Factors Determining the Behavioral Intention to Use Mobile Learning: An Application and Extension of the UTAUT Model

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

BACKGROUND

E-health systems have the potential to improve healthcare delivery and access to medical services in resource-constrained settings. Despite its impact, the system exhibits a low level of consumer acceptance and intention to use it. This research paper aims to analyze the intention of health service employees to use e-health systems in southwest Ethiopia using the UTAUT-2 model.

METHOD

Institutional-based cross-sectional studies were conducted at four referral hospitals (two private and two public) to examine the acceptance of e-health among consumers. Employees who had previous experience with diagnostic information systems and the health logistic information system were given structured questionnaires based on the UTAUT-2 model. The data were analyzed using the PLS-SEM method to identify the key factors that influence the intention to use e-health systems. The data were analyzed using SPSS version 20 and SmartPLS 3 software.

RESULT

Out of the 400 surveyed employees, 225 (56.25%) valid questionnaires were collected. The findings indicate that three factors-effort expectancy (β = 0.276, t = 3.015, p = 0.001), habit (β = 0.309, t = 3.754, p = 0), and performance expectancy (β = 0.179, t = 1.905, p = 0.028)-had a significant positive impact on employees' intention to use e-health systems. On the other hand, factors such as social influence, facilitating conditions, hedonic motivation, and price values did not appear as significant predictors of intention to use e-health. The study model was able to predict 63% of employees' intentions to use e-health systems.

CONCLUSION

Effort expectancy, habit, and performance expectancy were significant predictors of employees' intention to use e-health systems among health service employees in southwest Ethiopia. The study supports the ideas that ease of use, experience with information systems, and the role of the systems in improving job performance contribute to employees' intention to use e-health. Policymakers and healthcare organizations in the region can use these findings to develop strategies for successful implementation and adoption of e-health systems, ultimately improving healthcare services and outcomes for the population.

Factors That Affect the Acceptance of Educational AI Tools by Greek Teachers-A Structural Equation Modelling Study

The discussion around integrating AI technologies into educational practice is current among scholars and in sociopolitical circles. This study examines the factors influencing teachers' acceptance of educational AI tool (EAIT) use, aiming to inform the development of a pedagogical framework for the responsible integration of AI tools in education. A conceptual model was developed by amalgamating constructs of TAM (perceived usefulness and perceived ease of use) and UTAUT (social influence and facilitating conditions) while integrating the variables of perceived trust and personal innovativeness and considering the impact of teachers' pedagogical beliefs. A total of 342 Greek teachers participated in the quantitative survey conducted. The proposed model was evaluated using partial least squares structural equation modelling (PLS-SEM). The findings illuminated perceived usefulness as the most significant predictor of teachers' behavioural intention to use EAIT. The research also revealed that social influence and personal innovativeness exert considerable influence. While constructivist pedagogical beliefs were found to have no direct impact on EAIT acceptance, the results indicated that educators who embrace those teaching methods exhibit a high propensity to perceive EAIT as useful and trustworthy. Furthermore, the study's analysis demonstrated that trust had a significantly positive effect on usefulness, and innovativeness influences positively and significantly both usefulness and ease of use.

Evaluating customer perspectives on omnichannel shopping satisfaction in the fashion retail sector

The effective implementation of omnichannel commerce can fundamentally alter how consumers shop online. This study attempted to understand Thai consumers' omnichannel fashion retail purchasing activities. The objectives of the study were to investigate the determinants shaping omnichannel customer experiences within the fashion retail industry and to examine the impact of omnichannel customer experiences on customer satisfaction within the Thai retail industry. The research utilized the Unified Theory of Acceptance and Use of Technology (UTAUT) model to analyze the effects of omnichannels on purchasing behaviors and levels of satisfaction of consumers. The study employed a survey research design, applying simple random sampling to select 509 respondents with omnichannel shopping experience in the clothing and fashion. The respondent data was analyzed using structural equation modeling utilizing the Amos software version 24. Analyzing the results revealed a significant correlation between omnichannel shopping and customer satisfaction in fashion retail shopping. Perceived ease of use, perceived enjoyment, integrated promotions, integrated customer service, and integrated transactions were all found to influence omnichannel experiences favorably. The findings suggest that fashion retailers prioritize customer satisfaction by enhancing their omnichannel experiences through better coordination and synchronization of their different customer service channels.

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

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

Home-monitoring for neovascular age-related macular degeneration in older adults within the UK: the MONARCH diagnostic accuracy study

Background

Most neovascular age-related macular degeneration treatments involve long-term follow-up of disease activity. Home monitoring would reduce the burden on patients and those they depend on for transport, and release clinic appointments for other patients. The study aimed to evaluate three home-monitoring tests for patients to use to detect active neovascular age-related macular degeneration compared with diagnosing active neovascular age-related macular degeneration by hospital follow-up.

Objectives

There were five objectives: Estimate the accuracy of three home-monitoring tests to detect active neovascular age-related macular degeneration. Determine the acceptability of home monitoring to patients and carers and adherence to home monitoring. Explore whether inequalities exist in recruitment, participants' ability to self-test and their adherence to weekly testing during follow-up. Provide pilot data about the accuracy of home monitoring to detect conversion to neovascular age-related macular degeneration in fellow eyes of patients with unilateral neovascular age-related macular degeneration. Describe challenges experienced when implementing home-monitoring tests.

Design

Diagnostic test accuracy cohort study, stratified by time since starting treatment.

Setting

Six United Kingdom Hospital Eye Service macular clinics (Belfast, Liverpool, Moorfields, James Paget, Southampton, Gloucester).

Participants

Patients with at least one study eye being monitored by hospital follow-up.

Reference standard

Detection of active neovascular age-related macular degeneration by an ophthalmologist at hospital follow-up.

Index tests

KeepSight Journal: paper-based near-vision tests presented as word puzzles. MyVisionTrack®: electronic test, viewed on a tablet device. MultiBit: electronic test, viewed on a tablet device. Participants provided test scores weekly. Raw scores between hospital follow-ups were summarised as averages.

Results

Two hundred and ninety-seven patients (mean age 74.9 years) took part. At least one hospital follow-up was available for 317 study eyes, including 9 second eyes that became eligible during follow-up, in 261 participants (1549 complete visits). Median testing frequency was three times/month. Estimated areas under receiver operating curves were < 0.6 for all index tests, and only KeepSight Journal summary score was significantly associated with the lesion activity (odds ratio = 3.48, 95% confidence interval 1.09 to 11.13, p = 0.036). Older age and worse deprivation for home address were associated with lower participation (χ2 = 50.5 and 24.3, respectively, p < 0.001) but not ability or adherence to self-testing. Areas under receiver operating curves appeared higher for conversion of fellow eyes to neovascular age-related macular degeneration (0.85 for KeepSight Journal) but were estimated with less precision. Almost half of participants called a study helpline, most often due to inability to test electronically.

Limitations

Pre-specified sample size not met; participants' difficulties using the devices; electronic tests not always available.

Conclusions

No index test provided adequate test accuracy to identify lesion diagnosed as active in follow-up clinics. If used to detect conversion, patients would still need to be monitored at hospital. Associations of older age and worse deprivation with study participation highlight the potential for inequities with such interventions. Provision of reliable electronic testing was challenging.

Future work

Future studies evaluating similar technologies should consider: Independent monitoring with clear stopping rules based on test performance. Deployment of apps on patients' own devices since providing devices did not reduce inequalities in participation and complicated home testing. Alternative methods to summarise multiple scores over the period preceding a follow-up.

Trial registration

This trial is registered as ISRCTN79058224.

Funding

This award was funded by the National Institute of Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 15/97/02) and is published in full in Health Technology Assessment; Vol. 28, No. 32. See the NIHR Funding and Awards website for further award information.

Factors influencing the continuance intention of the women's health WeChat public account: an integrated model of UTAUT2 and HBM

Background

Women's health WeChat public accounts play a crucial role in enhancing health literacy and fostering the development of healthy behaviors among women by disseminating women's health knowledge. Improving users' continuous usage behavior and retention rates for the women's health WeChat public account is vital for influencing the overall effectiveness of health communication on WeChat.

Objective

This study aimed to construct a comprehensive model, delving into the key factors influencing women's continuance intention of the women's health public accounts from the perspectives of perceived health threats, individual abilities, and technological perceptions. The goal is to provide valuable insights for enhancing user stickiness and the effectiveness of health communication on WeChat public accounts.

