Factors Affecting COVID-19 Preventive Behaviors of Young Adults based on eHealth Literacy and the Health Belief Model: A Cross-Sectional Study

Abstract

Following the COVID-19 pandemic, disease prevention and preventive behaviors have become crucial for public health. In young adults, the internet is a popular source of health information. However, research that explores the factors associated with disease preventive behaviors based on the eHealth literacy (eHL) and the Health Belief Model (HBM) in young adults is lacking. A cross-sectional study design was used. Snowball sampling was used to recruit the participants through social network services. Proportionate stratified sampling was applied according to age, sex, and education level to mitigate sampling bias. The URL link for the online survey was provided via their mobile phones. A total of 324 participants, aged 20 to 39, completed the structured questionnaires (response rate = 98.2%). Frequency and descriptive statistical analyses, independent t-tests, one-way analyses of variance, Pearson’s correlation coefficients, and multiple linear regression analyses were performed. Factors associated with COVID-19 preventive behaviors were COVID-19-related eHL (β = .376, P < .001) and self-efficacy (β = .221, P < .001), which were positively associated with COVID-19 preventive behaviors. Boosting self-efficacy and the ability to find, evaluate, and apply health information with sufficient evidence from the Internet can improve COVID-19 preventive behaviors. The government and healthcare personnel should consider psychological factors such as self-efficacy when developing COVID-19 disease prevention behavioral guidelines for the Internet.

Keywords

COVID-19 disease prevention health belief model self-efficacy eHealth young adults

What do we already know about this topic?

Information sources related to COVID-19 have become increasingly diverse. Young adult group has utilized internet easily such as online video platforms, messenger services, and social network services (SNS) to obtain the information related to COVID-19. However, false information and rumors related to COVID-19 are a common occurrence. Health literacy is a highly essential ability in the context of pandemics. Improving eHealth literacy (eHL) is highly associated with practice rate of preventive behaviors among young adult.

How does your research contribute to the field?

The current study highlights that COVID-19-related eHL and self-efficacy were positively associated with the performance of COVID-19 preventive behaviors among young adults.

What are your research’s implications toward theory, practice, or policy?

Introduction

The novel 2019 coronavirus disease (COVID-19) pandemic has spread rapidly since January 20, 2020. When the first COVID-19 patient was confirmed in South Korea, the world needed to rapidly accept varied information and act to prevent infection.¹ As of March 17, 2022, the number of confirmed cases of COVID-19 in South Korea exceeded 621 000 for the first time since the initial COVID-19 outbreak, with the number of newly confirmed cases rising sharply every day.² This number is in contrast to the current trend in the United States, where the number of daily confirmed cases has decreased from approximately 360 000 in early February to approximately 200 000 cases at present.²

The Korea Disease Control and Prevention Agency (KDCA) reports new infectious disease- and prevention-related information and quarantine rules daily through the mass media.^2,3 The news topic that South Korean adults are most interested in is “health”; statistics reveal that information related to COVID-19 is obtained most frequently through the Internet.⁴ In South Korea, the Internet has played a major role over the past 20 years, and information sources such as online video platforms, messenger services, and social network services (SNS) have become increasingly diverse, as has the Internet.⁵ On account of its accessibility, the Internet is the most commonly used source of information. However, false information and rumors related to COVID-19 are a common occurrence, as indicated by the new word, “infodemic,” which refers to the rapid spread of false information on the Internet during a disease outbreak.⁶ An infodemic can confuse the public and lead to the mistrust of health authorities.⁷ Many countries have had to manage infodemics, which endanger public health.⁷ Additionally, the public is easily exposed to unreliable information posted for product sales, and social media companies use algorithms to spread information to their users rapidly.⁸ Consequently, people have a greater responsibility to evaluate the health information they consume before making any health decisions,⁸ especially considering the reduced opportunities for face-to-face contact following social distancing regulations.^9,10 Therefore, eHealth literacy (eHL), which can help people discern and accept correct information on the Internet, is urgently needed to ensure the public’s compliance with appropriate quarantine rules.

