The aim of this systematic literature review is to advance the understanding of older adults’ (aged ≥60 years) eHealth learning and use during its domestication. The main target is older adults living in rural and remote environments, as they are far removed from traditional health care services [1-4]. According to the World Health Organization, health is understood as “a state of complete physical, mental, and social well-being and not merely the absence of disease of infirmity” [5]. As a general practice, eHealth can be seen as an umbrella concept for different health care services delivered or improved through information and communication technologies (ICTs) [6,7].

On the basis of future demographic changes, the world will face two challenges: a growing care burden per capita and organizational changes to health care systems [8,9]. To achieve its sustainable development goals, the United Nations [8] has outlined key policy changes that deal with current and future population dynamics. Recommendations include investing in life-long learning, especially digital competences, and promoting healthy aging and long-term care systems to meet the needs of the aging population. Care policy throughout Europe has emphasized deinstitutionalization and aging in place to reduce paternalistic care and improve the quality of care [10,11]. Furthermore, previous research in many cultural settings has found that older adults prefer living at home for as long as possible [9].

This study’s theoretical framework is built on the concept of distributed and situated digital competence, technology domestication, and previous research on barriers and enablers of technology use. The European Commission’s DigComp 2.0: The Digital Competence Framework for Citizens [12] defines digital competence as a combination of knowledge, skills, and attitudes related to the use of ICT tools. One competence is the protection of health and well-being, which means, for example, being aware of digital technologies that can be used to enhance social well-being and social inclusion. However, the framework can be criticized for being decontextualized and centered around individuals. Therefore, a socially and culturally oriented approach is followed, and digital competences are understood as the distributed and situated competences of older adults and their social networks [13,14].

The concept of domestication focuses on how technology users and nonusers adopt technologies culturally and socially in their everyday lives [15-17]. The domestication of technology includes four dimensions: appropriation, objectification, incorporation, and conversion. The process starts with appropriation, which does or does not create a relationship with the new technology, and continues to objectification, which is when the technology is given a place at home. Incorporation focuses on the technology’s place in and influence over the user’s everyday routines. Finally, the technology becomes familiar, and conversion is achieved [15-21]. Central to domestication are the public and personal meanings attached to the technology, which actively transform during the process [19]. Meanings are understood as individuals’ thoughts and feelings regarding the technology and how it is seen as part of his or her own cultural context [22,23].

Research into health-related barriers has found that the key reasons older adults avoid ICT adoption are the accessibility of support, their health status, lack of need or interest, functionality, added value, cost, and concerns regarding privacy and trust [24,25]. In the present review, barriers were not understood as insurmountable obstacles but rather as challenges that can be solved. Conversely, the following key enablers influence older adults’ use of eHealth: motivation, support, and feedback [26]. In addition, meaningful function and aesthetics are important when older adults adopt technology [27].

Recent international literature reviews on eHealth and older adults focus on a variety of topics: eHealth access and use from a health equity perspective [28], the facilitators of and barriers to eHealth use [24,26,29], and user involvement in technology design, including eHealth technologies [30,31]. In addition, Cheng et al [32] published a systematic review of eHealth interventions targeted at socially disadvantaged groups, including older adults. However, we still lack a review that examines older adults’ eHealth learning and use in real home settings and in a rural context from users’ perspectives. The purpose of the present review is to fill this gap by focusing on studies that report barriers and enablers that older adults face when learning to use and while using eHealth technology and how older adults are supported during the process. In addition, what eHealth technology means to older adults in rural and remote areas was examined. In reviewing relevant studies, this research seeks to answer the following questions:

The methodology follows the standard PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for studies that evaluate health care research [33]. PRISMA includes a 27-item checklist (Multimedia Appendix 1 [33]) and a 4-phase diagram (Figure 1) to help authors ensure clarity and transparency. A systematic literature review was selected “to appraise, synthesize, and summarize” [34] the literature and determine whether further primary research in the area is needed. The entire review process was undertaken by 1 author, and there were no additional authors.

