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Qi, H. E-Health Literacy Research Focuses and Trends. Encyclopedia. Available online: https://encyclopedia.pub/entry/18256 (accessed on 29 July 2024).
Qi H. E-Health Literacy Research Focuses and Trends. Encyclopedia. Available at: https://encyclopedia.pub/entry/18256. Accessed July 29, 2024.
Qi, Huiying. "E-Health Literacy Research Focuses and Trends" Encyclopedia, https://encyclopedia.pub/entry/18256 (accessed July 29, 2024).
Qi, H. (2022, January 14). E-Health Literacy Research Focuses and Trends. In Encyclopedia. https://encyclopedia.pub/entry/18256
Qi, Huiying. "E-Health Literacy Research Focuses and Trends." Encyclopedia. Web. 14 January, 2022.
E-Health Literacy Research Focuses and Trends
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This entry is adapted from the peer-reviewed paper 10.3390/healthcare10010066

With the rapid development of Internet technology, an increasing number of people are using networks to communicate and search for information in their lives and work. Because of the abundance of health information resources available on the Internet and the ease with which it can be accessed, people are gradually shifting away from traditional health information sources (such as newspapers, periodicals, and doctors’ offices) and toward the Internet.

E-health literacy bibliometric research focuses thematic evolution development trend visualization

1. Introduction

According to Peterson G et al., people commonly use the Internet to hunt for health and pharmaceutical information, and they use this knowledge to play a more active role in their therapy [1]. Chen established an association between searching for health information online and using that information, as well as an association between online medical help-seeking and utilization of online health information [2].
The Internet has made health information more accessible than ever, but there are concerns about the uneven quality of online health information. Especially after the outbreak of COVID-19, the sources of health information have become diverse and filled with false and misleading information [3]. However, people cannot identify true and false network information, which poses a threat to the public. How to overcome the negative effects of online error information and enable the public to quickly obtain accurate health information through networks and maintain their health is a need for the evolution of the times. It is now recognized that enhancing e-health literacy in the population is an effective way to obtain high-quality, web-based health resources [4], and thus, e-health literacy has become an emerging area of research that is gaining public attention.
Eysenbach first proposed the concept of “e-health” in 2001. He defined e-health as an emerging field at the intersection of medical informatics, public health, and business, referring to health services and information delivered or enhanced through the Internet and related technologies. In a broader sense, the term characterizes not only a technical development but also a state-of-mind, a way of thinking, an attitude, and a commitment for networked, global thinking, to improve health care locally, regionally, and worldwide by using information and communication technology [5].” In 2005, the WHO defined e-health as the use of information and communication technologies (ICT) for health [6]. The concept of e-health is the basis of the concept of e-health literacy.
Norman and Skinner first defined electronic health literacy (e-health literacy) as the ability to search, locate, and evaluate health information from electronic resources to solve health problems. Although many scholars have studied the concept of e-health literacy in the later stage, they have not formed a recognized version. To date, the concept and connotation of e-health literacy proposed by Norman and others are most widely cited. They divided e-health literacy into six core competencies: traditional literacy (basic reading, understanding, communication, and writing skills), health literacy (the ability to acquire, understand, evaluate, and apply health information to make decisions related to maintaining or promoting health), information literacy (the ability to access, evaluate, and use information), media literacy (the ability to select, understand, evaluate, and create information media), scientific literacy (the ability to use scientific methods to understand, evaluate, and explain health-related problems), and computer literacy (the ability to solve problems with computers) [7]. Norman stated that the core competencies that make up e-health competency are unlikely to change, although environmental changes could create new challenges for e-health literacy. However, with the increasing application of science and technology in the medical field, the dynamic development in the e-health field has led to continuous changes in the application and understanding of e-health literacy [8].
In recent years, research on e-health literacy has become the focus of many scholars. For example, Norman et al. designed an electronic health literacy scale [9], and CJ McKinley et al. explored the nature of the relationship between informational social support and components of online health information seeking [10]. Xesfingi et al. assessed the eHealth literacy level of citizens, using the eHealth Literacy Scale (eHEALS) [11], to help researchers quickly understand the overall research status and hot spots.

2. Analysis of Research Focus in E-Health Literacy

As seen from keyword clustering and thematic evolution, the research on ehealth literacy involves multiple subjects such as the elderly, college students, and patients with different diseases; analyzes a variety of health behaviors such as self-management, quality of life, and physical activity, as well as the digital divide caused by factors such as age and education; and develops relevant tools, as well as promoting ehealth through technology, social media, etc. Therefore, based on the co-word network of keywords, co-word timeline view, high-frequency keyword statistics, clustering, and thematic evolution path, and combined with the content of classical literature, this paper summarizes the ehealth literacy research into four topics: the evaluation of e-health literacy, the correlation between e-health literacy and health-promotion behaviors, influencing factors of e-health literacy, and interventions to improve e-health literacy.

