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Abstract

Objective

As digital therapeutics (DTx) continue to expand globally, understanding user-related factors that influence adoption is critical. This study investigates how digital literacy, trust in online information, and privacy concerns shape individuals’ intentions to use digital therapeutics, drawing on the technology acceptance model (TAM).

Methods

An online survey was conducted in South Korea, targeting adult participants aged 20 to 69. A total of 600 responses were analyzed. Digital literacy, online information trust, privacy concern, perceived usefulness, perceived ease of use, and DTx use intention were measured using previously validated multi-item Likert scales. Relationships among the variables were analyzed using path analysis and bootstrapping.

Results

Digital literacy (β = 0.13, p < .01) and online information trust (β = 0.10, p < .01) positively influenced DTx use intention. Digital literacy also predicted higher privacy concern (β = 0.31, p < .01), which in turn positively affected perceived usefulness (β = 0.22, p < .001). Perceived usefulness (β = 0.48, p < .001) and ease of use (β = 0.23, p < .001) significantly predicted use intention. The model explained 56.4% of the variance in DTx use intention (R² = .564).

Conclusion

The findings highlight the complex interplay among digital literacy, trust, and privacy in influencing DTx adoption. Emphasis on user-centered design, strong privacy protection, and digital literacy education will be essential for fostering broader acceptance of digital therapeutics.

Keywords

Digital therapeutics digital literacy privacy concern online information trust technology acceptance model

Introduction

In recent years, the issue of public awareness and acceptance of digital therapeutics (DTx) has emerged as a key concern, as these technologies offer novel approaches to improving human well-being across various aspects of life.^1,2 Due to the nature of digital therapeutics, which often involve the collection, storage, and analysis of sensitive personal health data, concerns about data privacy, security breaches, and unauthorized access may pose substantial barriers to their adoption.^3,4

This issue is particularly relevant in South Korea, a technologically advanced society experiencing rapid digitalization in the healthcare sector. While digital health innovations are gaining momentum, public concerns about data protection, trust in digital information, and technology readiness remain significant challenges to widespread adoption.

Previous research in South Korea has identified public perceptions of digital therapeutics along seven dimensions: regulation, cost-effectiveness, health benefits, medical concerns, device trust, health inequality, and health literacy.⁵ These perceptions have been found to directly influence the intention to use DTx. In particular, digital literacy and privacy concerns play a significant role in shaping such perceptions.

Building on these findings, the present study aims to further explore the determinants of DTx use intention, going beyond general perception and addressing the complex interplay among digital literacy, online information trust, and privacy concerns. These factors are believed to negatively influence the perceived ease of use and usefulness of DTx, thereby creating psychological and behavioral barriers to technology adoption—even when users acknowledge potential benefits.

In this context, the technology acceptance model (TAM) offers a robust theoretical framework, emphasizing the importance of perceived usefulness and perceived ease of use in technology adoption. This study adopts TAM not to extend it with novel constructs, but to use it as a conceptual lens to explain how key external factors—digital literacy, online information trust, and privacy concerns—relate to users’ perceptions and behavioral intentions regarding digital therapeutics.

By integrating these constructs into the TAM framework, the study seeks to clarify the mechanisms through which external sociotechnical factors shape technology acceptance. The goal is to contribute to the existing body of knowledge by applying TAM to a new and timely context—digital therapeutics in South Korea—while addressing specific barriers to adoption rooted in user perceptions and trust.

Furthermore, the findings aim to support the development of strategic health communication and system design approaches that can enhance public acceptance and foster a more effective and user-centered digital healthcare environment.

Theoretical and empirical background

Technology acceptance model (TAM) and digital literacy

The TAM was originally developed to identify the factors that influence users’ acceptance of information technologies introduced to improve organizational performance.⁶ It has been widely applied to investigate the adoption of computer-based technologies, services, and software systems. The model comprises two primary belief-based constructs: perceived usefulness and perceived ease of use. Perceived usefulness refers to the degree to which an individual believes that using a particular system will enhance their work performance, while perceived ease of use refers to the belief that the use of the system will not require significant physical or mental effort.

