Influence of doctor-patient trust on the adoption of mobile medical applications during the epidemic: a UTAUT-based analysis.

This study examines the factors influencing users' intention to continue using mobile medical apps within the framework of the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Through a combination of questionnaire surveys and interviews, the research finds that doctor-patient trust, Performance Expectancy (PE), social influence, and facilitating conditions significantly impact users' intention to utilize mobile medical apps. Furthermore, the study reveals the moderating effect of doctor-patient trust on social influence, indicating an increased trust level during the epidemic, attributed to positive media coverage, complimentary medical services, and risk-sharing initiatives. These results provide valuable insights for the field of internet healthcare, COVID-19 response strategies, health information management, and the advancement of digital health technologies, spotlighting the pivotal roles of trust, PE, and social influence in fostering sustained engagement with mobile health apps.

Exploring Acceptability, Barriers, and Facilitators for Digital Health in Dermatology: Qualitative Focus Groups With Dermatologists, Nurses, and Patients.

BACKGROUND: Although several digital health interventions (DHIs) have shown promise in the care of skin diseases their uptake in Germany has been limited. To fully understand the reasons for the low uptake, an in-depth analysis of patients' and health care providers' barriers and facilitators in dermatology is needed. OBJECTIVE: The objective of this study was to explore and compare attitudes, acceptability, barriers, and facilitators of patients, dermatologists, and nurses toward DHIs in dermatology. METHODS: We conducted 6 web-based focus groups each with patients (n=34), dermatologists (n=30), and nurses (n=30) using a semistructured interview guide with short descriptions of DHIs described in the literature. A content analysis was performed using deductive constructs, following the unified theory of acceptance and use of technology framework, and inductive categories. RESULTS: Patients identified many positive performance expectancies, such as reduced travel times and improvement in follow-up appointments. Dermatologists also stated positive effects (eg, promotion of standardized care), but also negative implications of health care digitalization (eg, increased workload). All stakeholders reported that a DHI should bring additional value to all stakeholders. A lack of digital competence among patients was identified as the major barrier to adoption by all 3 groups. Nurses and dermatologists want apps that are easy to use and easy to implement into their daily routines. Trust in selected institutions, colleagues, and physicians was identified as a facilitator. Patients reported their dependence on the dermatologists' acceptance. All groups expressed concerns about data privacy risks and dermatologists stated insecurities toward data privacy laws. CONCLUSIONS: To ensure successful digitalization in dermatology, apps should be user-friendly, adapted to users' skill levels, and beneficial for all stakeholders. The incorporation of dermatologists' perspectives is especially important as their acceptance may impact use among patients and nurses. DHIs should ensure and be transparent about data privacy. The found barriers and facilitators can be used for implementation strategies.

Sanctions and opportunities: Factors affecting China's high-tech SMEs adoption of artificial intelligence computing leasing business.

Due to sanctions, more Chinese high-tech SMEs are turning to rent AI computing power through cloud service providers. Therefore, it is necessary to give a variety of suggestions for China's high-tech SMEs to better develop AI applications through computing power leasing. Because traditional theories are difficult to explain this new technology adoption behavior, this research combines and extends TTF and UTAUT2 theories to take an empirical research. A total of 387 questionnaires were received, of which incomplete questionnaires and invalid questionnaires were issued, leaving 281 valid questionnaires. The results indicate that SME innovativeness, perceived risk, performance expectancy, price value and task technology fit are all significantly related to usage, whereas task technology fit moderates the other relationships significantly. Results give a variety of suggestions for China's high-tech SMEs to better develop AI applications through computing power leasing in the context of sanctions. This study not only suggests ways to increase the competitiveness of SMEs by optimizing leasing services but also give directions in investors' investment decisions. The findings are also applicable to the large-scale application of China's domestic AI chips in computing power leasing scenarios in the future.

Chinese Consumers' Attitudes toward and Intentions to Continue Using Skill-Sharing Service Platforms.

