Evidence map›Paper›PMID 37794870›Full record

ArticleEuropean heart journal. Digital health2023

Personalized digital behaviour interventions increase short-term physical activity: a randomized control crossover trial substudy of the MyHeart Counts Cardiovascular Health Study.

Ali Javed, Daniel Seung Kim, Steven G Hershman, Anna Shcherbina, Anders Johnson, Alexander Tolas, Jack W O'Sullivan, Michael V McConnell, Laura Lazzeroni, Abby C King and 6 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in European heart journal. Digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03090321 (MyHeart Counts Cardiovascular Health Study), which is not on this map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
7.9field-weighted citation impact, top 2% 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.

NCT03090321 naactive not recruitingnot on this map

MyHeart Counts Cardiovascular Health Study

TypeinterventionalSponsorStanford UniversityRan2015 to 2029Enrolled2,000,000ConditionsCardiovascular HealthArmsStand Prompt, Step Prompt, Cluster Prompt, Read AHA website
3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Validation of the Observational Assessment Tool for Tailoring (OATT).Prevention science : the official journal of the Society for Prevention Research · 2026
    Article
  7. AI and Digital Health: Personalizing Physical Activity to Improve Population Health.Circulation. Cardiovascular quality and outcomes · 2025
    Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. 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

16 authors at 2 institutions in 1 country.

Ali JavedDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Daniel Seung KimDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.ORCID https://orcid.org/0000-0003-2971-1909
Steven G HershmanDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Anna ShcherbinaDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Anders JohnsonDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Alexander TolasDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Jack W O'SullivanDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Michael V McConnellDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Laura LazzeroniDepartment of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA.
Abby C KingDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.ORCID https://orcid.org/0000-0002-7949-8811
Jeffrey W ChristleDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Marily OppezzoDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
C Mikael MattssonDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Robert A HarringtonDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Matthew T WheelerDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Euan A AshleyDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
Stanford University · USCardiovascular Institute of the South · US

Funding

Translational Research Core - Health Engagement & Action Translational (HEAT)P30DK092924 · NIDDK · KAISER FOUNDATION RESEARCH INSTITUTE · PI Alyce Sophia Adams, HILARY Kessler SELIGMAN · 2011 to 2026
$9.2M
Testing Multi-Level Remote Physical Activity Interventions in a National Sample of Older Women: The WHISH EnCore TrialR01AG071490 · NIA · STANFORD UNIVERSITY · PI ABBY C KING, Marcia L. Stefanick · 2022 to 2026
$3.1M
NIA NIH HHS R01 AG071490NIDDK NIH HHS P30 DK092924
6 · The paper itself

Abstract

Aims: Physical activity is associated with decreased incidence of the chronic diseases associated with aging. We previously demonstrated that digital interventions delivered through a smartphone app can increase short-term physical activity. Methods and results: We offered enrolment to community-living iPhone-using adults aged ≥18 years in the USA, UK, and Hong Kong who downloaded the MyHeart Counts app. After completion of a 1-week baseline period, e-consented participants were randomized to four 7-day interventions. Interventions consisted of: (i) daily personalized e-coaching based on the individual's baseline activity patterns, (ii) daily prompts to complete 10 000 steps, (iii) hourly prompts to stand following inactivity, and (iv) daily instructions to read guidelines from the American Heart Association (AHA) website. After completion of one 7-day intervention, participants subsequently randomized to the next intervention of the crossover trial. The trial was completed in a free-living setting, where neither the participants nor investigators were blinded to the intervention. The primary outcome was change in mean daily step count from baseline for each of the four interventions, assessed in a modified intention-to-treat analysis (modified in that participants had to complete 7 days of baseline monitoring and at least 1 day of an intervention to be included in analyses). This trial is registered with ClinicalTrials.gov, NCT03090321. Conclusion: Between 1 January 2017 and 1 April 2022, 4500 participants consented to enrol in the trial (a subset of the approximately 50 000 participants in the larger MyHeart Counts study), of whom 2458 completed 7 days of baseline monitoring (mean daily steps 4232 ± 73) and at least 1 day of one of the four interventions. Personalized e-coaching prompts, tailored to an individual based on their baseline activity, increased step count significantly (+402 ± 71 steps from baseline,

Indexed as

Apple WatchDigital healthDigital interventionseBhavioural interventionsPersonalized medicinePhysical activity

Identifiers

PMID37794870
PMCPMC10545510
OpenAlexW4385717376

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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.