Review
Abstract
Background: Digital health tools are increasingly vital in rural health care due to widespread hospital closures and the rapid adoption of telehealth during the COVID-19 pandemic. Rural older adults, a uniquely vulnerable population, face barriers to accessing these tools due to rurality and usability challenges. Although a growing body of literature examines the acceptability and usability of digital tools among rural older adults, no study has synthesized this research to establish best practices.
Objective: This study aims to review existing literature on digital health tools for rural older adults, highlighting key lessons learned about their acceptability and identifying strategies to improve usability for this population.
Methods: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, this study reviewed literature that investigated the role of digital health tools on the health outcomes of rural older adults (ie, at least 60 years old). The literature was retrieved from 5 electronic databases through June 2023. This study and all reviewed literature were conducted in the United States. Guided by a systematic process, 2 reviewers assessed relevant articles for eligibility, analyzed data, and extracted relevant content. The extracted findings were organized according to the evidence-based technology acceptance model, which assesses the acceptability of a technology by its usefulness, ease of use, and intention to use.
Results: The preliminary title review produced 7728 results, and 38 eligible manuscripts were included in the final review. Studies included both rural older adults and providers of rural older adults as participants. Digital health tools included, but were not limited to, videoconferencing, phone calls, telehealth monitoring, telemedicine appointments, and computer-based interventions. Findings on the usefulness of digital health tools by rural older adults were mixed. While digital health tools were useful for overcoming barriers to accessing care, these tools were less useful for rural older adults with limited digital literacy. Additionally, some studies described that the technology was easy but difficult to use when faced with environmental barriers, equipment issues, and discomfort with the technology. Rural older adults often reported an intention to use the technology after the study. Yet, on a few occasions, participants who preferred in-person care visits or did not have buy-in on the technology reported no intention to use the technology again.
Conclusions: Our review highlights that rural older adults and their providers generally view digital health tools as acceptable for delivering care and, in some cases, as a viable alternative to in-person clinic visits. While certain barriers impacted the acceptance of these tools among rural older adults, many of these challenges were not directly linked to their age or rural location; thus, they are potentially applicable to urban older adults.
Trial Registration: PROSPERO CRD42021287924; https://www.crd.york.ac.uk/PROSPERO/view/CRD42021287924
doi:10.2196/70012
Keywords
Introduction
Digital health tools facilitate communication between patients and health care providers and offer access to resources. These tools encompass a range of technologies, including mobile health apps, electronic health records, wearable devices, and telehealth services. Social distancing mandates related to COVID-19 facilitated increased funding to support improved access to broadband internet and the rapid uptake of digital health tools []. To increase digital tool access and use by rural residents, in the spring of 2022, the US Department of Health and Human Services announced a US $16.3 million expansion to telehealth care in the Title X Family Planning Program []. Thus, rural health care professionals and systems were able to integrate digital tool uptake in their care rapidly []. Telehealth uptake in health clinics and hospitals increased by 154% in March 2020 compared with March 2019 []. For many rural patients, digital health tools are an essential component of their health care management and will likely remain important for timely and continuous rural care coordination [].
Rural older adults represent a vulnerable population at the intersection of aging and rural residency, facing well-documented yet preventable challenges in accessing health care []. Rural residents are rapidly aging in place. For instance, 25% of older adults live in a rural or small town, and this is expected to rise to 33% by 2030 []. Additionally, for many rural older adults, care management is complex, confusing, and further challenged by coordination between distant health care facilities []. Since 2010, over 160 rural hospitals have permanently closed their doors, reducing access to inpatient care, which is critical for improving rural community health []. Therefore, aging rural populations will increasingly experience limited access to specialty care and poorer health outcomes [].
Digital health tools can potentially overcome care coordination challenges for rural older adults. Once rural older adults engage with digital health tools, they often find their experience satisfactory and, at times, comparable to in-person visits []. Rural older adults evaluated web-based consultations conducted by service providers with high efficiency and satisfaction scores []. Once older adults understand the technology, they often find it an acceptable mode of care when punctuated by in-person visits.
