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Abstract

Background

While digital literacy has become an essential competency for individuals across generations and sectors of society, supporting digital literacy in older adults is particularly challenging. South Korea is among the many countries undergoing rapid digitalization and population aging. Therefore, it is timely to identify the current understanding of digital literacy among older adults in South Korea.

Aim

To identify prior studies that quantitatively measure digital literacy among older adults in South Korea and to identify and evaluate how digital literacy was measured in the reviewed studies.

Methods

The study followed Arksey and O’Malley's scoping review framework, searching through four international (PubMed, CINAHL, Embase, and Cochrane Library) and four Korean (RISS, KISS, KCI, and KMBase) databases.

Results

Among 42 studies included in the final analysis, 38 were cross-sectional studies, and 21 employed primary data. Digital literacy was assessed in various scopes, including digital literacy, e-health literacy, Internet use, and smartphone use. Of the 25 identified measures, three were validated; the rest varied greatly, from using a few items from large surveys to employing investigator-developed measures. Based on the European Commission's Digital Competence Framework, the most commonly addressed components were “information and data literacy” and “communication and collaboration.”

Conclusions

In recent years, attention toward digital literacy among South Korean older adults has grown rapidly. However, the level of digital literacy among older adults in South Korea remains inconclusive given measurement heterogeneity. Developing and validating more robust measures are warranted to evaluate digital literacy among older adults with diverse functions and circumstances.

Keywords

Digital health digital literacy e-health measurement older adults scoping review

Introduction

Since the concept of “digital literacy” was first introduced in the late 1990s,¹ it has become an indispensable competence in the rapidly digitalizing world. As technology continues to expand and introduce new skills and competencies into our daily lives,² the definition of digital literacy has evolved from the emphasis on the mastery of digital tools¹ to a focus on domain-specific literacy, such as e-health literacy.³ According to the European Commission's Digital Competence (DigComp) Framework⁴ (one of the most widely recognized digital literacy frameworks), digital literacy comprises five dimensions: (1) information and data literacy, (2) communication and collaboration, (3) digital content creation, (4) safety, and (5) problem solving.

Although cultivating digital literacy is an ongoing demand for every generation and sector in society, supporting digital literacy in older adults is particularly challenging.^5–7 For older adults, barriers to adopting new technology are multifaceted, including declines in physical function, emotional resistance, or cognitive decline.⁸ Studies consistently report that old age is associated with low technology usage,^9,10 and older adults are less likely to search the Internet for health information.¹¹ Considering that population aging is a global trend,¹² understanding and supporting digital literacy for older adults in a constantly evolving digital realm is crucial to building an inclusive and sustainable digital environment.

To date, few reviews have examined digital literacy among older adults.^5,13,14 Chesser et al.⁵ examined the e-health literacy gap among underserved populations in the United States, ranging from immigration and employment statuses to ethnicity and age. However, considering that the experiences of underserved populations are heterogeneous by their characteristics, the experience of each identity deserves more attention. Another review by Shi et al.¹⁴ targeted Chinese older adults and assessed studies that measured e-health literacy using the eHealth Literacy Scale (eHEALS). However, as the concept of digital literacy is multidimensional and most validated scales do not necessarily cover all domains of digital literacy,^4,13 conducting a review of digital literacy that covers studies based on diverse measures is necessary for a comprehensive understanding of the current status of older adults’ digital literacy.

Regarding digital literacy in older adults, South Korea deserves attention because the country is currently undergoing rapid digitalization and population aging, phenomena that are highly prominent among many industrialized countries. South Korea witnessed the beginning of the digital society with approximately half of the population using the Internet and mobile services circa 2000.¹⁵ Two decades after, in 2022, South Korea has achieved widespread technology use, as exemplified by the high rate of smartphone penetration (97.1%), even among individuals 60 years old and above (90%).¹⁶ According to the Organization for Economic Cooperation and Development (OECD), out of 38 OECD member countries, South Korea has the fastest aging rate and is on track to reach the highest old-age-to-working-age ratio by 2070.¹⁷ Thus, understanding digital literacy among older adults in South Korea can provide valuable insights into the challenges and opportunities that may apply to other countries undergoing similar trends in their population and technologies.

Therefore, we conducted a scoping review¹⁸ aimed to (1) identify and critically appraise studies that quantitatively measured digital literacy among older adults living in South Korea, (2) identify measures used to evaluate digital literacy in the selected studies, and (3) evaluate digital literacy measures used in the selected studies by addressing the elements of digital literacy via the DigComp Framework.⁴

Materials and methods

Search strategy and data sources

This scoping review was planned and developed following the updated version of Arksey and O’Malley's¹⁹ methodological framework of scoping studies.²⁰ Based on the Population, Concept, and Context model for scoping reviews,^21,22 we focused on older adults’ (Population) digital literacy (Concept) in South Korea (Context). While older adults are generally defined as individuals aged 65 and older,²³ we found that many studies used age criteria younger than 65 years (e.g., 60 or 55 years and older) to define older adults.^6,24–42 Therefore, we applied broader age criteria for older adults—which includes those aged younger than 65 if researchers of the original studies defined them as older adults—to align with such studies. Moreover, this study defined digital literacy as literacy in or utilization of any type of digital device. We employed a broad definition to gain a comprehensive understanding of current research on older adults’ use and literacy of digital devices in varying domains, including digital health literacy, e-health literacy, m-health literacy, and general or specific technology use (e.g. Internet use and smartphone use). To identify relevant peer-reviewed journal articles, we searched through four international electronic databases (PubMed, CINAHL, Embase, and Cochrane Library) and four Korean databases (RISS, KISS, KCI, and KMBase). Primary search terms included “digital literacy,” “older adults,” and “Korean,” with a combination of alternative keywords in the Boolean search. Supplemental Table S1 presents a full list of database-specific search terms. Covidence (Veritas Health Innovation Ltd) was used for data management and extraction.

Eligibility criteria

Studies were eligible for the review if they (1) quantitatively measured individual-level digital literacy, (2) targeted Korean older adults aged 60 years or older living in South Korea, (3) were published in Korean or English language between January 2000 and June 2022, and (4) were published in peer-reviewed journals. Studies that did not directly target older adults were excluded. However, studies in which the younger population was included as a distinct age category to compare against older adults were included for analysis. As this study aimed to identify quantitative studies on Korean older adults’ digital literacy in peer-reviewed journal articles, the following types of studies were excluded: reviews, case reports, commentaries, letters to editors, studies of qualitative design, unpublished master's theses or doctoral dissertations, conference abstracts, and book chapters. Despite the concept of digital literacy first introduced in the 1990s, we set the search period from January 2000 because the wide use of digital technologies and devices began around the 2000s in South Korea.¹⁵

Study selection

Upon completion of the literature search, all references from the databases were transferred to the reference management system (Covidence, Veritas Health Innovation Ltd), and duplicates were removed. Based on the eligibility criteria, two reviewers (HK, JC) conducted title and abstract screening. They (HK, JC) then independently conducted full-text reviews. For each step, reviewers discussed to resolve any disagreement and reached a consensus regarding the eligibility of each study.

Figure 1 summarizes an overview of the study screening and selection process in the PRISMA flow diagram. A total of 450 articles were identified from the initial search: 263 articles from the international databases (PubMed: 94; CINAHL: 61; Embase: 41; Cochrane Library: 12; and additional PubMed search: 55) and 187 articles from the Korean databases (RISS: 26; KCI: 65; KMBase: 26; and KISS: 70). After removing 160 duplicates, the titles and abstracts of 290 articles were screened. Finally, a full-text screening was conducted with the remaining 63 articles, resulting in 42 articles as the final sample.

