develop and verify a COVID-19–related health behavior questionnaire, explore its status and structure, and examine the associations between these behaviors and participants’ health literacy and eHealth literacy. Methods A snowball sampling method was adopted to recruit participants to complete anonymous cross-sectional questionnaire surveys online that assessed sociodemographic information, self-reported coronavirus knowledge, health literacy, eHealth literacy, and COVID-19–related health behaviors. Results Of 1873 college students who were recruited, 781 (41.7%) had adequate health literacy; the mean eHealth literacy score was 30.16 (SD 6.31). The COVID-19–related health behavior questionnaire presented a two-factor structure—COVID-19–specific precautionary behaviors and conventional health behaviors—with satisfactory fit indices and internal consistency (Cronbach α=.79). The mean score of COVID-19–related health behaviors was 53.77 (SD 8.03), and scores differed significantly (P<.05) with respect to residence, college year, academic major, family economic level, self-reported health status, having a family member or friend infected with coronavirus, and health literacy level. Linear regression analysis showed that health literacy and eHealth literacy were positively associated with COVID-19–specific precautionary behaviors (βhealth literacy=.149, βeHealth literacy=.368; P<.001) and conventional health behaviors (βhealth literacy=.219, βeHealth literacy=.277; P<.001). Conclusions The COVID-19–related health behavior questionnaire was a valid and reliable measure for assessing health behaviors during the pandemic. College students with higher health literacy and eHealth literacy can more actively adopt COVID-19–related health behaviors. Additionally, compared to health literacy, eHealth literacy is more closely related to COVID-19–related health behaviors. Public intervention measures based on health and eHealth literacy are required to promote COVID-19–related health behaviors during the pandemic, which may be helpful to reduce the risk of COVID-19 infection among college students.

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.

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.

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