The Perceived Usability of Virtual Visits Among Black Adults' Receiving Oncology Care: A Qualitative Analysis.

BACKGROUND: With the COVID-19 pandemic came rapid uptake in virtual oncology care. During this, sociodemographic inequities in access to virtual visits (VVs) have become apparent. To better understand these issues, we conducted a qualitative study to describe the perceived usability and acceptability of VVs among Black adults diagnosed with cancer. METHODS: Adults who self-identified as Black and had a diagnosis of prostate, multiple myeloma, or head and neck cancer were recruited from 2 academic medical centers, and their community affiliates to participate in a semi-structured interview, regardless of prior VV experience. A patient and family advisory board was formed to inform all components of the study. Interviews were conducted between September 2, 2021 and February 23, 2022. Transcripts were organized topically, and themes and subthemes were determined through iterative and interpretive immersion/crystallization cycles. RESULTS: Of the 49 adults interviewed, 29 (59%) had participated in at least one VV. Three overarching themes were derived: (1) VVs felt comfortable and convenient in the right contexts; (2) the technology required for VVs with video presented new challenges, which were often resolved by an audio-only telephone call; and (3) participants reported preferring in-person visits, citing concerns regarding gaps in nonverbal communication, trusting providers, and distractions during VV. CONCLUSION: While VVs were reported to be acceptable in specific circumstances, Black adults reported preferring in-person care, in part due to a perceived lack of interpersonal connectedness. Nonetheless, retaining reimbursement for audio-only options for VVs is essential to ensure equitable access for those with less technology savvy and/or limited device/internet capabilities.

Designing and deploying caller tunes on mobile phones to promote malaria vaccine uptake in Africa: can the technology acceptance model (TAM) help?

Malaria remains a significant global health challenge, with millions of cases and high mortality rates annually, especially in low-income countries. Africa bears a substantial burden, with direct costs of malaria among children under five reaching millions of dollars in countries like Ghana, Tanzania, and Kenya. In 2021, over 610,000 malaria-related deaths were reported, 96% of which occurred in sub-Saharan Africa. Despite existing interventions, such as long-lasting insecticidal nets, indoor residual spraying, and intermittent preventive treatment, the re-emergence of malaria underscores the need for innovative preventive strategies. This study explores the potential of utilizing mobile phone caller tunes to raise awareness and promote the uptake of the RTS,S malaria vaccine. The technology acceptance model (TAM) provides a framework for understanding how users perceive and adopt new technologies. Caller tunes, a mobile phone feature that plays audio for callers waiting to be connected, have been effective in health communication campaigns in Asia and Africa. This approach could be leveraged to enhance malaria vaccine awareness, particularly in low-income countries where vaccine hesitancy is prevalent and malaria endemic. Overall, mobile technologies have significantly improved healthcare delivery in Africa, facilitating communication, monitoring, and treatment adherence in remote areas. Integrating caller tunes with health messages about the malaria vaccine could address vaccine hesitancy and improve uptake. This would require collaboration with telecommunication companies, healthcare providers, and policymakers to design culturally and linguistically appropriate messages. However, the cost of caller tune services, the need for internet access, and cultural differences are the expected challenge that may occur in this approach. Therefore, strategic partnerships and intersectoral approaches can mitigate these issues, making caller tunes a viable tool for public health communication. Raising awareness through this innovative method could enhance the adoption of the RTS,S vaccine and support ongoing malaria control efforts in Africa.

Perceptions and Satisfaction With the Use of Digital Medical Services in Urban Older Adults of China: Mixed Methods Study.

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.

Using the technology acceptance model to assess clinician perceptions and experiences with a rheumatoid arthritis outcomes dashboard: qualitative study.

