TY - JOUR
T1 - Use of Biological Feedback as a Health Behavior Change Technique in Adults
T2 - Scoping Review
AU - Richardson, Kelli M.
AU - Jospe, Michelle R.
AU - Saleh, Ahlam A.
AU - Clarke, Thanatcha Nadia
AU - Bedoya, Arianna R.
AU - Behrens, Nick
AU - Marano, Kari
AU - Cigan, Lacey
AU - Liao, Yue
AU - Scott, Eric R.
AU - Guo, Jessica S.
AU - Aguinaga, April
AU - Schembre, Susan M.
N1 - Publisher Copyright:
© 2023 Journal of Medical Internet Research. All rights reserved.
PY - 2023/1
Y1 - 2023/1
N2 - 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
AB - 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
KW - monitoring
KW - physiologic; biomarkers; feedback
KW - psychological; health behavior; health promotion; biological; adults; biosensing; technology; support; intervention; electronic database; cardiovascular disease; obesity; device
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U2 - 10.2196/44359
DO - 10.2196/44359
M3 - Review article
C2 - 37747766
AN - SCOPUS:85172425485
SN - 1439-4456
VL - 25
JO - Journal of medical Internet research
JF - Journal of medical Internet research
IS - 1
M1 - e44359
ER -