Extensive empirical research has demonstrated that these two beliefs influence users’ attitudes and behavioral intentions toward new technologies, either directly or indirectly. As TAM has been applied across various domains, it has evolved through the incorporation of additional variables. Research has explored individual-related factors such as gender, age, ethnicity, prior experience, innovativeness, and self-efficacy, as well as technology-related attributes, contextual conditions like socioeconomic status, and subjective norms.⁷ These extensions underscore the complexity of technology acceptance and the necessity of considering diverse user characteristics and environmental influences.

In the context of TAM, perceived ease of use is one of the most significant predictors of technology adoption, and digital literacy plays a critical role in shaping this perception. Prior research on Korean users has identified three dimensions of digital literacy: the ability to utilize information, the capacity for creative digital production, and proficiency in digital communication.⁸ These dimensions of digital literacy have been shown to significantly influence the intention to adopt digital therapeutics, although generational differences have been observed. For younger generations such as Millennials and Generation Z, higher digital literacy is associated with stronger intentions to use digital therapeutics. In contrast, among the Baby Boomer generation, digital literacy does not directly affect usage intention. Instead, it enhances favorable perceptions of digital therapeutics, which in turn influence the intention to use them.⁵

This finding suggests that individuals with high levels of digital literacy are more likely to perceive digital health platforms as intuitive and user-friendly, leading to a stronger sense of perceived ease of use. They are also more capable of navigating digital systems, understanding their functions, and independently resolving minor issues, which contributes to a more positive user experience overall. Furthermore, digital literacy can also enhance perceived usefulness, the other key construct of TAM. Users who are proficient in digital technologies are better positioned to comprehend the benefits and potential of digital therapeutics, thereby developing more favorable beliefs about their utility. Previous studies have confirmed that digital literacy significantly influences both perceived ease of use and perceived usefulness, which in turn shape users’ behavioral intentions to adopt new technologies.^9,10 Similarly, research by Ghazizadeh, Lee, and Boyle¹¹ emphasizes that individuals with higher digital literacy are more likely to embrace digital health technologies and demonstrate more positive attitudes toward their adoption.

Based on these theoretical and empirical insights, the following hypotheses are proposed:

H1: Digital literacy will be negatively associated with privacy concerns.

H2a: Digital literacy will be positively associated with perceived usefulness.

H2b: Digital literacy will be positively associated with perceived ease of use.

H3: Digital literacy will be positively associated with the intention to use digital therapeutics.

Online information trust, technology acceptance, and privacy concerns

Online information trust refers to users’ confidence in the accuracy, credibility, and quality of information provided through digital platforms.^12–15 As with other digital health technologies, the adoption of digital therapeutics (DTx) can be significantly influenced by the degree to which users trust online information and by their concerns regarding personal data protection. These two factors are closely interrelated and play a critical role in shaping users’ attitudes and behavioral intentions toward adopting new technologies.

When users place a high level of trust in online health information, they are more likely to believe that digital therapeutics are based on accurate and reliable data, which may in turn enhance their perceived usefulness of the technology. Moreover, this trust may reduce the perceived complexity of the system and thereby improve perceived ease of use. If users believe that the information provided by digital therapeutics is trustworthy, they are more likely to view the technology as both useful and easy to use. This perception can lead to more positive attitudes toward the technology and, ultimately, a stronger intention to adopt it. Empirical evidence supports this view, indicating that trust in online health information significantly influences both perceived usefulness and perceived ease of use, which are critical determinants in TAMs.¹⁶

In contrast, privacy concerns refer to users’ apprehensions about the security and confidentiality of their personal information.^17,18 In the context of digital therapeutics, these concerns are often associated with the collection, storage, and potential misuse of sensitive health data. Privacy concerns may act as a substantial barrier to technology adoption. Even when digital therapeutics offer potential benefits, users may hesitate to use them if they are worried about data privacy. Such hesitation can negatively impact both perceived usefulness and ease of use, thereby reducing the likelihood of acceptance. Prior studies have identified privacy concerns as a key factor influencing user acceptance of technology, especially in health-related contexts where sensitive information is involved.¹³

Given these dynamics, it is important to explore how online information trust and privacy concerns interact with core constructs from the TAM to influence the intention to use digital therapeutics. Trust in online information has been shown to significantly impact perceived usefulness and perceived ease of use, thereby influencing the likelihood of adoption.¹⁶ Meanwhile, privacy concerns have been identified as a central determinant of users’ willingness to adopt digital health technologies, particularly in situations involving the management of personal health data.¹³

In terms of generational differences, recent research shows that privacy concerns negatively affect the intention to use digital therapeutics among Millennials and Generation Z, while such concerns do not significantly influence usage intentions among the Baby Boomer generation.⁵ These findings highlight the need to consider demographic variability in the role of trust and privacy perceptions in digital health adoption.