2.1. Research on E-Health Literacy Evaluation

An essential foundation for studying public e-health literacy is a scientific evaluation of e-health literacy among different demographics, which sets the groundwork for comprehending the current situation and devising intervention strategies. As indicated in Table 1, academics have created a variety of assessment tools to assess e-health literacy. There are differences in the relevant assessment models of these tools and their application scenarios, applicable groups, evaluation topics, evaluation dimensions, etc.
Table 1. Assessment tools for eHealth literacy.
Name Content Dimensions Literature
eHEALS 8 items Traditional literacy; Media literacy; Information literacy; Computer literacy; Science literacy; Health literacy [9]
e-HLS 19 items Communication; Trust; Action [12]
DHLI 28 items Operational skills; Navigation skills; Information searching; Evaluating reliability; Determining relevance; Adding content; Protecting the privacy [13]
eHLA 96 items Information need identification and question formulation; Information search; Information assessment; Information management [14]
DHLAT 13 items Functional health literacy; Health literacy self-assessment; Familiarity with health and health care; Knowledge of health and disease; Technology familiarity; Technology confidence; Incentives for engaging with technology [15]
eHLQ 35 items Using technology to process health information; Understanding of health concepts and language; Ability to actively engage with digital services; Feel safe and in control; Motivated to engage with digital services; Access to digital services that work; Digital services that suit individual needs [16][17]
TeHLI 18 items Functional eHealth literacy; Communicative eHealth literacy; Critical eHealth literacy; Translational eHealth literacy [18][19]
The eHEALS scale, developed by Norman, is the first self-assessment tool for evaluating e-health literacy. With a total of eight items, the scale attempts to assess six core competencies of e-health literacy, using a five-point Likert rating system to score each item. The higher the score, the better the e-health literacy [9]. The eHEALS scale is one of the most extensively used instruments to evaluate e-health literacy. Several new e-health literacy scales have been created based on this research. The e-HLS (e-health literacy scale) instrument, constructed by Seckin G, has 19 items, including three dimensions of communication, trust, and action [12]; the Digital Health Literacy Instrument (DHLI) devised by Vaart RVD et al. has 21 self-assessment projects and 7 performance-based items that require respondents to apply e-health literacy to answer objective questions [13]. The eHealth Literacy Assessment Toolkit (eHLA), created by Farnoe A et al., contains four health literacy assessment tools and three digital literacy assessment tools [14].
Additionally, several researchers built assessment tools based on the self-developed concept and framework of e-health literacy. Jean BS and others produced the DHLAT (Digital Health Literacy Assessment Tool), a story-based tool for evaluating adolescent e-health literacy [15]. In the hypothetical environment, students individually answer a series of questions to assist a peer in using the Internet to find information about the disease (type 1 diabetes) with which she has recently been diagnosed. Norgaard O. et al. developed the eHealth Literacy Framework (eHLF), which encompasses individual knowledge and skills, systems, and interactions between individuals and systems [16]. Built on eHLF, Kayser L et al. designed an eHLQ (eHealth Literacy Questionnaire) with 35 items in 7 categories, which adds the two components of personal experience and interaction with systems, providing a broader dimension of e-health literacy [17]. Paige SR et al. proposed the transactional model of eHealth literacy (TMeHL), emphasizing communicative features and focusing on individual abilities to interact and exchange information with others while solving health concerns [18]. They generated the Transactional eHealth Literacy Instrument (TeHLI) to assess perceptual abilities associated with the capacity to comprehend, discuss, evaluate, and utilize online health information [19].
Aside from designing assessment tools, eHEALS is frequently utilized since it can test e-health literacy with a brief questionnaire. However, the scale is built based on the context of Britain and America, and only an English version available, so it has to be tested to see if it is also valid in other linguistic situations. As a consequence, researchers from around the world have translated eHEALS into nearly twenty languages for testing and evaluation, including Dutch [20], Japanese [21], German [22], Portuguese [23], Spanish [24], Turkish [25], Italian [26], Korean [27], Hungarian [28], Serbian [29], Polish [30], Chinese [31], Greek [32], Norwegian [33], Amharic [34], Swedish [35], Arabic [36], and Indonesian [37]. The findings indicated that the translated versions have high internal consistency and credibility.

