Preventing relapse to information technology addiction through weakening reinforcement: A self-regulation perspective
Introduction
While advancements in information technology (IT) provide real benefits to various areas of life such as recreation, e-commerce, and telecommuting [e.g., [1], [2], [3]], addictive behaviors may also emerge. In line with previous research [e.g., 4], IT addiction describes a psychological state of maladaptive dependency on using a technology. When people become addicted, they may suffer from many unwanted consequences. For instance, addiction to social networking sites is shown to foster task distraction, which further impairs work performance [5]. WeChat (a popular social networking tool in China) addiction, as another form of IT addiction, is found to be harmful to users’ mental, physical, and social health [6]. Realizing the misery of such consequences is likely to impel addicts to quit addiction [7].
Meanwhile, previous research has indicated that addicts who have reduced their usage to a normal level may easily fall into an addictive state again, and IT addicts show a similar high rate of relapse [8]. For instance, much evidence has shown that the relapse rate among alcoholics can be as high as 95% [9]. Anecdotal evidence1 also shows that over two-thirds of heavy IT addicts cannot completely eliminate their addiction. It indicates that addictive behaviors emerge repeatedly, even many interventions are provided. The serious outcomes of relapse to IT addiction should not be ignored. A recent social news2 showed that students who have ever performed satisfactorily are dismissed from universities due to a relapse to IT addiction after a three-month quitting effort to quit. Generally, the term “relapse” describes the tendency to revert to previous patterns of excessive use after periods of control or abstinence [10]. Relapse signifies that previous efforts to overcome addiction have been ineffective, which indicates the failure of recovery approaches. Only addicts who completely desist from their addiction without relapse can be considered as having a successful recovery approach [11]. Given that relapse poses a great challenge for successful recovery approaches of IT addiction, it is important to discern how to effectively prevent it.
In recent years, scholars have shown increasing concerns over IT addiction. Unlike earlier studies which have traditionally assumed IT usage is positive and beneficial to users [e.g., 12], new research efforts have started to examine the dark side of using ITs. Studies have emphasized the negative consequences of IT use [e.g., 13], explored ways to measure IT addiction [14], and revealed predictors of these issues [e.g., 15]. However, despite considerable merits of these studies, more efforts are needed to deepen our knowledge about IT addiction, as what has been achieved with research on substance addiction.
Many studies have attempted to reveal factors for preventing relapse to substance addiction [e.g., 16]. In contrast, little research has been undertaken on relapse to IT addiction. The need for enriching the understanding of this area has become progressively urgent, as the relapse problem grows larger and implies more failure or ineffectiveness of previous interventions. Noting these limitations in information systems (IS) research has convinced us that a conceptualization of relapse to IT addiction and an interpretation of the prevention process can help to fill the gaps in the literature and contribute to providing effective interventions.
Accordingly, this study aims to first conceptualize relapse to IT addiction based on a review of previous research. As relapse prevention has been regarded as a process of self-regulation [16, 18], we use a self-regulation perspective to identify methods for preventing relapse through weakening reinforcement, which is a key mechanism in the formation of addiction and relapse. Other factors that may predict addiction are controlled in our research model. A longitudinal survey is conducted. Finally, we discuss the theoretical and practical implications of our findings.
Section snippets
IT addiction
Compared with a lot of research that addresses the positive aspects of IT use [e.g., [19], [20], [21], [22]], scientific understandings on IT addiction are still evolving. Our review shows that the main literature can be classified into three categories (see Table 1).
Several studies have attempted to propose a number of symptoms to identify IT addiction. Pathological symptoms including behavioral salience, withdrawal symptoms, conflict, relapse and reinstatement can be used to differentiate
Research model and hypotheses
Building upon previous research and existing theories of self-regulation, we develop a model to explain how relapse to IT addiction can be effectively prevented. Then, we investigate how two forms of self-regulation (i.e., self-control and mindfulness) operate to reduce urges related to avoidance and approach, which are treated as two principal reinforcements of relapse. Fig. 1 depicts our research model.
Procedure and sample
Smartphone game addiction has been treated as a prevalent form of IT addiction [164]. For instance, nearly 15 million users in Western countries are shown to be addicted to a smartphone game called Candy Crush Saga [15]. Addiction to smartphone games is often associated with detrimental consequences, such as psychology and physiology disorders as well as conflicts [15,165]. In this study, we examine our research model in the context of smartphone game addiction.
