Modeling predictors of acceptance and use of electronic medical record system in a resource limited setting: Using modified UTAUT model

Factors influencing clinician performance post-electronic health record implementation: an empirical analysis in Moroccan hospitals

BACKGROUND

In recent years, the Moroccan Ministry of Health and Social Protection has invested considerable resources in implementing electronic health record (EHR) systems to provide citizens with quality healthcare services through efficient structures. However, the rhythm of EHR deployment across the country is very slow, requiring urgent evaluation to remove barriers to successful EHR adoption.

OBJECTIVE

This study aims to investigate the critical factors affecting healthcare providers' performance post-EHR implementation in Moroccan public hospitals.

METHODS

A cross-sectional study was conducted in three hospitals affiliated with Hassan II University Hospital Center in Fez. Data were collected using a questionnaire survey administered to a sample of 368 healthcare providers from March 2021 to July 2021. Clinician performance was assessed using a proposed research model that integrates the Information System Success Model and the Technology-Organization-Environment framework. The final model was analyzed and tested by using structural equation modeling. Statistical analyses were conducted using SPSS version 25 and Amos version 26.

RESULTS

The findings highlighted that the most critical factors influencing clinician performance are clinician satisfaction (β = 0.5, p < 0.001), followed by organization (β = 0.28, p < 0.001), and system quality (β = 0.17, p = 0.01). Additionally, information quality indirectly affects clinician performance (β = 0.19, p < 0.001). However, the environmental factor does not appear to have a significant impact (β = -0.004, p = 0.94).

CONCLUSION

This study, performed for the first time in Morocco, identifies key factors for policymakers and healthcare organizations to enhance the successful implementation of EHR systems. Additionally, it serves as a valuable framework for future studies in this area.

Health Workers' Acceptance and Satisfaction on the Usability of the Digital Health Goods, in Kono District, Sierra Leone

Introduction

Digital health systems implementation in developing countries is increasing exponentially, and digital health interventions are essential tools to improve healthcare access and quality. In contrast, the evidence base is meager about the acceptance and satisfaction of end users towards digital health goods. Hence, this study aims to evaluate the acceptance and satisfaction of end users on the usability of digital goods in Sierra Leone.

Methods

Health facility-based cross-sectional study design was employed, and a total of 151 participants were included. Data were collected using a validated data collection tool. Initially, descriptive data analysis was done. Finally, bivariate and multivariate logistic regressions were applied to identify predictors for user acceptance of digital health goods. Finally, findings are presented as AORs along with 95% CIs.

Results

The study considered 151 respondents for analysis. In this study, 72.2% with 95%  CI: 64.4-78.8% of respondents have good acceptance of the digital health systems. The findings revealed that 49.7% and 45.7% of respondents were strongly satisfied and satisfied, respectively. The regression analysis indicated that perceived ease of use [AOR=5.56; 95% CI: 2.17, 14.26], digital health system type [AOR=0.18, 95% CI: 0.06, 0.55], and frequency of digital system use [AOR=0.04; 95% CI: 0.01, 0.41] were predictors of user acceptance. The major barriers for successful implementation were inability to be used offline, being slow, and taking longer time to input information in the digital systems.

Conclusion

End user acceptance and satisfaction with digital health goods were high. Perceived ease of use, digital system type, and frequency of using digital systems are predictors of user acceptance. Major barriers to digital systems implementation include inability to be used offline and taking longer time to input information in the systems. Long-term system acceptance could be achieved through addressing end user preference and potential barriers of implementation.

Acceptance of artificial intelligence clinical assistant decision support system to prevent and control venous thromboembolism among healthcare workers: an extend Unified Theory of Acceptance and Use of Technology Model

Background

Venous thromboembolism (VTE) is an important global health problem and the third most prevalent cardiovascular disorder. It has been proven that computerized tools were helpful in the prevention and control of VTE. However, studies that focused on the acceptance of computerized tools for VTE prevention among healthcare workers were limited.

Objective

This study aims to explore what factors are influencing healthcare workers' acceptance of the Artificial Intelligence Clinical Assistant Decision Support System (AI-CDSS) for VTE prevention based on the extended Unified Theory of Acceptance and Use of Technology (UTAUT).

Methods

We conducted a cross-sectional survey among healthcare workers in three grade-A tertiary hospitals in Shanxi, China. Statistically, the hypothesized model was evaluated by AMOS structural equation modeling.

Results

510 (72.86%) valid surveys were collected in total. The results showed that performance expectancy (β = 0.45, P < 0.001), effort expectancy (β = 0.21, P < 0.001), and top management support (β = 0.30, P < 0.001) positively influenced healthcare workers' intention. Top management support was an antecedent of performance expectancy (β = 0.41 , P < 0.001), social influence (β = 0.57, P < 0.001), effort expectancy (β = 0.61, P < 0.001), and information quality (β = 0.59, P < 0.001). In addition, Social influence positively influenced performance expectancy (β = 0.52, P < 0.001), and information quality positively influenced system quality (β = 0.65, P < 0.001). Social influence did not influence nurses' behavioral intention (β = 0.06, p = 0.376), but negatively influenced clinicians' behavioral intention in the model (β = -0.19, P < 0.001). System quality positively influenced nurses' behavioral intention; (β = 0.16, P < 0.001), and information quality positively influenced clinicians' behavioral intention (β = 0.15, p = 0.025).

Conclusion

With this model explaining 76.3% variance of the behavioral intention variable, this study could be useful as a reference for hospital administrators to evaluate future developments and facilitate the implementation of AI-CDSS for VTE prevention.

Implementation research logic model in the design and execution of eHealth innovations for maternal and newborn healthcare in Ethiopia

BACKGROUND

The use of eHealth innovations is becoming increasingly important in improving health outcomes, especially for maternal and newborn health. However, planning and executing these innovations can be challenging due to their complex nature. To provide guidance and clarity on implementation approaches, researchers need to use implementation research (IR) tools. We conducted IR to recognize the challenges in implementing eHealth innovations in the context of maternal and newborn healthcare using the implementation research logic model (IRLM). Therefore, this paper aims to describe the practical application of IRLM to design, execute and evaluate eHealth innovations that improve maternal and newborn care in public facilities in Ethiopia.

METHODS

We employed rapid review, formative assessment and process evaluation of an eHealth innovation in selected healthcare facilities serving maternal and newborn care. The eHealth innovation we developed and deployed was named 'ADHERE' (Antenatal Care, ChilDbirtH CarE and Postnatal CaRE), representing the continuum of maternal care. The rapid review was conducted as an initial step using the Consolidated Framework for Implementation Research (CFIR). We employed a mix of data collection methods: interview/discussion, eHealth system or document review and direct observation. Furthermore, we executed various stakeholder engagement activities: two co-creation workshops and on-site iterative discussions. We applied the Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies (FRAME-IS) to capture ongoing implementation learnings.

RESULTS

We developed IRLM of the eHealth innovation implementation for three contexts: urban, peri-urban and remote public healthcare facilities. The model depicted the mechanism of interaction between implementation determinants and implementation strategies to produce the intended implementation outcomes. The IRLM helped to identify more than 35 implementation barriers or facilitators for eHealth interventions and to develop over 17 mitigation strategies for the study contexts. The initial IRLM was refined through ongoing implementation learnings and the mitigation strategies that were executed.

CONCLUSIONS

The IRLM is a comprehensive and effective guiding tool for the development, implementation and evaluation of innovations in various low- and middle-income contexts. Researchers and implementing partners should adapt and use it.

Effect of short message service reminders in improving optimal antenatal care, skilled birth attendance and postnatal care in low-and middle-income countries: a systematic review and meta-analysis

BACKGROUND

Digital health has emerged as a promising solution for enhancing health system in the recent years, showing significant potential in improving service outcomes, particularly in low and middle-income countries where accessing essential health service is challenging. This review aimed to determine the effectiveness of short message services on focused antenatal care, skilled birth attendance, and postnatal care improvement in low and middle-income countries.

METHOD

Electronic databases such as PubMed, EMBASE, Scopus, Cochrane, and Google and Google Scholar were searched. We extracted data of antenatal care visits, skilled birth attendance, and postnatal care visits from RCTs and quasi-experimental studies. The quality of included studies was examined using JBI risk of bias assessment tools. A measure of the random-effects model was used to estimate the pooled effect size expressed as Relative Risk (RR) with a 95%CI. The certainty of the evidence was assessed using Grade pro software.

