Digital Health Literacy in Dentistry: A Critical Review

ABSTRACT

Objective:  To investigate the current research on digital health literacy (DHL) in dentistry to better understand its associations with dental outcomes and gaps in the literature.

Material and Methods:  The methodology followed the PRISMA-ScR checklist. A critical review was conducted by selecting articles from the online databases PubMed, Web of Science and Latin American and Caribbean Literature on Health Sciences Database (LILACS) and searches were also carried out in Google Scholar to identify articles in the gray literature published until February 2025. Studies on DHL in dentistry were analysed and only full-text, peer-reviewed articles were selected for analysis.

Results:  The bibliographical search identified 1855 articles, of which 15 were selected for qualitative synthesis. All of the included studies had a cross-sectional design, the majorityof the studies was carried out in Brazil and most of them used the eHealth Literacy Scale (eHEALS) to measure DHL levels. The research gaps identified concerning DHL in dentistry point to the need for further research in diverse sociodemographic groups and settings to better understand the impact of DHL in this area of knowledge.

Conclusion:  This review has shown that few articles published to date have focused on digital health literacy in dentistry, indicating that the relationships between digital literacy, oral health, and health literacy needs to be further explored.

Keywords:
Digital Health; Health Literacy; Oral Health; Public Health Dentistry.

Introduction

In recent years, the digital revolution has radically transformed how people access information, communicate with each other and make decisions. Studies indicate an exponential increase in the use of digital devices and internet access worldwide [¹]. Estimates point to approximately 5.44 billion people around the world using the internet, equivalent to 67.1 percent of the world’s total population [²].

Use of Information and Communication Technologies (ICTs) in the health sector gave rise to the term eHealth, defined as “the use of information and communication technology in support of health and health-related fields” [³]. This concept also includes mobile health, defined as “the use of mobile wireless technologies for health” [³]. Currently, the term digital health has been introduced, which comprises eHealth and other related areas, such as the use of advanced computer sciences in big data and artificial intelligence [⁴].

Using information in the health sector requires people to have skills and competencies to access, understand, evaluate and apply said information, a field of study known as health literacy [⁵]. In eHealth, these skills and competences are essential for individuals to access and evaluate the quality of the information disclosed on the internet to make the best health decisions [⁶]. For this purpose, they must have adequate electronic health (eHealth) literacy6, defined by Norman and Skinner as “the ability to search, find, understand, and evaluate health information from electronic sources and apply the knowledge acquired to address or deal with health problems” [⁷]. In 2006, the authors published the first scale to measure this construct - the eHealth Literacy Scale (eHEALS) [⁷].

Digital health literacy (DHL) emerged as a field of study and knowledge from eHealth literacy, defined as “the ability to appraise health information from electronic sources and apply this knowledge to address or solve a health-related problem and as such has emerged as an important component of greater health literacy” [⁸].

In dentistry, DHL implies the ability to navigate the vast sources of information available on the internet, evaluate the quality and relevance of this information and apply it effectively to restore and maintain good oral health. Its relevance is indisputable, since oral health plays a crucial role in people’s general health [⁹]. Moreover, as the amount of oral health information available online continues to grow, we need to assess people’s competence in understanding and using this information effectively [¹⁰].

The COVID-19 pandemic boosted the search for health-related information online and teleconsultation services, aiming to reduce the flow of unnecessary patient referrals to health units, and to reach populations distant from diagnostic and therapeutic centers [⁸-¹⁰]. Before this digital health transformation, DHL is not only relevant for patients, but also for dentistry teams who need to be up-to-date with scientific evidence to correctly advise clients about their oral health and to offer them the best evidence-based treatment options [¹¹]. Thus, digital health literacy is an essential facet of modern dentistry and requires continuous attention from health professionals and institutions to promote equitable access to quality information and effective oral care [¹¹].

Health students often see themselves as health educators, which requires skills to search for health information online and verify its accuracy [¹]. This fact demands restructuring the curriculum of undergraduate dentistry courses to offer greater opportunities for accessing digital platforms with high-quality scientific content and developing adequate digital skills to use them in assisting their patients in the search for reliable information [¹²]. Besides, developing DHL-related competencies can empower dentinstry students to work in an increasingly digital health system.

This study identifies and discusses the current knowledge on Digital Health Literacy (DHL) in dentistry to examine the state of the art on this topic and contribute to a more comprehensive understanding of this emerging field.

Material and Methods

The adopted methodology followed the guidelines of the Joanna Briggs Institute [¹³] and used the PRISMA-ScR checklist (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) to report the results [¹⁴].

Guiding Question

To address the objective of this study, we conducted a critical literature review guided by the following question: What is the current state of the art regarding digital health literacy in the dental context?

Search Strategy

The bibliographic search was conducted according to the methodological process recommended by the Joanna Briggs Institute, structured in three stages: (1) Initial identification of relevant studies: we carried out a preliminary search in the PubMed database using the terms health literacy, digital health literacy and oral health. In this stage, we examined titles, abstracts, and indexed terms to refine and validate the search strategy. (2) Expanded electronic search: we conducted a comprehensive search in the PubMed, Web of Science, and LILACS (Latin American and Caribbean Literature on Health Sciences Database) databases, using search terms in Portuguese, English, and Spanish, as well as MeSH and DeCS descriptors. The terms used included: health literacy, digital health literacy, eHealth literacy, eHealth, oral health, eHEALS, “letramento em saúde”, “saúde digital”, “alfabetización en salud”, “salud digital”, and “salud buccal”. The advanced trilingual search strategy was designed in alignment with the objective of this review and combined terms using the Boolean operators “OR” and “AND” (Table 1). Gray literature search: additional searches were conducted in Google Scholar to identify potentially relevant articles not indexed in the consulted databases.

Table 1
Full search strategy.