Based on these theoretical and empirical insights, the proposed research model is presented in Figure 1, and the following hypotheses are derived accordingly.

H4: Online information trust will be negatively associated with privacy concerns.

H5a: Online information trust will be positively associated with perceived usefulness.

H5b: Online information trust will be positively associated with perceived ease of use.

H6: Online information trust will be positively associated with the intention to use digital therapeutics.

H7a: Privacy concerns will be negatively associated with perceived usefulness.

H7b: Privacy concerns will be negatively associated with perceived ease of use.

H8a: Perceived usefulness will be positively associated with the intention to use digital therapeutics.

H8b: Perceived ease of use will be positively associated with the intention to use digital therapeutics.

Figure 1.

Research model.

Research method and analytical approach

Participants and data collection

To empirically test the proposed hypotheses, a nationwide online survey was conducted through a professional research firm, Embrain. The survey was administered from July 1 to July 8, 2021, using proportional quota sampling based on gender and age among the company's registered research panel members. A total of 600 valid responses were collected for analysis, comprising 306 men (51%) and 294 women (49%). The age distribution of the sample was as follows: 20 s (16.8%, n = 101), 30 s (16.3%, n = 98), 40 s (21.3%, n = 128), 50 s (21.7%, n = 130), and 60 s and older (17.3%, n = 104). The sample reflected a broad demographic to ensure generalizability of the findings within the Korean adult population.

Measurement of key variables

Digital literacy was measured using a scale adapted from Kim, Eom and Shim,⁵ which was originally developed based on the theoretical framework proposed by Eshet-Alkalai and colleagues.^19,20 This scale captures a broad range of digital competencies across three key dimensions: information utilization ability, creative producing ability, and digital communication ability.

In the original study by Kim, Eom, and Shim,⁵ an exploratory factor analysis of 16 items revealed a three-factor structure. “Information utilization ability” included items such as “I can find the information I need through a search engine” and “I can configure the web browser (Explorer, etc.).” “Creative producing ability” involved tasks such as producing fan art (audio/video/images) and remixing popular media content. Finally, “digital communication ability” encompassed behaviors like sending group messages, expressing oneself clearly online, and using the Internet to build interpersonal understanding.

Respondents answered each item on a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The internal consistency (Cronbach's α) for each sub-dimension in the original study was above .82, and the same reliability was maintained in this study.

Online information trust was measured using items adapted from Rains.¹⁵ The scale included four items rated on a 5-point Likert scale, including statements such as “Health information provided on the Internet is of high qualitative value.” The reliability of this scale was high (Cronbach's α = .886).

Privacy concerns were measured by adapting items from Malhotra et al.²¹ which were originally designed to assess Internet users’ concerns about personal data protection. The scale was customized for this study and included three subdimensions: control over personal information, awareness of privacy practices, and data collection. In the original study by Malhotra et al. (2004), the internal consistency coefficients were reported as follows: α = .85 for control, α = .73 for awareness, and α = .91 for collection. Participants responded on a 5-point Likert scale, and the overall reliability of the scale was acceptable (Cronbach's α = .890).

Perceived usefulness and perceived ease of use , key constructs from the TAM, were each measured using four items rated on a 5-point Likert scale.^6,22 Items for perceived usefulness included statements such as “Digital therapeutics can help treat diseases more efficiently” (Cronbach's α = .842). Perceived ease of use was measured using items such as “Learning how to use digital therapeutics is easy,” with the scale demonstrating high internal consistency (Cronbach's α = .814). In the original TAM study,² the reliability coefficients were reported as α = .97 for perceived usefulness and α = .91 for perceived ease of use, supporting the robustness of the measurement scales.

