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Volume 13, Issue 3 (2025)
Health Educ Health Promot 2025, 13(3): 421-427 |
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Received: 2025/05/5 | Accepted: 2025/07/3 | Published: 2025/07/20
Received: 2025/05/5 | Accepted: 2025/07/3 | Published: 2025/07/20
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Effect of Health Literacy on the Internet Users' Electronic Word of Mouth. Health Educ Health Promot 2025; 13 (3) :421-427
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URL: http://hehp.modares.ac.ir/article-4-80711-en.html
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Introduction
The primary positive aspect of the internet is its ability to provide users with widespread access to information, whether as a provider or a recipient. Its limitless accessibility allows people to share information 24/7, offering real-time support and communication across cultural and global boundaries. While there are numerous benefits to this accessibility, the sharing of health information is somewhat debatable. The health information shared or acquired needs to be verified and validated before passing it on to others, given its significant impact on the likelihood of encountering due diligence issues. However, equipping individuals to critically evaluate health information has made them more resilient to misinformation instead [1]. This situation has indirectly created a new responsibility for society regarding the messages they disseminate, enhancing their potential for social engagement. With the practical advantages of the internet, traditional word of mouth has evolved into dynamic electronic word of mouth (e-WOM), allowing society to share health information in real time without requiring face-to-face meetings or voice calls. Individuals can now send statements or questions to their intended audience, with feedback expected almost instantaneously. This convenience has led to increased communication through the internet and popular social media platforms, yet the reliability and accuracy of the information shared have sparked a controversial debate among health experts [2].
However, this issue can be addressed through health literacy, defined as an individual’s ability to acquire and interpret information and knowledge that is contextually relevant to maintaining and improving their health [3]. Health information is said to be accessible and usable by individuals through health literacy, which may pose a challenge for those with limited levels of understanding [4]. Health literacy comprises four key components: accessing, understanding, evaluating, and applying health information, integrated with three main domains: health care, disease prevention, and health promotion [5]. This study will deliberately focus on the three domains, starting with health care. This domain emphasizes individuals’ ability to navigate the complex healthcare system by understanding the health or medical information they receive and effectively communicating with healthcare professionals.
A lack of understanding of the technical processes and terminology related to appointment procedures, diagnoses, medical instructions, and treatment options can present significant obstacles for individuals with low health literacy [6]. Meanwhile, the second domain of disease prevention focuses on individuals’ knowledge and skills to prevent injuries and diseases. Individuals must have a clear understanding of preventive measures, signs, and symptoms, as this knowledge will help them make better-informed health-related choices and decisions. Health outcomes can be improved through disease prevention, as its interventions aim to alter the natural history of the disease [7]. Lastly, health promotion is the domain that encompasses individuals’ understanding of health longevity by maintaining and improving their overall well-being. This domain differs slightly from the other domains of health literacy in that it emphasizes the inclusivity of individuals within a healthy community. Health promotional activities typically target a larger audience, raising awareness about how to achieve better health. For instance, optimizing the use of social media in health promotion allows public health authorities to disseminate targeted health messages to hard-to-reach individuals while engaging with the public through dynamic promotional campaigns [8, 9].
With an adequate level of health literacy, individuals are expected to be well-engaged and participate in health-related discussions, able to provide comprehensive details about specific medical conditions in the most understandable terms. This would enable smoother communication, with trust no longer being an issue for the participants involved. This is because an individual’s level of health literacy has been found to influence how much they trust various sources of health information, including healthcare providers [10]. Consequently, this situation has created two distinct perspectives on word of mouth, where the health messages shared between the parties involved may indicate whether negative or positive e-WOM has occurred. Although many companies wish to be associated with positive e-WOM from their consumers, studies have unfortunately shown that consumers are more likely to be influenced by negative e-WOM messages [11]. Nonetheless, socio-demographic factors can help turn the tide positively for both health literacy and e-WOM. Age and gender are the most common socio-demographic factors found to influence the two domains of health literacy [12] and e-WOM [13]. Therefore, this study compared the impacts of health literacy domains (health care, disease prevention, and health promotion) on e-WOM based on socio-demographic factors.
