TY - JOUR
T1 - User engagement with smartphone apps and cardiovascular disease risk factor outcomes
T2 - Systematic review
AU - Spaulding, Erin M.
AU - Marvel, Francoise A.
AU - Piasecki, Rebecca J.
AU - Martin, Seth S.
AU - Allen, Jerilyn K.
N1 - Funding Information:
FM and SM are founders of and hold equity in the Corrie Digital Health platform. This arrangement has been reviewed and approved by Johns Hopkins University in accordance with its conflict of interest policies. The MiCORE study at Johns Hopkins (PI: SM) testing the Corrie Digital Health platform has received material support from Apple and iHealth and funding from the Maryland Innovation Initiative, Wallace H. Coulter Translational Research Partnership, Louis B. Thalheimer Fund, and Johns Hopkins Individualized Health Initiative. In addition to the above funding for the MiCORE study, SM has received research support from the American Heart Association (20SFRN35380046 and COVID19-811000), PCORI (ME-2019C1-15328), National Institutes of Health (P01 HL108800), Aetna Foundation, the David and June Trone Family Foundation, the Pollin Digital Innovation Fund, PJ Schafer Cardiovascular Research Fund, CASCADE FH, and Google. ES, RP, and JA have no conflicts of interest to declare.
Funding Information:
ES received the following financial support for the research, authorship, and publication of this paper: NIH/NHLBI T32 HL007024 Postdoctoral Fellowship in Cardiovascular Epidemiology Institutional Training, NIH/NINR F31 NR017328 Ruth L. Kirschstein National Research Service Award, and NIH/NINR T32 NR012704 Pre-Doctoral Fellowship in Interdisciplinary Cardiovascular Health Research. RP has received the following financial support for the research, authorship, and publication of this paper: NIH/NINR F31 NR018362 Ruth L. Kirschstein National Research Service Award.
Publisher Copyright:
© Erin M Spaulding, Francoise A Marvel, Rebecca J Piasecki, Seth S Martin, Jerilyn K Allen.
PY - 2021/1
Y1 - 2021/1
N2 - Background: The use of mobile health (mHealth) interventions, including smartphone apps, for the prevention of cardiovascular disease (CVD) has demonstrated mixed results for obesity, hypercholesterolemia, diabetes, and hypertension management. A major factor attributing to the variation in mHealth study results may be mHealth user engagement. Objective: This systematic review aims to determine if user engagement with smartphone apps for the prevention and management of CVD is associated with improved CVD health behavior change and risk factor outcomes. Methods: We conducted a comprehensive search of PubMed, CINAHL, and Embase databases from 2007 to 2020. Studies were eligible if they assessed whether user engagement with a smartphone app used by an individual to manage his or her CVD risk factors was associated with the CVD health behavior change or risk factor outcomes. For eligible studies, data were extracted on study and sample characteristics, intervention description, app user engagement measures, and the relationship between app user engagement and the CVD risk factor outcomes. App user engagement was operationalized as general usage (eg, number of log-ins or usage days per week) or self-monitoring within the app (eg, total number of entries made in the app). The quality of the studies was assessed. Results: Of the 24 included studies, 17 used a randomized controlled trial design, 4 used a retrospective analysis, and 3 used a single-arm pre- and posttest design. Sample sizes ranged from 55 to 324,649 adults, with 19 studies recruiting participants from a community setting. Most of the studies assessed weight loss interventions, with 6 addressing additional CVD risk factors, including diabetes, sleep, stress, and alcohol consumption. Most of the studies that assessed the relationship between user engagement and reduction in weight (9/13, 69%), BMI (3/4, 75%), body fat percentage (1/2, 50%), waist circumference (2/3, 67%), and hemoglobin A1c (3/5, 60%) found statistically significant results, indicating that greater app user engagement was associated with better outcomes. Of 5 studies, 3 (60%) found a statistically significant relationship between higher user engagement and an increase in objectively measured physical activity. The studies assessing the relationship between user engagement and dietary and diabetes self-care behaviors, blood pressure, and lipid panel components did not find statistically significant results. Conclusions: Increased app user engagement for prevention and management of CVD may be associated with improved weight and BMI; however, only a few studies assessed other outcomes, limiting the evidence beyond this. Additional studies are needed to assess user engagement with smartphone apps targeting other important CVD risk factors, including dietary behaviors, hypercholesterolemia, diabetes, and hypertension. Further research is needed to assess mHealth user engagement in both inpatient and outpatient settings to determine the effect of integrating mHealth interventions into the existing clinical workflow and on CVD outcomes.
AB - Background: The use of mobile health (mHealth) interventions, including smartphone apps, for the prevention of cardiovascular disease (CVD) has demonstrated mixed results for obesity, hypercholesterolemia, diabetes, and hypertension management. A major factor attributing to the variation in mHealth study results may be mHealth user engagement. Objective: This systematic review aims to determine if user engagement with smartphone apps for the prevention and management of CVD is associated with improved CVD health behavior change and risk factor outcomes. Methods: We conducted a comprehensive search of PubMed, CINAHL, and Embase databases from 2007 to 2020. Studies were eligible if they assessed whether user engagement with a smartphone app used by an individual to manage his or her CVD risk factors was associated with the CVD health behavior change or risk factor outcomes. For eligible studies, data were extracted on study and sample characteristics, intervention description, app user engagement measures, and the relationship between app user engagement and the CVD risk factor outcomes. App user engagement was operationalized as general usage (eg, number of log-ins or usage days per week) or self-monitoring within the app (eg, total number of entries made in the app). The quality of the studies was assessed. Results: Of the 24 included studies, 17 used a randomized controlled trial design, 4 used a retrospective analysis, and 3 used a single-arm pre- and posttest design. Sample sizes ranged from 55 to 324,649 adults, with 19 studies recruiting participants from a community setting. Most of the studies assessed weight loss interventions, with 6 addressing additional CVD risk factors, including diabetes, sleep, stress, and alcohol consumption. Most of the studies that assessed the relationship between user engagement and reduction in weight (9/13, 69%), BMI (3/4, 75%), body fat percentage (1/2, 50%), waist circumference (2/3, 67%), and hemoglobin A1c (3/5, 60%) found statistically significant results, indicating that greater app user engagement was associated with better outcomes. Of 5 studies, 3 (60%) found a statistically significant relationship between higher user engagement and an increase in objectively measured physical activity. The studies assessing the relationship between user engagement and dietary and diabetes self-care behaviors, blood pressure, and lipid panel components did not find statistically significant results. Conclusions: Increased app user engagement for prevention and management of CVD may be associated with improved weight and BMI; however, only a few studies assessed other outcomes, limiting the evidence beyond this. Additional studies are needed to assess user engagement with smartphone apps targeting other important CVD risk factors, including dietary behaviors, hypercholesterolemia, diabetes, and hypertension. Further research is needed to assess mHealth user engagement in both inpatient and outpatient settings to determine the effect of integrating mHealth interventions into the existing clinical workflow and on CVD outcomes.
KW - Cardiovascular disease
KW - Engagement
KW - Health behaviors
KW - MHealth
KW - Mobile phone
KW - Risk factors
KW - Smartphone
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U2 - 10.2196/18834
DO - 10.2196/18834
M3 - Review article
C2 - 33533730
AN - SCOPUS:85101026730
SN - 2561-1011
VL - 5
JO - JMIR Cardio
JF - JMIR Cardio
IS - 1
M1 - e18834
ER -