UNASSIGNED: Constant technological improvements require practitioners to be open to adopting technologies such as telehealth for enhanced patient care. Understanding the barriers and facilitators of telehealth adoption will guide stakeholders in making decisions for safe and effective implementation of telehealth.
UNASSIGNED: Effective use of telehealth improves patient outcomes. It is unclear if optometry students feel supported in using and/or are accepting of telehealth. This study evaluated telehealth acceptance of optometry students, its association with their technology self-efficacy, and whether telehealth training alters this relationship.
UNASSIGNED: Final-year optometry students at the University of Melbourne were invited to participate in a telehealth course. A 22-item online survey adapted from the Technology Proficiency Self-Assessment for twenty-first Century Learning was used to evaluate technology self-efficacy pre- and post-learning. Telehealth acceptance was evaluated using a 34-item survey according to the Unified Theory of Acceptance and Use of Technology-2. A 5-point Likert scale was used for each item, yielding two total scores. Respondent demographics, frequency of usage and number of devices were recorded. Descriptive statistics, ANOVA and Pearson correlation were used to analyse demographic variables and relationship between technology self-efficacy and telehealth acceptance.
UNASSIGNED: 58 (68%) and 49 (58%) students participated in the pre- and post-learning surveys. Majority were 20-29-year-old females. Students used between two and four devices for online activities, with 62% being online at least hourly. Technology self-efficacy scores (average ± SD) pre- and post-learning were 83.8% ± 8.2 and 87.8% ± 7.1. Telehealth acceptance scores pre- and post-learning were 66.1% ± 9.6 and 73.98% ± 9.9. There was no association with gender, number of devices and frequency of online use for all scores. Correlation between technology self-efficacy and telehealth acceptance was insignificant pre-learning (p = 0.3) but was significant post-learning (p = 0.04).
UNASSIGNED: Optometry students demonstrated high technology self-efficacy compared to telehealth acceptance. Telehealth training resulted in marked improvement in telehealth acceptance.

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 (β), 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 (β = 0.215, p-value < 0.018), performance expectancy (β = 0.245, p-value < 0.001), and attitude (β = 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.
CONCLUSIONS: 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.

UNASSIGNED: Artificial intelligence (AI) chatbots have the potential to assist individuals with chronic health conditions by providing tailored information, monitoring symptoms, and offering mental health support. Despite their potential benefits, research on public attitudes toward health care chatbots is still limited. To effectively support individuals with long-term health conditions like long COVID (or post-COVID-19 condition), it is crucial to understand their perspectives and preferences regarding the use of AI chatbots.
UNASSIGNED: This study has two main objectives: (1) provide insights into AI chatbot acceptance among people with chronic health conditions, particularly adults older than 55 years and (2) explore the perceptions of using AI chatbots for health self-management and long COVID support.
UNASSIGNED: A web-based survey study was conducted between January and March 2023, specifically targeting individuals with diabetes and other chronic conditions. This particular population was chosen due to their potential awareness and ability to self-manage their condition. The survey aimed to capture data at multiple intervals, taking into consideration the public launch of ChatGPT, which could have potentially impacted public opinions during the project timeline. The survey received 1310 clicks and garnered 900 responses, resulting in a total of 888 usable data points.
UNASSIGNED: Although past experience with chatbots (P<.001, 95% CI .110-.302) and online information seeking (P<.001, 95% CI .039-.084) are strong indicators of respondents\' future adoption of health chatbots, they are in general skeptical or unsure about the use of AI chatbots for health care purposes. Less than one-third of the respondents (n=203, 30.1%) indicated that they were likely to use a health chatbot in the next 12 months if available. Most were uncertain about a chatbot\'s capability to provide accurate medical advice. However, people seemed more receptive to using voice-based chatbots for mental well-being, health data collection, and analysis. Half of the respondents with long COVID showed interest in using emotionally intelligent chatbots.
UNASSIGNED: AI hesitancy is not uniform across all health domains and user groups. Despite persistent AI hesitancy, there are promising opportunities for chatbots to offer support for chronic conditions in areas of lifestyle enhancement and mental well-being, potentially through voice-based user interfaces.

This study aimed to investigate the acceptance of adapted physical activity (APA) by teachers and students before the use of a mobile telepresence robot (MTR), used to remotely supervise isolated older adults\' physical activity. While previous studies have shown MTR to be fairly well accepted by older adults, nothing is known about its acceptance by APA teachers themselves. However, if they did not accept it, the MTR would not be used in the end. This would be a public health issue because isolated older adults would not benefit from supervised APA, yet beneficial to their health. To this end, 334 participants answered a survey that measured different psychological variables, based on the technology acceptance model (TAM). Student\'s t-tests and structural equation modeling were used for data processing. Results showed that, before use, there was not any significant difference between teachers\' and students\' acceptance of the MTR. Then, perceived usefulness for teaching APA, perceived ease of use, perceived enjoyment, and intention to use the MTR were lower than the mean of the scale, while perceived usefulness for older adults was higher than the mean of the scale. Finally, this study has validated an extended version of the TAM (including the need for competence and MTR self-efficacy), which allowed it to explain 84.3% of the variance of the students\' and APA teachers\' intention to use the MTR for teaching APA to isolated older adults. Initial obstacles to the use of the MTR seem to exist on the part of APA teachers, prior to their first use, whereas this is not the case for older adults. APA teachers\' acceptance should therefore be investigated in future studies to examine whether this trend is confirmed after the effective use of the MTR.