eHL is a highly essential ability through which individuals can find and understand information on the Internet. It further helps an individual to determine whether health information is correct and can be used in relation to health problems.¹¹ Those with low health literacy may have a low understanding of COVID-19 symptoms and the prevention of infectious diseases, and they tend to spread incorrect information about COVID-19 and vaccinations.¹² COVID-19-related eHL refers to an assessment of an individual’s self-rated ability to use the internet to find, assess, and use health information regarding COVID-19.¹³ In a previous study, low eHL was associated with poor compliance with health recommendations for COVID-19 prevention.¹⁴ Furthermore, there was a positive correlation between eHL and COVID-19 preventive behaviors among undergrad students majoring in Healthcare.¹⁵ Moreover, when health literacy was high, the practice rate of COVID-19 preventive behaviors such as handwashing, social distancing, and limiting gatherings was found to be high.¹⁶ A study on the digital health information literacy of college students revealed that participants had no major problems with the functional ability to search for information related to COVID-19 on the Internet; however, they could not evaluate the information and had difficulties detecting any commercial intent behind the searched COVID-19 information.¹⁷ Therefore, eHL is essential for the effective prevention of COVID-19.

As of June 2022, the average completion rate of the third dose of COVID-19 vaccination in South Korea was 59.1% for those aged 20 to 39, which is lower than the average of 83.4% for adults aged 40 or older.² According to the statistics of confirmed cases of COVID-19 by age, the incidence rate was 4995 per 100 000 people in their 20s and 4102 per 100 000 in people in their 30s (the highest among adults).¹⁸ Vaccinations for COVID-19 started later for adults in their 20s and 30s, the age group with a high risk of contracting COVID-19. As adults in their 20s and 30s are more active in social and leisure activities than other age groups,¹⁹ they pose a higher risk of transmitting an infectious disease or, conversely, becoming infected.

Owing to the prolonged spread of COVID-19, individuals need to stay alert regarding the spread of infectious diseases, even after their vaccinations, by following basic rules such as minimizing personal contact, wearing a mask, and washing their hands.² Furthermore, it is necessary to study the factors influencing individual preventive behaviors, as they have a great influence on the national quarantine system. The Health Belief Model (HBM) was proposed in 1950 to predict individual preventive health behaviors. It is a social cognitive model that originally comprised 5 constructs: perceived susceptibility (an individual’s assessment of their risk of contracting a disease); perceived severity (an individual’s perception of the seriousness and potential consequences of the disease); perceived benefits (an individual’s beliefs about whether the suggested behavior will reduce the risk); perceived barriers (an individual’s assessment of the difficulties); and cues to action (the internal or external motivations promoting the desired behavior).²⁰ Thereafter, self-efficacy (an individual’s belief regarding their capabilities to successfully perform a behavior), a major variable in social cognitive theory, was added as a variable in this model to enhance its explanatory power.²⁰ In examining the factors that affect the intention to prevent COVID-19 in adults older than 20, several preliminary studies have applied the HBM and found that preventive behavior intention was significantly higher with a higher perceived severity, perceived susceptibility, and perceived benefit.^21,22 In a study conducted with South Korean university students, preventive behaviors related to COVID-19 significantly decreased with a higher perceived barrier.²³ A study on the factors influencing COVID-19 prevention behaviors in adults demonstrated higher perceived benefits and lower perceived barriers significantly increased participants’ preventive behaviors against COVID-19.²⁴

Self-efficacy is defined as the belief that an individual can successfully perform the behaviors necessary to achieve a certain outcome in a particular domain.²⁵ It is a driving force that makes people strive to achieve a given goal with confidence in their ability, even in difficult situations. Self-efficacy does not refer to an individual’s ability but rather the person’s judgment regarding whether they exert a certain capacity.²⁵ It plays a significant mediating effect between health literacy and health behavioral intention in adolescents and adults.²⁶ It also has a direct effect on the degree of therapeutic behavior performance in patients with the human immunodeficiency virus (HIV).²⁷ Furthermore, in a study conducted with students enrolled in a nursing department, self-efficacy was significantly positively correlated with COVID-19 preventive behavioral intention.²⁸

However, in the context of the COVID-19 pandemic, there is a lack of research on COVID-19-related eHL and the health beliefs of young adults in their 20s and 30s, who tend to acquire information from the Internet. In particular, few South Korean studies include COVID-19-related eHL as a factor influencing preventive behaviors against COVID-19. Furthermore, young adults in South Korea have the lowest rate of COVID-19 vaccination; therefore, they have a high risk of contracting COVID-19.

The South Korean government began to implement policies for a phased recovery of daily life activities on November 1, 2021. These policies comprised quarantine rules and continuous behaviors to prevent infection, which are essential for public health.¹⁸ From this context, this study identifies the factors that affect preventive health behaviors against COVID-19 among young adults in South Korea based on COVID-19-related eHL and the HBM. Out of the 6 constructs of the HBM, cues to action is not included in this study because most of the health information on the Internet, containing recommendations of preventive behavioral measures, already functions as cues for action.²⁹

Methods

Study Design

This descriptive cross-sectional study identifies the factors affecting COVID-19 preventive behaviors of young adults based on COVID-19-related eHL and the HBM.