The sharing economy has rapidly transformed traditional consumption patterns worldwide. The emergence of skill-sharing services-which allow individuals to share their skills, abilities, and time through online platforms-has recently garnered attention. In China, the demand for skill-sharing services continues to grow, as these services effectively meet consumer needs. To understand this growing demand, this study aims to explore users' attitudes and intentions toward the use of skill-sharing service platforms in the Chinese market. A survey was conducted that incorporated 500 Chinese users who had used skill-sharing service platforms over the previous three months. A total of 409 datasets were analyzed, using structural equation modeling and multiple group analysis, in AMOS 24.0. The results showed that performance expectancy, effort expectancy, social influence, facilitating conditions, and self-efficacy positively influenced users' attitudes toward skill-sharing services, while privacy, functionality, and safety risks negatively affected these attitudes. Users' attitudes toward skill-sharing services significantly enhanced their intentions to continue using them, with the level of trust playing a crucial moderating role between attitude and the intention to continue using these services. These findings provide a significant theoretical and practical foundation for the further development of skill-sharing service platforms, the optimization of marketing strategies, and future research.

Analyzing health service employees' intention to use e-health systems in southwest Ethiopia: using UTAUT-2 model.

BACKGROUND: E-health systems have the potential to improve healthcare delivery and access to medical services in resource-constrained settings. Despite its impact, the system exhibits a low level of consumer acceptance and intention to use it. This research paper aims to analyze the intention of health service employees to use e-health systems in southwest Ethiopia using the UTAUT-2 model. METHOD: Institutional-based cross-sectional studies were conducted at four referral hospitals (two private and two public) to examine the acceptance of e-health among consumers. Employees who had previous experience with diagnostic information systems and the health logistic information system were given structured questionnaires based on the UTAUT-2 model. The data were analyzed using the PLS-SEM method to identify the key factors that influence the intention to use e-health systems. The data were analyzed using SPSS version 20 and SmartPLS 3 software. RESULT: Out of the 400 surveyed employees, 225 (56.25%) valid questionnaires were collected. The findings indicate that three factors-effort expectancy (ß = 0.276, t = 3.015, p = 0.001), habit (ß = 0.309, t = 3.754, p = 0), and performance expectancy (ß = 0.179, t = 1.905, p = 0.028)-had a significant positive impact on employees' intention to use e-health systems. On the other hand, factors such as social influence, facilitating conditions, hedonic motivation, and price values did not appear as significant predictors of intention to use e-health. The study model was able to predict 63% of employees' intentions to use e-health systems. CONCLUSION: Effort expectancy, habit, and performance expectancy were significant predictors of employees' intention to use e-health systems among health service employees in southwest Ethiopia. The study supports the ideas that ease of use, experience with information systems, and the role of the systems in improving job performance contribute to employees' intention to use e-health. Policymakers and healthcare organizations in the region can use these findings to develop strategies for successful implementation and adoption of e-health systems, ultimately improving healthcare services and outcomes for the population.

Assessing AI adoption in developing country academia: A trust and privacy-augmented UTAUT framework.

The rapid evolution of Artificial Intelligence (AI) and its widespread adoption have given rise to a critical need for understanding the underlying factors that shape users' behavioral intentions. Therefore, the main objective of this study is to explain user perceived behavioral intentions and use behavior of AI technologies for academic purposes in a developing country. This study has adopted the unified theory of acceptance and use of technology (UTAUT) model and extended it with two dimensions: trust and privacy. Data have been collected from 310 AI users including teachers, researchers, and students. This study finds that users' behavioral intention is positively and significantly associated with trust, social influence, effort expectancy, and performance expectancy. Privacy, on the other hand, has a negative yet significant relationship with behavioral intention unveiling that concerns over privacy can deter users from intending to use AI technologies which is a valuable insight for developers and educators. In determining use behavior, facilitating condition, behavioral intention, and privacy have significant positive impact. This study hasn't found any significant relationship between trust and use behavior elucidating that service providers should have unwavering focus on security measures, credible endorsements, and transparency to build user confidence. In an era dominated by the fourth industrial revolution, this research underscores the pivotal roles of trust and privacy in technology adoption. In addition, this study sheds light on users' perspective to effectively align AI-based technologies with the education system of developing countries. The practical implications encompass insights for service providers, educational institutions, and policymakers, facilitating the smooth adoption of AI technologies in developing countries while emphasizing the importance of trust, privacy, and ongoing refinement.

Intention to use personal health record system and its predictors among chronic patients enrolled at public hospitals in Bahir Dar city, northwest Ethiopia: using modified UTAUT2 model.

