Literature DB >> 33533730

User Engagement With Smartphone Apps and Cardiovascular Disease Risk Factor Outcomes: Systematic Review.

Erin M Spaulding1,2, Francoise A Marvel3,4, Rebecca J Piasecki1, Seth S Martin2,3,4,5,6, Jerilyn K Allen1,4,6.   

Abstract

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. ©Erin M Spaulding, Francoise A Marvel, Rebecca J Piasecki, Seth S Martin, Jerilyn K Allen. Originally published in JMIR Cardio (http://cardio.jmir.org), 03.02.2021.

Entities:  

Keywords:  cardiovascular disease; engagement; health behaviors; mHealth; mobile phone; risk factors; smartphone

Year:  2021        PMID: 33533730     DOI: 10.2196/18834

Source DB:  PubMed          Journal:  JMIR Cardio        ISSN: 2561-1011


  9 in total

1.  A Mobile Health-Based Disease Management Program Improves Blood Pressure in People With Multiple Lifestyle-Related Diseases at Risk of Developing Vascular Disease - A Retrospective Observational Study.

Authors:  Masashi Kanai; Takuya Toda; Kojiro Yamamoto; Marina Akimoto; Yuta Hagiwara
Journal:  Circ Rep       Date:  2022-05-31

2.  Contrasting a Mobile App With a Conversational Chatbot for Reducing Alcohol Consumption: Randomized Controlled Pilot Trial.

Authors:  Patrick Dulin; Robyn Mertz; Diane King; Alexandra Edwards
Journal:  JMIR Form Res       Date:  2022-05-16

Review 3.  Remote Healthcare for Elderly People Using Wearables: A Review.

Authors:  José Oscar Olmedo-Aguirre; Josimar Reyes-Campos; Giner Alor-Hernández; Isaac Machorro-Cano; Lisbeth Rodríguez-Mazahua; José Luis Sánchez-Cervantes
Journal:  Biosensors (Basel)       Date:  2022-01-27

4.  The Relationship Between Weight Loss Outcomes and Engagement in a Mobile Behavioral Change Intervention: Retrospective Analysis.

Authors:  Alissa Carey; Qiuchen Yang; Laura DeLuca; Tatiana Toro-Ramos; Youngin Kim; Andreas Michaelides
Journal:  JMIR Mhealth Uhealth       Date:  2021-11-08       Impact factor: 4.773

Review 5.  Big Data in Cardiology: State-of-Art and Future Prospects.

Authors:  Haijiang Dai; Arwa Younis; Jude Dzevela Kong; Luca Puce; Georges Jabbour; Hong Yuan; Nicola Luigi Bragazzi
Journal:  Front Cardiovasc Med       Date:  2022-04-01

6.  Use of Mobile Apps in Heart Failure Self-management: Qualitative Study Exploring the Patient and Primary Care Clinician Perspective.

Authors:  Leticia Bezerra Giordan; Rimante Ronto; Josephine Chau; Clara Chow; Liliana Laranjo
Journal:  JMIR Cardio       Date:  2022-04-20

7.  User engagement in relation to effectiveness of a digital lifestyle intervention (the HealthyMoms app) in pregnancy.

Authors:  Jairo H Migueles; Emmie Söderström; Pontus Henriksson; Johanna Sandborg; Ralph Maddison; Marie Löf
Journal:  Sci Rep       Date:  2022-08-13       Impact factor: 4.996

Review 8.  The Association Between Smartphone App-Based Self-monitoring of Hypertension-Related Behaviors and Reductions in High Blood Pressure: Systematic Review and Meta-analysis.

Authors:  Aikaterini Kassavou; Michael Wang; Venus Mirzaei; Sonia Shpendi; Rana Hasan
Journal:  JMIR Mhealth Uhealth       Date:  2022-07-12       Impact factor: 4.947

9.  Smoking Cessation Smartphone App Use Over Time: Predicting 12-Month Cessation Outcomes in a 2-Arm Randomized Trial.

Authors:  Jonathan B Bricker; Kristin E Mull; Margarita Santiago-Torres; Zhen Miao; Olga Perski; Chongzhi Di
Journal:  J Med Internet Res       Date:  2022-08-18       Impact factor: 7.076

  9 in total

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