Xinxin Wang
Wei Luan- 1Shanghai Jiao Tong University School of Nursing, Shanghai, China
- 2Department of VIP Service, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
With the rapid development of digital health today, the lack of digital health literacy in older adults is an urgent problem. It is crucial that older adults adapt to the digital reform in medical treatment, pension, health management, and other fields. Therefore, we reviewed the current development status of digital health literacy among older adults. A total of 47 articles were included in this scoping review. Our findings revealed that research on digital health literacy in older adults is still in its infancy. Further development is warranted especially in terms of assessment tools and intervention methods.
Introduction
With the rapid development of modern science and technology, the achievements of digital technologies such as artificial intelligence, virtual and augmented reality, and machine learning have been continuously applied in healthcare services (1). While the quality of healthcare products and services has improved, the ways in which older adults acquire and share health knowledge is also changing (2). In China, 95.09% of older adults believe that it is necessary to learn to browse the Internet after the initial stages of the COVID-19 pandemic, and 93.36% suppose that they can learn to use a smartphone (3), which reflects their strong desire to use digital technology. Therefore, to arouse enthusiasm of older adults in health management and make digital devices and software more accessible for use, it is also important to improve the digital health literacy (DHL) of older adults. DHL is an extended concept of health literacy, which refers to the ability of individuals to acquire, process, communicate, and understand health information and services, make effective health decisions, and promote and improve individual and collective health in the context of the use of digital information and technologies (4).
According to the definition provided by Norman and Skinner (5), eHealth Literacy (eHL) is “the ability to seek, discover, evaluate, and appraise eHealth information, and apply the acquired knowledge to solve health problems” (5). Moreover, Norman pointed out that with the continuous development of new technologies and environmental changes, the way in which health knowledge spreads will evolve with the corresponding environmental changes (6). The development of science and technology in recent years has a significant impact on individual's medical procedures, health management methods, and community health services. Although many scholars have considered the impact of technological development on the concept of eHL. However, while they have tried to update the concept of eHL, they still use the term eHL (7–9). In 2012, the concept of DHL was first mentioned (10). Compared with eHL, DHL measures focus on interactivity on the Web, including adding self-generated content and protecting privacy (11). Under the framework of DHL, health knowledge is presented to individuals more attractively, by providing continuous, dynamic, and highly personalized health management solutions, improving personal health management capabilities while focusing on individual health and living a healthier life (1).
Prior literature shows that age, gender, educational attainment, marital status, credibility of Internet health information, experience and more were identified as modifiable factors related to eHL in older adults (12–14). Kim et al. (15) and Karnoe et al. (16) summarized the assessment tools for eHL. The systematic review of Oh SS et al. focused on the evaluation tools of eHL in older adults (17). Jacobs RJ et al. outlined eHealth interventions to improve health literacy, and the review results show that computer-based applications were the most common intervention methods (18). Choukou MA et al. summarized how e-services implemented in vulnerable populations improved DHL during the COVID-19 pandemic and identified the barriers and facilitators for their implementation (19). However, most reviews still use the concept of eHL and they do not distinguish between eHL and DHL. While eHL and DHL are often used interchangeably, eHL measurement is distinguished by focusing on online health information gathering (11). As the concept of digital literacy has evolved in recent years, so has that of DHL. Therefore, this scoping review includes studies that apply both eHL and DHL concepts, considering eHL as the predecessor of DHL.
Purpose
This review aims to describe and synthesize published research related to DHL among older adults. The focus is on research findings related to the influencing factors, impacts, assessment tools, and intervention methods. The questions that guided the review were: (1) What factors affect DHL in older adults? (2) How does DHL affect older adults? (3) Which tools have been used to assess DHL among older adults? (4) What are the existing methods to improve the DHL of older adults?
Methods
A scoping review intends to examine the scope and nature of existing research on a topic or issue, determine the value of conducting a comprehensive systematic review, and identify gaps in the existing research (20). A scoping review methodology is based on the framework outlined by Arksey and O'Malley (21). Scoping reviews use descriptive summaries and inductive analysis to summarize research findings. This review aims to provide a comprehensive summary of the existing relevant literature, and therefore does not perform a critical appraisal of included studies.