BACKGROUND: Improving shared decision-making using a treat-to-target approach, including the use of clinical outcome measures, is important to providing high quality care for rheumatoid arthritis (RA). We developed an Electronic Health Record (EHR) integrated, patient-facing sidecar dashboard application that displays RA outcomes, medications, and lab results for use during clinical visits ("RA PRO dashboard"). The purpose of this study was to assess clinician perceptions and experiences using the dashboard in a university rheumatology clinic. METHODS: We conducted focus group (FG) discussions with clinicians who had access to the dashboard as part of a randomized, stepped-wedge pragmatic trial. FGs explored clinician perceptions towards the usability, acceptability, and usefulness of the dashboard. FG data were analyzed thematically using deductive and inductive techniques; generated themes were categorized into the domains of the Technology Acceptance Model (TAM). RESULTS: 3 FG discussions were conducted with a total of 13 clinicians. Overall, clinicians were enthusiastic about the dashboard and expressed the usefulness of visualizing RA outcome trajectories in a graphical format for motivating patients, enhancing patient understanding of their RA outcomes, and improving communication about medications. Major themes that emerged from the FG analysis as barriers to using the dashboard included inconsistent collection of RA outcomes leading to sparse data in the dashboard and concerns about explaining RA outcomes, especially to patients with fibromyalgia. Other challenges included time constraints and technical difficulties refreshing the dashboard to display real-time data. Methods for integrating the dashboard into the visit varied: some clinicians used the dashboard at the beginning of the visit as they documented RA outcomes; others used it at the end to justify changes to therapy; and a few shared it only with stable patients. CONCLUSIONS: The study provides valuable insights into clinicians' perceptions and experiences with the RA PRO dashboard. The dashboard showed promise in enhancing patient-clinician communication, shared decision-making, and overall acceptance among clinicians. Addressing challenges related to data collection, education, and tailoring dashboard use to specific patient populations will be crucial for maximizing its potential impact on RA care. Further research and ongoing improvements in dashboard design and implementation are warranted to ensure its successful integration into routine clinical practice.

Assessing clinical medicine students' acceptance of large language model: based on technology acceptance model.

While large language models (LLMs) have demonstrated significant potential in medical education, there is limited understanding of medical students' acceptance of LLMs and the factors influencing their use. This study explores medical students' acceptance of LLMs in learning and examines the factors influencing this acceptance through the lens of the Technology Acceptance Model (TAM). A questionnaire survey conducted among Chinese medical students revealed a high willingness to use LLMs in their studies. The findings suggest that attitudes play a crucial role in predicting medical students' behavioral intentions to use LLMs, mediating the effects of perceived usefulness, perceived ease of use, and perceived risk. Additionally, perceived risk and social influence directly impact behavioral intentions. This study provides compelling evidence supporting the applicability of the TAM to the acceptance of LLMs in medical education, highlighting the necessity for medical students to utilize LLMs as an auxiliary tool in their learning process.

Clinical virtual simulation: predictors of user acceptance in nursing education.

BACKGROUND: Using virtual patients integrated in simulators expands students' training opportunities in healthcare. However, little is known about the usability perceived by students and the factors/determinants that predict the acceptance and use of clinical virtual simulation in nursing education. OBJECTIVES: To identify the factors/determinants that predict the acceptance and use of clinical virtual simulation in learning in nursing education. METHODS: Observational, cross-sectional, analytical study of the use of clinical virtual simulation in nursing to answer the research question: What factors/determinants predict the acceptance and use of a clinical virtual simulator in nursing education? We used a non-probabilistic sampling, more specifically a convenience sample of nursing degree students. The data were collected through a questionnaire adapted from the Technology Acceptance Model 3. In technology and education, the Technology Acceptance Model is a theoretical model that predicts the acceptance of the use of technology by users. RESULTS: The sample comprised 619 nursing students, who revealed mean values of perceived usefulness (M = 5.34; SD = 1.19), ease of use (M = 4.74; SD = 1.07), and intention to use the CVS (M = 5.21; SD = 1.18), in a Likert scale of seven points (1-the worst and 7 the best possible opinion). This study validated the use of Technology Acceptance Model 3 adapted and tested the related hypotheses, showing that the model explains 62% of perceived utility, 32% of ease of use, and 54% of intention to use the clinical virtual simulation in nursing by nursing students. The adequacy of the model was tested by analysis of the direct effects of the relationships between the internal constructs (PU-BI, ß = 0.11, p = 0.012; PEOU-BI, ß = -0.11, p = 0.002) and the direct relations between some of the constructs internal to the Technology Acceptance Model 3 and the external determinants Relevance for learning and Enjoyability. In the proposed model, the external constructs that best predicted perceived usefulness, ease of use, and behaviour intention to use the clinical virtual simulation in nursing were Relevance for learning and Enjoyability. CONCLUSIONS: These study results allowed us to identify relevance for learning and enjoyability as the main factors/determinants that predict the acceptance and use of clinical virtual simulation in learning in nursing.