Method

An online survey was conducted among women receiving gynecological care at a certain hospital to gage their willingness for sustained use of the women's health WeChat public accounts. Through structural equation modeling, the study investigated the influencing factors on women's sustained intention to use the women's health WeChat public accounts.

Results

The study included a total of 853 adult women. Among them, 241 (28.3%) women had followed women's health official accounts in the past but do not currently follow them, 240 (28.1%) women had followed women's health official accounts in the past and are still following them, and 372 (43.6%) women had never followed women's health official accounts. Currently, 240 women are still browsing women's health public accounts, 52 of whom read women's health public accounts every day, and most of them read women's health public accounts for 10-20 min at a time (100, 11.7%). The results of the structural equation model revealed that performance expectancy, social influence, hedonic motivation, habit, and e-health literacy had significantly positive effects on women's sustained intention to use public accounts (performance expectancy: β = 0.341, p < 0.001; social influence: β = 0.087, p = 0.047; hedonic motivation: β = 0.119, p = 0.048; habit: β = 0.102, p < 0.001; e-health literacy: β = 0.158, p < 0.001). E-health literacy and self-efficacy indirectly influence sustained intention by affecting performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit. The effect sizes of e-health literacy on performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit were 0.244 (p < 0.001), 0.316 (p < 0.001), 0.188 (p < 0.001), 0.226(p < 0.001), 0.154 (p < 0.001), and 0.073 (p = 0.046). The effect sizes of self-efficacy on performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit were 0.502 (p < 0.001), 0.559 (p < 0.001), 0.454 (p < 0.001), 0.662 (p < 0.001), 0.707 (p < 0.001), and 0.682 (p < 0.001). Additionally, perceived severity and perceived susceptibility indirectly affected sustained intention by influencing performance expectancy and social influence. The effect sizes of perceived severity on performance expectancy and social influence were 0.223 (p < 0.001) and 0.146 (p < 0.001). The effect size of perceived susceptibility to social influence was 0.069 (p = 0.042).

Conclusion

Users' e-health literacy, self-efficacy, perception of disease threat, and users' technological perceptions of the WeChat public accounts are critical factors influencing women's continuance intention of using the WeChat public accounts. Therefore, for female users, attention should be given to improving user experience and enhancing the professionalism and credibility of health information in public account design and promotion. Simultaneously, efforts should be made to strengthen users' health awareness and cultivate e-health literacy, ultimately promoting sustained attention and usage behavior among women toward health-focused public accounts.

Examining the association between emotional intelligence and chatbot utilization in education: A cross-sectional examination of undergraduate students in the UAE

Background

While Emotional Intelligence (EI) demonstrably affects academic success, literature lacks exploration of how implementing chatbot in education might influence both academic performance and students' emotional intelligence, despite the evident potential of such technology.

Aim

To investigate the associations between Emotional Intelligence (EI), chatbot utilization among undergraduate students.

Methods

A cross-sectional approach was employed, utilizing a convenience sample of 529 undergraduate students recruited through online questionnaires. The participants completed the Trait Emotional Intelligence Questionnaire and modified and a modified versions of the unified theory of acceptance and use of technology (UTAUT) model.

Results

of the 529 participants, 83.6 % (n = 440) of participants regularly used chatbot for learning. Students demonstrated a moderate average EI score (129.60 ± 50.15) and an exceptionally high score (89.61 ± 20.70) for chatbot acceptance and usage. A statistically significant (p < 0.001) positive correlation was found between chatbot usage frequency and EI total score. Gender and major emerged as significant factors, with female students (p < 0.05) and health science students (p < 0.05) utilizing chatbot less compared to male and other major students, respectively. A negative correlation (r = -0.111, p = 0.011) was observed between study hours and chatbot usage, suggesting students with higher study hours relied less on chatbot.

Conclusions

The positive correlation between chatbot use and EI in this study sparks promising avenues for enhancing the learning experience. By investing in further research to understand this link and integrate AI tools thoughtfully, policymakers and educators can cultivate a learning environment that prioritizes both academic excellence and student well-being, reflecting the values and perspectives of UAE culture.

Successful Electronic Consultation Service Initiative in Quebec, Canada With Primary Care Physicians' and Specialists' Experiences on Acceptance and Use of Technological Innovation: Cross-Sectional Exploratory Study

BACKGROUND

Electronic consultation (eConsult) is an eHealth service that allows primary care providers (PCPs) to electronically consult specialists regarding their patients' medical issues. Many studies have demonstrated that eConsult services improve timely access to specialist care; prevent unnecessary referrals; improve PCPs', specialists', and patients' satisfaction; and therefore have a large impact on costs. However, no studies have evaluated PCPs' and specialists' acceptance of eConsult services in Quebec, Canada, and worldwide.

OBJECTIVE

This exploratory study aims to identify factors affecting eConsult service acceptance by PCPs and specialists in urban and rural primary care clinics across 3 regions in the province of Quebec, Canada, by integrating the Unified Theory of Acceptance and Use of Technology and Task-Technology Fit (TTF) models and user satisfaction. This research was designed to broaden and assist in scaling up this effective eHealth service innovation across the province.

METHODS

A cross-sectional web-based survey was sent to all PCPs (n=263) and specialists (n=62) who used the eConsult Quebec Service between July 2017 and May 2021. We proposed a unified model integrating the Unified Theory of Acceptance and Use of Technology model and TTF model and user satisfaction by endorsing 11 hypotheses. The partial least squares was used to investigate factors influencing the acceptance of the eConsult Quebec Service.

RESULTS

Of the 325 end users, 136 (41.8%) users responded (PCPs: 101/263, 38.4%; specialists: 35/62, 57%). The results of the analysis with partial least squares method indicate that 9 of our 11 hypotheses are supported. The direct relationships uniting the various constructs of the model highlighted the importance of several key constructs and predominant correlations. The results suggest that satisfaction is the key driver behind the use of the eConsult Quebec Service. Performance expectancy (P<.001) and effort expectancy (P=.03) can have a positive impact on behavioral intention (BI), and BI (P<.001) can impact adoption. TTF has an influence on performance expectancy (P<.001), adoption (P=.02), and satisfaction (P<.001). However, the results show that there is no direct effect between social influence (P=.38) and BI or between facilitating conditions (P=.17) and adoption.

CONCLUSIONS

This study provides a better understanding of the factors influencing PCPs' and specialists' intention to adopt the eConsult Quebec Service. Furthermore, this study tests a research model and a technology that have never been explored in Quebec until now. On the basis of the results, the service is a good fit to meet the users' need to improve access to specialized medical advice. Therefore, the results of our study have made a valuable contribution to the implementation of the service by policy makers in order to maximize acceptance, use, adoption, and success across the province of Quebec. Moreover, after 4 successful years, the eConsult Quebec pilot project is now the Conseil Numérique digital consultation service.

Pre-Service Teachers' GenAI Anxiety, Technology Self-Efficacy, and TPACK: Their Structural Relations with Behavioral Intention to Design GenAI-Assisted Teaching

Generative artificial intelligence (GenAI) has taken educational settings by storm in the past year due to its transformative ability to impact school education. It is crucial to investigate pre-service teachers' viewpoints to effectively incorporate GenAI tools into their instructional practices. Data gathered from 606 pre-service teachers were analyzed to explore the predictors of behavioral intention to design Gen AI-assisted teaching. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, this research integrates multiple variables such as Technological Pedagogical Content Knowledge (TPACK), GenAI anxiety, and technology self-efficacy. Our findings revealed that GenAI anxiety, social influence, and performance expectancy significantly predicted pre-service teachers' behavioral intention to design GenAI-assisted teaching. However, effort expectancy and facilitating conditions were not statistically associated with pre-service teachers' behavioral intentions. These findings offer significant insights into the intricate relationships between predictors that influence pre-service teachers' perspectives and intentions regarding GenAI technology.

Evaluation of a motorised patient transfer device based on perceived workload, technology acceptance, and emotional states

PURPOSE

The high prevalence of musculoskeletal disorders (MSDs) among healthcare workers is partly attributed to the low adoption of patient transfer assistive devices. This study aimed to evaluate the nurses' perceived workload, technology acceptance, and emotional states during the use of the sliding board (SB) and mechanical intervention in the form of a Motorised Patient Transfer Device (MPTD).

METHODS

The SB and MPTD activities were performed by seven nurses on a simulated patient. The nurses' facial expressions were recorded during the trial. The NASA Task Load Index and technology acceptance questionnaire were also assessed.

