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BACKGROUND: In an aging and information-driven society, older adults have distinct perceptions of and specific demands for digital medical services. It is essential for society to understand these needs and develop a more thoughtful approach to digital health care. OBJECTIVE: This study aims to evaluate the behavioral intention and satisfaction of older adults with digital medical services by identifying the perceived factors and the pathways through which these factors influence their behavior. METHODS: This study used a mixed methods approach, combining qualitative and quantitative analyses. A focus group interview was conducted with 30 randomly selected older adults, and the interviews were transcribed verbatim and coded using grounded theory. In addition, 876 valid questionnaires were collected to describe older adults' perceptions of and satisfaction with digital medical care. Then, t tests and ANOVA were used to explore differences among various demographic groups, while hierarchical multiple regression was conducted to identify the factors most closely related to satisfaction. Structural equation modeling was used to identify multiple mediating effects. RESULTS: The qualitative study identified the core category of "medical service relief and transformation paths for older adults in the context of digital reform." Quantitative analysis revealed that more than half of the older adults were satisfied with digital medical services, and behavioral intentions were higher among those with higher incomes and education levels. Structural equation modeling confirmed that external variables, such as digital skills training, positively influenced perceived ease of use (ß=.594, P<.001), perceived usefulness (ß=.544, P<.001), and promoted digital medical behavioral intentions (ß=.256, P<.001), while also reducing perceived risk (ß=-.295, P<.001). Additionally, perceived ease of use (ß=.168, P<.001) and perceived usefulness (ß=.508, P<.001) positively impacted behavioral intention, whereas perceived risk (ß=-.05, P=.037) exerted a negative influence. Furthermore, behavioral intention (ß=.641, P<.001) significantly and positively affected older adults' satisfaction with digital medical care. The mediation test identified 4 significant paths: (1) external variables → perceived ease of use → behavioral intention (effect size of 13.9%); (2) external variables → perceived usefulness → behavioral intention (effect size of 38.4%); (3) external variables → perceived ease of use → perceived usefulness → behavioral intention (effect size of 10.1%); and (4) a direct effect (35.5%) from external variables to behavioral intention. CONCLUSIONS: Based on the study's findings, addressing the needs of older adults and enhancing perceived usefulness are the most effective ways to encourage the use of digital health care devices. Community support plays a crucial role in helping older adults integrate into digital health care, and adapting the design of services and products to suit their needs improves their perceptions of digital health care. This, in turn, promotes usage behavior and satisfaction, while the negative impact of perceived risk remains minimal.

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Objective: This study investigates the interplay between the Technology Acceptance Model (TAM), self-regulation strategies, and academic self-efficacy, and their collective impact on academic performance and perceived learning among college students engaged in remote education. Methods: A sample of 872 university students from Southern China participated in this study. Structural Equation Modeling (SEM) was employed to analyze the theoretical relationships among the variables. The research focused on two primary areas: the connection between academic self-efficacy and gameful self-regulation strategies within the framework of TAM, and the influence of TAM's three dimensions on students' perceived learning and academic performance. Results: Findings highlight self-efficacy and gameful self-regulation strategies, in enhancing technology acceptance. Improved acceptance of technology is shown to positively affect academic performance and the perceived learning experience of students in classes using game-based online resources. Conclusion: The study emphasizes the significance of self-efficacy and gameful self-regulation strategies in shaping students' perceptions and attitudes towards technology. These factors are found to be key determinants of both perceived learning and academic achievement in the context of game-based online resource classes.