2.2. Research on the Correlation between E-Health Literacy and Health-Promotion Behaviors

Health-promoting behaviors include health responsibility, stress management, exercise behavior, dietary behavior, self-realization, and social support, all of which are positive activities or concepts that are beneficial to preserve or promote health [38]. They can assist individuals in avoiding disease, enhancing health, increasing quality of life, and maintaining excellent physical and mental health. Due to the widespread use of the Internet and mobile devices, most people have access to health-related information on the Internet. Individuals with varying levels of e-health literacy range in their ability to seek, comprehend, evaluate, and use online health information, as well as solve health-related problems. Understanding the importance of e-health literacy on health behaviors will equip professionals with the knowledge to enhance population health intervention, increase e-health literacy, and encourage healthy behaviors. Therefore, academics have begun to focus on the link between e-health literacy and health behaviors. Table 2 shows that the level of e-health literacy is a key factor in improving health behaviors.
Table 2. Research on the correlation between e-health literacy and health behaviors.
Health-Promotion Behaviors Conclusions Literature
Health responsibility Individuals with better e-health literacy were better able to self-manage and engage in medical decisions, were more willing to be vaccinated, and had greater ability to follow public health guidance. [39][40][41][42][43]
Stress management Individuals with better e-health literacy were more likely to be able to control negative emotions and prevent psychological disorders. [10][44][45][46]
Nutrition Individuals with better e-health literacy had healthy eating habits and adopted balanced diets. [47][48][49]
Exercise Individuals with better e-health literacy levels exercised more frequently with higher participation. [48][49][50][51][52]
Social support Individuals with better e-health literacy enjoyed positive interpersonal interactions and are adept at utilizing interpersonal resources. [53][54]
Self-actualization Individuals with better e-health literacy had a high quality of life, a sense of purpose, and a sense of hope. [55][54]
Health responsibility refers to paying attention to and being accountable for one’s health. Studies have shown that individuals with greater levels of e-health literacy are linked to regular online searches for health information [39], as well as greater frequency of web-based health-seeking actions [40]. Individuals with better e-health literacy can acquire more accurate health-related information, evaluate the quality of information more properly, have better self-management capacity, connect with healthcare practitioners more effectively, and engage in treatment and nursing decision-making [41][42]. Furthermore, in the case of the COVID-19 pandemic, the higher the level of e-health literacy, the greater the willingness to receive vaccination and the better the compliance with public health guidelines [43].
Stress management is the ability to cope with stress. Mental health benefits significantly from e-health literacy. People with e-health literacy can better analyze and alter their health state, avoid negative feelings such as fear and distrust, and enhance their mental health [10]. Individuals with greater levels of e-health literacy are more equipped to cope with challenges, which means they are less likely to suffer from sleeplessness or psychological anguish [44]. Moreover, since the outbreak of COVID-19, a great amount of incorrect and misleading information has been spreading, causing people to be confused and fearful [45]. Individuals with high e-health literacy can better obtain accurate information and manage negative emotions and symptoms, minimizing the epidemic’s frequent mental health issues (such as depression, sleeplessness, and posttraumatic stress disorder) [46].
Nutrition relates to a person’s eating habits and food choices. Healthy food consumption is adversely connected with e-health literacy, but a balanced diet and regular eating habits are favorably correlated [47]. Individuals with better e-health literacy are more likely to adopt healthy eating behaviors (for example, consuming low-fat meals, low-sugar cereals, vegetables, and fruits) [48] because they can more properly search for and interpret information about healthy eating on the Internet [49].
Exercise refers to the regular undertaking of exercise. E-health literacy can positively predict exercise [48]. Individuals with greater literacy are more likely to exercise frequently and participate in sports [49][50] (for example, exercise at least three times a week [51]). Furthermore, an emerging online fitness culture (including health, exercise, and fitness groups or blogs on various social networking sites) disseminates pertinent health and fitness information through online social interaction to inspire and motivate people to live a healthy life. Users of online fitness who have a high level of e-health literacy may better recognize the beneficial information in a large number of mixed materials and modify their lifestyles through appropriate activities [52].
Self-actualization implies the attitude and expectations of life. The link between e-health literacy and quality of life is clear and favorable [53]. Individuals with a high level of e-health literacy may actively create their internal resources to accomplish spiritual growth, giving them a strong feeling of purpose and optimism for the future [54].
Social support describes closeness and intimacy with others. Individuals with high e-health literacy are more likely to be able to solve interpersonal difficulties and sustain meaningful connections with others [54]. At the same time, they may make greater use of interpersonal resources and achieve better results in social relationships [55].

2.3. Research on Influencing Factors of E-Health Literacy

With the rapid development of the Internet and the increase in health information from various online sources, investigating the population’s level of e-health literacy and analyzing its influencing factors can help to formulate intervention measures to improve the population’s e-health literacy. Researchers used questionnaires and interviews to gather and evaluate data, and they discovered that the population’s degree of e-health literacy was influenced by a variety of factors, as shown in Table 3.
Table 3. Research on influencing factors of e-health literacy.
Factor Conclusion Literature
Demographic characteristics Age, gender, education, income, residential area, health status, and professional differences were associated with e-health literacy levels [56][57]
Attitude Attitudes toward accessing Internet resources, as well as an understanding of the Internet’s use and significance, had a substantial influence on the degree of e-health literacy [58][59]
Motive Health awareness and confidence in using Internet technology were factors related to e-health literacy [11][60]
First, age is associated with e-health literacy. The younger the age, the greater the level of e-health literacy [56]. In terms of gender, women are more likely than men to seek health information on the Internet [61]; as for education, a higher education level is associated with higher e-health literacy [62]; in terms of the aspect of income, people with lower incomes have lower e-health literacy [63]; and as for residential area, the utility of online medical resources in rural populations is lower than that in urban populations [64]. People with good health perceptions are more likely to have e-health literacy, possibly because they are more inclined to seek medical resources before their health deteriorates [58]; additionally, because medical students are more exposed to medical health information in their courses of study, their electronic literacy level is higher than that of other majors [57].
Second, research indicated that a favorable attitude toward the use of online resources is associated with better levels of e-health literacy [58]. Recognizing the utility of receiving health information via the Internet and the significance of making health decisions utilizing Internet resources is another crucial component correlated to e-health literacy [59].
Finally, the motive is the internal driving force that triggers certain behaviors. Individual health awareness, as one of the reasons, has a direct influence on the use of Internet health resources; for example, those who engage in physical activity seem to be more prone to have e-health literacy [11]. Furthermore, confidence in the use and evaluation of network resources will influence e-health literacy. The amount of information literacy [11], frequency of Internet use [65], and network competency [60] are all essential parts of e-health literacy.