Figure 1.

PRISMA flowchart of literature search and selection process.

Data extraction and synthesis

Once the final study sample was determined, one reviewer (HK) extracted the following data from the sample studies: general information, study methods, participant characteristics, information on digital literacy, mode of data collection (online, offline, or mixed), study aims, and main findings. Two reviewers (JB, JC) reviewed and verified the extracted data. As this study aims to examine the level of digital literacy in prior studies, details about digital literacy were collected, including the scope of digital literacy (e.g. e-health literacy, Internet use, and smartphone use) and measures of digital literacy. Means and standard deviations of measures were extracted when available. When the numeric score of measures was not reported, relevant descriptive statistics were collected. For example, if a study gauged smartphone use via a yes–no binary questionnaire, the proportion of older adults using smartphones was collected. Furthermore, given the heterogeneity among measures of digital literacy, measures used in the sample studies were assessed based on the DigComp Framework.⁴ For the studies that used measures with a complete list of items available, two reviewers (HK, JB) independently evaluated the measures and cross-checked the findings. Any disagreements were resolved through discussion. The final evaluation was reviewed by all reviewers (HK, JB, and JC).

Quality assessment

One reviewer (HK) independently rated each study based on the Mixed-Methods Appraisal Tool (MMAT),⁴³ and two independent reviewers (JB, JC) reviewed and validated the quality assessment ratings to assess the quality of the articles. Any disagreements were resolved through discussion. The MMAT was developed to evaluate the quality of a wide range of studies, from mixed-methods studies and randomized controlled trials to quantitative and qualitative studies.⁴³ We reported overall quality scores using asterisks: 0 (None, indicating none of the quality criteria were met) to 100% (*****, indicating all five criteria were met).⁴³ This system has been used for quality assessment in descriptive quantitative reviews that examined older adults as the main target population.^14,44

Results

Study characteristics

Of the 42 sample studies, the year of publication ranged from 2014 to 2022, with a particularly large volume of studies since 2020 (see Figure 2). Among them, 31 (73.8%) studies were published in Korean, while 11 (26.2%) studies were published in English. Most of the studies employed a cross-sectional design (38/42), while few employed longitudinal (2/42), non-randomized experimental (1/42), and single-group pre-posttest (1/42) designs. Half of the studies used primary data (21/42), and the other half used secondary data (21/42). Most of the secondary data include the National Survey of Older Koreans (8/21), the Digital Divide Survey (4/21), and the Korea Media Panel Survey (4/21), primarily targeting older adults. However, when the data targeted the general population (e.g. the Korea Media Panel Survey), data from older participants were extracted and analyzed in each study. Studies examined digital literacy in varying scopes, such as digital literacy (18/42), e-health literacy (9/42), Internet use (4/42), smartphone use (2/42), specific technology use/utilization (6/42), and others (3/42). Table 1 summarizes the study characteristics.

Figure 2.

Number of publications by the year of publication (N = 42).

Table 1.

Summary of included studies (n = 42).

Category	n (%)	Studies
Language
English	11 (26.2)	^{31,41,45–53}
Korean	31 (73.8)	^{6,24–30,32–40,42,54–66}
Study design
Cross-sectional	38 (90.5)	^{6,24–33,35–38,40–42,46–48,50–66}
Longitudinal	2 (4.8)	^34,39
Non-randomized experimental	1 (2.4)	⁴⁹
Single-group pre-posttest	1 (2.4)	⁴⁵
Data collection
Primary data	21 (50.0)	^{24–28,33–35,38,42,45,47,49,50,54–57,59,63,65}
Secondary data	21 (50.0)
Digital Divide Survey (2016, 2017, 2017, 2020)	4 (9.5)	^6,30,37,41
Korea Media Panel Survey (2010–2018, 2019, 2019, 2020)	4 (9.5)	^29,36,39,64
Korean Middle and Elderly Technology Acceptance Survey (2019, 2019)	2 (4.8)	^32,40
National Survey of Older Koreans (7 from 2017, 2020)	8 (19.0)	^{48,51,52,58,60–62,66}
SK Telecom Survey on the Daily Life of Older Adults	1 (2.4)	³¹
Data collected by Chang et al. ⁵⁷	2 (4.8)	^46,53
Scope of digital literacy
Digital literacy	18 (42.9)	^{6,24,26,27,34,37–39,42,47,54–56,60–64}
E-health literacy	9 (21.4)	^{25,35,45,46,49,50,53,57,65}
Internet use	4 (9.5)	^41,51,52,59
Smartphone use	2 (4.8)	^29,36
Specific technology use/utilization	6^a (14.3)	^{28,30,32,40,48,58}
Others	3^b (7.1)	^31,33,66
Total	42 (100.0)

Includes text message or social networking service (SNS), desktop/laptop, digital information, and digital technology.

Includes digital self-efficacy, information technology literacy, and information application level.

Table 2 shows the author, year of publication, sample size, study design, scope of digital literacy, mode of data collection, study aims and findings, and MMAT scores of the sample studies. The sample is restricted to the older population aged 60 years or above, excluding the comparative younger population sample, if any. All but three studies used offline data collection (39/42): one study used an online method, another used a mixed method (offline and online), and another did not report any. The aims of the studies ranged from validating measures of digital literacy^46,57 to examining the associations between digital literacy and relevant factors.

Table 2.

Characteristics of the included studies (n = 42).

