Understanding Social Media Information Sharing in Individuals with Depression: Insights from the Elaboration Likelihood Model and Schema Activation Theory.

Purpose: How individuals engage with social media can significantly impact their psychological well-being. This study examines the impact of social media interactions on mental health, grounded in the frameworks of the Elaboration Likelihood Model and Schema Activation Theory. It aims to uncover behavioral differences in information sharing between the general population and individuals with depression, while also elucidating the psychological mechanisms underlying these disparities. Methods: A pre-experiment (N=30) and three experiments (Experiment 1a N=200, Experiment 1b N=180, Experiment 2 N=128) were executed online. These experiments investigated the joint effects of information quality, content valence, self-referential processing, and depression level on the intention to share information. The research design incorporated within-subject and between-subject methods, utilizing SPSS and SPSS Process to conduct independent sample t-tests, two-factor ANOVA analyses, mediation analyses, and moderated mediation analyses to test our hypotheses. Results: Information quality and content valence significantly influence sharing intention. In scenarios involving low-quality information, individuals with depression are more inclined to share negative emotional content compared to the general population, and this tendency intensifies with the severity of depression. Moreover, self-referential processing acts as a mediator between emotional content and intention to share, yet this mediation effect weakens as the severity of depression rises. Conclusion: Our study highlights the importance of promoting viewpoint diversity and breaking the echo chamber effect in social media to improve the mental health of individuals with depression. To achieve this goal, tailoring emotional content on social media could be a practical starting point for practice.

Assessing the Impact of Internet Skills on Depressive Symptoms Among Chinese Middle-Aged and Older Adults: Cross-Sectional Instrumental Variables Analysis.

Background: The potential benefits of IT for the well-being of older adults have been widely anticipated. However, findings regarding the impact of internet use on depressive symptoms are inconsistent. As a result of IT's exponential growth, internet skills have supplanted internet access as the source of the digital divide. Objective: This study evaluates the effect of internet skills on depressive symptoms through an instrumental variables (IV) approach. Methods: Data from the China Health and Retirement Longitudinal Study's wave 4 (2018) were used. This included 16,949 community residents aged 45 years and older. To overcome the endogeneity issue, we used an IV approach. Results: Our results reveal the emergence of a second-level digital divide, the disparity in internet skills, among Chinese middle-aged and older adults. Liner regression suggests that a 1% increase in internet skills is associated with a 0.037% decrease in depressive symptoms (ß=-.037, SE 0.009), which underestimates the causal effect. As expected, internet skills are an endogenous variable (F test P value <.001). IV regressions indicate that a 1% increase in internet skills reduces 1.135% (SE 0.471) to 1.741% (SE 0.297) of depressive symptoms. These 2 IV are neither weak (F-1=16.7 and 28.5; both >10) nor endogenous (Wu-Hausman test P value of .10; >.05 or >.01). Conclusions: Better mental health is predicted through improved and higher internet skills. Consequently, residents and policy makers in China should focus on bridging the digital divide in internet skills among middle-aged and older adults.

Connecting through clicks: A longitudinal examination of internet use and depressive symptoms among middle- and old-aged Chinese.

AIM: While prior investigations into the influence of internet engagement on depressive symptoms in middle-aged and older individuals have largely been favorable, concerns persist. Some research posits that internet use may detract from direct interpersonal interactions, elevating depression risks. Here, we scrutinize these contrasting views, endeavoring to delineate the relationship between internet use, social participation, and the ensuing depressive manifestations. METHODS: We analyzed nationally representative data from three consecutive waves (2013-T1, 2015-T2, 2018-T3) of the China Health and Retirement Longitudinal Study survey. Measures of social participation encompassed formal social participation (i.e., attending clubs for mahjong, chess, sports, or other activities; participation in community organizations, volunteering, or enrolling in training courses) and informal social participation (i.e., interactions with friends or extending assistance to relatives, friends, or neighbors). Structural equation modeling was used to evaluate a focused longitudinal mediation model. RESULTS: Our dataset comprised 13 671 individuals aged 45 years or older. Baseline internet use was associated with a decrease in depressive symptoms by T3 ( c ' = -0.143, SE = 0.055). The longitudinal association between internet use and the alleviation of depressive symptoms was partially mediated by enhanced formal social participation (indirect effect a 1 × b 1 = -0.023, SE = 0.011). CONCLUSIONS: For developing nations such as China, grappling with a rapidly aging demographic and scarce mental health infrastructure, pioneering initiatives that merge digital and formal social participation might be a valuable component in a multifaceted approach to alleviate late-life depression. Geriatr Gerontol Int 2024; 24: 218-224.

The Impact of Everyday ICT Use on Depressive Symptoms Among Older Adults in China: A Subjective Social Status Perspective.