RESULTS

The MPTD significantly reduced the mean overall NASA-TLX score by 68.7% (p = 0.004) and increased the overall acceptance score (median = 8.30) by 21.2% (p = 0.016) when compared to the SB (median = 6.85). All the subjects reported positive feelings towards MPTD. However, facial expression analysis showed that the nurses had a significantly higher peak density of fear while using MPTD (p = 0.016). Besides, there was no improvement in the negative valence and contempt emotion compared to the SB.

CONCLUSION

Overall, nurses showed positive perceptions and acceptance of MPTD even when they experienced negative emotions.IMPLICATIONS FOR REHABILITATIONThe Motorised Patient Transfer Device (MPTD) reduced the perceived workload of nurses and showed a higher acceptance level compared to the commonly used baseline device (SB).Factors that attributed to the nurses' negative emotions can be used to improve technology and patient transfer processes.More training should be given to familiarise the health practitioners with the new assistive device to reduce their fear of technology.

Health professionals' technology readiness on the acceptance of teleradiology in the Amhara regional state public hospitals, northwest Ethiopia: Using technology readiness acceptance model (TRAM)

BACKGROUND

Considering individual differences caused by personality differences is crucial for end users' technology acceptance. However, previous studies overlooked the influence of users' technology readiness on technology acceptance. This study, therefore, aimed to evaluate the influence of technology readiness on teleradiology acceptance in the Amhara Regional State Public Hospitals using a technology readiness acceptance model.

METHODS

An institutional-based cross-sectional mixed study design was conducted in September 2021 among 547 health professionals working at sixteen public hospitals in the Amhara region of northwest Ethiopia. Eight key informants were interviewed to explore organizational-related factors. Face-to-face and Google Meet approaches were used to collect the data. We applied structural equation modeling to investigate the influence of technology readiness on health professionals' teleradiology acceptance using Analysis of Moment Structures Version 23 software.

RESULTS

Of the total participants, 70.2% and 85.7% were ready and intended to use teleradiology, respectively. According to technology readiness measuring constructs, optimism and innovativeness positively influenced health professionals' technology acceptance. Perceived ease of use and perceived usefulness showed a statistically positive significant effect on health professionals' intention to use teleradiology. In addition, a statistically significant mediation effect was observed between technology readiness measuring constructs and behavioral intention to use. Furthermore, a shortage of budget, inadequate infrastructure, and users' lack of adequate skills were reported as critical organizational challenges.

CONCLUSIONS

We found a higher proportion of readiness and intention to use teleradiology among health professionals. Personality difference measuring constructs and organizational factors played considerable influence on teleradiology acceptance. Therefore, before the actual implementation of teleradiology, ensuring the system's user-friendliness, improving infrastructure, allocating an adequate budget, and availing of capacity-building opportunities are recommended.

What Contributes to Student Language Learning Satisfaction and Achievement with Learning Management Systems?

Learning management systems (LMSs) have received substantial global attention and have undergone extensive research, with most discussions focusing on users' acceptance and continuation of LMS use in the higher education sector. However, research is scarce in terms of identifying the factors that are advantageous to K-12 students' learning and satisfaction when using LMSs for language learning. This study aims to examine the impacts of internal and contextual factors on secondary students' learning satisfaction and English achievement when using LMSs. Data were collected from 289 students through an online survey. The results of the structural equation modeling showed that satisfaction had the most significant impact on English achievement. Furthermore, both internal and contextual factors, including technology self-efficacy, interest, task value, teacher support, and technology facilitation, positively impacted learning satisfaction with LMSs. In addition, teacher support exerted the strongest impact on satisfaction, followed by interest and technology self-efficacy. However, only internal factors, such as interest and task value, were positively associated with English achievement. Neither teacher support nor technology facilitation significantly impacted English performance. Given the increasing availability of LMS usage, the findings of this study can facilitate the more effective implementation of LMSs in China and globally. The study contributes to the theory and practice of LMSs use in K-12 English education. The limitations and implications of the study were discussed as well.

Pre-Implementation Analysis of the Usability and Acceptability of a Poststroke Complex Telehealth Biofeedback Intervention

IMPORTANCE

Complex telehealth interventions can facilitate remote occupational therapy services and improve access for people living with chronic neurological conditions. Understanding the factors that influence the uptake of these technologies is important.

OBJECTIVE

To explore the fit between electromyography (EMG) biofeedback and telerehabilitation for stroke survivors, optimize EMG biofeedback interventions, and, more broadly, support other efforts to develop complex telerehabilitation interventions.

DESIGN

Pre-implementation mixed-methods analysis of usability and acceptability data collected during a pilot and feasibility study.

SETTING

Community.

PARTICIPANTS

Adult stroke survivors with hemiparesis (N = 11; M age = 54 yr).

INTERVENTION

Game-based EMG biofeedback system for arm sensorimotor rehabilitation, delivered via telehealth.

OUTCOMES AND MEASURES

Post-Study System Usability Questionnaire, an extended Unified Theory of Acceptance and Use of Technology model questionnaire, and semistructured interview. We coded the interview data using questionnaire constructs.

RESULTS

Participants used an EMG biofeedback intervention at home. Quantitative measures show high levels of perceived usability and acceptability, supported by qualitative findings describing specific facilitators and barriers.

CONCLUSIONS AND RELEVANCE

Pre-implementation studies can improve the design and relevance of complex telehealth interventions. One major conclusion from this study is the influence of therapy providers on acceptability and usability of complex telehealth interventions. Plain-Language Summary: This study contributes to an emerging body of literature that examines the use of complex telehealth interventions with survivors of neurological injury. The findings highlight the value and support the development and use of complex telehealth interventions, which have the potential to improve remote access to occupational therapy for clients living with chronic neurological conditions. Complex telehealth interventions can open doors for survivors of neurological injury who face barriers to accessing occupational therapy and would benefit from technology-enabled therapy at home.

Exploring the factors affecting elementary mathematics teachers' innovative behavior: an integration of social cognitive theory

Teacher innovative behavior is one of the vital factors, affecting student engagement, addresses diverse needs, promotes critical thinking, fosters lifelong learning, and contributes to educational research and development. By encouraging and supporting teacher innovation, we may can ensure that education remains relevant, effective, and impactful in preparing students for the future. Teacher innovative behavior is also needed to improve the mathematics skills of elementary school students, and it is important to determine the predictors that significantly affecting Teacher innovative behavior. Therefore, this study aimed to develop a model that predicted possible factors affecting mathematics teachers' innovative behavior based on Social Cognitive Theory (SCT). Data were collected from 132 elementary school teachers in China to verify the model, and the analysis was conducted using a structural equation modelling approach. Theoretically, 10 of the 15 hypotheses were found to be significant. The results showed that facilitating conditions and self-efficacy significantly affect mathematics teachers' innovative behavior. Meanwhile, Technological, Pedagogical and Content Knowledge (TPACK) knowledge, Social Influences, Rewards, Work engagement and anxiety did not show any effect. The contribution developed a model and provided new knowledge about the factors affecting elementary school teachers' innovative behavior. Practically, this could be used to improve teachers' innovative behavior.

Undergraduate students' perceptions of using videoconferencing for EFL learning: Evidence from Tencent Meeting application

This paper examined Chinese undergraduate students' perceptions of using videoconferencing in learning English as a foreign language (EFL) during the COVID-19 pandemic. The data were collected among 348 Chinese university students who attended sixteen-week learning of Integrated English Course through Tencent Meeting, the most widely used videoconferencing application in China. We adopted voluntary response sampling method in this cross-sectional study. Students completed an online survey on "Wenjuanxing", China's biggest online questionnaire distribution platform. A structural equation model (SEM) was constructed and analyses revealed that perceived ease of use and perceived usefulness were significant predictors of students' satisfaction and participation intention. Students' computer self-efficacy had a positive effect on their perceived ease of use, perceived usefulness, and participation intention while their frequency of using videoconferencing did not influence these variables. This study contributes to the existing literature on the acceptance of videoconferencing in the context of EFL learning and offers insights for developing up-to-date videoconferencing teaching strategies.

"Chatting with ChatGPT": Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model

Open AI's ChatGPT has emerged as a popular AI language model that can engage in natural language conversations with users. Based on a qualitative research approach using semistructured interviews with 32 ChatGPT users from India, this study examined the factors influencing users' acceptance and use of ChatGPT using the unified theory of acceptance and usage of technology (UTAUT) model. The study results demonstrated that the four factors of UTAUT, along with two extended constructs, i.e. perceived interactivity and privacy concerns, can explain users' interaction and engagement with ChatGPT. The study also found that age and experience can moderate the impact of various factors on the use of ChatGPT. The theoretical and practical implications of the study were also discussed.

