Mitigating the digital divide: exploring moderation and mediation effects on eHealth performance in a comparative study of Europe and Southeast Asia

Introduction

The integration of digital technologies into healthcare, commonly referred to as eHealth, has emerged as a transformative force in the delivery of health services worldwide. This study emphasizes the importance of understanding the multifaceted determinants that influence eHealth performance. As healthcare systems increasingly adopt digital solutions, disparities in eHealth adoption and effectiveness between developed regions, such as Europe, and developing regions, such as Southeast Asia, underscore the need for comprehensive research.

The digital divide in eHealth reflects unequal access to and adoption of digital technologies across different populations and regions (1). In Europe, advanced technological capabilities and well-formulated policies facilitate the seamless integration of eHealth solutions. Conversely, Southeast Asia faces challenges due to varying technology utilization rates, economic resources, and unequal internet accessibility. The coronavirus disease 2019 (COVID-19) pandemic has further highlighted these disparities, as countries with robust digital infrastructure effectively provided telehealth services while those with limited capacities struggled.

This study aims to understand the direct impact of E-government development on eHealth performance, with digital literacy as a mediating factor. E-government development is the integration of information and communication technology (ICT) into government processes to enhance service delivery, efficiency, transparency, and citizen engagement. It facilitates digital interactions, improves access to services, streamlines operations, encourages citizen participation, and adapts to technological advancements for better governance outcomes (2). Digital literacy refers to individuals’ ability to effectively use digital health technologies. By exploring how digital literacy influences the integration of technology and eHealth performance, this study seeks to provide insights into improving healthcare access and quality. Additionally, religious beliefs are examined as a moderating variable that can significantly affect interactions with eHealth. These beliefs influence health decisions and acceptance of medical interventions, underscoring the need for culturally sensitive approaches in eHealth strategies.

This investigation is significant because it highlights the necessity of integrating digital literacy initiatives into eHealth strategies while considering the cultural and religious nuances that may affect technology adoption. The role of religious beliefs is particularly crucial, as they can significantly shape individuals’ perceptions and interactions with eHealth technologies. By examining these dimensions, the findings are intended to inform policymakers and healthcare practitioners about effective strategies for improving eHealth outcomes, especially in regions facing infrastructural and cultural challenges.

Theoretical background and hypotheses

The literature surrounding eHealth has evolved significantly, reflecting the growing importance of digital technologies in healthcare delivery. Central to this discourse is the examination of E-government development, digital literacy, and religious beliefs as key determinants influencing eHealth performance. This literature review synthesizes existing research, highlighting the interconnectedness of these factors and their implications for healthcare accessibility and quality.

E-government development and eHealth performance

E-government development plays a crucial role in enhancing eHealth performance by strategically implementing digital governmental services and infrastructure to improve healthcare delivery and outcomes. This integration utilizes digital technologies and online platforms to optimize healthcare access, delivery, and management. eHealth performance is fundamentally linked to the effectiveness and efficiency of eHealth solutions in enhancing healthcare delivery and outcomes (3). Various eHealth technologies, such as Telehealth, mHealth, Health Analytics, and Digital Health Systems, empower individuals, improve patient-provider interactions, streamline data management, and enhance clinical decision-making (4,5).

Integrating eHealth solutions with robust E-government platforms ensures secure access to healthcare services. Government-backed health portals improve data exchange among providers, maximizing the potential of digital health solutions. This integration is globally recognized for its transformative impact on healthcare services (6). In developed nations, E-government strategies prioritize enhancing service efficiency and accessibility. Through adept use of digital tools, these countries facilitate healthcare access, bolster data management, and support personalized healthcare delivery via real-time monitoring, telemedicine, and advanced data analytics.