Intention to use digital therapeutics was measured using three items adapted from the work of Venkatesh and Davis²³ and refined to align with the context of this study. The items included: “I intend to use digital therapeutics,” “I would speak positively about digital therapeutics,” and “I would recommend digital therapeutics to others.” The scale demonstrated high internal consistency (Cronbach's α = .886), supporting its reliability in this context.

Data analysis procedure

To test the proposed hypotheses, this study employed structural equation modeling (SEM) using path analysis. All SEM analyses were conducted using AMOS version 21.0 (IBM Corp.), which enabled the estimation of both direct and indirect effects. SEM is suitable for simultaneously examining the direct and indirect effects among latent variables and for validating complex theoretical models such as the extended TAM utilized in this research.

The model fit was assessed using several commonly accepted indices. The overall model demonstrated an acceptable to good fit, based on the following results: Goodness-of-fit index (GFI) = 0.916, comparative fit index (CFI) = 0.937, incremental fit index (IFI) = 0.937, root mean square residual (RMR) = 0.033 Root mean square error of approximation (RMSEA) = 0.076.

According to established benchmarks,²⁴ a GFI, CFI, and IFI greater than 0.90 indicates a good model fit. An RMR below 0.05 suggests that the residuals between the observed and predicted data are minimal. Additionally, an RMSEA value below 0.08 is generally interpreted as indicating reasonable model fit, with values below 0.05 considered excellent. To evaluate the precision of the estimated effects, 2000 bootstrap samples were used to compute bias-corrected 95% confidence intervals (CI) for all direct, indirect, and total effects. The upper and lower bounds (UCI/LCI) are reported in [Table 1]. An effect was considered statistically significant if the 95% CI did not include zero.

Table 1.

Causal effect decomposition: Direct, indirect, and total effects.

	Path			Direct Effect	Indirect Effect	Total Effect	95% CI Lower	95% CI Upper
H1	Digital Literacy	→	Privacy Concern	0.31***	0	0.31***
H2a	Digital Literacy	→	Perceived Usefulness	0.041	0.29**	0.332**	0.250	0.365
H2b	Digital Literacy	→	Perceived Ease of Use	0.358***	0.022	0.38**	-0.001	0.056
H3	Digital Literacy	→	DTx Use Intention	0.125**	0.247**	0.372**	0.196	0.329
H4	Online Information Trust	→	Privacy Concern	−0.038	0	−0.038
H5a	Online Information trust	→	Perceived Usefulness	0.083**	0.116**	0.2**	0.060	0.167
H5b	Online Information trust	→	Perceived Ease of Use	0.214***	−0.003	0.211**	−0.16	0.002
H6	Online Information trust	→	DTx Use Intention	0.099**	0.145**	0.243**	0.082	0.200
H7a	Privacy Concern	→	Perceived Usefulness	0.216***	0.041	0.257**	−0.009	0.090
H7b	Privacy Concern	→	Perceived Ease of Use	0.07	0	0.07
H8a	Perceived Usefulness	→	DTx Use Intention	0.488***	0	0.488***
H8b	Perceived Ease of Use	→	DTx Use Intention	0.224***	0.288**	0.511**	0.232	0.357

*p < .05, ** p < .01, *** p < .001.

Taken together, these results indicate that the hypothesized model provides an adequate representation of the observed data, and that the path coefficients can be interpreted with statistical confidence.

Results

Hypotheses 1 to 3: Associations with digital literacy

These hypotheses examined the associations between digital literacy and the outcome variables. Contrary to the expectation in Hypothesis 1, digital literacy was positively associated with privacy concerns (β = 0.310, p < .001), and therefore H1 was not supported.

Regarding Hypotheses 2a and 2b, digital literacy was not significantly associated with perceived usefulness, resulting in H2a not being supported. However, digital literacy was positively associated with perceived ease of use (β = 0.358, p < .001), providing support for H2b.

Digital literacy also showed a positive association with the intention to use digital therapeutics (β = 0.125, p < .01), supporting H3.

Hypotheses 4 to 6: Associations with online information trust

These hypotheses explored the associations between online information trust and other variables in the model. Hypothesis 4 proposed a negative relationship between online information trust and privacy concerns; however, no statistically significant association was found, and H4 was not supported.

Online information trust was positively associated with both perceived usefulness (β = 0.083, p < .01) and perceived ease of use (β = 0.214, p < .001), supporting H5a and H5b.