Search
Articles were identified by searching four databases: Web of Science (All Databases), PubMed, Embase.com, and Chinese database CNKI. The databases were searched in January 2022 and June 2022. A librarian at the University was consulted for assistance with the search. The following search terms were used: digital health literacy; eHealth literacy; e-health literacy; old*; old people; older; older people; older adult; elder; elder people; elders; elderly people; elder adults; aged; aged people; aged person; aging. Secondary searches included the following terms: computer literacy; online health literacy; electronic health literacy; health information literacy; health information seeking; health information searching; senior; baby boomer; retiree*. Inclusion criteria were: (1) Chinese and English literature published between 2011 and 2021. (2) Literature related to DHL or eHL. (3) The participants were older adults (age ≥ 65) or belonged to a subgroup of older adults. Exclusion criteria were: (1) Reviews, books, letters to the editor, and abstracts of speeches. (2) The participants were adults, and there was no subgroup of older adults.
Search outcome
The initial and secondary search yielded 1,924 articles. The literature search results were reviewed, and duplicate results were excluded using Endnote X9, leaving 1,468 articles. According to the inclusion and exclusion criteria of the study, two authors independently scrutinized the titles and abstracts of the articles, leaving 613 articles. If two reviewers had doubts, the full version was analyzed independently. Disagreements between the reviewers were solved by a third reviewer. A total of 134 full-text articles were assessed for eligibility. After screening the full-text articles, 47 articles were finally included [Figure 1 (22)].
Figure 1. Flowchart of the literature screening process.
Results
Influencing factors
Socio-demographic factors
Several studies showed that gender, age, place of residence, education level, marital status, socioeconomic status, pension methods, and type of medical insurance are the main factors affecting the DHL of older adults (23–32). Those who were younger, had a higher level of education, and a higher socioeconomic status tended to have higher DHL.
Factors related to digital equipment
Factors such as whether older adults own digital devices (23, 28), the frequency of using digital devices (31, 33), and the range of Internet activities (31) will also affect their DHL. Older adults who own digital devices and have a high usage rate are more likely to have high DHL.
Social support factors
Older people's confidence in their DHL often depends on others. If someone in the family is proficient in digital technology and can effectively share health information, they are able to manage their health together (34). Meanwhile, a library or community support also plays a positive role in improving health behaviors and outcomes in older adults (35).
Psychological factors
Older people with more positive attitudes toward health knowledge (23, 35), higher interest in digital technology, and confidence in managing their health through digital devices have higher self-rated DHL scores (24, 36, 37) (Table 1).
Table 1. Influencing factors of DHL among older adults.
The impacts of DHL
When exploring the relationship between an eHL health-promoting lifestyle, and health cognition in the Chinese older adults, Li et al. proposed that a health-promoting lifestyle is related to eHL and cognitive health (32), and Cui et al. found that eHL was an important mediating factor for older adults' structural social capital and health behaviors (26). Liu et al. stated that the eHL of older adults can directly affect their quality of life and indirectly affect it by influencing life satisfaction (39). Seçkin et al. discovered that in their sample of older adults the eHL and electronic confidence measures were significant predictors of a positive health perception index (40). Ernsting C proposed that eHL is necessary for the successful use of health apps and should be fully considered in designing health education strategies (41). Lin et al. pointed out that eHL has direct and indirect effects on medication adherence and quality of life (38). In addition, in the context of the COVID-19 pandemic, some scholars have emphasized that older adults' sense of coherence has a direct negative impact on anxiety and plays a mediating role in the relationship between anxiety and DHL or financial satisfaction (42, 43). According to the health empowerment theory, enhancing health empowerment requires identifying and recognizing personal and social background resources. For older adults isolated at home alone, eHL and social support can predict their self-care behaviors, which can be used to promote and sustain self-care practices (44).
Assessment tools
Since Norman and Skinner developed the first eHL assessment scale in 2006, an increasing number of assessment scales have been created. With the continuous development of science and technology, the core of assessment gradually shifted from eHL to DHL. This review distills tools that have been used for older adults. No assessment tools have been identified that only target older adults for DHL (Table 2).
Table 2. DHL assessment tools for older adults.
eHealth literacy scale (eHEALS)
The eHEALS (5) is a scale designed to measure an individual's combined knowledge, comfort, and perceptual skills in discovering, evaluating, and applying ehealth information to address health problems. Norman and Skinner compiled it based on their Lily Model of eHL (5). The scale's Cronbach α was 0.88. The correlation coefficient ranged from r = 0.51 to 0.76, and from baseline to 6-month follow-up, the test-retest reliability ranged from 0.68–0.40. At present, local translation, reliability, and validity studies of the scale have been conducted among older adults in many countries, proving that eHEALS is a reliable and effective tool for older adults (47–55). Although it is the most widely used DHL assessment tool so far, eHEALS is a self-assessment scale and lacks objective items for evaluating the DHL of older adults. In the face of the great changes in health knowledge acquisition and communication induced by today's digital environment, eHEALS' existing projects are insufficient.