In contrast, developing countries encounter considerable challenges in the healthcare sector, mainly due to insufficient resources and infrastructure to support comprehensive E-government solutions (7). This shortfall impedes the seamless integration of digital services into healthcare systems, resulting in ongoing disparities in access to quality care. Without robust E-government initiatives, individuals in remote areas may not have access to telemedicine or mHealth applications. Additionally, the lack of government-backed health portals exacerbates these disparities, limiting access to essential eHealth resources like health analytics and digital health systems (8). Consequently, healthcare delivery in these regions struggles with inadequate facilities and a shortage of skilled professionals, perpetuating the healthcare access gap. Based on the literature, this study proposes:

Hypothesis 1: The level of E-government development positively influences eHealth performance.

The assessment of E-government development relies on the E-government Development Index (EGDI), a robust tool measuring a nation’s progress in E-government initiatives as defined by the United Nations. Comprising three key components (Online Service Index, Telecommunication Infrastructure Index, and Human Capital Index), EGDI offers a comprehensive evaluation of a nation’s E-government capabilities. To evaluate the eHealth performance within a country, this study utilizes a vital eHealth Market metric involving user engagement and revenue generation across four specific categories: eHealth Devices, eHealth Applications, Online Pharmacy platforms, and Online Doctor Consultation services. These categories encompass various devices and applications aimed at monitoring and analyzing lifestyle-related parameters, ultimately enhancing users’ overall well-being. By standardizing eHealth market revenue through logarithmically transformed revenue data, this approach enables a comprehensive assessment of the relative economic significance of eHealth activities within national economies.

The role of digital literacy

eHealth performance is intrinsically linked to the critical concept of digital literacy. Digital literacy, defined as individuals’ proficiency in using digital technologies effectively, plays a crucial role in realizing the full potential of eHealth initiatives (9). It empowers individuals with the skills necessary to navigate eHealth platforms, access vital healthcare information, and actively participate in telemedicine consultations (10). The effective utilization of digital health technologies is contingent upon individuals’ digital literacy, which manifests in various ways within the healthcare context.

When assessing the integration of ICT in healthcare, it is essential to consider individuals’ capacity to navigate digital platforms and access online healthcare resources. For instance, in the context of telemedicine, patients’ digital literacy is pivotal for engaging in remote healthcare consultations and communicating health concerns effectively. In the realm of mobile health (mHealth), digital literacy significantly influences the efficacy of solutions, as users’ ability to understand health data and implement recommended actions is vital. Researchers have indicated a positive correlation between digital literacy and health-related behaviors, suggesting its potential role as a mediator in translating health information into behavioral changes (11). Those with higher levels of digital literacy can effectively utilize E-government platforms, contributing to more accurate healthcare data and improved health trends (10). Conversely, regions with lower digital literacy may struggle to fully utilize these platforms, potentially leading to disparities in healthcare access (12).

Bridging the digital literacy gap is crucial for maximizing the effectiveness of E-government initiatives in enhancing healthcare accessibility and eHealth performance. Public education investments improve digital literacy, particularly in using online government services, through targeted training programs that equip citizens with essential skills. Higher digital literacy correlates with increased E-government service utilization, improving access to resources (13). Additionally, addressing barriers through community engagement fosters inclusive educational strategies (14). Ultimately, enhanced digital literacy empowers individuals to utilize eHealth resources effectively, leading to better healthcare outcomes and more efficient service delivery (15). Based on the literature review, this study proposes:

Hypothesis 2: Digital literacy mediates the relationship between E-government development and eHealth performance.

The assessment of digital literacy incorporates the utilization of the Network Readiness Index (NRI), a composite index comprising three hierarchical levels (16). These levels are organized around fundamental pillars that encompass various dimensions of network readiness, including aspects pertaining to technology, human capital, and governance. By scrutinizing these aspects, the NRI provides valuable insights into the scope of digital literacy and the overall digital readiness within each nation. This comprehensive evaluation of eHealth performance, integrating the dimension of digital literacy, offers valuable insights into the alignment between technology and users’ capabilities. Consequently, this contributes to the formulation of more effective and inclusive healthcare strategies.