Instrument and Methods
This cross-sectional descriptive correlational research was conducted among Malaysian Internet users in Peninsular Malaysia in two months, from July to August 2024.
A proportionate quota sampling technique was applied, with each region of Peninsular Malaysia represented by 100 samples. Cumulatively, since Peninsular Malaysia comprises four major regions—Central, Southern, Northern, and East Coast—a total of 400 samples were targeted as respondents.
Although the degree of generalizability is questionable in quota sampling, it at least provides adequate statistical power to distinguish differences in groups due to its characteristic of oversampling underrepresented groups [14]. The sample size of 400 respondents was deemed appropriate in accordance with the regression analysis minimum requirement of 100 samples [15].
These respondents were respectfully approached by the researcher to voluntarily participate in the study, where they were required to complete a self-administered questionnaire consisting of 56 items. The self-administered questionnaire was constructed and adapted from two well-established instruments: the Electronic Word of Mouth Questionnaire [16] and the New Short-Form Health Literacy Instrument (HLS-SF12) [17]. This instrument employed four Likert scales of agreement, ranging from strongly agree to strongly disagree, for all items except the demographic questions. A quantitative research expert validated the content validity of this questionnaire before it was submitted for ethical review. Subsequently, the questionnaire was approved by the ethical committee, which recognized that the researcher was attentive to the issues of privacy and integrity of the collected data. Additionally, a pilot study involving 50 samples was conducted prior to the actual data collection to verify the reliability of the instrument. It demonstrated good reliability, with Cronbach’s Alpha values ranging from 0.798 to 0.90 [18].
This instrument was disseminated through various platforms, including email, WhatsApp, Telegram, and other social media. Data were collected within a single time frame of two months. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. Participants were fully informed regarding the study objectives, and written/verbal consent was obtained before the initiation of data collection. The study was conducted on a voluntary basis, with no coercion applied to participants in the research process. The strictest confidentiality of the data was maintained, and the collected data will be used only for research purposes. It took approximately three months to collect 450 responses, including the pilot study data, as some regions presented greater challenges; for instance, the northern region required almost two months to obtain a complete set of 100 responses. Nevertheless, the practicality of Google Forms significantly assisted the researcher, particularly with the ‘required’ features that enabled the collection of zero missing responses. This study predominantly involved females, accounting for 68.5% of respondents, and individuals aged 18 to 30 years made up 77.5%. This segmentation of profiles was anticipated by the researcher, as individuals aged 20 to 39 years are known to have the highest internet usage, at 99.6% [19].
SPSS 29 was used by the researcher to assist in data analysis for descriptive and multiple regression analyses, ensuring the achievement of the respective research objectives.
Findings
Males’ e-WOM was better explained by the three domains of health literacy (R²=0.505). However, the disease prevention and healthcare domains significantly influenced e-WOM among female Internet users, while health promotion was the only domain of health literacy that significantly influenced the e-WOM of male Internet users (Table 1).
Table 1. Multiple regression analysis of health literacy dimensions predicting e-WOM by gender
![src=./files/hehp/images/HTML_Publish/80711/1.png]()
The health literacy of individuals aged 41-50 years or 18-30 years could explain 54.1% and 41% of their e-WOM, respectively. Additionally, all three domains of health literacy were found to significantly predict e-WOM among individuals in these age categories, with healthcare identified as the strongest predictor, followed by disease prevention and health promotion (Table 2).