RESULTS

Twenty-six studies were included in this review. The risk of bias assessment was greater than 50% in included studies. In aggregate, mobile short message service reminders had a significant effect on optimal antenatal care (RR = 1.34, 95% CI: 1.12-1.60), skilled birth attendance (RR = 1.18, 95% CI: 1.05-1.33), and postnatal care (RR = 1.51; 95% CI: 1.34-1.71). There was high heterogeneity for ANC with I2 = 96%; (p < 0.001), skilled birth attendance I2 = 92.6% (p = 0.000), and postnatal care I2 = 78.4% (p < = 0.001).

CONCLUSIONS

Short message service yielded a positive effect in improving antenatal care visit, skilled birth attendance, and postnatal care attendance in low-and middle-income countries. Short message service reminder intervention should be promoted as a tool to improve maternal health service utilization in low and middle-income countries.

Determining the factors affecting implementation of health and safety app towards improvement of safety culture: A study in school of engineering building

The improvement of safety culture in the academic sector is often overlooked, as Occupational Safety and Health (OSH) practices are typically associated with industries. Consequently, research on health and safety in educational centers building is limited. This study aims to bridge this gap by investigating the factors influencing the implementation of a health and safety application in an engineering school building in the Philippines, using the dimensions of safety culture and the UTAUT framework. The research involved designing and executing the health & safety app using the affiliated MS 365 - Microsoft Power Apps, which was tested by 232 engineering students in Metro Manila. The obtained data were then analyzed using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) approach. The results indicated that the users' intention to use and perceived usability were crucial factors influencing their behavior towards the app. Additionally, performance expectancy and social influence affected their behavioral intentions towards the application. Moreover, the app's perceived usability and usage behavior significantly influenced users' overall participation in health and safety activities. This study stands as a unique contribution to the literature on safety culture in the academic sector. The study emphasizes the importance of incorporating technology in health and safety culture on campus, benefiting researchers, academic institutions, industries, and students alike. By integrating technology such as safety training apps, institutions can improve safety performance, empower students with relevant skills, and enhance overall safety culture on campus and in workplaces.

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.

Understanding the predictors of health professionals' intention to use electronic health record system: extend and apply UTAUT3 model

BACKGROUND

The implementation of Electronic Health Record (EHR) systems is a critical challenge, particularly in low-income countries, where behavioral intention plays a crucial role. To address this issue, we conducted a study to extend and apply the Unified Theory of Acceptance and Use of Technology 3 (UTAUT3) model in predicting health professionals' behavioral intention to use EHR systems.

METHODS

A quantitative research approach was employed among 423 health professionals in Southwest Ethiopia. We assessed the validity of the proposed model through measurement and structural model statistics. Analysis was done using SPSS AMOS version 23. Hypotheses were tested using structural equation modeling (SEM) analysis, and mediation and moderation effects were evaluated. The associations between exogenous and endogenous variables were examined using standardized regression coefficients (β), 95% confidence intervals, and p-values, with a significance level of p-value < 0.05.

RESULTS

The proposed model outperformed previous UTAUT models, explaining 84.5% (squared multiple correlations (R2) = 0.845) of the variance in behavioral intention to use EHR systems. Personal innovativeness (β = 0.215, p-value < 0.018), performance expectancy (β = 0.245, p-value < 0.001), and attitude (β = 0.611, p-value < 0.001) showed significant associations to use EHR systems. Mediation analysis revealed that performance expectancy, hedonic motivation, and technology anxiety had significant indirect effects on behavioral intention. Furthermore, moderation analysis indicated that gender moderated the association between social influence, personal innovativeness, and behavioral intention.

CONCLUSION

The extended UTAUT3 model accurately predicts health professionals' intention to use EHR systems and provides a valuable framework for understanding technology acceptance in healthcare. We recommend that digital health implementers and concerned bodies consider the comprehensive range of direct, indirect, and moderating effects. By addressing personal innovativeness, performance expectancy, attitude, hedonic motivation, technology anxiety, and the gender-specific impact of social influence, interventions can effectively enhance behavioral intention toward EHR systems. It is crucial to design gender-specific interventions that address the differences in social influence and personal innovativeness between males and females.

Health professionals' acceptance of mobile-based clinical guideline application in a resource-limited setting: using a modified UTAUT model

INTRODUCTION

Clinical guidelines are crucial for assisting health professionals to make correct clinical decisions. However, manual clinical guidelines are not accessible, and this increases the workload. So, a mobile-based clinical guideline application is needed to provide real-time information access. Hence, this study aimed to assess health professionals' intention to accept mobile-based clinical guideline applications and verify the unified theory of acceptance and technology utilization model.

METHODS

Institutional-based cross-sectional study design was used among 803 study participants. The sample size was determined based on structural equation model parameter estimation criteria with stratified random sampling. Amos version 23 software was used for analysis. Internal consistency of latent variable items, and convergent and divergent validity, were evaluated using composite reliability, AVE, and a cross-loading matrix. Model fitness of the data was assessed based on a set of criteria, and it was achieved. P-value < 0.05 was considered for assessing the formulated hypothesis.

RESULTS

Effort expectancy and social influence had a significant effect on health professionals' attitudes, with path coefficients of (β = 0.61, P-value < 0.01), and (β = 0.510, P-value < 0.01) respectively. Performance expectancy, facilitating condition, and attitude had significant effects on health professionals' acceptance of mobile-based clinical guideline applications with path coefficients of (β = 0.37, P-value < 0.001), (β = 0.44, P-value < 0.001) and (β = 0.57, P-value < 0.05) respectively. Effort expectancy and social influence were mediated by attitude and had a significant partial relationship with health professionals' acceptance of mobile-based clinical guideline application with standardized estimation coefficients of (β = 0.22, P-value = 0.027), and (β = 0.19, P-value = 0.031) respectively. All the latent variables accounted for 57% of health professionals' attitudes, and latent variables with attitudes accounted for 63% of individuals' acceptance of mobile-based clinical guideline applications.

CONCLUSIONS

The unified theory of acceptance and use of the technology model was a good model for assessing individuals' acceptance of mobile-based clinical guidelines applications. So, enhancing health professionals' attitudes, and computer literacy through training are needed. Mobile application development based on user requirements is critical for technology adoption, and people's support is also important for health professionals to accept and use the application.

Intention to use picture archiving and communication system and its predictors among physicians and nurses at specialized teaching hospitals in Amhara region, Northwest Ethiopia

Background

Picture archiving and communication system is an innovation system in the health information that reduces costs, facilitates access to medical image, and improves workflow in radiology department. However, studies indicated that intention and usage of picture archiving and communication system is limited in middle-income and developing countries.

Objective

This study aimed to assess the intention to use picture archiving and communication system and its predictors among physicians and nurses at specialized teaching hospitals in Amhara region, Northwest Ethiopia.

Method

Institution-based cross-sectional study design was conducted from October 11 to November 12, 2023. Proportional allocation and a simple random sampling were used to select participants of the study. A self-administered structured English questionnaire was used, and a 5% pretest was performed. Data were entered into Epi data 4.6 and exported to SPSS 26 and AMOS 23. Descriptive and structural equation modeling analysis was performed. The hypothesis was tested using a path coefficient and a p-value <0.05.

Results

About 54.7% (95%: CI: 50.9-58.4) of the participant intended to use picture archive and communication system with a 90.38% of response rate. Performance expectancy (β = 0.146, p-value <0.05), perceived enjoyment (β = 0.397, p-value <0.001), and computer literacy (β = 0.191, p-value <0.001) had positive influence on intention to use picture archiving and communication system.

Conclusions

Overall, more than half of physicians' and nurses' intention to use picture archiving and communication system were at hopeful stage for future. Performance expectancy, perceived enjoyment and computer literacy had direct positive effect on intention to use picture archiving and communication system among physicians and nurses. The designers, developers, and managers of the picture archiving and communication system should consider these variables. Furthermore, using this system can improve quality of health service through change workflow in to digital image, clinicians evaluate image more quickly and saving resources.

Facing the digital frontier: exploring user acceptance of electronic health records in an urban, rural and remote setting in the Philippines

OBJECTIVES

A thorough understanding of user needs and behavioural intent-to-use underpins the development of a responsive health information system. This study aimed to examine health workers' intent-to-use an electronic health record (EHR) system in an urban, rural and remote setting in the Philippines.

METHODS

Following the Unified Theory of Acceptance and Use of Technology framework, user acceptance and the factors influencing intent-to-use the EHR were examined through a self-administered questionnaire. A total of 128 EHR users, comprising physicians, nurses, midwives, barangay health workers and administrative staff, were surveyed. Median scores for each domain were compared across the sites using the Kruskal-Wallis test. Ridge regression analysis was used to identify factors associated with behavioural intent-to-use.