Electronic health literacy scale (e-HLS)
e-HLS is a self-assessment scale developed by Seckin et al. (56). Through exploratory factor analysis and confirmatory factor analysis, for the older subsample (age ≥ 60 years) the Cronbach α = 0.94, CFI = 0.95, NFI = 0.90. e-HLS evaluates the six competencies mentioned in the traditional concept of e-health literacy while paying attention to the expansion of the concept of eHL, by adding indicators for evaluation, communication, and use of e-health information. It contains tools in three domains: behavioral literacy (action factor), cognitive literacy (trust factor), and interaction literacy (communication factor) (56). He et al. examined the reliability and validity of e-HLS among patients with stroke in China. They found that e-HLS can be applied to these patients after translation and cultural adaption (Cronbach'α = 0.907, test-retest reliability = 0.691) (57).
Digital health literacy scale (DHLI)
Van der Vaart and Drossaert developed DHLI in 2017 to measure navigation skills, operational skills, evaluating reliability, information searching, and determining relevance. Based on eHEALS, the evaluation of information communication and privacy confidentiality ability was included (11). Additionally, the researchers added a simulated situational assessment for each skill. In a study among older Korean adults, the Cronbach α = 0.93, and test-retest reliability was 0.844. Findings suggest that K-DHLI is reliable and effective for evaluating the use of e-health resources in older adults (47).
The eHealth literacy questionnaire (eHLQ)
eHLQ is a self-assessment evaluation tool developed by Kayser et al. (45). It is based on the Ehealth Literacy Framework(eHLF), which comprises seven dimensions that describe the attributes of the users, the intersection between users and the technologies, and users' experience of systems (45, 58). After using the Bayesian mediated multiple indicators and cause models, Cheng's research demonstrates that eHLQ can be used to access valuable suggestions, help optimize digital health use, and promote health equity (59).
Digital health literacy assessment (DHLA)
DHLA was developed by Liu et al. (46). The researchers considered that the environment and culture also impact DHL, and therefore, based on eHEALS, items related to these factors were included. It is a self-assessment tool that can classify participants into high, moderate, and low-risk groups based on the degree of risk of misinterpreting health information. The internal consistency of DHLA was satisfactory (α = 0.87), and the construct validity factor analysis found three factors, accounting for 76.6% of the variance. Studies have not yet been conducted with older adults in other countries (46).
Intervention method
The existing DHL intervention methods for older adults are primarily based on education and training. Usually, they adopt the Health Belief Model and the Information-Motivation-Behavioral skills model as the conceptual framework (60–63). Of the included studies, three entailed face-to-face teaching. Chang et al. conducted a structured curriculum in community activity centers for older adults. The course content was practical and effectively improved their DHL (61). However, the training process did not vary according to individuals, and the training interface did not fully consider the needs of older adults (such as fonts and article length). Lee and Kim adopted an intergenerational mentoring approach, allowing college students to provide face-to-face mentoring to older adults, ensuring that older adults have a pleasant learning experience while also addressing their problems in a targeted manner (64). However, they included a small sample and did not explicitly assess what older adults learned. Xie reduced the computer anxiety of older adults and increased their interest in health knowledge by allowing them to conduct unified training in the library (65). However, the study did not have a control group and could not prove whether the intervention was scientifically effective. Of the included studies, four studies adopted online interventions. Prior to the intervention, older adults' DHL status and training needs were established in advance through focus group discussions or questionnaires. Fink et al. and Nahm et al. have designed courses that can improve older adults' digital health knowledge and digital equipment operation skills (62, 63); The course designed by Perestelo-Perez et al. not only provides reading materials, videos, and online exams but also allows older adults to communicate with each other in the learning process (60). Bevilacqua et al. used a training called ACCESS program, which was based on blended didactical and interactive educational techniques (66). It enables older adults to gradually master the concept of digital health by using related applications, and adopting digital health equipment or software to communicate in five-stage courses. In the context of the ongoing COVID-19 pandemic, online teaching is more conducive to preventing the spread of the virus. However, online education requires certain resources (such as computers and mobile phones); therefore, online education is inaccessible to older adults who do not have or use such equipment (Table 3).