Understanding psychology students' perspective on video psychotherapy and their intention to offer it after graduation: a mixed-methods study

Introduction

Video psychotherapy (VPT) demonstrated strong clinical efficacy in the past, with patients and psychotherapists expressing satisfaction with its outcomes. Despite this, VPT only gained full recognition from the German healthcare system during the COVID-19 pandemic. As society increasingly relies on new media, it seems likely that VPT will become even more relevant. Previous studies surveyed practicing psychotherapists and patients about advantages and disadvantages of VPT. In contrast, our approach targets a younger generation, specifically psychology students intending to become licensed practitioners after graduation.

Methods

Our mixed-methods study was conducted in an online survey format and had two main objectives. Firstly, we investigated which person-related variables are associated with psychology students' behavioral intention to offer VPT after graduation, using a multiple regression analysis. Secondly, we explored psychology students' perception of advantages and disadvantages of VPT and identified their desired learning opportunities regarding VPT in their study program, using qualitative content analysis.

Results

A sample of 255 psychology students participated. The multiple regression model explains 73% of inter-individual variance in the intention to offer VPT, with attitudes toward VPT showing the strongest relationship with intention to offer VPT. Expected usefulness, satisfaction with video conferencing, and subjective norm also showed significant relations. The students provided 2,314 statements about advantages, disadvantages, and desired learning opportunities, which we coded by means of three category systems. In terms of advantages, the most frequently mentioned categories were low inhibition threshold, flexibility in terms of location, and no need to travel. For disadvantages, the predominant categories included lack of closeness between patient and psychotherapist, lack of nonverbal cues, and problems with technology or internet connection. Regarding desired learning opportunities, training for technical skills, practical application through role-playing and self-experience, and general information about VPT were the most mentioned categories. In addition, we identified numerous other aspects related to these topics, reflecting a differentiated and balanced assessment of VPT.

Discussion

We discuss the theoretical and practical implications of our findings for training the next generation of psychotherapists and outline a specific five-step plan for integrating VPT into study programs.

A machine learning ensemble approach to predicting factors affecting the intention and usage behavior towards online groceries applications in the Philippines

The emergence of e-commerce platforms, especially online grocery shopping, is heightened by the COVID-19 pandemic. Filipino consumers started to adapt online due to the strict quarantine implementations in the country. This study intended to predict and evaluate factors influencing the intention and usage behavior towards online groceries incorporating the integrated Protection Motivation Theory and an extended Unified Theory of Acceptance and Use of Technology applying machine learning ensemble. A total of 373 Filipino consumers of online groceries responded to the survey and evaluated factors under the integrated framework. Artificial Neural Network that is 96.63 % accurate with aligned with the result of the Random Forest Classifier (96 % accuracy with 0.00 standard deviation) having Perceived Benefits as the most significant factor followed by Perceived Vulnerability, Behavioral Intention, Performance Expectancy, and Perceived. These factors will lead to very high usage of online grocery applications. It was established that machine learning algorithms can be used in predicting consumer behavior. These findings may be applied and extended to serve as a framework for government agencies and grocers to market convenient and safe grocery shopping globally.

Gravitating towards Fintech: A study on Undergraduates using extended UTAUT model

One of the most pressing issues affecting people worldwide is the accessibility of financial services in the wake of the COVID-19 outbreak. While peoples' adoption of technological advancements has spiraled over time, the acceptance of Fintech services edged up for instilling resilience during the pandemic. Hence, the study aims at exhuming the Fintech adoption for sustainable financial inclusion among young undergraduate users through the Unified Theory of Acceptance and Use of Technology (UTAUT) model. To test the model, the researchers obtained data from 375 undergrads. The study adopted the Structural Equation Modelling (SEM) approach in AMOS software to examine the determinants that affect the users to embrace Fintech services. The findings revealed that performance expectancy, effort expectancy, and facilitating conditions significantly influence the students' intention to use Fintech, whereas, the users' facilitating condition and behavioral purposes positively influence them to use the financial technology. Interestingly, the social influence and personal innovativeness did not affect their intention to accept and adopt Fintech. Therefore, the study results will help explore the expectations, preferences, and actual level of use of Fintech among undergraduates and contribute to the escalation of Fintech use, leading to sustainable financial inclusion.

Assessment of users' adoption behaviour for stock market investment through online applications

Investing in stocks has become increasingly accessible, with beginners able to start an account via a brokerage's website or mobile app with very little money. Online trading through applications allows you to trade independently without a broker's interference. This not only lowers the overall cost of trading but also makes it hassle-free, increasing the value of the business significantly. Using an online trading account gives an investor more control. This paper examined the user's perspective on stock market investment through online applications. The impact of users' awareness, benefits & choice of investment, reliability, safety, risk-related factors, financial literacy, technical aspect, and dependency was analyzed on users' adoption behaviour. An empirical survey with a valid sample of 424 respondents from India was collected from the respondent and analyzed using descriptive analysis, correlation analysis, reliability analysis, analysis of variance, and regression analysis. Results indicated that users' awareness, benefits & choice of investment, reliability, safety, risk-related factors, financial literacy, technical aspect, and dependency significantly influence the users' adoption behaviour in using stock trading applications. The findings will assist potential investors in comprehending the factors influencing the adoption of such apps and aiding the organizations engaged in operating or creating such applications in understanding user behaviour, which will significantly add value to the society at large.

Clinicians' Perceptions of Artificial Intelligence: Focus on Workload, Risk, Trust, Clinical Decision Making, and Clinical Integration

Artificial intelligence (AI) offers the potential to revolutionize healthcare, from improving diagnoses to patient safety. However, many healthcare practitioners are hesitant to adopt AI technologies fully. To understand why, this research explored clinicians' views on AI, especially their level of trust, their concerns about potential risks, and how they believe AI might affect their day-to-day workload. We surveyed 265 healthcare professionals from various specialties in the U.S. The survey aimed to understand their perceptions and any concerns they might have about AI in their clinical practice. We further examined how these perceptions might align with three hypothetical approaches to integrating AI into healthcare: no integration, sequential (step-by-step) integration, and parallel (side-by-side with current practices) integration. The results reveal that clinicians who view AI as a workload reducer are more inclined to trust it and are more likely to use it in clinical decision making. However, those perceiving higher risks with AI are less inclined to adopt it in decision making. While the role of clinical experience was found to be statistically insignificant in influencing trust in AI and AI-driven decision making, further research might explore other potential moderating variables, such as technical aptitude, previous exposure to AI, or the specific medical specialty of the clinician. By evaluating three hypothetical scenarios of AI integration in healthcare, our study elucidates the potential pitfalls of sequential AI integration and the comparative advantages of parallel integration. In conclusion, this study underscores the necessity of strategic AI integration into healthcare. AI should be perceived as a supportive tool rather than an intrusive entity, augmenting the clinicians' skills and facilitating their workflow rather than disrupting it. As we move towards an increasingly digitized future in healthcare, comprehending the among AI technology, clinician perception, trust, and decision making is fundamental.

Adopting e-government to monitor public infrastructure projects execution in Nigeria: The public perspective

Public infrastructure projects (PIPs) are critical to the socioeconomic development of any country and similar to most public activities, their governance requires effective public participation to be successful. Information and communication technology adoption in government-public engagements (i.e., e-government) has improved public participation in governance in developed countries. This study utilizes the unified theory of acceptance and use of technology to investigate determining factors for the Nigerian public to adopt e-government tools to promote public participation in monitoring PIPs execution. It adopts questionnaire survey and structural equation modelling techniques to show that performance expectancy, facilitating conditions, social influence, and effort expectancy significantly and positively affect behavioral intention to adopt e-government tools to monitor PIPs execution in Nigeria. This study provides scholars with an exploratory baseline for extension of e-government adoption to public infrastructure project management. This study also provides recommendations to policy makers, government technocrats, and project engineers on the need for policy changes, creation of interactive and up-to-date project websites for PIPs in Nigeria.