2.4. Research on Intervention Measures for Improving E-Health Literacy

With the widespread use of information and communication technology in the medical profession, numerous medical and health institutions and organizations are progressively posting health information on the Internet, and the Internet has become an essential source of high-quality health information. However, Internet resources can only contribute if the public has adequate e-health literacy and avoids low-quality materials that are harmful to health. According to research, the amount of e-health literacy is the best predictor of individual health behavior [66]. As a result, researchers began to focus on the design and implementation of intervention measures to foster and promote e-health literacy. Table 4 shows the most often utilized intervention approaches to increase e-health literacy at the moment.
Table 4. Interventions to improve e-health literacy.
Method Subject Conclusion Literature
Professional health website Teenagers with epilepsy and their parents, heart disease patients, the elderly, informal caregivers, etc. The content, quality, and feasibility of the site were effective in boosting participants’ electronic health literacy, and participants provided good comments on the intervention, supporting its efficacy and accessibility. [67][68]
Education video Patients undergoing coronary angiography, HIV/AIDS patients, Japanese adults, high school students, the elderly, etc. The development and design of electronic health literacy project training was an effective technique to increase the population’s electronic health literacy, as well as the participants’ self-health management strategies. [69][70]
Health care mobile terminal Parents of children with early childhood caries: caries, cancer patients and their caregivers, college students, etc. To increase users’ electronic health literacy, health APPs and wearable medical devices could give individualized health information and services efficiently. [71][72]
Consultant The elderly and the general population under the COVID-19 epidemic People with low electronic health literacy can benefit from guidance that increases their confidence in accessing Internet technologies and selecting reliable information, which can help narrow the gap. [73][74]
Participants accessing high-quality professional health information websites, using, querying, and learning credible health information offered by websites, and contacting relevant professionals are examples of interventions employing professional health websites. To avoid poor information on the website disrupting the learning effect of participants, high-quality websites sponsored by the government and hospitals were deployed. The results of a study on the effects of the use of professional health websites by diverse groups of teenagers with epilepsy and their parents [67], patients with heart disease [75], the elderly [76], and informal caregivers [77] revealed that participants’ e-health literacy had improved, and they had a positive attitude about the use of websites to impact their health. Furthermore, in addition to providing trustworthy information, aspects such as easy access, user-friendliness, and simple language [68] contributed to e-health literacy education.
Participants in training programs were guided in the process of searching, examining, and assessing electronic health information. Participating in massive open online courses (MOOCs) [69], viewing instructional films [78][79], reading text and graphic materials [80], and taking associated quizzes [81] were all practices of training, and learning techniques included autonomous learning, collaborative learning [82], and discussion learning [70]. Following the completion of the training project, participants’ e-health literacy, ability to search for health information online, knowledge of network health information, and ability to evaluate network information were greatly enhanced. It can be observed that conducting targeted e-health literacy training programs in the population effectively increases public e-health literacy.
Mobile health care apps can provide appropriate information and interventions based on users’ needs economically and efficiently and promote interaction and communication between app providers and users, allowing users to better understand medical information and monitor and manage their health status. Similarly, wearable medical devices can assist users in understanding and evaluating health information from other sources based on their personal experience by collecting and providing feedback on relevant data and resources, leading to subsequent electronic health behaviors. Competent medical health mobile terminals may provide enough health education, hence increasing the population’s e-health literacy.
Mobile health care apps can provide appropriate information and intervention based on users’ needs, in an economical and efficient manner, and promote interaction and communication between app providers and users, allowing users to better understand medical information and monitor and manage their health status [71][83]. Similarly, wearable medical devices can assist users in understanding and evaluating health information from other sources based on their personal experience by collecting and providing relevant data and resources, leading to subsequent electronic health behaviors [72]. Effective medical health mobile terminals can provide adequate health education, hence enhancing public e-health literacy.
Meanwhile, during the recent coronavirus epidemic, with correct information, disinformation, and changing recommendations blended in a massive amount of materials, there was a tremendous need for instructions on how to identify trustworthy health information among them. As a result, the engagement of people with higher e-health literacy in guiding people with lower e-health literacy, such as college students assisting the elderly [73] and volunteer doctors providing the most up-to-date epidemic-related information to the general population [74], can help improve e-health literacy and narrow the digital divide.