RESULTS

Over 94% of users across all sites reported their intent-to-use the EHR in the near future. Of the seven predictor variables examined, only self-efficacy was found to be significantly associated with behavioural intent-to-use. Intent-to-use the EHR increased by 31% (p=0.007) for each unit increase in self-efficacy score among participants.

DISCUSSION

Acceptance was high across the three sites, with self-efficacy being a predictor of intent-to-use the technology. This suggests that users are more likely to adopt an EHR if they believe they have the capacity to successfully navigate the technology and perform their designated tasks with it.

CONCLUSION

Co-producing interventions with primary care providers is crucial in sustaining EHR systems. Rather than developing a technology based on the surveillance needs of policymakers, an EHR developed from the grassroots was shown to be well-received by end-users.

Intention to Use an Electronic Community Health Information System Among Health Extension Workers in Rural Northwest Ethiopia: Cross-Sectional Study Using the Unified Theory of Acceptance and Use of Technology 2 Model

BACKGROUND

IT has brought remarkable change in bridging the digital gap in resource-constrained regions and advancing the health care system worldwide. Community-based information systems and mobile apps have been extensively developed and deployed to quantify and support health services delivered by community health workers. The success and failure of a digital health information system depends on whether and how it is used. Ethiopia is scaling up its electronic community health information system (eCHIS) to support the work of health extension workers (HEWs). For successful implementation, more evidence was required about the factors that may affect the willingness of HEWs to use the eCHIS.

OBJECTIVE

This study aimed to assess HEWs' intentions to use the eCHIS for health data management and service provision.

METHODS

A cross-sectional study design was conducted among 456 HEWs in 6 pilot districts of the Central Gondar zone, Northwest Ethiopia. A Unified Theory of Acceptance and Use of Technology model was used to investigate HEWs' intention to use the eCHIS. Data were cleaned, entered into Epi-data (version 4.02; EpiData Association), and exported to SPSS (version 26; IBM Corp) for analysis using the AMOS 23 Structural Equation Model. The statistical significance of dependent and independent variables in the model was reported using a 95% CI with a corresponding P value of <.05.

RESULTS

A total of 456 HEWs participated in the study, with a response rate of 99%. The mean age of the study participants was 28 (SD 4.8) years. Our study revealed that about 179 (39.3%; 95% CI 34.7%-43.9%) participants intended to use the eCHIS for community health data generation, use, and service provision. Effort expectancy (β=0.256; P=.007), self-expectancy (β=0.096; P=.04), social influence (β=0.203; P=.02), and hedonic motivation (β=0.217; P=.03) were significantly associated with HEWs' intention to use the eCHIS.

CONCLUSIONS

HEWs need to be computer literate and understand their role with the eCHIS. Ensuring that the system is easy and enjoyable for them to use is important for implementation and effective health data management.

Ageing well with tech: Exploring the determinants of e-healthcare services adoption in an emerging economy

The adoption of e-healthcare services is critical for improving healthcare accessibility and efficiency, particularly in regions with diverse populations, such as Malaysia. Although e-healthcare services offer numerous advantages, their adoption is considerably low and requires a thorough understanding of the key factors that influence their use. This study investigated the determinants and dynamics of e-healthcare adoption among adults over 40 years by extending the unified theory of acceptance and use of technology. We employed a quantitative research approach, specifically a cross-sectional design. Data were collected from 393 Malaysian respondents through a structured survey questionnaire, using convenience sampling. They were analyzed using partial least-squares-structural equation modeling. The findings revealed that performance expectancy, effort expectancy, social influence, and perceived product value significantly influenced individuals' intentions to use e-healthcare services. Meanwhile, perceived risk had an insignificant negative effect. Facilitating conditions significantly influenced individuals' intentions and actual usage of e-healthcare services. Furthermore, individuals' intentions to use e-healthcare services significantly affected their actual use of these services. Additionally, the intention to use e-healthcare services mediated the relationship between the factors and usage of e-healthcare services, except for perceived risk. Surprisingly, perceived service accuracy had no significant moderating effect on the relationship between individuals' intention to use and their actual use of e-healthcare services. This study offers valuable insights for educators, practitioners, and policymakers, enriching the scholarly discourse in this field. For education, integrating e-healthcare topics into curricula can enhance digital health literacy. In practice, healthcare providers should focus on improving user experience and addressing barriers to technology adoption. For policy making, developing supportive policies, and infrastructure to facilitate e-healthcare adoption is crucial to enhancing public health outcomes.

Technology adoption of electronic medical records in developing economies: A systematic review on physicians' perspective

Electronic Medical Records (EMRs) are a tool that could potentially improve the outcomes of patient care by providing physicians with access to up-to-date and accurate vital patient information. Despite this potential, EMR adoption in developing economies has been dilatory. This systematic review aims to synthesize the related literature on the adoption of EMRs in developing economies, with a focus on the perspective of physicians. With the aim to discern the key factors that impact EMR adoption as perceived by physicians and to offer guidance for future research on filling any gaps identified in the existing literature, this study utilized a systematic literature review by following the PRISMA guidelines. Out of 1160 initial articles, 21 were selected for analysis after eliminating duplicates and non-qualifying articles. Results show that common enablers of EMR adoption from physicians' perspective were identified to be computer literacy, education, voluntariness, and the system functionality including its features and user interface, implying that the provision of proper interventions focusing on the aspects of the health information system has an impact in maximizing the utilization and capabilities of EMRs among healthcare providers. The most prevalent barriers include the lack of training and IT usage experience along with resistance to changes associated with respondents' age and gender, the lack of time for learning complex EMR systems, and costs of the new technology. This indicates that a thorough planning and proper budget allocation is necessary prior to implementing and integrating EMR systems in healthcare institutions. From this synthesis of the common research conclusions, limitations, and recommendations from physicians' perspective, the result of this systematic review is expected to shed light on the optimal technology adoption of EMRs and its contribution to the health care systems of developing economies.

Intention to use patient portal and its predictors among patient with diabetes in Amhara region referral hospitals, Northwest Ethiopia, 2023: UTAUT-2 model

Background

Patient portal technology is increasingly utilized in the health care system for diabetes management as a means of communication and information-sharing tools, and it has the potential to improve access, quality, and outcomes for patients with diabetes. However, its adaptation is very low, and patients' intention toward the patient portal is unknown. This study aims to fill this gap by determining the intention to use the patient portal and its predictors among patients with diabetes in Ethiopia.

Method

An institution-based cross-sectional study was conducted on patients with diabetes from April 3 to May 8 in eight referral hospitals in the Amhara region, Ethiopia 2023. Samples were proportionally allocated for each hospital, and participants were selected by using a systematic random sampling method. The data were collected by using an interviewer-administered questionnaire using the Kobo collection mobile app. Descriptive statistics were performed using SPSS version 26. The degree of association between exogenous and endogenous variables was assessed and validated using structural equation modeling using AMOS version 21.

Result

A total of 1037 (96.2% response rate) patients with diabetes participated in the study. Of them, 407 (39.25%), 95% CI: [36.4-42.2] were found to have an intention to use the patient portal. Digital literacy (β = 0.312, 95% CI: [0.154-0.465], p < .01), performance expectancy (β = 0.303, 95% CI: [0.185-0.420], p < .01), effort expectancy (β = 0.25, 95% CI: [0.131-0.392], p < 0.01) facilitating condition (β = 0.22, 95% CI: [0.081-0.36], p < .01) and habit (β = 0.111, 95% CI: [-0.009 to 0.227], p < .05) were significantly associated with the intention to use patient portals. Effort expectancy and facilitating conditions were positively moderated by gender.

Conclusion

This study found that patient with diabetes' intention to use patient portals was low. To increase patients with diabetes' intention to use the patient portal, interventions in digital literacy, performance expectations, effort expectations, facilitating conditions, and habits are required.

An acceptance analysis of a sexual health education digital tool in resource-poor regions of Kenya: an UTAUT based survey study

BACKGROUND

Unplanned pregnancies and sexually transmitted diseases are a concern in Sub-Saharan Africa, particularly in low-income areas. Access to sexual health information is limited, partly due to the absence of comprehensive sex education in the national school curriculum and social taboos. In response to these challenges, this study introduces a web-based prototype, designed to provide essential sexual health information, targeting 18 to 35-year-old Kenyans, focusing on contraception, menstruation, and female genital mutilation.

METHOD

Aiming to investigate young adults' behavioral intention to use a digital tool for sexuality education, by analyzing factors affecting acceptance and usability in low-income and resource-poor regions in Kenya. To explore the acceptability and use of the developed digital tool, this study used a modified version of the Unified Theory of Acceptance and Use of Technology (UTAUT), complemented by the System Usability Scale (SUS) questionnaire. For statistical analysis, a Structural Equation Model (SEM) including Confirmatory Factor Analysis (CFA) and Linear Regression was used. Regarding the reporting of the E-survey results, the Checklist for Reporting Results of Internet E-surveys (CHERRIES), was considered.