Table 3. Intervention methods for improving older adults' DHL.
Discussion
The primary factors that affect the DHL of older adults include demographic and sociological factors, whether or not they use digital devices, confidence in managing health through digital devices, attitudes, and family support. Older people with better social conditions and higher education are more likely to accept digital technology to manage their health. Attitudes toward digital health and digital devices will also affect their use. Meanwhile, the DHL of older adults will directly or indirectly affect their quality of life, life satisfaction, anxiety, and other factors. Notably, all of the included cross-sectional studies employ the concept of eHL regardless of the year in which the study was conducted. In future research on older adults, researchers should introduce the concept of DHL and corresponding evaluation tools to explore the influencing factors of older adults' DHL. The demographic and socioeconomic characteristics of older adults should be further split to obtain more detailed information on the factors related to DHL. More in-depth research will help better understand the current situation of DHL in older adults to facilitate improvement in their DHL in a targeted manner.
Among the assessment tools used to evaluate the DHL of older adults, eHEALS has been widely used in research in many countries over the past 5 years, and is a popular assessment tool. Except for DHLI, which employs virtual situations to evaluate the simulated operation of older adults, the others use self-evaluation, which may lack objectivity. Furthermore, all research tools included in this review have only been adaptively tested in older adults and were not developed to validate DHL in older adults specifically. In the future, researchers that develop assessment tools should be aware that the concept of DHL is constantly evolving, and the competencies it requires from individuals are different from those of eHL. In addition to evaluating the ability to obtain, evaluate, and apply health information, the ability to communicate, integrate health information, and protect privacy in the process should also be evaluated. In addition, to evaluate the DHL of older adults more accurately, researchers may consider developing an evaluation tool applied especially to older adults. Moreover, they should attempt to avoid the questionnaire method owing to the lack of objectivity in the evaluation results.
In general, the existing intervention methods to improve the DHL of older adults have achieved certain results such as improving the eHEALS score, strengthening the computer application ability of older adults, and enhancing the confidence of older adults in the application of digital devices. In the future, in addition to the design of intervention methods, researchers should consider the following aspects: Prior to training, older adults should be apprised of the benefits of digital technology. Researchers should mobilize older adults' enthusiasm to learn to enhance their confidence in health management through digital technology. Additionally, it is important to identify the possibility of implementing group teaching for older adults with different digital abilities. During the training process, researchers should also pay attention to the continuous decline of older adults' cognitive and physical functions (67). Researchers should revise training plans dynamically while accurately assessing the training needs of older adults and adding customisations based on individual preferences. After the initial stages of the COVID-19 pandemic, the digital health teaching method for older adults may change. The previous face-to-face teaching method may not have been carried out effectively owing to pandemic-related restrictions. If an online course approach is adopted, it will create another obstacle for older adults. Further teaching methods should be developed in the future exploration of teaching practice, such as family collaboration mode and mutual aid mode.
Limitations
Although four commonly used databases were applied for the literature search, studies on older adults' DHL in other databases may have been excluded. Additionally, the title and abstract review may be insufficient to reflect the initial findings of all studies effectively, and some relevant articles may have been removed. Finally, only Chinese and English literature were selected in this review process, which may result in an incomplete literature search.
Conclusion
The results of this scoping review reflect the current state of research on DHL in older adults. In general, among the included studies, not many studies focus solely on DHL, and most studies still focus on eHL or consider eHL and DHL as the same. However, although in recent years digital technologies have been increasingly applied to older adults' health care, the capabilities contained in the conceptual framework of eHL have been unable to cope with it effectively. Therefore, to ensure equitable and inclusive access to health knowledge in the digital healthcare era, DHL for older adults needs to be improved, as this attempt can bridge the digital divide and improve health equity. In the future, studies are required for comprehensive and in-depth exploration of DHL of older adults.
Author contributions
XW and WL contributed to the literature review and classification. XW wrote the first draft of the manuscript. WL contributed to manuscript revision and approved the submitted version. All authors contributed to the article and approved the submitted version.
