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The level of electronic health literacy among older adults: a systematic review and meta-analysis

Archives of Public Health volume 82, Article number: 204 (2024) Cite this article

Abstract

Background

In the context of deeper integration of the internet and healthcare services, eHealth literacy levels have become an important predictor of public health outcomes and health-promoting behaviors. However, there is a lack of comprehensive understanding of eHealth literacy levels among older adults.

Objective

To systematically assess the level of eHealth literacy among older adults.

Methods

We conducted searches in MEDLINE, Embase, Web of Science, CINAHL, PsycINFO, China National Knowledge Infrastructure Database (CNKI), Wanfang Database, Weipu Database (VIP), and Chinese Biomedical Database (Sinomed) to collect survey studies on the eHealth literacy levels of the older adults, with a search timeframe from the establishment of the database to May 2024. The quality of the included literature was assessed using the Agency for Healthcare Research and Quality (AHRQ) and the Newcastle-Ottawa Scale (NOS). Additionally, subgroup analysis and meta-regression were conducted to detect sources of heterogeneity. Funnel plots and Egger’s test were used to assess publication bias.

Results

A total of 48 relevant studies were included, including 45 cross-sectional, 2 cohort studies and 1 longitudinal study, comprising 33,919 older adults. The quality of the studies was all above moderate, with 10 high-quality publications. Meta-integration results showed that the eHealth literacy score of older adults was 21.45 (95% CI:19.81–23.08). Subgroup analysis showed that among the elderly population, females had lower eHealth literacy at 19.13 (95% CI:15.83–22.42), those aged 80 years and older had lower eHealth literacy at 16.55 (95% CI:11.73–21.38), and elderly individuals without a spouse and living alone had even lower eHealth literacy at 18.88 (95% CI:15.71–22.04) and 16.03 (95% CI:16.51–21.79). Based on region, eHealth literacy was lower among older adults in developing countries at 20.71 (95% CI:18.95–22.48). Meta-regression results indicate that sample size and region can significantly impact heterogeneity.

Conclusion

Our results found that the average eHealth literacy score of the elderly was 21.45, which was much lower than the passing level (≥ 32), suggesting that more attention should be paid to the eHealth literacy aspect of the elderly. Meanwhile, due to the limitation of the literature sources, the global representativeness of the results of this study still needs to be supported by more research data from other countries.

Peer Review reports

Text box 1 Contributions to the literature

EHealth literacy is one of the indispensable abilities in the Internet information age, but the overall eHealth literacy level of the elderly population is still unclear.

The level of eHealth literacy is closely related to health-related behaviors, so there is a need to focus on and improve the eHealth level of elderly people who live alone, especially in developing countries.

Policies and interventions need to be tailored to individuals, such as older women, who need more education on the use of electronic information technology.

Introduction

The World Health Organization reports that the global population aged 60 and older has surpassed 1 billion and is projected to reach 2.1 billion by 2050, further intensifying the trend of global aging [1]. It is well-established that as individuals age, their physiological systems decline, leading to an increase in health issues. As a result, the older adult population is the primary user of health services and has greater needs for medical information and services compared to other demographic groups [2, 3]. Prior to the advent of electronic information technology, older patients had limited access to medical protection and few options for medical services, such as health management, information counseling, and medical consultation. However, the internet has emerged as the most convenient and efficient means of obtaining and transmitting health information, thanks to the rapid advancement of information technology [4]. The growing utilization and incorporation of electronic information, communication technology, and mobile devices in healthcare have facilitated elderly individuals’ access to health information and medical services through online platforms such as the internet and smart devices [5].

Accessing medical services and information online is undeniably convenient, contingent upon possessing the necessary internet-enabled devices and proficiency in utilizing the internet. However, the vast array of information available online necessitates a discerning approach, as the quality of information can vary significantly. Therefore, individuals must also possess a level of critical thinking skills to navigate and evaluate the information effectively. Nevertheless, previous studies have indicated that older adults are a particularly vulnerable group in the digital age [6], only 5.56–83.46% of older adults utilize the Internet seek healthcare services and medical information [7, 8]. Additionally, more than 50% of the elderly face challenges in accessing reliable, high-quality health information and lack the ability to discern between credible sources [2, 9]. Research indicates that the effectiveness of eHealth technology adoption is constrained by the level of eHealth literacy of the public, the higher the level of eHealth literacy, the better the ability of information acquisition and assessment [10]. EHealth literacy was first proposed by scholars such as Norman, it refers to an individual’s ability to obtain, understand, evaluate health information from various online resources, and use it to solve health problems [11], eHealth literacy is considered a key skill that older adults must acquire in the digital age of disease management and healthcare, and is also predicted to be the most cost-effective means of maintaining health for all [4, 6]. Meanwhile, relevant scholars have discovered that the eHealth literacy of older adults is closely linked to their health outcomes. By enhancing the eHealth literacy levels of the elderly, their dietary habits can be improved, and their medication adherence can be strengthened [12, 13].