Fostering engagement in virtual anatomy learning for healthcare students.

BACKGROUND: The use of virtual learning platforms is on the rise internationally, however, successful integration into existing curricula is a complex undertaking fraught with unintended consequences. Looking beyond medical and pedagogic literature can provide insight into factors affecting the user experience. The technology acceptance model, widely used in software evaluation, can be used to identify barriers and enablers of engagement with virtual learning platforms. Here, the technology acceptance model was used to scaffold the exploration of the factors that influenced students' perceptions of the virtual anatomy platform, Anatomage and how these shaped their intention to use it. METHODS: Focus groups identified factors influencing students use of the Anatomage tables. Interventions were rolled out to address these findings, then further focus groups and the technology acceptance model identified how factors including self-efficacy, enjoyment, and social norms influenced students' intention to use the Anatomage table in the future. RESULTS: Students raised significant concerns about understanding how to use the Anatomage table. Moreover, students who considered themselves to be poor at using technology perceived the Anatomage table as more complicated to use. The subjective norm of the group significantly altered the perceived ease of use and usefulness of the Anatomage. However, enjoyment had the greatest impact in influencing both perceived usefulness and perceived ease of use. Indicating that enjoyment is the largest contributing factor in altering technology engagement in healthcare cohorts and has the biggest potential to be manipulated to promote engagement. CONCLUSIONS: Focus groups used in tandem with the technology acceptance model provide an effective way to understand student perceptions around technology used in the healthcare curricula. This research determined interventions that promote student engagement with virtual learning platforms, which are important in supporting all healthcare programmes that incorporate technology enhanced learning.

Immersive medical training: a comprehensive longitudinal study of extended reality in emergency scenarios for large student groups.

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.

Empirical Study on the Usage of Telemedicine by Rural and Urban Health Care Consumers in Taiwan: Integrating the Perspectives of Technology Acceptance Model and Theory of Planned Behavior.

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.

Embracing the Future of Health Care: Investigating Medical Students' Willingness to Become Online Doctors.

Purpose: With the rapid advancement of technology, online health care services are becoming increasingly prominent. This study aims to investigate medical students' perceptions, attitudes, and readiness to adopt online health care services. Methods: Based on a literature review, this study constructed a conceptual model describing the relationships among medical students' perception, personality traits, and usage intention, grounded in the Technology Acceptance Model and Technology Readiness Index (TRI). The data for this study were collected from January to February 2023 through a questionnaire survey at Wenzhou Medical University, China. The proposed hypotheses were tested using structural equation modeling through AMOS software. Results: Out of the 340 respondents, 281 (82.6%) validly responded. Among these, 58.4% of medical students agreed and strongly agreed with the intention to become an online doctor. Within the TRI's motivational factors, optimism positively and significantly affected perceived usefulness (PU) and perceived ease of use (PEOU). Innovativeness also significantly enhanced PEOU. Among the inhibitory factors, insecurity was found to have a negative and statistically significant influence on PU. The rest of the dimensions did not have a significant effect on either PU or PEOU. Importantly, both PU and PEOU demonstrated a direct and substantial effect on usage intention. Conclusions: This study emphasizes the significance of comprehending medical students' readiness to adopt the role of online doctors in shaping the future of health care. By equipping medical students with the necessary skills and competencies, health care institutions can effectively leverage the full potential of online health care services while ensuring the provision of high-quality, accessible, and patient-centered care in the digital era.

Attitude and utilization of ChatGPT among registered nurses: A cross-sectional study.

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.

A meta-analysis of technology acceptance in healthcare from the consumer's perspective.

