Evidence map›Paper›PMID 39383524›Full record

ArticleJMIR mHealth and uHealth2024

Digital Health Readiness: Making Digital Health Care More Inclusive.

Timothy Bober, Bruce L Rollman, Steven Handler, Andrew Watson, Lyndsay A Nelson, Julie Faieta, Ann-Marie Rosland

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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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

7 authors.

Timothy BoberDivision of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States.ORCID 0000-0002-5313-2387
Bruce L RollmanDivision of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States.ORCID 0000-0002-2937-7464
Steven HandlerDivision of Geriatric Medicine, University of Pittsburgh, Pittsburgh, PA, United States.ORCID 0000-0002-3940-3224
Andrew WatsonDepartment of Surgery, University of Pittsburgh, Pittsburgh, PA, United States.ORCID 0000-0002-8546-5020
Lyndsay A NelsonDivision of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashvillie, TN, United States.ORCID 0000-0002-7304-5643
Julie FaietaDepartment of Rehab Science and Technology, University of Pittsburgh, Pittsburgh, PA, United States.ORCID 0000-0002-2032-338X
Ann-Marie RoslandDivision of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States.ORCID 0000-0002-5809-5861

Funding

Understanding the Impact of Digital Health Literacy and Health Supporters on Technology Use for Self-Management among Adults with Type 2 DiabetesR01DK136788 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Carissa A Low, Ann-Marie Rosland · 2024 to 2026
$1.4M
NIDDK NIH HHS R01 DK136788
6 · The paper itself

Abstract

This paper proposes an approach to assess digital health readiness in clinical settings to understand how prepared, experienced, and equipped individual people are to participate in digital health activities. Existing digital health literacy and telehealth prediction tools exist but do not assess technological aptitude for particular tasks or incorporate available electronic health record data to improve efficiency and efficacy. As such, we propose a multidomain digital health readiness assessment that incorporates a person's stated goals and motivations for use of digital health, a focused digital health literacy assessment, passively collected data from the electronic health record, and a focused aptitude assessment for critical skills needed to achieve a person's goals. This combination of elements should allow for easy integration into clinical workflows and make the assessment as actionable as possible for health care providers and in-clinic digital health navigators. Digital health readiness profiles could be used to match individuals with support interventions to promote the use of digital tools like telehealth, mobile apps, and remote monitoring, especially for those who are motivated but do not have adequate experience. Moreover, while effective and holistic digital health readiness assessments could contribute to increased use and greater equity in digital health engagement, they must also be designed with inclusivity in mind to avoid worsening known disparities in digital health care.

Indexed as

TelemedicineDigital HealthHealth LiteracyHumansdigital disparitiesdigital healthdigital health literacydigital health readinessdigital health toolhealth systeminclusivityinformaticsliteracypatient support

Identifiers

PMID39383524
PMCPMC11499716

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.