Relapse occurs after quitting for
Measurement model
We adopted SmartPLS 3.0 to estimate our research model[172]. Mindfulness was measured as a second-order aggregated construct, with factor scores generated from its first-order constructs. The resulting scores were used as formative items of the aggregated construct [174]. To analyze the validity of mindfulness, we assessed its items’ weights. We found that the items were all significant, except for “describing” (t = -0.032). Item weights reflected the relative signification of formative items
Discussion
This study aims to enhance our understanding toward preventing relapse to IT addiction. Given that relapse prevention is often a self-management program [17], we apply a self-regulatory perspective to identify factors that help to prevent relapse. The proposed research model is analyzed in the context of smartphone game addiction, which is a common and representative form of IT addiction. Regarding the reinforcement mechanisms of relapse, our findings show that both avoidance urge (i.e.,
Conclusions
The goals of this study are to understand the concept of relapse into IT addiction, and to empirically investigate how to prevent such relapse by identifying valuable prevention factors. We propose a research model based on the self-regulation perspective. Our longitudinal survey study collects data from two different time points for validating the proposed hypotheses empirically. Our results provide strong evidence that both negative and positive reinforcements can evoke relapse. Meanwhile,
Funding sources
The work described in this study was supported by grants from the National Natural Science Foundation of China (Nos 71801166, 72001168, 72071137), the Philosophy and Social Science Research in Colleges and Universities of Jiangsu Province (No. 2020SJZDA086), and Research Grants Council of the Hong Kong Special Administrative Region, China (No. CityU 11508917).
CRediT authorship contribution statement
Chongyang Chen: Conceptualization, Methodology, Formal analysis, Investigation, Writing – original draft, Funding acquisition. Kem Z.K. Zhang: Conceptualization, Methodology, Writing – review & editing, Funding acquisition. Xiang Gong: Writing – review & editing. Matthew K.O. Lee: Supervision, Funding acquisition. Yao-Yu Wang: Funding acquisition.
Chongyang Chen is an Associate Professor at Zhejiang University of Finance & Economics. She received her PhD in Information Systems from the joint PhD program between the University of Science and Technology of China and City University of Hong Kong. Her research interests include IT adoption, the dark side of IT usage, and electronic commerce. Her research has been published in international journals and conferences, such as Information & Management, Information Systems Journal, International
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Chongyang Chen is an Associate Professor at Zhejiang University of Finance & Economics. She received her PhD in Information Systems from the joint PhD program between the University of Science and Technology of China and City University of Hong Kong. Her research interests include IT adoption, the dark side of IT usage, and electronic commerce. Her research has been published in international journals and conferences, such as Information & Management, Information Systems Journal, International Journal of Information Management, Computers in Human Behavior, Internet Research, International Conference on Information Systems, Hawaii International Conference on System Sciences, and Pacific Asia Conference on Information Systems.
Kem Z.K. Zhang is a faculty member in the Faculty of Business Administration, Lakehead University, Canada. He received his PhD in Information Systems from the joint PhD program between the University of Science and Technology of China and City University of Hong Kong. His research interests include electronic commerce and human behaviors in emerging social media. He has published papers in a number of journals, such as Information Systems Journal, Information & Management, Decision Support Systems, Journal of the Association for Information Science and Technology, Computers in Human Behavior, International Journal of Information Management, Electronic Commerce Research and Applications, and Journal of Electronic Commerce Research.
Xiang Gong is an Associate Professor at the Xi'an Jiaotong University. He received his PhD in Information Systems from the joint PhD program between the University of Science and Technology of China and City University of Hong Kong. His research interests include IT adoption and usage, dark side of using IT, and sharing economy. His research has been published in international journals and conferences, such as Information & Management, International Journal of Information Management, Internet Research, and Pacific Asia Conference on Information Systems.
Matthew K.O. Lee is Chair Professor of Information Systems & E-Commerce at the College of Business, City University of Hong Kong. He holds a PhD degree from the University of Manchester in the UK, and he is a qualified Barrister-at-Law, a Chartered Engineer (UK Engineering Council), and a professional member of the British Computer Society. Professor Lee has a research and professional interest in IT-based innovation adoption and diffusion (focusing on systems implementation management issues), knowledge management, social computing, electronic commerce, and legal informatics. Professor Lee's publications in the information systems and electronic commerce areas include a book as well as over one hundred refereed articles in international journals, conference proceedings, and research textbooks. His work has appeared in leading journals such as MIS Quarterly, Journal of MIS, Communications of the ACM, and the Journal of International Business Studies. Professor Lee also serves on the editorial board of several research journals in the field.
Yao-Yu Wang received the PhD degree from the City University of Hong Kong, and University of Science and Technology of China. He is a professor of Management Science and Engineering at the Soochow University, Suzhou, Jiangsu, China. His research interests include operations and supply chain management, and decision analysis. He has published more than 20 papers in journals such as Information and Management, IEEE Transactions on Engineering Management, European Journal of Operational Research, Computers & Operations Research, International Journal of Production Research, Journal of the Operational Research Society, and Computers & Industrial Engineering.