Ref.	Year	Sample size, N	Design	Scope	Mode of data collection	Study aim	Main findings	MMAT
Ahn and Seo²⁴	2014	85	Cross-sectional	Digital media literacy	Online	To investigate how generational and economic status affect digital media literacy.	Digital media literacy differed by generation and economic status. Older adults showed high levels of literacy in their understanding of media, evaluation of media information, and media use ethics (comparable to adolescents) while showing the lowest levels in communication and expression among age groups.	****
An et al.⁵⁴	2020	500	Cross-sectional	Digital literacy	Offline	To explore psychological and mental health promotion based on age through the relationship with communication behavior variables.	Health information behavior mediated the relationship between age and psychological well-being. Digital literacy moderated the relationship between age and health information behavior, whereby older adults with high digital literacy showed greater health information behavior than the younger population with high digital literacy.	****
An et al.⁵⁶	2021	500	Cross-sectional	Digital literacy	Offline	To examine how elderly and non-elderly verify health information differently based on digital literacy and health empowerment.	Health empowerment affected health information verification behavior only in the younger population. However, digital literacy moderated the relationship between health empowerment and health information verification behavior among older adults.	****
An et al.⁵⁵	2022	500	Cross-sectional	Digital literacy	Offline	To examine health beliefs of chronic diseases as the moderator on the effects of older adults’ health empowerment and digital literacy on communication with clinicians.	Older adults who had greater health empowerment with low levels of either susceptibility or perceived barriers had better communication with clinicians.	****
Chang et al.⁵⁷	2018	187	Cross-sectional	E-health literacy	Offline	To translate the eHealth Literacy Scale (eHEALS) into Korean and assess its psychometric properties.	K-eHEALS was evidenced with adequate psychometric properties to evaluate e-health literacy among Koreans.	****
Cho and Ha²⁵	2019	110	Cross-sectional	E-health literacy	Offline	To examine the mediating effects of health beliefs on the relationships between disease-related knowledge and self-care and between e-health literacy and self-care among outpatient hypertensive patients.	Positive associations were observed among e-health literacy, health belief, self-care, and disease-related knowledge (except for the association between e-health literacy and self-care). Disease-related knowledge and self-care were mediated by health beliefs.	****
Choi and Song²⁶	2020	396	Cross-sectional	Digital information literacy	Offline	To examine self-efficacy as a mediator between digital information literacy and life satisfaction among older adults.	Digital information literacy was positively associated with life satisfaction and self-efficacy. Self-efficacy mediated the relationship between digital information literacy and life satisfaction.	***
Hu²⁷	2020	173	Cross-sectional	Digital literacy	Not stated	To examine the effects of digital literacy and accessibility on digital communication, confidence, self-control, and life satisfaction among older adults.	Digital literacy positively predicted digital self-control. Digital accessibility predicted positive overall digital life, mediated by digital confidence and self-control.	**
Kim et al.⁴²	2017	158	Cross-sectional	Digital literacy	Offline	To examine the effect of information technology (IT) education on digital literacy and quality of life among middle-aged and older adults.	IT education generally had a positive effect on middle-aged and older adults’ digital literacy and quality of life.	****
Kim et al.²⁸	2014	119	Cross-sectional	Desktop/laptop use	Offline	To understand the types of Internet use and identify barriers of use among older adults in Korea.	Entertainment (music/movie) and knowledge (information search) were the main uses of the Internet for older adults; sex and age differences existed. Complexity in computer and Internet use was identified as a barrier to Internet access.	***
Kim et al.³³	2014	374	Cross-sectional	Information application level	Offline	To understand the present status of older adults’ information use level and examine its effect on quality of life.	Older adults’ information use level was positively associated with information searches and quality of life.	***
Kim et al.⁵⁹	2021	289	Cross-sectional	Internet literacy	Offline	To examine older adults’ intention to participate in exercise based on Internet literacy and extended technology acceptance model.	Internet literacy of older adults who participate in exercise positively affected the usefulness and ease of the Internet-based reservation system.	***
Lee et al.³⁵	2019	203	Cross-sectional	E-health literacy	Offline	To examine influencing factors of older women's health behaviors.	A difference in e-health literacy between women in their 60s and 70s was observed, though not in health concern, information orientation, or behavior. Health information orientation and living with a spouse affected the health behavior of women in their 60s and 70s, respectively.	***
Lee et al.⁵⁰	2020	104	Cross-sectional	E-health literacy	Offline	To compare the role and influencing factors of information and communication technology (ICT) use among older adults from South Korea and the USA.	Koreans reported higher levels of e-health literacy than Americans. In both groups, education levels and confidence in ICT use positively predicted e-health literacy.	****
Lee et al.⁴⁷	2020	200	Cross-sectional	Digital literacy	Offline	To assess the differences in the need for Internet of Things (IoT) among people with disabilities, older adults (collectively, vulnerable groups), their caregivers, and their healthcare providers.	People with disabilities, older adults, and their caregivers rated emergency and security as the most needed IoT service features, while healthcare providers rated safety as the most needed feature for vulnerable groups.	***
Lim et al.⁶³	2020	239	Cross-sectional	Digital literacy	Offline	To examine the effect of the level of older adults’ digital literacy on their quality of life.	Motivation and capacity to use digital devices positively predicted older adults’ social relationships and sense of personal growth.	****
Park and Kim³⁸	2021	203	Cross-sectional	Digital literacy	Mixed	To determine the role of cognitive flexibility in the association between older adults’ digital literacy and successful aging.	Cognitive flexibility significantly mediated the association between older adults’ digital literacy and successful aging.	***
Song and Shin⁶⁵	2020	102	Cross-sectional	E-health literacy	Offline	To examine associations between e-health literacy, perceived health status, and health-seeking behaviors.	Health-seeking behaviors were positively associated with e-health literacy and subject health.	****
Jung and Choi⁵⁸	2022	6264	Cross-sectional	Text message or social networking service (SNS)	Offline	To examine the contact frequency with others as the mediator between the use of text messages or SNS and psychological well-being among Korean older adults; to investigate the moderating role of household composition on the mediating effect of frequency of contact.	Older adults with a higher ability to text or use SNS reported higher contact frequency, life satisfaction, and lower depressive symptoms, with no difference based on household composition. Contact frequency was a mediator between the ability to text or use SNS and psychological well-being only among those living with a spouse.	****
Kim²⁹	2020	1364	Cross-sectional	Smartphone use	Offline	To systematically examine the factors that influence smartphone use among Korean older adults.	Smartphone use experience differed by sex, age, education, income, residential area, employment, marital status, and household composition. The purpose of use also differed by sociodemographic factors except for marital status.	****
Kim and Lee⁶	2018	1463	Cross-sectional	Digital literacy	Offline	To examine the determining factors of digital information use among senior mobile consumers.	Income, motivation to use or attitude toward the use of digital devices, digital literacy, and family support positively predicted digital information use in quality and quantity, while negative attitude was a negative predictor.	***
Kim and Shim⁶⁰	2020	9248	Cross-sectional	Digital literacy	Offline	To identify the association between perceived age and digital literacy among older adults and examine the effect of these variables on the social activity participation of older adults.	Older adults’ digital literacy was low; however, it was positively associated with social activity participation and satisfaction.	****
Kim et al.³⁰	2020	1494	Cross-sectional	Digital information utilization	Offline	To identify the types of digital information use among middle-aged/older adults and examine the effect of each type on life satisfaction.	Middle-aged/older adults were classified as active, medium, and suboptimal levels of digital information use. Active use had a positive effect on life satisfaction.	****
Kim et al.³¹	2021	623	Cross-sectional	Digital self-efficacy	Offline	To investigate enjoyment and anxiety as mediators in the association between digital music service use and self-efficacy.	Enjoyment and anxiety significantly mediated the relationship between digital music experience and self-efficacy.	***
Kim et al.³²	2021	500	Cross-sectional	Digital technology utilization	Offline	To understand the effect of digital device accessibility on the attitude toward aging among middle-aged and older adults; to examine multimediation of digital technology utilization and online health information-seeking behaviors.	Middle-aged/older adults’ digital device accessibility had a positive effect on digital technology utilization. Digital technology utilization and online health information-seeking behaviors mediated the relationship between digital device accessibility and attitude toward aging.	****
Kim et al.⁴⁶	2021	180	Cross-sectional	E-health literacy	Offline	To examine and compare K-DHLI and K-eHEALS in assessing e-health literacy among Korean older adults.	Both measurements were evidenced with adequate psychometric properties to assess older adults’ e-health resource use.	****
Lee⁶²	2021	9920	Cross-sectional	Digital literacy	Offline	To examine social networks as mediators in the relationship between digital literacy and quality of life among older adults.	Digital literacy and quality of life were positively associated, which was partially mediated by social networks.	****
Lee and Tak⁶¹	2020	8942	Cross-sectional	Digital literacy	Offline	To investigate the effect of digital literacy and contact with children and grandchildren using ICT on older adults’ cognitive function.	Digital literacy was the greatest influencing factor for older adults’ cognitive function. Contact with grandchildren using ICT had a positive association with digital literacy and cognitive function.	****
Lee et al.⁴⁸	2021	10,055	Cross-sectional	Digital technology use	Offline	To investigate the moderating effect of social interaction in the association between digital technology use and depressive symptoms among Korean older adults.	Digital technology use and social connections were negatively associated with depressive symptoms. Older adults with infrequent (vs frequent) contact benefited more from digital technology use.	****
Oh³⁶	2021	2780	Cross-sectional	Smartphone use	Offline	To assess the effects of smartphone skills and the innovativeness of online shopping among older adults.	Online shopping users (vs non-users) reported higher innovativeness and smartphone skills, both of which positively predicted online shopping.	*****
Oh and Yoo³⁷	2018	329	Cross-sectional	Digital literacy	Offline	To understand the effect of digital literacy on older adults’ psychological well-being and quality of life.	Older adults’ digital literacy improved their depression, loneliness, anxiety, self-esteem, and life satisfaction.	****
Park and Jeong⁶⁴	2022	2281	Cross-sectional	Digital literacy	Offline	To compare the status of digital literacy and levels of online community and social participation of older adults in single-person households to the MZ generation in single-person households and multiperson households and highlight the causal mechanism between digital literacy and social participation.	Older adults in single-person (vs multiperson) households showed lower levels of digital literacy and online or social community participation. Online community participation mediated the association of digital literacy and social community participation among older adults in single-person households.	****
Park and Kim⁵²	2020	1919	Cross-sectional	Internet use	Offline	To examine associated factors of Internet use, such as opportunity, motivation, and other health variables, among Korean older adults with diabetes.	Internet use was positively associated with education, economic status, motivation to learn, ICT training, physical and cognitive health, and community service and negatively associated with age. ICT training and better health were key predictors.	****
Park and Kim⁵¹	2020	1919	Cross-sectional	Internet use	Offline	To categorize older adults with diabetes into different groups depending on their Internet use.	Older adults with diabetes were classified into non-users, communicating users, and smart users. Smart users (relative to other classes) were positively associated with education, income, and physical, cognitive, and psychosocial health. Communicating users reported a lower incidence of depression.	****
Um et al.⁶⁶	2021	10,058	Cross-sectional	IT literacy	Offline	To examine the relationship between Korean older adults’ IT literacy and healthy aging based on age groups.	IT literacy was positively associated with subjective well-being, cognitive function, and social participation and negatively associated with chronic disease and depression. It predicted only cognitive, social, and psychological health among the oldest-old group while predicting wider aspects of health among the younger- and middle-old groups.	****
Um et al.⁴⁰	2021	500	Cross-sectional	Digital technology use	Offline	To investigate the relationship between health literacy and the digital divide among middle-aged and older adults and examine sex-based differences.	Middle-aged/older adults’ health information literacy was positively associated with technology literacy among men but not women.	****
Yang and Lee⁴¹	2022	3629	Cross-sectional	Internet use	Offline	To investigate the associated factors behind mobile use and the mobile use levels among older adults based on the presence of disabilities and examine the moderating effects of disabilities on the relationships between associated factors and mobile Internet use.	Older adults with disabilities (relative to those without) reported lower use of mobile Internet while reporting stronger associations between mobile Internet use and (1) Internet use skills, (2) motivation and attitude toward technology use, and (3) operational skills for mobile devices.	****
Yang et al.⁵³	2020	187	Cross-sectional	E-health literacy	Offline	To examine associated factors of older adults’ e-health literacy.	Positive attitudes toward Internet health information predicted e-health literacy in older and young adults.	****
Lee³⁴	2015	122	Longitudinal	Digital literacy	Offline	To understand how cognitive–pragmatic language in normal aging changes over time and examine the influencing factors using a longitudinal design.	Those who maintained cognitive–pragmatic language ability (vs those who declined) showed higher levels in all but one domain of cognitive–pragmatic language abilities. The two groups differed in age, education, language experience, digital literacy, and social participation.	****
Park and Kim³⁹	2019	4065	Longitudinal	Digital literacy	Offline	To investigate the longitudinal trend of the digital divide across different generations of older adults.	Digital access improved in all generations despite the digital divide observed, with income and education levels predicting smartphone access. A disparity in digital literacy and use was observed between the ages of 55–74 and over 75. Smartphone ownership and digital literacy had a positive effect on older adults’ digital use.	*****
Lee et al.⁴⁹	2022	52	Non-randomized experimental	E-health literacy	Offline	To assess the results of a 12-week program based on mutual aid and intergenerational exchange between older adults and young adults.	Older adults who participated in the program reported decreased anxiety and increased (1) ICT skills, (2) confidence in using computers, and (3) overall e-health literacy.	*****
Chang et al.⁴⁵	2021	11	Single-group pre-posttest	E-health literacy	Offline	To examine the feasibility and preliminary results of the newly developed education program focused on Internet health information.	The intervention resulted in improved knowledge of, attitude toward, and understanding of Internet-based health information, e-health literacy, and search performance.	*****