Table 2. Multiple regression analysis of health literacy dimensions predicting e-WOM by age
![src=./files/hehp/images/HTML_Publish/80711/2.png]()
The health literacy of individuals with secondary education, postgraduate studies, a diploma, or a bachelor’s degree could respectively explain 60.2%, 42.5%, 40.8%, and 27.5% of their e-WOM. Despite the highest R² value for secondary education, the healthcare domain was the only predictor for e-WOM, while individuals with a bachelor’s degree exhibited two domains with significant beta values, indicating two predictors for e-WOM. Specifically, disease prevention was identified as the strongest predictor of e-WOM, followed by health promotion. The bachelor’s degree category was the only one with two significant predictors, in contrast to secondary education and diploma, both of which demonstrated the healthcare domain as the sole predictor (Table 3).
Table 3. Multiple regression analysis of health literacy dimensions predicting e-WOM by education
![src=./files/hehp/images/HTML_Publish/80711/3.png]()
The health literacy of individuals who were self-employed could explain 68.8% of e-WOM, while the health literacy of those who were not working, and those who were working in the private or public sectors could explain 39.2%, 27%, and 17.1%, respectively, of their e-WOM. Although the self-employed category demonstrated a higher R² value, e-WOM could only be predicted by healthcare. In contrast, the e-WOM among individuals who were not working was predicted by the disease prevention and healthcare domains. Additionally, e-WOM for both public and private sector workers was not significantly predicted by any of the health literacy domains (Table 4).
Table 4. Multiple regression analysis of health literacy dimensions predicting e-WOM by occupation
![src=./files/hehp/images/HTML_Publish/80711/Screenshot_2025-10-08_112610.png]()
Discussion
This research compared the impacts of health literacy on e-WOM based on the socio-demographic factors of gender, age, highest education, and occupation among Internet users in Peninsular Malaysia. Most findings align with past research, indicating a closer gap in the literature review. The results from the multiple regression analyses demonstrated more significant predictive effects of health literacy domains on e-WOM among respondents who were female, aged 18-30 years, held a bachelor’s degree, and were currently not working.
Firstly, in the comparisons of gender, previous research has reported that females have a higher usage of health forums and blogs when searching for health information online [20]. Women are known to exhibit stronger traits of conscientiousness and agreeableness, which consequently incline them to be more compliant with preventive health behaviors [21]. This explains why disease prevention is the strongest predictor of their e-WOM. Regarding males, despite studies addressing the underdevelopment of their health literacy [22], they are commonly found to be poorly health literate, which negatively influences their help-seeking behavior and engagement with healthcare professionals [23].
Second, in the comparisons of age, despite individuals aged 41-50 years having the highest percentage of ICT usage for seeking health information (72%), individuals aged 20 to 39 years have the highest overall usage of the internet, at 99.6% [19]. These young individuals may not be particularly inclined to seek health information, but they have been reported to possess higher levels of health literacy [24]. Their good health literacy levels may suggest that they do not feel the need to look for health information, as they are more aware of what is happening with their health and surroundings. Young adults are usually underrepresented in health promotional activities, as they tend to be overlooked by authorities despite their societal relevance [25]. However, as they grow older, their health literacy is likely to decline significantly [24], and that is when good health-seeking behavior, including seeking health information online, becomes increasingly important.
Thirdly, in the comparisons of the highest education among the respondents, it was reported that the e-WOM of those with bachelor’s degrees can be better predicted by two out of three domains of health literacy compared to individuals with other educational attainments. Multiple past studies have previously stated how educational background can influence an individual’s level of health literacy [12, 24, 26]. While this study found a similar result regarding the predictive effects among those with bachelor’s degrees, the postgraduate studies category indicated otherwise. It was found that e-WOM could be significantly explained by the health literacy domains, but there was no single predictor among them. Inductively, this finding can be considered new information for the body of knowledge on health literacy, as postgraduate students are known to have higher health literacy levels than average [27, 28].