Funding
This study has been funded by Shanghai Municipal Health Commission (202150032), Shanghai Hospital Association (X2020083), and Shanghai Jiao Tong University (ZT201902).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
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References
1. Dunn P, Conard S. Digital health literacy in cardiovascular research. Int J Cardiol. (2018) 269:274–5. doi: 10.1016/j.ijcard.2018.07.011
2. Alvarez-Galvez J, Salinas-Perez JA, Montagni I, Salvador-Carulla L. The persistence of digital divides in the use of health information: a comparative study in 28 European countries. Int J Public Health. (2020) 65:325–33. doi: 10.1007/s00038-020-01363-w
3. Institute of Social Development Strategy Development CAoSS. Internet Ageing Research in the Post-Epidemic Era. Available online at: http://ie.bjd.com.cn/a/202109/26/AP614fcff1e4b07f4e484fd7cd.html (accessed September 26, 2021).
4. Dunn P, Hazzard E. Technology approaches to digital health literacy. Int J Cardiol. (2019) 293:294–6. doi: 10.1016/j.ijcard.2019.06.039
5. Norman CD, Skinner HA. Eheals: the ehealth literacy scale. J Med Internet Res. (2006) 8:e27. doi: 10.2196/jmir.8.4.e27
6. Norman C. Ehealth literacy 2.0: problems and opportunities with an evolving concept. J Med Internet Res. (2011) 13:e125. doi: 10.2196/jmir.2035
7. Chan CV, Kaufman DR. A framework for characterizing ehealth literacy demands and barriers. J Med Internet Res. (2011) 13:e94. doi: 10.2196/jmir.1750
8. Kayser L, Kushniruk A, Osborne RH, Norgaard O, Turner P. Enhancing the effectiveness of consumer-focused health information technology systems through ehealth literacy: a framework for understanding users' needs. JMIR Human Fact. (2015) 2:e9. doi: 10.2196/humanfactors.3696
9. Paige SR, Stellefson M, Krieger JL, Anderson-Lewis C, Cheong J, Stopka C. Proposing a transactional model of ehealth literacy: concept analysis. J Med Internet Res. (2018) 20:e10175. doi: 10.2196/10175
10. Mein E, Fuentes B, Soto Más F, Muro A. Incorporating digital health literacy into adult Esl education on the Us-Mexico border. Rhetor Prof Commun Glob. (2012) 3:162–74.
11. van der Vaart R., Drossaert C. Development of the digital health literacy instrument: measuring a broad spectrum of health 10 and health 20 skills. J Med Internet Res. (2017) 19:e27. doi: 10.2196/jmir.6709
12. Shi Y, Ma D, Zhang J, Chen B. In the digital age: a systematic literature review of the E-health literacy and influencing factors among Chinese older adults. Z Gesundh Wiss. (2021)4:1–9. doi: 10.1007/s10389-021-01604-z
13. Chesser A, Burke A, Reyes J, Rohrberg T. Navigating the digital divide: a systematic review of ehealth literacy in underserved populations in the United States. Inform Health Soc Care. (2016) 41:1–19. doi: 10.3109/17538157.2014.948171
14. Chang SJ, Jang SJ, Lee H, Kim H. Building on evidence to improve ehealth literacy in older adults: a systematic review. CIN. (2021) 39:241–7. doi: 10.1097/CIN.0000000000000674
15. Oh SS, Kim KA, Kim M, Oh J, Chu SH, Choi J. Measurement of digital literacy among older adults: systematic review. J Med Internet Res. (2021) 23:e26145. doi: 10.2196/26145
16. Karnoe A, Kayser L. How is ehealth literacy measured and what do the measurements tell us? a systematic review knowledge. Manag E-Learn. (2015) 7:576–600. doi: 10.34105/j.kmel.2015.07.038
17. Kim H, Xie B. Health literacy in the ehealth era: a systematic review of the 9literature. Patient Educ Couns. (2017) 100:1073–82. doi: 10.1016/j.pec.2017.01.015
18. Jacobs RJ, Lou JQ, Ownby RL, Caballero J. A systematic review of ehealth interventions to improve health literacy. Health Informatics J. (2016) 22:81–98. doi: 10.1177/1460458214534092
19. Choukou MA, Sanchez-Ramirez DC, Pol M, Uddin M, Monnin C, Syed-Abdul S. Covid-19 infodemic and digital health literacy in vulnerable populations: a scoping review. Digital Health. (2022) 8:20552076221076927. doi: 10.1177/20552076221076927