N: sample size; MMAT: Mixed-Methods Appraisal Tool.

Associated factors of digital literacy

Figure 3 summarizes the associated factors of digital literacy identified in the sample studies. Individual factors included those associated with health, attitudes, perceptions, and behaviors of individuals. Social and environmental factors encompassed factors associated with social interactions and accessibility to devices and learning to use them.

Figure 3.

Summary of associated factors of digital literacy in the included studies.

Measurement of digital literacy

The measurement of digital literacy was heterogeneous across studies. Each measure in the sample studies was assessed based on the DigComp Framework.⁴ As the fair evaluation of the scales requires all items, only the measures with a full list of items presented were assessed based on the DigComp Framework. However, if the studies used secondary datasets with items available online, the items were retrieved from the online codebook, and those studies were included in the DigComp evaluation (see Table 3).

Table 3.

Digital literacy measurement based on the DigComp Framework.

Source	Studies	Number of items, scoring	DigComp components^a
Source	Studies	Number of items, scoring	1	2	3	4	5
eHEALS^b	^{25,35,45,46,49,50,53,57,65}	8-item, 5-point	O^c	O	X^d	O	O
K-DHLI^e	⁴⁶	21-item, 4-point	O	O	O	O	X
FACETS^f	^32,40	10-item, 6-point	O	O	O	X	O
Digital Divide Index^g	²⁶	5-item, 5-point	O	O	X	X	X
Internet literacy^g	⁵⁹	5-item, 5-point	O	X	X	X	X
Digital literacy^g	⁶³	25-item, 5-point	O	O	O	O	O
Daily usage and amount of desktop and laptop use; type of Internet use^g	²⁸	2-item, reported hour of usage; 2-item, 4-point; 7-item, binary^h	O	O	X	X	X
Information and communication technology (ICT) device use, online activity, and information search^g	³³	9-item, 5-point	O	O	X	X	X
Perception of the Internet, smartphone, and Internet of Things^g	⁴⁷	7-item, binary	O	X	X	X	X
Frequency of Internet and email usage^g	³⁴	Single-item, 4-point	O	O	X	X	X
Digital Divide Survey
2016 version	³⁷	11-item, scale point unknown	O	O	O	O	X
2017 version	⁶	38-item, 4-point	O	O	O	O	O
2017 version	³⁰	7-item, 4-point	O	O	O	X	X
2020 version	⁴¹	1-item, binary; 25-item, 4-point	O	O	O	X	X
Korea Media Panel Survey
2010–2018 versions	³⁹	18/20-item, binary	O	O	O	O	O
2019 version	²⁹	14-item, binary	O	O	X	X	O
2019 version	³⁶	20-item, binary	O	O	O	O	O
2020 version	⁶⁴	47-item, 5-point	O	O	O	O	O
National Survey of Older Koreans
2017 version	^60,61,66	10-item, binary	O	O	X	X	X
2017 version	⁵⁸	3-item, 4-point	X	O	X	X	X
2017 version	⁴⁸	9-item, binary	O	O	X	X	X
2017 version	⁵²	Single-item, binary	O	X	X	X	X
2017 version	⁵¹	10-item, binary	O	O	X	X	X
2020 version	⁶²	11-item, binary	O	O	X	X	X
SK Telecom Survey on the Daily Life of Older Adults	³¹	10-item, 5-point	O	X	X	X	O

Digital Competence (DigComp) components are as follows: (1) information and data literacy, (2) communication and collaboration, (3) digital content creation, (4) safety, and (5) problem solving. For more information, see Ferrari et al.⁴

eHEALS: eHealth Literacy Scale.