Participants

This study was conducted with young adults aged 20 to 39, who used the Internet on devices such as computers, tablets, and mobile phones from December 2021 to February 2022. The inclusion criteria were those who used the Internet with these devices and could read and answer online questionnaires. When calculating the sample size for the regression analysis using G*Power 3.1 software,³⁰ the significance level of .05, an effect size of 0.10, and power of 0.85 were applied, with 12 predictors, as suggested by Cohen³¹; the required sample size was 300 people. Considering a dropout rate of about 10.0%, 330 respondents were sampled. Out of the 330 questionnaires recovered, 324 were analyzed, excluding 6 questionnaires with insufficient responses.

Snowball sampling was used to recruit the participants owing to the COVID-19 pandemic regulations. Therefore, data were collected from a participant, who then further introduced another participant, and so on. To mitigate sampling bias, proportionate stratified sampling was applied according to age, sex, and education level. It is because, in previous studies, compliance with preventive behavioral recommendations was different according to age (20s and 30s), sex, and education level.^14,32,33 Only those who were informed about the purpose of the study and voluntarily expressed their willingness to participate were eligible. After obtaining a respondent’s written consent to participate in the study and collecting their personal information, the URL link (http://naver.me/53yLwvoC) for the online survey and participation procedure was provided on their mobile phones.

Measures

General characteristics

Regarding general characteristics, data were collected on age, sex, education level, occupation, income, COVID-19 information source, Internet use time, and the COVID-19 testing experiences of their acquaintances.

COVID-19-related eHL

COVID-19-related eHL was measured using the eHL Scale (eels), developed by Norman and Skinner¹¹ and translated into Korean (K-eHEALS) by Chung et al.³⁴ The scale was used after adding the expression “related to COVID-19” to the K-eHEALS. Before using the scale, approval was obtained from the original developer and translator for the use and the insertion of the phrase “COVID-19-related.” The K-eHEALS consists of 8 items scored on a 5-point Likert scale, with a total range of 8 to 40 points. Higher scores indicate a higher level of COVID-19-related eHEALS. In the previous study by Chung et al³⁴ on Korean young adults, the eHEALS had been used and Cronbach’s α was .88. In this study, Cronbach’s α was .84.

Health beliefs related to COVID-19

The scale by Jo and Choi²³ was used to measure the perceived susceptibility (2 items), perceived severity (3 items), perceived benefit (3 items), and perceived barrier (2 items) among the HBM for COVID-19. Each item is scored on a 5-point scale, with 5 indicating “strongly agree” and one indicating “strongly disagree.” A higher score for each construct item indicates a higher level of health beliefs. As for the reliability of the scale, Cronbach’s α was .70 in the study by Jo and Choi,²³ which was conducted with Korean college students, and .61 in this study.

Self-efficacy is intended to measure the generalized beliefs regarding one’s abilities in a variety of new situations. In this study, the General Self-Efficacy Scale,³⁵ which was modified into Korean by Lee et al,³⁶ was used. This scale consists of 10 items scored on a 4-point Likert scale, with 4 indicating “strongly agree” and 1 indicating “not at all” (range = 10-40). A higher score indicates a higher level of self-efficacy. In the study by Lee et al,³⁶ Cronbach’s α was .75, and Cronbach’s α was .87 in this study.

COVID-19 preventive behaviors

For the prevention of COVID-19, a scale developed by Jo and Choi,²³ based on the COVID-19 preventive behavioral guidelines presented by the KDCA,² was used. The scale comprises 11 items: handwashing, coughing, wearing a mask, hygiene precautions, avoiding eating out, reducing visits to shopping centers, reducing public transport use, reducing karaoke use, refraining from going out, social distancing, and avoiding physical contact with people. A 4-point Likert scale was used, with 4 indicating “strongly agree” and 1 indicating “strongly disagree,” where a higher score indicates a higher level of preventive behaviors. In the study by Jo and Choi,²³ on Korean college students, Cronbach’s α was .87. In this study, Cronbach’s α was .75.