An empirical evaluation of technology acceptance model for Artificial Intelligence in E-commerce

Artificial Intelligence (AI) has become essential to Electronic-Commerce technology over the past decades. Its fast growth has changed the way consumers do online shopping. Using the Technology Acceptance Model (TAM) as a theoretical framework, this research examines how AI can be made more effective and profitable in e-commerce and how entrepreneurs can make AI technology to assist in achieving their business goals. In this regard, an online survey was conducted from the online purchasers of e-commerce firms. The Partial Least Square (PLS) Smart was used to examine the data. The broadly used TAM was identified as an appropriate hypothetical model for studying the acceptance of AI technology in e-commerce. The findings of this study show that Subjective Norms positively impact Perceived Usefulness (PU) and Pursued Ease of Use (PEU), trust has a positive effect on PEU, and PEU positively impacts PU and attitudes toward use. Similarly, PU also has a positive effect on attitudes toward use and intention to use. Furthermore, the findings do not support the impact of Trust on PU and attitudes towards behavioural intention to use. Lastly, behavioural intention to use positively impacted the actual use of AI technology. This study adds theoretical and practical knowledge for adopting the TAM model in the E-commerce sector. It helps entrepreneurs to implement the TAM model in their business to use AI in a better and more appropriate way.

What motivates customers to repurchase online under social distancing?

Global e-commerce is growing rapidly during the COVID pandemic. Previous research on customers' online shopping decisions rarely considered social distancing. To investigate customers' continued intention toward online purchases while socially isolated, we propose a framework based on the UTAUT model. A survey of 330 valid samples was collected through an online survey among internet users during a period of social distancing in Indonesia. Hypotheses were validated using a structural equation modeling approach. The results showed that social contingency is the most influential factor on customers' intention to repurchase online under social restriction conditions, followed by customer perceived value and other significant factors. The findings contribute to providing a new understanding of customers' online repurchase intentions when they are in a contingency situation.

Analysis of factors affecting the effectiveness of face-to-face marketing learning via TikTok, YouTube and video conferencing

After the COVID-19 pandemic, the use of virtual platforms, social networks and online applications has been totally modified by returning to face-to-face systems. The mandatory use of these tools in the period of social distancing has led to their extensive development. This paper analyzes the effects of the use of ICTs in a purely face-to-face environment. Therefore, it analyzes the factors that affect student satisfaction and effectiveness in marketing learning through the use of digital tools and online applications in face-to-face classes, and this analysis is from a dual perspective of user and learning dissatisfaction. Using a learner-centered approach in university classes, the use of the digital platform Blackboard, the digital tool YouTube and the social network TikTok in university marketing teaching is analyzed. The study is carried out on a sample of 327 university students of different levels. The analysis is performed through a mixed methodology using a symmetric (PLS-SEM) and non-symmetric (fsQCA) approach, allowing a better generalization of the results. In the measurement of effectiveness, both user assessment and student learning assessment are significative, the two being affected in a similar way. However, they are not related to each other, acting independently. Attitude is the construct that has the greatest impact on both types of satisfaction. Perceived enjoyment also exerts a notable influence, especially on learning satisfaction. The study presents one of the first post-pandemic approaches to the analysis of the effectiveness of technological tools (ICT tools) in the face-to-face setting of university marketing classes.

The Behavioral Intention to Adopt Circular Economy-Based Digital Technology for Agricultural Waste Valorization

Thailand generates considerable amounts of agricultural food waste. This research focuses on the manufacturing and retail agricultural food system in the northeastern region of Thailand. Our study aimed to investigate the user segments and factors that influence users' behavioral intentions to utilize mobile technology for agricultural waste valorization. This study is based on the Unified Theory of the Adoption and Utilization of Technology (UTAUT2). In order to classify these segments, we performed a cluster analysis using demographic variables: gender, age, and income. In addition, the researchers employed a method known as multigroup structural equation modeling to determine and contrast the users' behavioral intentions. The results showed two types of users: (1) older users with various income ranges, and (2) younger users with a low-income range. Explicitly, age and income were the significant variables for the demographic segmentation, but gender was not. The results also revealed that social influence, price value, and trust highly affected the behavioral intentions of older and various-income users, but did not influence younger and low-income users. However, privacy strongly affected the behavioral intentions in the younger segment, but not those in the older one. Lastly, habit or regularity influenced the behavioral intentions of users in both segments. This study highlights implications for how developers and practitioners might adapt their platform strategies using a circular agricultural platform and user behaviors.

Older Adults and New Technology: Mapping Review of the Factors Associated With Older Adults' Intention to Adopt Digital Technologies

BACKGROUND

Ongoing advancements in digital solutions support older adults' healthy aging and well-being. However, a unified synthesis of sociodemographic, cognitive, attitudinal, emotional, and environmental factors that influence older adults' intention to use these new digital technologies is still lacking. Understanding the salient factors that influence older adults' intention to use digital technologies will help to ensure that technology is developed appropriately and contextually. This understanding is also likely to contribute to developing technology acceptance models specifically for the aging generation, by reorganizing principles and constructing objectivity criteria for future research studies.

OBJECTIVE

This review aims to identify the key factors associated with older adults' intention to use digital technologies and to provide a comprehensive conceptual framework to describe the relationships between these key factors and older adults' intention to use digital technologies.

METHODS

A mapping review was conducted using 9 databases from inception to November 2022. Articles were selected for review if they had an evaluative component of older adults' intention to use digital technologies. Three researchers independently reviewed the articles and extracted the data. Data synthesis was performed via narrative review and quality appraisal was measured using 3 different tools based on each article's study design.

RESULTS

We identified a total of 59 articles investigating older adults' intention to use digital technologies. The majority (40/59, 68%) of articles did not use an existing framework or model for technology acceptance. Studies mostly adopted a quantitative research design (27/59, 46%). We found 119 unique factors reported to influence older adults' intention to use digital technologies. These were categorized into 6 distinct themes: Demographics and Health Status, Emotional Awareness and Needs, Knowledge and Perception, Motivation, Social Influencers, and Technology Functional Features.

CONCLUSIONS

Given the importance of global demographic change toward an aging society, there is surprisingly limited research on the factors that influence older adults' intention to use digital technologies. Our identification of the key factors across different types of digital technology and models supports the future integration of a comprehensive perspective encompassing environmental, psychological, and social determinants for older adults' intention to use digital technologies.

Understanding student intentions to take online courses: A theory-driven examination of adoption factors and prior experience

Online education options have expanded rapidly, yet empirical knowledge of students' adoption choices remains relatively limited. Within higher education, it is important for both instructors and administrators to understand what students value in online courses in order to provide a quality learning experience and manage enrollment demands. The current work applies and expands on the Unified Theory of Acceptance and Use of Technology (UTAUT) to examine factors involved in course modality choices. Study 1 (N = 257) uses a single discipline to validate measures of online course perceptions and provide initial predictive evidence. Study 2 (N = 1257) examines adoption intentions among students in a wide range of disciplines. Performance expectancies, hedonic motivation, and flexibility emerged as the most substantial factors in student decisions about course modality. The results also reveal shifts in online course perceptions over time, including larger shifts for students with no prior online course experience. These findings expand current understanding of why students choose to take (or avoid) online courses, particularly concerning the role of flexibility in enrollment decisions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10639-023-11823-4.

A comparative analysis of digital health usage intentions towards the adoption of virtual reality in telerehabilitation

BACKGROUND

With the rapid development of the metaverse and the problem of non-attendance in traditional rehabilitation, virtual reality in telerehabilitation has become increasingly vital in modern medicine. However, research on determining predictors that influence the public's behavioral intention to adopt VR-based telerehabilitation has not been extensively studied.

OBJECTIVE

This study aims to propose a new research model with a comparative analysis on understanding factors affecting the public's behavioral intention to adopt VR in telerehabilitation for different user groups.

METHODS

A total of 215 respondents from the general public completed an online questionnaire to validate the proposed research model. The collected data was analyzed using SPSS and AMOS. The proposed model was additionally validated using CFA and multiple linear regression.

RESULTS

This study found that effort expectancy, threat appraisals, and trust had a positive significant influence on the public's behavioral intention to adopt VR in telerehabilitation. However, performance expectancy and facilitating conditions had no significant relationship with behavioral intention. Notably, the average of the primary factors for older adults was generally higher than for younger adults.

CONCLUSIONS

The present study confirms the applicability of the proposed research model. Our findings contribute up-to-date insights for related stakeholders to minimize implementation failures and develop successful adoption strategies for the future expansion of telerehabilitation.

Effects of a remote-handling-concept-based task-oriented arm training (ReHab-TOAT) on arm-hand skill performance in chronic stroke: a study protocol for a two-armed randomized controlled trial

BACKGROUND

Improving arm-hand skill performance is a major therapeutic target in stroke rehabilitation and needs intensive and varied training. However, guided treatment time is limited. Technology can assist in the training of patients, offering a higher intensity and more variety in content. A new task-oriented arm training approach was developed, using a 'Remote Handling concept based' device to provide haptic feedback during the performance of daily living activities (ReHab-TOAT). This study aims to investigate the effects of ReHab-TOAT on patients' arm-hand function and arm-hand skill performance, quality of life of both patients in the chronic phase after stroke and their caregivers and the patients' perception regarding the usability of the intervention.

