Lippke Sonia, Dahmen Alina, Gao Lingling, Guza Endi, Nigg Claudio R
Department of Psychology & Methods/Focus Area Diversity, Jacobs University Bremen gGmbH, Bremen, 28759, Germany.
Dr. Becker Klinikgruppe, Cologne, 50968, Germany.
Psychol Res Behav Manag. 2021 Feb 19;14:207-219. doi: 10.2147/PRBM.S274502. eCollection 2021.
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.
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.
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).
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.
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.
健康的网络活动（例如，利用电子健康和在线治疗）与幸福感呈正相关。然而，不健康的网络活动（上网时间过长、网络使用问题/PIU、网络依赖/ID等）与幸福感降低、孤独感以及其他相关负面因素有关。虽然大多数证据是相关性的，但一些研究也表明网络活动可以预测幸福感。
本文旨在通过（a）范围综述和（b）对网络活动与心理健康之间相互关系进行建模的理论理解，详细阐述网络活动在多大程度上可以预测心理健康。
我们通过使用搜索词“互联网”或“应用程序”或“数字”或“在线”或“移动应用程序”以及“使用”或“活动”或“行为”或“参与”以及“幸福感”或“孤独感”，在不同的电子数据库（如科学网）中进行搜索，用于（a，范围综述）或CCAM用于（b，理论理解）。
范围综述（a）总结了近期的研究结果：网络活动对幸福感的预测程度取决于网络活动本身：促进自我管理的网络活动对幸福感有益，但过多的网络活动、PIU和ID对幸福感有害。为了理解（b）为什么、何时以及网络活动如何预测幸福感，需要理论理解和一个模型。虽然存在关于幸福感或网络活动的理论，但很少有理论同时考虑这两个方面并兼顾其他行为。其中一个这样的理论是补偿性延续行动模型（CCAM），它描述了网络使用与其他生活方式行为和幸福感之间的关系机制，并且在CCAM中，个体受到采用和维持幸福感这一目标的驱动——也称为高级目标。很少有研究测试CCAM或其选定的方面，其中包括网络活动和幸福感。结果证明了这种多因素、复杂方法的潜力：它可以帮助在人口结构变化时期以及医疗保健系统缺乏人力资源的情况下改善健康促进工作。
对未来研究的建议是采用像CCAM这样的理论方法并测试干预效果，并在不同环境中支持个体。主要目标应该是进行健康的网络活动以支持幸福感，并预防不健康的网络活动。行为管理和学习因此应该旨在预防有问题的网络使用和网络依赖。
