Evidence map›Paper›PMID 32607481›Full record

ArticleJAMIA open2020

Citizen science to further precision medicine: from vision to implementation.

Carolyn Petersen, Robin R Austin, Uba Backonja, Hugo Campos, Arlene E Chung, Eric B Hekler, Pei-Yun S Hsueh, Katherine K Kim, Anthony Pho, Liz Salmi and 2 more

Open access · goldAbstract read
In one paragraph

Article in JAMIA open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 6% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

  1. Guideline
  2. Patient Participation in AI for Health Curriculum.Journal of participatory medicine · 2025
    Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Citizen Science Studies in Nursing: A Systematic Review.Nursing reports (Pavia, Italy) · 2024
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Combining the Digital, Social and Physical Layer to Create Age-Friendly Cities and Communities.International journal of environmental research and public health · 2021
    Article
  18. Article
  19. Precision Health: The Role of the Social and Behavioral Sciences in Advancing the Vision.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2020
    Article
  20. 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

12 authors at 12 institutions in 1 country.

Carolyn PetersenDivision of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA.
Robin R AustinSchool of Nursing, University of Minnesota, Minneapolis, Minnesota, USA.
Uba BackonjaNursing & Healthcare Leadership, University of Washington Tacoma, Tacoma, Washington, USA.
Hugo CamposKaiser Permanente, Kaiser Permanente Innovation, Oakland, California, USA.
Arlene E ChungDepartments of Internal Medicine and Pediatrics & the Program on Health & Clinical Informatics, UNC School of Medicine, Chapel Hill, North Carolina, USA.
Eric B HeklerDepartment of Family Medicine & Public Health, Center for Wireless & Population Health Systems, Design Lab, Qualcomm Institute, University of California-San Diego, San Diego, California, USA.
Pei-Yun S HsuehCenter for Computational Health, IBM TJ Watson Research Center, Yorktown Heights, New York, USA.
Katherine K KimBetty Irene Moore School of Nursing, Department of Public Health Sciences-School of Medicine, University of California-Davis, Sacramento, California, USA.
Anthony PhoSchool of Nursing, Columbia University, New York, New York, USA.
Liz SalmiOpenNotes/Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
Anthony SolomonidesFamily Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA.
Rupa S ValdezDepartment of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, USA.
Beth Israel Deaconess Medical Center · USColumbia University · USIBM (United States) · USKaiser Permanente · USMayo Clinic · USNorthShore University HealthSystem · USQualcomm (United States) · USUC Davis Health System · USUniversity of Minnesota · USUniversity of North Carolina Health Care · USUniversity of Virginia · USUniversity of Washington · US

Funding

QuBBD: Statistical & Visualization Methods for PGHD to Enable Precision Medicine R01EB025024 · NIBIB · UNIV OF NORTH CAROLINA CHAPEL HILL · PI CHUNG, ARLENE E. · 2017 to 2019
$918k
NIBIB NIH HHS R01 EB025024
6 · The paper itself

Abstract

The active involvement of citizen scientists in setting research agendas, partnering with academic investigators to conduct research, analyzing and disseminating results, and implementing learnings from research can improve both processes and outcomes. Adopting a citizen science approach to the practice of precision medicine in clinical care and research will require healthcare providers, researchers, and institutions to address a number of technical, organizational, and citizen scientist collaboration issues. Some changes can be made with relative ease, while others will necessitate cultural shifts, redistribution of power, recommitment to shared goals, and improved communication. This perspective, based on a workshop held at the 2018 AMIA Annual Symposium, identifies current barriers and needed changes to facilitate broad adoption of a citizen science-based approach in healthcare.

Indexed as

citizen sciencecommunity participationconsumer involvementhealthcare systemspatient acceptance of healthcareresearch methodology

Identifiers

PMID32607481
PMCPMC7309265
OpenAlexW2994228576

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.