Additionally, there was a positive relationship between educational level and health promotional behavior, whereby lower education levels correspond to lower health promotional behavior [29]. Simply put, having a higher level of health literacy can suggest how their e-WOM may be influenced by their ability to comprehend and share health information. Lastly, in the comparisons of respondents’ occupations, there were more significant predictive effects of health literacy domains on e-WOM among those who were not working. In contrast, this finding does not align with previous research, indicating that employed individuals tend to seek more health information online compared to the unemployed [30]. However, this contradictory finding may arise from the fact that individuals who are not working have more time to use the Internet and engage in social networking through social media [31]. Consequently, there may be a significant increase in Internet usage among these individuals as they look for health information, especially regarding disease prevention. This is particularly important, as unemployed individuals may be more cautious about getting sick, given that illness could incur medical costs in addition to their usual living expenses [32].
Although there are limited studies that have compared the integration of health literacy and e-WOM, many studies have been conducted on the effects of socio-demographic factors on health literacy [12, 26, 33]. Nonetheless, it is vital to acknowledge that Malaysians’ health literacy has not been fully leveraged by the government to ensure the reliability and accuracy of the disseminated health information. This evident concern was particularly apparent during the COVID-19 pandemic when the situation of ‘infodemic’ became increasingly critical as rumors regarding health information disorders spread rapidly [34]. Accordingly, the Malaysian Communications and Multimedia Commission (MCMC) has attempted to address the issue by encouraging citizens to visit the official website ‘Sebenarnya’ to verify the factuality of the news [35]. If Malaysians can fully utilize their good health literacy to distinguish between good and bad health information during information dissemination, this would assist the government in achieving more positive health outcomes [36]. Furthermore, the significance of health literacy is prioritized by the Malaysian government, as it is highlighted in the Healthy Malaysia National Agenda (ANMS) 2020-2030, which established the National Health Literacy Policy (DLKK) in 2024. The agenda aims to empower Malaysians to take responsibility for their health-related decision-making by adopting a healthier lifestyle [37]. Regardless of socio-demographic factors, the government should take advantage of the importance of health literacy to shift society’s e-WOM toward a positive transmission process.
Hence, this study recommends that the Malaysian government, specifically the public health authorities, consistently empower society and the public regarding the importance of using social media to share reliable and accurate health information. This suggestion aligns with the DLKK, particularly the 9th initiative, which emphasizes the significance of community support in strengthening the health literacy capacities of the community [37]. This initiative highlights the importance of organizing community empowerment activities that align with the strengths of health literacy, enabling the public to take charge of their own health-related decision-making. Nonetheless, this empowerment initiative is particularly ineffective without a strong foundation in health literacy. This is because social media users may be distracted by peripheral information, which can hinder their processing of intended health messages [38], consequently creating problems for those with low health literacy. On the other hand, future studies are recommended to conduct comparative research based on household income as one of the parameters, as it is one of the most influential factors affecting health literacy. Future researchers may also apply probability sampling techniques, such as proportionate stratified random sampling, to avoid instances of sampling bias in selecting the targeted respondents.
Gender, age, highest education, and occupation were the socio-demographic factors compared, in line with previous studies’ findings, indicating that they are the most commonly identified influential factors of health literacy. The three domains of health literacy better explained e-WOM among respondents who were male, aged 41 to 50 years, had secondary education, and were self-employed. Nonetheless, more significant predictive effects of health literacy domains on e-WOM were found among respondents who were female, aged 18-30 years, held a bachelor’s degree, and were currently not working.
Conclusion
Gender, age, highest education, and occupation are influential factors of health literacy.
Acknowledgments: We would like to thank the Malaysian Ministry of Higher Education, Universiti Teknologi MARA (UiTM), and the Research Management Centre (RMC) of UiTM for funding this study through internal grant DUCS-F 600-UiTMSEL (Pl. 5/4) (100/2022).
Ethical Permissions: Ethical approval was obtained from the UiTM Research Ethics Committee [Code: REC/02/2023 (ST/MR/45)].
Conflicts of Interests: There are no conflicts of interests.