20. Peters MD, Godfrey CM, Khalil H, McInerney P, Parker D, Soares CB. Guidance for conducting systematic scoping reviews. Int J Evid Based Healthc. (2015) 13:141–6. doi: 10.1097/XEB.0000000000000050
21. Arksey H, O'Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. (2005) 8:19–32. doi: 10.1080/1364557032000119616
22. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The prisma 2020 statement: an updated guideline for reporting systematic reviews. BMJ. (2021) 372:n71. doi: 10.1136/bmj.n71
23. Arcury TA, Sandberg JC, Melius KP, Quandt SA, Leng X, Latulipe C, et al. Older adult internet use and ehealth literacy. J Appl Gerontol. (2020) 39:141–50. doi: 10.1177/0733464818807468
24. De Santis KK, Jahnel T, Sina E, Wienert J, Zeeb H. Digitization and health in Germany: cross-sectional Nationwide Survey. JMIR Public Health Surveill. (2021) 7:e32951. doi: 10.2196/32951
25. Liu Z, Zhang H, Zhang Y, Du C-C, LI H-J, Zhao J, et al. Current situation and influencing factors of e-health literacy among rural older adults in Zhengzhou. Modern Prevent Med. (2020) 47:283–286+309. Available online at: https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFDLAST2020&filename=XDYF202002023&uniplatform=NZKPT&v=vm1EScKczwEsMyg-z2SKiyYNRrvNQWZKP-x-xF4LpnLsdJhZrd8h_R2MjnxVlgw
26. Cui GH Li SJ, Yin YT, Chen LJ Li JQ, Liang FY, et al. The relationship among social capital, ehealth literacy and health behaviours in Chinese elderly people: a cross-sectional study. BMC Public Health. (2021) 21:45. doi: 10.1186/s12889-020-10037-4
27. Lee OE-K, Kim D-H, Beum KA. Factors affecting information and communication technology use and ehealth literacy among older adults in the Us and South Korea. Educ Gerontol. (2020) 46:575–86. doi: 10.1080/03601277.2020.1790162
28. Cherid C, Baghdadli A, Wall M, Mayo NE, Berry G, Harvey EJ, et al. Current level of technology use, health and ehealth literacy in older canadians with a recent fracture-a survey in orthopedic clinics. Osteoporos Int. (2020) 31:1333–40. doi: 10.1007/s00198-020-05359-3
29. Tennant B, Stellefson M, Dodd V, Chaney B, Chaney D, Paige S, et al. ehealth literacy and web 20 health information seeking behaviors among baby boomers and older adults. J Med Internet Res. (2015) 17:e70. doi: 10.2196/jmir.3992
30. Zhou H, Zheng A. Current situation and influencing factors of e-health literacy among community older adults. JNanjing Med Uni(Soc Sci). (2018) 18:455–8. doi: 10.7655/NYDXBSS20180610
31. Berkowsky RW. Exploring predictors of ehealth literacy among older adults: findings from the 2020 Calspeaks survey. Gerontol Geriatr Med. (2021) 7:23337214211064227. doi: 10.1177/23337214211064227
32. Li S, Cui G, Yin Y, Wang S, Liu X, Chen L. Health-promoting behaviors mediate the relationship between ehealth literacy and health-related quality of life among chinese older adults: a cross-sectional study. Qual Life Res. (2021) 30:2235–43. doi: 10.1007/s11136-021-02797-2
33. Papp-Zipernovszky O, Horváth MD, Schulz PJ, Csabai M. Generation gaps in digital health literacy and their impact on health information seeking behavior and health empowerment in Hungary. Front Public Health. (2021) 9:635943. doi: 10.3389/fpubh.2021.635943
34. Magsamen-Conrad K, Dillon JM, Verhoff CB, Faulkner SL. Online health-information seeking among older populations: family influences and the role of the medical professional. Health Commun. (2019) 34:859–71. doi: 10.1080/10410236.2018.1439265
35. Lin Z, Zhang Y, Matteson M, Li X, Tu X, Zhou Y, et al. Older adults' ehealth literacy and the role libraries can play. J Librariansh Inf Sci. (2021) 53:488–98. doi: 10.1177/0961000620962847
36. Yang E, Chang SJ Ryu H, Kim HJ, Jang SJ. Comparing factors associated with ehealth literacy between young and older adults. J Gerontol Nurs. (2020) 46:46–56. doi: 10.3928/00989134-20200707-02
37. Cajita MI, Hodgson NA, Budhathoki C, Han H-R. Intention to use mhealth in older adults with heart failure. J Cardiovasc Nurs. (2017) 32:E1–7. doi: 10.1097/JCN.0000000000000401