However, eHealth literacy levels vary based on time, environment, geographic region, and economic status. Some studies have noted significant differences in eHealth literacy between older and younger adults [14]. Currently, there is a lack of global data on the eHealth literacy levels of older adults. Therefore, the aim of our study is to conduct a systematic review of the relevant literature to accurately assess the level of eHealth literacy among older adults and identify potential influencing factors. This review aims to provide an evidence-based foundation for developing eHealth literacy interventions targeted at older adults.

Methods

The systematic review was performed according to the guidelines of the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA). The study protocol has completed registration on International Prospective Register of Systematic Reviews (PROSPERO), CRD42024529520.

Search strategy

In this study, MEDLINE, Embase, Web of Science, CINAHL, PsycINFO, CNKI, Wanfang, VIP, Sinomed were systematically searched by the researcher (XJ), and the researcher (YJL) supervised and reviewed the searching process and results from the time of database inception to May 2024. A combination of subject terms (e.g., Mesh subject terms were used to search PubMed) and free terms were used for the search. The following terms were used in the search strategy (“aged” OR “aging” OR “elder” OR “elderly” OR “old adult” OR “older adult” OR “old people” OR “older” OR “old” OR “senior” OR “senium”) AND (“eHealth literacy” OR “e-Health literacy” OR “ehealth literacy” OR " e-health literacy” OR “electronic health literacy” OR “digital health literacy” OR “mobile health literacy " OR “mHealth literacy”). Synonyms are connected using OR and non-synonyms are combined using AND. In addition, references to the included literature were tracked as an additional means of obtaining any other eligible studies. Detailed search strategies for each database are provided in Appendix 1, Supplementary Material.

Selection criteria

Inclusion criteria: (1) participants were older adults aged 60 years or above; (2) study type was observational studies including cross-sectional study or cohort study; (3) reports the electronic health literacy scores of the elderly or provides raw data that can be used for calculation; (4) the screening scale is the electronic health literacy scale (eHealth literacy scale, eHEALS). Exclusion criteria: (1) duplicate publication (Select the largest sample size or the newest survey time); (2) low-quality study (AHRQ scores ≤ 3 or NOS scores < 4); (3) study with no access to the full text or no raw data provided; (4) conference papers. (5) not published in Chinese or English languages.

Study selection and data extraction

The researchers employed EndNote 20 Literature Manager to import and manage the search results. Following the elimination of duplicates by EndNote 20, the researchers initially screened the literature by reading the titles and abstracts according to the inclusion and exclusion criteria. They then rescreened the articles retained after the initial screening by reading through the full text of the articles to determine the final literature to be included in the research. Two researchers (XJ and LSW) independently conducted the literature screening and data extraction, with the results cross-checked at the end of each step. Any discrepancies were resolved through discussion or consultation with a third researcher (GRW). The data extraction process involved the following elements: first author, year, country, survey setting, study design, age, sample size, and eHealth literacy score. Baseline data were extracted from cohort studies. In the event that multiple papers were published based on the same dataset, only the paper with the most comprehensive information was included in the analysis.

Quality assessment

The cross-sectional study was evaluated using the risk of bias assessment tool recommended by the Agency for Healthcare Research and Quality (AHRQ) [15]. The tool comprises 11 entries, with a total score of 11 points. Each entry is scored as “yes” with one point, “no” or “unclear” with zero points. A score of 0–3 was classified as indicative of low quality, 4–7 as indicative of medium quality, and 8–11 as indicative of high quality. For cohort studies, the methodological quality of each included study was evaluated using the Newcastle-Ottawa scale (NOS) [16]. The Newcastle-Ottawa scale comprises eight items and assesses each study in three domains. Each study was evaluated in three domains, with scores of 0–3, 4–6, and 7–9 indicating low, medium, and high quality, respectively. The assessment of the study was conducted by two researchers independently, with both researchers completing the evaluation and cross-checking the results. In the event of a discrepancy, the two researchers discussed the matter and, if they were unable to reach an agreement, a third party was consulted to make a determination.