RESULTS

Survey information from 77 persons (69 female, 7 male, 1 diverse) were collected. A modified UTAUT appears as an appropriate model for measuring the constructs and integrating evidence-based approaches to advanced and safe sexual healthcare information. Results from the SEM showed perceived usefulness, attitude towards healthcare integrated evidence technology, and usability as well as having a significant positive impact on the acceptance, the intention to use as well as wellbeing. Having the resources and knowledge necessary for the usage of a digital tool turns out to have a significant negative impact. A SUS score of 67.3 indicates the usability of the tool for sexual health information, assessed as okay.

CONCLUSIONS

The study adopts validated methods to assess the acceptability and usability of a digital sexual health education tool in Kenya. Emphasizing its potential effectiveness and highlighting the influence of cultural and contextual factors on technology adoption.

AI in medical education: medical student perception, curriculum recommendations and design suggestions

Medical AI has transformed modern medicine and created a new environment for future doctors. However, medical education has failed to keep pace with these advances, and it is essential to provide systematic education on medical AI to current medical undergraduate and postgraduate students. To address this issue, our study utilized the Unified Theory of Acceptance and Use of Technology model to identify key factors that influence the acceptance and intention to use medical AI. We collected data from 1,243 undergraduate and postgraduate students from 13 universities and 33 hospitals, and 54.3% reported prior experience using medical AI. Our findings indicated that medical postgraduate students have a higher level of awareness in using medical AI than undergraduate students. The intention to use medical AI is positively associated with factors such as performance expectancy, habit, hedonic motivation, and trust. Therefore, future medical education should prioritize promoting students' performance in training, and courses should be designed to be both easy to learn and engaging, ensuring that students are equipped with the necessary skills to succeed in their future medical careers.

Exploring facilitators and barriers of the sustainable acceptance of e-health system solutions in Ethiopia: A systematic review

BACKGROUND

eHealth is the use of information and communications technologies in support of health and health-related fields, including healthcare services, health surveillance, health literature, and health education knowledge and research, has the potential to improve the delivery and support of healthcare services by promoting information sharing and evidence-based health practice. Acceptance of e-health in Ethiopia using systematic review is uncertain. As a result, this study aimed to assess barriers and facilitators of the sustainable acceptance of e-health system adoption in Ethiopia through a systematic review of the literature.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist was used to conduct this study. Relevant articles have been searched in Google Scholar, Medline, PubMed, Embrace, Web of Science, Scopus, Cochrane Library, and empirical research done in Ethiopia is the main emphasis of the search strategy. The total number of studies that satisfied the criteria for inclusion was ten. In this research, empirical data related to e-health acceptance factors were retrieved, examined, and summarized by the authors.

RESULTS

This systematic review identified a total of 25 predictors that have been found in the ten studies. The identified facilitators were effort expectancy, performance expectancy, facilitating conditions, social influences, attitude, computer literacy, participant age, perceived enjoyment, and educational status, duration of mobile device use, organizational culture, and habit. Moreover, technology anxiety was the most barrier to sustainable acceptance of e-health systems in Ethiopia.

CONCLUSIONS

The most common facilitator identified from the predictors was effort expectancy, which played a major role in the adoption of the e-health system in Ethiopia. Therefore, eHealth implementers and managers in those settings should give users of the system priority in improving the technical infrastructure by regularly providing them with basic facilitating conditions. They should also pay attention to the system they want to implement because doing so will improve the users' perception of the system's value and attitude.

Individual and contextual level enablers and barriers determining electronic community health information system implementation in northwest Ethiopia

BACKGROUND

The government of Ethiopia has envisioned digitalizing primary healthcare units through the electronic community health information system (eCHIS) program as a re-engineering strategy aiming to improve healthcare data quality, use, and service provision. The eCHIS is intended as a community-wide initiative to integrate lower health structure with higher administrative health and service delivery unit with the ultimate goal of improving community health. However, the success or failure of the program depends on the level of identifying enablers and barriers of the implementation. Therefore, this study aimed to explore individual and contextual-level enablers and barriers determining eCHIS implementation.

METHOD

We conducted an exploratory study to determine the enablers and barriers to successfully implementing eCHIS in rural Wogera district, northwest Ethiopia. In-depth interviews and key informant interviews were applied at participants from multiple sites. A thematic content analysis was conducted based on the key themes reported. We applied the five components of consolidated framework for implementation research to interpret the findings.

RESULTS

First, based on the intervention's characteristics, implementers valued the eCHIS program. However, its implementation was impacted by the heavy workload, limited or absent network and electricity. Outer-setting challenges were staff turnover, presence of competing projects, and lack of incentive mechanisms. In terms of the inner setting, lack of institutionalization and ownership were mentioned as barriers to the implementation. Resource allocation, community mobilization, leaders' engagement, and availability of help desk need emphasis for a better achievement. With regard to characteristics of the individuals, limited digital literacy, older age, lack of peer-to-peer support, and limited self-expectancy posed challenges to the implementation. Finally, the importance of mentoring and engaging community and religious leaders, volunteers, having defined plan and regular meetings were identified elements of the implementation process and need emphasis.

CONCLUSION

The findings underlined the potential enablers and barriers of eCHIS program for quality health data generation, use, and service provision and highlighted areas that require emphasis for further scale-up. The success and sustainability of the eCHIS require ongoing government commitment, sufficient resource allocation, institutionalization, capacity building, communication, planning, monitoring, and evaluation.

Assessing Factors That Influence Womenpreneurs' Intention to Use Technology: A Structural Equation Modeling Approach

The growth of financial literacy is significant nowadays. Because of this, more people are becoming increasingly responsible in their financial planning, investments, and living expenses. In developing new technology, it is necessary to know the technological acceptance of the prospective users of the technology itself. This study aims to identify the primary factors influencing the technology acceptance levels of lower-middle socio-economic users for a digital financial literacy application. The proposed model in this research was developed based on UTAUT, TAM, and Usability model, and it consists of six primary constructs: (1) Performance Expectancy; (2) Effort Expectancy; (3) Social Influence; (4) Resources and Cost; (5) Satisfaction; (6) Behavior Intention. All the hypotheses used in this study were statistically measured using SmartPLS tools. This study found that because many lower-middle socio-economic users lack sufficient understanding of technology to properly utilize it, that a digital platform is not the right tool to teach them financial literacy.

Factors affecting wearable ECG device adoption by general practitioners for atrial fibrillation screening: cross-sectional study

Introduction

Atrial fibrillation (AF) is a challenging cardiovascular disease worldwide. Wearable electrocardiograph devices (WEDs) have great potential to improve the detection rate of AF in primary care. However, the factors that influence general practitioners' (GPs) perception and acceptance of WEDs are not well understood. To identify factors that influence the intention of GPs to utilize WEDs in a clinical setting to screen patients for AF.

Method

The research hypotheses and questionnaire items were designed and developed based on the unified theory of acceptance and technology (UTAUT) framework. We used stratified sampling and obtained the data through an online survey. Structural equation modeling was used to analyze the collected data.Results: A total of 1,004 valid questionnaires from GPs across Sichuan province in China were collected. Three factors increased GPs' intention to utilize WEDs to screen patients for AF, including performance expectancy (β = 0.121, p = 0.004), social influence (β = 0.356, p < 0.001), and price perception (β = 0.587, p < 0.001). Perception risk (β = -0.059, p < 0.001) decreased usage intention, while effort expectancy (β = -0.079, p = 0.155) and facilitating conditions (β = -0.014, p = 0.868) did not affect usage intention. Gender (β = -0.022, p = 0.179), age (β = 0.006, p = 0.699), education level (β = -0.22, p = 0.184) and training (β = 0.007, p = 0.69) were not significantly correlated with usage intention, and these four factors had no moderating effect on the path coefficients.

Discussion

GPs' intention to utilize WEDs is affected by performance expectancy, price perception, perception risk and social influence. Researcher should improve the usability and perception of WEDs for screening and carry out studies to provide high-quality evidence for the security and efficacy of wearable devices.