Databases	Keywords
PubMed/Medline	("Digital Health"[All Fields] OR “Salud Digital"[All Fields] OR ("Digital Health"[Title/Abstract] OR “Digital Health Technologies"[Title/Abstract] OR “Digital Health Technology"[Title/Abstract] OR “health digital"[Title/Abstract] OR “Salud Digital"[Title/Abstract] OR “Saude Digital"[Title/Abstract] OR “eHealth"[Title/Abstract] OR “Health 2.0"[Title/Abstract] OR “Medicine 2.0"[Title/Abstract] OR “mHealth"[Title/Abstract] OR “mHealth Alliance"[Title/Abstract] OR “Mobile Health"[Title/Abstract] OR “eSalud"[Title/Abstract] OR “mSalud"[Title/Abstract] OR “Salud 2.0"[Title/Abstract] OR “e-Saude"[Title/Abstract] OR “eSaude"[Title/Abstract])) AND ("Oral Health"[Title/Abstract] OR “health oral"[Title/Abstract] OR “Salud Bucal"[Title/Abstract] OR “Saude Bucal"[Title/Abstract] OR ("Oral Health"[All Fields] OR “Salud Bucal"[All Fields]))
LILACS	("Oral Health” OR “Health, Oral” OR “Salud Bucal” OR “Saúde Bucal” OR mh:("Oral Health") AND instance:"lilacsplus” AND instance:"lilacsplus") AND ("Digital Health” OR “Digital Health Technologies” OR “Digital Health Technology” OR “Health Technologies, Digital” OR “Health Technology, Digital” OR “Health, Digital” OR “Salud Digital” OR “Tecnología de Salud Digital” OR “Saúde Digital” OR “Tecnologia de Saúde Digital” OR “Tecnologia Digital para Saúde” OR “eHealth” OR “Health 2.0” OR “Medicine 2.0” OR “mHealth” OR “mHealth Alliance” OR “Mobile Health” OR “eSalud” OR “Medicina 2.0” OR “mSalud” OR “Salud 2.0” OR “e-Saúde” OR “eSaúde” OR “Medicina 2.0” OR “Medicina Virtual” OR “mSaúde” OR “Saúde 2.0” OR “Saúde Móvel” OR mh:("Digital Health") AND instance:"lilacsplus” AND instance:"lilacsplus") OR ("Digital Health Literacy” OR “Letramento Digital em Saúde” OR “eHEALS “ OR “Health Literacy” OR “Literacy, Health” OR “Alfabetización en Salud” OR “Letramento em Saúde” OR mh:("Health Literacy") AND instance:"lilacsplus” AND instance:"lilacsplus") AND instance:"lilacsplus
Web of Science	((#1) OR #2) AND #3 #1: ALL=(“Digital Health Literacy” OR “Letramento Digital em Saúde” OR “eHEALS “ OR “Health Literacy” OR “Literacy, Health” OR “Alfabetización en Salud” OR “Letramento em Saúde”) #2: ALL=(“Digital Health” OR “Digital Health Technologies” OR “Digital Health Technology” OR “Health Technologies, Digital” OR “Health Technology, Digital” OR “Health, Digital” OR “Salud Digital” OR “Tecnología de Salud Digital” OR “Saúde Digital” OR “Tecnologia de Saúde Digital” OR “Tecnologia Digital para Saúde” OR “eHealth” OR “Health 2.0” OR “Medicine 2.0” OR “mHealth” OR “mHealth Alliance” OR “Mobile Health” OR “eSalud” OR “Medicina 2.0” OR “mSalud” OR “Salud 2.0” OR “e-Saúde” OR “eSaúde” OR “Medicina 2.0” OR “Medicina Virtual” OR “mSaúde” OR “Saúde 2.0” OR “Saúde Móvel”) #3: ALL=(“Oral Health” OR “Health, Oral” OR “Salud Bucal” OR “Saúde Bucal”)
Google Schoolar	“Digital Health Literacy” OR “Digital Health” AND “Oral health”

Eligibility Criteria

Studies published up to February 2025 were considered eligible. We included only peer-reviewed, full-text articles that investigated digital health literacy (DHL) in dentistry. No restrictions were placed on study design, provided the topic aligned with the review objective.

Study Selection

Study selection was carried out in three stages: (1) database searches according to the final strategy (Table 1); (2) screening of titles and abstracts to remove clearly irrelevant studies; and (3) full-text reading to assess eligibility against the inclusion criteria.

Review Process

The entire process of searching, selecting eligible articles, and extracting data was performed by two trained and calibrated reviewers, with the support of a librarian from the institution. In cases of disagreement between reviewers, a third evaluator was consulted, and final decisions were reached after team discussion.

Data Extraction

After screening titles and abstracts, the articles were organized in a Microsoft Excel^® spreadsheet containing information on year of publication, objectives, methods, and main findings/conclusions. Based on this systematization, we excluded studies that were unrelated to the scope of the review. Screening and selection were carried out independently by the reviewers, considering the relevance of each article after detailed evaluation of its methodology, results, and conclusions.

Results

A total of 1855 articles were identified through database searching: 230 from PubMed, 758 from Web of Science and 867 from LILACS. Based on the inclusion criteria adopted, 1639 articles were excluded after reading the titles and abstracts, and one article was excluded after reading the full text. In the end, seven articles were selected for review, the oldest being published in 2015 and the most recent in 2025. After an additional search conducted on Google Scholar, eight new articles were included. Then, 15 articles were selected for qualitative synthesis [¹⁰,¹¹,¹⁵-²⁷] (Figure 1).

Figure 1
Flow chart of the main stages of the integrative review.

General characteristics of the articles identified were recorded in table format documenting author names/year, country of study, aims/objective, instruments/methods and results/conclusion (Table 2).

Table 2
Summary of relevant studies selected for review.