Data analysis

The effect sizes of the study results were pooled and analyzed using Stata software (version 16.0). The heterogeneity of the study was determined jointly by Cochrane’s Q test and I2 index. A fixed-effects model was employed for meta-analysis in the presence of Ρ ≥ 0.05 and I2 < 50%, while a random-effects model was used for effect size pooling in the event of Ρ < 0.05 and I2 ≥ 50%. Subgroup analyses and meta-regression were also conducted to further analyze the sources of heterogeneity. To ascertain the stability and reliability of the study results, a one-by-one exclusion method was employed in sensitivity analyses. Statistical significance was determined at the 0.05 level. In order to detect the presence of publication bias in the outcome indicators, Egger’s test, funnel plot, and trim-and-fill method were combined.

Results

Search results

A comprehensive literature search yielded a total of 3476 studies. After eliminating duplicates, 2343 studies remained. Following an initial reading of titles and abstracts, 129 studies were selected for further analysis. After rescreening full-text,81 studies were excluded. Ultimately, 48 studies were included for meta-analysis. The specific process and results are shown in Fig. 1.

Fig. 1
figure 1

Flow diagram of the searching and screening of eHealth literacy for the older adults

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Study characteristics and methodological quality

A total of 48 studies were included in the study, cross sectional (n = 45), cohort studies (n = 2) and longitudinal study (n = 1) [Table 1]. The total sample size of the studies was 33,919, of which studies included a minimum sample size of 52 and a maximum of 6,183, with 22.4% of the studies having a sample size greater than 500. Most of the studies were published after 2020, with 2023 being the most common (n = 15) at 31.3%, and 77.6% of the studies were from developing countries. Literature quality assessment showed that all included studies were of medium to high quality, with high quality literature (n = 10), accounting for 20.8%. [Appendix 3, Supplementary Material]

Table 1 Characteristics of included studies of eHealth literacy among the older adults
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Results of the meta-analysis of the eHealth literacy

The results of the 48 included studies were tested for heterogeneity, and the results demonstrated significant heterogeneity among studies (I²=99.8%, P < 0.001). Therefore, the random effects model was employed for the analysis. The meta-analysis results indicated that the composite score of eHealth literacy among the elderly was 21.45 (95% CI: 19.81, 23.08). The forest plot is presented in Fig. 2.

Fig. 2
figure 2

Forest plot of eHealth literacy scores among older adults

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Subgroup analysis and metaregression analysis

The included studies were classified according to gender, age group(i.e.,60–69,70–79,and ≥ 80), marital status, residential status, sample size, and region( based on the United Nations criteria for classifying countries, i.e., developed country, or developing country) [Table 2].The results of the subgroup analysis indicated that men had higher eHealth literacy scores (21.46, 95% CI: 20.04–22.88) than women (19.13, 95% CI: 15.83–22.42). Based on age group, individuals aged ≥ 80 years old exhibited the lowest eHealth literacy scores (16.55, 95% CI: 11.73–21.38). The results of subgroup analysis indicated that those with no spouses and elderly living alone exhibited the lowest eHealth literacy levels, with scores of 18.88 (95% CI: 15.71–22.04) and 16.03 (95% CI: 16.51-2) The scores for sample sizes < 300, 300–500, and > 500 were 22.85 (95% CI: 20.95–24.74), 21.16 (95% CI: 18.75–23.57), 18.80(95%CI: 15.18–22.42). And the eHealth literacy levels of the elderly in developed and developing countries were 23.98 (95% CI: 20.78–27.17) and 20.71 (95% CI: 18.95–22.48), respectively. The meta-regression results are shown in Table 3.

Table 2 Subgroup analysis of eHealth literacy scores among older adults
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Table 3 Meta-regression analysis results of eHealth literacy scores among older adults
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Sensitivity analysis and publication Bias

A sensitivity analysis was conducted using the exclusion-by-exclusion method. The results demonstrated that there was no significant change in the scores obtained by excluding each study, suggesting that the results of the studies were more stable. The risk of bias was evaluated using a funnel plot and Egger’s test. The funnel plot indicated that the distribution of the included studies was not completely symmetrical (see Fig. 3). The result of Egger’s test (t = 2.39, P = 0.021 < 0.05) suggested that there was a certain publication bias in this study. Further analysis was conducted using the trim-and-fill method, which revealed that the distribution of the funnel plot was essentially symmetrical after the inclusion of nine additional documents, with a combined result of 20.02 (95% CI: 18.60, 21.44). (see Appendix 4, Supplementary material). And the combined results were statistically significant before and after using the trim-and-fill method (P < 0.001), indicating that the change in the combined effect value was not significant, the publication bias did not have a significant effect on the combined results, and the results were robust.