Technology Adoption and Human Resource Management Practices: The Use of Artificial Intelligence for Recruitment in Bangladesh

Artificial intelligence (AI) is now considered indispensable in undertaking operational activities, especially in the area of human resource analytics. However, in practice, the rate of the adoption of such modern algorithms in organisations is still in its early stages. Consequently, the primary objective of this study is to identify the main antecedents of the adoption of AI-based technologies in recruitment, using the lens of the unified theory of acceptance and use of technology (UTAUT) model, alongside perceived credibility and moderating variables, in the context of an emerging nation in South Asia, namely Bangladesh. Data were collected from 283 human resource professionals employed in different manufacturing and service firms in Bangladesh through the administration of a questionnaire, which was analysed by applying PLS-SEM. The outcomes of the study show that all the direct hypothesised relationships were found to be significant, apart from the extended variable of perceived credibility. However, no moderating effect of gender or firm size was found in any of the hypothesised propositions. Finally, policy implications and recommendations for future researchers are proposed.

Promoting Healthcare Workers' Adoption Intention of Artificial-Intelligence-Assisted Diagnosis and Treatment: The Chain Mediation of Social Influence and Human-Computer Trust

Artificial intelligence (AI)-assisted diagnosis and treatment could expand the medical scenarios and augment work efficiency and accuracy. However, factors influencing healthcare workers' adoption intention of AI-assisted diagnosis and treatment are not well-understood. This study conducted a cross-sectional study of 343 dental healthcare workers from tertiary hospitals and secondary hospitals in Anhui Province. The obtained data were analyzed using structural equation modeling. The results showed that performance expectancy and effort expectancy were both positively related to healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Social influence and human-computer trust, respectively, mediated the relationship between expectancy (performance expectancy and effort expectancy) and healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Furthermore, social influence and human-computer trust played a chain mediation role between expectancy and healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Our study provided novel insights into the path mechanism of healthcare workers' adoption intention of AI-assisted diagnosis and treatment.

The Acceptance Behavior of Smart Home Health Care Services in South Korea: An Integrated Model of UTAUT and TTF

With the COVID-19 pandemic, the importance of home health care to manage and monitor one's health status in a home environment became more crucial than ever. This change raised the need for smart home health care services (SHHSs) and their extension to everyday life. However, the factors influencing the acceptance behavior of SHHSs have been inadequately investigated and failed to address why users have the intention to use and adopt the services. This study aimed to analyze the influential factors and measure the behavioral acceptance of SHHSs in South Korea. This study adopted the integrated model of the unified theory of acceptance and use of technology (UTAUT) and task-technology fit (TTF) to understand the behavioral acceptance of SHHSs from users' perceptions and task-technology fit. Multiple-item scales were established based on validated previous measurement scales and adjusted in accordance with SHHS context. Data from 487 valid samples were analyzed statistically, applying partial least square structural equation modeling. The results indicated that the integrated acceptance model explained 55.2% of the variance in behavioral intention, 44.9% of adoption, and 62.5% of the continuous intention to use SHHSs, supporting 11 of the 13 proposed hypotheses. Behavioral intention was positively influenced by users' perceptions on performance expectancy, effort expectancy, social influence, and functional conditions. Task-technology fit significantly influenced performance expectancy and behavioral intention, validating the linkage between the two models. Meanwhile, task characteristics were insignificant to determine task-technology fit, which might stem from complex home health care needs due to the COVID-19 pandemic, but were not sufficiently resolved by current service technologies. The findings implied that the acceptance of SHHSs needs to be evaluated according to both the user perceptions of technologies and the matching fit of task and technology. Theoretically, this study supports the applicability of the integrated model of UTAUT and TTF to the domain of SHHS, and newly proposed the measurement items of TTF reflecting the domain specificity of SHHS, providing empirical evidence during the pandemic era in South Korea. Practically, the results could suggest to the planners and strategists of home health care services how to promote SHHS in one's health management.

The Determinants of User Acceptance of Mobile Medical Platforms: An Investigation Integrating the TPB, TAM, and Patient-Centered Factors

Mobile medical platforms (MMPs) can make medical services more accessible and effective. However, the patient-centered factors that influence patients' acceptance of MMPs are not well understood. Our study examined the factors affecting patients' acceptance of MMPs by integrating the theory of planned behavior (TPB), the technology acceptance model (TAM), and three patient-centered factors (i.e., perceived convenience, perceived credibility, and perceived privacy risk). Three hundred and eighty-nine Chinese respondents were recruited in this study and completed a self-administered online questionnaire that included items adapted from validated measurement scales. The partial least squares structural equation modeling results revealed that perceived privacy risk, perceived credibility, and perceived ease of use directly determined the perceived usefulness of an MMP. Perceived convenience, perceived credibility, and perceived usefulness significantly affected the patients' attitudes toward MMPs. Perceived usefulness, attitude, perceived privacy risk, and perceived behavioral control were important determinants of the patients' behavioral intentions to use MMPs. Behavioral intention and perceived behavioral control significantly influenced perceived effective use. Perceived credibility and perceived ease of use significantly affected perceived convenience. However, social influence had no significant effect on attitude and behavioral intention. The study provides important theoretical and practical implications, which could help practitioners enhance the patients' use of MMPs for their healthcare activities.

Adoption of mobile health services using the unified theory of acceptance and use of technology model: Self-efficacy and privacy concerns

Mobile health (mHealth) services have been widely used in medical services and health management through mobile devices and multiple channels, such as smartphones, wearable equipment, healthcare applications (Apps), and medical platforms. However, the number of the users who are currently receiving the mHealth services is small. In China, more than 70% of internet users have never used mHealth services. Such imbalanced situation could be attributed to users’ traditional concept of medical treatment, psychological factors (such as low self-efficacy) and privacy concerns. The purpose of this study is to explore the direct and indirect effects of mHealth users’ self-efficacy and privacy concerns on their intention to adopt mHealth services, providing guidelines for mHealth service providers to enhance users’ intention of adoption. A questionnaire was designed by the research team and 386 valid responses were collected from domestic participants in China. Based on the unified theory of acceptance and use of technology (UTAUT) model, a research model integrated self-efficacy and privacy concerns was constructed to investigate their effects on users’ intention to adopt mobile mHealth services. The results show that self-efficacy could facilitate users’ intention to adopt mHealth services, and had a significantly positive effect on perceived ubiquity, effort expectancy, performance expectancy and subjective norm. This study verifies the direct and indirect effects of self-efficacy and privacy concerns on users’ intention to adopt mHealth services, providing a different perspective for studying mHealth adoption behavior. The findings could provide guidelines for mHealth service providers to improve their service quality and enhance users’ intention of adoption.

Emerging technologies adoption in healthcare: A SOHI model

The internet and emerging technologies have increased the utilisation of digital platforms. This study aims to draw on performance expectancy, social influence, and satisfaction to investigate a proposed model which is geared toward social media healthcare information (SOHI) adoption. The proposed model uses a structured online questionnaire, and 300 responses were evaluated using partial least squares and structural equation modelling [PLS-SEM]. From the findings, performance expectancy of social media (PESM) and satisfaction with social media (SATSM) were revealed to be significant predictors of behavioural intention towards social media (BISM). Satisfaction with social media (SATSM) had the greatest impact on BISM, accounting for 63.8 per cent of the variance in users' intentions to utilise SOHI. Similarly, PESM and social influence on social media (SISM) had the most predictive influence on SATSM, accounting for 50.5 per cent of the variance in users' social media satisfaction, which led to SOHI adoption. Unlike others, the social influence on social media (SISM) did not have a significant effect on BISM. BISM and satisfaction with social media (SATSM) were significant predictors of SOHI adoption, accounting for 54.5 per cent of the variance in SOHI adoption. The recommendations in this study would help healthcare professionals change their approach to digital healthcare engagement.

Investigating Accessibility of Social Security System (SSS) Mobile Application: A Structural Equation Modeling Approach

Due to the Philippines’ current condition in COVID-19, the Social Security System (SSS) has launched a mobile app as an intervention for walk-in appointments and another convenient way to exchange information. By integrating the extended Technology Acceptance Model (TAM) with the Theory of Planned Behavior (TPB), this study scrutinizes and investigates the various factors influencing the SSS mobile app’s accessibility. An online questionnaire composed of 60 items required at least 200 respondents. The researchers measured twelve latent variables, including social influence, awareness of service, computer self-efficacy, quality of internet connection, perceived ease of use, perceived usefulness, subjective norms, the impression of use, demographic, attitude towards using, behavioral intention to use, and actual use of SSS mobile app. The results of Structural Equation Modeling (SEM) indicated that awareness of service had a substantial direct influence on computer self-efficacy and perceived usefulness. In addition, computer self-efficacy had a substantial direct influence on the quality of internet connection and perceived ease of used, in which this perceived ease of use had a substantial direct influence on perceived usefulness and attitude toward using the mobile application. This study’s findings can be used to provide information on the key factors that have been identified as having a considerable effect on the app’s accessibility and further improving the overall service efficiency of the SSS mobile app. Finally, the study’s model construct will be valuable for researchers and other sectors investigating user–software interaction of applicable government or private service mobile applications.