Despite high levels of satisfaction with digital tools by rural older adults, compared with urban older adults, this vulnerable population has reduced telehealth use [,]. Also, although rural residents are willing to adopt digital health tools [,], studies show that rural older adults report slower telehealth uptake than younger rural adults [,]. This is partially due to barriers that make using digital health tools difficult for rural older adults. Some of these barriers include technical literacy, lack of technical support, cost, ownership of technology, and visual acuity []. In a systematic review including rural adults aged 55 years and older who have used telehealth, older adults reported a willingness to learn how to use various digital tools, but 30% felt too inexperienced with technology to use them []. Similarly, in a sample of Medicare enrollees, rural cancer survivors had a significantly lower predicted probability of internet use for patient-provider communication when compared with urban cancer survivors with Medicare (28% vs 46%) []. Importantly, not all rural older adults will find digital health tools to be a favorable health care management tool. Yet, funding to increase broadband access and the threat of widening rural medical deserts will facilitate continued telehealth uptake of digital tools by health care systems, thereby reinforcing the increased uptake of digital health tools by rural older adults. Increasing the acceptability of digital health tools and reducing barriers to their uptake for rural older adults are essential for providing health care to rural older adults.
Given the rapid acceleration of digital health tools by rural health care providers, rural older adults find digital health tools helpful. Still, rural older adults have reduced uptake of these technologies compared with both urban older adults and younger rural adults. With the increasing use of digital health tools, understanding their acceptability among rural older adults is crucial for ensuring this vulnerable population stays engaged in their care management and coordination as reliance on these tools continues to grow. Details about the rural older adults’ digital health tool acceptability and usage can inform tool intervention design, implementation, and evaluation. Existing research summarizes the effectiveness of services such as telehealth among older adults, but strategies to improve rural older adults’ usage of digital health tools are limited []. Therefore, this study will systematically review the existing literature in the United States on rural adults’ acceptability of digital health tools and assess lessons learned on digital health tool usage among rural older adults.
Methods
Study Design
The study was analyzed and reported in accordance with the Cochrane systematic review guidelines and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines () [,].
Search Strategy and Data Sources/Protocol Registration
A trained librarian conducted searches in MEDLINE (Ovid), Cochrane Database of Systematic Reviews (Wiley), Embase (Elsevier), CINAHL (EBSCO), and PsycINFO (EBSCO) databases. This search included articles published in English through June 5, 2023. Keywords and subject headings related to the following topics were used to identify possible articles: rural residents, older adults, the use of technology-enhanced tools to navigate telehealth, and acceptability. See the supplementary materials for the complete search strategy. Following, we searched the references of eligible articles for additional relevant articles. The protocol was registered post hoc in the International Prospective Register of Systematic Reviews (PROSPERO CRD42021287924).
All articles eligible for data extraction underwent title and abstract review, and full-text review by a pair of reviewers. Reviewers independently assessed the articles based on the eligibility criteria (see below) using standardized procedures in the systematic review software Covidence (Covidence systematic review software, Melbourne, Victoria, Australia). A pair of reviewers discussed and resolved conflicts in weekly meetings. Each article was assessed for quality by 2 reviewers. Extracted content and Quality Assessments were reported using Microsoft Excel and Covidence.
Eligibility Criteria
We included research articles of investigations conducted in the United States that assessed a digital health tool’s ability to connect patients with providers, where at least 25% of the sample population identified as rural, and at least 25% of the sample identified as at least 60 years old. Articles were excluded if they were a review (eg, systematic or scoping), withdrawn, a conference proceeding, an abstract, or a dissertation. We also excluded articles published before 1999, as we deemed that the technology or lessons learned from the technology over 25 years ago were antiquated.