To begin the search process, the author consulted an information specialist at her university library regarding search phrases and relevant databases. A literature search was conducted in January 2020 and included the following international web-based databases: ProQuest (ERIC—Education Collection, Social Science Database, Applied Social Sciences Index and Abstracts, Sociological Abstracts, and Sociology Database), Ebsco (AgeLine, Academic Search Elite, and CINAHL Complete), Web of Science (Arts and Humanities Citation Index, Social Sciences Citation Index, Science Citation Index Expanded, and Emerging Sources Citation Index), and Scopus (Elsevier). Relevant articles were found using the search terms specified in Textbox 1 and their combinations. An example search string used to search Scopus (Elsevier) can be found in Multimedia Appendix 2. The search was applied to the field title, abstract, and keywords. Although the conversions around eHealth began at the turn of the millennium [6], the review’s start date of 2010 was chosen as there has been a lot of change in health technologies over the past decade [35]. The initial database search yielded 3612 papers (n=393, 10.88% from ProQuest, n=394, 10.91% from Ebsco, n=2767, 76.61% from Web of Science, and n=58, 1.61% from Scopus). No articles were included that were identified from sources other than the abovementioned databases.

Figure 1 shows a flowchart depicting how PRISMA was used to select the studies. All articles were exported to Refworks (ProQuest), a reference management system that automatically discards duplicate papers. Of the 3612 papers, the removal reduced the number of papers to 3115 (86.24%). The remaining articles were screened for title, abstract, and keywords to select studies relevant to the research topic. Following the screening of the 3115 articles, a total of 489 (15.7%) articles were obtained. The remaining articles were exported to NVivo 12 (QSR International), a qualitative data analysis software, and the remaining duplicates were manually discarded. Full-text articles were then assessed for eligibility based on the preliminary inclusion and exclusion criteria.

Finally, full-text articles (31/489, 6.3%) that met the following criteria (Textbox 2) were accepted: published in a peer-reviewed scientific journal; written in English; published between January 1, 2010, and January 22, 2020; had an empirical study design aimed at supporting older adults’ use of eHealth technology in real home settings at the user’s home; completely or partially focused on technology users’ perspectives; had participants with a mean age of 60 years; and included participants who were older adults with or without health conditions. Initially, the aim was to select studies that included only older adults aged >65 years, which is a common age limit for older adults in research [36]; however, because of the low number of studies, the age range was extended to a mean of 60 years. In addition, living in rural or remote areas was a planned inclusion criterion; however, it was modified to living in any area, as not enough studies met the original criterion. However, one research question focused only on studies conducted in rural and remote areas.

For the final set of full-text articles, a data extraction sheet was developed (Multimedia Appendix 3 [37-65]). The gathered data included information on article titles, authors, journals, publication years, methods, eHealth technologies, target groups, total number of participants, participant genders and ages, participants’ area of residence (eg, rural or remote), and countries of residence. The included articles were analyzed in NVivo 12 using a qualitative thematic approach guided by the concepts of domestication and digital competence. In addition, previous research on the barriers to and enablers of technology use was used. The author thoroughly read and reread the articles and identified 154 subcategories that described significant sentences and phrases concerning the research questions. The obtained subcategories were clustered into 8 upper-level categories to produce a more nuanced understanding.

The selected 31 articles were published in 29 different journals representing multidisciplinary research. Of the 31 papers, 16 (52%) were quantitative, 4 (13%) were qualitative, and 11 (35%) were mixed methods studies. Most studies used >1 method; only 16% (5/31) used just one method. The most common qualitative data collection methods were surveys and questionnaires (20/31, 65%) and technical logs (12/31, 39%). The most common qualitative data collection methods were interviews (9/31, 29%) and focus groups (5/31, 16%). The studies were conducted in the following 12 countries: the United States (9/31, 29%), Canada (2/31, 6%), Italy (2/31, 6%), Spain (2/31, 6%), Sweden (2/31, 6%), the United Kingdom (2/31, 6%), France (1/31, 3%), Germany (1/31, 3%), Ireland (1/31, 3%), Lebanon (1/31, 3%), Norway (1/31, 3%), and Switzerland (1/31, 3%). In 19% (6/31) of studies, the country was not identified.