O: included in the questionnaire.

X: not included in the questionnaire.

K-DHLI: Korean version of the Digital Health Literacy Instrument.

FACETS: Functional Assessment of Currently Employed Technology Scale.

Investigator-developed measurement.

Binary: yes/no binary choice.

In total, 25 measures were identified, among which only three were validated: eHEALS,³ the Korean version of the Digital Health Literacy Instrument (K-DHLI),^57,67 and the Functional Assessment of Currently Employed Technology Scale (FACETS)⁶⁸ (3/25). The eHEALS was used in nine studies to measure digital literacy, while the K-DHLI and the FACETS were used in one and two studies, respectively. Seven studies employed investigator-developed measures (7/25). Among secondary studies that used national survey data, a large variability in digital literacy measures was observed even when the same dataset from the same year was used (15/25). The number of items varied from 1 to 47 items.

Most of the measures included the information and data literacy (24/25) and communication and collaboration (21/25) components of the DigComp Framework. The digital content creation component was assessed in more than one-third of the measures (10/25), while the safety (8/25) and problem-solving (9/25) components were assessed at a slightly lesser frequency. Interestingly, using the same dataset did not yield the same result from the DigComp evaluation, as each study operationalized digital literacy using different sets of survey questions. For example, the evaluation based on the Digital Divide Survey ranged from three to five components, assessed as the number of items ranging from a minimum of 7 to a maximum of 38.

Comparison of studies using the eHEALS

Among 19 measures that contained full items, the eHEALS, originally developed by Norman and Skinner,³ was the only validated scale that was used in nine studies. Table 4 summarizes nine studies that used the eHEALS.

Table 4.

Studies that used the eHEALS (n = 9).

Study	N	Mean age (SD^a) or proportion	Residence	Other sample characteristics	Scale adaptation	Total/mean score^a (SD)
Chang et al.⁵⁷	187	73.18 (4.76)	Seoul	57.2% currently having a disease	Adapted from Norman and Skinner³ in Korean	30.91 (4.17)
Cho and Ha²⁵	110	60s: 31.4% 70s: 30.8% 80+: 8.3% (excluding those aged ∼60)	Busan	Patients receiving treatment for hypertension	Adapted version in Chang et al.⁵⁷	60s: 2.92 (0.93) 70s: 2.75 (0.86) 80+: 2.42 (0.88)
Lee et al.³⁵	203	60s: 66.5% 70s: 33.5%	N/A	Community-dwelling female older adults	Adapted version in Lee et al.⁶⁹	60s: 24.31 (7.99) 70s: 17.07 (9.51)
Lee et al.⁵⁰	104	71.34 (6.69)	Urban areas	From low-income urban areas	Adaptation not stated	3.56 (0.6)
Song and Shin⁶⁵	102	70.01 (4.84) 60s: 54.4% 70–74: 29.1% 75+: 15.5%	Seoul, Gyeonggi, Northern Gyeongsang	N/A	Adapted version in Chang et al.⁵⁷	28.35 (5.01)
Kim et al.⁴⁶	180	73.07 (4.76)	Seoul	57.8% currently having a disease	Adapted version in Chang et al.⁵⁷ (same data)	3.88 (0.52)
Yang et al.⁵³	187	73.2 (4.78)	N/A	57.8% having a disease	Adaptation not stated	30.95 (4.17)
Lee et al.⁴⁹	52	72.9 (N/A)	Seoul	82% having an average of 1.27 chronic illnesses	Adaptation not stated	3.45 (0.60)
Chang et al.⁴⁵	11	74.64 (N/A)	N/A	72.7% currently having a disease	Adapted version in Chang et al.⁵⁷	28.31 (1.08)

Total score indicates the sum of eight items of the eHealth Literacy Scale (eHEALS) with scores ranging from 8 to 40. Mean score indicates the total score divided by the number of items, thereby ranging from 1 to 5.

N: sample size; SD: standard deviation; N/A: not applicable.

Seven studies had sample sizes of more than 100 participants, while two did not. Further, seven studies provided the mean age of participants, all of whom were over 70 years old. Information on the place of residence was limited and somewhat varied but was focused mostly on urban areas. Regarding other notable participant characteristics, one study recruited participants receiving treatment for hypertension,²⁵ while two studies had more than 70% of participants with diseases^45,49 and three other studies had more than 50% of participants with diseases.^46,53,57

Among these nine studies, five used the translated version by Chang et al.,⁵⁷ and one used the translated version by Lee et al.⁶⁹ Three studies did not provide details on the version of the scale used. The eHEALS scores ranged from 17.07 on a 40-point scale among older adults in their 70s³⁵ to 30.91 on a 40-point scale.⁵⁷ Notably, two studies reported low levels of digital literacy, one of which targeted participants receiving treatment for hypertension, with mean scores of 2.42 to 2.92 on a five-point scale based on age groups.²⁵ The other study targeted community-dwelling female older adults with a total score of 17.07 on a 40-point scale among those in their 70s.³⁵

Discussion

In this review, we identified 42 quantitative studies that examined Korean older adults’ digital literacy and provided an overview of the studies. We also evaluated the measures of digital literacy used in each study based on the DigComp Framework. Further, we compared the level of digital literacy among the studies that employed the eHEALS,³ the most frequently used scale among the sample studies. This review is timely, as South Korea is experiencing the fastest rate of aging among OECD countries,¹⁷ along with the high levels of digitalization in society.¹⁶ The topic is also relevant to emerging older adults who are likely to be better prepared for the current digital use, as technological advances will introduce new challenges regardless of current digital competency. To our best knowledge, this scoping review is among the first to evaluate the current understanding of digital literacy among Korean older adults and identify limitations in previous quantitative studies. This review revealed that most studies on this topic were published in 2020 and onward, perhaps indicating that older adults in South Korea are in the process of entering the digital realm. We found that 38 of 42 studies used cross-sectional data, 18 of which conducted research using open government data.^{6,29,30,32,36,37,39–41,48,51,52,58,60–62,64,66} We also observed that factors promoting digital literacy varied across studies, including self-efficacy, health empowerment, positive attitudes toward technology, technology education, health-seeking behavior, family support, and cognitive flexibility.^{6,26,38,42,53,65} Studies also examined associations between digital literacy and physical and mental health.^{26,30,33,37,38,48,52,58,61,63,66}

Interestingly, studies are limited in identifying regional variations in digital literacy among older adults. Previous studies highlight the digital divide between rural and urban areas in Korea⁷⁰ and globally.^71,72 Future research on regional variations in digital literacy may help furnish insights into region-specific differences and avenues for future interventions. For example, older adults in rural areas may show lower levels of digital literacy relative to those in urban areas, but they may also report lower levels of perceived need for digital literacy given the slow rate of digitalization in rural areas.⁷³ A region-specific nuance should be understood to better design an intervention program to improve digital literacy and advocate for equity in digital access across regions.