BACKGROUND: As digital technologies and especially artificial intelligence (AI) become increasingly important in health care, it is essential to determine whether and why potential users intend to use related health information systems (HIS). Several theories exist, but they focus mainly on aspects of health care or information systems, in addition to general psychological theories, and hence provide a small number of variables to explain future behavior. Thus, research that provides a larger number of variables by combining several theories from health care, information systems, and psychology is necessary.
OBJECTIVE: This study aims to investigate the intention to use new HIS for decisions concerning short- and long-term medical treatments using an integrated approach with several variables to explain future behavior.
METHODS: We developed an integrated theoretical model based on theories from health care, information systems, and psychology that allowed us to analyze the duality approach of adaptive and nonadaptive appraisals and their influence on the intention to use HIS. We applied the integrated theoretical model to the short-term treatment using AI-based HIS for surgery and the long-term treatment of diabetes tracking using survey data with structured equation modeling. To differentiate between certain levels of AI involvement, we used several scenarios that include treatments by physicians only, physicians with AI support, and AI only to understand how individuals perceive the influence of AI.
RESULTS: Our results showed that for short- and long-term treatments, the variables perceived threats, fear (disease), perceived efficacy, attitude (HIS), and perceived norms are important to consider when determining the intention to use AI-based HIS. Furthermore, the results revealed that perceived efficacy and attitude (HIS) are the most important variables to determine intention to use for all treatments and scenarios. In contrast, abilities (HIS) were important for short-term treatments only. For our 9 scenarios, adaptive and nonadaptive appraisals were both important to determine intention to use, depending on whether the treatment is known. Furthermore, we determined R² values that varied between 57.9% and 81.7% for our scenarios, which showed that the explanation power of our model is medium to good.
CONCLUSIONS: We contribute to HIS literature by highlighting the importance of integrating disease- and technology-related factors and by providing an integrated theoretical model. As such, we show how adaptive and nonadaptive appraisals should be arranged to report on medical decisions in the future, especially in the short and long terms. Physicians and HIS developers can use our insights to identify promising rationale for HIS adoption concerning short- and long-term treatments and adapt and develop HIS accordingly. Specifically, HIS developers should ensure that future HIS act in terms of HIS functions, as our study shows that efficient HIS lead to a positive attitude toward the HIS and ultimately to a higher intention to use.

Robot-assisted physical rehabilitation offers promising benefits for patients, yet its adoption among therapists remains a complex challenge. This study investigates the acceptance of robot-assisted physical rehabilitation technology among therapists in Vietnam, a middle-income country with a growing demand for rehabilitation services. Drawing on the Technology Acceptance Model 2 (TAM2) and the Theory of Planned Behaviour (TPB), an online survey and semi-structured interviews were conducted to explore therapists\' attitudes and intentions towards using this technology. The results show that Vietnamese therapists recognised its potential benefits and expressed a willingness to use it. Although having similar acceptance patterns compared to developed regions, they demonstrated significantly higher levels of agreement across acceptance constructs. This may be attributed to factors such as the novelty effect, cultural perceptions of robots, and the high workload of therapists in Vietnam. Gender and location were found to influence two acceptance constructs-subjective norms and image, respectively-highlighting the need for tailored strategies in technology implementation. The study underscores the importance of considering socio-cultural factors in the adoption of technology and provides insights for enhancing the acceptance and effectiveness of robot-assisted physical rehabilitation in Vietnam. This contributes to the global understanding of therapist acceptance of technology in this field.
While robot-assisted physical rehabilitation offers promising benefits, there is limited understanding of therapist acceptance on a global scale, highlighting the need for more research in this area.This study in a middle-income country, Vietnam, reveals a generally positive view among therapists, but specific issues such as the novelty effect, cultural perceptions of robots, and high therapist workload impact acceptance levels, indicating the need for tailored strategies.Strategies for implementing robot-assisted physical rehabilitation should include addressing training needs, providing technological support, and considering sociocultural factors to enhance acceptance and effectiveness.

Robot technologies could lead to radical changes in farming. But what does the public know and think about agricultural robots? Recent experience with other agricultural technologies-such as plant genetic engineering-shows that public perceptions can influence the pace and direction of innovation, so understanding perceptions and how they are formed is important. Here, we use representative data from an online survey (n = 2269) to analyze public attitudes towards crop farming robots in Germany-a country where new farming technologies are sometimes seen with skepticism. While less than half of the survey participants are aware of the use of robots in agriculture, general attitudes are mostly positive and the level of interest is high. A framing experiment suggests that the type of information provided influences attitudes. Information about possible environmental benefits increases positive perceptions more than information about possible food security and labor market effects. These insights can help design communication strategies to promote technology acceptance and sustainable innovation in agriculture.