Authors' Contribution: Sumardi NA (First Author), Introduction Writer/Methodologist/Main Researcher/Discussion Writer/Statistical Analyst (100%)
Funding/Support: Special gratitude goes to the Malaysian Ministry of Higher Education, Universiti Teknologi MARA (UiTM), and the Research Management Centre (RMC) of UiTM for funding this study through internal grant DUCS-F 600-UiTMSEL (Pl. 5/4) (100/2022).
The primary positive aspect of the internet is its ability to provide users with widespread access to information, whether as a provider or a recipient. Its limitless accessibility allows people to share information 24/7, offering real-time support and communication across cultural and global boundaries. While there are numerous benefits to this accessibility, the sharing of health information is somewhat debatable. The health information shared or acquired needs to be verified and validated before passing it on to others, given its significant impact on the likelihood of encountering due diligence issues. However, equipping individuals to critically evaluate health information has made them more resilient to misinformation instead [1]. This situation has indirectly created a new responsibility for society regarding the messages they disseminate, enhancing their potential for social engagement. With the practical advantages of the internet, traditional word of mouth has evolved into dynamic electronic word of mouth (e-WOM), allowing society to share health information in real time without requiring face-to-face meetings or voice calls. Individuals can now send statements or questions to their intended audience, with feedback expected almost instantaneously. This convenience has led to increased communication through the internet and popular social media platforms, yet the reliability and accuracy of the information shared have sparked a controversial debate among health experts [2].
However, this issue can be addressed through health literacy, defined as an individual’s ability to acquire and interpret information and knowledge that is contextually relevant to maintaining and improving their health [3]. Health information is said to be accessible and usable by individuals through health literacy, which may pose a challenge for those with limited levels of understanding [4]. Health literacy comprises four key components: accessing, understanding, evaluating, and applying health information, integrated with three main domains: health care, disease prevention, and health promotion [5]. This study will deliberately focus on the three domains, starting with health care. This domain emphasizes individuals’ ability to navigate the complex healthcare system by understanding the health or medical information they receive and effectively communicating with healthcare professionals.
A lack of understanding of the technical processes and terminology related to appointment procedures, diagnoses, medical instructions, and treatment options can present significant obstacles for individuals with low health literacy [6]. Meanwhile, the second domain of disease prevention focuses on individuals’ knowledge and skills to prevent injuries and diseases. Individuals must have a clear understanding of preventive measures, signs, and symptoms, as this knowledge will help them make better-informed health-related choices and decisions. Health outcomes can be improved through disease prevention, as its interventions aim to alter the natural history of the disease [7]. Lastly, health promotion is the domain that encompasses individuals’ understanding of health longevity by maintaining and improving their overall well-being. This domain differs slightly from the other domains of health literacy in that it emphasizes the inclusivity of individuals within a healthy community. Health promotional activities typically target a larger audience, raising awareness about how to achieve better health. For instance, optimizing the use of social media in health promotion allows public health authorities to disseminate targeted health messages to hard-to-reach individuals while engaging with the public through dynamic promotional campaigns [8, 9].
With an adequate level of health literacy, individuals are expected to be well-engaged and participate in health-related discussions, able to provide comprehensive details about specific medical conditions in the most understandable terms. This would enable smoother communication, with trust no longer being an issue for the participants involved. This is because an individual’s level of health literacy has been found to influence how much they trust various sources of health information, including healthcare providers [10]. Consequently, this situation has created two distinct perspectives on word of mouth, where the health messages shared between the parties involved may indicate whether negative or positive e-WOM has occurred. Although many companies wish to be associated with positive e-WOM from their consumers, studies have unfortunately shown that consumers are more likely to be influenced by negative e-WOM messages [11]. Nonetheless, socio-demographic factors can help turn the tide positively for both health literacy and e-WOM. Age and gender are the most common socio-demographic factors found to influence the two domains of health literacy [12] and e-WOM [13]. Therefore, this study compared the impacts of health literacy domains (health care, disease prevention, and health promotion) on e-WOM based on socio-demographic factors.