Author, Year and Country	Objectives	Methods/Instruments	Main Findings	Conclusions
Valizadeh-Haghi and Rahmatizadeh (2018), Iran [10]	To describe the importance and benefits of access to eHealth information resources from the perspective of dental patients; determine the eHealth literacy of dental patients; to identify factors that affect eHealth literacy.	Sample of 171 adult patients from a private clinic with dental diseases. The eHEALS instrument was used to measure eHealth literacy and a sociodemographic questionnaire was applied. The association of age, gender and schooling with eHEALS scores was assessed.	Average eHEALS score was 30.55. Age was the only sociodemographic variable associated with eHEALS scores. There was a significant correlation between total eHEALS scores and the importance of accessing eHealth information (r=0.33, p<0.001).	The dental patients in the sample had a high level of eHealth literacy. Dental institutions should focus on increasing awareness about the quality of online health information and encouraging patients to use evaluation tools, especially those with low eHealth literacy.
Hakeem et al. (2023), Saudi Arabia [11]	To investigate the association between eHealth literacy and the number of teeth and brushing frequency in a sample of patients attended at the Taibah University College of Dentistry Hospital in Madinah, Saudi Arabia.	Sample of 478 participants over 18 years old. Demographic variables were collected, including age, gender, income and schooling. eHEALS was used to measure DHL. The number of teeth was clinically assessed according to the DMFT index, and brushing frequency was assessed using a self-administered questionnaire.	Older male individuals, with low levels of education and income, and with less brushing frequency, were associated with inadequate eHealth literacy levels compared with groups classified as problematic and sufficient eHealth Literacy. Participants with better eHealth literacy had a significantly higher average number of teeth compared to those with inadequate eHealth literacy.	There was a positive association between eHealth literacy levels and oral health outcomes. Improving eHealth literacy levels may help promote better oral health behaviors and outcomes.
Hanna et al. (2017), Australia [15]	To explore online information-seeking behavior among patients with third molars (TM) and whether patients’ TM knowledge is associated with their level of internet use and eHEALS scores.	Sample composed of 165 adult dental patients referred by their dentists to the Department of Oral and Maxillofacial Surgery at Adelaide Dental Hospital. A sociodemographic questionnaire, the eHEALS scale, the Control Preferences Scale (CPS), which measure the preferred role of patient in making a dental treatment choice, and the online dental procedural information seeking (POIQ) scale were applied. Information about internet access status and TM knowledge among TM online information seekers were obtained.	There was no statistically significant association between internet access and online search for information about dental procedures. However, there was an association between seeking online dental information and a more active role in making a dental treatment choice (CPS scores). There was a positive, strong and significant correlation between eHEALS and POIQ scores. TM knowledge scores were not associated with either the level of internet use or the eHEALS scores.	Different levels of internet use for dental procedural information was not significantly associated with TM knowledge. Online dental procedural information seekers were unable to recognize online health information quality which may limit their ability to identify high-quality online health information.
Baek et al. (2021), Brazil [16]	To examine the validity and reliability of the Brazilian eHEALS (BR-eHeals) in a sample of patients treated at a public university dental clinic.	Sample of 132 adults over 18 years old. eHEALS scale was applied in the waiting room of a dental environment. Sociodemographic data and information on internet use were also collected.	The 1-factor model presented adequate fit, good internal fit, reliability and convergent validity. Configurational invariance was found for gender, schooling and age groups. Both age and schooling were strong predictors of eHEALS factor scores. Scalar invariance was observed for gender and age, while partial scalar invariance was confirmed for schooling.	The instrument provided reliable estimates when used in dental settings. The instrument was able to discriminate eHealth literacy levels between different age groups and schooling levels.
Kim and Lim (2022), South Korea [17]	To identify new variables that can promote oral health behaviors in adults by exploring the level of e-health literacy, oral health knowledge, and oral health behavior, and to provide fundamental data for effective strategy development.	Sample of 312 individuals, men and women aged 19 years or older. An instrument with 77 questions was used: 15 items on sociodemographic characteristics; 31 items on eHealth literacy, using the eHealth Literacy Scale instrument developed by Lee (2011); 18 items on oral health knowledge, with questions related to teeth, periodontium, and oral hygiene product; and 13 items on oral health behaviors, with questions related to dietary habits, use of oral hygiene products, regular dental check-ups, and smoking	Women, those with higher education levels and those who visited a dental clinic within the past year had higher scores in oral health behavior (better behaviors). Self-perceived oral health status and interest in oral health were associated with higher behavior scores. Using the internet for oral health information more frequently and perceiving internet information as reliable were also linked to higher health behavior scores. Higher eHealth literacy was associated with increased oral health behavior.	Oral health behaviors showed significant differences for gender, schooling, experience of visiting a dental clinic within the last year, self-perceived oral health status, interest in oral health, frequency of internet use for oral health-related matters, and reliability on internet oral health information. eHealth literacy was a factor that affected oral health behavior.
Chen et al., (2023), USA [18]	To assess individuals’ health literacy skills from a multidimensional theory-based perspective using both subjective and objective measures and to examine the relationship between health literacy and preventive care use in a sample of university students.	A sample of 561 university students from Oklahoma State University participated in the study. Sociodemographic data were collected. The Behavioral Risk Factor Surveillance System (BRFSS) questionnaire and the National College Health Assessment (NCHA) survey were used to measure participants’ use of preventive care. Health Insurance Literacy Measure (HILM), eHealth Literacy Scale (eHEALS), Aspect of Health Literacy Scale (AAHLS), and the Newest Vital Sign (NVS) were used to assess health literacy.	Average scores were 64.80 for HILM, 32.04 for eHEALS, 26.49 for AAHLS, and 5.22 for NVS. Individuals with better self-perceived health were more likely to use preventive care, such as annual dental checkups. Higher scores on HILM, eHEALS, AAHLS, and NVS were associated with a higher likelihood of using various types of preventive care, such as physical exams, blood pressure checks, cholesterol level tests, as well as annual flu vaccinations.	Health literacy played an important role among the relationship of individual preventive care use, age, schooling, gender, race/ethnicity, health insurance coverage, and self-rated health status, influencing the use of preventive care.
Iyer and Sethuraman (2024), India [19]	To evaluate the relationship between eHealth literacy, learning styles, and access to web-based electronic content for accessing health information for dental students in Vadodara, Gujarat, India.	Sample of 285 undergraduate students, interns, and graduate dental students. eHealth literacy levels were measured using the eHealth Literacy Scale (eHEALS). Learning styles were assessed by the Visual Aural Read/Write Kinesthetic (VARK) Questionnaire version 8.01. Data on the use of web-based electronic resources to access health information was collected using a questionnaire.	Average eHEALS score was 30.2. There was no statistically significant difference in eHEALS scores among predominantly visual, auditory, reading/writing, and kinesthetic learners. There was a statistically significant association between the preferred use of video demonstration content and being a kinesthetic learner for accessing health information.	Participants were multimodal learners, predominantly kinesthetic. No statistically significant difference was observed in eHealth literacy between students with different learning styles.
Lotto et al. (2023), Brazil [20]	To conduct a cross-cultural adaptation and validation of the eHealth Literacy Scale (eHEALS) into Brazilian Portuguese and its associations with oral health-related quality of life among Brazilian undergraduate students.	Sample of 521 undergraduate students from distinct programs (health sciences, including dentistry and others) of two Brazilian Universities. Cross-cultural adaptation was performed by conceptual equivalence, literal translation, semantic and operational equivalence of items, and back-translation. The eHEALS, General Perceived Self-Efficacy Scale (GSES) and Oral Health Impact Profile-14 (OHIP-14) instruments were applied, in addition to a sociodemographic questionnaire.	Mean score of the eHEALS was 28.0. The instrument showed excellent internal consistency, good stability and was significantly correlated with the GSES. Higher eHEALS scores were identified among younger white health sciences students who had visited a dentist in the last 2 years. eHEALS scores showed significant positive association with health information-seeking behavior in the last 24 h.	The Brazilian version of eHEALS presented adequate psychometric properties to determine the eHealth literacy levels of undergraduate students, being an adequate predictive factor of health information-seeking behavior.