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Young healthcare professionals and medical graduates often fall short in the practical experience necessary for handling medical emergencies. This can not only lead to strained feelings of inadequacy and insecurity among future physicians and less experienced healthcare providers in general, but also to detrimental outcomes for patients as emergency medicine demands rapid decision-making with low tolerance for errors. New didactic modalities and approaches may be needed to effectively address this shortcoming. Immersive technologies are powerful novel educational tools with untapped potential in medical training, and may be particularly suitable for simulation trainings in the high-stakes field of emergency medicine.Herein, we systematically explored the educational potential of extended reality (XR) technology, particularly virtual reality (VR), in the management of patients presenting as medical emergencies, combining the use of the STEP-VR application with an untethered hardware setup.Importantly, we aimed at studying multiple, large cohorts of senior medical students involving a total of 529 participants and collecting data over a period of two years. We assessed students' acceptance of the training through a modified questionnaire measuring device handling, content complexity, degree of immersion, learning success, and seminar design.Our results show high, sustained acceptance and ease of use across different student cohorts and subgroups, with most students finding XR/VR engaging and beneficial for acquiring emergency medicine skills. Importantly, the prevalence of simulation sickness was minimal. Moreover, no major effect of the head-mounted displays (HMDs) price range was noted with regard to the learning experience. The results underscore the potential of XR/VR capabilities in effectively enhancing medical education, particularly in areas of high-stakes clinical scenarios and emergency care, by providing realistic and reproducible immersive training environments.In summary, our findings suggest that XR/VR-based training approaches could significantly contribute to preparing future physicians for the complexities of emergency medical care, encouraging the integration of such technologies into medical curricula. However, careful consideration must be given to its suitability for all students and the practical challenges of its implementation, highlighting the need for further research to harness its full potential for medical education.

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The "SmartCaregivers" 1.0 mobile application is a beacon of hope for caregivers (CG) in rural areas, often facing limited access to facilities and support. This study, conducted from February to August 2021, aimed to comprehensively analyze the need for developing a database system and a mobile application tailored to enhance caregiver support and resource management for long-term dependent individuals in the rural areas of Maha Sarakham province, Thailand. The research followed a rigorous research and development (R & D) approach, specifically the ADDIE model (analysis, design, development, implementation, and evaluation). Data were collected from 402 caregivers and 10 key informants through surveys and interviews, as well as from 402 caregivers during the implementation and evaluation phases. The application's impact was assessed using a quasi-experimental design with a one-group pre-post-test, and its acceptance was evaluated through the technology acceptance model (TAM). The application significantly improved caregivers' knowledge scores, with a mean increase from 10.49 ± 2.53 to 12.18 ± 2.76 post-intervention. High scores for perceived usefulness (4.36 ± 0.62) and ease of use (4.31 ± 0.59) reassure the audience about the application's effectiveness in providing rapid access to health information, aiding decision-making, and improving care coordination. The system quality was also highly rated, with users appreciating the variety of functions and structural design. This potential for transformation and improvement instills hope and optimism for the future of caregiving in rural areas.

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This study investigates Romanian physicians' acceptance of telemedicine using the Technology Acceptance Model. We analyzed 1093 responses to an online survey distributed nationwide to physicians via email by the National Authority of Quality Management in Health, employing the partial least squares algorithm to estimate the relationship between the behavioral intention to adopt telemedicine and its potential determinants. Our findings reveal that the model accounts for 84.6% of the variance in behavioral intention to use telemedicine. Among the two constructs of the TAM model, perceived usefulness is a stronger predictor of behavioral intention than perceived ease of use. Additionally, subjective norms positively and significantly influence physicians' intention to use telemedicine and their perception of its usefulness. Furthermore, perceived incentives and accessibility to medical records also positively impact the behavioral intention to use telemedicine.

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Background: Technology has completely transformed healthcare, starting with X-ray machines and MRIs to telehealth and robotic surgeries to e-health records. The launch of minimally invasive surgery (MIS) serves as a milestone in medical history, offering benefits such as smaller incisions, shorter hospital stays, and faster recovery, making it a preferred surgical option. This study mainly explores patients' willingness to adopt robot-assisted surgery (RAS) technology in a surgical intervention and is assessed in the backdrop of the Technology Acceptance Model (TAM). Methods: This research project employs a post-positivist research philosophy and a cross-sectional research design. A structured, pre-tested questionnaire was used to collect data from 280 respondents. Results: The results revealed that trust had a significant impact on Perceived Usefulness (ß = 0.099) and Perceived Ease of Use (ß = .157), and eHealth literacy had a significant impact on Perceived Ease of Use (ß = 0.438) and Perceived Usefulness (ß = 0.454). Additionally, Perceived Usefulness partially influenced behavioral intention (ß = 0.123), and attitude had a significant influence on behavioral intention (ß = 0.612). The analysis revealed an insignificant impact of eHealth literacy on Perceived Usefulness (ß = 0.067). The Standard Root Mean Square Residual (SRMR) value was <0.8. Mediation analysis also revealed partial mediation between the constructs. The SRMR rating of this model is 0.067, indicating that it fits the data well. Conclusion: This study revealed that a patient's intention will be high if he or she believes that RAS is beneficial in treating his or her ailment. In comparison, information related to RAS is clearly known, and it does not directly affect selection intention. eHealth literacy is a significant antecedent to patients' behavioral intention. Hence, the healthcare industry must devise strategies to promote the acceptance of RAS at all levels.

