Evidence map›Paper›PMID 39172776›Full record

ReviewPLOS digital health2024

How to design equitable digital health tools: A narrative review of design tactics, case studies, and opportunities.

Amy Bucher, Beenish M Chaudhry, Jean W Davis, Katharine Lawrence, Emily Panza, Manal Baqer, Rebecca T Feinstein, Sherecce A Fields, Jennifer Huberty, Deanna M Kaplan and 4 more

Abstract readReview
In one paragraph

Review in PLOS digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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

  1. Pooled it
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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

14 authors.

Amy BucherBehavioral Reinforcement Learning Lab (BReLL), Lirio, Inc., Knoxville, Tennessee, United States of America.ORCID https://orcid.org/0000-0001-6514-4441
Beenish M ChaudhrySchool of Computing and Informatics, University of Louisiana at Lafayette, Lafayette, Louisiana, United States of America.
Jean W DavisCollege of Nursing, University of Central Florida, Orlando, Florida, United States of America.ORCID https://orcid.org/0000-0002-9374-2905
Katharine LawrenceDepartment of Population Health, NYU Grossman School of Medicine, New York, New York, United States of America.
Emily PanzaDepartment of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, Rhode Island, United States of America.ORCID https://orcid.org/0000-0001-9874-4160
Manal BaqerNeamah Health Consulting, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0009-0001-0104-0210
Rebecca T FeinsteinAIHealth4All Center for Health Equity using Machine Learning and Artificial Intelligence, University of Illinois at Chicago, Chicago, Illinois, United States of America.ORCID https://orcid.org/0000-0002-0504-2977
Sherecce A FieldsDepartment of Psychological and Brain Sciences, Texas A&M University, College Station, Texas, United States of America.ORCID https://orcid.org/0000-0002-6618-3394
Jennifer HubertyFit Minded Inc., Phoenix, Arizona, United States of America.
Deanna M KaplanDepartment of Family and Preventive Medicine, Emory University School of Medicine, Atlanta, Georgia, United States of America.ORCID https://orcid.org/0000-0002-9300-3029
Isabelle S KustersDepartment of Clinical, Health, and Applied Sciences, University of Houston-Clear Lake, Houston, Texas, United States of America.ORCID https://orcid.org/0000-0002-2740-748X
Frank T MateriaOtolaryngology and Population Health, University of Kansas Medical Center, Kansas City, Kansas, United States of America.ORCID https://orcid.org/0000-0002-8015-1743
Susanna Y ParkRadiant Foundation, Salt Lake City, Utah, United States of America.ORCID https://orcid.org/0000-0002-3256-9651
Maura KepperPrevention Research Center, Brown School, Washington University in St. Louis, St. Louis, Missouri, United States of America.

Funding

Using the Multiphase Optimization Strategy to Optimize a Culturally Tailored Online Behavioral Weight Loss Intervention for Sexual Minority WomenK23MD015092 · NIMHD · MIRIAM HOSPITAL · PI PANZA, EMILY · 2020 to 2024
$826k
NIMHD NIH HHS K23 MD015092
6 · The paper itself

Abstract

With a renewed focus on health equity in the United States driven by national crises and legislation to improve digital healthcare innovation, there is a need for the designers of digital health tools to take deliberate steps to design for equity in their work. A concrete toolkit of methods to design for health equity is needed to support digital health practitioners in this aim. This narrative review summarizes several health equity frameworks to help digital health practitioners conceptualize the equity dimensions of importance for their work, and then provides design approaches that accommodate an equity focus. Specifically, the Double Diamond Model, the IDEAS framework and toolkit, and community collaboration techniques such as participatory design are explored as mechanisms for practitioners to solicit input from members of underserved groups and better design digital health tools that serve their needs. Each of these design methods requires a deliberate effort by practitioners to infuse health equity into the approach. A series of case studies that use different methods to build in equity considerations are offered to provide examples of how this can be accomplished and demonstrate the range of applications available depending on resources, budget, product maturity, and other factors. We conclude with a call for shared rigor around designing digital health tools that deliver equitable outcomes for members of underserved populations.

Identifiers

PMID39172776
PMCPMC11340894

What OpenQuestion 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 OpenQuestion graph.