Influence of religious beliefs

In the realm of eHealth, the influence of religious beliefs emerges as a compelling variable that significantly shapes individuals’ perceptions and interactions with digital health technologies. Religious convictions can guide health-related decisions and influence the acceptability of certain medical interventions or technological applications (17). For some individuals, religious teachings may serve as a framework for making healthcare choices, while for others, specific doctrines may prohibit certain medical procedures, leading them to decline eHealth interventions that contradict their beliefs (18).

The impact of religious beliefs on healthcare decision-making is critical to understanding eHealth performance. Individuals’ religious convictions can profoundly affect their acceptance or rejection of medical treatments and interventions. For instance, certain religious doctrines may prevent individuals from accepting specific medical procedures, which can result in hesitance towards eHealth solutions that conflict with their teachings (19). Additionally, religious norms may dictate preferences for traditional healthcare practices over eHealth alternatives (20). Conversely, religious teachings that emphasize the sanctity of the body and the importance of health preservation may motivate individuals to seek healthcare solutions, including eHealth options, to maintain their overall well-being (21).

The interaction between religious beliefs and the utilization of eHealth resources adds an intricate layer to the assessment of eHealth performance. Studies have shown that religious beliefs can moderate the relationship between eHealth utilization and healthcare outcomes (22). In instances where eHealth interventions are perceived to conflict with religious teachings, individuals may hesitate to embrace these technologies, even when they could enhance their health outcomes. Conversely, individuals whose religious beliefs align with certain eHealth practices may be more inclined to engage with these technologies, thereby showcasing the moderating effect of religious convictions on eHealth performance (23).

The influence of religious beliefs on eHealth performance varies across cultural and societal contexts. Cultural norms, social structures, and regional factors interact with religious convictions to shape healthcare choices and eHealth utilization patterns. In some cultures, religious practices are deeply embedded in healthcare rituals, affecting receptivity to eHealth interventions. In contrast, areas characterized by prominent secularism may experience a diminished influence of religious beliefs on eHealth performance. Furthermore, studies suggest that industrialized nations are transitioning towards secular-rational values (24), which can challenge established religious institutions and complicate the alignment of religious beliefs with healthcare ideals (25).

Additionally, the impact of spirituality on mental health in Thailand illustrates the importance of integrating culturally sensitive eHealth interventions. Thongsalab (26) revealed that traditional therapies, such as temple-based treatments, highlight the influence of religious beliefs and stigma on attitudes toward mental health services. Similarly, highly religious doctors in Brazil may face challenges stemming from their beliefs when addressing spiritual aspects within healthcare (27). These case studies emphasize the need to consider cultural and societal contexts when assessing the moderating role of religious beliefs on eHealth adoption and performance (28). Based on the literature review, this study proposes:

Hypothesis 3: Religious beliefs moderate the relationship between E-government development and eHealth performance.

One approach to assessing religious beliefs within the context of eHealth is to consider the percentage of the largest religious population within a specific region or country, offering insights into the prominence of a specific faith and its potential implications for healthcare decisions. Furthermore, categorizing religious beliefs into distinct denominations or groups allows for a more nuanced exploration of how different religious communities may uniquely approach healthcare and eHealth solutions. Contrasting majority religious beliefs with those of minority or non-religious groups can uncover variations in healthcare attitudes and behaviors, thereby enriching the understanding of the interplay between religion and eHealth performance.

The literature review explores the intricate relationships among E-government initiatives, digital literacy, religious beliefs, and their implications for healthcare outcomes, with a particular focus on eHealth performance. E-government development significantly influences healthcare accessibility, while digital literacy plays a pivotal role in shaping individuals’ engagement with eHealth. Furthermore, religious convictions impact healthcare decision-making, influencing the utilization of eHealth services. An in-depth examination of these dimensions reveals the intricate nature of contemporary healthcare and its critical connection to eHealth performance. The conceptual framework is illustrated in Figure 1.