References

  1. Peterson, G.; Aslani, P.; Williams, K.A. Consumer use of the internet for medicines information. Int. J. Pharm. Pract. 2010, 12, 185–190.
  2. Chen, Y.Y.; Li, C.M.; Liang, J.C.; Tsai, C.C. Health information obtained from the internet and changes in medical decision making: Questionnaire development and cross-sectional survey. J. Med. Internet Res. 2018, 20, e47.
  3. Abdulai, A.F.; Tiffere, A.H.; Adam, F.; Kabanunye, M.M. COVID-19 information-related digital literacy among online health consumers in a low-income country. Int. J. Med. Inform. 2021, 145, 104322.
  4. Dib, F.; Mayaud, P.; Chauvin, P.; Launay, O. Online mis/disinformation and vaccine hesitancy in the era of COVID-19: Why we need an eHealth literacy revolution. Hum. Vaccines Immunother. 2021, 17, 3262–3267.
  5. Eysenbach, G. What is e-health? J. Med. Internet Res. 2001, 3, E20.
  6. World Health Organization. eHealth at WHO. Available online: https://www.who.int/observatories/global-observatory-for-ehealth (accessed on 7 December 2021).
  7. Norman, C.D.; Skinner, H.A. eHealth literacy: Essential skills for consumer health in a networked world. J. Med. Internet Res. 2006, 8, e9.
  8. Norman, C. eHealth literacy 2.0: Problems and opportunities with an evolving concept. J. Med. Internet Res. 2011, 13, e125.
  9. Norman, C.D.; Skinner, H.A. eHEALS: The eHealth literacy scale. J. Med. Internet Res. 2006, 8, e27.
  10. McKinley, C.J.; Wright, P.J. Informational social support and online health information seeking: Examining the association between factors contributing to healthy eating behavior. Comput. Hum. Behav. 2014, 37, 107–116.
  11. Xesfingi, S.; Vozikis, A. eHealth literacy: In the quest of the contributing factors. Interact. J. Med. Res. 2016, 5, 81–93.
  12. Seçkin, G.; Yeatts, D.E.; 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.
  13. Vaart, R.V.D.; Drossaert, C. Development of the digital health literacy instrument: Measuring a broad spectrum of Health 1.0 and Health 2.0 skills. J. Med. Internet Res. 2017, 19, e27.
  14. Karnoe, A.; Furstrand, D.; Christensen, K.B.; Norgaard, O.; Kayser, L. Assessing competencies needed to engage with digital health services: Development of the eHealth literacy assessment toolkit. J. Med. Internet Res. 2018, 20, e178.
  15. Jean, B.S.; Taylor, N.G.; Kodama, C.; Subramaniam, M. Assessing the digital health literacy skills of tween participants in a school-library-based after-school program. J. Consum. Health Internet 2017, 21, 40–61.
  16. Norgaard, O.; Furstrand, D.; Klokker, L.; Karnoe, A.; Osborne, R.H. The e-health literacy framework: A conceptual framework for characterizing e-health users and their interaction with e-health systems. Knowl. Manag. E-Learn. 2015, 7, 522–540.
  17. Kayser, L.; Karnoe, A.; Furstrand, D.; Batterham, R.; Christensen, K.B.; Elsworth, G.; Osborne, R.H. 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.
  18. Paige, S.R.; Stellefson, M.; Krieger, J.L.; Anderson-Lewis, C.; Cheong, J.W.; Stopka, C. Proposing a transactional model of eHealth literacy: Concept analysis. J. Med. Internet Res. 2018, 20, e10175.
  19. Paige, S.R.; Stellefson, M.; Krieger, J.L.; Miller, M.D.; Anderson-Lewis, C. Transactional eHealth literacy: Developing and testing a multi-dimensional instrument. Health Commun. 2019, 24, 737–748.
  20. Vaart, R.; Deursen, A.; Drossaert, C.H.; Taal, E.; Laar, M. Does the eHealth literacy scale (eHEALS) measure what it intends to measure? Validation of a Dutch version of the eHEALS in two adult populations. J. Med. Internet Res. 2011, 13, e86.
  21. Mitsutake, S.; Ai, S.; Ishii, K.; Okazaki, K.; Oka, K. Developing Japanese version of the ehealth literacy scale (eHEALS). Nihon Koshu Eisei Zasshi 2011, 58, 361–371.
  22. Soellner, R.; Huber, S.; Reder, M. The concept of eHealth literacy and its measurement: German translation of the eHEALS. J. Media Psychol.-Ger. 2014, 26, 29–38.
  23. Tomás, C.C.; Queirós, P.J.P.; Ferreira, T.D.J.R. Analysis of the psychometric properties of the Portuguese version of an eHealth literacy assessment tool. Rev. Enferm. Ref. 2014, IV, 19–28.