Statistical Analysis

Data analysis was performed using SPSS 26.0 (SPSS; IBM, Armonk, NY, USA). For the general characteristics of the study participants, frequency and descriptive statistical analyses were performed. The difference in COVID-19 preventive behaviors according to general characteristics was analyzed using independent t-tests and one-way analyses of variance (ANOVA). The correlation between major variables was analyzed with Pearson’s correlation coefficients. After inputting the variables that showed significant correlations with COVID-19 preventive behaviors, factors affecting the COVID-19 preventive behaviors were identified with a multiple linear regression analysis.

Ethical Considerations

Data collection was performed after being reviewed and approved (no. MC21QISI0127) by the Institutional Clinical Research Review Committee of University C. We obtained participants’ online consent after explaining the voluntary participation process, anonymity, and revocation, and assuring them that that there were no disadvantages.

Results

Participants’ General Characteristics

The average age of the participants was 28.86 (±5.86) years, and 50.6% of them were women. Of the participants, 55.9% had a college degree or higher, 55.9% were employed, and 41.7% had an income level higher than KRW 2 million to KRW 4 million or less. Furthermore, 41.0% of participants used the Internet for more than 2 h and less than 3 h a day. The most common COVID-19-related information source was the Internet with 73.1% of the participants using it. Moreover, 91.4% of participants had a close acquaintance test positive for COVID-19 (Table 1).

Table 1.

General Characteristics and Differences in COVID-19 Preventive Behaviors According to Participants’ Characteristics (N = 324).

Variable	n (%)	M ± SD	t or F	P
Age (years)		28.86 ± 5.86
20s	168 (51.9)	37.79 ± 3.83	0.514	.608
30s	156 (48.1)	37.56 ± 4.14
Sex
Male	160 (49.4)	37.63 ± 4.05	0.227	.821
Female	164 (50.6)	37.73 ± 3.92
Education level
<University	133 (41.0)	37.72 ± 3.82	0.150	.881
≥University	181 (55.9)	37.65 ± 4.10
Job
No	143 (44.1)	37.54 ± 4.00	0.577	.564
Yes	181 (55.9)	37.80 ± 3.97
Income (10 000 won)
≤200	131 (40.4)	37.62 ± 3.81	0.634	.531
201-400	135 (41.7)	37.52 ± 4.24
≥401	58 (17.9)	38.21 ± 3.73
Internet usage (h/day)
<2	69 (21.3)	37.30 ± 3.57	0.560	.572
2-2.99	133 (41.0)	37.65 ± 3.95
≥3	122 (34.0)	37.93 ± 4.24
COVID-19 information source
Internet and social networking services	231 (71.3)	37.55 ± 4.08	0.974	.331
TV, newspaper, acquaintances	93 (28.7)	38.02 ± 3.71
Experience of COVID-19 test of acquaintances
No	28 (8.6)	37.14 ± 4.03	0.750	.454
Yes	296 (91.4)	37.73 ± 3.98

COVID-19-Related eHL, Health Beliefs, and COVID-19 Preventive Behaviors

The mean of COVID-19-related eHL was 31.29 (±4.07). Within the HBM, the mean of self-efficacy was 30.19 (±4.00). Among the items concerning COVID-19 preventive behaviors, the average score for “I always wear a mask when I go out” was the highest. Contrastingly, the average score for the item, “I limit my use of public transportation” was the lowest (Table 2).

Table 2.

Descriptive Scores of COVID-19-Related eHealth Literacy, Health Beliefs, and COVID-19 Preventive Behaviors.

Variables	M ± SD
COVID-19 preventive behaviors (range = 1-4)
1. Avoid eating with other people	3.36 ± 0.64
2. Wear a mask when going out of the house	3.98 ± 0.14
3. Avoid using public transportation	2.68 ± 1.05
4. Avoid visiting shopping malls or department stores	3.17 ± 0.91
5. Avoid visiting closed places such as theaters	3.65 ± 0.63
6. Cover mouth and nose when coughing or sneezing	3.60 ± 0.54
7. Avoid going to crowded places	3.34 ± 0.66
8. Take shower and avoid using others’ personal equipment	3.55 ± 0.53
9. Wash hands more often	3.71 ± 0.49
10. Avoid touching others such as no hand shaking	3.40 ± 0.75
11. Keep distance at least 2 m when eating outside	3.25 ± 0.71
Total (range = 11-44)	37.68 ± 3.98
COVID-19-related eHealth literacy (range = 8-40)	31.29 ± 4.07
Health beliefs
Perceived susceptibility (range = 1-5)	4.02 ± 0.77
Perceived severity (range = 1-5)	3.87 ± 0.88
Perceived benefit (range = 1-5)	3.55 ± 0.86
Perceived barrier (range = 1-5)	3.24 ± 1.01
Self-efficacy (range = 10-40)	30.19 ± 4.00

Note. M = mean, SD = standard deviation.

