Evidence map›Paper›PMID 33533730›Full record

ReviewJMIR cardio2021

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

Erin M Spaulding, Francoise A Marvel, Rebecca J Piasecki, Seth S Martin, Jerilyn K Allen

Open access · goldAbstract readReview
In one paragraph

Review in JMIR cardio, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 3 pooled it
16.5field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

43 citing papers in PubMed, 3 syntheses or guidelines pooled it, 73 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Erin M SpauldingJohns Hopkins University School of Nursing, Baltimore, MD, United States.ORCID https://orcid.org/0000-0001-8390-2277
Francoise A MarvelDigital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.ORCID https://orcid.org/0000-0002-6422-1772
Rebecca J PiaseckiJohns Hopkins University School of Nursing, Baltimore, MD, United States.ORCID https://orcid.org/0000-0003-4979-5636
Seth S MartinThe Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, United States.ORCID https://orcid.org/0000-0002-7021-7622
Jerilyn K AllenJohns Hopkins University School of Nursing, Baltimore, MD, United States.ORCID https://orcid.org/0000-0002-9288-5971
Johns Hopkins University · US

Funding

Sex Hormones in Pulmonary Arterial HypertensionP01HL108800 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI LOYD, JAMES E · 2012 to 2021
$22.0M
CARDIOVASCULAR EPIDEMIOLOGY INSTITUTIONAL TRAININGT32HL007024 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI Elizabeth Selvin · 1985 to 2026
$17.5M
Interdisciplinary Training in Cardiovascular Health ResearchT32NR012704 · NINR · JOHNS HOPKINS UNIVERSITY · PI ALLEN, JERILYN K · 2011 to 2020
$1.8M
The Process of User Engagement with mHealthF31NR017328 · NINR · JOHNS HOPKINS UNIVERSITY · PI SPAULDING, ERIN MURDOCK · 2017 to 2019
$129k
Medical emergency team trigger clusters: Describing symptom experience during clinical deterioration in the context of medical emergency team careF31NR018362 · NINR · JOHNS HOPKINS UNIVERSITY · PI PIASECKI, REBECCA J · 2019 to 2019
$45k
NHLBI NIH HHS P01 HL108800NHLBI NIH HHS T32 HL007024NINR NIH HHS F31 NR017328NINR NIH HHS F31 NR018362NINR NIH HHS T32 NR012704
6 · The paper itself

Abstract

backgroundThe 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.

objectiveThis 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.

methodsWe 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.

resultsOf 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 A

conclusionsIncreased 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.

Indexed as

cardiovascular diseaseengagementhealth behaviorsmHealthmobile phonerisk factorssmartphone

Identifiers

PMID33533730
PMCPMC8411427
OpenAlexW3127700251

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.