Figure 1 Conceptual framework of this study. EGDI, E-government Development Index; NRI, Network Readiness Index.

Methods

Study design

This study conducted a quantitative analysis using secondary data from European and Southeast Asian countries. Regression analysis was employed to assess the direct impact of E-government on eHealth performance, considering digital literacy as a mediating factor. The panel data analysis method combines time series and cross-sectional data, enabling researchers to study dynamics over time while examining multiple entities.

Data sources

Data were sourced from official health agencies, international organizations, academic publications, and databases. The dataset spans 2019 to 2022 due to the COVID-19 pandemic, which made the digital divide in eHealth more apparent, ensuring the use of recent information. A total of 31 countries from Europe and Southeast Asia were selected based on geographic diversity, encompassing both developed and emerging economies. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The Ethics Committee in Human Research, National Institute of Development Administration granted an ethical exemption for this research (Protocol ID No. ECNIDA 2023/0179). Since all data are obtained from publicly accessible databases, informed consent is not required for this research. The data supporting the findings of this study were obtained from the following sources:

• eHealth Performance: Statista Digital Health Overview
• E-Government Development: UN E-Government Report
• Digital Literacy: Surfshark Digital Literacy Report
• Religion: Pew Research Religious Composition Data

This selection enables the study to assess varying levels of eHealth infrastructure, economic development, and cultural diversity. The dataset consists of 496 observations (31 countries × 4 years × 4 indicators). The descriptive statistics was shown in Table 1.

Key variables and measurements

The study assesses E-government’s direct impact on eHealth performance using market values from Statista and the EGDI from the UN. To enhance statistical robustness, indirect effects of digital literacy and religious beliefs are explored. Digital literacy is evaluated using the Network Readiness Index (NRI) from the World Economic Forum, reflecting a country’s digital ecosystem, including infrastructure, affordability, and policy support. Higher NRI scores indicate better digital access, skill development, and policy support, fostering an environment conducive to digital literacy and improved eHealth performance. NRI also drives E-government development, promoting citizen engagement and socioeconomic advancement through digital platforms.

For the moderating variable of religious beliefs, this study sought to explain their role in shaping attitudes and behaviors related to eHealth adoption. Recognizing that religious values and norms can influence healthcare decision-making and trust in digital health systems is essential. Data from the Pew Research Center’s Religious Composition by Country were employed, coupled with coding for different religions (i.e., 1 = Christianity, 2 = Islam, 3 = Buddhism, and 4 = Atheism), to enhance understanding of how religious beliefs impact eHealth performance.

In Table 1, Bulgaria serves as an example to illustrate several key indicators. The eHealth Performance score of 0.0483 reflects the average revenue generated by Bulgaria’s eHealth sector as a percentage of the nation’s total GDP from 2019 to 2022, highlighting the economic significance of eHealth services within the broader economy. The E-Government Development score of 0.742, averaged over the same period, assesses the country’s E-government infrastructure and service readiness on a scale from 0 to 1, with higher scores indicating enhanced capabilities. This score underscores Bulgaria’s commitment to delivering accessible and well-developed online public services, including government portals and digital citizen interactions. The Digital Literacy score of 0.63 evaluates overall digital literacy in Bulgaria on a scale from 0 to 1, considering factors such as internet affordability, quality, electronic security, and access to digital services. Additionally, the Religion score of 0.8 indicates that approximately 80% of Bulgaria’s population identifies as Christian (Code 1), a demographic factor that significantly shapes cultural and social norms within the country.

Statistical analytic strategies

Typically, when dealing with panel data, researchers consider three types of regression methods: Pooled Ordinary Least Squares (POLS), fixed-effects models, and random effects models. However, because POLS primarily accounts for dependencies between entities while neglecting time and individual characteristics, it may not be suitable for this study’s objectives. Consequently, a choice had to be made between fixed-effects and random effects models for this analysis.