Instrument and Methods
This cross-sectional descriptive correlational research was conducted among Malaysian Internet users in Peninsular Malaysia in two months, from July to August 2024.
A proportionate quota sampling technique was applied, with each region of Peninsular Malaysia represented by 100 samples. Cumulatively, since Peninsular Malaysia comprises four major regions—Central, Southern, Northern, and East Coast—a total of 400 samples were targeted as respondents.
Although the degree of generalizability is questionable in quota sampling, it at least provides adequate statistical power to distinguish differences in groups due to its characteristic of oversampling underrepresented groups [14]. The sample size of 400 respondents was deemed appropriate in accordance with the regression analysis minimum requirement of 100 samples [15].
These respondents were respectfully approached by the researcher to voluntarily participate in the study, where they were required to complete a self-administered questionnaire consisting of 56 items. The self-administered questionnaire was constructed and adapted from two well-established instruments: the Electronic Word of Mouth Questionnaire [16] and the New Short-Form Health Literacy Instrument (HLS-SF12) [17]. This instrument employed four Likert scales of agreement, ranging from strongly agree to strongly disagree, for all items except the demographic questions. A quantitative research expert validated the content validity of this questionnaire before it was submitted for ethical review. Subsequently, the questionnaire was approved by the ethical committee, which recognized that the researcher was attentive to the issues of privacy and integrity of the collected data. Additionally, a pilot study involving 50 samples was conducted prior to the actual data collection to verify the reliability of the instrument. It demonstrated good reliability, with Cronbach’s Alpha values ranging from 0.798 to 0.90 [18].
This instrument was disseminated through various platforms, including email, WhatsApp, Telegram, and other social media. Data were collected within a single time frame of two months. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. Participants were fully informed regarding the study objectives, and written/verbal consent was obtained before the initiation of data collection. The study was conducted on a voluntary basis, with no coercion applied to participants in the research process. The strictest confidentiality of the data was maintained, and the collected data will be used only for research purposes. It took approximately three months to collect 450 responses, including the pilot study data, as some regions presented greater challenges; for instance, the northern region required almost two months to obtain a complete set of 100 responses. Nevertheless, the practicality of Google Forms significantly assisted the researcher, particularly with the ‘required’ features that enabled the collection of zero missing responses. This study predominantly involved females, accounting for 68.5% of respondents, and individuals aged 18 to 30 years made up 77.5%. This segmentation of profiles was anticipated by the researcher, as individuals aged 20 to 39 years are known to have the highest internet usage, at 99.6% [19].
SPSS 29 was used by the researcher to assist in data analysis for descriptive and multiple regression analyses, ensuring the achievement of the respective research objectives.
Findings
Males’ e-WOM was better explained by the three domains of health literacy (R²=0.505). However, the disease prevention and healthcare domains significantly influenced e-WOM among female Internet users, while health promotion was the only domain of health literacy that significantly influenced the e-WOM of male Internet users (Table 1).
Table 1. Multiple regression analysis of health literacy dimensions predicting e-WOM by gender
The health literacy of individuals aged 41-50 years or 18-30 years could explain 54.1% and 41% of their e-WOM, respectively. Additionally, all three domains of health literacy were found to significantly predict e-WOM among individuals in these age categories, with healthcare identified as the strongest predictor, followed by disease prevention and health promotion (Table 2).
Table 2. Multiple regression analysis of health literacy dimensions predicting e-WOM by age
The health literacy of individuals with secondary education, postgraduate studies, a diploma, or a bachelor’s degree could respectively explain 60.2%, 42.5%, 40.8%, and 27.5% of their e-WOM. Despite the highest R² value for secondary education, the healthcare domain was the only predictor for e-WOM, while individuals with a bachelor’s degree exhibited two domains with significant beta values, indicating two predictors for e-WOM. Specifically, disease prevention was identified as the strongest predictor of e-WOM, followed by health promotion. The bachelor’s degree category was the only one with two significant predictors, in contrast to secondary education and diploma, both of which demonstrated the healthcare domain as the sole predictor (Table 3).