de Oliveira Collet et al. (2024), Brazil [21]	To assess whether Brazilian adults with higher levels of digital health literacy are less susceptible to the influence of the internet on their oral health-related behaviors.	Sample of 418 Brazilian adults, including graduate students and patients from the Dental Clinic of the State University of Maringá, participated in the study. They completed an online questionnaire via Google Forms, which included the eHEALS scale, items on how they seek health and oral health information online, their behaviors regarding this information, and sociodemographic and economic questions.	85.2% of participants accessed the internet via mobile device, and 70.8% sought health information before consulting a professional. 42% researched dental diagnoses/treatments, 46% checked the dentist's social media before appointments, and 38.8% reported self-medication based on online information. 22% used products recommended by influencers. The mean eHEALS score was 27.8 ± 8.13. Higher eHEALS scores were associated with higher education and income, less influence from influencers, and a lower likelihood of ignoring medical recommendations. Logistic regression showed that increased eHEALS scores were associated with reduced consumption of products endorsed by digital influencers.	Higher income and education were associated with higher digital health literacy. Individuals with higher eHEALS scores tend to search more for health information online, including dental diagnoses and procedures, and check dentists' profiles before appointments. Additionally, they are more likely to trust healthcare professionals, being less influenced by online information and digital influencers. These individuals demonstrate greater critical thinking when evaluating online content, reducing the likelihood of disregarding professional guidance.
Lotto et al. (2020), Brazil [22]	To evaluate the effectiveness of educational text messages on oral health in controlling early childhood caries (ECC) among children from low socioeconomic backgrounds and in improving the digital health literacy levels of their parents or caregivers, considering caries experience, the presence of dental biofilm, and dietary habits.	Sample of 104 dyads (parents/caregivers and children) was allocated into intervention and control groups (1:1), stratified by eHEALS scores (parents) and ICDAS scores (children). This was a single-blind, randomized controlled trial. The intervention involved biweekly educational messages via WhatsApp and audio narrations on ECC management. Children were assessed using ICDAS and the visible plaque index (VPI) at baseline, 3, and 6 months. Parents completed the eHEALS and a dietary questionnaire at baseline and after 6 months. The follow-up lasted 6 months, and the groups were compared based on the studied variables.	The groups were statistically similar at baseline. The mean eHEALS score was 24.5 ± 8.5 (control group), 24.0 ± 8.1 (intervention group), and 24.3 ± 8.3 overall. Clinical outcomes remained comparable over time; however, the increase in maximum ICDAS was significant in the control group (P = 0.008) but not in the intervention group. The increase in VPI in the intervention group at 3 months did not persist. The eHEALS score increased significantly in the intervention group (+10.32%, P = 0.001), especially among more engaged parents (+14.11%). Intervention participants reported higher consumption of sugar-free sweets. Sensitivity analysis showed variations of up to 27.61% for eHEALS and a trend toward a greater difference between the intervention and control groups.	The educational strategy increased the digital health literacy of parents or caregivers, influencing reported changes in the sugar consumption patterns of preschool-aged children. Additionally, the text messages sent to parents or caregivers proved to be effective in controlling the severity of childhood caries in preschoolers from low socioeconomic backgrounds and with low digital health literacy levels.
Trantali et al. (2022), Greece [23]	To examine the level of eHealth literacy perceived by health sciences students in Greece.	Sample of 113 undergraduate health sciences students (Medicine & Dentistry, Pharmacy, Public & Community Health, Other Health & Care Sciences) over 18 years old. Data were collected using Google Forms by a sociodemographic questionnaire and the eHEALS scale.	Participants’ average eHEALS score was 31.9, with medical and dental students having the highest score (33.7) and other health and care sciences students having the lowest score (29.8), with a statistically significant difference in eHEALS scores between University Departments (p=0.009).	University departments can develop curricula that focus on developing practical eHealth literacy and critical thinking skills to educate future health sciences professionals.
Yilmazel (2023), Turkey [24]	To explore the relationships between eHealth literacy, health promotion activities, and preventive health practices to understand the factors influencing adolescents’ health behaviors and information-seeking habits.	Sample of 706 adolescents aged 14 to 19 years. Sociodemographic characteristics (age, gender, parents’ schooling, place of residence, income level, satisfaction with health, chronic conditions, and preferred health service) were collected by a questionnaire. The eHealth Literacy Scale (eHEALS) was used to measure the level of eHealth literacy, and the Adolescent Health Promotion Scale (AHPS) was used to assess adolescents’ preventive health practices.	54.8% of the participants had a high level of eHealth literacy, with an average eHEALS score of 29.40. 51.3% had a high level of health promotion practices, including no alcohol consumption and no smoking; had their annual weight, blood pressure, cholesterol measured; annual dental examination, and regular exercise rate. There was a positive significant correlation between eHealth literacy and AHPS, and between AHPS subscales and eHealth literacy. Higher eHealth literacy increased annual dental examination.	eHealth literacy affected both health promotion and preventive health practices for adolescents, including annual dental examination.
Zaberi et al., (2022), Malaysia [25]	To determine the online health information-seeking behavior, eHealth literacy and factors associated with eHealth literacy for dental auxiliary personnel in Pahang, to determine if this group is prepared to educate their patients appropriately.	Sample of 456 dental auxiliary personnel (dental therapists, dental technologists, and dental surgery assistants). Two questionnaires were used: one with questions related to sociodemographic data, internet access and use, online health information-seeking behavior, and self-perceived health status; and another one with the eHealth Literacy Scale (eHEALS) instrument.	About 91.2% of the subjects were classified as having good eHealth literacy. Average Health literacy level was 30.5. The eHealth literacy score was higher for dental therapists compared to dental surgery assistants. The factors significantly associated with good eHealth literacy were: frequently searching the internet for health information, self-perceived had good health and self-perceived good oral health.	The proportion of the sample with good eHealth literacy was high and was associated to perceptions about their own overall and dental health.
Al-yaseen et al., (2024), United Kingdom [26]	To co-design the prototype of an app called App for Children’s Teeth with parents, providing them with a source of information on how to care for their children’s teeth and promote positive dental habits.	Sample of 10 parents or caregivers of children aged ≤6 years (aged ≥18 years). The eHealth Literacy Scale (eHEALS) was used to diagnose their digital HL levels to develop an app, that can be more appropriate, accessible, and user-friendly. A structured interview using the “Think Aloud” method was conducted where participants navigated through the app prototype while expressing their thoughts and perceptions aloud, along with questions based on the Theoretical Framework of Acceptability (TFA).	According to eHEALS responses, 78% of participants judged the internet as useful or very useful in helping them make health decisions, and 89% felt it was important or very important for them to be able to access health resources on the internet. Based on parents’ opinions and their suggestions for content and design, and eHEALS responses, a prototype app called App for Children’s Teeth (ACT) was developed. Parents judged the structure to be appropriate to their suggestions, simple, and easy to navigate and use.	Incorporation of theoretical framework, user participation in the design process, and emphasis on simplicity and user-friendly interface were identified as key factors contributing to the success of the intervention. eHEALS was an important tool to understand parents’ needs with the eHealth field, and the overall high levels of eHEALS demonstrated that they were in a good position to help inform the development of the prototype and comment about it.
Barbosa et al. (2024), Brazil [27]	To assess the psychometric properties of the adapted version of the eHealth Literacy Scale (eHEALS-BrA) for Brazilian adolescents, and to evaluate differences in their scores according to several variables, including self-perception of oral health.	Sample of of 260 Brazilian adolescents aged 13 to 19 years old from five public schools conveniently selected in Belo Horizonte, Minas Gerais, Brazil. The adapted version of eHEALS for adolescentes was applied, analysing the following variables: sociodemographic characteristics, the WHOQOL-Bref instrument, information about general health, internet access, self-assessment of skills related to using the internet, search behavior for health information and a question about self-rated oral health.	The mean age of the sample was 15.63 years old. The instrument demonstrated good reliability and satisfactory internal consistency. The eHEALS-BrA was correlated with the physical, psychological, and environmental domains of the WHOQOL-Bref. Higher scores of eHEALS-BrA were found among male adolescents, individuals who practiced physical activity, those with better self-rated health, those who considered the internet useful for searching for health information and those with better self-rated skills related to using the internet. No differences were found in the instrument scores regarding the dental variable.	The instrument eHEALS-BrA presented adequate psychometric properties for measuring digital health literacy in the sample of Brazilian adolescents evaluated in the study.

