Langener Anna M, Stulp Gert, Kas Martien J, Bringmann Laura F
Groningen Institute for Evolutionary Life Sciences, Groningen, Netherlands.
Department of Sociology, Faculty of Behavioural and Social Sciences, University of Groningen & Inter-University Center for Social Science Theory and Methodology, Groningen, Netherlands.
JMIR Ment Health. 2023 Mar 17;10:e42646. doi: 10.2196/42646.
Social interactions are important for well-being, and therefore, researchers are increasingly attempting to capture people's social environment. Many different disciplines have developed tools to measure the social environment, which can be highly variable over time. The experience sampling method (ESM) is often used in psychology to study the dynamics within a person and the social environment. In addition, passive sensing is often used to capture social behavior via sensors from smartphones or other wearable devices. Furthermore, sociologists use egocentric networks to track how social relationships are changing. Each of these methods is likely to tap into different but important parts of people's social environment. Thus far, the development and implementation of these methods have occurred mostly separately from each other.
Our aim was to synthesize the literature on how these methods are currently used to capture the changing social environment in relation to well-being and assess how to best combine these methods to study well-being.
We conducted a scoping review according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.
We included 275 studies. In total, 3 important points follow from our review. First, each method captures a different but important part of the social environment at a different temporal resolution. Second, measures are rarely validated (>70% of ESM studies and 50% of passive sensing studies were not validated), which undermines the robustness of the conclusions drawn. Third, a combination of methods is currently lacking (only 15/275, 5.5% of the studies combined ESM and passive sensing, and no studies combined all 3 methods) but is essential in understanding well-being.
We highlight that the practice of using poorly validated measures hampers progress in understanding the relationship between the changing social environment and well-being. We conclude that different methods should be combined more often to reduce the participants' burden and form a holistic perspective on the social environment.
社交互动对幸福感很重要，因此，研究人员越来越多地尝试捕捉人们的社交环境。许多不同学科都开发了测量社交环境的工具，而社交环境会随时间发生很大变化。经验取样法（ESM）常用于心理学研究个体内部和社交环境的动态变化。此外，被动传感通常用于通过智能手机或其他可穿戴设备的传感器捕捉社交行为。此外，社会学家使用自我中心网络来追踪社会关系是如何变化的。这些方法中的每一种都可能涉及人们社交环境中不同但重要的部分。到目前为止，这些方法的开发和实施大多是相互独立进行的。
我们的目的是综合有关这些方法目前如何用于捕捉与幸福感相关的不断变化的社交环境的文献，并评估如何最好地结合这些方法来研究幸福感。
我们根据PRISMA（系统评价和Meta分析的首选报告项目）指南进行了一项范围综述。
我们纳入了275项研究。我们的综述总共得出了3个要点。第一，每种方法都以不同的时间分辨率捕捉社交环境中不同但重要的部分。第二，测量方法很少经过验证（超过70%的ESM研究和50%的被动传感研究未经验证），这削弱了所得结论的稳健性。第三，目前缺乏方法的组合（只有15/275，即5.5%的研究将ESM和被动传感结合使用，没有研究将所有三种方法结合使用），但这对于理解幸福感至关重要。
我们强调，使用未充分验证的测量方法的做法阻碍了我们在理解不断变化的社交环境与幸福感之间关系方面的进展。我们得出结论，应该更频繁地结合不同方法，以减轻参与者的负担，并形成对社交环境的整体看法。