Selecting the appropriate regression model for panel data involved three phases. First, heteroskedasticity in the panel data was examined using Stata to avoid violations of regression assumptions (29). Next, the Hausman Test (30) was used to compare fixed and random effects models; if the null hypothesis was rejected (P<0.05), a fixed-effects model was chosen. Fixed effects account for unobserved heterogeneity, while random effects assume randomly distributed individual effects (31). Following model selection, entity and time fixed effects were evaluated with and without control factors to achieve ceteris paribus conditions. Finally, the mediator (NRI) and moderator (religion) variables were introduced to explore their influence on the relationship between EGDI and eHealth performance. The Hausman test evaluates estimator significance, indicating fixed effects if random effects are inconsistent (32). These theoretical foundations are supported by literature grounding the methodology to yield meaningful insights.

Results

Phase 1

Figure 2 is the output of heteroskedasticity tests. The F statistic is 1.64 with an associated P value of 0.1991, which is greater than the significance level of 0.05. Similarly, the Breusch-Pagan test yields a P value of 0.8105, also exceeding the 0.05 threshold. Both tests indicate that there is no evidence of predictability in error variance, confirming the absence of heteroskedasticity. Therefore, the assumption of constant error variance is met in this regression analysis.

Figure 2 Results of heteroskedasticity tests. EGDI, E-government Development Index; MS, mean square; MSE, mean squared error; NRI, Network Readiness Index; SS, sum of squares.

After confirming no heteroskedasticity, the Hausman test decides between fixed and random effects models. Results show a P value of 0.01 (χ² test), favoring fixed effects due to endogeneity. Therefore, the fixed-effects model is chosen for regression, outlined in Figure 3.

Figure 3 Hausman test results for model selection. EGDI, E-government Development Index; NRI, Network Readiness Index.

Phase 2

The fixed effects model was carried out in Stata, focusing on eHealth performance as the dynamic outcome variable with EGDI serving as the time-varying predictor. Additionally, it explores the potential mediating effect of digital literacy. The output was shown in Table 2.

The R-squared estimates the proportion of the variance in the dependent variable that is explained by the independent variable. Table 1 displays four R-squared values for distinct models, varying in fixed-effects inclusion. Models 1 and 2 utilize nation fixed-effects, while models 3 and 4 integrate both nation and time fixed-effects. A comparison reveals model 4 (0.8773) as markedly enhancing model fit. By accounting for time-invariant and time-varying unobserved heterogeneity, model 4 enhances precision and accuracy in estimating EGDI’s impact on eHealth performance.

Essentially, in model 4, it becomes evident that EGDI exerts a positive and statistically significant influence on eHealth performance (β=1.1931, P<0.01). This suggests that, within a particular nation, a 1-unit change in EGDI over time corresponds to an expected increase of 1.1931 in eHealth performance. Furthermore, the study extends the analysis by regressing eHealth performance on the interaction of EGDI and NRI, as illustrated in Figure 4. The findings indicate a significant indirect effect of EGDI on eHealth performance through NRI mediation, with a coefficient of 0.45 (0.63×0.72).

Figure 4 Mediating outcome in the research model. EGDI, E-government Development Index; NRI, Network Readiness Index.

Phase 3

This study examined religion as a moderator between EGDI and eHealth performance. A moderator affects the strength or direction of this relationship (33). Even if religion’s direct effect isn’t significant, inferences about its moderating role can be made if EGDI is statistically significant. The results in Figure 5 show that within R-squared of 0.8807, indicating that the model explains a substantial portion of the variance in the eHealth market. Additionally, the low P value (P<0.001) suggests that the model is statistically significant, meaning that at least one of the predictors is related to the eHealth market. Among these interaction terms (EGDI with different religious beliefs), only the interaction with Religion4 (i.e., Atheism) is significant (β=2.6799, P=0.007), suggesting that the interaction between EGDI and Atheism has a significant and positive effect on the eHealth market. In other words, the presence of Atheism seems to have a strong influence on the relationship between EGDI and the eHealth market.

