DOI 10.1016/j.amjoto.2025.104716
Telehealth utilization and perceptions among deaf or hard of hearing adults: A cross-sectional analysis of the HINTS6 national dataset.
Аннотация
OBJECTIVE
Telehealth has emerged as a vital medium for healthcare delivery and has been integrated increasingly in clinic and hospital settings in the post-COVID-19 era. However, accessibility of telehealth for individuals who are deaf or hard of hearing (DHH) remains underexplored. As effective communication is critical to high-quality healthcare, a deeper understanding of how DHH individuals interact with telehealth and identifying specific barriers they face can inform targeted interventions to improve care.
METHODS
We conducted a cross-sectional analysis of the 2022 Health Information National Trends Survey (HINTS 6), a nationally representative dataset. Respondents were stratified by self-identified DHH status. Demographic, internet access, health behavior, and telehealth perception variables were compared between DHH and normal hearing individuals. Statistical analyses were performed using chi-square tests and t-tests.
RESULTS
Among 5694 respondents, 521 identified as DHH. Chi-square testing found that DHH patients reported poorer general health (p < 0.01), lower internet use (p < 0.01), and less engagement with online health resources (p < 0.01), with similar rates of telehealth being offered and utilized. However, DHH individuals were less likely to perceive telehealth as convenient (p = 0.04) and more likely to cite difficulty using the platform (p = 0.01). They were also more likely to value the inclusion of others in their telehealth visits (p < 0.01) and report technical issues (p < 0.01).
CONCLUSIONS
While DHH individuals use telehealth at similar rates to the general population, they face significant barriers related to convenience, usability, and communication. Enhancing platform accessibility and expanding support for these patients can help reduce difficulties and further promote equity in telehealth.
Предметные рубрики MeSH
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Обработка статьи · этапы, ошибки и управление
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