Regarding the instruments used to measure DHL in the selected studies, thirteen articles used the eHEALS scale [¹⁰,¹¹,¹⁵, ¹⁶,¹⁸-²⁶], and the average scores ranging from 26.2 [¹⁵] to 32.04 [¹⁸], considering that its final score ranges from 8 to 40. The study conducted by Hakeem et al. [¹¹] provided no average score for the eHEALS responses. Instead, the authors classified participants according to their scores into following categories: inadequate (8-20 points), problematic (21-26 points), and sufficient (27-40 points), citing Norman and Skinner [⁷]; however, these criteria were not used in the original study [⁷]. Baek et al. [¹⁶] also failed to provide a global score for the instrument. In addition, the study by Al-Yaseen et al. [²⁶] only showed the percentage of parents who agreed with the positive statements of eHEALS.

Two other instruments were used to measure DHL in the selected studies. Kim and Lim [¹⁷] used the eHealth Literacy (EHS) tool, developed by Lee [²⁸] to evaluate associations with oral health outcomes in a sample of Korean adults. The instrument was composed of 31 items with three factors: functional eHealth Literacy, communicative eHealth Literacy and critical eHealth Literacy. Barbosa et al. [²⁷] adapted the eHEALS instrument for the adolescent population in Brazil (eHEALS-BrA) and applied it to a sample involving a total of 260 adolescents aged 13 to 19, with a mean age of 15.64 years. The mean eHEALS-BrA score showed no statistically significant differences (p=0.582) across the different levels of self-perceived oral health.

Most studies were conducted with samples of undergraduate health science students (including dentistry students) and adults who sought treatment in public and private dental clinics. Five studies were conducted with adolescents, dental auxiliary personnel, and children’s parents [²²,²⁴-²⁶,²⁷]. Five studies were conducted in Brazil [¹⁶,²⁰,²¹,²²,²⁷]. Some studies evaluated DHL as an outcome [¹⁰,¹⁶,¹⁹,²²,²³,²⁵,²⁷], and others evaluated DHL as a predictor variable of oral health outcomes [¹¹,¹⁵,¹⁷,¹⁸,²¹,²⁴,²⁶] or both [²⁰].

Discussion

The scientific literature on DHL has grown considerably in recent decades, reflecting the growing importance of Information and Communication Technologies (ICTs) in the health sector [³,¹²]. However, the present study identified only fifteen articles published until early 2025 that addressed DHL in dentistry using validated instruments to measure this construct, and related to variables in the dental field, such as dental students or patients of dental clinics, health promotion interventions in the dental field, or associations with oral outcomes. The results indicated that the relationships between digital literacy, oral health, and health literacy remain notably little explored.

Most of the reviewed studies investigated adult populations using dental services in the public and private sectors [¹⁰,¹¹,¹⁵-¹⁷,²¹] and university students from health courses, including dentistry [¹⁸-²⁰,²³]. Adolescents, dental auxiliary staff and parents or caregivers of children were also studied, but in reduced numbers [²²,²⁴-²⁶,²⁷]. These findings suggest the need to expand the studied populations to include other demographic groups such as children, pregnant women and older adults for a more comprehensive understanding of DHL and its impact on their oral health. We highlight the importance of investigations on the applicability of available instruments and new ones to assess DHL in specific populations and contexts [²⁷,²⁹]. It is crucial to develop valid instruments tailored to different age groups, such as children, adolescents, and older adults, as well as for groups under specific conditions and contexts, such as pregnant women and immigrants, because most studies with these groups only adapted and applied older eHealth Literacy instruments and no new instruments were developed to validate the DHL specifically in each group, nor in the current context of new demands for DHL [³⁰].

Regarding the geographic distribution, the selected studies were conducted in India, Turkey, Malaysia, United Kingdom, United States, South Korea, Saudi Arabia, Greece, Iraq, Australia, and five studies in Brazil. Thus, Brazil is the country that published a significant portion of studies on the subject with intersections with the dental area until the beginning of 2025, indicating the interest of researchers in the subject and the potential for advancement in this area. Research conducted in Brazil has validated eHEALS for different population groups: undergraduate students [²⁰], adolescents [²⁷], and adults [³¹]. Additionally, the Digital Health Literacy Instrument (DHLI-BrA) was adapted specifically for adolescents [²⁹].

As for objectives, the reviewed studies sought to evaluate the psychometric properties of eHEALS in dental patients and dentistry students [¹⁶,¹⁹,²⁰,²³]; to investigate variables associated with eHEALS scores [¹⁰,¹⁶,¹⁹-²¹,²⁵] in the dental context; to explore eHealth literacy levels as predictor of health outcomes such as preventive dental care utilization [¹⁸], oral health behaviors [¹¹,¹⁷], oral health status [¹¹,¹⁷], to control the severity of Early Childhood Caries (ECC) inlowsocioeconomic status preschoolers [²²]; and eHealth information [¹⁰,²⁰]. A study used the eHEALS scores of parents to help researchers design a mHealth prototype to improve preschool oral health [²⁶]. eHEALS presented good psychometric properties with a sample of dental patients and undergraduate health courses students [¹⁶,²⁰].

Regarding the variables associated with eHEALS scores, Lotto et al. [²⁰] identified higher scale scores among younger white undergraduate students from health sciences courses, with more years of graduation, whose fathers worked in specialized functions, and among those who were frequently interested in digital health information. As for dental patients, Baek et al. [¹⁶] found that participants aged 18 to 45 years and those with higher schooling presented greater means for eHEALS subscales. Valizadeh-Haghi and Rahmatizadeh [¹⁰] noted that participant age has a significant effect on eHealth literacy levels. In a study with dental auxiliary personnel, Zaberi et al. [²⁵] verified that searching the internet for health information, self-perceived good health and self-perceived good oral health were variables frequently associated with better eHEALS scores. eHEALS scores were not associated with the learning style of undergraduate and graduate students from a dental college in Vadodara, India [¹⁹]. Yilmazel [²⁴] verified that 27% of the eHEALS variance were explained by variables related to health promotion activities and preventive health practices, including annual weight measurement, annual dental examination, annual blood glucose measurement, no tobacco and no alcohol use.

