Evidence map›Paper›PMID 29671879›Full record

ReviewClinical cardiology2018

Harnessing mHealth technologies to increase physical activity and prevent cardiovascular disease.

David I Feldman, W Theodore Robison, Justin M Pacor, Luke C Caddell, Erica B Feldman, Rachel L Deitz, Theodore Feldman, Seth S Martin, Khurram Nasir, Michael J Blaha

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Clinical cardiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
  2. Trial
  3. Trial
  4. Trial
  5. Article
  6. Article
  7. Article
  8. ePSICONUT: An e-Health Programme to Improve Emotional Health and Lifestyle in University Students.International journal of environmental research and public health · 2022
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Health Factors Associated with Cardiovascular Wellness.Current atherosclerosis reports · 2019
    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

10 authors.

David I FeldmanDepartment of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida.ORCID http://orcid.org/0000-0002-8664-7678
W Theodore RobisonDepartment of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida.
Justin M PacorDepartment of Internal Medicine, Joan C. Edwards School of Medicine, Marshall University, Huntington, West Virginia.
Luke C CaddellDepartment of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida.
Erica B FeldmanDepartment of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida.
Rachel L DeitzDepartment of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida.
Theodore FeldmanCenter for Healthcare Advancement & Outcomes, Baptist Health South Florida, Miami, Florida.
Seth S MartinCiccarone Center for the Prevention of Heart Disease, Johns Hopkins School of Medicine, Baltimore, Maryland.
Khurram NasirCiccarone Center for the Prevention of Heart Disease, Johns Hopkins School of Medicine, Baltimore, Maryland.ORCID http://orcid.org/0000-0002-2632-1318
Michael J BlahaCiccarone Center for the Prevention of Heart Disease, Johns Hopkins School of Medicine, Baltimore, Maryland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Research into prevention of cardiovascular disease has increasingly focused on mobile health (mHealth) technologies and their efficacy in helping individuals adhere to heart-healthy recommendations, including daily physical activity levels. By including the use of mHealth technologies in the discussion of physical activity recommendations, clinicians empower patients to play an active daily role in modifying their cardiovascular risk-factor profile. In this review, we critically evaluate the mHealth and physical activity literature to determine how these tools may lower cardiovascular risk while providing real-time tracking, feedback, and motivation on physical activity levels. We analyze the various domains-including user knowledge, social support, behavioral change theory, and self-motivation-that potentially influence the effectiveness of smartphone applications to impact individual physical activity levels. In doing so, we hope to provide a thorough overview of the mHealth landscape, in addition to highlighting many of the administrative, reimbursement, and patient-privacy challenges of using these technologies in patient care. Finally, we propose a behavioral change model and checklist for clinicians to assist patients in utilizing mHealth technology to best achieve meaningful changes in daily physical activity levels.

Indexed as

SmartphoneCardiovascular DiseasesExerciseHumansSelf CareTelemedicineEpidemiologyPreventive Cardiology

Identifiers

PMID29671879
PMCPMC6489886

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.