Evidence map›Paper›PMID 31532482›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2019

Challenges and opportunities using online portals to recruit diverse patients to behavioral trials.

Amir Alishahi Tabriz, Patrice Jordan Fleming, Yongyun Shin, Ken Resnicow, Resa M Jones, Susan A Flocke, Deirdre A Shires, Sarah T Hawley, David Willens, Jennifer Elston Lafata

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Trial
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  6. Article
  7. Article
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  9. Article
  10. Article
  11. Implementation ofJournal of clinical and translational science · 2024
    Article
  12. Embedding research study recruitment within the patient portal preCheck-in.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Selecting EHR-driven recruitment strategies: An evidence-based decision guide.Journal of clinical and translational science · 2022
    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

10 authors.

Amir Alishahi TabrizDivision of Pharmaceutical Outcomes and Policy, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Patrice Jordan FlemingDivision of Pharmaceutical Outcomes and Policy, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Yongyun ShinDepartment of Biostatistics, Virginia Commonwealth University, Richmond, Virginia, USA.
Ken ResnicowDepartment of Health Behavior & Health Education, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA.
Resa M JonesDepartment of Epidemiology and Biostatistics, College of Public Health and Fox Chase Cancer Center, Temple University, Philadelphia, Pennsylvania, USA.
Susan A FlockeDepartment of Family Medicine, Oregon Health Sciences University, Portland, Oregon, USA.
Deirdre A ShiresSchool of Social Work, Michigan State University, East Lansing, Michigan, USA.
Sarah T HawleyDepartment of Medicine, Center for Health Communications Research, University of Michigan and Ann Arbor VA Center for Clinical Management Research, Ann Arbor, Michigan, USA.
David WillensHenry Ford Health System, Detroit, Michigan, USA.
Jennifer Elston LafataDivision of Pharmaceutical Outcomes and Policy, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

Funding

e-Assist: A Post-Visit Patient Portal Tool to Promote Colorectal Cancer ScreeningR01CA197205 · NCI · VIRGINIA COMMONWEALTH UNIVERSITY · PI ELSTON LAFATA, JENNIFER M · 2015 to 2019
$3.0M
NCI NIH HHS R01 CA197205
6 · The paper itself

Abstract

We describe the use of an online patient portal to recruit and enroll primary care patients in a randomized trial testing the effectiveness of a colorectal cancer (CRC) screening decision support program. We use multiple logistic regression to identify patient characteristics associated with trial recruitment, enrollment, and engagement. We found that compared to Whites, Blacks had lower odds of viewing the portal message (OR = 0.46, 95% CI = 0.37-0.57), opening the attached link containing the study material (OR = 0.75, 95% CI = 0.62-0.92), and consenting to participate in the trial (OR = 0.85, 95% CI = 0.67-0.93). We also found that compared to Whites, Asians had lower odds of viewing the portal message (OR = 0.53, 95% CI = 0.33-0.64), opening the attached link containing the study material (OR = 0.76, 95% CI = 0.54-0.97), consenting to participate in the trial (OR = 0.68, 95% CI = 0.53-0.95), and completing the trial's baseline questionnaire (OR = 0.59, 95% CI = 0.36-0.90). While portals offer an opportunity to mitigate human bias in trial invitations, because of racial disparities-not only in who has a portal account, but in how they interact with trial recruitment and enrollment material within the portal-using portals alone for trial recruitment may generate study samples that are not racially diverse.

Indexed as

Early Detection of CancerPatient PortalsPatient SelectionAgedColorectal NeoplasmsElectronic Health RecordsFemaleHealth Status DisparitiesHumansLogistic ModelsMaleMiddle AgedPatient Acceptance of Health CarePragmatic Clinical Trials as TopicPrimary Health CareRacial Groupscolorectal cancer screeningelectronic health recordhealth disparitiespatient portalpragmatic clinical trial

Identifiers

PMID31532482
PMCPMC6857600

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.