Introduction: Chronic diseases are the leading causes of death in the world. In sub-Saharan Africa, it leads to more mortality than almost every other region in the world. Currently, digital health technology like personal health records plays a crucial role in managing patients with chronic diseases. In low-resource countries like Ethiopia, it is uncertain how many chronic patients intend to use PHRs and the accompanying circumstances. Hence, the aim of this study was to assess chronic patients' intention to use PHRs and its predictors enrolled in public health hospitals in Bahir Dar city, northwest Ethiopia. Method: An institutional-based cross-sectional study was conducted among 924 respondents from April 5 to May 9, 2023, in Bahir-Dar city public hospitals. A stratified sampling technique followed by a systematic sampling technique was applied to select the study participants. An interviewer-administrated questionnaire was conducted using Kobo Collect. A UTAUT2 model was applied to develop theoretical frameworks. SPSS version 25 software was used to estimate the descriptive statistics, and the structural equation model analysis was used to evaluate model constructs using AMOS version 21 software. Results: In this study, a total of 908 study subjects participated. The proportion of chronic patients' intention to use PHR was 46.7% [95.0% CI (43.4-50.1)]. According to the findings, performance expectancy (ß = 0.259, p-value <0.001), effort expectancy (ß = 0.214, p-value <0.001), social influence (ß = 0.174, p-value <0.001), and facilitating condition (ß = 0.114, p-value <0.01) had a significant effect on the intention to use PHRs. Conclusion: Generally, the overall intention to use PHR was low. Our finding illustrates that the effects of performance expectancy, effort expectancy, social influence, and facilitating conditions had a positive effect on patients' intentions to use PHRs. The effect of effort expectancy on the intention to use a PHR was positively moderated by age. Since the findings of this study would help policymakers and programmers to future academics interested in this area and insight to future research workers. Therefore, implementers should focus on improving patient capacity, motivating users, and raising awareness regarding PHR.

The path to cashless transaction: A study of user intention and attitudes towards quick response mobile payments.

This study explores the factors influencing users' behavioral intentions, attitudes and actual adoption of quick response (QR) mobile payment in the least developed country (LDC) of Bangladesh, by extending the original unified theory of acceptance and use of technology (UTAUT) model. The study conducts a mixed-methods investigation by combining the partial least squares (PLS) and focus group discussion (FGD) methods to empirically evaluate the research model and cross-validate the findings. Using purposive sampling, data were gathered from 412 respondents, followed by 10 respondents who took part in the FGD, who all met the sample criteria. The study findings indicate that performance expectancy, effort expectancy, and social influence significantly positively influence users' behavioral intention, while self-concept, perceived self-efficacy, and habit substantially influence their attitudes towards using QR mobile payments. The findings also confirm a positive effect of users' attitudes toward using QR mobile payment on both behavioral intention and actual use, and a positive effect of behavioral intention on the actual use of QR mobile payments. These findings offer several important theoretical and managerial implications.

Understanding the predictors of health professionals' intention to use electronic health record system: extend and apply UTAUT3 model.

BACKGROUND: The implementation of Electronic Health Record (EHR) systems is a critical challenge, particularly in low-income countries, where behavioral intention plays a crucial role. To address this issue, we conducted a study to extend and apply the Unified Theory of Acceptance and Use of Technology 3 (UTAUT3) model in predicting health professionals' behavioral intention to use EHR systems. METHODS: A quantitative research approach was employed among 423 health professionals in Southwest Ethiopia. We assessed the validity of the proposed model through measurement and structural model statistics. Analysis was done using SPSS AMOS version 23. Hypotheses were tested using structural equation modeling (SEM) analysis, and mediation and moderation effects were evaluated. The associations between exogenous and endogenous variables were examined using standardized regression coefficients (ß), 95% confidence intervals, and p-values, with a significance level of p-value < 0.05. RESULTS: The proposed model outperformed previous UTAUT models, explaining 84.5% (squared multiple correlations (R2) = 0.845) of the variance in behavioral intention to use EHR systems. Personal innovativeness (ß = 0.215, p-value < 0.018), performance expectancy (ß = 0.245, p-value < 0.001), and attitude (ß = 0.611, p-value < 0.001) showed significant associations to use EHR systems. Mediation analysis revealed that performance expectancy, hedonic motivation, and technology anxiety had significant indirect effects on behavioral intention. Furthermore, moderation analysis indicated that gender moderated the association between social influence, personal innovativeness, and behavioral intention. CONCLUSION: The extended UTAUT3 model accurately predicts health professionals' intention to use EHR systems and provides a valuable framework for understanding technology acceptance in healthcare. We recommend that digital health implementers and concerned bodies consider the comprehensive range of direct, indirect, and moderating effects. By addressing personal innovativeness, performance expectancy, attitude, hedonic motivation, technology anxiety, and the gender-specific impact of social influence, interventions can effectively enhance behavioral intention toward EHR systems. It is crucial to design gender-specific interventions that address the differences in social influence and personal innovativeness between males and females.