  24. Pérez, G.P.; Almagro, B.J.; Gómez, Á.H.; Gómez, J.I.A. Validation of the eHealth literacy scale (eHEALS) in Spanish University Students. Rev. Esp. Comun. Salud Pública 2015, 89, 329–338.
  25. Gencer, Z.T. Analysis of validity and reliability of Norman and Skinner’s E-Health scale literacy for cultural adaptation. Kulak Burun Bogaz Ihtis Derg 2017, 52, 131–145.
  26. Diviani, N.; Dima, A.L.; Schulz, P.J. A psychometric analysis of the Italian version of the eHealth literacy scale using item response and classical test theory methods. J. Med. Internet Res. 2017, 19, e114.
  27. Chung, S.Y.; Bu, K.P.; Nahm, E.S. The Korean eHealth Literacy Scale (K-eHEALS): Reliability and validity testing in younger adults recruited online. J. Med. Internet Res. 2018, 20, e138.
  28. Zrubka, Z.; Hajdu, O.; Rencz, F.; Baji, P.; Péntek, M. Psychometric properties of the Hungarian version of the eHealth Literacy Scale. Eur. J. Health Econ. 2019, 20, S57–S69.
  29. Gazibara, T.; Cakic, J.; Cakic, M.; Pekmezovic, T.; Grgurevic, A. eHealth and adolescents in Serbia: Psychometric properties of eHeals questionnaire and contributing factors to better online health literacy. Health Promot. Int. 2019, 34, 770–778.
  30. Duplaga, M.; Sobecka, K.; Wójcik, 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.
  31. Chang, A.; Schulz, P.J. The measurements and an elaborated understanding of Chinese eHealth Literacy (C-eHEALS) in chronic patients in China. Int. J. Environ. Res. Public Health 2018, 15, 1553.
  32. Efthymiou, A.; Middleton, N.; Charalambous, A.; Papas Ta Vrou, E. Adapting the eHealth Literacy Scale for carers of people with chronic diseases (eHeals-Carer) in a sample of Greek and Cypriot carers of people with dementia: Reliability and validation study. J. Med. Internet Res. 2019, 21, e12504.
  33. Dale, J.G.; Lüthi, A.; Skaraas, B.F.; Rundereim, T.; Dale, B. Testing measurement properties of the Norwegian version of Electronic Health Literacy Scale (eHEALS) in a group of day surgery patients. J. Multidiscip. Healthc. 2020, 13, 241–247.
  34. Shiferaw, K.B. Validation of the Ethiopian version of eHealth Literacy Scale (ET-eHEALS) in a population with chronic disease. Risk Manag. Healthc. Policy 2020, 13, 465–471.
  35. Wngdahl, J.; Jaensson, M.; Dahlberg, K.; Nilsson, U. The Swedish version of the Electronic Health Literacy Scale: Prospective psychometric evaluation study including thresholds levels. JMIR mHealth uHealth 2020, 8, e16316.
  36. Wngdahl, J.; Dahlberg, K.; Jaensson, M.; Nilsson, U. Arabic version of the Electronic Health Literacy Scale in Arabic-speaking individuals in Sweden: Prospective psychometric evaluation study. J. Med. Internet Res. 2021, 23, e24466.
  37. Wijaya, M.C.; Kloping, Y.P. Validity and reliability testing of the Indonesian version of the eHealth Literacy Scale during the COVID-19 pandemic. Health Inform. J. 2021, 27, 1460458220975466.
  38. Walker, S.N.; Sechrist, K.R.; Pender, N.J. Health promotion model—Instruments to measure health promoting lifestyle: Health-promoting lifestyle profile (Adult version). J. Nurs. Res. 1995, 22, 796–811. Available online: http://hdl.handle.net/2027.42/85349 (accessed on 7 December 2021).
  39. Heiman, H.; Keinki, C.; Huebner, J. EHealth literacy in patients with cancer and their usage of web-based information. J. Cancer Res. Clin. Oncol. 2018, 144, 1841–1850.
  40. Guendelman, S.; Broderick, A.; Mlo, H.; Gemmill, A.; Lindeman, D. Listening to communities: Mixed-method study of the engagement of disadvantaged mothers and pregnant women with digital health technologies. J. Med. Internet Res. 2017, 19, e240.
  41. Zrubka, Z.; Fernandes, S.B.; Baji, P.; Hajdu, O.; Kovacs, L.; Kringos, D.; Klazinga, N.; Gulácsi, L.; Brodszky, V.; Rencz, F.; et al. Exploring eHealth Literacy and patient-reported experiences with outpatient care in the Hungarian general adult population: Cross-sectional study. J. Med. Internet Res. 2020, 22, e19013.
  42. Nejati, B.; Li, C.C.; Aaronson, N.K.; Cheng, A.S.K.; Browall, M.; Lin, C.Y.; Brostrom, A.; Pakpour, A.H. Determinants of satisfactory patient communication and shared decision making in patients with multiple myeloma. Psychooncology 2019, 28, 1490–1497.
