Abstract:Abstract-The urge to progressively motivate ecounselling in schools is somewhat dependent on students" behavioural intention towards the use of counselling technologies. This paper presents an empirical approach of using Unified Theory of Acceptance and Use of Technology model to ascertain students" behavioural intention to adopt and use e-counselling in Ghana.
“…Good performance expectancy with indicators of perceived usefulness, extrinsic motivation, job suitability, relative advantage, and expectations of the results of filling in patient health data into the EMR would cause the health professions to have the intention and commitment to carry out work that will ultimately fill the EMR. The results of this study also indicated that performance expectations have a direct, partial effect on behavioral intentions, such as enthusiasm, persuasion, and willingness (Emmanuel et al, 2015); (Tarhini et al, 2016); (Ramdhani et al, 2017); (Sharifian et al, 2014); (Ma et al, 2016); (Archer & Cocosila, 2011); (Shiferaw & Mehari, 2019); (Bawack & Kala Kamdjoug, 2018); (Wrzosek et al, 2020); (Abdekhoda & Salih, 2017); (Fatimatus Zayniyah, 2016) ; (Gagnon et al, 2014); and this is not line with the result of the study (Enaizan et al, 2020).…”
Health and well-being are the third Sustainable Development Goals (SDGs) in the 2030 Agenda for Sustainable Development. To accomplish this, Soetomo hospital as the largest referral hospital in the province of East Java is expected to have an Electronic Medical Record (EMR) completeness level of 100 percent by 2024. This study aimed to examine the impact of performance expectation and behavioral intention on hospital EMR technology usage. This was an observational study with a cross sectional research design. From a population of 390 health workers, a sample of 195 was generated using proportional random sampling. Validity and reliability can be determined using SPSS software. Utilizing SEM PLS software, the analysis is evaluated. Results indicate that performance expectation can have a direct effect on technology use EMR (T Statistic = 21,506) and an indirect effect via behavioral intention (T Statistic = 15,038). The relationship between behavioral intention and technology use EMR is direct (T statistic = 5,475). Conclusion: Performance expectations explain 52% of behavioral intention, while behavioral intentions explain 85% of technology use EMR.
“…Good performance expectancy with indicators of perceived usefulness, extrinsic motivation, job suitability, relative advantage, and expectations of the results of filling in patient health data into the EMR would cause the health professions to have the intention and commitment to carry out work that will ultimately fill the EMR. The results of this study also indicated that performance expectations have a direct, partial effect on behavioral intentions, such as enthusiasm, persuasion, and willingness (Emmanuel et al, 2015); (Tarhini et al, 2016); (Ramdhani et al, 2017); (Sharifian et al, 2014); (Ma et al, 2016); (Archer & Cocosila, 2011); (Shiferaw & Mehari, 2019); (Bawack & Kala Kamdjoug, 2018); (Wrzosek et al, 2020); (Abdekhoda & Salih, 2017); (Fatimatus Zayniyah, 2016) ; (Gagnon et al, 2014); and this is not line with the result of the study (Enaizan et al, 2020).…”
Health and well-being are the third Sustainable Development Goals (SDGs) in the 2030 Agenda for Sustainable Development. To accomplish this, Soetomo hospital as the largest referral hospital in the province of East Java is expected to have an Electronic Medical Record (EMR) completeness level of 100 percent by 2024. This study aimed to examine the impact of performance expectation and behavioral intention on hospital EMR technology usage. This was an observational study with a cross sectional research design. From a population of 390 health workers, a sample of 195 was generated using proportional random sampling. Validity and reliability can be determined using SPSS software. Utilizing SEM PLS software, the analysis is evaluated. Results indicate that performance expectation can have a direct effect on technology use EMR (T Statistic = 21,506) and an indirect effect via behavioral intention (T Statistic = 15,038). The relationship between behavioral intention and technology use EMR is direct (T statistic = 5,475). Conclusion: Performance expectations explain 52% of behavioral intention, while behavioral intentions explain 85% of technology use EMR.
“…This study focused on assessing the nurses' feedback on WMMS, which includes (1) acceptance, (2) usability, and (3) experience. First, the perceived acceptance of WMMS was measured using the Unified Theory of Acceptance and Use of Technology model 12,13 with a Cronbach's α of .87 14 . It consists of four primary constructs, namely, (1) performance expectancy, the belief that using the system can improve job performance; (2) effort expectancy, the user-friendliness of the system; (3) social influence, the perception of other people about the system; and (d) facilitating conditions, the availability of resources to use the system feasibly.…”
A common medication safety strategy involves a Web-based medication management system. Still, there is no consensus about its acceptance and usability, even more so among nurses in the Philippines. Thus, this pilot study used a mixed-methods design to explore the nurses' feedback (N = 26) about Web-based medication management system in a telehealth hospital. Their acceptance, perceived usability, and experience of Web-based medication management system were assessed using the Unified Theory of Acceptance and Use of Technology model, Post Study System Usability Questionnaire, and semistructured interview guide, respectively. Results showed nurses agreed on their acceptance of Web-based medication management system (M = 3.72 [SD = 0.69]) and slightly agreed on its usability (M = 5.18 [SD = 1.02]). It also generated the Nursing Capsule of Web-based medication management system use that combines the quantitative model with age and length of practice as significant predictors and the qualitative interaction vortex with three themes (i.e., engaging, enabling, and exciting). These findings emphasized the need for effective technological adaptation to advance nursing practice and patient care.
“…In addition to referring to TAM, this study also bases its concept on the Unified Theory of Acceptance and Use of Technology Model (UTAUT) developed by Venkatesh et al (2003). The idea of UTAUT refers to eight models that examine behavior, among others Theory of Reasoned Action (TRA), Motivational Model/MM, TAM Theory of Planned Behavior/TPB, a combined Theory of Planned Behavior and Technology Acceptance Model/TPB-TAM, Model of Personal Computer use and a combined Theory of Diffusion of Innovations Theory/MPC-TDIT, and Socio Cognitive Theory (SCT) (Kolog et al 2015).…”
Section: Unified Theory Of Acceptance and Use Of Technology Model (Utmentioning
The Covid-19 pandemic marks an era of using online as a medium of learning communication, including counseling services. School Counselor are required to use ICT as a form of adaptation to learning with students. The research design using a quantitative Structural equation modeling aimed to test correlation of two or more variables. The participants are 214 School Counselor who are members of the Indonesian Guidance and Counseling Association (ABKIN) and the Guidance and Counseling Teacher Council (MGBK). This study measures the participation of School Counselor who fill out online questionnaires with respect to their perceptions of maximizing the use of ICT in providing counseling services. Measurement of the successful use of ICT in Guidance and counseling (BK) services during a pandemic will be measured through the attributes of Computer Anxiety (CA), Computer Self-Efficacy (CSA), Collegial Collaboration (CC), Lack Facility (LF), Perceive Usefulness (PU), and Perceived Ease of Use (PEOU). The results showed findings in which all attributes have a significant outcome on the use of ICT on School Counselor.
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