Additionally, a positive association was found between online information trust and the intention to use digital therapeutics (β = 0.099, p < .01), providing support for H6.

Hypotheses 7a to 8b: Associations with privacy concerns and cognitive evaluations

The analysis revealed a positive association between privacy concerns and perceived usefulness (β = 0.216, p < .001), which was contrary to the hypothesized negative direction. Thus, H7a was not supported, although a significant relationship was observed in the opposite direction. Privacy concerns were not significantly associated with perceived ease of use, and H7b was not supported.

Both perceived usefulness (β = 0.488, p < .001) and perceived ease of use (β = 0.224, p < .001) were positively associated with the intention to use digital therapeutics, supporting H8a and H8b, respectively. The results of the full path analysis are presented in Figure 2.

Figure 2.

Structural model of intention to use digital therapeutics. Note. χ² = 412.708, df = 92, p = .000; GFI = 0.916, CFI = 0.937, IFI = 0.937, RMR = 0.033, RMSEA = 0.076.

Decomposition: Direct, indirect, and total effects

To examine the mediating relationships between variables, the direct, indirect, and total effects were analyzed using the bootstrapping method. Most total effects were statistically significant, with several notable patterns observed.

Digital literacy showed a significant direct effect on perceived ease of use (β = 0.358, p < .001), while the indirect effect was not significant. Similarly, online information trust had a significant direct effect on perceived ease of use (β = 0.214, p < .001), but its indirect effect was not significant. Privacy concern exhibited a significant direct (β = 0.216, p < .001) on perceived usefulness, but the indirect effect was not significant.

Digital literacy did not have a significant direct effect on perceived usefulness but showed a significant indirect effect (β = 0.29, p < .01) with a 95% CI [0.250, 0.365], resulting in a statistically significant total effect (β = 0.332, p < .01). Online information trust displayed both a significant direct effect (β = 0.083, p < .01) and an indirect effect (β = 0.116, p < .01), with a 95% CI of [0.060, 0.167], on perceived usefulness.

The direct effect of perceived usefulness on DTx use intention was significant (β = 0.488, p < .001). In addition, the indirect effect of perceived ease of use on DTx use intention through perceived usefulness was also significant (β = 0.288, 95% CI = [0.232, 0.357]), indicating that perceived usefulness plays a mediating role in this relationship.

The detailed breakdown of effects is presented in Table [1].

Discussion

This study investigated the factors associated with the intention to use digital therapeutics by examining the relationships among digital literacy, online information trust, and privacy concerns, grounded in the TAM. Several meaningful insights can be drawn from the results.

First, individuals with higher digital literacy exhibited greater privacy concerns. At the same time, they perceived digital therapeutics as easier to use, which was associated with stronger usage intentions. This dual finding implies that while digitally literate users are more sensitive to data protection issues, they are also better equipped to navigate digital health platforms. These results suggest the importance of developing comprehensive privacy education and implementing robust security features specifically targeted toward digitally savvy users.²⁵ Developers and healthcare providers should prioritize transparent communication about privacy policies and data practices to foster user trust. In addition, offering tools that allow users to control their personal data, along with educational resources, may help mitigate privacy concerns.²⁶

Second, trust in online information was found to positively influence users’ perceptions of both the ease of use and the usefulness of digital therapeutics, as well as their intention to adopt these technologies. This emphasizes the essential role of trust in the acceptance of digital therapeutics and the need for continuous efforts to build and maintain that trust.²⁷ For instance, it is crucial to ensure that information related to digital therapeutics is accurate, evidence-based, and regularly updated. Highlighting the qualifications and credibility of content creators and certifying institutions can enhance perceived trustworthiness. Encouraging user feedback and reviews may also help foster a reliable and supportive community around digital therapeutics.

Third, contrary to expectations, higher privacy concerns were associated with higher perceived usefulness. This unexpected finding suggests that users who are more concerned about privacy may also be more discerning and have higher standards for quality in digital therapeutics.²⁸ These users may place greater value on platforms that demonstrate strong security measures and transparent data practices. This highlights the importance of emphasizing privacy protection and security as core components of digital therapeutics. Developers and service providers should continuously update and improve security protocols while also creating channels for users to express privacy concerns and suggestions, ultimately enhancing user satisfaction.

