Online social media fatigue and psychological wellbeing—A study of compulsive use, fear of missing out, fatigue, anxiety and depression

https://doi.org/10.1016/j.ijinfomgt.2018.01.012Get rights and content

Highlights

  • Stressor-strain-outcome (SSO) framework was utilised to understand media fatigue.

  • Relationship between psychosocial well-being and social media fatigue was examined.

  • Repeated cross-sectional surveys (N = 1554, 1144) with adolescents were utilised.

  • Compulsive social media use positively predicted tendency to experience fatigue.

  • Social media fatigue was linked to high anxiety and depression among adolescents.

  • Compulsive media use mediates between fear of missing out and social media fatigue.

Abstract

The constant development of online social media features and related services has constantly attracted and increased the number of social media users. But, at the same time, a myriad of users have deviated themselves, temporarily or permanently, from social media use due to social media fatigue. Scholars have investigated different antecedents and consequences of social media fatigue. However, empirical relationships between psychosocial wellbeing and social media fatigue are currently not known. To bridge this gap, the current study utilises the stressor-strain-outcome framework (SSO) to examine whether psychosocial wellbeing measures, such as compulsive media use and fear of missing out, trigger fatigue and, furthermore, whether social media fatigue results in anxiety and depression. The study utilised repeated cross-sectional methodology whereby two waves of data (N = 1554, 1144) were collected to test the research model with adolescent social media users in India. The study findings suggest that compulsive media use significantly triggered social media fatigue, which later result in elevated anxiety and depression. Fear of missing out indirectly predicted social media fatigue through mediation of compulsive social media use. The theoretical and practical implications, limitations of the present study and agenda for future studies are presented and discussed.

Introduction

An increasing number of social media users are straying from their participation on social media because of encountering social media fatigue (Guest Post, 2017). Prior research has defined social media fatigue as a situation whereby social media users suffer from mental exhaustion after experiencing various technological, informative and communicative overloads through their participation and interactions on the different online social media platforms (Bright, Kleiser, & Grau, 2015; Lee, Son, & Kim, 2016; Ravindran, Kuan, Chua, & Hoe Lian, 2014; Zhang, Zhao, Lu, & Yang, 2016).

This phenomenon has recently motivated scholars from around the world to conduct empirical investigations to determine the antecedents and consequences of social media fatigue (Cramer, Song, & Drent, 2016; Luqman, Cao, Ali, Masood, & Yu, 2017; Sasaki, Kawai, & Kitamura, 2016; Yoa & Cao, 2017). The relative determinants of social media fatigue can be stemmed from psychological and behavioural stress-related conditions, such as information overload and connection overload as well as social interactive activities (Bright et al., 2015; LaRose, Connololy, Lee, Li, & Hales, 2014; Lim, Park, Iijima, & Ahn, 2017; Walton, 2017; Zhang, Zhao, Lu, & Yang 2016). Due to this emotional suffering, social media users are likely to refrain, either temporarily or permanently, from participating in online social media interactions (Oghuma, Libaque-Saenz, Wong, & Chang, 2016; Swar, Hameed, & Reychav, 2017).

Scholars argue that social media fatigue has significant negative implications for both users as well as the businesses and service operators (Oghuma et al., 2016; Shin & Shin, 2016). On a user level, social media fatigue results in deterioration in both mental and physiological strengths whereby users are likely to develop unhealthy behaviours (Choi & Lim, 2016; Shin & Shin, 2016; Sun et al., 2017). Similarly, social media fatigue can be detrimental for businesses and service operators because fatigue results in withdrawal from service use, which translates into lower profits for companies and service operators. Despite these serious implications, research examining social media fatigue is still in its early stage wherein most existing studies have exclusively focused on its relationship with frequency of service use, service satisfaction, privacy, discontinuity, excessive social media use, social media exhaustion and technostress, as well as technology and physical overload (see Table 1). In comparison to this body of literature, the relationship between psychosocial wellbeing and social media fatigue has not yet been well-studied. This gap is addressed by the present study, which utilises a repeated cross-sectional research methodology to investigate this relationship over time. Two waves of cross-sectional data sets were collected in May 2017 (N = 1554) and September 2017 (N = 1144) with adolescent social media users. The current study investigates whether compulsive social media use and fear of missing out among adolescent social media users trigger social media fatigue? Furthermore, whether social media fatigue contributes to increase in anxiety and depression among adolescent social media users.