Uncovering mathematics teachers' instructional anticipations in a digital one-to-one environment: A modified UTAUT study.

More and more digital technologies are being integrated into school learning, and one strategy by policymakers to reinforce this trend is employing digital one-to-one approaches. For digital technologies to be fruitfully integrated into school-based learning scenarios, teachers and their anticipations are key. In our study, we want to explore how internal, external and technological factors affect the instructional anticipations of mathematics teachers in a digital one-to-one educational environment. Therefore, we employed a modified model of the Unified Theory of Acceptance and Use of Technology. Through our structural equation study, in which data from more than 900 mathematics teachers were analyzed, we identified that especially technological and external factors can predict mathematics teachers' instructional anticipations. Findings from our study could be particularly relevant for educational policymakers, informing them about the importance of factors or interventions related to educational technology implementation.

Feasibility of Holographic Team Training Simulation: An Information Technology (IT) Perspective for Healthcare and Educational Institutions.

Introduction This study examines the feasibility and practicality of holographic display technology (HDT) in health professions education from an information technology (IT) support staff perspective. Considering a lack of feasibility studies for introducing newer technologies, it focuses on feasibility's acceptance and practicality dimensions during a simulation-based team training workshop. Method A multimethod design feasibility study assessed the acceptability and practicality of HDT for the IT staff through a Unified Theory of Acceptance and Use of Technology (UTAUT)-based survey and a focus group discussion after a team training simulation workshop.  Results Quantitative results showed a reliability coefficient (α=0.83) and a positive correlation between facilitating conditions (FC) and effort expectancy (EE), self-efficacy (SE) and social influence (SI), SI and attitude toward technology (AT), SE and attitude to use, and behavioral intention (BI) and EE. Negative correlations included SE and performance expectancy (PE), comfort with technology and FC, comfort and anxiety, and attitude to use and experience. Qualitative findings yielded four key themes from the focus group discussions that corroborated the quantitative findings.  Discussion The study findings highlight the promising potential for HDT feasibility in educational settings. Future research should extend to diverse contexts to validate these preliminary findings and explore broader educational applications.

Developing the teledentistry acceptance survey for dentists - TAS-D: a Delphi study.

INTRODUCTION: The increasing interest in teledentistry since the COVID-19 pandemic warrants an evaluation of dentists' willingness to adopt it. This study aimed to develop a questionnaire to assess dentist's intention to use teledentistry and the associated factors. METHODS: A literature search was used to identify items for the questionnaire. The Unified Theory of Acceptance and Use of Technology (UTAUT2) was adopted as framework. A Delphi panel was constituted of researchers with relevant publications and the International Association of Dental Research e-Oral Health Network members. Three Delphi consultations were conducted to establish consensus on items. Consensus was set at 80% agreement and content validity ratio (CVR), reaffirmed iteratively. RESULTS: Nineteen out of 25 (76%) invited experts participated in the first round, 17 in the second and 15 in the third. The preliminary questionnaire had 81 items in three sections, reduced to 66, 45 and 33 items in the first, second and third rounds. After revision, the final version comprised eight items assessing dentists' backgrounds in Sect. 1, seven items identifying teledentistry uses in Sect. 2, and 17 items assessing intention to use teledentistry and its determinants in seven dimensions in Sect. 3. The initial CVR was 0.45, which increased to 0.80 at the end of the third round. CONCLUSION: A survey tool was developed to assess the acceptance of teledentistry, and its determinants based on the UTAUT2 framework through consensus among teledentistry experts. The tool had excellent validity and needs further evaluation of its psychometric properties.

Uptake and engagement of a clinically moderated digital peer support platform to support the mental well-being older adults: a qualitative investigation.

