This cross-sectional study was conducted at the outpatient department of Siriraj Hospital, a major medical school that serves as a tertiary referral center in Bangkok, Thailand, from January to July 2021. The inclusion criteria comprised older patients and their relatives visiting the outpatient department. Individuals with communication difficulties such as language or hearing problems, or those who were unable to communicate fluently in Thai, were excluded.

The questionnaire was divided into three main sections. Part 1 focused on gathering general information about the participants including their age, sex, medical benefit occupation, monthly income, number of doctor visits per year, internet usage, duration of daily internet use, devices used for internet access, and prior experience with telemedicine usage. Part 2 assessed the participants’ eHealth literacy level using the eHealth Literacy Scale (eHEALs). The scale consists of eight questions designed to measure self-perceived ability to use technology for gathering health information combined with the knowledge, perceived comfort, and ability to find, evaluate, and implement electronic health information [18,19]. The scores are obtained by assessing the degree of agreement using a five-point Likert scale ranging from 1 “strongly disagree” to 5 “strongly agree” for each of 8 items. Therefore, the scores could range from 8 to 40, with higher scores indicating higher levels of eHealth literacy [20]. There are several methods for interpreting the results of eHEALs. To categorize eHealth literacy, a cut-off score was used to explore factors associated with overall level of eHealth literacy. For this purpose, we used the eHEALs cut-off score of ≥26 to indicate adequate eHealth literacy [21]. However, another method for classification of eHEALs was also used, by exploring each item of the questionnaire and rating the scores of 4 and 5 per item as ‘agreeing’ [22]. The high level of eHealth literacy was defined as having ‘agreeing’ ≥5 out of 8 eHEALS items [22]. This method would provide more insights into each eHealth literacy issue and may be more meaningful for considering solutions. Part 3 focused on the participants’ attitudes toward accessing telemedicine and included multiple-choice questions and opinion-based questions.

Research assistants explained the study to the participants using an information sheet. Adequate time was given to the participants to read the information sheet and ask any questions they had before provided written consent. Once consent was obtained, participants were requested to respond to the questionnaire. If any explanations were required, the research assistants provided additional information to help participants complete the questionnaire.

Ethical approval was obtained from the local ethical board, the Institutional Review Board of Faculty of Medicine, Siriraj Hospital, Mahidol University (SIRB) (COA no. Si 802/2020). Informed consent were obtained from all participants, in accordance with the principle of the Helsinki declaration. Data related to the participants’ identities were not collected in the case record forms. The personal information of participants were anonymized. Participants received US $15 for time expensed in answering the questionnaire.

The determination of sample size for this study was based on expected differences in proportion of eHealth literacy with the hypothesis that older people would have higher proportions of inadequate eHealth literacy compared to younger population. Inadequate eHealth literacy was classified using eHEALS score <26. Sample size calculation was estimated based on a previous study [21], where participants classified as having inadequate eHealth literacy comprised of 72.8% older participants and the group with adequate eHealth literacy had 57.9% of older people. When considering a two-sided type I error of 0.05 with 80% power, it was determined that 160 participants would be needed in each group. Allowing for 20% of incomplete data, a total of 400 participants were planned for the study.

Demographic information and characteristic variables were summarized using descriptive statistics. Continuous variables were represented by the mean (SD) for normally distributed data or median (IQR) for non-normal distributions. Categorical variables were described using frequency and percentage. For continuous variables, comparisons between the older and younger groups; two-sample t tests and Mann-Whitney U tests were applied after testing for normality of the data. Pearson’s χ² test or Fisher exact test were used to test categorical variables as appropriate. The analyses were performed using PASW Statistics for Windows (version 29.0, SPSS).

Our study highlights the very low level of eHealth literacy among older adults compared to younger adults in a middle-income country. Moreover, competency in several aspects of eHealth literacy in both older and younger groups was also unsatisfactory. Several factors associated with a low level of eHealth literacy in this study, such as age, income level, and education level, were nonmodifiable. However, eHealth literacy itself is modifiable through several interventions. The level of eHealth literacy further influences the acceptance and ability to undertake digital health care services. Factors affecting eHealth literacy and attitudes toward accepting telemedicine are key factors to explore and intervene when planning to implement novel digital technologies at the population level.

Several socioeconomic disadvantages are associated with lower levels of eHealth literacy. This study showed results concordant with previous studies [3,23-25], indicating that participants with lower levels of eHealth literacy were more likely to be older and have lower levels of educational attainment. Additionally, low eHealth literacy appeared to be related to inadequate financial resources, resulting in less exposure to digital devices and technologies. This trend was evidenced more prominently among the older adult group in our study, similar to findings from previous studies [23,26].