Table 3. Multiple regression analysis of health literacy dimensions predicting e-WOM by education
The health literacy of individuals who were self-employed could explain 68.8% of e-WOM, while the health literacy of those who were not working, and those who were working in the private or public sectors could explain 39.2%, 27%, and 17.1%, respectively, of their e-WOM. Although the self-employed category demonstrated a higher R² value, e-WOM could only be predicted by healthcare. In contrast, the e-WOM among individuals who were not working was predicted by the disease prevention and healthcare domains. Additionally, e-WOM for both public and private sector workers was not significantly predicted by any of the health literacy domains (Table 4).
Table 4. Multiple regression analysis of health literacy dimensions predicting e-WOM by occupation
Discussion
This research compared the impacts of health literacy on e-WOM based on the socio-demographic factors of gender, age, highest education, and occupation among Internet users in Peninsular Malaysia. Most findings align with past research, indicating a closer gap in the literature review. The results from the multiple regression analyses demonstrated more significant predictive effects of health literacy domains on e-WOM among respondents who were female, aged 18-30 years, held a bachelor’s degree, and were currently not working.
Firstly, in the comparisons of gender, previous research has reported that females have a higher usage of health forums and blogs when searching for health information online [20]. Women are known to exhibit stronger traits of conscientiousness and agreeableness, which consequently incline them to be more compliant with preventive health behaviors [21]. This explains why disease prevention is the strongest predictor of their e-WOM. Regarding males, despite studies addressing the underdevelopment of their health literacy [22], they are commonly found to be poorly health literate, which negatively influences their help-seeking behavior and engagement with healthcare professionals [23].
Second, in the comparisons of age, despite individuals aged 41-50 years having the highest percentage of ICT usage for seeking health information (72%), individuals aged 20 to 39 years have the highest overall usage of the internet, at 99.6% [19]. These young individuals may not be particularly inclined to seek health information, but they have been reported to possess higher levels of health literacy [24]. Their good health literacy levels may suggest that they do not feel the need to look for health information, as they are more aware of what is happening with their health and surroundings. Young adults are usually underrepresented in health promotional activities, as they tend to be overlooked by authorities despite their societal relevance [25]. However, as they grow older, their health literacy is likely to decline significantly [24], and that is when good health-seeking behavior, including seeking health information online, becomes increasingly important.
Thirdly, in the comparisons of the highest education among the respondents, it was reported that the e-WOM of those with bachelor’s degrees can be better predicted by two out of three domains of health literacy compared to individuals with other educational attainments. Multiple past studies have previously stated how educational background can influence an individual’s level of health literacy [12, 24, 26]. While this study found a similar result regarding the predictive effects among those with bachelor’s degrees, the postgraduate studies category indicated otherwise. It was found that e-WOM could be significantly explained by the health literacy domains, but there was no single predictor among them. Inductively, this finding can be considered new information for the body of knowledge on health literacy, as postgraduate students are known to have higher health literacy levels than average [27, 28].
Additionally, there was a positive relationship between educational level and health promotional behavior, whereby lower education levels correspond to lower health promotional behavior [29]. Simply put, having a higher level of health literacy can suggest how their e-WOM may be influenced by their ability to comprehend and share health information. Lastly, in the comparisons of respondents’ occupations, there were more significant predictive effects of health literacy domains on e-WOM among those who were not working. In contrast, this finding does not align with previous research, indicating that employed individuals tend to seek more health information online compared to the unemployed [30]. However, this contradictory finding may arise from the fact that individuals who are not working have more time to use the Internet and engage in social networking through social media [31]. Consequently, there may be a significant increase in Internet usage among these individuals as they look for health information, especially regarding disease prevention. This is particularly important, as unemployed individuals may be more cautious about getting sick, given that illness could incur medical costs in addition to their usual living expenses [32].