METHODS

A randomized clinical trial was designed. Adult chronic stroke patients suffering from hemiparesis and arm-hand problems, with an Utrechtse Arm-hand Test score of 1-3, will be invited to participate. Participants in the experimental group receive ReHab-TOAT additional to care as usual. ReHab-TOAT contains task-oriented arm training for stroke patients in combination with haptic feedback, generated by a remote handling device. They will train for 4 weeks, 3× per week, 1.5h per day. Participants in the control group will receive no additional therapy apart from care as usual. The Fugl-Meyer Assessment (FMA), measuring participants' motor performance of the affected arm, is used as the primary outcome measure. Secondary outcome measures are arm-hand capacity of the patient (ARAT), perceived arm-hand skill performance (MAL), actual arm-hand skill performance (accelerometry), patients' quality of life (EuoQol-5D) and caregivers' quality of life (CarerQoL). Participants' perception regarding the usability of the intervention, including both the developed approach and technology used, will be evaluated by the System Usability Scale and a questionnaire on the user experience of technology. Measurements will be performed at 1, 2, 3 and 4 weeks pre-intervention (baseline); immediately post-intervention; and 3, 6 and 9 months post-intervention. Statistical analysis includes linear mixed model analysis.

DISCUSSION

This study is designed to investigate the evidence regarding the effects of ReHab-TOAT on patients' performance at different levels of the International Classification of Functioning, disability and health (ICF) model, i.e. a framework measuring functioning and disability in relation to a health condition, and to provide insights on a successful development and research process regarding technology-assisted training in co-creation.

TRIAL REGISTRATION

Netherlands Trial Register NL9541. Registered on June 22, 2021.

Factors influencing the behavioral intention to use contactless financial services in the banking industry: An application and extension of UTAUT model

Introduction

Contactless financial services are an innovative exploration of the banking industry to integrate digital technology. This study further modified the UTAUT model based on the theories of trust, perceived risk, and perceived advantage and constructed a conceptual model to examine the influencing factors of the behavior of using contactless financial services. The purpose of this paper is to figure out factors influencing users’ behavior intention of contactless financial services, in order to promote use behavior, and boost the further development of contactless financial services.

Methods

The model was validated using the data collected through questionnaires. The structural equation modelling (SEM) method was used to validate the research model. We analyzed the generated hypotheses by using AMOS version 23.0. In this study first analyzed the measurement model to test the reliability and validity of the instrument, and then analyzed the structural model to test our research hypotheses.

Results

The results reveal that trust and perceived risk are important factors that affect the behavioral intention of contactless financial services; users perceive that contactless financial services have advantages over traditional offline channel, their intention to use contactless financial services will be increased; social influence also has a positive impact on behavioral intention.

Discussion

This paper not only provides a theoretical understanding of contactless financial services use behavior but also offers practical insights to government legislative branches and app developers. By providing personalized services and refining the policies and regulations in the digital environment to promote the development of contactless financial services.

Investigating the intention of purchasing private pension scheme based on an integrated FBM-UTAUT model: The case of China

The newly established private pension scheme in China has received great attention as it would be an important supplement to China’s social safety net and corporate annuity amid an aging population. It provides a way of helping to address the challenge of ensuring adequate retirement income, and the scheme is expected to grow significantly in the coming years. This study investigates factors affecting the intention of purchasing the private pension scheme using a conceptual model based on the integration of Fogg Behavioral Model (FBM) and Unified Theory of Acceptance and Use of Technology (UTAUT) model. The questionnaire-based data from a sample of 462 respondents had been analyzed. Both exploratory factor analysis and confirmatory factor analysis were used to assess validity. The hypothesized relationships in the integrated FBM-UTAUT model were tested using structural equation modeling. The research findings indicate that anticipation, social influence, effort expectancy, performance expectancy, side benefits and facilitating conditions have significant positive impacts on intention to purchase. According to the exploratory factor analysis, the integrated FBM-UTAUT model can explain more than 70% of the total variance. Meanwhile, effort expectancy can be affected by time effort, thought effort and physical effort collectively, while performance expectancy can be affected by risk and trust. It is revealed that the integrated FBM-UTAUT model can be effective in explaining purchase intentions in a private pension scheme context, and this study is expected to offer helpful advice on the design of pension products and the reform of pension policies.

Assessment of the Building Situation Tool Adoption Among Firefighters

Technology is a standard tool that first responders use in their assessment and planning during disasters. Despite the considerable number of hardware and software solutions adopted, first responders still often rely on paper plans when examining indoor disasters. The purpose of this research is to investigate the technical competencies of firefighters and test the building situation tool (BUST) to replace the paper plans. A mixed method approach was used to assess the technology self-efficacy and gather insight into perceived usefulness, ease of use, and the user experience from the firefighters (N=20). The findings show a sufficient level of competency, and that first time users prefer guided instructions, clarity in the user interface, controls, and options to customize the user interface. The findings have practical implications for the future development of BUST and its adoption to the workflow of firefighters.

On the Technology Acceptance Behavior of Romanian Preschool Teachers

This study investigates how compatibility and perceived enjoyment affect the link between intention to use and actual technology use in Romanian preschool education, building on earlier studies.

METHODS

300 participants were invited to participate in this research from 15 Romanian counties. 182 preschool teachers' questionnaires were utilized for data analysis after the return and screening of responses. A valid and accurate scale evaluating preschool teachers' behavior towards technology adoption was included in the questionnaire, along with self-reported demographic data, professional identification, and other information. Data was analyzed using SPSS V.16.

RESULTS

(1) Intention to use, compatibility, perceived enjoyment, and actual use were positively associated. (2) The effect of compatibility and perceived enjoyment on the link between intention to use and actual technology use was carried out in the following way: Intention to use → Compatibility with technology → Perceived enjoyment → Actual use. We hypothesize that intention to use affects compatibility, compatibility affects perceived enjoyment, and, lastly, perceived enjoyment affects actual use. For a more robust validation of results, we have also modelled this relationship with the Radial Basis Function (RBF) neural network.

CONCLUSION

Compatibility and perceived enjoyment partially mediate the relationship between intention to use and actual technology use in class by Romanian preschool teachers. According to the theory of planned behavior, this study brought to light the intricacy of the relationship between preschool teachers' intention to utilize technology in the classroom and their actual usage of it. Limitations and implications are discussed.

Acceptance of Smart Technologies in Blended Learning: Perspectives of Chinese Medical Students

Smart technologies are essential in improving higher education teaching and learning. The present study explores the factors that influence students' behavioural intentions to adopt and use smart technologies in blended learning. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT2) model, a survey of 305 students was conducted to collect data. A structural equation model was applied to analyse the data. The findings show that adopting smart technologies requires appropriate social context and organizational support. Moreover, the data indicated that performance expectancy, effort expectancy, social influence, hedonic motivation, and habit are vital in determining students' behavioural intention to use smart technologies. However, facilitating conditions and price value were found to have no significant impact on the students' behavioural intention to use smart technologies. The study contributes to a better understanding of the nexus of blended learning and smart technologies, thus improving students' experiences in blended learning settings.

Canadian Older Adults' Intention to Use an Electronic Decision Aid for Housing Decisions: Cross-sectional Web-Based Survey

BACKGROUND

Older adults with disabilities such as loss of autonomy face the decision of whether to stay at home or move to a health care facility such as a nursing home. Therefore, they may need support for this difficult decision.

OBJECTIVE

We assessed the intention of Canadian older adults to use an electronic decision aid (eDA) to make housing decisions and identified the factors that influenced their intention.

METHODS

We conducted a cross-sectional study using a web-based survey targeting older adults across 10 Canadian provinces and 3 territories. We included respondents from a web-based panel who were aged ≥65 years, understood English or French, had access to an electronic device with an internet connection, and had made a housing decision over the past few months or were planning to make a decision in the coming year. We based the web-based survey on the Unified Theory of Acceptance and Use of Technology (UTAUT). We adapted 17 UTAUT items to measure respondents' intention to use the eDA for housing decisions, as well as items measuring 4 intention constructs (performance expectancy, effort expectancy, social influence, and facilitating conditions). We also assessed eHealth literacy using both subjective and objective scales. We used descriptive statistics and multivariable linear regression analyses to identify the factors influencing the intention to use the eDA.