BACKGROUND: The uptake of traditional mental health services among older adults remains low. Digital peer support offers older adults a resource for engaging with others to independently support their mental well-being. This qualitative study explored the uptake and engagement of a clinically moderated digital peer support platform (Breathing Space) for older adults with depressive symptoms and alcohol use concerns. METHODS: Semi-structured interviews with 30 participants aged 60-80 years explored participants' uptake and engagement with Breathing Space, a novel, moderated, private, and anonymous peer support platform. Data were analysed using reflective thematic analysis and are discussed with reference to the Unified Theory of Acceptance and Use of Technology2. RESULTS: Three themes were constructed to characterize participants' experiences: (i) navigating the complexities of peer-peer online engagement; (ii) the function of anonymity in online connection; and (iii) experiences of app features and content. CONCLUSIONS: Future development of digital peer support for older adults would benefit from the following: (i) co-design with older adults; (ii) providing choice over anonymity and increased options for interacting with peers; (iii) streamlining the basic functionality with popular platforms; (iv) providing options for users to curate their digital experience; and (v) providing telephone support for troubleshooting technical difficulties. Future research should explore the use of digital peer support among older adults who experience social exclusion challenges.

The role of Contact-Tracing Mobile Apps in pandemic prevention: A multidisciplinary perspective on health beliefs, social, and technological factors.

During the recent COVID-19 pandemic, governments implemented mobile applications for contact tracing as a rapid and effective solution to mitigate the spread of the virus. However, these seemingly straightforward solutions did not achieve their intended objectives. In line with previous research, this paper aims to investigate the factors that influence the acceptance and usage of contact-tracing mobile apps (CTMAs) in the context of disease control. The research model in this paper integrates the Unified Theory of Acceptance and Use of Technology and the Health Belief Model (HBM). The present study involved a diverse sample of 770 French participants of all genders, ages, occupations, and regions. Critical elements from the Health Belief Model, technological factors related to the app, and social factors, including the centrality of religiosity, were assessed using well-established measurement scales. The research's findings demonstrate that several factors, such as perceived benefits and perceived severity, social influence, health motivation, and centrality of religiosity, significantly impact the intention to use a CTMA. These findings suggest that CTMAs hold promise as valuable tools for managing future epidemics. However, addressing challenges, revising implementation strategies, and potentially collaborating with specialized industry partners under regulatory frameworks are crucial. This practical insight can guide policymakers and public health officials in their decision-making.

Predictors of Health Care Practitioners' Intention to Use AI-Enabled Clinical Decision Support Systems: Meta-Analysis Based on the Unified Theory of Acceptance and Use of Technology.

BACKGROUND: Artificial intelligence-enabled clinical decision support systems (AI-CDSSs) offer potential for improving health care outcomes, but their adoption among health care practitioners remains limited. OBJECTIVE: This meta-analysis identified predictors influencing health care practitioners' intention to use AI-CDSSs based on the Unified Theory of Acceptance and Use of Technology (UTAUT). Additional predictors were examined based on existing empirical evidence. METHODS: The literature search using electronic databases, forward searches, conference programs, and personal correspondence yielded 7731 results, of which 17 (0.22%) studies met the inclusion criteria. Random-effects meta-analysis, relative weight analyses, and meta-analytic moderation and mediation analyses were used to examine the relationships between relevant predictor variables and the intention to use AI-CDSSs. RESULTS: The meta-analysis results supported the application of the UTAUT to the context of the intention to use AI-CDSSs. The results showed that performance expectancy (r=0.66), effort expectancy (r=0.55), social influence (r=0.66), and facilitating conditions (r=0.66) were positively associated with the intention to use AI-CDSSs, in line with the predictions of the UTAUT. The meta-analysis further identified positive attitude (r=0.63), trust (r=0.73), anxiety (r=-0.41), perceived risk (r=-0.21), and innovativeness (r=0.54) as additional relevant predictors. Trust emerged as the most influential predictor overall. The results of the moderation analyses show that the relationship between social influence and use intention becomes weaker with increasing age. In addition, the relationship between effort expectancy and use intention was stronger for diagnostic AI-CDSSs than for devices that combined diagnostic and treatment recommendations. Finally, the relationship between facilitating conditions and use intention was mediated through performance and effort expectancy. CONCLUSIONS: This meta-analysis contributes to the understanding of the predictors of intention to use AI-CDSSs based on an extended UTAUT model. More research is needed to substantiate the identified relationships and explain the observed variations in effect sizes by identifying relevant moderating factors. The research findings bear important implications for the design and implementation of training programs for health care practitioners to ease the adoption of AI-CDSSs into their practice.

The Moderating Effects of Gender and Study Discipline in the Relationship between University Students' Acceptance and Use of ChatGPT.