The current study also addresses three main limitations in the prior literature on social media fatigue, namely limited focus on specific age and cultural groups, and exclusive focus on single shot studies (i.e. cross-sectional surveys at a single point of time). Our review of prior literature revealed that the main focus has been on university-attending young-adults, either from the Western world or East Asian countries. In comparison to this, adolescent social media users from developing countries, such as India, are rarely studied. Similarly, most prior studies are purely cross-sectional in nature wherein data are collected at a single point of time. To address these limitations, the current study utilised repeated cross-sectional studies whereby the same measures were evaluated with similar target user groups over time, i.e., data were collected twice over a period of five months. Furthermore, the study focused on adolescents in a lesser studied cultural and demographic group of social media users. The study concluded with significant theoretical and practical implications for scholars as well as practitioners.

Section snippets

Social media fatigue

A systematic review of prior social media fatigue literature was performed (see Table 1). Prior studies on social media fatigue have looked into two types of online social media, namely online social networking sites (e.g., Facebook) and mobile instant messengers (e.g., KakaoTalk) (Bright et al., 2015; Chen & Lee, 2013; Ravindran et al., 2014; Shin & Shin, 2016). Most of the prior studies were conducted in industrialised Asian countries, for example South Korea, Taiwan, Japan and China (Lee,

Research model

Prior literature has utilised different theoretical frameworks for studying social media fatigue, including the limited capacity model (LCM), the stressor-strain-outcome (SSO) model and the transactional theory of stress and coping (TTSC), in order to determine causal relationships and consequences in relation to social media fatigue (Blabst & Diefenbach, 2017; Bright et al., 2015; Lee, Chou et al., 2014; Lee, Son et al., 2016; Lim et al., 2017; Luqman et al., 2017; Zhang et al., 2016). In the

Measurement model

A confirmatory factor analysis (CFA) using the measurement model was performed to evaluate the model fit by utilising different goodness of model fit indices. A good model fit suggests that the theoretical model fits well with empirical data. Scholars have suggested different threshold values for goodness of model fit indices for demonstrating good model fit, namely Chi-square/degree of freedom (X2/df) > 3, Comparative Fit Index (CFI) ≥ 0.95, Tucker–Lewis Index (TLI) ≥ 0.95, and Root Mean

Discussion

Prior literature has examined the different antecedents and consequences or outcomes of social media fatigue. However, the empirical linkages between psychosocial wellbeing and social media fatigue were not known. This gap is addressed by the current study using the stressor-strain-outcome (SSO) framework. This study utilised repeated cross-sectional methodology, which consisted of two large cross-sectional surveys with adolescent social media users, separated over a period of five months. Two

Study implications

The present study findings have several theoretical and practical implications. The theoretical implications are as follows: First, prior literature has not yet examined the psychosocial wellbeing related aspects of social media fatigue. Therefore, the present study is possibly the first empirical study that has examined them, thus significantly contributing to theory development as well as prior mushrooming literature on social media fatigue. Second, the outcomes or consequences of social

Study limitations and future work

The present study findings and related implications should be considered in the light of four important limitations. First, since the data were collected in one specific country and with one age group (i.e., adolescents), it is suspected that current findings may change if other age groups and cultural backgrounds are considered. To address this limitation, we encourage other scholars to validate a similar research model with other age and cultural groups. Second, the present study only focused

Conclusion

Social media is a popular informative and communicative platform among users across the globe. Despite the various positive outcomes which are beneficial to users in various aspects in life, negative consequences due to excessive social media use are also ineviTable Social media fatigue is a prevalent factor which negatively influences users’ mental and behavioural conditions. The present study has examined the relationship between social media fatigue and psychosocial wellbeing by utilising

Acknowledgements

This study was financially supported by Academy of Finland mobility grants (Decision No 318452, 311191, 298098). We like to sincerely thank Professor Cathy Weng from National Taiwan University of Science & Technology (NTUST), Taiwan for providing insightful feedback that helped us in preparing this manuscript.

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