Capturing the Dynamics of the Social Environment Through Experience Sampling Methods, Passive Sensing, and Egocentric Networks: Scoping Review

Abstract

Background: 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.

Objective: 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.

Methods: We conducted a scoping review according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

Results: 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.

Conclusions: 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.

Keywords: ambulatory assessment; digital phenotyping; egocentric network; experience sampling method; mobile phone; passive measures; social context.

Figure 1

Flow diagram of the included studies (adapted from Page et al [35]). *The first number indicates the records that were identified using the first search string, which aimed to extract studies that used the experience sampling method or passive sensing, whereas the second number indicates the records that were identified using the second search string, which aimed to extract studies that used repeated egocentric networks.

Figure 2

Overview of which aspects each method captures. The example items are based on the items that were used in the selected experience sampling method (ESM) and egocentric network studies. We developed categories to summarize which aspects of the social environment were captured in the selected studies. The first column shows which aspects the ESM studies captured and how often (in percentage) those aspects were measured in the 238 selected ESM studies that only used 1 measurement. Subsequently, the second column shows how often (in percentage) different aspects were included in the 12 selected egocentric network studies. The last column shows which aspects can be potentially captured using passive sensing; as those aspects are only indirectly and often implicitly measured, we did not calculate any percentages.