Data Extraction
Paired reviewers conducted consensus meetings to agree upon the rationale for data extraction content and synthesize the results. displays the extraction content. In short, paired reviewers reported each article’s title, first author, and year of publication. The outcome variables collected from each study included the participants’ age (average or mean), study design, and type of digital health tool technology (eg, videoconference or wearables). Following the technology acceptance model (TAM), we extracted data related to the core TAM domains: perceived usefulness, perceived ease of use, and intention to use []. The perceived usefulness domain describes how much technology improves a patient’s performance. Perceived ease of use is the effort required to use the technology. Last, intention to use refers to a patient’s willingness to use the technology. Given that we aim to synthesize acceptability and lessons learned, our analysis did not assess the effect of the outcomes. This systematic review did not need an exploration of heterogeneity or a sensitivity analysis.
| Study | Population characteristics | Study design | Technology | Usefulness | Ease of use | Intention to use | |
| Age | Rural | ||||||
| Anderson et al [] | Mean age 61 years | Community-based outpatient clinics in rural Southeast Texas | Qualitative | Videoconferencing |
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| Barton et al [] | 28.5% of the sample is 60 years or older | 67.3% of the sample is from rural Colorado | Cross-sectional | Phone call, videoconference |
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| Bernacchi et al [] | Mean age 60.2 years | Rural dwelling residents from Southeast US | Mixed methods | Videoconferencing |
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| Bonsignore et al [] | Mean age 72 years | Rural counties in Western North Carolina | Mixed methods | Telemonitoring |
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| Browning et al [] | Mean age 81 years | Residents of rural Southwest Virginia | Retrospective quality improvement case series | Phone-based telehealth monitoring |
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| Collie et al [] | Mean age 60.7 (SD 9.24) years | Resident of Intermountain region of North-eastern California | Pretest-posttest | Videoconferencing |
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| Cummings et al [] | Mean age 52.8 (SD 16.2) years | Rural counties in eastern North Carolina | Descriptive | Nonmydriatic retinal imaging telemedicine system |
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| DeHart et al [] | 41.2% of the sample is 55 years or older | Rural resident from South-Eastern State | Mixed methods | Web and mobile-based telehealth with remote monitoring |
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| Demaerschalk et al [] | Mean age 66.3 (SD 13.5) years | Patients at rural medical centers, more than 185 miles from a primary stroke center | Randomized control trial | Telestroke |
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| Depatie and Bigbee [] | Senior living facility serving adults aged 60 years or older | Rural northern California senior centers | Descriptive mixed methods | Mobile health technology |
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| DeVido et al [] | Mean age 54 (SD 19.4) years | Providers at a rural population-serving hospital | Case report | Telepsychiatry |
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| Donahue et al [] | Mean age 57.9 (SD 12.4) years | Rural North Carolina county | Cohort | Phone-based digital health care |
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| Finley et al [] | 82% of the sample is 65 years or older | Three rural outpatient telehealth clinics, or one urban outpatient clinic in Arizona | Mixed methods | Telecardiology |
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| Geller et al [] | 54.6% of the sample is 61 years or older | Patients and their providers from rural practices in Vermont | Quasi-experimental | Computer-based interactive interventions |
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| Gutierrez et al [] | Mean age 65.2 years | Patients from a VAa hospital in rural Wisconsin | Mixed methods | Telehospitalist |
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| Hatch et al [] | 47.4% of the sample is 65 years or older | 33.1% of the sample resided in a rural area | Descriptive cross-sectional cohort | Telehealth |
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| Hicks et al [] | Mean age 68.9 years | Residents in rural midwestern state | Experimental | Telemonitoring |
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| Holloway et al [] | Mean age 61.3 (SD 11.6) years | Residents in rural Montana | Pretest-posttest | PRISMb digital health care videoconferencing |
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| Khairat et al [] | Mean age 77.8 years | 66.7% of the sample resided in rural North Carolina | Cross-sectional | Videoconferencing follow-up care |
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| Kulcsar et al [] | Mean age 60.3 (SD 16.1) years | The majority of patients resided in rural New Hampshire or rural Vermont | Cross-sectional quality improvement | Telerheumatology |