BACKGROUND: Many supportive cancer care (SCC) services were teledelivered during COVID-19, but what facilitates patients\' intentions to use teledelivered SCC is unknown.
OBJECTIVE: The study aimed to use the unified theory of acceptance and use of technology to investigate the factors associated with the intentions of breast cancer survivors (BCS) in Hong Kong to use various types of teledelivered SCC (including psychosocial care, medical consultation, complementary care, peer support groups). Favorable telehealth-related perceptions (higher performance expectancy, lower effort expectancy, more facilitating conditions, positive social influences), less technological anxiety, and greater fear of COVID-19 were hypothesized to be associated with higher intentions to use teledelivered SCC. Moreover, the associations between telehealth-related perceptions and intentions to use teledelivered SCC were hypothesized to be moderated by education level, such that associations between telehealth-related perceptions and intentions to use teledelivered SCC would be stronger among those with a higher education level.
METHODS: A sample of 209 (209/287, 72.8% completion rate) women diagnosed with breast cancer since the start of the COVID-19 outbreak in Hong Kong (ie, January 2020) were recruited from the Hong Kong Breast Cancer Registry to complete a cross-sectional survey between June 2022 and December 2022. Participants\' intentions to use various types of teledelivered SCC (dependent variables), telehealth-related perceptions (independent variables), and sociodemographic variables (eg, education, as a moderator variable) were measured using self-reported, validated measures.
RESULTS: Hierarchical regression analysis results showed that greater confidence using telehealth, performance expectancy (believing telehealth helps with daily tasks), social influence (important others encouraging telehealth use), and facilitating conditions (having resources for telehealth use) were associated with higher intentions to use teledelivered SCC (range: β=0.16, P=.03 to β=0.34, P<.001). Moreover, 2-way interactions emerged between education level and 2 of the telehealth perception variables. Education level moderated the associations between (1) performance expectancy and intention to use teledelivered complementary care (β=0.34, P=.04) and (2) facilitating conditions and intention to use teledelivered peer support groups (β=0.36, P=.03). The positive associations between those telehealth perceptions and intentions were only significant among those with a higher education level.
CONCLUSIONS: The findings of this study implied that enhancing BCS\' skills at using telehealth, BCS\' and their important others\' perceived benefits of telehealth, and providing assistance for telehealth use could increase BCS\' intentions to use teledelivered SCC. For intentions to use specific types of SCC, addressing relevant factors (performance expectancy, facilitating conditions) might be particularly beneficial for those with a higher education level.

MOOCs, the Massive Open Online Courses, are online educational courses that offer open access to a large number of participants globally. However, online engagement during MOOC learning remains a problem, as reflected in relatively high dropout rates. This paper involves academic and emotional support, aiming to explore whether they contribute to users\' sustainable use of the MOOC platform. A total of 410 college students learning English as a foreign language (EFL) and with MOOC learning experience participated in this study. Employing the structural equation modeling (SEM) techniques, we examined the relationships among five factors in the EFL MOOC learning context: academic support (AS), emotional support (ES), perceived usefulness (PU), perceived ease of use (PEoU), and platform reputation (PR). The results indicate that academic support influences learners\' perceptions of the usefulness and ease of use of the MOOC platform, as well as enhancing learners\' feelings of being emotionally supported. Simultaneously, platform reputation plays a crucial role in influencing learners\' perceptions of MOOC platforms. However, results suggest that emotional support does not have a statistically significant impact on the perceived usefulness and perceived ease of use of the platform in EFL MOOC learning contexts.

This review explores the Metaverse, focusing on user perceptions and emphasizing the critical aspects of usability, social influence, and interoperability within this emerging digital ecosystem. By integrating various academic perspectives, this analysis highlights the Metaverse\'s significant impact across various sectors, emphasizing its potential to reshape digital interaction paradigms. The investigation reveals usability as a cornerstone for user engagement, demonstrating how social dynamics profoundly influence user behaviors and choices within virtual environments. Furthermore, the study outlines interoperability as a paramount challenge, advocating for establishing unified protocols and technologies to facilitate seamless experiences across disparate Metaverse platforms. It advocates for the adoption of inclusive, ergonomically oriented designs aimed at enhancing user participation. It addresses the ethical and societal challenges posed by the Metaverse, including concerns related to digital harassment, invasive marketing practices, and breaches of privacy. Additionally, the review identifies existing gaps in the literature, particularly regarding the Metaverse\'s implications for healthcare, its impact on educational outcomes, and the urgent need for empirical data concerning its long-term effects on user psychology and behavior. By providing a comprehensive synthesis of the current understanding of user experiences and challenges within the Metaverse, this paper contributes to the academic dialogue, laying the groundwork for future research initiatives. It aims to steer the development of the Metaverse towards a trajectory that is ethically sound, socially responsible, inclusive, and aligned with societal expectations, thereby fostering a digital realm that upholds the highest standards of integrity and inclusivity.