Evidence map›Paper›PMID 40791999›Full record

ArticleFrontiers in digital health2025

Sociodemographic predictors of digital health adoption in patients with asthma and COPD.

Daniela Téllez, Elroy Boers, Leanne Kaye, Vy Vuong, Meredith A Barrett

Abstract read
In one paragraph

Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Daniela TéllezResMed Science Center, San Diego, CA, United States.
Elroy BoersResMed Science Center, Halifax, NS, Canada.
Leanne KayeResMed Science Center, San Diego, CA, United States.
Vy VuongResMed Science Center, San Diego, CA, United States.
Meredith A BarrettResMed Science Center, San Diego, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Remote healthcare adoption has grown significantly in United States (US). However, better characterization of patient behaviors and comfort with the use of digital health is needed, especially among vulnerable populations. The objective of this study was to evaluate how sociodemographic characteristics may relate to the adoption of digital health among patients with asthma and chronic obstructive pulmonary disease (COPD). Methods: Adults residing in the US and using a digital platform for asthma or COPD management were surveyed to understand (1) level of comfort sharing health data with their healthcare providers and (2) the presence of remote care concerns, specifically clinical, technological, privacy and financial concerns. Multivariable logistic regression models assessed the relationship between baseline disease status, sex, age, race, education, insurance, and income, with health data sharing patterns and areas of concern with remote care. Results: About one-third of survey respondents reported sharing health data with their provider, and most respondents had at least one concern in receiving remote care, with clinical and privacy concerns being the most frequently reported. However, attitudes and behaviors toward virtual health delivery were mixed. Patients with lower income were 65% more likely to share any health data (OR 1.65, 95% CI 1.13-2.43, Discussion: Patterns of data sharing and concerns with remote care varied across sociodemographic predictors, sometimes in opposing ways. These learnings highlight the need for further research, including moderating and mediating factors like social support, health literacy, and rurality, to uncover the real-world use and impact of digital health services at a population level.

Indexed as

asthmaCOPDdigital healthremote caresocial determinants of health

Identifiers

PMID40791999
PMCPMC12336217

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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.