Fourth, the causal effect decomposition analysis provided deeper insight into how direct and indirect pathways jointly shape behavioral outcomes. While many paths demonstrated significance across all three levels (direct, indirect, and total effects), a few patterns stood out. For instance, the influence of digital literacy on perceived usefulness was found to be statistically nonsignificant in its direct form but became significant when mediated through perceived ease of use and privacy concerns. This indicates that digital literacy may not immediately translate into perceptions of usefulness, but its value unfolds through intermediary constructs. This finding emphasizes the importance of examining indirect effects in behavioral models, especially when evaluating technology adoption in complex digital health contexts.

Similarly, privacy concern did not directly affect behavioral intention to use digital therapeutics, but it did exert a significant indirect effect via perceived usefulness. This pathway underscores how attitudinal and evaluative constructs serve as key channels through which psychological barriers like privacy apprehensions influence ultimate user behaviors. It suggests that even when privacy concerns do not prevent users from adopting digital therapeutics outright, they still influence the user's evaluation process, which in turn affects adoption intentions.²⁹

In contrast, variables such as perceived ease of use and perceived usefulness demonstrated both strong direct and indirect effects on usage intention, reaffirming their centrality in the TAM framework. Particularly, perceived ease of use not only had a robust direct effect on intention but also indirectly enhanced perceived usefulness, further strengthening its role as a pivotal mediator in shaping user attitudes.

The interplay of direct and mediated effects also revealed the dual pathways through which digital literacy and online information trust operate. Both constructs directly influenced intention but also showed sizable indirect effects, suggesting that their influence extends beyond surface-level competencies or trust perceptions. These variables affect how users cognitively and emotionally evaluate digital therapeutics, shaping downstream adoption behaviors through a web of interrelated perceptions.

Collectively, the decomposition results highlight the importance of modeling layered relationships in digital health research, where multiple variables interact in both linear and mediated pathways. Relying solely on direct effects would risk underestimating the broader influence of foundational constructs like digital literacy and information trust. For practitioners, this means interventions should not only target surface behaviors but also nurture the evaluative and experiential dimensions—such as perceived ease of use—that bridge the gap between competencies and intentions.

In sum, the relationships among digital literacy, online information trust, privacy concerns, and technology acceptance are complex and at times contradictory. However, it is evident that digital literacy and privacy concerns are critical factors influencing the adoption of digital therapeutics. Policymakers and regulatory bodies should establish clear and standardized guidelines regarding data privacy and security in digital health technologies. Simultaneously, efforts to enhance digital literacy should be prioritized, enabling users to acquire the necessary skills to effectively utilize digital therapeutics.^5,29,30

By fostering transparent communication and implementing robust security measures, stakeholders can address privacy-related concerns, strengthen trust in online information, and enhance digital literacy. These strategies are likely to contribute to greater acceptance and utilization of digital therapeutics, ultimately supporting the development of more effective and user-centered digital healthcare solutions.

This study also offers a theoretical contribution by clarifying the role of the TAM in understanding digital health adoption. Rather than structurally extending TAM by adding external variables, this study employs TAM as a conceptual framework to examine how digital literacy, online information trust, and privacy concerns influence users’ cognitive evaluations—specifically, perceived usefulness and perceived ease of use—and ultimately, their behavioral intentions.

Several aspects make this study uniquely positioned to contribute to the existing literature. First, it applies TAM to the emerging field of digital therapeutics (DTx), a domain that has received limited attention in TAM-based research despite its growing relevance in healthcare. Second, while prior studies often use TAM as a base for structural extensions such as TAM2³¹ or UTAUT,³² this study takes a conceptual approach, using TAM to understand how broader sociotechnical and psychological constructs interact within the model. Third, the research is situated in South Korea—a highly digitalized but culturally distinct environment—thereby offering context-sensitive insights into digital health adoption. By integrating structural modeling with cultural relevance, this study advances both theoretical understanding and practical application of TAM in the digital health domain.

Limitations and future research

While this study provides meaningful insights into factors influencing the adoption of digital therapeutics, several limitations should be acknowledged.

First, although the digital literacy scale was based on a current framework, it may not fully capture emerging competencies such as AI literacy, algorithmic transparency, or new media navigation. Future research should update measurement tools to reflect these developments.