The number of participants ranged from 1 to 4380, although not all were older adults. In all articles, either the mean or median age and SD or the age range was defined. However, in studies in which only the SD and mean or median age were given, it was not possible to strictly count the age of the youngest and oldest participants. In 90% (28/31) of articles, the mean or median age of the technology users was ≥60 years, and in 39% (12/31) of articles, the minimum age was >60 years. Some articles (6/31, 19%) included technology users aged<50 years, and it was possible to separate them from the older adults in the findings. This means that the findings were still based on participants who were aged >60 years or whose mean or median age was ≥60 years. In 42% (13/31) of articles, most participants were women, and in 35% (11/31) of articles, most participants were men. In 6% (2/31) of papers, female and male participants were equally represented, and in 16% (5/31) of papers, gender was not defined.

All participants used eHealth technologies in real home settings. The eHealth technologies that occurred most frequently were mobile apps (18/31, 58%), monitoring systems (12/31, 39%), web-based platforms (11/31, 35%), assistive technologies (2/31, 6%), and ambient awareness technology (1/31, 3%). No eHealth robots were included in this study. Most technologies were targeted at older adults with different noncommunicable diseases. Of those, the largest target groups were cardiac disease (5/31, 16%), diabetes (3/31, 10%), and cancer (3/31, 10%). In total, 2 technologies were used for older adults with polypharmacy issues and 2 for those in palliative care. In 16% (5/31) of studies, eHealth technologies were aimed at isolated older adults, and in 13% (4/31) of studies, the technology was for older adults with depression, anxiety, or apathetic qualities. In total, 1 eHealth technology was only for healthy older adults, and 5 were for older adults or adults of any age group in general. In some studies, the participants were veterans (4/31, 13%), and in others, they were older family caregivers (4/31, 13%).

To understand how older adults were supported while domesticating eHealth technologies, the thematic analysis produced 25 subcategories related to their learning to use and the use of technology. The subcategories were clustered into two upper-level categories: social network support (22/31, 71%) and nonsocial support (3/31, 10%). Of the 31 articles, 27 (87%) reported that support was provided to users during the domestication process [15,17].

To advance the understanding of older adults’ (aged ≥60 years) eHealth learning and use during its domestication, a systematic literature review of 31 empirical studies published between 2010 and January 2020 was conducted. The aim was to summarize the literature on the barriers and enablers that older adults encounter when learning to use and using eHealth technology and how they are supported in real home settings. The main targets were rural and remote older adults. The key findings of this review confirmed that social networks supporting older adults are important enablers for learning how to use and using eHealth technology. In addition, this review revealed that health-related difficulties often prevent older adults from domesticating eHealth technologies. Various eHealth technologies have been reported as necessary for older adults in rural and remote areas, although some sources of inconvenience and concern related to internet connectivity and use were found.

One of the goals of this review was to find out which barriers and enablers are related to learning how to use and using eHealth technologies in the domestication processes among older adults living at home. The findings were divided into 4 dimensions (appropriation, objectification, incorporation, and conversion) of the domestication process [15,17]. The barriers and enablers are in line with previous similar systematic reviews [24,26]. The accessibility of support and training, usability of the technology, and its suitability for daily life were also stressed in the present review. However, for example, concerns regarding the cost or importance of motivation to use eHealth technologies were not key factors in this review. There was a significant difference between the number of reported barriers (n=48) and enablers (n=63), with enablers being more common. This may be because of a desire to highlight the benefits of eHealth technology in a study, even if unintentionally. The appropriation dimension had the most barriers, which suggests that the first phase of domestication is critical. Previous research [68,69] has expressed that access and support for older adults using technology, especially in the early weeks of its domestication, may be the most important factor in successful technology adoption. Overall, the studies focused less on the learning process than on the use of technology.

In addition, this systematic review asked how older adults living at home are supported during the domestication of eHealth technology. In most cases, older adults distributed their digital competences with their social networks, which supported the domestication of eHealth technology. The social network included warm experts who are “nonprofessional persons who help inexperienced users come to terms with digital devices” [70], such as family members and peers. The network also included formal personnel, such as health care professionals and technical staff. Previous qualitative research related to eHealth learning and use [71] has underlined that there is a need to clarify the role of peer-to-peer support in the domestication of technology. This study revealed that peer-to-peer support has its place in the digital health technology context [38,44,52] as well as in other settings [14]. However, health care professionals were found to be the ones with whom digital competences were most often distributed; therefore, this review argues that digital competences related to eHealth learning and use are not only technical skills but also knowledge and skills related to health care, which is why health care professionals are also needed to support eHealth technology users.