Evaluation of an Electronic Medical Record Module for Nursing Documentation in Paediatric Palliative Care: Involvement of Nurses with a Think-Aloud Approach

BACKGROUND

Paediatric palliative care (PPC) is a noncurative approach to the care of children and adolescents with life-limiting and life-threatening illnesses. Electronic medical records (EMRs) play an important role in documenting such complex processes. Despite their benefits, they can introduce unintended consequences if future users are not involved in their development.

AIM

The aim of this study was to evaluate the acceptance of a novel module for nursing documentation by nurses working in the context of PPC.

METHODS

An observational study employing concurrent think-aloud and semi-structured qualitative interviews were conducted with 11 nurses working in PPC. Based on the main determinants of the unified theory of acceptance and use of technology (UTAUT), data were analysed using qualitative content analysis.

RESULTS

The main determinants of UTAUT were found to potentially influence acceptance of the novel module. Participants perceived the module to be self-explanatory and intuitive. Some adaptations, such as the reduction of fragmentation in the display, the optimization of confusing mouseover fields, and the use of familiar nursing terminology, are reasonable ways of increasing software adoption.

CONCLUSIONS

After adaptation of the modules based on the results, further evaluation with the participation of future users is required.

The Acceptance and Use of Electronic Medical Records in Developing Countries within the Unified Theory of Acceptance and Use of Technology Framework

BACKGROUND: The Indonesian Ministry of Health requires hospitals to record and report all activities in the Hospital Management Information System (SIMRS). However, the disruptive use of software, hardware, and Brainware has reduced its effective management and usability, which has become a separate workload. Electronic Medical Record (EMR) is one of the important implementations of SIMRS because it relates to the ability to identify information, results, history taking, examinations, and records of all patients. Furthermore, it has become a current global trend for most hospitals and has also been used as a substitute for paper medical records. AIM: This study aims to collect and identify the user characteristic, technology used, and other variables influencing the acceptance and use of information and technology systems based on the unified theory of acceptance and use of technology (UTAUT) model. METHOD: Secondary data were obtained from scientifically published journals online in the form of original articles that are accessed in full text with the help of search engines such as Springer link, Proquest, PubMed, and Prospero. RESULT: It was found that the most dominant technology system in hospitals outside the use of HIS, Electronic Health Record (EHR), physician assistants, E-Prescribing, Telemedicine, extended producer responsibility, and Technology solution for tuberculosis was EMR. It had the largest influence variable in several studies based on the UTAUT model. The most dominant characteristics of users were women between the ages of 20 and 30 years with 0 and 5 years working experience, and also 60% were nurses. The result also showed that 17 other variables had influenced the use of information and technology systems in the UTAUT model. Conclusion: Literature study provides evidence that acceptance and use of health information technology systems, especially RME in hospitals influenced by the main variable UTAUT. Variables related to technical aspects, behavior, and user characteristics as new endogenous and new exogenous mechanisms. Management of health service providers in increasing acceptance and use of EMR needs to pay attention to the availability of infrastructure, user factors are also an important concern in helping to deal with problems in developing countries.

Healthcare providers' readiness for electronic health record adoption: a cross-sectional study during pre-implementation phase

BACKGROUND

The adoption of an electronic health record (EHR) in the healthcare system has the potential to make healthcare service delivery effective and efficient by providing accurate, up-to-date, and complete information. Despite its great importance, the adoptions of EHR in low-income country settings, like Ethiopia, were lagging and increasingly failed. Assessing the readiness of stakeholders before the actual adoption of EHR is considered the prominent solution to tackle the problem. However, little is known about healthcare providers' EHR readiness in this study setting. Accordingly, this research was conducted aiming at examining healthcare providers' readiness for EHR adoption and associated factors in southwestern Ethiopia.

METHODS

An institutional-based cross-sectional study was conducted from September 1 to October 30, 2021. A total of 423 healthcare providers working in public hospitals were selected using a simple random sampling technique. Multivariable logistic regression was fitted to identify determinant factors of overall healthcare providers' readiness after the other covariates were controlled.

RESULT

In this study, the overall good readiness level of EHR adoption was 52.8% (n = 204) [95% CI of 47.9% to 56.6%]. Age, computer literacy, computer access at health facilities, attitude towards EHRs, awareness about EHRs, perceived benefit, and perceived technology self-efficacy were significantly associated with the overall health care providers' readiness for the adoption of EHR using a cut point of P-value less than 0.05.

CONCLUSION

Around half of the respondents had a good level of overall healthcare providers' readiness for the adoption of EHR which was considered inadequate. This finding implied that a huge effort is required to improve readiness before the actual implementation of EHRs. The finding implied that younger-aged groups were more ready for such technology which in turn implied; the older one needs more concern. Enhancing computer literacy, confidence building to raise self-efficacy of such technology, addressing the issue of computer availability at health facilities, building a positive attitude, awareness campaign of EHR, and recognizing the usefulness of such systems were the necessary measures to improve EHR readiness in this setting. Additionally, further studies are recommended to encompass all types of EHR readiness such as organizational readiness, technology readiness, societal readiness, and so on. Additionally, exploring the healthcare provider opinion with qualitative study and extending the proposed study to other implementation settings are recommended to be addressed by future works.

Participatory Design of a Medication Module in an Electronic Medical Record for Paediatric Palliative Care: A Think-Aloud Approach with Nurses and Physicians

BACKGROUND

Electronic medical records (EMRs) play a key role in improving documentation and quality of care in paediatric palliative care (PPC). Inadequate EMR design can cause incorrect prescription and administration of medications. Due to the fact of complex diseases and the resulting high level of medical complexity, patients in PPC are vulnerable to medication errors. Consequently, involving users in the development process is important. Therefore, the aim of this study was to evaluate the acceptance of a medication module from the perspective of potential users in PPC and to involve them in the development process.

METHODS

A qualitative observational study was conducted with 10 nurses and four physicians using a concurrent think-aloud protocol and semi-structured qualitative interviews. A qualitative content analysis was applied based on a unified theory of acceptance and use of technology.

RESULTS

Requirements from the user's perspective could be identified as possible influences on acceptance and actual use. Requirements were grouped into the categories "performance expectancies" and "effort expectancies".

CONCLUSIONS

The results serve as a basis for further development. Attention should be given to the reduction of display fragmentation, as it decreases cognitive load. Further approaches to evaluation should be taken.

Human Resource Professionals' Intention to Use and Actual Use of Human Resource Information Systems

Human resource information systems (HRISs) are widely used and have a strategic impact on organizations. The fundamental objective of this paper is to reveal the predominant antecedents affecting their adoption and implementation by replicating the unified theory of acceptance and use of technology (UTAUT) model from a South Asian emergent country perspective. The study collected data from human resource professionals employed in manufacturing and service companies located in Bangladesh, which were analyzed by employing partial least squares-based structural equation modeling software. It was revealed that performance expectancy, social pressure, and facilitation conditions significantly influence the intention to use and the actual use of HRIS, but that user’s effort expectancy had no significant impact. The study contributes by enriching the previous findings and validating the results based on relevant literature. Furthermore, managerial implications, the limitations of the study and suggested future study directions are presented.

Radiation Oncologists' Perceptions of Adopting an Artificial Intelligence-Assisted Contouring Technology: Model Development and Questionnaire Study

Background

An artificial intelligence (AI)–assisted contouring system benefits radiation oncologists by saving time and improving treatment accuracy. Yet, there is much hope and fear surrounding such technologies, and this fear can manifest as resistance from health care professionals, which can lead to the failure of AI projects.

Objective

The objective of this study was to develop and test a model for investigating the factors that drive radiation oncologists’ acceptance of AI contouring technology in a Chinese context.

Methods

A model of AI-assisted contouring technology acceptance was developed based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model by adding the variables of perceived risk and resistance that were proposed in this study. The model included 8 constructs with 29 questionnaire items. A total of 307 respondents completed the questionnaires. Structural equation modeling was conducted to evaluate the model’s path effects, significance, and fitness.

Results

The overall fitness indices for the model were evaluated and showed that the model was a good fit to the data. Behavioral intention was significantly affected by performance expectancy (β=.155; P=.01), social influence (β=.365; P<.001), and facilitating conditions (β=.459; P<.001). Effort expectancy (β=.055; P=.45), perceived risk (β=−.048; P=.35), and resistance bias (β=−.020; P=.63) did not significantly affect behavioral intention.