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| Liu et al [] | Mean age 67 years | Patients from a clinic in rural Wisconsin | Qualitative | Teleophthalmology |
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| Locke et al [] | Mean age 69.2 years | Residents of rural zip codes defined by the United States Census Bureau | Retrospective | Home computer video health technology |
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| McIlhenny et al [] | Mean age 63.8 (SD 12.46) years | Patients of rural medical clinics | Quasi-experimental | Computer-based telemedicine |
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| Owolo et al [] | Mean age 59.9 (SD 13.5) years | 28.9% of the sample was considered rural | Retrospective cohort | Web-based telemedicine |
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| Robinson et al [] | Mean age 71 (SD 6.8) years | Residents from rural New York | Cross-sectional | Telemedicine |
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| Rodriguez et al [] | Mean age 63 (SD 12) years | Patients and providers from rural medical centers and remote community-based outreach clinics in Pennsylvania | Mixed methods | Electronic consultations |
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| Schlittenhardt et al [] | Mean age 54 years | 78% of the sample from rural areas | Mixed methods | Tele-Continence care |
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| Schooley et al [] | Mean age 63.5 years | Residents of rural Vermont | Mixed methods | Information technology mediums |
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| Silvestrini et al [] | Mean age 60 years | Patients referred from clinics in rural Washington, Oregon, or Alaska | Qualitative | TelePain |
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| Strowd et al [] | Mean age 44.5 (SD 24.1) years | 26% of the sample resided in a rural zip code | Retrospective cohort | Video and phone-based digital technology |
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| Svistova et al [] | A large portion of the sample is aged 65 years and older | Rural residents in Pennsylvania | Qualitative focus group | Zoom teleconferencing |
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| Switzer et al [] | Mean age 70 years | Patients from one of 12 hospitals, 10 of which were in rural Georgia | Cohort | Telestroke |
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| Virmani et al [] | Mean age 65.8 (SD 9.2) years | Residents in rural Arkansas | Cross-sectional | Web-based televideo |
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| Waymouth et al [] | Providers of older adults | Providers in a rural area | Qualitative | Assistive and remote monitoring technology |
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| Weiner et al [] | Mean age 69.7 (SD 12.8) years | Residents of Choctaw Nation of Oklahoma | Clinical trial | Videoconferencing |
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| West and Milio [] | Mean age 68.3 years | Patients from a rural homecare organization | Mixed methods case study | Rural homecare organization telemedicine |
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| West et al [] | 55 years or older | Residents of rural upstate New York | Cohort clinical trial | Web-based telemedicine with videoconferencing |
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| Zulman et al [] | Mean age 56 (SD 17) years | 53% of the sample as rural | Mixed methods | Tablet-based health technology |
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aVA: Veterans Health Administration.
bPRISM: Promoting Realistic Individual Self Management.
cPCP: primary care provider.
Quality Appraisal
The quality assessments were achieved through critical appraisal tools used in Joanna Briggs Institute Systematic Reviews [] and the McGill Mixed Methods Appraisal Tool Version 2018 []. Two reviewers assessed the quality of each included article represented in the extracted data. Weekly meetings were held to discuss conflicts. Studies with a quality score of less than 50% were not included in the analysis, indicating evidence of reporting bias.
Results
Overview of Reviewed Studies
provides a summary of the selection process and illustrates our systematic review of the literature. The preliminary title review produced 7728 results, out of which 7616 underwent the abstract review, and 511 completed the full-text review. Following the assessment, 16 studies were excluded because they scored less than 50% of the total possible score for each respective quality test. Our final review included 39 studies.

details our data extraction, elucidating article information according to the first author and publication date, study population age, study design, technology used, and TAM domains. Since 25% of the population had to be at least 60 years old for eligibility, it is important to highlight that studies reported the mean age, included samples exclusively of older adults (eg, Medicare enrollees), and provided the percentage of participants within specific age ranges. The study design of eligible studies was cross-sectional (n=8), qualitative (n=7), and mixed methods (n=11). We will detail lessons learned from the eligible studies according to the TAM domains below.
