Evidence map›Paper›PMID 38175828›Full record

ReviewPLOS digital health2024

An introduction to digital determinants of health.

Swathikan Chidambaram, Bhav Jain, Urvish Jain, Rogers Mwavu, Rama Baru, Beena Thomas, Felix Greaves, Shruti Jayakumar, Pankaj Jain, Marina Rojo and 5 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 92 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
92citing papers in PubMed, 6 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

92 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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32 more citing papers are in PubMed but not listed here.

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

15 authors.

Swathikan ChidambaramDepartment of Surgery & Cancer, Imperial College London, St. Mary's Hospital, London, United Kingdom.ORCID https://orcid.org/0000-0002-4009-3243
Bhav JainMassachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.ORCID https://orcid.org/0000-0003-2648-4894
Urvish JainDietrich School of Arts and Sciences, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
Rogers MwavuMbarara University of Science & Technology, Uganda.
Rama BaruCentre of Social Medicine and Community Health, Jawaharlal Nehru University, New Delhi, India.
Beena ThomasIndian Council of Medical Research, National Institute for Research in Tuberculosis, Chennai, India.
Felix GreavesScience, Evidence and Analytics, National Institute for Health and Care Excellence, England, United Kingdom.
Shruti JayakumarDepartment of Surgery & Cancer, Imperial College London, St. Mary's Hospital, London, United Kingdom.
Pankaj JainHealth Plan Consumer and Provider Technology, Highmark Health, Pittsburgh, Pennsylvania, United States of America.ORCID https://orcid.org/0000-0002-6330-9350
Marina RojoPublic Health Innovation Lab, Med School, Buenos AIres University, Argentina.
Marina Ridao BattaglinoPublic Health Innovation Lab, Med School, Buenos AIres University, Argentina.ORCID https://orcid.org/0000-0003-0305-2087
John G MearaDepartment of Plastic and Oral Surgery, Longwood Avenue, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0003-4369-3209
Viknesh SounderajahDepartment of Surgery & Cancer, Imperial College London, St. Mary's Hospital, London, United Kingdom.
Leo Anthony CeliDivision of Pulmonary, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America.
Ara DarziDepartment of Surgery & Cancer, Imperial College London, St. Mary's Hospital, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, technology has been increasingly incorporated within healthcare for the provision of safe and efficient delivery of services. Although this can be attributed to the benefits that can be harnessed, digital technology has the potential to exacerbate and reinforce preexisting health disparities. Previous work has highlighted how sociodemographic, economic, and political factors affect individuals' interactions with digital health systems and are termed social determinants of health [SDOH]. But, there is a paucity of literature addressing how the intrinsic design, implementation, and use of technology interact with SDOH to influence health outcomes. Such interactions are termed digital determinants of health [DDOH]. This paper will, for the first time, propose a definition of DDOH and provide a conceptual model characterizing its influence on healthcare outcomes. Specifically, DDOH is implicit in the design of artificial intelligence systems, mobile phone applications, telemedicine, digital health literacy [DHL], and other forms of digital technology. A better appreciation of DDOH by the various stakeholders at the individual and societal levels can be channeled towards policies that are more digitally inclusive. In tandem with ongoing work to minimize the digital divide caused by existing SDOH, further work is necessary to recognize digital determinants as an important and distinct entity.

Identifiers

PMID38175828
PMCPMC10766177

What OpenQuestion holds

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LicenceCC BY
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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.