Modeling social support on social media: Effect of publicness and the underlying mechanisms

Measuring the Impact of Social Media on Young People's Mental Health: Development and Validation of the Social Media-Induced Tendency Scale

Social media use has been linked to adverse health outcomes such as depression. To facilitate interventions, understanding the varied causes of depression is necessary. The authors developed a social media-induced depression tendency (SMIDT) scale for use with young people and aimed to validate it for young people in Nigeria. The study was conducted in three parts using an online survey (Google Forms) with purposive sampling targeting young people. Study 1 was an exploratory study that developed the SMIDT scale with 361 young people aged 16 to 26 years (mean age = 22.81). A concise measure of SMIDT was obtained. In study 2, confirmatory factor analysis was performed on the SMIDT with young people aged 17 to 25 years (mean age = 23.61). Construct, discriminant, and concurrent validities were established, and three factors were identified (sensitivity/attention seeking, worthlessness, and escapism/reality avoidance), which explained 55.87% of the variance. Study 3 tested the predictive validity of the scale. The results showed that the 15-item SMIDT scale had high internal consistency and satisfactory validity. The SMIDT scale can enable the assessment of factors associated with social media-induced depression tendency. The three factors identified in the scale provide insight into the factors contributing to depression associated with social media use. The SMIDT scale has the potential to help identify at-risk individuals and in-developing interventions to prevent or reduce social media-induced depression tendencies. However, this study only focused on young people in Nigeria. Additional studies using the SMIDT scale are required to assess its generalizability and applicability in evaluating other factors, such as quality of life among young people. Moreover, while social media use has been associated with adverse health outcomes, it is crucial to recognize that it can also positively affect mental health. Further research is necessary to explore the complex relationships between social media use and mental health outcomes.

The role of communication technology across the life course: A field guide to social support in East York

This paper builds on a body of work over the decades that examines how East Yorkers give and receive support. We go beyond the earlier work taking into consideration communication technologies and how they play a role in the ways people exchange social support across the life course. We draw on 101 in-depth interviews conducted in 2013-2014 to shed light on the support networks of a sample of East York residents and discern the role of communication technologies in the exchange of different types of social support across age groups. Our findings show that not much has changed since the 1960s in terms of the social ties that our sample of East Yorkers have, and the types of support mobilized via social networks: companionship, small and large services, emotional aid, and financial support. What has changed is how communication technologies interweave in complex ways with different types of social ties (partners, siblings, friends, etc.) to mobilize social support. We found that communication technologies helped siblings and extended kin to increase the frequency of interaction and help exchange support at a distance. Communication technologies helped solidify friendship ties by providing a continuous flow of interaction. We draw implications for theories of social support and for social policy associated with interventions aimed at helping vulnerable groups cope in hard times such as the COVID-19 pandemic.

The Impact of Social Media Usage on Work Efficiency: The Perspectives of Media Synchronicity and Gratifications

As prevail of mobile networking, social media became ubiquitous in either work or our personal life. Based on Media Synchronization Theory and transformational framework, this study proposed a research model and examined how the social media' attributes impacting the work effectiveness through the work-oriented or social-oriented usage. The data of 322 valid questionnaires from respondents was analyzed by SmartPLS 3.2.8. The results indicated that the features of social media including availability and symbol variety had the significant influences on their work efficiency through work-oriented usage of social media. Publicness and symbol variety had impact on work efficiency via social-oriented usage of social media. In addition, both social media for work-oriented and social-oriented usage influenced employees' work efficiency. There were different considerations when people selected social media for work or for social purpose. Managers or companies could guide their employees to use the social media in a right way to increase their work features to complete their work efficiency, and create groups for employees so the work information could be shared efficiently.

e-Health Campaigns for Promoting Influenza Vaccination: Examining Effectiveness of Fear Appeal Messages from Different Sources

Background: In recent years, influenza has become a severe disease and pandemic threat. There are more than 290,000 to 650,000 influenza-related deaths globally each year. Influenza vaccination is the best way to prevent influenza and potentially serious influenza-related complications. The current study aims to examine the effectiveness of fear-induced health campaigns on social media in promoting influenza vaccination with the focus on different sources. Methods: A 2 × 3 × 2 (visible source × receiver source × technological source) factorial online experiment was designed to investigate the effectiveness of fear appeal messages offered by different sources on social media. A total of 534 college students were recruited to participate in the experiment. Results: Individuals who receive messages from a verified visible source have greater intention to perform flu vaccination and seek flu-related information than those who acquire messages from an unverified one. Besides, visible source, receiver source, and technological source interact to affect flu-related information seeking. Conclusions: In addition to the message itself, different levels of message sources on social media should be considered for e-health campaign design, especially visible sources.