Technology Usefulness
Digital health tools were useful for connecting patients to providers [,,,,,], assisting participants with improving health outcomes and care management [,,-,-,-,,], and reducing transportation burdens [,,,,,-,,]. Uniquely, Anderson et al [] reported on the role of telehealth videoconferencing in strengthening patients’ social and peer connections. Providers also considered that digital health tools were useful for care management [,,,,,] and communicating with other providers [,,]. Although the respective technology was considered useful, multiple studies reported that rural older adults needed additional supports to facilitate the usefulness of the technology, including behavioral goal setting [] and assistive devices [].
Despite the reported usefulness of digital health tools, some studies also reported that they were less than useful. Bernacchi et al [] revealed that digital health technology was less useful for participants with limited experience with digital technology. Similarly, according to Kulcsar et al [], nearly one in 5 patients scheduled for a telerheumatology visit was deemed unsuitable due to poor symptom understanding, symptom complexity, and the limitations of conducting a physical examination remotely.
Ease of Use
Articles that addressed the digital health tools’ ease of use described the tools as uncomplicated [], requiring an adequate amount of training to use [], easy to access health information [,], easier than an in-person examination [], easy to communicate with a health care professional [,,], and intuitive []. Hybrid models that provided supplemental real-time instruction with the technology improved the ease of use [,]. Importantly, some digital health tools were easier to use than others. For example, Schooley et al [] assessed that mental health evaluations via email and telephone were challenging because of barriers to observing nonverbal cues, yet were easier to accomplish via a videoconference. Additionally, Geller et al [] reported that audio features improved the ease of using a computer-based intervention for older adults. Providers also reported that digital health tools improved the ease of managing appointments [,], accessing and reviewing patient records [,], and contacting patients []. Weiner et al [] reported that a low “no-show” rate (3%) evidenced the ease of using videoconferencing visits. Locke et al [] reported that 90% of the providers reported that the technology was easy to use, despite the fact that more than half of the providers reported issues with scheduling, and 41% reported that patients were confused about using the technology.
Commonly, studies have reported on the challenges of using technology. Digital health tools were more complicated to use when faced with environmental barriers (eg, poor lighting) [,], technical or equipment issues [,,-,,,,,], discomfort with the technology [,,,], reduced access to adequate internet [,,,], and distrust in the technology []. DeHart et al [] and Hatch et al [] observed a positive relationship between education levels and ease of use, which was particularly challenging for older adults with low levels of education. Although many studies reported the challenges of using digital tool technology, West et al [] reported that supplemental instructions were critical for overcoming usage barriers.
Intention to Use the Technology
Most commonly, participants reported an intent to use the digital health tool technology through sustained use poststudy [,,,,,], future referrals or recommendations [], high levels of digital tool uptake [,,,], and evidence of improved care management [,,,]. For example, Locke et al [] reported that 96% of the participants preferred home video telehealth inhaler training rather than going to the clinic for in-person training. Bernacchi et al [] detailed another example of intention to use videoconferencing technology through the patient’s commitment to contact their health care provider despite challenges with equipment and broadband. Strowd et al [] and Finley et al [] reported that rural residents were more likely to consider telehealth in the future compared with urban residents. A study indicated that participants were more likely to continue with specific delivery modes of digital health tools, such as telephones, rather than web-based options [].
When participants did not intend to use the digital health tool technology, it was often due to a preference for in-person visits [,,,,,] or a lack of buy-in about the technology [,]. Additionally, 2 studies identified age associations with intentions to use digital health tools. Older adults had reduced intentions of continuing their care digitally [,].