Consumer-oriented health care technologies are increasingly available and transforming global health delivery systems. However, there is a paucity of research that systematically investigates health care technology acceptance from the consumer's perspective. This study conducts a literature review and meta-analysis to examine consumers' adoption intentions toward health care technologies. The findings suggest that technology acceptance models are transferable to health care technology with modifications, and factors such as perceived risks, technology performance expectancy, consumer trust, and habit significantly correlate with consumers' adoption intentions. This study provides valuable insights into health care technology management and practical implications for health care service designers, providers, and regulatory authorities.

A Social Work Analysis of Facilitators of and Barriers to Adopting Technology in Older Adults: A Systematic Literature Review.

Increasing concern within social work about delivering comprehensive and high-quality care to older adults necessitates exploring their interest in information and communication technologies. The aim is to determine, via a systematic review using the PRISMA method, how the scientific literature on older adults' technology experiences through the lens of the Technology Acceptance Model (TAM). The review differentiates between enabling factors and barriers that influence older adults' use and acceptance of technology from their own perspective. It provides social workers with a comprehensive overview of use of technologies and identify general guidelines to enhance older adults' personal and communal autonomy.

Comprehensive Senior Technology Acceptance Model of Daily Living Assistive Technology for Older Adults With Frailty: Cross-sectional Study.

BACKGROUND: There are considerable gaps between the need for assistive technologies and the actual adoption of these technologies among older adults, although older adults are among the groups that most need assistive technologies. Consequently, research is needed in this area because older adults' technology acceptance and influencing factors may differ depending on their level of frailty. OBJECTIVE: The objective of this study was to compare frail, prefrail, and robust groups of South Korean adults regarding their behavioral intention to use daily living assistive technologies and the affecting factors-namely, technological context factors, health contexts and abilities, and attitudinal factors-based on a comprehensive senior technology acceptance model. METHODS: A nationwide sample of 500 older South Korean adults (aged 55-92 years) was analyzed, and multivariate linear regression analyses of the robust, prefrail, and frail groups were performed. The independent and dependent variables consisted of 3 factors based on previous studies. First, technological context factors consisted of gerontechnology self-efficacy, gerontechnology anxiety, and facilitating conditions. Second, health contexts and abilities consisted of self-reported health conditions, cognitive ability, social relationships, psychological function, and physical function. Third and last, attitudinal factors consisted of behavioral intention to use assistive technologies, attitude toward use, perceived usefulness (PU), and perceived ease of use (PEOU). RESULTS: The results of the analyses showed that technological context factors such as gerontechnology self-efficacy, health contexts and abilities such as self-reported health conditions and psychological function, and attitudinal factors such as attitude toward use, PU, and PEOU had significant effects on behavioral intention to use daily living assistive technologies. In particular, gerontechnology self-efficacy had a significant relationship with behavioral intention to use these technologies in the robust (r=0.120; P=.03) and prefrail (r=0.331; P<.001) groups. Psychological function (life satisfaction) had a significant relationship with behavioral intention to use these technologies in the robust group (r=-0.040; P=.02). Self-reported health conditions had a significant relationship with behavioral intention to use these technologies in the prefrail group (r=-0.169; P=.01). Although each group had a different significant relationship with the variables, attitudinal factors such as attitude toward use affected all groups (robust group: r=0.190; P=.03; prefrail group: r=0.235; P=.006; and frail group: r=0.526; P=.002). In addition, PU and PEOU in the attitudinal factors had a significant relationship with behavioral intention to use assistive technologies in the robust (PU: r=0.160; P=.01; and PEOU: r=0.350; P<.001) and prefrail (PU: r=0.265; P<.001; and PEOU: r=0.120; P=.04) groups. CONCLUSIONS: This study found that the comprehensive senior technology acceptance model of daily living assistive technologies had different associations according to the frailty group. These findings provided insights into the consideration of interventions with daily living assistive technologies for older adults with varying levels of frailty.

Technology Acceptance Model for Exoskeletons for Rehabilitation of the Upper Limbs from Therapists' Perspectives.