Correlations Between Key Variables

COVID-19-related eHL (r = .419, P < .001) was moderately correlated with COVID-19 preventive behaviors (Table 3). Perceived susceptibility (r = .188, P < .001) and self-efficacy (r = .269, P < .001) were lowly associated with COVID-19 preventive behaviors. Perceived severity, perceived benefit, and perceived barrier were not significantly correlated with COVID-19 preventive behaviors at the bivariate level.

Table 3.

Correlations Among Variables (N = 324).

Variables	1	2	3	4	5	6	7
1. COVID-19-related eHealth literacy	1
2. Perceived susceptibility	.206^**	1	.
3. Perceived severity	.059	.219^**	1
4. Perceived benefit	.253^**	.089	.163^**	1
5. Perceived barriers	.030	–.017	.150^**	.164^**	1
6. Self–efficacy	.107	.084	–.055	.122^*	–.021	1
7. COVID-19 preventive behaviors	.419^**	.188^**	.080	.037	.078	.269^**	1

P < .05. ^**P < .01.

Factors Affecting COVID-19 Preventive Behaviors

The regression model yielded significant variables, including COVID-19-related eHL, perceived susceptibility, and self-efficacy (variance inflation factors = 1.010-1.053, Durbin–Watson D = 1.759, F = 32.62, P < .001; Table 4). The model explained 23.4% of the variance in COVID-19 preventive behaviors. COVID-19-related eHL (β = .376, P < .001) and self-efficacy (β = .221, P < .001) were found to be predictive of COVID-19 preventive behaviors. Thus, higher COVID-19-related eHL and self-efficacy were associated with better COVID-19 preventive behaviors in South Korean young adults.

Table 4.

Factors Associated With Preventive Behaviors for COVID-19 (N = 324).

Variable	B	SE	β	t	P
Intercept	17.182	2.194		7.833	<.001
COVID-19-related eHealth literacy	0.368	0.049	.376	7.496	<.001
Perceived susceptibility	0.295	0.161	.092	1.829	.068
Self-efficacy	0.219	0.049	.221	4.477	<.001
R²	.234
Adjusted R²	.227
F (p)	32.622 (<.001)

Note. SE = standard error.

Discussion

This study examined the factors associated with COVID-19 preventive behaviors based on the HBM in South Korean young adults aged 20 to 39. The results of a multiple linear regression analysis revealed that COVID-19-related eHL and self-efficacy were significant predictors related to COVID-19 preventive behaviors.

These results relating to COVID-19-related eHL were consistent with the high level of practice for COVID-19 preventive behaviors such as handwashing, social distancing, and limiting gatherings, in those with a high level of health literacy.^16,37 eHL encompasses the ability of individuals to find and understand necessary information, as well as to evaluate the quality of the found information and apply it to health-related behaviors.⁶ Therefore, it can be interpreted that a higher level of COVID-19-related eHL leads to a higher tendency to practice COVID-19 preventive behaviors based on an accurate understanding and evaluation of information found on the Internet.³⁸

In South Korea, the mobile device possession rate is almost 100.0% for young adults and 65.0% for the elderly.³⁹ Moreover, 86.9% of young adults search on the Internet, as compared with only 43.7% of the older population.³⁹ In the 26 countries of the European Union, similar to South Korea, 88% of young adults use the Internet, as compared to only 26% of older adults.⁴⁰ With a higher possession of media devices, there is a higher risk for young adults to be exposed to and spread misinformation regarding COVID-19.⁴¹ It is crucial to have eHL for young adults to evaluate the quality of information they obtain on the Internet.

The spread of insufficient and inaccurate COVID-19-related information is increasing and creating uncertainty and anxiety which hinders public health.⁶ In South Korea, infodemic events that contribute to the spread of COVID-19 or cause greater fear occur because of the spread and acceptance of false information.⁴² Furthermore, the majority of people use media technology platforms to seek information or news regarding COVID-19 preventive measures and to stay connected with others amid the COVID-19 crisis.⁴³ Therefore, for COVID-19 preventive behaviors, COVID-19-related eHL is a vital national competency that should not be overlooked.⁴⁴ Furthermore, the national guidelines for infectious diseases are consistently changing because of the prolonged pandemic period. As of March 2022, the KDCA has been sending home treatment notices via text messages to patients who test positive for COVID-19 and their families.² Infectious disease management is being implemented by including URLs in text messages and allowing people to install medical support apps independently on their devices.² COVID-19-related eHL is highly and urgently needed to ensure the proper understanding of the information provided through the Internet media, and to promote quarantine and preventive actions to prevent further infection.

