Use of Biological Feedback as a Health Behavior Change Technique in Adults: Scoping Review.

BACKGROUND: Recent advancements in personal biosensing technology support the shift from standardized to personalized health interventions, whereby biological data are used to motivate health behavior change. However, the implementation of interventions using biological feedback as a behavior change technique has not been comprehensively explored. OBJECTIVE: The purpose of this review was to (1) map the domains of research where biological feedback has been used as a behavior change technique and (2) describe how it is implemented in behavior change interventions for adults. METHODS: A comprehensive systematic search strategy was used to query 5 electronic databases (Ovid MEDLINE, Elsevier Embase, Cochrane Central Register of Controlled Trials, EBSCOhost PsycINFO, and ProQuest Dissertations & Theses Global) in June 2021. Eligible studies were primary analyses of randomized controlled trials (RCTs) in adults that incorporated biological feedback as a behavior change technique. DistillerSR was used to manage the literature search and review. RESULTS: After removing 49,500 duplicates, 50,287 articles were screened and 767 articles were included. The earliest RCT was published in 1972 with a notable increase in publications after 2000. Biological feedback was most used in RCTs aimed at preventing or managing diabetes (n=233, 30.4%), cardiovascular disease (n=175, 22.8%), and obesity (n=115, 15%). Feedback was often given on multiple biomarkers and targeted multiple health behaviors. The most common biomarkers used were anthropometric measures (n=297, 38.7%), blood pressure (n=238, 31%), and glucose (n=227, 29.6%). The most targeted behaviors were diet (n=472, 61.5%), physical activity (n=417, 54.4%), and smoking reduction (n=154, 20.1%). The frequency and type of communication by which biological feedback was provided varied by the method of biomarker measurement. Of the 493 (64.3%) studies where participants self-measured their biomarker, 476 (96.6%) received feedback multiple times over the intervention and 468 (94.9%) received feedback through a biosensing device. CONCLUSIONS: Biological feedback is increasingly being used to motivate behavior change, particularly where relevant biomarkers can be readily assessed. Yet, the methods by which biological feedback is operationalized in intervention research varied, and its effectiveness remains unclear. This scoping review serves as the foundation for developing a guiding framework for effectively implementing biological feedback as a behavior change technique. TRIAL REGISTRATION: Open Science Framework Registries; https://doi.org/10.17605/OSF.IO/YP5WAd. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/32579.

Adding a Brief Continuous Glucose Monitoring Intervention to the National Diabetes Prevention Program: A Multimethod Feasibility Study.

The National Diabetes Prevention Program (DPP) promotes lifestyle changes to prevent diabetes. However, only one-third of DPP participants achieve weight loss goals, and changes in diet are limited. Continuous glucose monitoring (CGM) has shown potential to raise awareness about the effects of diet and activity on glucose among people with diabetes, yet the feasibility of including CGM in behavioral interventions for people with prediabetes has not been explored. This study assessed the feasibility of adding a brief CGM intervention to the Arizona Cooperative Extension National DPP. Extension DPP participants were invited to participate in a single CGM-based education session and subsequent 10-day CGM wear period, during which participants reflected on diet and physical activity behaviors occurring prior to and after hyperglycemic events. Following the intervention, participants completed a CGM acceptability survey and participated in a focus group reflecting on facilitators and barriers to CGM use and its utility as a behavior change tool. A priori feasibility benchmarks included opt-in participation rates ≥ 50%, education session attendance ≥ 80%, acceptability scores ≥ 80%, and greater advantages than disadvantages of CGM emerging from focus groups, as analyzed using the Key Point Summary (KPS) method. Thirty-five DPP members were invited to participate; 27 (77%) consented, and 24 of 27 (89%) attended the brief CGM education session. Median survey scores indicated high acceptability of CGM (median = 5, range = 1-5), with nearly all (n = 23/24, 96%) participants believing that CGM should be offered as part of the DPP. In focus groups, participants described how CGM helped them make behavior changes to improve their glucose (e.g., reduced portion sizes, increased activity around eating events, and meditation). In conclusion, adding a single CGM-based education session and 10-day CGM wear to the DPP was feasible and acceptable. Future research will establish the efficacy of adding CGM to the DPP on participant health outcomes and behaviors.

Exploring the Impact of Dawn Phenomenon on Glucose-Guided Eating Thresholds in Individuals With Type 2 Diabetes Using Continuous Glucose Monitoring: Observational Study.

BACKGROUND: Glucose-guided eating (GGE) improves metabolic markers of chronic disease risk, including insulin resistance, in adults without diabetes. GGE is a timed eating paradigm that relies on experiencing feelings of hunger and having a preprandial glucose level below a personalized threshold computed from 2 consecutive morning fasting glucose levels. The dawn phenomenon (DP), which results in elevated morning preprandial glucose levels, could cause typically derived GGE thresholds to be unacceptable or ineffective among people with type 2 diabetes (T2DM). OBJECTIVE: The aim of this study is to quantify the incidence and day-to-day variability in the magnitude of DP and examine its effect on morning preprandial glucose levels as a preliminary test of the feasibility of GGE in adults with T2DM. METHODS: Study participants wore a single-blinded Dexcom G6 Pro continuous glucose monitoring (CGM) system for up to 10 days. First and last eating times and any overnight eating were reported using daily surveys over the study duration. DP was expressed as a dichotomous variable at the day level (DP day vs non-DP day) and as a continuous variable reflecting the percent of days DP was experienced on a valid day. A valid day was defined as having no reported overnight eating (between midnight and 6 AM). ∂ Glucose was computed as the difference in nocturnal glucose nadir (between midnight and 6 AM) to morning preprandial glucose levels. ∂ Glucose ≥20 mg/dL constituted a DP day. Using multilevel modeling, we examined the between- and within-person effects of DP on morning preprandial glucose and the effect of evening eating times on DP. RESULTS: In total, 21 adults (59% female; 13/21, 62%) with non-insulin-treated T2DM wore a CGM for an average of 10.5 (SD 1.1) days. Twenty out of 21 participants (95%) experienced DP for at least 1 day, with an average of 51% of days (SD 27.2; range 0%-100%). The mean ∂ glucose was 23.7 (SD 13.2) mg/dL. People who experience DP more frequently had a morning preprandial glucose level that was 54.1 (95% CI 17.0-83.9; P<.001) mg/dL higher than those who experienced DP less frequently. For within-person effect, morning preprandial glucose levels were 12.1 (95% CI 6.3-17.8; P=.008) mg/dL higher on a DP day than on a non-DP day. The association between ∂ glucose and preprandial glucose levels was 0.50 (95% CI 0.37-0.60; P<.001). There was no effect of the last eating time on DP. CONCLUSIONS: DP was experienced by most study participants regardless of last eating times. The magnitude of the within-person effect of DP on morning preprandial glucose levels was meaningful in the context of GGE. Alternative approaches for determining acceptable and effective GGE thresholds for people with T2DM should be explored and evaluated.