Although there are limited studies that have compared the integration of health literacy and e-WOM, many studies have been conducted on the effects of socio-demographic factors on health literacy [12, 26, 33]. Nonetheless, it is vital to acknowledge that Malaysians’ health literacy has not been fully leveraged by the government to ensure the reliability and accuracy of the disseminated health information. This evident concern was particularly apparent during the COVID-19 pandemic when the situation of ‘infodemic’ became increasingly critical as rumors regarding health information disorders spread rapidly [34]. Accordingly, the Malaysian Communications and Multimedia Commission (MCMC) has attempted to address the issue by encouraging citizens to visit the official website ‘Sebenarnya’ to verify the factuality of the news [35]. If Malaysians can fully utilize their good health literacy to distinguish between good and bad health information during information dissemination, this would assist the government in achieving more positive health outcomes [36]. Furthermore, the significance of health literacy is prioritized by the Malaysian government, as it is highlighted in the Healthy Malaysia National Agenda (ANMS) 2020-2030, which established the National Health Literacy Policy (DLKK) in 2024. The agenda aims to empower Malaysians to take responsibility for their health-related decision-making by adopting a healthier lifestyle [37]. Regardless of socio-demographic factors, the government should take advantage of the importance of health literacy to shift society’s e-WOM toward a positive transmission process.
Hence, this study recommends that the Malaysian government, specifically the public health authorities, consistently empower society and the public regarding the importance of using social media to share reliable and accurate health information. This suggestion aligns with the DLKK, particularly the 9th initiative, which emphasizes the significance of community support in strengthening the health literacy capacities of the community [37]. This initiative highlights the importance of organizing community empowerment activities that align with the strengths of health literacy, enabling the public to take charge of their own health-related decision-making. Nonetheless, this empowerment initiative is particularly ineffective without a strong foundation in health literacy. This is because social media users may be distracted by peripheral information, which can hinder their processing of intended health messages [38], consequently creating problems for those with low health literacy. On the other hand, future studies are recommended to conduct comparative research based on household income as one of the parameters, as it is one of the most influential factors affecting health literacy. Future researchers may also apply probability sampling techniques, such as proportionate stratified random sampling, to avoid instances of sampling bias in selecting the targeted respondents.
Gender, age, highest education, and occupation were the socio-demographic factors compared, in line with previous studies’ findings, indicating that they are the most commonly identified influential factors of health literacy. The three domains of health literacy better explained e-WOM among respondents who were male, aged 41 to 50 years, had secondary education, and were self-employed. Nonetheless, more significant predictive effects of health literacy domains on e-WOM were found among respondents who were female, aged 18-30 years, held a bachelor’s degree, and were currently not working.
Conclusion
Gender, age, highest education, and occupation are influential factors of health literacy.
Acknowledgments: We would like to thank the Malaysian Ministry of Higher Education, Universiti Teknologi MARA (UiTM), and the Research Management Centre (RMC) of UiTM for funding this study through internal grant DUCS-F 600-UiTMSEL (Pl. 5/4) (100/2022).
Ethical Permissions: Ethical approval was obtained from the UiTM Research Ethics Committee [Code: REC/02/2023 (ST/MR/45)].
Conflicts of Interests: There are no conflicts of interests.
Authors' Contribution: Sumardi NA (First Author), Introduction Writer/Methodologist/Main Researcher/Discussion Writer/Statistical Analyst (100%)
Funding/Support: Special gratitude goes to the Malaysian Ministry of Higher Education, Universiti Teknologi MARA (UiTM), and the Research Management Centre (RMC) of UiTM for funding this study through internal grant DUCS-F 600-UiTMSEL (Pl. 5/4) (100/2022).