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The use of artificial intelligence in education (AIEd) has become increasingly significant globally. In China, there is a lack of research examining the behavioral intention toward AIEd among pre-service special education (SPED) teachers in terms of digital literacy and teacher self-efficacy. Building on the technology acceptance model, our study evaluated the aspects influencing pre-service special education teachers' intention toward AI in education. Data was gathered from 274 pre-service SPED teachers studying at a Chinese public normal university of special education and analyzed using structural equation modeling (SEM). The results show that digital literacy is associated with the perceived usefulness and ease of use of AIEd, which influences SPED teachers' intention to use AIEd. Additionally, digital literacy significantly impacts the self-efficacy of SPED teachers. Given these results, AI designers in special education should comprehend the effectiveness and usability of AIEd for fostering behavioral intention formation. Simultaneously, special educational programs that identify key content and activities for digital literacy training should be developed, and educators should attempt to execute the relevant pre-service training to enhance the intention of pre-service SPED teachers toward AIEd.

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BACKGROUND: Cardiometabolic diseases (CMDs) are a group of interrelated conditions, including heart failure and diabetes, that increase the risk of cardiovascular and metabolic complications. The rising number of Australians with CMDs has necessitated new strategies for those managing these conditions, such as digital health interventions. The effectiveness of digital health interventions in supporting people with CMDs is dependent on the extent to which users engage with the tools. Augmenting digital health interventions with conversational agents, technologies that interact with people using natural language, may enhance engagement because of their human-like attributes. To date, no systematic review has compiled evidence on how design features influence the engagement of conversational agent-enabled interventions supporting people with CMDs. This review seeks to address this gap, thereby guiding developers in creating more engaging and effective tools for CMD management. OBJECTIVE: The aim of this systematic review is to synthesize evidence pertaining to conversational agent-enabled intervention design features and their impacts on the engagement of people managing CMD. METHODS: The review is conducted in accordance with the Cochrane Handbook for Systematic Reviews of Interventions and reported in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Searches will be conducted in the Ovid (Medline), Web of Science, and Scopus databases, which will be run again prior to manuscript submission. Inclusion criteria will consist of primary research studies reporting on conversational agent-enabled interventions, including measures of engagement, in adults with CMD. Data extraction will seek to capture the perspectives of people with CMD on the use of conversational agent-enabled interventions. Joanna Briggs Institute critical appraisal tools will be used to evaluate the overall quality of evidence collected. RESULTS: This review was initiated in May 2023 and was registered with the International Prospective Register of Systematic Reviews (PROSPERO) in June 2023, prior to title and abstract screening. Full-text screening of articles was completed in July 2023 and data extraction began August 2023. Final searches were conducted in April 2024 prior to finalizing the review and the manuscript was submitted for peer review in July 2024. CONCLUSIONS: This review will synthesize diverse observations pertaining to conversational agent-enabled intervention design features and their impacts on engagement among people with CMDs. These observations can be used to guide the development of more engaging conversational agent-enabled interventions, thereby increasing the likelihood of regular intervention use and improved CMD health outcomes. Additionally, this review will identify gaps in the literature in terms of how engagement is reported, thereby highlighting areas for future exploration and supporting researchers in advancing the understanding of conversational agent-enabled interventions. TRIAL REGISTRATION: PROSPERO CRD42023431579; https://tinyurl.com/55cxkm26. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52973.