The findings of de Oliveira Collet et al. [²¹] complement previous studies on the factors associated with digital health literacy and their implications in dentistry. The study conducted with Brazilian adults highlights that individuals with higher income and education levels tend to have greater digital health literacy. Moreover, the researchers observed that higher eHEALS scores are associated with lower susceptibility to online influence. These findings underscore the importance of digital health literacy not only in the adoption of healthy behaviors but also in individuals' critical ability to evaluate online oral health information [²¹].

Thus, DHL levels in the samples in the aforementioned studies were influenced by age, schooling level, information internet searching, self-perceived health and health preventive behaviors, revealing the complexity and interconnection of this construct with several variables and highlighting the importance of integrated approaches in promoting DHL in dentistry.

Some studies investigated eHealth literacy as a predictor variable for dental outcomes. Hanna et al. [¹⁵] explored online information seeking behavior among third molars patients served by public dental services and identified associations between eHEALS scores and the Perceived Online Information Quality (POIQ) scale, developed to assess participants’ perceptions about the reviewed online information regarding its trustworthiness, readability, usefulness, understandability and overall quality. Similarly, Valizadeh-Haghi and Rahmatizadeh [¹⁰] found a significant correlation between total eHEALS scores and the importance of accessing eHealth information among patients with oral problems. Hakeem et al. [¹¹] investigated the association between eHEALS scores and the number of teeth and brushing frequency in patients aged 18 years and older who sought dental treatment at the Taibah University College of Dentistry Hospital in Madinah, Saudi Arabia.

While Hanna et al. [¹⁵], Valizadeh-Haghi and Rahmatizadeh [¹⁰], and Hakeem et al. [¹¹] examined eHEALS scores in relation to trust in online information, access to eHealth resources, and oral hygiene practices, respectively, Lotto et al. [²⁰] demonstrated that an increase in eHEALS scores among parents of young children was associated with better control of early childhood caries (ECC). Moreover, the study highlighted that digital interventions, such as educational messages via WhatsApp, can enhance both parental eHealth literacy and children's dietary habits, contributing to caries prevention. These findings highlight the importance of eHealth literacy as a key factor influencing oral health behaviors and outcomes [²²].

Higher eHEALS scores were associated with a greater number of teeth and better brushing frequency [¹¹]. Kim and Lim [¹⁷] investigated variables that can promote oral health behaviors among adults in Korea, including DHL and oral health knowledge. A convenience sample of 350 adults answered an eHealth literacy tool developed by Lee [²⁷] and other questionnaires. Their analysis showed that gender, educational background, experience visiting a dental clinic within one year, self-perceived oral health status, and eHealth literacy levels were associated with better oral health behaviors [³⁰]. Iyer and Sethuraman [¹⁹] conducted a study with dental students in Vadodara, India, to investigate the relation between dental students’ eHealth literacy, learning styles, and web based e content used for receiving health information. Chen et al. [¹⁸] examined the role of health literacy, eHealth literacy and other variables on preventive care among college students in land-grant university situated in a rural county in north-central Oklahoma, US. Higher eHEALS scores were significantly associated with a greater number of preventive care services received by students such as physical examinations, blood pressure checks, blood tests for cholesterol and dental checks. Finally, Zaberi et al. [²⁵] investigated the association of eHEALS scores with other variables in a sample of dental auxiliary personnel working in government dental clinics in Pahang, Malaysia. They found significant positive associations of eHEALS scores with regularly accessing health information platforms and frequently using the internet to search for health information. Jointly, the findings of these articles indicated associations between eHealth literacy and oral health outcomes; thus, improving DHL may have implications for promoting better oral health behaviors and outcomes.

As observed above, the main instrument used to measure DHL in the selected studies was the eHEALS scale and its adaptations, except for Kim and Lim [¹⁷], who used another instrument published in a Korean thesis [²⁸]. eHEALS is an 8-item questionnaire developed to determine individuals’ ability to access digital resources and focus on perceived knowledge of how to use the Internet to find resources, evaluate the quality of said resources, and translate this knowledge into practice [⁷]. Although originally tested on teenagers, the instrument has been evaluated for validity in multiple languages and has been shown to work consistently across diverse population groups [³¹,³²]. Despite its qualities as a short and easy-to-apply questionnaire, it does not provide a definitive assessment of digital health literacy since it is a self-report metric, in which quality of assessment is limited by the confidence of the respondent to evaluate their own capabilities [³²,³³]. Without any objective test to confirm their judgment, the instrument may not represent the individual’s real abilities due to possible gaps between self-perception and the actual skills in using digital health resources. Hence, this could be the focus of investigation for instruments to be constructed in the future. It would therefore be inappropriate to use eHEALS as a means to accurately and objectively assess digital health literacy as a measure or standard of ability needed to interact with resources [³³].

Another limiting factor is that eHEALS lack properties to assess skills related to the appropriate use of Web 2.0, since it was developed before the advent of social media [³⁴]. According to Griebel et al. [³⁵], the skills measured by eHEALS have not changed over time but the context in which they are needed has gained another dynamic related to social media and mHealth. As such, future studies on DHL and dentistry should use more comprehensive instruments to increase researchers’ understanding of the associations between variables in the context of Web 2.0, like the Digital Health Literacy Instrument (DHLI) [³⁶], a tool developed to assess Health 1.0 and Health 2.0 skills using self-reporting and performance-based items. It evaluates six skills related to digital health literacy. Other instruments were developed for measuring DHL, such as transactional eHealth literacy instrument (TeHLI) and the eHealth literacy assessment toolkit (eHLA), however, the quality of evidence about their psychometric properties to measure the construct of DHL is low or moderate [³³], a fact that may have implications for the validity of the associations found in future studies. Another important aspect to be considered is that most of the instruments developed to measure DHL to date were developed based on conceptual frameworks from more than 10 years ago; therefore, their validity to the present day can be questioned. For example, the conceptual model of the eHEALS instrument was developed in 2006 and the one of DHLI in 2013 with patients with rheumatological problems [⁷,³⁶].

Considering the rapid development of digital health resources and the evolving digital demands of society, it is essential to conduct periodic qualitative research to assess the content validity of these instruments regarding societal needs over time. In this context, the study by Barbosa et al. [²⁹] included an adaptation of the Digital Health Literacy Instrument to enable its use via smartphones, as the original instrument was designed for computer use. The authors recognized the importance of this adaptation for the Brazilian context, where smartphones are the primary means of internet access, especially among adolescents [²⁹].