Figure 5 Moderating effects of religious beliefs on eHealth market. EGDI, E-government Development Index; NRI, Network Readiness Index.

In summary, the regression results from the fixed effects models, alongside the mediating and moderating effects of digital literacy and religious beliefs, provide valuable insights into the dynamics of eHealth performance in the context of Europe and Southeast Asia.

Fixed effects models

The fixed effects model was selected based on the Hausman test findings, which showed notable endogeneity issues. This preferred the fixed effects approach to account for unobservable, country-specific factors that remain constant over time. This model allows for a nuanced understanding of how EGDI influences eHealth performance over time, revealing a positive and statistically significant relationship (β=1.1931, P<0.01). This suggests that a 1-unit increase in EGDI correlates with a 1.1931 increase in eHealth performance, emphasizing the critical role of government initiatives in enhancing healthcare accessibility and outcomes. Research has shown that effective government policies can significantly impact eHealth adoption rates and overall health outcomes (34).

Mediating effect of digital literacy

The study further extends the analysis by examining the interaction between EGDI and the NRI, which serves as a proxy for digital literacy. The significant indirect effect of EGDI on eHealth performance through NRI (β=0.45) highlights the importance of digital literacy in mediating the relationship between government development and healthcare outcomes. This finding aligns with existing literature that emphasizes the role of digital literacy in enabling effective eHealth utilization. For instance, studies have shown that higher levels of digital literacy facilitate better access to eHealth services, ultimately leading to improved health outcomes (17,35). Additionally, researchers emphasize the necessity of enhancing digital health literacy among healthcare professionals to overcome barriers in adopting digital health tools (36).

Moderating effect of religious beliefs

The analysis also explores the moderating role of religious beliefs in the relationship between EGDI and eHealth performance. The results indicate that while religion’s direct effect may not be significant, its moderating influence is pronounced, particularly with Atheism (β=2.6799, P=0.007). This suggests that in contexts where Atheism is prevalent, the positive impact of EGDI on eHealth performance is enhanced. This finding resonates with research suggesting that societies with less religious influence tend to adopt eHealth technologies more readily, as there may be fewer cultural barriers to digital health initiatives (37). Bal and Kökalan (38) examined how cultural and religious contexts can significantly influence the acceptance of eHealth technologies, indicating that lower religiosity may facilitate greater openness to digital health solutions.

The context of Europe and Southeast Asia

These findings underscore the importance of tailoring eHealth strategies to account for both digital literacy and religious beliefs. In Europe, where digital literacy rates are generally higher, enhancing E-government initiatives can effectively improve eHealth outcomes. For instance, researchers highlight that healthcare professionals’ adoption of eHealth technologies is significantly influenced by their digital literacy levels, suggesting that enhancing these skills can lead to better health outcomes in European countries (39). Conversely, in Southeast Asia, where digital literacy may vary significantly, targeted educational programs could be essential for maximizing the impact of E-government on eHealth performance. While there is a growing interest in eHealth in Southeast Asia, there are considerable gaps in digital literacy that must be addressed through tailored educational initiatives (40).

Discussion

This study underscores the multifaceted nature of eHealth determinants, revealing that E-government development, digital literacy, and religious beliefs play interconnected roles in shaping eHealth performance across Europe and Southeast Asia. The findings demonstrate that while E-government development significantly influences eHealth outcomes, it does not operate in isolation. The positive relationship observed between the EGDI and eHealth performance indicates that effective government digital services can enhance healthcare accessibility and quality. However, the study emphasizes that improved E-government alone is insufficient for achieving superior eHealth performance.