This review’s final aim was to better understand the meanings attached to eHealth technologies for older adults living in rural and remote areas. Although the literature includes few studies set in rural and remote areas, this review confirms that eHealth technologies are needed in rural and remote areas for several reasons. eHealth technology is seen as solving many problems related to limited access to health care services, such as logistical, temporal, financial, and weather-related barriers. In addition, eHealth technologies can foster a sense of belonging in older rural residents by reducing feelings of isolation and by connecting them with peers or care providers. Previous research has also shown that ICT services can reduce social isolation and promote social connectivity in older adults experiencing physical and cognitive decline or living in remote areas [3,72,73]. However, the use of eHealth technology in rural and remote areas is hampered by the lack of high-speed internet connections and older adults’ lack of comfort in using ICTs. These issues are targets for future development. The findings of this systematic review confirm that the use and nonuse of eHealth technology are related to its fit in older adults’ technology-related cultural understanding and the context in which people act and live [13,14].

This review reveals several gaps that suggest directions for future research. First, a stronger focus on older adults’ learning processes is required in research on the domestication of eHealth technology. In the literature search, numerous articles focused only on older adults and the use of eHealth technology from a biomedical [74] or technical perspective [75]. They were excluded from the review as they did not focus on the user’s point of view. Burholt and Dobbs [2] also found that research on rural aging is dominated by a biomedical perspective. Second, as this review confirmed, eHealth technology is needed in rural and remote areas. Therefore, more studies in these settings are required to better understand the processes of domesticating eHealth technology among older rural residents. Third, research efforts in eHealth technology studies in real home settings are limited. Several studies were excluded from this review as they focused on a communal dwelling [76] or nursing home [77], although the aim of the care policies is aging in place [10], which may be because it is easier to reach older adults and conduct research in organized environments. Finally, methodologically, studies on the domestication of technology were mostly qualitative, and mixed methods studies were most common [18,78]. However, the studies reviewed here were mainly quantitative. Therefore, future qualitative studies on this topic should include the voices of older adults. Furthermore, by the time this review is published, new papers relevant to this topic will have also been published. Therefore, new systematic literature reviews should be regularly conducted on the topic of eHealth knowledge and use among older adults living at home in rural and remote areas.

This review has several limitations. First, as there was only 1 reviewer involved, this review’s quality and reliability were somewhat weakened. Additional reviewers would have challenged the decisions made by the author. Second, although the selected studies were conducted in 12 countries, Western countries and English-speaking countries dominated, and studies not written in English were excluded. As noted in earlier reviews [30], this may create a bias by, for example, basing the findings mainly on reports from Western cultures. Furthermore, despite this review’s intent, not all the studies were set in rural and remote areas, and therefore, its findings cannot be directly adopted in rural and remote contexts, with the exception of those of the third research question. The search included a comprehensive variation of health- and technology-related search terms (Textbox 1). The search terms did not include common abbreviations, such as eHealth and mHealth. However, these absences did not likely have a significant effect on the results. In addition, health technologies develop rapidly [35]; therefore, this review’s start date of 2010 may seem distant. However, a 10-year period is commonly used in qualitative reviews of eHealth technology [14,29]. As noted by Vuojärvi [79], “although technologies change rapidly, people and the ways technologies are used in everyday lives, and particularly in the learning process, do not necessarily do so.”

This literature review provides information and practical implications for designers, health care providers, and policy makers. eHealth technology targeted at older adults should be easy to use, and adequate support and training should be provided to users [25,80]. There are plenty of barriers that prevent older adults from ably and independently using eHealth technologies at home. Special attention should be paid to the most common barriers to learning how to use and using eHealth technologies: health-related difficulties, lack of internet connectivity, and other technical problems. We would like to emphasize the importance of considering older adults’ social and cultural practices when designing and implementing eHealth technologies. Social network support and technology integration into everyday life in rural areas contribute to a successful domestication process.