Conclusions

The physicians’ overall perceptions of an AI-assisted technology for radiation contouring were high. Technology resistance among Chinese radiation oncologists was low and not related to behavioral intention. Not all of the factors in the Venkatesh UTAUT model applied to AI technology adoption among physicians in a Chinese context.

Modeling the Factors that Influence Ghanaian Entrepreneurs to Adopt e-Commerce

This study investigated the factors that influence Ghanaian entrepreneurs to adopt e-commerce. Cross-sectional data was gathered from 520 entrepreneurs in the most populous and industrious regions in Ghana. The unified theory of acceptance and use of technology (UTAUT) was employed to effectively understand the unexplored phenomenon of e-commerce adoption among Ghanaian entrepreneurs. Partial Least Square-Structural Equation Modeling (PLS-SEM) was used to test the hypothesized relationships. The findings indicate that performance expectancy, effort expectancy, and social influence (SI) positively and significantly influenced the behavioral intention (BI) to adopt e-commerce. Facilitating conditions (FC) and BI had a significant positive relationship with the adoption of e-commerce.

Do We Need Trust Transfer Mechanisms? An M-Commerce Adoption Perspective

This study aimed to provide a comprehensive analysis of the factors that determine and shape consumers’ behavioral intention to adopt mobile commerce (m-commerce). By integrating the core constructs from the Unified Theory of Acceptance and Use of Technology (UTAUT), together with the trust-building mechanisms, this study explored the importance of the institutional mechanisms and their moderating effects between trust in the vendors and intention to adopt m-commerce. Traditionally, the effects of institutional mechanisms on trust and adoption intention have been considered separately in different study contexts. The purpose of this study was to extend the literature by simultaneously exploring two institutional mechanisms that are conceptually highly similar to each other, namely, structural assurance (SA) and perceived effectiveness of e-commerce institutional mechanisms (PEEIM). A self-administered survey was used to collect data, which were analyzed using partial least squares structural equation modelling (PLS-SEM). The results revealed that most of the constructs examined have significant relationships with the intention to adopt m-commerce. Additionally, PEEIM exhibits a significant moderating effect but SA does not. This study delineates how trust-building mechanisms play important roles in increasing consumers’ confidence in order to promote m-commerce adoption.

Acceptance of protection technology in a time of fear: the case of Covid-19 exposure detection apps

Purpose

This study explores the acceptance of protection technology, namely, exposure detection apps, in the context of the Covid-19 pandemic. Unlike other situations, the context of the pandemic is characterized by large levels of threat and fear which largely affect the human decision-making process. To identify such characteristics, this study investigates the acceptance of exposure detection apps from the perspective of protection motivation theory (PMT). It examines how the perceived risk of Covid-19, perceived fear of Covid-19, self-efficacy, response efficacy and protection motivation interact to predict the acceptance of exposure detection apps.

Design/methodology/approach

Data were collected from 306 Jordanian participants, and structural equation modelling was used for data analysis.

Findings

The results reveal that acceptance of these apps is triggered by the perceived risk of Covid-19, which increases the experienced level of fear. The latter then initiates a compelling desire or motivation to protect oneself by using the recommended adaptive response (exposure detection app). The results show that an increased level of self-efficacy and perceived efficacy of exposure detection apps also contribute to the development of protection motivation and later the intent to use exposure detection apps.

Originality/value

This study contributes to the technology acceptance domain by developing a context-driven model of the key characteristics of pandemics that lead to different patterns of technology acceptance. The key components in designing effective marketing campaigns to prompt the use of exposures detection apps are discussed.

Acceptance and usage of mHealth technologies amid COVID-19 pandemic in a developing country: the UTAUT combined with situational constraint and health consciousness

Purpose

The COVID-19 pandemic has created a devastating effect on public health. As “social distance” is a highly effective preventive measure of this pandemic, close contact between a patient and physician is strongly discouraged where possible. Consequently, mobile health (mHealth) technology is taking its momentum to fulfil this gap. The purpose of this study is, therefore, to empirically investigate the moderating as well as the direct role of situational constraint and health consciousness in the unified theory of acceptance and use of technology (UTAUT) constructs to understand the adoption and use behavior of mHealth care services amid pandemic.

Design/methodology/approach

Data were collected from existing mHealth users using an online survey questionnaire in Bangladesh. SmartPLS 3.0 and SPSS 23.0 were used for partial least squares-structural equation modeling.

Findings

Situational constraint and health consciousness both have strong direct positive effects on both behavioral intention (in all models) and use behavior (in Models 2 and 3). Further, this study revealed that effort expectancy remains insignificant in both direct and interaction effects whereas social influence becomes insignificant in interaction effects from direct significant effect (Models 1 and 2). Besides, the study reported that the relationship between behavioral intention and use behavior is moderated by situational constraint.

Originality/value

To the best of the authors’ knowledge, this study is the first in terms of mHealth empirical investigation considering the current pandemic situation. The incorporation of the situational constraint and health consciousness into the UTAUT model provides a holistic framework to understand the influence of the adoption and use behavior of mHealth amid pandemic.

Healthcare providers' acceptance of telemedicine and preference of modalities during COVID-19 pandemics in a low-resource setting: An extended UTAUT model

Background

In almost all lower and lower middle-income countries, the healthcare system is structured in the customary model of in-person or face to face model of care. With the current global COVID-19 pandemics, the usual health care service has been significantly altered in many aspects. Given the fragile health system and high number of immunocompromised populations in lower and lower-middle income countries, the economic impacts of COVID-19 are anticipated to be worse. In such scenarios, technological solutions like, Telemedicine which is defined as the delivery of healthcare service remotely using telecommunication technologies for exchange of medical information, diagnosis, consultation and treatment is critical. The aim of this study was to assess healthcare providers’ acceptance and preferred modality of telemedicine and factors thereof among health professionals working in Ethiopia.

Methods

A multi-centric online survey was conducted via social media platforms such as telegram channels, Facebook groups/pages and email during Jul 1- Sep 21, 2020. The questionnaire was adopted from previously validated model in low income setting. Internal consistency of items was assessed using Cronbach alpha (α), composite reliability (CR) and average variance extracted (AVE) to evaluate both discriminant and convergent validity of constructs. The extent of relationship among variables were evaluated by Structural equation modeling (SEM) using SPSS Amos version 23.

Results

From the expected 423 responses, 319 (75.4%) participants responded to the survey questionnaire during the data collection period. The majority of participants were male (78.1%), age <30 (76.8%) and had less than five years of work experience (78.1%). The structural model result confirmed the hypothesis “self-efficacy has a significant positive effect on effort expectancy” with a standardized coefficient estimate (β) of 0.76 and p-value <0.001. The result also indicated that self-efficacy, effort expectancy, performance expectancy, facilitating conditions and social influence have a significant direct effect on user’s attitude toward using telemedicine. User’s behavioral intention to use telemedicine was also influenced by effort expectancy and attitude. The model also ruled out that performance expectancy, facilitating conditions and social influence does not directly influence user’s intention to use telemedicine. The squared multiple correlations (r²) value indicated that 57.1% of the variance in attitude toward using telemedicine and 63.6% of the variance in behavioral intention to use telemedicine is explained by the current structural model.

Conclusion

This study found that effort expectancy and attitude were significantly predictors of healthcare professionals’ acceptance of telemedicine. Attitude toward using telemedicine systems was also highly influenced by performance expectancy, self-efficacy and facilitating conditions. effort expectancy and attitude were also significant mediators in predicting users’ acceptance of telemedicine. In addition, mHealth approach was the most preferred modality of telemedicine and this opens an opportunity to integrate telemedicine systems in the health system during and post pandemic health services in low-income countries.

Factors Affecting the Acceptance of Mobile Health by Medical Sciences Students: A Cross-Sectional Study

Background:

The use of mobile health has a pivotal role in the prevention and treatment of many diseases. This study aimed at determining the affecting factors in acceptance of mobile health by using a modified acceptance model, among medical sciences students in the south-west of Iran.

Materials and Methods:

This cross-sectional, analytical study was conducted in 2017. The research population included all the students of Lorestan University of Medical Sciences (LUMS). The 352 of students selected as the samples of study through a stratified sampling method. Data gathering was done through a valid and reliable questionnaire. The data was analyzed using Linear Structural Relations (LISREL) and Statistical Package for the Social Sciences (SPSS) software.

Results:

The findings showed that perceived usefulness (t_{7, 38}= 2.16, p = 0.03), performance expectancy (t_{7, 70}= 3.18, p = 0.01), facilitating conditions (t_{10, 61}= 4.17, p < 0.001), and attitude to use (t_{7, 14}= 5.49, p < 0.001) were effective in the behavior intention of mobile health. Moreover, the results showed that the behavior intention of mobile health applications (t_{10, 77}= 8.10, p < 0.001) is effective on its user behavior.