RESULTS

Of the 11,972 invited panelists, 1176 (9.82%) met the eligibility criteria, and 1000 (85.03%) respondents completed the survey. The mean age was 72.5 (SD 5.59) years. Most respondents were male (548/1000, 54.8%), White (906/1000, 90.6%), English speakers (629/1000, 62.9%), and lived in Ontario or Quebec (628/1000, 62.8%) and in urban areas (850/1000, 85%). The mean scores were 27.8 (SD 5.88) out of 40 for subjective eHealth literacy and 3.00 (SD 0.97) out of 5 for objective eHealth literacy. In our sample, the intention score was 4.74 (SD 1.7) out of 7. The mean scores of intention constructs out of 7 were 5.63 (SD 1.28) for facilitating conditions, 4.94 (SD 1.48) for performance expectancy, 5.61 (SD 1.35) for effort expectancy, and 4.76 (SD 1.59) for social influence. In the final model, the factors associated with intention included mother tongue (β=.30; P<.001), objective eHealth literacy (β=-.06; P=.03), performance expectancy (β=.55; P<.001), social influence (β=.37; P<.001), and facilitating conditions (β=.15; P<.001).

CONCLUSIONS

Findings from this pan-Canadian web-based survey on Canadian older adults suggest that their intention to use the eDA to make housing decisions is similar to the findings in other studies using UTAUT. The factors identified as influencing intention were mother tongue, objective eHealth literacy, performance expectancy, social influence, and facilitating conditions. These will guide future strategies for the implementation of the eDA.

Study on factors influencing college students' digital academic reading behavior

Background

Affected by the COVID-19, many colleges have adopted online teaching. Meanwhile, the digital transformation of academic journals has shifted readers' reading habits from traditional paper media to digital media. Digital academic reading has become the main reading method of college students during the COVID-19 pandemic.

Purpose

The purpose of this study was to investigate the behavioral characteristics of college students' digital academic reading and explore the internal factors and external environmental factors affecting the Intention and Use behavior of digital academic reading. At the same time this study provide recommendations to address these influencing factors in terms of the individual, the environment and library resources.

Methods

Based on UTAUT2 model and digital academic reading theories, this paper constructs a digital academic reading information behavior (DARB) model of college students to examine college students' digital academic reading behavior and intention. College students with digital academic reading behavior were recruited as research participants. A multi-stage sampling technique was used to collect representative samples from universities in Nanjing. 239 respondents participated in the questionnaire, with 189 providing valid data. Results: Effort expectancy (EE), social influence (SI), price value (PV), perceived risk (PR) and habit (BH) have a significant impact on behavioral intention (BI), and behavioral intention (BI) and habit (BH) have a significant impact on use behavior (B). However, performance expectancy (PE) and facilitating conditions (FC) have no significant influence on behavioral intention (BI).

Originality/value

The findings of this study will help fill the gap in previous research on the relationship between the influencing factors of digital academic reading and college students' reading intentions and behaviors, so as to provide a basis for improving the academic reading literacy program in colleges and optimizing the current digital academic reading environment.

Assessing the Acceptability of Home Blood Monitoring for Patients With Cancer Who Are Receiving Systemic Anticancer Therapy From a Patient, Caregiver, and Clinician Perspective: Focus Group and Interview Study

BACKGROUND

Regular blood testing is an integral part of systemic anticancer therapy delivery. Blood tests are required before every administration of treatment to ensure that a patient is sufficiently well to receive it. Blood testing is burdensome for patients as they require either an extra visit within 48 hours of planned administration of treatment or a significantly long visit if performed on the day of treatment. The additional time for appointments can have a significant impact on the quality of life of someone who is living with cancer. In the United Kingdom, the COVID-19 pandemic created unprecedented disruption to the delivery of cancer care. Face-to-face hospital visits were reduced, resulting in the need to develop more innovative ways of working to minimize treatment interruptions. This led to significant uptake of digital technologies, with new models of care rapidly deployed across the UK health service to meet these challenges.

OBJECTIVE

This study aimed to explore the acceptability of a point-of-care home blood monitoring device for people with cancer who are receiving systemic anticancer therapy, which is being developed in response to the increased need for remote care for patients with cancer.

METHODS

Qualitative focus groups and semistructured interviews were conducted with patients (23/47, 49%), caregivers (6/47, 13%), and health care professionals (18/47, 38%) over a 19-month time frame from May 2019 to December 2020. Data were analyzed using framework analysis guided by the Unified Theory of Acceptance and Use of Technology model.

RESULTS

Analysis identified 4 overarching themes: performance expectancy, effort expectancy, social influence, and facilitating conditions.

CONCLUSIONS

This study found that patients with cancer, their caregivers, and health care professionals had positive perceptions about home blood monitoring. Although they are often considered synonymously, self-testing and self-management are not mutually exclusive, and this study illustrated some disparity in opinions regarding patient self-management. Home blood monitoring has the potential to provide patients with cancer with a convenient option for blood monitoring. It would minimize hospital attendances, decrease late treatment deferrals, and provide prompt recognition of cancer treatment toxicities, thus enhancing the existing nurse-led protocols and clinical pathways. Home blood monitoring would create a long-term sustainable transformation for the delivery of cancer care, using digital health to act as a facilitator to address a pertinent issue regarding improving the efficiency of hospital resources and increasing the delivery of personalized patient care. Further studies are needed to determine how and where home blood monitoring would fit within clinical pathways, in a way that is robust and equitable.

SentiTAM: Sentiments centered integrated framework for mobile learning adaptability in higher education

Online communities provide facilities to share public opinions and or sentiments on a wide range of subjects, from routine topics to vital issues of critical interest. Nowadays, many higher education institutions (HEIs) recognize the value of students' sentiments and evaluate users' concerns for the successful adaptation of mobile learning applications (MLAs). While digital learning has been extensively studied previously, little has been known about why MLA is underutilized. Therefore, this study extends the literature by proposing the SentiTAM model underlying technology acceptance model (TAM), and students' sentiments on MLA platforms. A self-administered cross-sectional survey of 350 MLA users' data was analyzed through structural equation modeling (SEM) using the AMOS package program. In addition, we have performed sentiment analysis on students' opinions gathered through Google discussion forums and Twitter. The results show that MLA use intention is strongly influenced by sentiments and self-motivation, while perceived usefulness and perceived ease of use directly influence MLA usage. To the best of our knowledge, this study is the first attempt in MLA that investigates several vital factors, including sentiments as a multi-perspective tool and motivational factors with core constructs of TAM. The findings assist developing countries make smart decisions about how to use MLA with emerging technology.

A readiness assessment framework for the adoption of 5G based smart-living services

The subject of this article is to analyze the users’ attitude towards new, 5G-enabled smart living services before their commercial launch. The goal is to offer a framework for the analysis and evaluation of influential factors in the early adoption of 5G residential services. Additionally, the paper examines how mobile operators can leverage their existing infrastructure and services to boost the acceptance of both 5G as a technology and the provided smart-living services. To ascertain the potential impact that mobile operators can have on the adoption of such services, loyalty programs were taken into account as a separate factor in the acceptance study. The study was conducted in Serbia in the form of a survey. The analysis of the results yielded some notable conclusions such as trust in technology playing the leading role in influencing the behavior intention, while loyalty programs showed that they can influence attitudes towards individual smart living services. The presented results can be used to shape any future implementation of 5G-based services in Serbia, or any other country whose 5G infrastructure and services for the residential customer segment are yet to be established.

Determinants of blockchain adoption in news media platforms: A perspective from the Vietnamese press industry

Blockchain technology is being applied worldwide. Although a large body of blockchain research has been conducted in various fields, little is known about press perspectives on adopting blockchain in journalism. This study explores the determinants of applying blockchain in journalism activities in Vietnam. Based on Unified Theory of Acceptance and Use of Technology (UTAUT) and previous research, we surveyed 287 people working at press agencies in Vietnam. The results from testing nine research hypotheses show that five factors, namely Technology Affinity, Effort Expectancy, Facilitating Condition, Technology Readiness, and Regulatory Support, positively impact the intention of applying Blockchain in journalism activities in Vietnam. Two factors, namely Performance Expectancy and Trust, were not positively strongly correlated to the use of blockchain. Besides, Regulatory Support is found to have a moderating effect on the relationship between Facilitating Condition and Behavioral Intention.

