Toward a classification of technology design features promoting potentially addictive online behaviors

Background: Over the past two decades, the evolution of information and communication technologies (ICTs) has transformed various facets of people’s everyday life, offering benefits alongside emerging concerns related to problematic or addictive-like patterns of involvement in online activities enabled by contemporary digital devices. While gaming disorder has been formally acknowledged as an addictive disorder in the ICD-11, other potentially problematic online behaviors have been discussed as possible further candidates. Accordingly, better understanding the nature of the psychological mechanisms underlying their development and maintenance has been the focus of numerous research efforts in recent years. However, related studies generally overlook the fact that service providers have purposefully designed deeply absorbing or addictive online settings aimed at enhancing ICTs users retention on their web-based applications and platforms. It was recently suggested, therefore, to start exploring the extent to which technology design features contribute to problematic online behaviors by challenging ICTs users' self-control abilities. Methods: We reviewed the available evidence on the relationships between technology design features and loss of control in various online activities, including online video gaming, online gambling, cybersexual activities, online buying-shopping, social networking, and on-demand streaming of TV series. Based on reinforcement learning and behavioral control theories, we then proposed a theory-driven taxonomy of design features of online applications that facilitate dysregulated and potentially addictive online behaviors. Results: The identified design features were classified in six theory-informed categories including 1) reinforcement schedules (e.g., like feature, infinite scrolling); 2) personalized triggers (e.g., personalized recommendations, machine learning-based algorithms); 3) overvaluation of positive outcomes (e.g., graphics and sounds, chat settings); 4) features that interfere with reflection or deliberation (e.g., time-limited events, promotions); 5) partial goal fulfilment (e.g., rewards and points programmes, progress bar); and 6) features boosting cognitive bias (e.g., persistent online environment, temporarily available information). Conclusions: By emphasizing common psychological mechanisms contributing to the development of potentially addictive online behaviors (e.g., fear of missing out, social-oriented motivations, negative reinforcement mechanisms for emotionally vulnerable individuals or people experiencing distress) - and highlighting the specific design features that promote such mechanisms in online activities - the current taxonomy enriches the understanding of the underlying drivers of problematic and addictive involvement in online activities, which can be applied to prevention and intervention efforts.