Document Type

Article

Publication Date

9-3-2024

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This article is the author's final published version in JAMA network open, Volume 7, Issue 9, September 2024, Pages e2432718.

The published version is available at https://doi.org/10.1001/jamanetworkopen.2024.32718.

Copyright © 2024 Rising KL et al.

Abstract

IMPORTANCE: While telehealth use has grown, patient uptake is variable, which has the potential to increase health disparities. Identifying and understanding individuals' barriers to digital health readiness can help health systems efficiently deploy resources to provide personalized patient-centered support.

OBJECTIVE: To develop and validate an instrument to evaluate digital health readiness to identify and quantify barriers to digital readiness.

DESIGN, SETTING, AND PARTICIPANTS: In this qualitative mixed-methods study conducted from April 26, 2022, to June 8, 2023, the instrument was created in 4 phases. Patients and health care professionals were interviewed to explore barriers to telehealth use, scale items were developed for the screener, cognitive interviews were conducted to refine scale items, and psychometric properties of the screener were evaluated. The study was conducted in an urban, multisite academic health system and the surrounding community. Participants were older than 18 years, English-speaking, and able to provide informed consent. Professionals worked within the Jefferson Health system and were involved in telehealth services.

EXPOSURE: Participants completed a semistructured interview (duration: 6-19 minutes), a cognitive interview (duration: 13-137 minutes), or the draft screener survey (duration: 5-10 minutes).

MAIN OUTCOMES AND MEASURES: Development and validation of a screener for digital health readiness.

RESULTS: Of 519 patients approached, 19 were ineligible, 122 declined, and 11 were excluded from analysis, resulting in inclusion of 367 participants (32 patient interviews, 16 professional interviews, 15 cognitive interviews, 304 psychometric survey testing). All 16 professionals who were approached participated. Most patient participants were Black (46.7%) or White (37.9%), male (56.4%), and had a high school degree or some college (49.6%); mean (SD) age was 45 (23) years for participants in cognitive interviews, 53 (18) years for survey respondents, and 57 (14) years for patient interviews. The structured interviews uncovered 21 concepts, leading to 48 items that were refined through cognitive interviews. Psychometric analyses of the 29 items that emerged from the cognitive interviews resulted in a final screener with 24 items across 2 factors: technical readiness (18 items; factor loading range, 0.488-0.968) and quality-of-care concerns (6 items; factor loading range, 0.619-0.942).

CONCLUSIONS AND RELEVANCE: In this qualitative study of digital health readiness, the findings suggest that the screener items may be valid to assess the complexity of factors influencing digital health uptake and highlight several areas for potential intervention.

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Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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Supplement 2.pdf (13 kB)

PubMed ID

39254972

Language

English

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