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In Thailand, increasing caregiving needs for senior citizens, particularly in low-income homes, may elevate the caregiver (CG) burden. This study assesses the user acceptance and usability of the 'SmartCG' mobile application in enhancing healthcare management. The app offers health evaluations, home visits, knowledge management, screening forms, and care plans. Using the Technology Acceptance Model, 402 caregivers from Mahasarakham province evaluated the app's usability on a 5-point Likert scale. Results showed a significant increase in acceptance scores after using SmartCG (11.49 ± 1.54 to 13.19 ± 2.74, p < 0.001). Users reported high satisfaction with its ease of use (mean = 4.10 ± 0.61) and found the knowledge-based menu (mean = 4.07 ± 0.63) and visiting/map menus (mean = 4.05 ± 0.63) user-friendly. This study provides empirical evidence that the SmartCG app effectively enhances healthcare management, emphasizing the importance of user-friendly interfaces in healthcare technology.

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A quality systematic literature review was conducted about the use of TAM questionnaire for Telemedicine and IT healthcare systems worldwide by health professionals to investigate most valuable predictors for IT systems acceptance and possible parameters that influence them. The results highlight that perceived usefulness and perceived ease of use are the most important predictors and the development of the tool should also involve individual, social and organizational factors.

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OBJECTIVES: The purpose of this study was to investigate the HEV vaccination intention, its determinants, and overall influence mechanisms among childbearing-age women. METHOD: The current study was cross-sectional and conducted online from June 25, 2023 to September 25, 2023 in Nanjing, China. Logistic regression models were constructed to identify the intention-associated background factors. Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB) were integrated and expanded as TAM-TPB model to further investigate the determinants and overall influence mechanism of HEV vaccination intention among this population using structural equation modeling. RESULTS: A total of 423 eligible participants were included in this study. High general HEV knowledge was independently associated with an increased intention to get HEV vaccination (OR = 1.97, 95 % CI: 1.11-3.58, P = 0.023). All the hypotheses proposed in the theoretical TAM-TPB model were supported, with perceived ease of use, perceived usefulness, attitude, subjective norm, and perceived behavioral control positively affecting the intention of HEV vaccination (all P values <0.05), while perceived risk (P = 0.003) exhibited an inverse association with HEV vaccination intention. The model achieved an acceptable fit, and the total explained variance of HEV vaccination intention was as high as 86.20 %. Moreover, no significant common method bias was observed. CONCLUSION: This is the first theory-based study that explored the HEV vaccination intention, its determinants, and overall influence mechanism among childbearing-age women. The results of the current study are of great importance for improving the understanding of the HEV vaccination intention among females of childbearing age.

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OBJECTIVES: To describe the perceptions of telehealth services among lung cancer patients in rural areas of China, as well as to explore the potential of telemedicine to improve long-term health recovery at home for rural lung cancer patients. METHODS: A qualitative descriptive study design was used in this study and we conducted semi-structured interviews with 14 rural Chinese lung cancer patients between December 2022 and March 2023. Interview content was analyzed using Nvivo software and a framework analysis was performed using the Technology Acceptance Model to identify meaningful themes. RESULTS: Participants identified perceptual and technical factors related to perceived ease of use, benefits and drawbacks related to perceived usefulness, and facilitators and barriers related to intention to use. However, regional and disease features including literacy barriers, medical insurance condition, symptom burden, and rural cultural health seeking behavior conduct must be taken into account. CONCLUSIONS: Lung cancer patients in rural China believe that telehealth services could be an alternative solution for addressing health and care needs, but various aspects, such as user interface design, cost-effectiveness, and technological anxiety, need to be optimized. IMPLICATIONS FOR NURSING PRACTICE: More highly specialized nursing team, friendly telecare lung function modules, and media technology training courses should be developed for rural lung cancer patients to enhance the quality of their home care, meet their information needs and better control their disease progression.