This review has some limitations. The restricted search strategy employed may have led to the exclusion of studies that would have met the established inclusion criteria in other databases such as Scopus, CINAHL, Embase. Moreover, the selected studies were all cross-sectional in design which does not allow the inference of cause-and-effect relations between variables. The heterogeneity in sample sizes and methodologies adopted also hindered comparing the studies.

Future research on digital health literacy in the field of oral health can expand our knowledge and guide future interventions. Increased efforts are needed to evaluate the effectiveness of digital health literacy interventions, exploring different approaches and comparing their impact on oral health outcomes. Developing longitudinal studies to assess long-term cause-and-effect relations and the effects of improved digital health literacy on oral health behaviors is essential. Robust investigations should be conducted using objective dental hygiene measures, such as plaque index, and correlating oral hygiene behaviors with digital health literacy levels. Addressing critical factors related to health inequities requires investigation into the influences of socioeconomic, environmental, and cultural factors on the relations between digital health literacy and oral health. Additionally, future qualitative research may help to advance knowledge of other DHL-associated characteristics in dentistry which were not covered by the instruments used in the reviewed studies. To date, there is no specific instrument to measure DHL in dentistry, and developing a specific instrument for this purpose may contribute to a greater understanding of the relation between DHL and oral health outcomes such as oral hygiene practices, prevention and management of dental diseases, access to dental care and patient-provider communication.

For now, patients should receive support and training in digital health literacy from healthcare professionals, especially regarding the quality of health information, so that they can adequately evaluate information found on the internet. Moreover, dental professionals must be prepared to discuss the questions raised by their patients about information obtained online.

Conclusion

This critical review found few articles published to date that specifically address digital health literacy in dentistry, indicating the need to further explore the topic. We identified gaps in digital health literacy research in dentistry and the need for further research in diverse sociodemographic groups and settings, to better understand the impact of digital health literacy on patients’ oral health.

• Financial Support
  None.

Data Availability

The data used to support the findings of this study can be made available upon request to the corresponding author.