Acceptance of online distance learning (ODL) among students: Mediating role of utilitarian and hedonic value

Nowadays, the teaching methods are changed from offline to online primarily for the advent of the internet facility. The Industrial Revolution 4.0 ("Education 4.0") stresses offering online courses at the university level. The study aims to find out the factors influencing students' intentions to admit to online distance learning courses. In addition, the study wanted to establish the utilitarian and hedonic value construct in mediating the association between attitude and intention. Based on an intensive literature survey, an extended Technology Acceptance Model was proposed including some cognitive and technology-specific factors to test empirically. This is a quantitative study with an exploratory and descriptive scope and cross-sectional design. The information was gathered by applying the convenience sampling method from 293 Malaysian students who participated in anonymous surveys. The obtained data were analyzed using structural equation modeling applying AMOS 21 version. The study reveals that hedonic value, utilitarian value, perceived ease of use, and attitude except for perceived usefulness, affect behavioral intention to accept online distance learning courses except for perceived usefulness construct. The antecedents of utilitarian value are perceived fees, attitude, perceived usefulness, and perceived ease of use, whereas the antecedents of hedonic value are perceived fees, attitude, and perceived usefulness, except for perceived ease of use. Finally, self-efficacy affects perceived ease of use, perceived usefulness, and attitude towards joining online distance learning courses. This study's conclusions will benefit all stakeholders in the education system who are considering or have already adopted e-learning.

Factors Associated With Intention and Use of e-Mental Health by Mental Health Counselors in General Practices: Web-Based Survey

BACKGROUND

Mental health care counselors have a high intention to use e-mental health (EMH), whereas actual use is limited. Facilitating future use requires insight into underlying factors as well as eligibility criteria that mental health care counselors use in their decision to apply EMH.

OBJECTIVE

The aim of this study was to unfold the intention and underlying reasons for mental health counselors to use EMH and to unveil the criteria they use to estimate patient eligibility for EMH. The theoretical framework was based on the reasoned action approach model, the Unified Theory of Acceptance and Use of Technology, and the Measurement Instrument for Determinants of Innovation model.

METHODS

To empirically validate our theoretical model, a web-based survey was conducted among mental health care counselors (n=132). To unveil the eligibility criteria, participants were asked to rank their reasons for considering EMH suitable or unsuitable for a patient.

RESULTS

The mean intention to use EMH was positive (mean 4.04, SD 0.64). The mean use of EMH before the COVID-19 pandemic was 38% (mean 0.38, SD 0.22), and it was 49% (mean 0.49, SD 0.25) during the pandemic. In total, 57% of the patient population was considered eligible for EMH. Usefulness and benefits (β=.440; P<.001), Task perception (β=.306; P=.001), and Accessibility (β=.140; P=.02) explained the intention to use EMH (F_3,131=54.151; P<.001; R²=0.559). In turn, intention explained patient eligibility (F_1,130=34.716; P<.001; R²=0.211), whereas intention and patient eligibility explained EMH use (F_2,129=41.047; P<.001; R²=0.389). Patient eligibility partially mediated the relationship between intention to use EMH and EMH use, with a larger direct effect (c'=0.116; P<.001) than indirect effect (c=0.065, 95% CI 0.035-0.099; P<.001). Mental health counselors assessed patients' eligibility for EMH mainly through the availability of computers and the internet and patient motivation.

CONCLUSIONS

To stimulate the use of EMH, intention and patient eligibility need to be influenced. Intention, in turn, can be enhanced by addressing the perceived usefulness and benefits of EMH, perceived accessibility, and task perception. Access to a computer and patients' motivation to use EMH are important in facilitating patient eligibility. To cause an impact with EMH in general practice, mental health counselors need to be convinced of the benefits of EMH and transfer this enthusiasm to the patient. It is recommended to involve mental health counselors in the development of EMH to increase the (perceived) added value and use.

Longitudinal study of teacher acceptance of mobile virtual labs

Synthesizing the advancements in technology with classroom practices depends considerably on teachers acceptance of such internet and communication technology (ICT) tools. Adequate teacher training and upgrading of their IT skills are not prioritized in developing economies leading to poor adoption of emerging technology assisted pedagogic interventions. This paper investigated the underlying characteristics of teachers acceptance of mobile friendly virtual laboratories (M-VLs) as part of a longitudinal study conducted over 5 years covering both pre-pandemic and pandemic periods. Systematic analysis of quantitative data from 650 chemistry teachers was carried out. Viewing through the theoretical lens of Unified Theory of Acceptance and Use of Technology (UTAUT2) theory, the effects of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM) and habit (HA) on the behavioral intention (BI) and use behavior (UB) were scrutinized. Structural Equation Modeling (SEM) analysis revealed that PE, SI, and HA are the considerable predictors of the BI to use M-VLs and HA is the predictor of UB. The present study found HM influencing teacher's BI and UB before COVID-19. However during COVID-19 the FC influenced usage. Moreover, we found that the technology training focused on enhancing knowledge, skill and, access leads to teachers' are critical to empowering teachers and causing wider adoption.

Factors influencing adoption of e-learning in healthcare: integration of UTAUT and TTF model

BACKGROUND

The importance of successful implementation of e-learning, especially since the emergence of the Covid-19 pandemic, has become increasingly apparent to universities. Thus, identifying the effective factors in adopting e-learning in the Covid-19 pandemic is crucial. This study was conducted to identify determining factors in adopting E-learning in healthcare.

METHOD

This was a descriptive-analytical study in which 143 faculty members from Iran were randomly selected. The faculty members' intentions, concerning the adoption of e-learning, were assessed by the conceptual path model of integration of unified theory of acceptance and use of technology (UTAUT) and The Task-Technology Fit (TTF).

RESULTS

The results showed that the combination of the two classical theories, UTAUT and TTF, was an appropriate model to explain faculty members' intention in adopting e-learning. Moreover, the findings showed that technology and task characteristics, task- technology fit, social influences, effort expectancy, performance expectancy and facilitating conditions had direct and significant effect on e-learning adoption.

CONCLUSION

By presenting a conceptual path model to elucidate users' behavior in adopting e-learning, this study investigated and identified the key determining factors in adopting e-learning. The findings of the present study can contribute to the design and implementation of e-learning by practitioners, policy makers, and curriculum designers.

Rural small scale farmers' smart mobile phone usage acceptance prognosticators for agricultural marketing information access

The purpose of the article is to examine the rural small scale farmers' smart mobile phone usage acceptance prognosticators for agricultural marketing information access in selected farming towns in Zimbabwe. Responses were collected from rural small scale farmers in Marondera, farming town in Zimbabwe using structured questionnaire with a 7 point Likert scale. The research study depicted that trust, social influence, perceived risk and relative advantage have positive influence on rural small scale farmers' smart mobile phone usage acceptance for agricultural marketing information access adoption intention in Zimbabwe. The study has limitations which may affect the generalisability of the results since they can only be applied to the studied areas, all in Mashonaland East province of Zimbabwe. Agricultural marketers are encouraged to focus more attentively on smart mobile phone acceptance determinants such as social influence, perceived risk and trust when devising mobile agricultural marketing strategies especially during uncertain times. The study adds to theoretical literature development by extending knowledge on the UTAUT2 theoretical framework since there is paucity of research that have directly applied the same model in agricultural marketing and general agribusiness. Practically, the study enhances the need for adoption of contemporary technologies to solve the current challenges facing farmers in the marginalised rural areas, not only in Africa, but also dotted around the world.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s43545-022-00562-x.

Factors affecting university students switching intention to mobile learning: a push-pull-mooring theory perspective

Adopting technology by its intended users is one of the most important contributors to that technology's success. Therefore, the success of mobile learning (ML) depends on the students' acceptance of the method. Regarding this point, this quantitative research aims to identify factors that affect switching intention to adopt ML among university students in Indonesia based on migration theory, Push-Pull-Mooring (PPM) framework. A theoretical model was developed to examine the determinants that affect students' decision to use ML platforms. This study used an online survey questionnaire to obtain 616 valid responses. A comprehensive analysis of the influence factors of users switching behavior, including the moderating factors, was conducted using Structural Equation Modeling (SEM) and Amos software. The results confirmed that the push factor (learning convenience), pull factors (learning autonomy and enjoyment), and mooring factor (student innovativeness) are perceived as significant factors for accepting ML. Concerning the moderating factor, this study also revealed the significance of moderating factor experience in two causal effects of enjoyment and student innovativeness on the students' intention to switch using ML. Furthermore, based on the findings, several recommendations were suggested for the university policy-makers to develop effective strategic plans to get a competitive advantage.