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BACKGROUND: During the COVID-19 pandemic, there was a rapid adoption of telehealth care services as a public health strategy to maintain access to essential health care. In Australia, there has been increasing optimism for the expansion of telehealth services. However, little is known about the patterns and determinants of telehealth adoption among older adults, with concerns that an expansion of telehealth services may only be of benefit to those who already have better access to health care. OBJECTIVE: Leveraging data collected by The Sax Institute's 45 and Up COVID Insights study between November 2020 and April 2022, the objective of this study was to identify and describe the sociodemographic and health-related determinants of telehealth adoption and use among a cohort of older Australians. We hypothesized that health-related factors would be key determinants of telehealth adoption for Australians aged ≥65 years during the COVID-19 pandemic. METHODS: A repeated cross-sectional design was used. The relationships between telehealth use (classified as low, moderate, or high) and selected sociodemographic and health-related characteristics were assessed using logistic regression techniques. Variable selection and findings were situated within the Technology Acceptance Model, the Unified Theory of Acceptance, and the Use of Technology theoretical frameworks. RESULTS: Of the 21,830 participants aged ≥65 years, the proportion who indicated adopting telehealth ranged from 50.77% (11,082/21,830) at survey 1 in 2020 to 39.4% (7401/18,782) at survey 5 in 2022. High levels of telehealth use were associated with being female, aged <85 years, living in a major city, cohabiting with others, and being from the most socioeconomically disadvantaged areas (deciles 1-3). Individuals with a disability, chronic disease, multimorbidity, and lower perceived quality of life and those experiencing missed or delayed care were significantly more likely to use telehealth across all levels (P<.001). A temporal association was observed, whereby participants who engaged with telehealth services before or early in the pandemic (as assessed in survey 1) were more likely to continue telehealth use when assessed in survey 5 in 2022 (P<.001). CONCLUSIONS: This research contributes to the broader understanding of telehealth adoption and use among older adults. As telehealth models of care expand, there is an opportunity to tailor these services to the needs of older adults, particularly those living with chronic diseases and multimorbidity, by using targeted strategies that overcome barriers to accessing specialized health care services.

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AIM: This study explores the influencing factors of attitudes and behaviors toward use of ChatGPT based on the Technology Acceptance Model among registered nurses in Taiwan. BACKGROUND: The complexity of medical services and nursing shortages increases workloads. ChatGPT swiftly answers medical questions, provides clinical guidelines, and assists with patient information management, thereby improving nursing efficiency. INTRODUCTION: To facilitate the development of effective ChatGPT training programs, it is essential to examine registered nurses' attitudes toward and utilization of ChatGPT across diverse workplace settings. METHODS: An anonymous online survey was used to collect data from over 1000 registered nurses recruited through social media platforms between November 2023 and January 2024. Descriptive statistics and multiple linear regression analyses were conducted for data analysis. RESULTS: Among respondents, some were unfamiliar with ChatGPT, while others had used it before, with higher usage among males, higher-educated individuals, experienced nurses, and supervisors. Gender and work settings influenced perceived risks, and those familiar with ChatGPT recognized its social impact. Perceived risk and usefulness significantly influenced its adoption. DISCUSSION: Nurse attitudes to ChatGPT vary based on gender, education, experience, and role. Positive perceptions emphasize its usefulness, while risk concerns affect adoption. The insignificant role of perceived ease of use highlights ChatGPT's user-friendly nature. CONCLUSION: Over half of the surveyed nurses had used or were familiar with ChatGPT and showed positive attitudes toward its use. Establishing rigorous guidelines to enhance their interaction with ChatGPT is crucial for future training. IMPLICATIONS FOR NURSING AND HEALTH POLICY: Nurse managers should understand registered nurses' attitudes toward ChatGPT and integrate it into in-service education with tailored support and training, including appropriate prompt formulation and advanced decision-making, to prevent misuse.

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This study employs the Technology Acceptance Model to investigate the factors influencing Saudi Arabian diabetic patients' intention to use digital health services. There is an urgent need to investigate the possibilities of digital health services in managing diabetes given the startlingly rapidly increasing prevalence rate of diabetes in KSA. The study examines the variables affecting patients' acceptance and desire to use digital health tools to manage their diabetes. The study employs the Technology Acceptance Model to ascertain the crucial factors that impact patients' opinions regarding the usefulness and ease of use of digital healthcare technologies. The proposed model extends the traditional Technology Acceptance Model by adding two new constructs, perceived privacy and trust. These constructs were examined by analyzing the intentions of 600 respondents through online surveys. The study's conclusions showed that attitudes toward using digital health services for KSA diabetic patients are greatly influenced by every component of the extended Technology Acceptance Model. The study's conclusions add to the body of knowledge already in existence and offer insightful information to decision-makers hoping to improve digital health services.