Discussion
Principal Findings
This review aimed to assess lessons learned about the acceptability of digital health tools among rural older adults. Following a systematic review approach, we organized our findings according to the TAM, focusing on the usefulness, ease of use, and intention to use digital health tools of rural older adults. The domains of the TAM aim to detail predictors of potential acceptance or rejection of the technology. Our findings revealed that digital health tools were, in most cases, useful for care management, reducing transportation burdens, and improving patient-provider communication. Two articles reported that digital health tools were less useful when the technology was misaligned with the participant’s digital skills level or when the technology was unsuitable for the given care visit types. Several articles highlighted the ease of use of digital health tools for rural older adults, describing them as uncomplicated, intuitive, and effective for connecting with health care providers. Most articles that discussed the ease of using digital health tools focused on the ease of specific features of the tool (eg, audio capabilities) or the type of technology (eg, telephone vs digital). However, digital health tools were more difficult to use due to technical or equipment issues, discomfort with the technology, and limited access to broadband internet. Last, the findings on rural older adults’ intention to use digital health tools were robust, as evidenced by participants’ preference to continue using the technology after the study concluded and improved health outcomes. Comparatively, participants did not intend to use the digital health tools when they preferred an in-person visit or when they were not sold on the benefits of the digital health tool. Together, the TAM domains reveal that rural older adults and their providers largely consider digital health tools as acceptable modes of receiving care and, at times, a suitable alternative to in-person clinic visits. Despite barriers that reduced rural older adults’ acceptance of digital health tools, many of these barriers were not associated with their age or rural residence.
Technology Usefulness: Lessons Learned
Digital health tools are useful for accessing health care and care management, but their effectiveness in improving health outcomes in older adults is mixed. Our review highlights that digital health tools were useful for mitigating burdens related to accessing health care and care management for both providers and patients. Articles reported that useful care management needs included scheduling, accessing health records, and patient-provider communication. The positive findings on remote care management and usefulness are specific to this review, and it is important to note that the effectiveness of remote care management and monitoring on health outcomes is mixed. In a review of remote care management of depression and anxiety in older adults, the findings on psychiatric outcomes were mixed, and no studies demonstrated a statistically significant effect of remote care management on health care use or cost []. Another review of mobile integrated health interventions for older adults revealed that these interventions reduced emergency department call volume and transports []. Thus signaling that digital health tools were useful for care management during emergency health events.
To build on this body of evidence, our review uniquely emphasizes the usefulness of digital/remote care management for rural older adults—a population that has complex care needs but often resides in a medically underserved area with reduced access to broadband internet and technology literacy programming. However, future systematic and meta-reviews are needed to assess the effectiveness of digital health tools with care management features on health outcomes and costs for rural older adults.
Ease of Use: Lessons Learned
Easy-to-use technology is associated with improved health outcomes; however, the design of technology may not be sufficient, and external support (eg, timely technical assistance) may be necessary. According to the TAM, digital tools that are perceived to be easy to use are more likely to be accepted by the intended audience. Based on this review, rural older adults and their providers frequently highlighted user-friendly features of the tools that improved ease of use. However, there was strong evidence that external factors—such as technical issues, equipment limitations, and discomfort with the technology—hindered usability. There is a positive relationship between the health of older adults, their social connectedness, access to high-quality health care resources, and the perceived ease of use of digital health tools [,]. Notably, this evidence signals that technology design alone does not improve the ease of using digital health tools. Specifically for older adults, in-person synchronous technical assistance, access to remote technical assistance, and early interventions from hospital administrators are reported facilitators for increasing the ease of use of digital health tools [,,]. Overall, this evidence underscores the need for additional resources and external support to enhance the perceived ease of using digital health tools for rural older adults.
Intention to Use the Technology: Lessons Learned
Despite design flaws or technical difficulties, rural older adults generally intended to continue using technology beyond the observed period. Factors such as the preference for in-person care and a lack of buy-in about the technology influenced the participants’ intent to use digital health tools. Yet, our findings revealed that participants described an intention to use digital health tools despite also reporting that the technology was not always useful or easy to use [,,,]. In a similar study on patient portal use by older adults, challenges were noted with log-ins and the user interface design, such as color and font []. Despite these issues, older adults expressed an intention to continue using the portals due to their other beneficial features. In summary, in light of the barriers to ease of use and usefulness, rural older adults often overcame them to continue using digital health tools [].