References

• ^[1] World Health Organization, Global strategy on digital health 2020-2025. Geneva: World Health Organization; 2021. Available from: https://www.who.int/docs/default-source/documents/gs4dhdaa2a9f352b0445bafbc79ca799dce4d.pdf [Accessed on May 7, 2024].
  » https://www.who.int/docs/default-source/documents/gs4dhdaa2a9f352b0445bafbc79ca799dce4d.pdf
• ^[2] Digital around the World. DATAREPORTAL. Available from: https://datareportal.com/global-digital-overview [Accessed on May 5, 2024].
  » https://datareportal.com/global-digital-overview
• ^[3] World Health Organization. WHO guideline: Recommendations on digital interventions for health system strengthening. Geneva: World Health Organization, 2019. Available from: https://www.who.int/publications/i/item/9789241550505 [Accessed on May 7, 2024].
  » https://www.who.int/publications/i/item/9789241550505
• ^[4] What is digital health, eHealth, uHealth and Healthcare 4.0? Informatics and Health 2025; 2(2):137-142. https://doi.org/10.1016/j.infoh.2025.06.002
  » https://doi.org/10.1016/j.infoh.2025.06.002
• ^[5] Kickbusch I, Pelikan JM, Apfel F, Tsouros A. Health literacy: The solid facts. 2013. Available from: https://apps.who.int/iris/bitstream/handle/10665/128703/e96854.pdf [Accessed on April 7, 2024].
  » https://apps.who.int/iris/bitstream/handle/10665/128703/e96854.pdf
• ^[6] Norman CD, Skinner HA. eHealth literacy: Essential skills for consumer health in a networked world. J Med Internet Res 2006; 8(2):e9. https://doi.org/10.2196/jmir.8.2.e9
  » https://doi.org/10.2196/jmir.8.2.e9
• ^[7] Norman CD. Skinner HA. eHEALS: The eHealth literacy scale. J Med Internet Res 2006; 8(4):e27. https://doi.org/10.2196/jmir.8.4.e27
  » https://doi.org/10.2196/jmir.8.4.e27
• ^[8] Smith B, Magnani JW. New technologies, new disparities: The intersection of electronic health and digital health literacy. Int J Cardiol 2019; 292:280-282. https://doi.org/10.1016/j.ijcard.2019.05.066
  » https://doi.org/10.1016/j.ijcard.2019.05.066
• ^[9] Sabbah W, Folayan MO, El Tantawi M. The Link between Oral and General Health. Int J Dent 2019; 2019:7862923. https://doi.org/10.1155/2019/7862923
  » https://doi.org/10.1155/2019/7862923
• ^[10] Valizadeh-Haghi S, Rahmatizadeh S. eHealth literacy and general interest in using online health information: A survey among patients with dental diseases. Online J Public Health Inform 2018; 10(3):e219. https://doi.org/10.5210/ojphi.v10i3.9487
  » https://doi.org/10.5210/ojphi.v10i3.9487
• ^[11] Hakeem FF, Abdouh I, Hamadallah HH, Alarabi YO, Almuzaini AS, Abdullah MM, et al. The association between electronic health literacy and oral health outcomes among dental patients in Saudi Arabia: A cross-sectional study. Healthcare 2023; 11(12):1804. https://doi.org/10.3390/healthcare11121804
  » https://doi.org/10.3390/healthcare11121804
• ^[12] Arias López MDP, Ong BA, Borrat Frigola X, Fernández AL, Hicklent RS, Obeles AJT, et al. Digital literacy as a new determinant of health: A scoping review. PLOS Digital Health 2023; 2(10):e0000279. https://doi.org/10.1371/journal.pdig.0000279
  » https://doi.org/10.1371/journal.pdig.0000279
• ^[13] Peters MDJ, Godfrey C, McInerney P, Munn Z, Tricco AC, Khalil H. Scoping reviews. In: Aromataris E, Munn Z, editors. JBI Manual for Evidence Synthesis. Adelaide: JBI; 2020. Available from: https://synthesismanual.jbi.global [Accessed on August 12, 2025].
  » https://synthesismanual.jbi.global
• ^[14] Tricco AC, Lillie E, Zarin W, O'Brien KK, Colquhoun H, Levac D, et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and explanation. Ann Intern Med 2018; 169(7):467-473. https://doi.org/10.7326/M18-0850
  » https://doi.org/10.7326/M18-0850
• ^[15] Hanna K, Sambrook P, Armfield JM, Brennan DS. Internet use, online information seeking and knowledge among third molar patients attending public dental services. Aust Dent J 2017; 62(3):323-330. https://doi.org/10.1111/adj.12509
  » https://doi.org/10.1111/adj.12509
• ^[16] Baek JJH, Soares GH, da Rosa GC, Mialhe FL, Biazevic MGH, Michel-Crosato E. Network analysis and psychometric properties of the Brazilian version of the eHealth Literacy Scale in a dental clinic setting. Int J Med Inform 2021; 153:104532. https://doi.org/10.1016/j.ijmedinf.2021.104532
  » https://doi.org/10.1016/j.ijmedinf.2021.104532
• ^[17] Kim YS, Lim SR. Effects of e-health literacy and oral health knowledge on oral health behavior in adults. J Korean Soc Dent Hyg 2022; 22(1):11-19. https://doi.org/10.13065/jksdh.20220002
  » https://doi.org/10.13065/jksdh.20220002
• ^[18] Chen X, Luo G, Li M, Kreps G. Examining the relationship between health literacy and preventive care use. Health Behavior Res 2023; 6(4):1-19. https://doi.org/10.4148/2572-1836.1206
  » https://doi.org/10.4148/2572-1836.1206
• ^[19] Iyer RR, Sethuraman R. Role of ehealth literacy, learning styles, and patterns of web-based e-content access for seeking health information among dental university students in Vadodara, India. J Educ Health Promot 2024; 13:56. https://doi.org/10.4103/jehp.jehp_750_23
  » https://doi.org/10.4103/jehp.jehp_750_23
• ^[20] Lotto M, Maschio KF, Silva KK, Ayala Aguirre PE, Cruvinel A, Cruvinel T. eHEALS as a predictive factor of digital health information seeking behavior among Brazilian undergraduate students. Health Promot Int 2023; 38(4):daab182. https://doi.org/10.1093/heapro/daab182
  » https://doi.org/10.1093/heapro/daab182
• ^[21] de Oliveira Collet G, de Morais Ferreira F, Ceron DF, de Lourdes Calvo Fracasso M, Santin GC. Influence of digital health literacy on online health-related behaviors influenced by internet advertising. BMC Public Health 2024; 24(1):1949. https://doi.org/10.1186/s12889-024-19506-6
  » https://doi.org/10.1186/s12889-024-19506-6
• ^[22] Lotto M, Strieder AP, Ayala Aguirre PE, Oliveira TM, Andrade Moreira Machado MA, Rios D, et al. 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. https://doi.org/10.1016/j.jdent.2020.103456
  » https://doi.org/10.1016/j.jdent.2020.103456
• ^[23] Trantali T, Athanasopoulou C, Lagiou A, Sakellari E. eHealth literacy among health sciences students in Greece. Stud Health Technol Inform 2022; 289:252-255. https://doi.org/10.3233/SHTI210907
  » https://doi.org/10.3233/SHTI210907
• ^[24] Yilmazel G. Are health promotion activities and preventive health practices predictors of adolescent eHealth literacy? Health Promot Int 2023; 38(5):daad109. https://doi.org/10.1093/heapro/daad109
  » https://doi.org/10.1093/heapro/daad109
• ^[25] Nor AMN, Zaberi ZHS, Nazari NSM, Baharuddin NA. Internet use, online health information seeking behavior and electronic health literacy among dental auxiliary personnel in Malaysia. Southeast Asian J Trop Med Public Health 2022; 53(5):497-512.
• ^[26] Al-Yaseen W, Raggio DP, Araujo M, Innes N. "I Just Wanted a Dentist in My Phone" - Designing Evidence-Based mHealth Prototype to Improve Preschool Children's Oral and Dental Health: Multimethod study of the codevelopment of an app for children's teeth. JMIR Form Res 2024; 8:e49561. https://doi.org/10.2196/49561
  » https://doi.org/10.2196/49561
• ^[27] Barbosa MCF, Baldiotti ALP, Resende JL, Perazzo MF, Firmino RT, Granville-Garcia AF, et al. Assessment of the psychometric properties of the eHealth Literacy Scale for Brazilian adolescents. PLoS One 2024;19(11):e0314099. https://doi.org/10.1371/journal.pone
  » https://doi.org/10.1371/journal.pone
• ^[28] Lee SR. Ph.D. Thesis. The Graduate School of Hanyang University; Seoul, Republic of Korea. A Study for Developing eHealth Literacy Scale, 2018. Available from: https://hanyang.dcollection.net/public_resource/pdf/200000432020_20251229211846.pdf [Accessed on May 5, 2024].
  » https://hanyang.dcollection.net/public_resource/pdf/200000432020_20251229211846.pdf
• ^[29] Barbosa MCF, Baldiotti ALP, Braga NS, Lopes CT, Paiva SM, Granville-Garcia AF, et al. Cross-cultural adaptation of the Digital Health Literacy Instrument (DHLI) for use on Brazilian adolescents. Braz Dent J 2023; 34(5):104-114. https://doi.org/10.1590/0103-6440202305346
  » https://doi.org/10.1590/0103-6440202305346
• ^[30] Wang X, Luan W. Research progress on digital health literacy of older adults: A scoping review. Front Public Health 2022; 10:906089. https://doi.org/10.3389/fpubh.2022.906089
  » https://doi.org/10.3389/fpubh.2022.906089
• ^[31] Mialhe FL, Moraes KL, Sampaio HAC, Brasil VV, Vila VDSC, Soares GH, et al. Evaluating the psychometric properties of the eHealth Literacy Scale in Brazilian adults. Rev Bras Enferm 2021; 75(1):e20201320. https://doi.org/10.1590/0034-7167-2020-1320
  » https://doi.org/10.1590/0034-7167-2020-1320
• ^[32] Lee J, Lee EH, Chae D. eHealth literacy instruments: Systematic review of measurement properties. J Med Internet Res 2021; 23(11):e30644. https://doi.org/10.2196/30644
  » https://doi.org/10.2196/30644
• ^[33] Faux-Nightingale A, Philp F, Chadwick D, Singh B, Pandyan A. Available tools to evaluate digital health literacy and engagement with eHealth resources: A scoping review. Heliyon 2022; 8(8):e10380. https://doi.org/10.1016/j.heliyon.2022.e10380
  » https://doi.org/10.1016/j.heliyon.2022.e10380
• ^[34] Norman C. eHealth literacy 2.0: Problems and opportunities with an evolving concept. J Med Internet Res 2011; 13(4):e125. https://doi.org/10.2196/jmir.2035
  » https://doi.org/10.2196/jmir.2035
• ^[35] Griebel L, Enwald H, Gilstad H, Pohl AL, Moreland J, Sedlmayr M. eHealth literacy research-Quo vadis? Inform Health Soc Care 2018; 43(4):427-442. https://doi.org/10.1080/17538157.2017
  » https://doi.org/10.1080/17538157.2017
• ^[36] Van der Vaart R, 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(1):e27. https://doi.org/10.2196/jmir.6709
  » https://doi.org/10.2196/jmir.6709

Edited by

• Academic Editor:
  Wilton Wilney Nascimento Padilha

Publication Dates

• Publication in this collection
  23 Mar 2026
• Date of issue
  2026

History

• Received
  17 June 2024
• Reviewed
  09 Sept 2024
• Accepted
  21 Aug 2025