38. Lin CY, Ganji M, Griffiths MD, Bravell ME, Broström A, Pakpour AH. Mediated effects of insomnia, psychological distress and medication adherence in the association of ehealth literacy and cardiac events among iranian older patients with heart failure: a longitudinal study. Eur J Cardiovasc Nurs. (2020) 19:155–64. doi: 10.1177/1474515119873648
39. Liu W, Qin W, Xu L, Gao Z, Hu F, Zhang J, et al. Associations of e-health literacy with life satisfaction and quality of life among the elderly in Tai'an City. Chi J Public Health. (2021) 37:1333–6. doi: 10.11847/zgggws1135051
40. Seçkin G, Hughes S, Yeatts D, Degreve T. Digital pathways to positive health perceptions: does age moderate the relationship between medical satisfaction and positive health perceptions among middle-aged and older internet users? Innov Aging. (2019) 3:igy039. doi: 10.1093/geroni/igy039
41. Ernsting C, Stühmann LM, Dombrowski SU, Voigt-Antons JN, Kuhlmey A, Gellert P. Associations of health app use and perceived effectiveness in people with cardiovascular diseases and diabetes: population-based survey. JMIR Mhealth Uhealth. (2019) 7:e12179. doi: 10.2196/12179
42. Leung AYM, Parial LL, Tolabing MC, Sim T, Mo P, Okan O, et al. Sense of coherence mediates the relationship between digital health literacy and anxiety about the future in aging population during the Covid-19 pandemic: a path analysis. Aging Ment Health. (2020):. doi: 10.1080/13607863.2020.1870206
43. Yang BX, Xia L, Huang R, Chen P, Luo D, Liu Q, et al. Relationship between ehealth literacy and psychological status during Covid-19 pandemic: a survey of chinese residents. J Nurs Manag. (2021) 29:805–12. doi: 10.1111/jonm.13221
44. Wong AKC, Bayuo J, Wong FKY. Investigating predictors of self-care behavior among homebound older adults: the role of self-efficacy, ehealth literacy, and perceived social support. J Nurs Scholarsh. (2021). doi: 10.1111/jnu.12730
45. Kayser L, Karnoe A, Furstrand D, Batterham R, Christensen KB, Elsworth G, et al. A multidimensional tool based on the ehealth literacy framework: development and initial validity testing of the ehealth literacy questionnaire (Ehlq). J Med Internet Res. (2018) 20:e36. doi: 10.2196/jmir.8371
46. Liu P, Yeh L-L, Wang J-Y, Lee S-T. Relationship between levels of digital health literacy based on the Taiwan digital health literacy assessment and accurate assessment of online health information: cross-sectional questionnaire study. J Med Internet Res. (2020) 22:e19767. doi: 10.2196/19767
47. Kim H, Yang E, Ryu H, Kim HJ, Jang SJ, Chang SJ. Psychometric comparisons of measures of ehealth literacy using a sample of Korean older adults. Int J Older People Nurs. (2021) 16:e12369. doi: 10.1111/opn.12369
48. Stellefson M, Paige SR, Tennant B, Alber JM, Chaney BH, Chaney D, et al. Reliability and validity of the telephone-based ehealth literacy scale among older adults: cross-sectional survey. J Med Internet Res. (2017) 19:e362. doi: 10.2196/jmir.8481
49. Aponte J, Nokes KM. Validating an electronic health literacy scale in an older hispanic population. J Clin Nurs. (2017) 26:2703–11. doi: 10.1111/jocn.13763
50. Chung SY, Nahm ES. Testing reliability and validity of the ehealth literacy scale (eheals) for older adults recruited online. CIN. (2015) 33:150–6. doi: 10.1097/CIN.0000000000000146
51. Baek JJH, Soares GH, da Rosa GC, Mialhe FL, Biazevic MGH, Michel-Crosato E. Network analysis and psychometric properties of the brazilian version of the ehealth literacy scale in a dental clinic setting. Int J Med Inform. (2021) 153:104532. doi: 10.1016/j.ijmedinf.2021.104532
52. Lin C-Y, Brostrom A, Griffiths MD, Pakpour AH. Psychometric evaluation of the persian ehealth literacy scale (eheals) among elder iranians with heart failure. Eval Health Prof. (2020) 43:222–9. doi: 10.1177/0163278719827997