In this study, self-efficacy was confirmed as a significant influencing factor of COVID-19 preventive behaviors. A high sense of self-efficacy indicates a greater belief in one’s ability to perform preventive measures adequately. These results are consistent with those of prior studies.^28,45,46 Additionally, self-efficacy has been confirmed as a factor influencing not only COVID-19 preventive behaviors but also hypertension, HIV, and cancer preventive behaviors.^47-50 Perceived self-efficiency reduces a person’s stress levels and has far-reaching effects on their thought processes, motivation, and behaviors; therefore, is necessary to find ways to increase people’s self-efficacy to promote COVID-19 preventive behaviors.⁵¹

Perceived susceptibility was non-significant in the multivariate analysis; however, it had a significant positive correlation with COVID-19 preventive behaviors in the univariate analysis. In addition, perceived susceptibility had the highest average score compared to other concepts in the HBM. This result corresponds with those of a previous study, which show that perceived susceptibility was the belief that an individual had a high probability of contracting a disease and a variable that could strongly predict disease-preventive behaviors.⁵² In an intervention study, an increase in perceived susceptibility in adult men raised the rate of self-testing for prostate cancer screening.⁴⁹ Furthermore, perceived susceptibility rather than perceived severity had a highly effective influence on tuberculosis preventive behaviors.⁵³ Rather than sending threatening messages related to COVID-19 to promote preventive behaviors, increasing the level of perceived susceptibility, which is the feeling among individuals that they may fall ill by having an infectious disease anytime regardless of symptoms, may be more effective in promoting infectious disease preventive behaviors in a prolonged pandemic situation.⁵³

Among the COVID-19 preventive behaviors items, the item with the lowest performance was “I limit my use of public transportation,” and the item with the second lowest performance was “I reduce my visits to shopping centers and department stores.” Although the performance of preventive actions against COVID-19 was high among participants, such as washing hands, wearing a mask, and covering the nose and mouth when coughing, the performance of preventive actions related to avoiding visits to crowded places was generally low, which corresponded with the results of a previous COVID-19 preventive behavior study.⁵⁴ As for the participants belonging to the younger age group in this study, the performance of preventive behaviors related to these activities seems low as they actively engage in social and leisure activities.

This study has some limitations. Our cross-sectional design, small sample size, age group restrictions, and use of survey data have obvious constraints concerning the generalizability of the results. However, this study is meaningful in that the proportionate stratified sampling was performed at a similar rate without bias by age, sex, or education level during the sampling process.

Conclusion

COVID-19-related eHL and self-efficacy are important factors for the promotion of COVID-19 preventive behaviors in adults in their 20s and 30s. In particular, the ability to find, evaluate, and apply information with sufficient evidence and accurate material among the numerous pieces of information on the Internet is an essential competency. The performance of COVID-19 preventive behaviors will improve by increasing people’s self-efficacy, which makes them believe that they can comply with the COVID-19 preventive behaviors guidelines adequately through the enhancement of psychological factors.

Health promotion provider could consider both COVID-19-related eHL and self-efficacy factors when developing strategies for campaigns or education related to COVID-19 preventive behaviors among young adults. In future research, we suggest diversifying age groups and including older populations to compare and analyze the factors affecting COVID-19 preventive behaviors.

Supplemental Material

sj-docx-1-inq-10.1177_00469580231159487 – Supplemental material for Factors Affecting COVID-19 Preventive Behaviors of Young Adults based on eHealth Literacy and the Health Belief Model: A Cross-Sectional Study

Supplemental material, sj-docx-1-inq-10.1177_00469580231159487 for Factors Affecting COVID-19 Preventive Behaviors of Young Adults based on eHealth Literacy and the Health Belief Model: A Cross-Sectional Study by Hye Seung Choi and Jong-Eun Lee in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Footnotes

Acknowledgements

We extend our sincere thanks to the participants who completed the questionnaire.

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical Approval

Data collection was performed after being reviewed and approved (no. MC21QISI0127) by the Institutional Clinical Research Review Committee of the Catholic University of Korea. We obtained participants’ online consent after explaining the voluntary participation process, anonymity, revocation, and that there were no disadvantages.

ORCID iD

Jong-Eun Lee

Supplemental Material

Supplemental material for this article is available online.

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