Over the last few years, exoskeletons have been demonstrated to be useful tools for supporting the execution of neuromotor rehabilitation sessions. However, they are still not very present in hospitals. Therapists tend to be wary of this type of technology, thus reducing its acceptability and, therefore, its everyday use in clinical practice. The work presented in this paper investigates a novel point of view that is different from that of patients, which is normally what is considered for similar analyses. Through the realization of a technology acceptance model, we investigate the factors that influence the acceptability level of exoskeletons for rehabilitation of the upper limbs from therapists' perspectives. We analyzed the data collected from a pool of 55 physiotherapists and physiatrists through the distribution of a questionnaire. Pearson's correlation and multiple linear regression were used for the analysis. The relations between the variables of interest were also investigated depending on participants' age and experience with technology. The model built from these data demonstrated that the perceived usefulness of a robotic system, in terms of time and effort savings, was the first factor influencing therapists' willingness to use it. Physiotherapists' perception of the importance of interacting with an exoskeleton when carrying out an enhanced therapy session increased if survey participants already had experience with this type of rehabilitation technology, while their distrust and the consideration of others' opinions decreased. The conclusions drawn from our analyses show that we need to invest in making this technology better known to the public-in terms of education and training-if we aim to make exoskeletons genuinely accepted and usable by therapists. In addition, integrating exoskeletons with multi-sensor feedback systems would help provide comprehensive information about the patients' condition and progress. This can help overcome the gap that a robot creates between a therapist and the patient's human body, reducing the fear that specialists have of this technology, and this can demonstrate exoskeletons' utility, thus increasing their perceived level of usefulness.

Investigating the Predictors of Telemedicine Service Usage Intention in China During the COVID-19 Pandemic: An Extended Technology Acceptance Perspective.

Introduction: In China, digital health and telemedicine services grew particularly rapidly during the COVID-19 pandemic. The goal of this study was to examine the effects of technology acceptance model (TAM) predictors, previous social media health service exposure, and telemedicine experience on individual telemedicine service usage intention within the extended theoretical framework of TAM and TAM2. Methods: The study adopted a cross-sectional survey to collect data (N = 1,088) through a Chinese online panel provider (wenjuan.com). Structural equation modeling was performed to examine relationships between the variables in the proposed model. Results: Our results indicated that technology anxiety (TA) was negatively related to perceived ease of use (PEOU) and usage intention. PEOU mediated the relationship between TA and usage intention. Social media health information consumption was positively associated with perceived usefulness (PU). Previous telemedicine satisfaction was positively related to PEOU and PU, but the direct relationship between satisfaction with telemedicine and usage intention was not found to be significant. Besides, PEOU and PU mediated the relationship between previous telemedicine satisfaction and usage intention. Conclusions: Findings of the study not only contribute to literature pertaining to telemedicine promotion by identifying important mediation relationships but also help identify potential users and provide a convenient internet-based promotion channel since they reveal that social media health information consumption is positively related to PU of telemedicine services.

Developing and Validating a Tool to Assess Telemedicine Acceptance Among Physicians During Pandemic Using a Technology Acceptance Model.

Background: The World health organization declared the coronavirus outbreak a global pandemic on March 11, 2020. Telemedicine was one of the effective tools that were implemented during this pandemic. Most Lebanese physicians have been using telemedicine to perform virtual medical services during the COVID-19 pandemic. Therefore, it is important to assess the physicians' acceptability of telemedicine and willingness to use it in routine health care settings. Objective: We developed and validated a tool based on technology acceptance model (TAM) to explore the acceptance of telemedicine use during the pandemic among Lebanese physicians. Theoretical Background: Telemedicine Acceptance Model during Pandemic (TeAM) was developed based on TAM. The model was developed considering the associations between constructs affecting the physicians' attitudes about telemedicine use. TeAM is a tool assessing telemedicine acceptance based on the TAM. It has additional constructs tackling the perceived risks of telemedicine use, the perceived need for policies, the perceived need for training, and the perceived usefulness of telemedicine during a pandemic. Methods: This cross-sectional study was conducted online through an email-based questionnaire sent to physicians enrolled in the Lebanese Order of Physicians. Results: Three hundred ninety physicians (n = 390) completed the survey. The tool was structured to test 10 hypotheses, out of which 9 were supported. The Cronbach's alpha score of each construct ranged between 0.745 and 0.905, all greater than 0.7 indicating an acceptable to excellent internal consistency. Conclusion: This study was able to validate TeAM as a reliable tool that can assess the acceptance of telemedicine among physicians. Accordingly, several determinants influencing this acceptance were identified. Practice implications include hospitals, primary health care centers, and national health care systems willing to adopt telemedicine can use TeAM to assess the physicians' willingness to accept the implementation of telemedicine in their practice.

