JMIR Publications

ABSTRACT

Background:

Ecological momentary assessment (EMA) is a tool that captures emotional states, experiences, and behaviors in real or near-real time. Concurrent EMA and continuous glucose monitoring (CGM) data can provide an in-depth understanding of the impacts of psychosocial factors on momentary glucose levels. However, study methodology varies widely for EMA and CGM data collection and analysis.

Objective:

The goal of this scoping review was to summarize the objectives, methodologies, and outcomes of studies analyzing concurrent biopsychosocial EMA and CGM data in diabetes.

Methods:

This study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. Original research studies evaluating participants with diabetes with concurrent collection and analysis of EMA and CGM data were included in this review. One-hundred and six studies were identified from PubMed, Embase, and EBSCOhost from May 2009-Jan 2025 using the key terms “ecological momentary assessment”, “blood glucose self-monitoring,” “diabetes mellitus”, or “glucose monitoring.” From these, duplicates, non-original research articles, and articles not measuring concurrent EMA and CGM data were excluded for a total of thirteen studies included in this review. Methodological data was abstracted and summarized, including study characteristics, EMA protocols and outcomes, CGM outcomes, and integrated EMA and CGM study objectives.

Results:

Twelve of the thirteen studies primarily recruited adult populations and the majority of these studies (69%) included participants with the type 1 diabetes. The median EMA delivery duration was 14 days (range 3-18) with a median of 5 prompts delivered per day (range 1-28). EMA outcomes included a broad spectrum of biopsychosocial factors including emotion, self-care behaviors, interpersonal interactions, symptoms, and cognition. Nine of thirteen studies (69%) analyzed blinded CGM data. CGM data was analyzed for a median of 14 days (range 3-18 days). Fifty-four percent of studies utilized standard CGM glucose metrics (mean glucose, time in range, coefficient of variation and standard deviation). Other outcomes included non-standard measures as surrogate markers for eating patterns (binge-eating or restrictive eating) or hypoglycemic events. Integrated EMA and CGM data analysis answered a wide range of study objectives including the impact of psychosocial factors on momentary glucose metrics; the influence of momentary glucose on emotional states, mood, personal behaviors, sleep, and cognition; and study protocol or mobile application optimization among others.

Conclusions:

This review provides a detailed summary of the methodology and outcomes of original research articles utilizing combined EMA and blood glucose data measured via CGM. These combined methods allow for an opportunity to elucidate relationships between psychosocial factors with momentary glucose, an understanding of which is imperative for the development of future psychological and behavioral interventions in diabetes. However, standardization of protocols for future EMA and CGM data collection and analysis are needed to ensure data accuracy and reproducibility. Clinical Trial: Not applicable.