Evidence map›Paper›PMID 39172649›Full record

Trial reportJournal of the American Medical Informatics Association : JAMIA2025

Increasing adherence and collecting symptom-specific biometric signals in remote monitoring of heart failure patients: a randomized controlled trial.

Sukanya Mohapatra, Mirna Issa, Vedrana Ivezic, Rose Doherty, Stephanie Marks, Esther Lan, Shawn Chen, Keith Rozett, Lauren Cullen, Wren Reynolds and 5 more

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of the American Medical Informatics Association : JAMIA, 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. Article
  2. Article
  3. Review
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

15 authors.

Sukanya MohapatraDepartment of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, Los Angeles, CA 90024, United States.
Mirna IssaDepartment of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90024, United States.
Vedrana IvezicDepartment of Radiology, University of California, Los Angeles, Los Angeles, CA 90024, United States.
Rose DohertyDepartment of Radiology, University of California, Los Angeles, Los Angeles, CA 90024, United States.
Stephanie MarksDepartment of Radiology, University of California, Los Angeles, Los Angeles, CA 90024, United States.
Esther LanDepartment of Medicine, University of California, Los Angeles, Los Angeles, CA 90024, United States.
Shawn ChenDepartment of Radiology, University of California, Los Angeles, Los Angeles, CA 90024, United States.
Keith RozettOffice of Advanced Research Computing, University of California, Los Angeles, Los Angeles, CA 90024, United States.
Lauren CullenOffice of Advanced Research Computing, University of California, Los Angeles, Los Angeles, CA 90024, United States.
Wren ReynoldsOffice of Advanced Research Computing, University of California, Los Angeles, Los Angeles, CA 90024, United States.
Rose RocchioOffice of Advanced Research Computing, University of California, Los Angeles, Los Angeles, CA 90024, United States.
Gregg C FonarowDepartment of Medicine, University of California, Los Angeles, Los Angeles, CA 90024, United States.
Michael K OngDepartment of Medicine, University of California, Los Angeles, Los Angeles, CA 90024, United States.
William F SpeierDepartment of Radiology, University of California, Los Angeles, Los Angeles, CA 90024, United States.ORCID 0000-0002-0890-8684
Corey W ArnoldDepartment of Radiology, University of California, Los Angeles, Los Angeles, CA 90024, United States.

Funding

NHLBI NIH HHS R01 HL141773
6 · The paper itself

Abstract

objectivesMobile health (mHealth) regimens can improve health through the continuous monitoring of biometric parameters paired with appropriate interventions. However, adherence to monitoring tends to decay over time. Our randomized controlled trial sought to determine: (1) if a mobile app with gamification and financial incentives significantly increases adherence to mHealth monitoring in a population of heart failure patients; and (2) if activity data correlate with disease-specific symptoms. MATERIALS AND

methodsWe recruited individuals with heart failure into a prospective 180-day monitoring study with 3 arms. All 3 arms included monitoring with a connected weight scale and an activity tracker. The second arm included an additional mobile app with gamification, and the third arm included the mobile app and a financial incentive awarded based on adherence to mobile monitoring.

resultsWe recruited 111 heart failure patients into the study. We found that the arm including the financial incentive led to significantly higher adherence to activity tracker (95% vs 72.2%, P = .01) and weight (87.5% vs 69.4%, P = .002) monitoring compared to the arm that included the monitoring devices alone. Furthermore, we found a significant correlation between daily steps and daily symptom severity. DISCUSSION AND

conclusionOur findings indicate that mobile apps with added engagement features can be useful tools for improving adherence over time and may thus increase the impact of mHealth-driven interventions. Additionally, activity tracker data can provide passive monitoring of disease burden that may be used to predict future events.

Indexed as

Heart FailureMobile ApplicationsPatient ComplianceTelemedicineAgedFemaleFitness TrackersHumansMaleMiddle AgedMotivationProspective Studiesheart failuremHealthremote monitoring

Identifiers

PMID39172649
PMCPMC11648719

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.