Conclusions:

The results of our study showed that perceived usefulness, performance expectancy, facilitating conditions, and attitude to use of technology were the affecting factors in the acceptance of mobile health by the students. It is suggested that the policymakers and authorities comprehensively consider these important factors when introducing new technologies.

Factors That Influence Use of a Patient Portal by Health Professionals

Patient portals are websites or apps that provide patients with tools to manage healthcare appointments, access their health records, and communicate with clinicians. Patient portals have been demonstrated to be beneficial for improving communication between patients/carers and their healthcare team in a range of health settings. However, there is limited research on the barriers and enablers for implementing patient portals from the perspective of health professionals and healthcare teams, particularly in a paediatric setting. This study aimed to understand healthcare teams’ experiences of using a patient portal and, using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, explore the barriers and enablers to ongoing use. Participants were 11 health professionals participating in the pilot of a patient portal for patients/carers in paediatric care. Data were collected using semi-structured interviews. Analysis of the interview data identified nine themes about implementing a patient portal in paediatric care, all of which aligned with the four constructs of the UTAUT. This study identified that barriers and enablers of the uptake of a patient portal by health professionals in a paediatric context aligned with the UTAUT framework. Value for the patient, improved workflow, and adequate technical and implementation support were highlighted by participants.

Mediating effect of behavioural intention on podcast acceptance

This research contributes to knowledge in mediating effect of lecturers' behavioural intention towards the acceptance of podcasts technology in universities. A cross-sectional quantitative research design was involved in this study. Also, a total of eight hundred and twenty-nine (829) lecturers participated in this research from three different south-west Nigeria Federal universities. The research instrument was titled lecturer's acceptance questionnaire (LAQ) with a calculated Cronbach's alpha of .919, which confirmed the instrument validity. The gathered data was analysed by using both descriptive and inferential statistics. The formulated hypothesis was tested at .05 level of significance. The result from descriptive analysis of data suggested that behavioural intention was at a low level among lecturers and the results of hypothesis testing revealed the effect of behavioural intention as partial mediator of podcast acceptance. Based on these findings relevant conclusions and recommendations were suggested in this research.

Intention to use electronic medical record and its predictors among health care providers at referral hospitals, north-West Ethiopia, 2019: using unified theory of acceptance and use technology 2(UTAUT2) model

BACKGROUND

Electronic Medical Records (EMRs) are systems to store patient information like medical histories, test results, and medications electronically. It helps to give quality service by improving data handling and communication in healthcare setting. EMR implementation in developing countries is increasing exponentially. But, only few of them are successfully implemented. Intention to use EMRs by health care provider is crucial for successful implementation and adoption of EMRs. However, intention of health care providers to use EMR in Ethiopia is unknown.

OBJECTIVE

The aim of this study was to assess health care provider's intention to use and its predictors towards Electronic Medical Record systems at three referral hospitals in north-west, Ethiopia, 2019.

METHODS

Institutional based cross-sectional explanatory study design was conducted from March to September among 420 health care providers working at three referral hospitals in north-west Ethiopia. Data were analyzed using structural equation model (SEM). Simple and multiple SEM were used to assess the determinants of health care providers intention to use EMRs. Critical ratio and standardized coefficients were used to measure the association of dependent and independent variables, 95% confidence intervals and P-value were calculated to evaluate statistical significance. Qualitative data was analyzed using thematic analysis.

RESULT

The mean age of the study subjects was 32.4 years ±8.3 SD. More than two-third 293(69.8%) of the participants were male. Among 420 health care providers, only 167 (39.8%) were scored above the mean of intention to use EMRs. Factors positively associated with intention to use EMRs were performance expectancy (β = 0.39, p < 0.001), effort expectancy (β = 0.24,p < 0.001),social influence (β = 0.18,p < 0.001),facilitating condition (β = 0.23,p < 0.001), and computer literacy (β = 0.08,p < 0.001). Performance expectancy was highly associated with intention to use EMRs.

CONCLUSION

Generally, about 40 % of health care providers were scored above the mean of intention to use EMRs. Performance expectancy played a major role in determining health care providers' intention to use EMRs. The intention of health care providers to use EMRs was attributed by social influence, facilitating condition in the organization, effort expectancy, performance expectancy and computer literacy. Therefore, identifying necessary prerequisites before the actual implementation of EMRs will help to improve the implementation status.

Validation of the Ethiopian Version of eHealth Literacy Scale (ET-eHEALS) in a Population with Chronic Disease

Background

Although the measurement scale developed by Norman and Skinner is the widely used scale to assess consumers’ eHealth literacy, translating and validating the scale for the language of the target population under consideration is necessary. Amharic is the official national language of Ethiopia, with 29.3% of native speakers.

Methods

The total sample size calculated was 187 with 6% non-response rate. The internal consistency of the ET-eHEALS was measured using Cronbach’s alpha coefficient. Test–retest reliability was assessed by re-administering the ET-eHEALS questionnaire to 74 patients which is 40% of the total sample size. Construct validity was evaluated using exploratory factor analysis. The Kaiser–Meyer–Olkin (KMO) statistic and Bartlett’s test of sphericity were used to check the suitability of performing the factor analysis.

Results

Of the respondents, 63.1% (n=118) were males and 55.1% (n=103) were aged between 18 and 35 years, with 57.2% (n=107) of the participants being educated to high school diploma level or higher. Cronbach’s alpha coefficient for the translated ET-eHEALS total score was 0.94. Test–retest reliability of ET-eHEALS total score was acceptable for both agreements and consistent with ICC (interclass correlation coefficient) of 0.92. The KMO ratio of sampling appropriateness was acceptable (0.91), and Bartlett’s test of sphericity was significant with p < 0.001. The EFA (exploratory factor analysis) extracted two factors based on an extraction principle of a minimum eigenvalue of one. The extracted factor explained 80.2% of the common variance which is 51.8% for factor 1 and 28.4% for factor 2. Except for item, item fit for both infit and outfit mean squares were within the adequate range (0.5–1.5).

Conclusion

This study depicted that ET-eHEALS is a consistent and valid instrument to evaluate Amharic-speaking chronic patients’ eHealth literacy level. Since there is no prior validation of eHEALS in low-income country, this finding may indicate important directions for further improvement in eHEALS item performance in resource-limited settings.

Understanding consumer acceptance of healthcare wearable devices: An integrated model of UTAUT and TTF

BACKGROUND

Healthcare wearable devices (HWDs) enable continuous monitoring of consumers' health signals and have great potential to improve the efficiency and quality of healthcare. However, factors influencing consumer acceptance of HWDs are not well understood. Moreover, extant studies seem to fail to consider whether an HWD has appropriate functions to fit the requirements of consumers' healthcare activities.

OBJECTIVES

The objective of this study was to develop and empirically test a model by integrating the Unified Theory of Acceptance and Usage of Technology (UTAUT) and Task-Technology Fit (TTF) models to understand how consumers accept HWDs.

METHODS

A self-administered questionnaire was designed based on validated measurement scales. Data from 406 valid samples were analyzed using partial least squares structural equation modeling.

RESULTS

The results indicated that performance expectancy, effort expectancy, facilitating conditions, social influence, and task-technology fit positively affected consumers' behavioral intention to use HWDs, and together accounted for 68.0 % of its variance. Both task and technology characteristics were significant determinants of task-technology fit and exerted impacts on behavioral intention through the mediating roles of task-technology fit and effort expectancy.

CONCLUSIONS

The key findings showed that consumer acceptance of HWDs was affected by both users' perceptions (i.e., performance expectancy, effort expectancy, social influence and facilitating conditions) and the task-technology fit. The theoretical and practical implications and contributions were provided for future researchers and practitioners to increase consumers' use of HWDs in their healthcare activities.

A meta-analysis based modified unified theory of acceptance and use of technology (meta-UTAUT): a review of emerging literature

Over the past more than four decades, several theoretical models have been developed to understand the acceptance and use of information systems. Realising the dilemma in selecting the appropriate theoretical model to assess the acceptance and use of technology and considering the pattern of using the Unified Theory of Acceptance and Use of Technology (UTAUT), a modified version (meta-UTAUT) has been developed based on the synthesis of results from 162 existing studies. The aim of this article is to review the emerging literature on meta-UTAUT and offer some future research recommendations. The analysis suggests that studies have started citing the relationships suggested by meta-UTAUT and researchers have reviewed it alongside other alternative models while analysing acceptance and use of technology.