Evidence map›Paper›PMID 39786850›Full record

SynthesisJournal of medical Internet research2025

Use of mHealth Technology for Improving Exercise Adherence in Patients With Heart Failure: Systematic Review.

Pallav Deka, Erin Salahshurian, Teresa Ng, Susan W Buchholz, Leonie Klompstra, Windy Alonso

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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

6 authors.

Pallav Deka *College of Nursing, Michigan State University, East Lansing, MI, United States.ORCID 0000-0002-3648-9843
Erin SalahshurianCollege of Nursing, University of Nebraska Medical Center, Omaha, NE, United States.ORCID 0000-0001-7799-8698
Teresa NgCollege of Nursing, Michigan State University, East Lansing, MI, United States.ORCID 0000-0002-3961-5171
Susan W BuchholzCollege of Nursing, Michigan State University, East Lansing, MI, United States.ORCID 0000-0002-6311-9709
Leonie KlompstraDepartment of Health, Medicine and Care Sciences, Linkoping University, Linkoping, Sweden.ORCID 0000-0002-7493-0353
Windy AlonsoCollege of Nursing, University of Nebraska Medical Center, Omaha, NE, United States.ORCID 0000-0002-8711-6756

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe known and established benefits of exercise in patients with heart failure (HF) are often hampered by low exercise adherence. Mobile health (mHealth) technology provides opportunities to overcome barriers to exercise adherence in this population.

objectiveThis systematic review builds on prior research to (1) describe study characteristics of mHealth interventions for exercise adherence in HF including details of sample demographics, sample sizes, exercise programs, and theoretical frameworks; (2) summarize types of mHealth technology used to improve exercise adherence in patients with HF; (3) highlight how the term "adherence" was defined and how it was measured across mHealth studies and adherence achieved; and (4) highlight the effect of age, sex, race, New York Heart Association (NYHA) functional classification, and HF etiology (systolic vs diastolic) on exercise adherence.

methodsWe searched for papers in PubMed, MEDLINE, and CINAHL databases and included studies published between January 1, 2015, and June 30, 2022. The risk of bias was analyzed.

resultsIn total, 8 studies (4 randomized controlled trials and 4 quasi-experimental trials) met our inclusion and exclusion criteria. A moderate to high risk of bias was noted in the studies. All studies included patients with HF in NYHA classification I-III, with sample sizes ranging from 12 to 81 and study durations lasting 4 to 26 weeks. Six studies had an equal distribution of male and female participants whose ages ranged between 53 and 73 years. Videoconferencing was used in 4 studies, while 4 studies used smartphone apps. Three studies using videoconferencing included an intervention that engaged participants in a group setting. A total of 1 study used a yoga program, 1 study used a walking program, 1 study combined jogging with walking, 1 study used a cycle ergometer, 2 studies combined walking with cycle ergometry, and 1 study used a stepper. Two studies incorporated resistance exercises in their program. Exercise programs varied, ranging between 3 and 5 days of exercise per week, with exercise sessions ranging from 30 to 60 minutes. The Borg rating of perceived exertion scale was mostly used to regulate exercise intensity, with 3 studies using heart rate monitoring using a Fitbit. Only 1 study implicitly mentions developing their intervention using a theoretical framework. Adherence was reported to the investigator-developed exercise programs. All studies were mostly feasibility or pilot studies, and the effect of age, sex, race, and NYHA classification on exercise adherence with the use of mHealth was not reported.

conclusionsThe results show some preliminary evidence of the feasibility of using mHealth technology for building exercise adherence in patients with HF; however, theoretically sound and fully powered studies, including studies on minoritized communities, are lacking. In addition, the sustainability of adherence beyond the intervention period is unknown.

Indexed as

Heart FailurePatient ComplianceTelemedicineAgedExerciseExercise TherapyFemaleHumansMaleMiddle Agedactivity monitorsadherenceageexerciseexercise programsfeasibilityheartheart failuremHealthmHealth technologymobile healthmobile phoneracesexsmartphonesoftware appstelehealth technologyvideoconferencing

Identifiers

PMID39786850
PMCPMC11757971

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.