Regarding the measures, despite the increase in the volume of research on older adults’ digital literacy, the operationalization and assessment were heterogeneous and mostly insufficient to fulfill all five components of the DigComp Framework. Among 25 identified assessments, the most frequently used measure was the eHEALS. Even so, it was limited in covering all components of the DigComp Framework¹³ and was focused primarily on skills to use the Internet for health-related purposes.^3,74 The concept of digital literacy will continue to evolve and diversify as the digital environment keeps expanding with the emergence of new digital devices and software,⁷⁵ which warrants measures that can capture one's competency across the digital realm. However, given the constantly evolving nature of digital technology, measurement inconsistencies may be inevitable. Furthermore, it is important to note that discrepancies in findings based on measurement methods (i.e., offline vs. online) are unavoidable because older adults who participate in online assessments are more likely to have higher levels of digital literacy and accessibility compared to those who do not participate in online. Considering this fundamental difference that can potentially introduce bias into the findings, studies focusing on older adults’ digital literacy and engagement should be cautious when reporting results. It is crucial for these studies to consider how their chosen measurement method could unintentionally skew the outcomes and their subsequent interpretation.

Notably, four studies based on national surveys addressed all five components of the DigComp evaluation,^6,36,39,64 though they may pose potential limitations. First, researchers used different sets of survey items—even when using the same national survey dataset—in operationalizing digital literacy. Inconsistencies in the choice of items may make comparisons among studies challenging. Second, national surveys employ lengthy questionnaires, which may unintentionally burden older adults and ultimately affect the quality of survey data. For example, the Digital Divide Survey comprised 18 pages,⁷⁶ and the Korea Media Panel Survey had 23 pages, including a three-day media use tracking.⁷⁷ As older adults experience reduced attention,^78,79 a lengthy questionnaire may not be appropriate and could compromise the data quality.⁸⁰ Third, national surveys may pose selection bias risks because older adults participating in the survey may overrepresent cognitively well-functioning older adults. This systematically differential representation may compromise the generalizability of the data. Therefore, there is a need for more robust and succinct digital literacy measures targeted at general older adults.

While acknowledging the limitations in the digital literacy assessment, most measures included components of information search or use and communication or collaboration based on the DigComp Framework.⁴ Alternatively, three other components (content creation, safety, and problem solving) were not addressed in more than half of the measurements. This trend accords with the previous systematic review that examined the validated measures of digital literacy for older adults.¹³ It may also evidence the broad spectrum of digital literacy introduced in response to the constant development of digital technology^81,82 (e.g., computer literacy, media literacy, and e-health literacy) and how each type of digital literacy measures targets different types of digital use. Alternatively, information search and communication through digital devices may be more easily expected for older adults than digital content creation or problem solving. Hence, researchers may have focused on assessing those two domains that seem more appropriate for older adults’ competency. Evidently, this area deserves further investigation.

We additionally examined the level of older adults’ digital literacy based on the eHEALS. The eHEALS scores were comparable to the US sample of 866 older adults recruited online,⁸³ but the online sample in the US study may have higher familiarity with digital utilization and, hence, report higher levels of digital literacy. Alternatively, much lower eHEALS scores were reported in the systematic review of Chinese older adults’ digital literacy.¹⁴ However, the sample studies varied in regions and health conditions, making a fair comparison challenging. Regardless, given the simple digital competencies described in the eHEALS items, Korean older adults’ digital literacy remains low and requires further improvement.

This review has several limitations. First, the systematic literature search may have missed some articles. We restricted the search to peer-reviewed journal articles published in English or Korean. Even though the topic of digital literacy in South Korea is highly likely to be published in either of these languages, there remains a possibility of failing to identify relevant articles in other languages and databases. Second, this review was limited to quantitative studies. While qualitative studies are beyond the scope of this review, they would have provided a broader picture of digital literacy among older adults in South Korea. Third, the older population is a heterogeneous group in their digital experiences and their device accessibility and need to use digital devices.⁸⁴ However, such experiences were beyond the study scope. Hence, more attention should be paid to different groups of older adults with diverse digital identities and experiences to develop a tailored interventional approach to support them.

Future research can develop a novel measure for older adults’ digital literacy for a comprehensive evaluation of diverse aspects of the construct. As technology evolves, digital space will expand, and the concept of digital literacy will change and become diversified.^85,86 Using the DigComp Framework to capture the diverse aspects of digital literacy revealed that few measures fulfilled all five components in the sample studies. Thus, future research should develop an optimal measure that can capture the varying aspects of digital literacy while considering the cognitive capacity of older adults to keep up with the expanding digital realm. Further, the proposed potential sociodemographic factors are worth exploring to appreciate the digital literacy and usage level. Hence, future empirical research should focus on how individual and environmental factors promote or hinder digital literacy in older adults to help policymakers develop supportive programs and policies to promote aging in place in the digitalized society. Lastly, when measuring older adults’ digital literacy and engagement, future research should make sure to disclose measurement methods because of the increased likelihood of higher digital literacy and accessibility among those who participate in online assessments. Therefore, clear reporting and transparent disclosure of measurement methods are essential for research targeting older adults and their digital experience.

Conclusion

Scholarly interest in digital literacy among older adults has rapidly risen in South Korea over the past few years. While the level of digital literacy among older adults in South Korea remains inconclusive given measurement heterogeneity, demographic characteristics may facilitate the digital experiences of older adults in varying circumstances. Inconsistencies observed in digital literacy measures give scope for future research to develop a more streamlined measure that can promote consistent measures to systematically comprehend individual levels of digital literacy.

Supplemental Material

sj-docx-1-dhj-10.1177_20552076231197334 - Supplemental material for Digital literacy among Korean older adults: A scoping review of quantitative studies

Supplemental material, sj-docx-1-dhj-10.1177_20552076231197334 for Digital literacy among Korean older adults: A scoping review of quantitative studies by Hun Kang, Jiwon Baek, Sang Hui Chu and JiYeon Choi in DIGITAL HEALTH

Footnotes

Contributorship

JC and SHC conceptualized and supervised the study. JC, HK, and JB developed the methodology. JC, HK, and JB conducted formal analysis and validation. JC, HK, JB, and SHC wrote, reviewed, and edited the manuscript.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Approval

This is not applicable because this article does not involve human or animal subjects.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2020R1A6A1A03041989 (JC, JB); NRF-2022R1I1A1A01071924 (JB)), Mo-Im Kim Nursing Research Institute (JC, JB, and SHC), Institute for Innovation in Digital Healthcare, Yonsei University (JC), and Yale-NUS College Summer Internship Program (HK).

Guarantor

Informed Consent

This manuscript presents a scoping review of publicly available literature. The requirement for consent is not applicable since no individual data were used in this manuscript.

ORCID iD

JiYeon Choi

Supplemental Material

Supplemental material for this article is available online.