The intensive adoption of ChatGPT by university students for learning has encouraged many scholars to test the variables that impact on their use of such AI in their learning. This study adds to the growing body of studies, especially in relation to the moderating role of students' gender and their study discipline in their acceptance and usage of ChatGPT in their learning process. This study expanded the Unified Theory of Acceptance and Use of Technology (UTAUT) by integrating gender as well as study disciplines as moderators. The study collected responses from students in Saudi universities with different study disciplines and of different genders. The results of a structural model using Smart PLS showed a significant moderating effect of gender on the relationship between performance expectancy and ChatGPT usage. The results confirmed that the impact of performance expectancy in fostering ChatGPT usage was stronger in male than in female students. Moreover, social influence was shown to significantly affect males more than females in relation to ChatGPT usage. In addition, the findings showed that study discipline significantly moderates the link between social influence and ChatGPT usage. In the same vein, social influence significantly influences ChatGPT use in social sciences more than in applied sciences. Hence, the various implications of the study were discussed.

Understanding the Role of Technology Anxiety in the Adoption of Digital Health Technologies (DHTs) by Older Adults with Chronic Diseases in Shanghai: An Extension of the Unified Theory of Acceptance and Use of Technology (UTAUT) Model.

The unprecedented rapid growth of digital health has brought new opportunities to the health field. However, elderly patients with chronic diseases, as an important potential beneficiary group, are affected by the digital divide, leading to unsatisfactory usage of digital health technologies (DHTs). Our study focused on the factors influencing the adoption of DHTs among this vulnerable group. To extend the UTAUT theory, technology anxiety and several demographic predictors were included to address the age characteristics of the respondents. An on-site survey was conducted in general, district, and community hospitals in Shanghai (n = 309). Facilitating conditions negatively influenced technology anxiety. Technology anxiety hindered behavioural intention. Social influence had a significant but negative impact on behavioural intention. Education, whether older adults have had experience with DHTs and previous smartphone usage experiences were significantly associated with technology anxiety. The findings provide valuable information for multiple stakeholders, including family members of elderly users, product designers, and policymakers. Ameliorating facilitating conditions, improving devices' usage experience, encouraging attempts and focusing on groups with lower educational levels can help to reduce technology anxiety and promote DHT acceptance and use in older age groups.

Research on the influencing factors of promoting flipped classroom teaching based on the integrated UTAUT model and learning engagement theory.

With the rapid advancement of educational technology, the flipped classroom approach has garnered considerable attention owing to its potential for enhancing students' learning capabilities. This research delves into the flipped classroom teaching methodology, employing the Unified Theory of Acceptance and Use of Technology (UTAUT), learning engagement theory, and the 4C skills (comprising communication, collaboration, creativity, and critical thinking) to investigate its effects on learning capabilities. The research surveyed 413 students from three universities in Jiangxi Province, employing stratified random sampling. SPSS 24.0 and Amos were used for structural equation modeling and hypothesis testing analysis. The findings indicate that: (1) Performance expectancy, effort expectancy, and peer influence significantly enhance students' learning engagement in the flipped classroom. (2) Students' learning engagement in the flipped classroom notably promotes their learning capabilities. (3) Performance expectancy, effort expectancy, and peer influence can significantly boost learning capabilities by increasing learning engagement. (4) Personality traits significantly moderate the effect of peer influence on learning engagement, highlighting the crucial role of individual differences in learning. (5) The level of students' learning engagement is differentially influenced by performance expectancy and peer influence across various academic disciplines. Ultimately, this research provides valuable insights for educational policymakers and guides improvements in teaching practices, collectively advancing educational quality and equity.

Exploring the recycled water acceptance based on the technological perspective of UTAUT2: a hybrid analytical approach.

Introduction: The development of advanced sewage technologies empowers the industry to produce high-quality recycled water, which greatly influences human's life and health. Thus, this study investigates the mechanism of individuals' adoption of recycled water from the technology adoption perspective. Methods: Employing the mixed method of structural equation modeling and artificial neural network analysis, we examined a research model developed from the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) framework. To examine the research model, this study employs a leading web-survey company (Sojump) to collect 308 valid samples from the residents in mainland China. Results: The structural equation modeling results verified the associations between the six predictors (performance expectancy, effort expectancy, social influence, facilitating conditions, environmental motivation, and price value), individuals' cognitive and emotional attitudes, and acceptance intention. The artificial neural network analysis validates and complements the structural equation modeling results by unveiling the importance rank of the significant determinants of the acceptance decisions. Discussion: The study provides theoretical implications for recycled water research and useful insights for practitioners and policymakers to reduce the environmental hazards of water scarcity.