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.

UNASSIGNED: 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).
UNASSIGNED: 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.
UNASSIGNED: The results revealed that trust had a significant impact on Perceived Usefulness (β = 0.099) and Perceived Ease of Use (β = .157), and eHealth literacy had a significant impact on Perceived Ease of Use (β = 0.438) and Perceived Usefulness (β = 0.454). Additionally, Perceived Usefulness partially influenced behavioral intention (β = 0.123), and attitude had a significant influence on behavioral intention (β = 0.612). The analysis revealed an insignificant impact of eHealth literacy on Perceived Usefulness (β = 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.
UNASSIGNED: 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.

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.

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.

OBJECTIVE: 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.
CONCLUSIONS: 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.

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.
BACKGROUND: PROSPERO CRD42023431579; https://tinyurl.com/55cxkm26.
UNASSIGNED: DERR1-10.2196/52973.

The purpose of this study was to assess the significant factors that impact pregnant women\'s willingness to use smart fetal heart-rate monitoring devices. We propose a research model that integrates technological factors (perceived compatibility and perceived credibility) and personal factors (health anxiety, personal physiological conditions, health consciousness, and health beliefs). The subjects of this study were Chinese women who were pregnant or had previously given birth. Data were collected and analyzed from 397 paper-and-pencil and electronic questionnaires. Our structural equation model indicated that perceived usefulness (β = 0.490, t = 7.591, p < 0.001), perceived ease of use (β = 0.352, t = 5.631, p < 0.001), health anxiety (β = 0.095, t = 2.664, p = 0.008), personal physiological conditions (β = 0.075, t = 2.142, p = 0.032), and health consciousness (β = 0.078, t = 2.110, p = 0.035) were the determinants of the intention to use smart fetal heart-rate monitoring devices, with perceived usefulness having the highest degree of influence. Furthermore, we discovered that the levels of perceived compatibility and perceived credibility did not have direct correlations with the intention to use these devices, but they did significantly influence the model. Perceived compatibility (β = 0.345, t = 6.601, p < 0.001) and perceived credibility (β = 0.519, t = 9.958, p < 0.001) significantly influences perceived ease of use. Perceived credibility (β = 0.421, t = 7.802, p < 0.001) significantly influences perceived usefulness. Based on these results, suggestions for future research are put forward.

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.

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.

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.