Fig. 3
figure 3

Funnel plot of publication bias in eHealth literacy scores for older adults

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Discussion

In the face of the intensifying global aging trend and the increase in the elderly population, paying attention to and safeguarding the physical health of the elderly population and maintaining their normal physiological functions are important measures to alleviate the medical pressure and economic burden, and to promote the sustainable development of the society. EHealth literacy, as an important predictor of health outcomes and health behaviors in the older adult, is one of the indispensable personal competencies for the older adult in the Internet information age. In this study, the eHealth literacy score of older adults was 21.45 (95% CI: 19.81,23.08), which was much lower than the pass level [33, 65]. EHealth literacy, as an important means of evaluating the public’s use of internet information technology, is considered to be a set of basic competencies that individuals possess to improve their self-health in the digital age [66]. The results of several systematic reviews have shown that [12, 13], there is a positive relationship between eHealth literacy and health-related behaviors, and that older adults with high e-health literacy perform better in self-care and medication use adherence. And interventions on eHealth literacy can help the physical condition and health management of the older adults [67].

Subgroup analysis by gender demonstrated that eHealth literacy was lower among older women than among older men, which is contrary to the findings of Meier et al [68] on health literacy among older adults. This may be attributed to the fact that eHealth literacy encompasses not only health literacy but also the ability to access and utilize electronic information using media, computers, etc [11, 22]. Kim et al. found [69] that females are indeed weaker than males in the utilization of electronic information technology, the probability of using the internet for men is 1.5% higher than that for women [70]. Yoon et al. pointed out [71] that socioeconomic status may directly affect older adults’ ability to use the internet. Most of the women in this study were from developing countries, and in the context of previous realities (economic situation of the country, distribution of educational resources, historical and cultural backgrounds, etc.), the lower socio-economic status of older women undoubtedly hindered their utilization of the internet [72]. Therefore, for elderly women, we should reduce their difficulty in accessing information and improve their ability to utilize electronic information technology, and promote the enhancement of elderly women’s eHealth literacy by increasing the convenience of accessing electronic information resources. Nevertheless, some scholars [73] have found that there is no difference in eHealth literacy by gender. This may be related to the fact that the study’s analyzed population also included adults under 60 years of age. This indicates that the disparity in women’s access to information resources is gradually diminishing.

A gradual decrease in eHealth literacy scores with increasing age was found in the age subgroups, which is consistent with the findings of previous studies [73, 74]. Although eHealth literacy has great potential for health promotion among older adults [66], older adults have difficulties in learning, accepting, and utilizing electronic information technology and online healthcare services due to various physiological, psychological, and others, including technology anxiety, declining cognitive abilities, and lack of training or support [75, 76], and the problem becomes more pronounced the older they get [77].But some studies [67] have indicated that positive training interventions have a positive effect on the eHealth literacy of older adults. In particular, face-to-face digital health literacy training has been shown to significantly improve the eHealth literacy level of older adults. Therefore, how to apply scientific and effective interventions to the real world is a key step in improving eHealth literacy among the elderly. Primary healthcare institutions, as the cornerstone of the medical service system, have characteristics such as convenient access to services and a wide coverage area. Therefore, we can rely on primary healthcare institutions, combined with the strength of community workers, to carry out training and guidance in electronic information technology (such as health information search methods, operational guidance for common applications, methods for identifying false information, etc.) gradually improve the electronic health literacy of the elderly to meet their practical needs in the digital age.

EHealth literacy scores were found to be lower among the older adults without spouses and living alone, a finding that is consistent with the results reported by Liu et al [74]. This may be attributed to the level of social support received. Prior research has indicated that social support is a significant predictor of older adults’ utilization of electronic information resources for the purpose of searching for health behaviors [78]. And it has also been found that adopting a collaborative peer learning approach has a long-term positive effect on eHealth literacy among older adults [79]. This suggests that eHealth literacy can be improved by increasing the social support of elderly people [73, 80]. Among the sources of social support, support from family and friends is an effective way to improve eHealth literacy [81, 82]. Consequently, an increasing number of scholars have put forth the proposition of bridging the digital divide among the elderly through the implementation of “technology feedback, intergenerational support, and peer education,” with the objective of enhancing their proficiency in internet usage.