Antecedent, behaviour, and consequence (a-b-c) of deploying the contact tracing app in response to COVID-19: Evidence from Europe.

In response to the current coronavirus (COVID-19) pandemic, countries have or intend to deploy contact tracing apps as a way of containing and or reducing the community spread of the virus. Whilst a few studies have so far been conducted on the acceptability of the app, little is known about the antecedent, behaviour, and consequence (a-b-c) of deploying the app and its success thereof. This study, therefore, proposes and validates an integrated a-b-c and technology acceptance model of deploying the contract tracing app in four European countries. The study adopts a quantitative approach and uses publicly available cross country survey data from the Center for Open Science. An extract of 2512 data is analysed using SEM-PLS. The results confirmed the integrated a-b-c and technology acceptance model that underpins the study and revealed that the chance of achieving a positive outcome with citizens complying with recommendations of the app was only 17.1 % or R2 = 0.171 (±0.020) whilst the chance of negative consequent or deviant response of uninstallation of the app by the citizens was 54.3 % or R2 = 0.543 (±0.021). The results have huge implications for governments and public health institutions in their attempt to deploy the contract tracing app.

A Longitudinal Comparison of Pharmacy Documentation Platforms Using the Technology Acceptance Model: Experiences With Opioid Risk Screening.

Background: Pharmacy practice continues to expand in scope, and technology platforms to assist with meeting the standards for documentation of billable services are needed. The ONE Program (Opioid and Naloxone Education) is an initiative centered on the community pharmacy focused on opioid risk screening for patients receiving opioid prescriptions. Objective: Opioid risk screening results and pharmacist interventions were documented using first REDCap and later the DocStation platforms. This study compared pharmacy staff experience with these 2 platforms. Methods: A survey using the Technology Acceptance Model (TAM) was designed to compare usability, ease of use, social influence, and facilitating conditions. Results: Analyses using descriptive statistics and open-ended responses showed similar results for each platform; however, pharmacy staff indicated that REDCap required less time when entering information, whereas the DocStation platform offered elevated pharmacy practice service opportunities, management support, and available informational technology support services. Conclusion: Health care technology continues to advance in meeting the needs of expanded service provision through pharmacy. This longitudinal study shows the value of the TAM framework in identifying efficiencies and deficiencies of health care technology systems.

An integrated model for predicting pupils' acceptance of artificially intelligent robots as teachers.

Artificially intelligent robots as teachers (AI teachers) have attracted extensive attention due to their potential to relieve the challenge of global teacher shortage and realize universal elementary education by 2030. Despite mass production of service robots and discussions about their educational applications, the study of full-fledged AI teachers and children's attitudes towards them is quite preliminary. Here, we report a new AI teacher and an integrated model to assess how pupils accept and use it. Participants included students from Chinese elementary schools via convenience sampling. Questionnaires (n = 665), descriptive statistics and structural equation modeling based on software SPSS Statistics 23.0 and Amos 26.0 were carried out in data collection and analysis. This study first developed an AI teacher by coding a lesson design, course contents and Power Point with script language. Based on the popular Technology Acceptance Model and Task-Technology Fit Theory, this study identified key determinants of the acceptance, including robot use anxiety (RUA), perceived usefulness (PU), perceived ease of use (PEOU) and robot instructional task difficulty (RITD). Moreover, this study found that pupils' attitudes towards the AI teacher, which could be predicted by PU, PEOU and RITD, were generally positive. It is also found that the relationship between RITD and acceptance was mediated by RUA, PEOU and PU. This study holds significance for stakeholders to develop independent AI teachers for students.