The mediating effect of digital literacy is particularly noteworthy. The significant indirect relationship between EGDI and eHealth performance through digital literacy highlights the necessity of equipping populations with the skills and knowledge to effectively utilize eHealth services. This finding suggests that digital literacy programs should be integrated into eHealth strategies, ensuring that individuals are not only provided with access to digital health resources but also possess the competencies to navigate and utilize these technologies effectively. Policymakers should prioritize educational initiatives that foster digital literacy, particularly in regions where technological infrastructure is being developed.

Furthermore, the exploration of religious beliefs as a moderating factor adds another layer of complexity to the understanding of eHealth dynamics. The study found that Atheism significantly moderates the relationship between E-government development and eHealth performance, indicating that regions with lower levels of religious adherence may be more receptive to adopting eHealth solutions. This suggests that cultural and religious contexts can influence the acceptance and utilization of digital health technologies. In contrast, areas with strong religious influences may encounter resistance to modern healthcare innovations, as traditional beliefs and practices can shape individuals’ willingness to embrace technology-driven solutions.

While this study highlights the positive impact of Atheism on eHealth performance, it is essential to recognize that other religious beliefs, such as Christianity, Islam, and Buddhism, may also play significant roles in shaping attitudes toward digital health services. Each of these religions encompasses unique cultural values and norms that can influence healthcare decision-making and technology adoption. For instance, Christianity’s emphasis on community and care may encourage the use of eHealth resources among its followers, while Islamic teachings regarding health and well-being could affect perceptions of digital health initiatives. Similarly, Buddhist principles of mindfulness and holistic health might impact how eHealth services are perceived and utilized. Therefore, further investigation into the effects of these diverse religious beliefs is warranted to develop a more comprehensive understanding of their influence on eHealth performance.

The implications of this study are threefold, encompassing implications for policymakers, practitioners, and researchers. For policymakers, while enhancing the E-government development is crucial, parallel efforts should concentrate on advancing digital literacy. The study’s findings offer guidance to policymakers that tailoring eHealth strategies should consider the religious landscape. In regions where religiosity is low, focusing on the digital divide and ensuring equitable access to eHealth resources is top priority. However, in regions with strong religious influences, strategies must also navigate the complex terrain of religious beliefs to bridge the gap in healthcare access. Additionally, in regions where Atheism is prevalent, there exists an opportunity for significant expansion in the eHealth market by investing in digital health infrastructure and services. The interaction between E-government development and Atheism suggests for practical strategies in eHealth market and presents a promising area for academic exploration that could reshape both policy and theory in this domain.

For practitioners, healthcare providers must integrate digital literacy and health education into their services, providing patients with essential training in eHealth resources and digital tools. Ethical awareness is crucial as healthcare professionals implement eHealth solutions, considering the impact of religious beliefs on patient perspectives and preferences in digital healthcare provision. From a practical standpoint, while the findings are nuanced, they suggest that healthcare practitioners should consider the diverse religious landscape when designing and implementing eHealth interventions. Customized approaches that account for regional variations in religious beliefs may be more effective in promoting eHealth adoption and improving healthcare outcomes. In addition, the findings provide market stakeholders with valuable insights that resource allocation decisions should consider religious demographics. Higher E-government development regions in Atheist-majority areas could see improved eHealth market outcomes. Targeted initiatives may yield greater returns.

For researchers, scholars may investigate the specific aspects of digital literacy with the most significant impact while identifying potential confounding factors is essential. Additionally, it is imperative to broaden the examination of various religious beliefs’ moderating effects and their implications for eHealth within culturally diverse contexts. This finding prompts a reconsideration of how religious beliefs interact with socioeconomic factors in shaping eHealth outcomes. Different regions may have distinct healthcare systems, levels of digital infrastructure, and religious compositions. Moreover, the non-significant findings for Christianity, Islam, and Buddhism in this study may reflect the specific context under investigation. Therefore, a thorough investigation of the complex mechanisms underlying this phenomenon is of significant academic value, with a particular emphasis on elucidating why Atheism appears to have a distinct and positive influence on eHealth market performance in response to the growth of E-government development.

