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: 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.