53. Zrubka Z, Hajdu O, Rencz F, Baji P, Gulacsi L, Pentek M. Psychometric properties of the hungarian version of the ehealth literacy scale. Eur J Health Econ. (2019) 20:S57–69. doi: 10.1007/s10198-019-01062-1
54. Sudbury-Riley L, FitzPatrick M, Schulz PJ. Exploring the measurement properties of the ehealth literacy scale (eheals) among baby boomers: a multinational test of measurement invariance. J Med Internet Res. (2017) 19:e53. doi: 10.2196/jmir.5998
55. Duplaga M, Sobecka K, Wojcik S. The reliability and validity of the telephone-based and online polish ehealth literacy scale based on two nationally representative samples. Int J Environ Res Public Health. (2019) 16:3216. doi: 10.3390/ijerph16173216
56. Seckin G, Yeatts D, Hughes S, Hudson C, Bell V. Being an informed consumer of health information and assessment of electronic health literacy in a national sample of internet users: validity and reliability of the E-Hls instrument. J Med Internet Res. (2016) 18:e161. doi: 10.2196/jmir.5496
57. He Y, Guo L, Zauszniewski JA, Wei M, Zhang G, Lei X, et al. A reliability and validity study of the electronic health literacy scale among stroke patients in China. Top Stroke Rehabil. (2021) 20:1–9. Epub 2021/12/21. doi: 10.1080/10749357.2021.2016100
58. Norgaard O, Furstrand D, Klokker L, Karnoe A, Batterham R, Kayser L, et al. The e-health literacy framework: a conceptual framework for characterizing e-health users and their interaction with e-health systems. Knowledge Manag E-Lear: Int J. (2015) 7:522–40. doi: 10.34105/j.kmel.2015.07.035
59. Cheng C, Elsworth G, Osborne RH. Validity evidence based on relations to other variables of the ehealth literacy questionnaire (Ehlq): Bayesian approach to test for known-groups validity. J Med Internet Res. (2021) 23:e30243. doi: 10.2196/30243
60. Perestelo-Perez L, Torres-Castano A, Gonzalez-Gonzalez C, Alvarez-Perez Y, Toledo-Chavarri A, Wagner A, et al. Ic-health project: development of moocs to promote digital health literacy: first results and future challenges. Sustainability. (2020) 12:6642. doi: 10.3390/su12166642
61. Chang SJ, Yang E, Lee KE Ryu H. Internet health information education for older adults: a pilot study. Geriatric Nurs (New York, NY). (2021) 42:533–9. doi: 10.1016/j.gerinurse.2020.10.002
62. Fink A, Beck JC. Developing and evaluating a website to guide older adults in their health information searches: a mixed-methods approach. J Appl Gerontol. (2015) 34:633–51. doi: 10.1177/0733464813486961
63. Nahm ES, Zhu S, Bellantoni M, Keldsen L, Russomanno V, Rietschel M, et al. The effects of a theory-based patient portal e-learning program for older adults with chronic illnesses. Telemed J E Health. (2019) 25:940–51. doi: 10.1089/tmj.2018.0184
64. Lee OEK, Kim DH. Bridging the digital divide for older adults via intergenerational mentor-up. Res Soc Work Pract. (2019) 29:786–95. doi: 10.1177/1049731518810798
65. Xie B. Improving older adults' e-health literacy through computer training using Nih online resources. Libr Inf Sci Res. (2012) 34:63–71. doi: 10.1016/j.lisr.2011.07.006
66. Bevilacqua R, Strano S, Di Rosa M, Giammarchi C, Cerna KK, Mueller C, et al. Ehealth literacy: from theory to clinical application for digital health improvement. results from the access training experience. Int J Environ Res Public Health. (2021) 18:e1800. doi: 10.3390/ijerph182211800
Keywords: digital health literacy, e-health literacy, older adults, older people, scoping review
Citation: Wang X and Luan W (2022) Research progress on digital health literacy of older adults: A scoping review. Front. Public Health 10:906089. doi: 10.3389/fpubh.2022.906089
Received: 28 March 2022; Accepted: 18 July 2022;
Published: 05 August 2022.
Edited by:
Mike Conway, The University of Utah, United StatesReviewed by:
Clément Meier, University of Lausanne, SwitzerlandRonald W. Berkowsky, California State University, United States
Copyright © 2022 Wang and Luan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Wei Luan, bHVhbndlaV9yZW5qaSYjeDAwMDQwOzE2My5jb20=