Despite the results of the Meta regression analysis indicating that region and sample size may be significant factors influencing the heterogeneity of the study, heterogeneity still exists after conducting subgroup analyses based on region and sample size, suggesting that the sources of heterogeneity in the research still need further exploration. The results of the subgroup analysis by region show. that there are differences in the level of electronic health literacy between elderly people in developed countries and those in developing countries. The division of countries according to their level of development revealed that the older adults in developing countries exhibited lower levels of eHealth literacy. The reason for this may be related to differences in Internet information construction, the number of elderly population, and welfare protection for the older adults. As indicated by the World Health Organization (WHO), developing countries are experiencing the most rapid growth in the number of individuals aged 60 and above [1]. It is projected that by 2050, nearly 80% of the world’s older population will be residing in less developed countries. In light of the rapidly growing number of older adults, developing countries must take an active role in addressing the social, economic, and medical challenges posed by this demographic shift. It is imperative that they prioritize the health and well-being of their older populations and promote active aging. Meanwhile, in this study, it was observed that the results of studies divided into different sample sizes exhibited some discrepancies. The sample size has a direct impact on the accuracy and reliability of the results. Therefore, it is recommended that further large-sample, multicenter studies be conducted in the future to further validate the robustness of the results.

Strength and limitations

In general, our study conducted a comprehensive search of the relevant study on the eHealth literacy of the older adult and employed a systematic evaluation of the level of eHealth literacy among this population. Furthermore, studies with low quality literature were excluded in order to ensure the veracity and dependability of the data. Ultimately, our research also yielded insights into the key population for eHealth literacy intervention, offering a novel perspective for future research. Nevertheless, this study is not without limitations. First, this study included only Chinese and English literature, as well as a lack of searching the gray literature, which may have led to some bias in the data results; Secondly, significant heterogeneity was observed among the included studies, which may be due to differences in study design, sample inclusion, and data processing among the studies. Of course, the considerable heterogeneity between studies somewhat limits the generalizability of the results, and further validation of the results is still needed in the future; Next, the uneven distribution of samples and regions is another limitation of this study. Most of the studies included in the analysis come from developing countries, which may limit the representativeness of the electronic health knowledge levels of older adults in developed areas. Therefore, future studies should include more data from developed regions, which would be useful for further investigation and follow-up studies on the level of eHealth literacy among older adults.

Conclusions

In summary, our study found that the overall eHealth literacy level of the older adult is relatively low, which hinders the popularization and utilization of electronic information resources and internet medical services for the older adult. We also found that there are differences in the level of eHealth literacy among older adults by gender and age, and the reasons that hinder their use vary. Therefore, it is recommended that follow-up and management of eHealth literacy be added to the health management of the older adults to promote the formation and improvement of their health-related behaviors. For example, training classes can be organized in the community based on the different needs of the older adults (such as teaching mobile applications, popularizing electronic health literacy inquiry methods, methods for identifying online information, and solutions for when problems arise) to enhance their ability to apply, judge, and make decisions regarding electronic information; Secondly, knowledge competitions on electronic information technology, etc. can also be organized to understand and promote the elderly’s mastery of knowledge in the form of games; In addition, an eHealth literacy profile management booklet for the older adults can be established to conveniently record their usage of electronic information technology and any existing issues, facilitating the updating and setting of teaching content for future training classes.

Data availability

No datasets were generated or analysed during the current study.

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  1. Xin Jiang and Lushan Wang are co-first authors.

Authors and Affiliations

  1. Department of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, China

    Xin Jiang, Yingjie Leng, Ruonan Xie, Chengxiang Li & Zhuomiao Nie

  2. The Traditional Chinese Medicine Hospital of Longquanyi, Chengdu, 610100, China

    Lushan Wang

  3. Medical College of University of Electronic Science and Technology of China, Chengdu, 611731, China

    Daiqing Liu

  4. West China School of Public Health and West China Fourth Hospital, West China Nursing School, Sichuan University, Chengdu, 610041, China

    Guorong Wang

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Contributions

Study design: JX, WLS. Data extraction and collection: JX, LYJ, and XRN. Data analysis and interpretation: JX, LCX, and NZM. Manuscript writing: JX, LDQ. and WGR. All authors read and approved the final manuscript.

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Jiang, X., Wang, L., Leng, Y. et al. The level of electronic health literacy among older adults: a systematic review and meta-analysis. Arch Public Health 82, 204 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13690-024-01428-9

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Archives of Public Health

ISSN: 2049-3258