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.



中文翻译：

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互联网活动在多大程度上能预测心理健康？

背景：健康的互联网活动（例如，利用电子健康和在线治疗）与幸福感呈正相关。然而，不健康的互联网活动（过多的在线时间、有问题的互联网使用/PIU、互联网依赖/ID 等）与幸福感下降、孤独感和其他相关负面方面有关。虽然大多数证据是相关的，但一些研究还表明，互联网活动可以预测幸福感。
目的：本文的目的是通过（a）范围审查和（b）对互联网活动和心理相互关系建模的理论理解，详细阐述互联网活动在多大程度上预测心理健康的问题。福利。
方法：我们使用搜索词“互联网”或“应用程序”或“数字”或“在线”或“移动应用程序”和“使用”或“活动”或“行为”或“参与度”搜索了不同的电子数据库，例如 Web of Science ”和“幸福”或“孤独”（a，范围审查）或 CCAM（b，理论理解）。
结果：范围审查 (a) 总结了最近的发现：互联网活动对幸福感的预测程度取决于互联网活动本身：促进自我管理的互联网活动有益于幸福感，但过多的互联网活动、PIU 和 ID对健康有害。要了解 (b) 互联网活动为何、何时以及如何预测幸福感，需要理论理解和模型。虽然存在关于幸福感或互联网活动的理论，但在考虑其他行为的同时考虑这两个方面的理论并不多。一种这样的理论是补偿性遗留行动模型（CCAM），它描述了互联网使用如何与其他生活方式行为和幸福相关的机制，并且个人受到 CCAM 中采用和保持幸福的目标的驱动——也称为更高层次的目标。很少有研究测试 CCAM 或它的选定方面，包括互联网活动和幸福感。结果证明了这种多因素、复杂的方法的潜力：它可以帮助在人口变化和卫生保健系统缺乏人力资源的情况下改善健康促进。
结论和建议：对未来研究的建议是采用 CCAM 等理论方法和测试干预效果，以及支持不同环境中的个人。主要目标应该是开展健康的互联网活动以支持幸福感，并防止不健康的互联网活动。因此，行为管理和学习应旨在防止有问题的互联网使用和互联网依赖。