Conclusions

The study’s conclusion highlights the complex interplay shaping eHealth performance, revealing the joint influence of E-government development and digital literacy. Particularly, in regions with prevalent Atheism, E-government advancement notably increases eHealth market performance. This underscores the role of advanced digital infrastructure and literacy in enhancing healthcare accessibility, particularly in Atheism-dominant areas. The findings advocate for tailored strategies considering cultural and religious diversity in eHealth adoption. Moreover, the research enriches the discourse on digital healthcare across Europe and Southeast Asia, offering crucial insights for policy and theoretical advancements in the eHealth sector.

Nonetheless, it is essential to recognize the limitations of this study. A primary concern is the focus on indirect variables, particularly regarding digital literacy. While the study emphasizes its mediating role, the complexity of digital literacy suggests that other factors may also exert indirect influences, potentially leaving important dimensions unexamined. For instance, investigating how technological access influences user engagement with eHealth services or examining how security awareness impacts trust in digital health platforms would provide valuable insights. Employing methodologies such as qualitative interviews or surveys could further illuminate users’ experiences with various aspects of digital literacy and their corresponding effects on eHealth performance.

Similarly, the exploration of religious beliefs may not fully capture the intricate relationships among various belief systems, as the study primarily addresses their moderating effects and may overlook compound or indirect impacts on eHealth performance. For instance, it is crucial to recognize the significant influence of religious beliefs with cultural values on health behaviors and technology acceptance. Engaging religious leaders and communities may enhance the acceptance of eHealth initiatives, particularly in regions with strong religious connections, such as those influenced by Islam or Christianity. Working together on strategies, such as promoting eHealth services through cultural events and religious sermons, can help build trust and encourage people to use these services. Future research may examine how these factors can affect the development of eHealth resources to create culturally sensitive interventions that meet the health needs of diverse populations.

Additionally, it is important to acknowledge that the sample size of 31 countries may limit the generalizability of the findings. While this selection allows for a focused analysis of diverse socio-cultural variables such as digital literacy and religious beliefs, it may not fully represent the global landscape. Future research should aim to expand the sample size by including a broader geographical coverage or analyzing additional countries. This approach would enhance the robustness of the findings and provide a more comprehensive understanding of how these socio-cultural factors influence eHealth performance across different contexts. By broadening the scope of future studies, the outcomes contribute to a deeper and more nuanced understanding of the complex interplay between socio-cultural variables and eHealth outcomes.

Finally, the study’s narrow scope regarding variables and conceptual models may have simplified the analysis. Concentrating on specific variables such as digital literacy and religious beliefs could limit the understanding of the broader spectrum of factors affecting eHealth outcomes. Consequently, the models employed may not adequately reflect the complexity of interactions among these determinants. This observation underscores the importance of conducting more comprehensive research that includes a wider variety of variables. For example, integrating additional unobserved variables such as government openness and corruption levels could enhance the understanding of the institutional and regulatory factors that affect key outcomes. These factors are significant in shaping policy implementation, public trust, and operational transparency, all of which are essential for understanding complex socioeconomic dynamics. This broader perspective may help clarify their impact on EGDI and eHealth performance.

Acknowledgments

None.

Footnote

Peer Review File: Available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-24-67/prf

Funding: None.

Conflicts of Interest: The author has completed the ICMJE uniform disclosure form (available at https://mhealth.amegroups.com/article/view/10.21037/mhealth-24-67/coif). The author has no conflicts of interest to declare.

Ethical Statement: The author is accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The Ethics Committee in Human Research, National Institute of Development Administration granted an ethical exemption for this research (Protocol ID No. ECNIDA 2023/0179). Since all data are obtained from publicly accessible databases, informed consent is not required for this research.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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