References

Gilster

. Digital literacy. New York: Wiley Computer Pub., 1997.

Rice

Bailon

. A qualitative analysis of publicly available standards and guidance about digital literacies in U.S. States. Educ Inf Technol 2023; 28: 6927–6946. doi:10.1007/s10639-022-11482-x

Norman

Skinner

. eHEALS: the eHealth literacy scale. J Med Internet Res 2006; 8: 27.

Ferrari

Punie

Brecko

. DIGCOMP: a framework for developing and understanding digital competence in Europe. 2013.

Chesser

Burke

Reyes

, et al. 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.

Kim

Lee

. Determinants of mobile digital information usage among senior consumers: focusing on secondary digital divide. Family Environ Res 2018; 56: 493–506.

Lee

Kim

Hong

. An empirical study of the elderly’s information literacy on their happiness. J Korea Ind Inf Syst Res 2015; 20: 125–131.

Smith

. Older adults and technology use. Washington, DC: Pew Research Center, 2014. http://www.pewinternet.org/2014/04/03/olderadults-and-technology-use/

Choi

Dinitto

. The digital divide among low-income homebound older adults: Internet use patterns, eHealth literacy, and attitudes toward computer/Internet use. J Med Internet Res 2013; 15: 93.

10.

Reiners

Sturm

Bouw

, et al. Sociodemographic factors influencing the use of eHealth in people with chronic diseases. Int J Environ Res Public Health J 2019; 16: 645. doi:10.3390/ijerph16040645

11.

Nguyen

Mosadeghi

Almario

. Persistent digital divide in access to and use of the Internet as a resource for health information: results from a California population-based study. Int J Med Informatics 2017; 103: 49–54.

12.

World Health Organization. Ageing and health. [place unknown]: World Health Organization, 2022. https://www.who.int/news-room/fact-sheets/detail/ageing-and-health#:∼:text=People%20worldwide%20are%20living%20longer,aged%2060%20years%20or%20over.

13.

Kim

, et al. Measurement of digital literacy among older adults: systematic review. J Med Internet Res 2021; 23: e26145. doi:10.2196/26145

14.

Shi

Zhang

, et al. In the digital age: a systematic literature review of the e-health literacy and influencing factors among Chinese older adults. J Public Health J 2023; 31: 679–687. doi:10.1007/s10389-021-01604-z

15.

Larson

. Digital development in Korea: building an information society. London: Routledge, 2011.

16.

Gallup Report. The 2012-2022 report on smartphone use & brand, smart watch, and wireless earphone. 24 June, 2023. https://www.gallup.co.kr/gallupdb/reportContent.asp?seqNo=1309.

17.

OECD. Old-age dependency ratio (indicator) . [place unknown]: Organization of Economic Cooperation and Development, 2022. doi:10.1787/e0255c98-en

18.

Munn

Pollock

Khalil

, et al. What are scoping reviews? Providing a formal definition of scoping reviews as a type of evidence synthesis. JBI Evid Synth 2022; 20: 950–952.

19.

Arksey

O’Malley

. Scoping studies: towards a methodological framework. Int J Soc Res Methodol 2005; 8: 19–32.

20.

Levac

Colquhoun

O’Brien

. Scoping studies: advancing the methodology. Implement Sci 2010; 5: 69.

21.

Aromataris

Munn

. JBI manual for evidence synthesis. 2020.

22.

Peters

Godfrey

Khalil

, et al. Guidance for conducting systematic scoping reviews. Int J Evid Based Healthc 2015; 13: 141–146.

23.

OECD. Elderly population (indicator). [place unknown]: Organization of Economic Cooperation and Development, 2022. doi:10.1787/8d805ea1-en

24.

Ahn

Seo

. An analysis of sub-factors of digital media literacy divide: focusing on the effects of generation and economic status. J Digital Convergence 2014; 12: 69–78.

25.

Cho

. Mediating effects of health belief on the correlations among disease-related knowledge, eHealth literacy, and self-care behaviors in outpatients with hypertension. Korean J Adult Nurs 2019; 31: 638–649.

26.

Choi

Song

. The mediating effect of self-efficacy between the elderly’s digital information literacy and life satisfaction. J Korea Acad-Ind Coop Soc 2020; 21: 246–255.

27.

. Analysis of the effect of the digital divide on the digital daily life of the elderly. J Digital Convergence 2020; 18: 9–15.

28.

Kim

Lee

. An analysis on the Internet uses and barriers of the older adults in Korea. J Korean Soc Lib Inf Sci 2014; 48: 257–276.

29.

Kim

. How much do we know about the use of smartphones in the silver generation? Determinants of the digital divide within the silver generation. Inf Soc Media 2020; 21: 33–64.

30.

Kim

. A study about the types of digital information utilization and life satisfaction of middle-aged and the older people. J Korean Assoc Reg Inf Soc 2020; 21: 51–74.

31.

Kim

. Experience of digital music services and digital self-efficacy among older adults: enjoyment and anxiety as mediators. Technol Soc 2021; 67: 101773.

32.

Kim

Shin

Chae

, et al. The relationship between digital device accessibility and aging attitudes of Korean middle-aged and older adults: multi-mediation effects of digital technology utilization and online health information seeking. J Korean Assoc Reg Inf Soc 2021; 24: 77–107.

33.

Kim

Lee

. The effect of the elderly’s information application level on quality of life. J Korean Assoc Reg Inf Soc 2014; 17: 25–47.

34.

Lee

. A longitudinal study on cognitive-pragmatic language in normal aging: demographic and experiential influences. J Korean Gerontol Soc 2015; 35: 797–811.

35.

Lee

Yun

. Health concern, health information orientation, e-health literacy and health behavior in aged women: focused on 60-70s. J Convergence Inf Technol 2019; 9: 39–47.

36.

. Influencing factors of senior consumers’ non-face-to-face shopping channel use: focus on consumer innovativeness and smartphone skills. Inf Soc Media 2021; 22: 1–27.

37.

Yoo

. A study on the effect of digital literacy on the psychological wellbeing and life satisfaction of the elderly. Korean Public Manage Rev 2018; 32: 319–344.

38.

Park

Kim

. The mediating effect of cognitive flexibility on the relationship between digital literacy and successful aging of senior. J Humanit Soc Sci 2021; 12: 2407–2422.

39.

Park

Kim

. A panel analysis (2010–2018) of the digital divide among different age groups among older adults. J Korean Data Anal Soc 2019; 21: 2407–2418.

40.

Yoon

Shin

, et al. The relationship between health literacy and digital divide of middle-aged and older adults: focused on gender differences. J Korean Assoc Reg Inf Soc 2021; 24: 127–153.

41.

Yang

Lee

. The moderating effects of disability on mobile Internet use among older adults: population-based cross-sectional study. J Med Internet Res 2022; 24: e37127. doi:10.2196/37127

42.

Kim

Cho

Suh

. A study of the effectiveness of information literacy education among the elderly: a focus on digital literacy and quality of life. Korean J Public Adm 2017; 55: 229–259.

43.

Hong

Fàbregues

Bartlett

, et al. The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. Educ Inf 2018; 34: 285–291.

44.

Frazer

Mitchell

Stokes

, et al. A rapid systematic review of measures to protect older people in long-term care facilities from COVID-19. BMJ Open 2021; 11: e047012. doi:10.1136/bmjopen-2020-047012

45.

