Factors Associated With Use of and Satisfaction With Telehealth by Adults in Rural Virginia During the COVID-19 Pandemic

This survey study examines the use of and satisfaction with telehealth services by adults in rural Virginia during the COVID-19 pandemic.


Introduction
COVID-19 has accelerated the expansion of telehealth, heralding an opportunity to integrate technology into clinical care delivery in new and purposeful ways.However, there are disparities among people in rural communities that limit opportunities to gain experience and comfort using technology for health information and services, including lower home broadband access, lower health literacy, and less use of online health information compared with urban populations. 1,2In this survey study, we examine the use of and satisfaction with telehealth services during the pandemic in a predominantly rural sample and estimate the magnitude of the association between demographic and health characteristics, health literacy, internet access, and the odds of using telehealth.

Sample
The Virginia Commonwealth University institutional review board approved this study, which follows the American Association for Public Opinion Research (AAPOR) reporting guideline.Respondents were recruited through the Virginia Living Well Registry (VALW), a community-based convenience sample registry of adults residing in primarily rural Virginia counties (Rural-Urban Continuum Codes 4-9).A total of 401 participants registered to the VALW before January 2020 were invited to complete a self-administered consent and survey online or through mailed paper surveys between June 2020 and January 2021.A waiver of signed consent was obtained for mailed surveys to enable survey completion via telephone.Additional information on study methods is available in the eAppendix in the Supplement.The overall response rate was 61%.An additional 6 participants who completed the VALW after June 2020 were included.

Measures
Outcomes were self-reported telehealth use (yes vs no) and patient satisfaction with telehealth services 3 since March 2020.Telehealth included communication via telephone, video, or electronic monitoring systems.Single-item screeners were used to identify low or inadequate health literacy, 4 health insurance coverage, internet access, and overall perceived health.Health literacy was operationalized as perceived confidence completing medical forms independently, which has been shown to successfully identify individuals with low health literacy. 4Race and ethnicity were selfreported using categories defined by Office of Management and Budget standards.Race and ethnicity were analyzed in this study because disparities in preventive care use by race/ethnicity are well documented; in Virginia, rural Black residents experience greater incidence and/or mortality for some screenable cancers compared with White residents, suggesting that there are disparities in access to care.Rurality was categorized as Rural-Urban Continuum Codes 4 to 9 using participant address. 5Higher Perceived Stress Scale 6 scores indicated greater perceived stress and were included given the pandemic context, which may be associated with health care seeking.

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Statistical Analysis
Means, SDs, frequencies, and proportions were used to describe demographic and health characteristics.Stratified analyses using 2-sided t tests and χ 2 tests were used to examine potential differences between telehealth users vs nonusers, and satisfaction with telehealth.Multiple logistic regression was used to determine significance (P < .05)and magnitude of associations using SAS statistical software version 9.4 (SAS Institute).a Racial/ethnic differences by telehealth use and satisfaction were tested as differences between non-Hispanic White and underrepresented racial and ethnic individuals (non-Hispanic Black, Hispanic, American Indian, Asian, and unknown).a Because of the very small participant samples among Hispanic, American Indian, and Asian respondents, race/ethnicity was dichotomized as non-Hispanic White and underrepresented racial and ethnic groups (African American/Black, Hispanic, Asian, and American Indian).

Table 1 .
Respondent Characteristics and Differences by Telehealth Use and Telehealth Satisfaction

Table 2 .
Logistic Regression Model of Factors Associated With Telehealth Use