Second, although the study included a broad adult population, it did not conduct subgroup analyses by age. Age-specific patterns of adoption may warrant investigation in future studies.

Third, digital therapeutics were treated as a generalized concept. However, user perceptions may vary depending on the therapeutic focus (e.g., mental health vs. chronic disease). Domain-specific analyses could improve conceptual clarity.

Fourth, sociocultural variables—such as institutional trust or attitudes toward surveillance—were not directly measured but may have influenced user responses in the Korean context. Cross-cultural research is needed to explore contextual differences in digital health adoption.

Lastly, psychographic variables (e.g., digital lifestyle, privacy orientation) were not included. Incorporating such factors in future models may yield more nuanced user typologies and better predictive power.

Conclusion

This study explored how digital literacy, online information trust, and privacy concerns influence users’ intentions to adopt digital therapeutics, using an extended TAM as the theoretical framework. The findings highlight the complex interplay among cognitive, technological, and psychological variables in shaping digital health behaviors.

Digital literacy enhanced both perceived ease of use and intention to adopt, while also increasing privacy concerns—underscoring the dual role of digital competence. Online information trust significantly improved both perceived usefulness and ease of use, reinforcing the importance of credible content in digital health environments. Interestingly, privacy concern—often seen as a barrier—was associated with greater perceived usefulness, suggesting that heightened concern may drive more critical evaluation of health technologies.

Taken together, these findings underscore the need for user-centered design, robust data protection, and targeted digital literacy initiatives in the development and dissemination of digital therapeutics. As digital health ecosystems evolve, future research must continue refining the constructs and models used to understand adoption, while also considering cultural and contextual dynamics. Enhancing trust, usability, and privacy simultaneously will be essential for fostering sustainable engagement with emerging digital health solutions.

Footnotes

Acknowledgements

The authors would like to thank the Korea Society of Internet Ethics for the opportunity to present an earlier version of this study at their academic conference and for the valuable feedback provided by the reviewers and participants.

ORCID iDs

Soo Jin Kim

Juhee Eom

Ethical approval

This study was approved by Institutional Review Board of [Details omitted for double-blind peer review]. This study was approved by Institutional Review Board of Dongguk University (DUIRB-202109-21).

Contributorship

S.J.K. & J.E. designed, researched literature and conceived the study. J.E. gained ethical approval and S.J.K. performed data analysis. S.J.K. wrote the first draft of the manuscript. All authors reviewed and edited the manuscript and approved the final version of the manuscript.

Funding

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea. (NRF-2023S1A5A8082451). This research was supported by [Details omitted for double-blind peer review].

Declaration of conflicting interests

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

Disclosure

A previous study by the authors (Kim, Eom, & Shim, 2022) used the same dataset to compare digital therapeutics use intention across generational cohorts using structural equation modeling. The current manuscript is a distinct work that applies the TAM to explore how digital literacy, online information trust, and privacy concerns affect individuals’ intention to use digital therapeutics. The theoretical framework, analytic model, and study focus differ from the previous publication. For full transparency, we disclose this prior publication:

Kim, S., Eom, J., & Shim, J. (2022). A comparative study on intention to use digital therapeutics: MZ generation and baby Boomers’ digital therapeutics use intention in Korea. International Journal of Environmental Research and Public Health, 19(15), 9556.

Guarantor

S.J.K.

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Applying the technology acceptance model to predict digital therapeutics use in South Korea: The roles of digital literacy,online information trust,and privacy concern

Abstract

Objective

Methods

Results

Conclusion

Keywords

Introduction

Theoretical and empirical background

Technology acceptance model (TAM) and digital literacy

Online information trust, technology acceptance, and privacy concerns

Research method and analytical approach

Participants and data collection

Measurement of key variables

Data analysis procedure

Results

Hypotheses 1 to 3: Associations with digital literacy

Hypotheses 4 to 6: Associations with online information trust

Hypotheses 7a to 8b: Associations with privacy concerns and cognitive evaluations

Decomposition: Direct, indirect, and total effects

Discussion

Limitations and future research

Conclusion

Footnotes

Acknowledgements

ORCID iDs

Ethical approval

Contributorship

Funding

Declaration of conflicting interests

Disclosure

Guarantor

References