The concept of eHealth literacy among older individuals has been explored separately [3] from the younger population, as the need for support and barriers to implementation are substantially different. It has been emphasized that eHealth literacy increases with age among young adults, but decreases among older adults [3,23,25-28]. Among older participants in this study, the reported difficulties in eHealth literacy were related to having a low level of knowledge and skills in using the internet. This may also expand their lack of confidence in using information from the internet to make health-related decisions. Several systematic reviews and a recent scoping review demonstrated the benefit of interventions to improve level of eHealth literacy [29-31]. Most studies used health behavior and learning theories. Intervention materials commonly included existing or self-designed websites or applications, with some using incorporating standardized training materials. Outcome measures included information, psychological motivation, and behavioral changes, with only limited studies reporting improved health outcomes. Nevertheless, such strategies should still be considered when planning the delivery policy for implementing digital technologies among older people, not only to include standard materials and tools, but to deliver with more sessions of training programs to enhance confidence for older citizens.

During the COVID-19 pandemic, the importance of digital technologies has skyrocketed for disseminating health information and providing necessary services [22]. Telemedicine was one of the most widely expanded technologies, covering a broader range of health conditions, including preventive, curative, and rehabilitative aspects. The services also expanded to include several chronic medical conditions, including older people with frailty and dementia [32]. Nevertheless, there were some barriers to the adoption of technology among older adults. The top barriers to using telemedicine among older adults were related to a low level of eHealth literacy such as lack of knowledge, difficulty learning, and using the technology [8,21,22,33]. Moreover, concerns related to the privacy and security of the technology, as well as the health outcomes of using online services, were also raised [22]. Our studies discovered similar findings regarding those barriers, which appear to be modifiable through several interventions. However, age-related challenges such as hearing and vision impairments, functional limitations, and ergonomic difficulties, which were not directly addressed in our study, also significantly impact accessibility [22]. For instance, older adults with visual impairments may require larger font sizes, while those with degenerative joint conditions might benefit from specially designed interfaces. Although current conventional digital tools mat not be well-equipped for these changes and prevent older people from using it. These factors were not explored in our study but should also be considered when contemplating plans to implement digital technologies for older people.

Previous studies conducted in high-income countries have shown the benefits of arranging various styles of interventions to improve eHealth literacy in older people [30]. It has been shown that older people can become proficient in using technology, similar to younger adults, with adequate support, understandable explanations of its benefits, and a suitable learning pace [34]. Therefore, encouragement to gain knowledge and skills in digital technologies and having a positive attitude toward the use of telemedicine could enhance uptake in digital health for older adults. Low- and middle income countries are expected to have the highest proportion of older people, along with an expected shortage in several resources for delivering on-site health care services. Using digital health in appropriate service areas would be a promising solution for those settings. Being well prepared by including a training program for older users would increase the chances of successful implementation. Older people have the potential to learn and uptake novel technologies, not less than the younger population, but at different paces. Having volunteers in their communities to provide training through public health centers or activities clubs might be one of the interesting policies to reach more older groups. The process requires considerable work, such as developing local content, coordinating governments and private organizations to provide funding for eHealth literacy projects, and empowering community members to take the initiative to improve their health. However, this will be a sustainable option for the long term. Therefore, to overcome several limitations for older people in resource-limited settings, it is essential to implement a comprehensive policy with ongoing support from public and private sectors to enhance internet accessibility, improve digital literacy and competencies for people in the community. The establishment of a program such as the Intergenerational eHealth Literacy Program with additional support to explore and resolve structural limitations would be beneficial. The Intergenerational eHealth Literacy Program is designed to leverage the technological expertise of younger generations to teach older adults how to search for, understand, and evaluate health information from electronic sources, and apply the knowledge acquired to address health-related issues [35]. Adding a provision program to solve infrastructure issues would be essential. Such comprehensive policy would be an effective strategy to reduce barriers to access to digital technologies and to ensure sustainability.

Our study has some strengths and limitations. Firstly, we used eHAELS questionnaire, a standardized tool that has been validated across several countries with various settings. Secondly, we compared the level of eHealth literacy between older people and younger encounter in the LMIC setting where previous studies mostly conducted from high-income countries and not comparing across age-groups. However, there are several limitations in our studies worth mentioning. Firstly, the study was conducted using cross-sectional design which limits the ability to assess changes in eHealth literary over time. Secondly, the study used self-reported questionnaires to assess eHealth literacy and internet usage which might lead to some reporting bias. Nevertheless, several interventional studies exploring benefits of eHealth literacy and recent systematic reviews demonstrated that eHAELS is the most used and has been widely validated that allowed us to compare across settings [36]. Thirdly, our study was conducted in Thailand, one of the LMIC. The fact that it was conducted in one country, it might not be generalized to other countries with different settings. Fourthly, physical factors affecting eHealth literacy was not explored in this study. Lastly, other psychological aspects, apart from anxiety, such as perceived usefulness; ease of use and complexity of navigation of the sources, might also be affecting the willingness to engage with digital technology. These aspects were not explored in the present study.

Our study provides insight into the low level of eHealth literacy among older adults compared to younger participants in a middle-income country. We also address the barriers to uptake innovative modes of health care delivery that could be modifiable by providing suitable interventions. Providing information and service through digital technology for older adults would be more successful if adequate support were also prepared.