To what extent is internet activity predictive of psychological well-being?

Abstract

Background: Healthy internet activity (eg, making use of eHealth and online therapy) is positively associated with well-being. However, unhealthy internet activity (too much online time, problematic internet use/PIU, internet dependency/ID, etc.) is associated with reduced well-being, loneliness, and other related negative aspects. While most of the evidence is correlational, some research also shows that internet activity can be predictive for well-being. Objective: The aim of this article is to elaborate on the question as to what extent internet activity is predictive of psychological well-being by means of (a) a scoping review and (b) theoretical understanding which model the interrelation of internet activity and psychological well-being. Methodology: We searched different electronic databases such as Web of Science by using the search terms “Internet” OR “App” OR “digital” OR “online” OR “mobile application” AND “Use” OR “Activity” OR “Behavior” OR “Engagement” AND “Well-being” OR “Loneliness” for (a, the scoping review) or CCAM for (b, the theoretical understanding). Results: The scoping review (a) summarizes recent findings: the extent to which internet activity is predictive for well-being depends on the internet activity itself: internet activity facilitating self-management is beneficial for well-being but too much internet activity, PIU and ID are detrimental to well-being. To understand (b) why, when and how internet activity is predictive for well-being, theoretical understanding and a model are required. While theories on either well-being or internet activity exist, not many theories take both aspects into account while also considering other behaviors. One such theory is the Compensatory Carry-Over Action Model (CCAM) which describes mechanisms on how internet use is related to other lifestyle behaviors and well-being, and that individuals are driven by the goal to adopt and maintain well-being-also called higher-level goals – in the CCAM. There are few studies testing the CCAM or selected aspects of it which include internet activity and well-being. Results demonstrate the potentials of such a multifactorial, sophisticated approach: it can help to improve health promotion in times of demographic change and in situations of lacking personnel resources in health care systems. Conclusion and Recommendation: Suggestions for future research are to employ theoretical approaches like the CCAM and testing intervention effects, as well as supporting individuals in different settings. The main aim should be to perform healthy internet activities to support well-being, and to prevent unhealthy internet activity. Behavior management and learning should accordingly aim at preventing problematic internet use and internet dependency.