Additional Considerations for Digital Tool Acceptability
In synthesizing lessons learned, our review identified several phenomena, not salient enough to categorize as a lesson, but worthy of continued discussion. Namely, our review reveals both differences and commonalities in user behavior and preferences between older adults in rural and urban areas. As reduced access to broadband internet is a common barrier for rural residents, this was not the most reported impediment to digital tool acceptability in this review, as expected. According to the Federal Communications Commission’s data reported in 2021, 23%-50% of rural residents had poor access to broadband internet []. The rather limited mention of challenges associated with rural internet connectivity, in this review, is inconsistent with the existing literature, which indicates that poor internet connection is a key barrier to digital tool use acceptability for rural residents []. Also notable is that multiple studies reported a measure of digital tool acceptance among rural residents compared with urban residents. For example, Finley et al [] reported urban-rural differences in intention to use, indicating that rural patients, compared with urban and suburban patients, had more favorable attitudes toward telecardiology. This higher acceptance of digital health tools by rural patients likely punctuates the growing reliance on and acceptance of digital health tools in the wake of dwindling local health care resources and rising health care costs. While these findings suggest that rural and urban residents share common barriers to technology acceptability, our conclusions do not suggest that “one-size-fits-all” interventions should be considered. Rather, additional qualitative examinations on the rural-urban differences in attitudes toward digital health tools and the acceptability of these tools are warranted.
This review synthesized a diverse representation of technology modes (eg, videoconference or phone call), highlighting the robust intervention designs implemented in rural settings. These findings strengthen the evidence base on digital tool acceptability among rural patients, with all modes being reported as acceptable. Yet, important distinctions emerged across the reported technology modes, making salient conclusions about the most acceptable modes speculative. For example, both Anderson et al [] and Svistova et al [] used videoconferencing; however, Anderson et al [] employed a Veterans Affairs-supported platform, and Svistova et al [] used Zoom. The journal articles provided limited details regarding platform-distinctive features, though such distinctions could plausibly impact acceptability and usability very differently. In the current review, technology modes were extracted as they were identified in the original article to ensure transparency. A more detailed analysis of the technology’s distinctive features and their impact on acceptability warrants further investigation.
The data collected for this study includes both pre– and post–COVID-19 pandemic publications, which provide key insights into how rural older adults’ acceptance of digital health tools evolved, resulting from the rapid uptake of telehealth due to COVID-19 precautions. Many of the studies that were published prior to the COVID-19 pandemic often emphasize the same sentiment of the digital divide between younger and older generations. The existing literature evidences that the pandemic exacerbated this divide, as prepandemic older adults were less likely to benefit from technological innovations []. Specifically, pre- and early-pandemic trends indicated that age and rural zip codes were inversely related to continuous digital tool use []. Multiple studies from our review that were published prepandemic identified that younger participants were more likely to engage in digital tool technologies [,]. Yet, in a peripandemic investigation, Bernacchi et al [] describe that videoconferencing with a nurse increased access to care for older rural cancer patients. Similarly, postpandemic, individuals older than 65 years used telemedicine over 3 times more when compared with prepandemic, further emphasizing this technological shift [].
The findings of this review have practice and research implications. To improve practice, our findings suggest that health care providers adopt hybrid care models—combining both digital and in-person visits. It is essential for providers to emphasize the benefits of digital health tools, such as reducing travel burdens and offering greater convenience [,,,,,,]. Additionally, future research should include interventions aimed at increasing technology literacy among rural older adults and provide additional synchronous and asynchronous supports to help rural older adults better understand the technology [,,-,,,,,]. For caregivers who support rural older adults, digital health tools have the potential to reduce caregiving burdens. Tools such as remote monitoring enable doctors and nurses to keep patient health under observation while the patient remains in the comfort of their home [,,]. This technology could reduce the burden on caregivers and limit accidents. Last, it is our hope that these findings will influence policy that increases funding for the development of digital health tools that can decrease health disparities within rural older adult populations.