  43. Patil, U.; Kostareva, U.; Hadley, M.; Manganello, J.A.; Sentell, T. Health literacy, digital health literacy, and COVID-19 pandemic attitudes and behaviors in U.S. college students: Implications for interventions. Int. J. Environ. Res. Public Health 2021, 18, 3301.
  44. .Chung-Ying, L.; Maryam, G.; Griffiths, M.D.; Ernsth, B.M.; Anders, B.; Pakpour, A.H. 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, 155–164.
  45. Nguyen, M.H.; Pham, T.T.M.; Nguyen, K.T.; Nguyen, Y.H.; Duong, T.V. Negative impact of fear of COVID-19 on health-related quality of life was modified by health literacy, eHealth literacy, and digital healthy diet literacy: A multi-hospital survey. Int. J. Environ. Res. Public Health 2021, 18, 4929.
  46. Yang, B.X.; Xia, L.; Huang, R.; Chen, P.; Lou, D.; Liu, Q.; Kang, L.J.; Zhang, Z.J.; Liu, Z.C.; Yu, S.H.; et al. Relationship between eHealth literacy and psychological status during COVID-19 pandemic: A survey of Chinese residents. J. Nurs. Manag. 2021, 29, 805–812.
  47. Yang, S.C.; Luo, Y.F.; Chiang, C.H. Electronic health literacy and dietary behaviors in Taiwanese college students: Cross-sectional study. J. Med. Internet Res. 2019, 21, e13140.
  48. Hsu, W.C.; Chiang, C.H.; Yang, S.C. The effect of individual factors on health behaviors among college students: The mediating effects of eHealth Literacy. J. Med. Internet Res. 2014, 16, e287.
  49. Aslan, G.K.; Kartal, A.; Turan, T.; Yigitoglu, G.T.; Kocakabak, C. Association of electronic health literacy with health-promoting behaviours in adolescents. Int. J. Nurs. Pract. 2021, 27, e12921.
  50. Huang, C.L.; Yang, S.C.; Chiang, C.H. The associations between individual factors, eHealth Literacy, and health behaviors among college students. Int. J. Environ. Res. Public Health 2020, 17, 2108.
  51. Yang, S.C.; Luo, Y.F.; Chiang, C.H. The associations among individual factors, eHealth Literacy, and Health-promoting lifestyles among college students. J. Med. Internet Res. 2017, 19, e15.
  52. Jong, S.T.; Drummond, M.J.N. Exploring online fitness culture and young females. Leis. Stud. 2016, 35, 758–770.
  53. Filabadi, Z.R.; Estebsari, F.; Milani, A.S.; Feizi, S.; Nasiri, M. Relationship between electronic health literacy, quality of life, and self-efficacy in Tehran, Iran: A community-based study. J. Educ. Health Promot. 2020, 9, 175.
  54. Cho, H.; Han, K.; Park, B.K. Associations of eHealth literacy with health-promoting behaviours among hospital nurses: A descriptive cross-sectional study. J. Adv. Nurs. 2018, 74, 1618–1627.
  55. Neter, E.; Brainin, E. eHealth literacy: Extending the digital divide to the realm of health information. J. Med. Internet Res. 2012, 14, e19.
  56. Austin, D.W.; Poornima, B.; Chloe, T.; Kerrie, S. Preferences for online mental health services among Australian and Indian samples: A cross-cultural comparison. Psychol. Stud. 2018, 63, 376–383.
  57. Tsukahara, S.; Yamaguchi, S.; Igarashi, F.; Uruma, R.; Sato, Y. Association of eHealth Literacy with lifestyle behaviors in university students: Questionnaire-based cross-sectional study. J. Med. Internet Res. 2020, 22, 1–11.
  58. Shiferaw, K.B.; Tilahun, B.C.; Endehabtu, B.F.; Gullslett, M.K.; Mengiste, S.A. E-health literacy and associated factors among chronic patients in a low-income country: A cross-sectional survey. BMC Med. Inform. Decis. Mak. 2020, 20, 181.
  59. Rathnayake, S.; Senevirathna, A. Self-reported eHealth literacy skills among nursing students in Sri Lanka: A cross-sectional study. Nurse Educ. Today 2019, 78, 50–56.
  60. Tubaishat, A.; Habiballah, L. eHealth literacy among undergraduate nursing students. Nurse Educ. Today 2016, 42, 47–52.
  61. Nolke, L.; Mensing, M.; Kramer, A.; Hornberg, C. Sociodemographic and health-(care-)related characteristics of online health information seekers: A cross-sectional German study. BMC Public Health 2015, 15, 31.
  62. Cherid, C.; Baghdadli, A.; Wall, M.; Mayo, N.E.; Berry, G.; Harvey, E.J.; Albers, A.; Bergeron, S.G.; Morin, S.N. 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, 1333–1340.
  63. Zibrik, L.; Khan, S.; Bangar, N.; Stacy, E.; Lauscher, H.N.; Ho, K. Patient and community centered eHealth: Exploring eHealth barriers and facilitators for chronic disease self-management within British Columbia’s immigrant Chinese and Punjabi seniors. Health Policy Technol. 2015, 4, 348–356.