OBJECTIVES: While numerous studies have highlighted the positive effects of everyday information and communication technology (EICT) use among older adults, emerging evidence signals potential detriments to mental health, particularly among younger demographics. This study aims to examine the effect of EICT on depressive symptoms among Chinese older adults. We hypothesize that EICT use among older adults will contribute to higher amounts of depressive symptoms, mediated by a decline in subjective social status. METHODS: We conducted a longitudinal mediation analysis with data from the China Family Panel Studies (CFPS), a nationally representative survey. A total of 3,234 older adults aged 60 years and older were selected from Wave 2016 (T1), Wave 2018 (T2), and Wave 2020 (T3) of the CFPS. Structural equation modeling was used to construct complete longitudinal path model. RESULTS: EICT use at T1 predicted a decline in subjective social status at T2 (ß = -0.215, p = .001), which in turn predicted higher depressive symptoms at T3 (ß = -0.375, p = .005). The mediating effect of subjective social status was statistically supported (indirect effect 0.081, p = .042). DISCUSSION: We reveal the potential negative impact of EICT use among older adults and its underlying mechanism. It lays the groundwork for the formulation of relevant public health initiatives, critical for stemming and mitigating the burgeoning incidence of depressive symptoms within China's aging population.

Internet use and depressive symptoms among Chinese older adults: Two sides of internet use.

Objective: To explore the relationship between internet use which includes time spent on the internet, internet skills, types of online activities, and depressive symptoms in older adults. Methods: We used 2020 China Family Panel Studies (CFPS) data with 3,171 older adults aged 60 years. Depression symptoms were measured with the Center for Epidemiologic Studies Depression (CES-D), and internet use was measured by time spent on the internet, internet skills, and types of online activities. Multiple linear regression models were used to explore the relationship between internet use and depressive symptoms in older adults. Results: Longer time spent on the internet was associated with higher scores of depressive symptoms (ß = 0.14). Higher internet skills were associated with lower scores of depressive symptoms (ß = -0.42). Watching short-form videos (ß = 1.34) was associated with higher depressive symptom scores, and the use of the WeChat function (ß = -0.96) was associated with lower depressive symptom scores, while online games and online shopping were not significant. Conclusion: The effect of internet use on depressive symptoms in older adults is a double-edged sword. Controlling the time spent on the internet, improving internet skills, and guiding specific a type of online activities in older adults can improve depressive symptoms through rational use.

Impact of Internet Use on Cognitive Decline in Middle-Aged and Older Adults in China: Longitudinal Observational Study.

BACKGROUND: Given that cognitive decline lacks effective treatment options and has severe implications for healthy aging, internet use may achieve nonpharmacological relief of cognitive decline through cognitive stimulation and social engagement. OBJECTIVE: This longitudinal study aimed to investigate the relationship between the diversity, frequency, and type of internet use and cognitive decline, and to provide theoretical support and suggestions for mitigating cognitive decline in middle-aged and older adults. METHODS: Data were obtained from a total of 10,532 survey respondents from the China Family Panel Studies database from wave 3 (2014) and wave 5 (2018) of the survey. Cognitive function was measured using vocabulary tests, and internet use was categorized into five aspects: study, work, socializing, entertainment, and commercial-related activities. Associations between the diversity, frequency, and type of internet use and cognitive decline were estimated by controlling for demographic variables and health status risk factors through fixed-effects models. RESULTS: After controlling for demographic and health status risk factors, the type and frequency of internet use were found to be associated with cognitive functioning during the subsequent 4-year period, and different types of internet use had different effects on cognitive decline. Frequency of internet use of at least once a week for study (ß=0.620, 95% CI 0.061 to 1.180; P=.04), work (ß=0.896, 95% CI 0.271 to 1.520; P=.01), and entertainment (ß=0.385, 95% CI -0.008 to 0.778; P=.06), as well as less than once a week for social purposes (ß=0.860, 95% CI 0.074 to 1.650; P=.06), were associated with better cognitive function. Frequency of internet use of less than once a week for commercial-related activities (ß=-0.906, 95% CI -1.480 to -0.337; P=.005) was associated with poorer cognitive function. Using the internet for more than one type of activity (ß=0.458, 95% CI 0.065 to 0.850; P=.03) and at least once a week (ß=0.436, 95% CI 0.066 to 0.806; P=.02) was associated with better cognitive function. CONCLUSIONS: This study shows that breadth and depth of internet use are positively associated with cognitive function and that different types of internet use have different roles in cognitive decline. The importance of the internet as a nonpharmacological intervention pathway for cognitive decline is emphasized. Future research could explore specific mechanisms of influence.

Does digital technology reduce health disparity? Investigating difference of depression stemming from socioeconomic status among Chinese older adults.

BACKGROUND: Prior studies on health disparity have shown that socioeconomic status is critical to inequality of health outcomes such as depression. However, two questions await further investigation: whether disparity in depression correlated with socioeconomic status will become larger when depression becomes severer, and whether digital technology will reduce the disparity in depression correlated with socioeconomic status. Our study aims to answer the above two questions. METHODS: By using the dataset from China Health and Retirement Longitudinal Study 2015, we use quantile regression models to examine the association between socioeconomic status and depression across different quantiles, and test the moderating effect of digital technology. RESULTS: Our study obtains four key findings. First, the negative effects of socioeconomic status on depression present an increasing trend at high quantiles. Second, Internet usage exacerbates the disparity in depression associated with education level on average, but reduces this disparity associated with education level at high quantiles. Third, Internet usage reduces the disparity in depression associated with income on average and at high quantiles. Fourth, mobile phone ownership has almost no moderating effect on the relationship between socioeconomic status and depression. CONCLUSIONS: Our findings suggest the potential use of digital technology in reducing disparity in depression correlated with socioeconomic status among middle-aged and aged individuals in developing countries.