Chang

Yang

Lee

, et al. Internet health information education for older adults: a pilot study. Geriatr Nurs 01 Mar 2021; 42: 533–539.

46.

Kim

Yang

Ryu

, et al. Psychometric comparisons of measures of eHealth literacy using a sample of Korean older adults. Int J Older People Nurs 2021; 16: e12369.

47.

Lee

Park

Kim

, et al. Discrepancies in demand of Internet of Things services among older people and people with disabilities, their caregivers, and health care providers: face-to-face survey study. J Med Internet Res 2020; 22: e16614.

48.

Lee

Ferraro

Kim

. Digital technology use and depressive symptoms among older adults in Korea: beneficial for those who have fewer social interactions? Aging Ment Health 2021; 25: 1839–1847.

49.

Lee

Kim

Lee

, et al. Information communication technology use to improve eHealth literacy, technophobia, and social connection among community dwelling older adults. Educ Gerontol 2022; 48: 445–457. doi:10.1080/03601277.2022.2045727

50.

Lee

OEK

Kim

Beum

. Factors affecting information and communication technology use and eHealth literacy among older adults in the US and South Korea. Educ Gerontol 2020; 46: 575–586.

51.

Park

Kim

. Readiness for utilizing digital intervention: patterns of Internet use among older adults with diabetes. Prim Care Diabetes J 2020; 14: 692–697.

52.

Park

Kim

. Predictors of Internet use among older adults with diabetes in South Korea: survey study. JMIR Med Inform 2020; 8: e19061.

53.

Yang

Chang

Ryu

, et al. Comparing factors associated with eHealth literacy between young and older adults. J Gerontol Nurs 2020; 46: 46–56.

54.

Lim

Chung

. Psychological wellbeing through health information behavior: effects of the elderly’s digital literacy. J Korean Gerontol Soc 2020; 40: 833–854.

55.

Lim

Chung

. The effects of digital literacy and health empowerment on elders’ communication with doctors: focusing on moderating effect of health beliefs. J Korean Acad Commun Health Nurs 2022; 33: 53–62.

56.

Lim

Chung

. Study on health information verification behavior according to digital literacy & health empowerments. J Korean Gerontol Soc 2021; 41: 309–325.

57.

Chang

Yang

Ryu

, et al. Cross-cultural adaptation and validation of the eHealth literacy scale in Korea. Korean J Adult Nurs 2018; 30: 504–515.

58.

Jung

Choi

. The association between ability to use text message or SNS and psychological well-being among older adults: mediating effect of informal social contact and moderated mediating effect of household composition. J Korea Gerontol Soc 2022; 42: 201–221.

59.

Kim

Lee

Yoon

Y-J

. A study on intention of participating in exercise by using Extended Technology Accepted Model (ETAM) with Internet literacy: elderly with experience in Internet reservation system. Korean J Phys Educ 2021; 60: 13–28.

60.

Kim

Shim

. Digital literacy of elderly people and social activities. Korean J Policy Anal Eval 2020; 30: 153–180.

61.

Lee

Tak

. The effects of digital literacy and the frequency of contact with children or grandchildren via ICT on the cognitive function of the elderly. Korea Gerontol Soc 2020; 40: 413–428.

62.

Lee

. The effects of digital literacy in the elderly on quality of life and mediating effect of social network. J Humanit Soc Sci 2021; 12: 307–322.

63.

Lim

Kim

. The effects of digital literacy on the quality of life in elderly. J Lifelong Learn Soc 2020; 16: 111–135.

64.

Park

Jeong

. Elderly one-person households’ digital literacy, online community activities, and social participation: focusing on the comparison of MZ generation and the elderly single-person and multi-person households. J Speech Media Commun Res 2022; 21: 281–318.

65.

Song

Shin

. The effects of e-Health literacy and subjective health status on health-seeking behaviors of elderly using the Internet in the community. J Digital Convergence 2020; 18: 321–332.

66.

Kim

, et al. The relationship between information technology literacy and healthy aging in the Korean older adults: focused on comparison age difference. J Korean Assoc Reg Inf Soc 2021; 24: 29–60.

67.

van der Vaart

Drossaert

. Development of the digital health literacy instrument: measuring a broad spectrum of health 1.0 and health 2.0 skills. J Med Internet Res 24 Jan 2017; 19: 27.

68.

Lepkowsky

Arndt

. Functional Assessment of Currently Employed Technology Scale (FACETS): reliability and validity. Int J Med Sci Clin Invent 2018; 5: 4064–4068.

69.

Lee

Byoun

Lim

. The influence of individual’s e-health literacy on doctor-patient communication. J Cybercommunication Acad Soc 2010; 27: 89–125.

70.

Hwang

. Digital divide in Internet use within the urban hierarchy: the case of South Korea. Urban Geogr 2004; 25: 372–389.

71.

Fong

. Digital divide between urban and rural regions in China. Electron J Inf Syst Dev Countries 2009; 36: 1–12.

72.

Lembani

Gunter

Breines

, et al. The same course, different access: the digital divide between urban and rural distance education students in South Africa. J Geogr Higher Educ 2020; 44: 70–84.

73.

Salemink

Strijker

Bosworth

. Rural development in the digital age: a systematic literature review on unequal ICT availability, adoption, and use in rural areas. J Rural Stud 2017; 54: 360–371.

74.

van der Vaart

van Deursen

Drossaert

, et al. 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.

75.

Blevins

. Teaching digital literacy composing concepts: focusing on the layers of augmented reality in an era of changing technology. Comput Compos 2018; 50: 21–38.

76.

National Information Society Agency. The Report on the Digital Divide 2017. https://www.nia.or.kr/site/nia_kor/ex/bbs/View.do?cbIdx=81623&bcIdx=19480&parentSeq=19480.

77.

Korea Information Society Development Institute. Korea Media Panel Survey. https://stat.kisdi.re.kr/kor/contents/ContentsList.html?subject=SURV&sub_div=S.

78.

Commodari

Guarnera

. Attention and aging. Aging Clin Exp Res 2008; 20: 578–584.

79.

Drag

Bieliauskas

. Contemporary review 2009: cognitive aging. J Geriatr Psychiatry Neurol June 2010; 23: 75–93.

80.

Farage

Miller

Ajayi

, et al. Design principles to accommodate older adults. Glob J Health Sci 2012; 4: 2–25.

81.

Bawden

. Origins and concepts of digital literacy. Digital Literacies: Concepts, Policies and Practices 2008, pp.17–32.

82.

Martin

Grudziecki

. DigEuLit: concepts and tools for digital literacy development. Innov Teach Learn Inf Comput Sci 2006; 5: 249–267.

83.

Chung

Nahm

. Testing reliability and validity of the eHealth Literacy Scale (eHEALS) for older adults recruited online. Comput Inform Nurs 2015; 33: 150–156.

84.

Hänninen

Taipale

Luostari

. Exploring heterogeneous ICT use among older adults: the warm experts’ perspective. New Media Soc 2021; 23: 1584–1601.

85.

Bulfin

McGraw

. Digital literacy in theory, policy and practice: old concerns, new opportunities. Teaching and Digital Technologies: Big Issues and Critical Questions 2015, pp.266–281.

86.

Pangrazio

Godhe

Ledesma

AGL

. What is digital literacy? A comparative review of publications across three language contexts. E-learning Digital Media 2020; 17: 442–459.

Supplementary Material

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