  64. Bailey, C.E.; Kohler, W.J.; Makary, C.; Davis, K.; Sweet, N.; Carr, M. eHealth Literacy in otolaryngology patients. Ann. Otol. Rhinol. Laryngol. 2019, 128, 1013–1018.
  65. Wong, D.; Cheung, M. Online health information seeking and eHealth literacy among patients attending a primary care clinic in Hong Kong: A cross-sectional survey. J. Med. Internet Res. 2019, 21, e10831.
  66. Kim, S.H.; Son, Y.J. Relationships between eHealth literacy and health behaviors in Korean adults. CIN Comput. Inform. Nurs. 2017, 35, 84–90.
  67. Guven, S.T.; Daalgic, A.I.; Duman, O. Evaluation of the efficiency of the web-based epilepsy education program (WEEP) for youth with epilepsy and parents: A randomized controlled trial. Epilepsy Behav. 2020, 111, 107142.
  68. Xie, B. Improving older adults’ e-health literacy through computer training using NIH online resources. Libr. Inf. Sci. Res. 2012, 34, 63–71.
  69. Blakemore, L.M.; Meek, S.; Marks, L.K. Equipping learners to evaluate online health care resources: Longitudinal study of learning design strategies in a health care massive open online course. J. Med. Internet Res. 2020, 22, e15177.
  70. Xie, B. Experimenting on the impact of learning methods and information presentation channels on older adults’ e-health literacy. J. Am. Soc. Inf. Sci. Technol. 2011, 62, 1797–1807.
  71. Kim, H.; Goldsmith, J.V.; Sengupta, S.; Mahmood, A.; Powell, M.P.; Bhatt, J.; Chang, C.F.; Bhuyan, S.S. Mobile health application and e-Health Literacy: Opportunities and concerns for cancer patients and caregivers. J. Cancer Educ. 2019, 34, 3–8.
  72. Sobko, T.; Brown, G. Reflecting on personal data in a health course: Integrating wearable technology and ePortfolio for eHealth. Australas. J. Educ. Technol. 2018, 35, 55–70.
  73. Lee, E.K.; Kim, D.H. Bridging the digital divide for older adults via intergenerational mentor-up. Res. Soc. Work Pract. 2019, 29, 786–795.
  74. Furstrand, D.; Pihl, A.; Orbe, E.B.; Kingod, N.; Sndergaard, J. “Ask a Doctor About Coronavirus”: How physicians on social media can provide valid health information during a pandemic. J. Med. Internet Res. 2020, 23, e24586.
  75. Melholt, C.; Joensson, K.; Spindler, H.; Hansen, J.; Andreasen, J.J.; Nielsen, G.; Noergaard, A.; Tracey, A.; Thorup, C.; Kringelholt, R.; et al. Cardiac patients’ experiences with a telerehabilitation web portal: Implications for eHealth literacy. Patient Educ. Couns. 2018, 101, 854–861.
  76. Xie, B. Effects of an eHealth Literacy intervention for older adults. J. Med. Internet Res. 2011, 13, e90.
  77. Nahm, E.S.; Resnick, B.; Orwig, D.; Magaziner, J.; Bellantoni, M.; Sterling, R.; Brennan, P.F. A theory-based online hip fracture resource center for caregivers Effects on dyads. Nurs. Res. 2012, 61, 413–422.
  78. Hu, J.; Ren, J.; Zheng, J.; Li, Z.; Xiao, X. A quasi-experimental study examining QR code-based video education program on anxiety, adherence, and satisfaction in coronary angiography patients. Contemp. Nurse 2020, 56, 428–440.
  79. Nokes, K.M.; Reyes, D.M. Do brief educational sessions increase electronic health literacy of low-income persons living with HIV/AIDS? Comput. Inform. Nurs. 2019, 37, 315–320.
  80. Mitsuhashi, T. Effects of two-week e-learning on eHealth literacy: A randomized controlled trial of Japanese Internet users. PeerJ 2018, 6, e5251.
  81. Hernandez-Rabanal, C.; Vall, A.; Boter, C. Training, the key to improving eHealth literacy of upper secondary school students. Gac. Sanit. 2018, 32, 48–53.
  82. Xie, B. Older adults, e-health literacy, and collaborative learning: An experimental study. J. Am. Soc. Inf. Sci. Technol. 2011, 62, 933–946.
  83. Lotto, M.; Strieder, A.P.; Aguirre, P.; Oliveira, T.M.; Machado, M.A.A.M.; Rios, D.; Cruvinel, T. Parental-oriented educational mobile messages to aid in the control of early childhood caries in low socioeconomic children: A randomized controlled trial. J. Dent. 2020, 101, 103456.
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Huiying Qi
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