Evidence map›Paper›PMID 37816886›Full record

ReviewNPJ digital medicine2023

Does clinical research account for diversity in deploying digital health technologies?

Nathan A Coss, J Max Gaitán, Catherine P Adans-Dester, Jessica Carruthers, Manuel Fanarjian, Caprice Sassano, Solmaz P Manuel, Eric Perakslis

Abstract readReview
In one paragraph

Review in NPJ digital medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. 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

8 authors.

Nathan A CossHumanFirst, Inc., San Francisco, CA, USA.ORCID http://orcid.org/0000-0003-0454-1464
J Max GaitánHumanFirst, Inc., San Francisco, CA, USA. max@gohumanfirst.com.ORCID http://orcid.org/0000-0001-9552-8921
Catherine P Adans-DesterHumanFirst, Inc., San Francisco, CA, USA.
Jessica CarruthersHumanFirst, Inc., San Francisco, CA, USA.
Manuel FanarjianHumanFirst, Inc., San Francisco, CA, USA.ORCID http://orcid.org/0000-0001-7720-7171
Caprice SassanoHumanFirst, Inc., San Francisco, CA, USA.
Solmaz P ManuelDepartment of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, CA, USA.ORCID http://orcid.org/0000-0002-7061-066X
Eric PerakslisHumanFirst, Inc., San Francisco, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital health technologies (DHTs) should expand access to clinical research to represent the social determinants of health (SDoH) across the population. The frequency of reporting participant SDoH data in clinical publications is low and is not known for studies that utilize DHTs. We evaluated representation of 11 SDoH domains in 126 DHT-enabled clinical research publications and proposed a framework under which these domains could be captured and subsequently reported in future studies. Sex, Race, and Education were most frequently reported (in 94.4%, 27.8%, and 20.6% of publications, respectively). The remaining 8 domains were reported in fewer than 10% of publications. Medical codes were identified that map to each of the proposed SDoH domains and the resulting resource is suggested to highlight that existing infrastructure could be used to capture SDoH data. An opportunity exists to increase reporting on the representation of SDoH among participants to encourage equitable and inclusive research progress through DHT-enabled clinical studies.

Identifiers

PMID37816886
PMCPMC10564850

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.