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This study analyzes the perception and usage of ChatGPT based on the technology acceptance model (TAM). Conducting reticular analysis of coincidences (RAC) on a convenience survey among university students in the social sciences, this research delves into the perception and utilization of this artificial intelligence tool. The analysis considers variables such as gender, academic year, prior experience with ChatGPT, and the training provided by university faculty. The networks created with the statistical tool "CARING" highlight the role of perceived utility, credibility, and prior experience in shaping attitudes and behaviors toward this emerging technology. Previous experience, familiarity with video games, and programming knowledge were related to more favorable attitudes towards ChatGPT. Students who received specific training showed lower confidence in the tool. These findings underscore the importance of implementing training strategies that raise awareness among students about both the potential strengths and weaknesses of artificial intelligence in educational contexts.

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This paper presents the impact of using virtual reality (VR) in education and focuses on the main factors that affect the behavioral intention of using this new technology for the benefit of both professors and students. As part of our research methodology, we conducted a survey based on the Technology Acceptance Model and used partial least squares structural equation modelling. The results show that the intention to use VR technology in education is influenced by both usage satisfaction and the task-technology fit. The system quality of the VR technology proved to be important in influencing both the task-technology fit and perceived usefulness. The findings are useful for professors considering the adoption of new technologies that might improve the efficiency of learning for their students. Additionally, managers of educational institutions can use these insights to direct investments towards this type of innovation, which appeals to newer generations.

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This study investigates the acceptance of large language models (LLMs) among older adults using the Technology Acceptance Model (TAM). The research, conducted through a cross-sectional survey, explores the influence of perceived ease of use and perceived usefulness on intension to use among older adults. The results show that the subjective norm, image, job relevance, output quality, result demonstrability, perceived ease of use have a significant positive and direct impact on perceived usefulness (ß=0.138, 0.240, 0.213, 0.280, 0.181, 0.176, P<0.05). Perceived ease of use and perceived usefulness have a significant positive and direct impact on Intension to use (ß=0.335, 0.307, P<0.05). The study's practical implications highlight the need for tailored chatbots, offering valuable insights for developers and policymakers aiming to enhance the integration of innovative technologies among older populations.

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The health sector has prioritized the physical health of vulnerable Generation X individuals at high Coronavirus risk. Despite vaccination efforts, both infected and healthy people continue facing health threats. Unlike other industries devastated by COVID-19, wearable fitness technology equipment (WFTE) is essential for health-focused individuals. This research examined customers' intention to use WFTE using an adapted Technology Acceptance Model (TAM) framework. A key contribution is the inclusion of perceived health risk and its impact on WFTE value perceptions and usage attitudes post-pandemic. The study gathered qualitative data from coronavirus patients and survey data from 513 participants. Structural equation modeling analysis supported the theoretical model. While the standard TAM evaluated intent to use WFTE, this study uniquely examined how WFTE's functional, hedonic, and symbolic value shapes its perceived value. Perceived health risk was found to significantly impact perceived WFTE value and usage attitudes after the pandemic recovery. Findings offer managerial implications to boost WFTE adoption among the vulnerable Generation X demographic.

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Introduction: The outbreak of the novel coronavirus disease-19 posed significant challenges globally, impacting various sectors and health care systems profoundly. In response, telemedicine has emerged as a vital solution to address health care demands and resource shortages. However, there is a lack of comprehensive research on telemedicine usage among health care consumers in urban and rural areas of Taiwan. Methods: This study aimed to investigate the usage, attitudes, and intentions of telemedicine utilization among health care consumers in Taiwan, integrating the Technology Acceptance Model and Theory of Planned Behavior. A cross-sectional study was conducted from April 2023 to May 2024, involving 1,053 participants who utilized telemedicine services. Structured questionnaires were used for data collection, and statistical analyses were performed using SPSS 21.0 software. Results: The results revealed significant disparities in telemedicine utilization between urban and rural areas, with urban residents exhibiting higher levels of perceived ease of use, perceived usefulness, attitude toward use, trust, and intention to use telemedicine. Regression analysis indicated a significant association between urban residence and male gender with telemedicine utilization, contrary to previous research findings. These disparities may stem from differences in health care accessibility and cultural norms prevalent in urban and rural areas. Conclusions: Further investigation into gender differences and interventions to promote telemedicine usage among females, particularly in urban areas, are recommended. This study provides valuable insights for future research and health care policy formulation.