Limitations
This study has several strengths and limitations. The synthesis of our findings was guided by the core domains of the TAM []. Previous studies have reported that the Perceived Usefulness, Perceived Ease of Use, and Intention to Use domains are important for determining user acceptability. They are the core of all TAM models used across the literature, thus chosen for this study. Yet, additional domains and extensions have been added over time, including the “Attitudes Toward Using” domain [,]. Although our synthesis is limited to conclusions derived from the core domains, these domains provide sufficient information to inform our overall aim of assessing user acceptability. Additionally, a trained librarian conducted a data search of publicly available databases (eg, PubMed). Despite our comprehensive search conducted by a trained librarian, some relevant studies may have been missed due to factors such as publication dates postreview, non–English language restrictions, or potential oversight in keyword selection. It is important to note that participants in health outcomes research are often younger than 65, have higher household incomes, greater technological literacy, and are more likely to reside in urban areas [,,]. Therefore, our review’s focus on rural older adults and digital tool use may highlight a potential participant bias in our sample, limiting the generalizability of our findings to the broader rural older adult population. As with all scholarly reviews, researcher bias could have impacted the results. However, because multiple reviewers assessed each manuscript and attended consensus meetings for each manuscript, this bias was reduced.
Conclusion
This study aimed to systematically review articles that incorporated digital health tools used by rural older adults in order to assess their acceptability and usage of the tools. Following the TAM, we highlighted the usefulness, ease of use, and intention to use digital health tools. In summary, digital health tools were valuable for rural older adults with complex care needs, helping mitigate access barriers and support care management tasks like scheduling and patient-provider communication. While rural older adults and providers found the tools user-friendly, external factors such as technical issues and equipment limitations impeded usability, signaling the need for additional support and resources. Despite challenges with ease of use, rural older adults expressed an intention to continue using digital health tools, recognizing their overall benefits in managing care, especially in underserved areas. As medical deserts widen in rural communities, and in response to the rapid uptake of telemedicine due to COVID-19 precautions, digital health tool reliance is likely to grow for rural residents. Understanding what this uniquely vulnerable population views as acceptable and what facilitates their uptake of digital health tools is critical for addressing health disparities and bridging the digital divide in rural communities.
Funding
MWL and ZMS were supported by a grant from the National Cancer Institute (Grant Number: K01CA262342). MWL is also supported by a Northwestern University Clinical and Translational Sciences Institute grant (Grant Numbers: NUCATS; UL1TR001422, Principal Investigator: Richard D’Aquilla), an Institutional Research Grant (IRG-21-144-27) from the American Cancer Society (Principal Investigator: Leonidas Platanias), and funds from the Northwestern University Center for Community Health (grant number: not applicable). Opinions and comments expressed in this paper belong to the authors and do not necessarily reflect those of the National Institutes of Health.
Authors' Contributions
ZMS was responsible for formal analysis, methodology, project administration, visualization, writing the original draft, and reviewing and editing subsequent drafts. EQ was responsible for the formal analysis, writing the original draft, and reviewing and editing subsequent drafts. JP was responsible for writing the original draft and reviewing and editing subsequent drafts.
Conflicts of Interest
None declared.
PRISMA checklist.
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Abbreviations
| PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses. |
| TAM: technology acceptance model |
Edited by M Mardini; submitted 30.Dec.2024; peer-reviewed by NA Puccinelli-Ortega, LR Guo; comments to author 22.Jul.2025; revised version received 09.Sep.2025; accepted 10.Nov.2025; published 04.Feb.2026.
Copyright©Zachary M Siegel, Ellie Quinkert, Jiya Pai, Corinne H Miller, Marquita W Lewis. Originally published in JMIR Aging (https://aging.jmir.org), 04.Feb.2026.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Aging, is properly cited. The complete bibliographic information, a link to the original publication on https://aging.jmir.org, as well as this copyright and license information must be included.

