The Mediating Influence of the Unified Theory of Acceptance and Use of Technology on the Relationship Between Internal Health Locus of Control and Mobile Health Adoption: Cross-sectional Study

Nurses' acceptance of nursing information systems: A multi-center cross-sectional study in China

BACKGROUND

In China, nursing information systems (NIS) implementation can face numerous barriers to acceptance, including the attitudes of potential users. However, few studies have evaluated this acceptance.

OBJECTIVE

The aim of this study was to explain the acceptance of NIS utilizing a survey based on unified theory of acceptance and use of technology.

METHODS

A multi-center cross-sectional study utilizing an online survey was conducted. SPSS AMOS was used to conduct a structural equation modelling analysis. This research followed the STROBE Checklist.

RESULTS

A total of 3973 Nurses participated in the study between January 2023 and March 2023. The acceptance of NIS among nurses was overall moderate to high. The proposed model has been rigorously tested and validated using empirical data, ensuring its credibility and dependability. Performance expectancy (PE), social influence (SI), and attitude significantly and positively affected intentions to use NIS. Effort expectancy (EE) did not show any significant effects in the sample. Facilitating conditions (FCs) was found to have a negative relationship with the intention to use NIS. There was a statistically significant difference BI between the different age groups, working years, and computer training experience. The model demonstrates a good fit with the observed data.

CONCLUSIONS

This study identified PE, SI, and attitude as facilitators of nurses' intentions to use NIS. The findings about EE indicates that the ease of using NIS does not seem to be a concern among nurses. Moreover, high FC might be perceived as indicative of a complex system or extensive usage, that can lead to increased workload and reduced behavioural intention (BI). The significant differences in BI among various demographic groups highlight the need for more studies understanding the preferences and barriers faced by different, levels of experience and training backgrounds.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Factors Influencing the Behavioral Intentions and Use Behaviors of Telemedicine in Patients With Diabetes: Web-Based Survey Study

BACKGROUND

Telemedicine has great potential for diabetes management. The COVID-19 pandemic has boosted the development of telemedicine. However, the factors influencing the behavioral intentions to use and use behaviors of telemedicine in patients with diabetes in China are not clear.

OBJECTIVE

We aimed to understand the determinants of behavioral intention to use telemedicine based on an extended Unified Theory of Acceptance and Use of Technology model and to identify demographic factors associated with telemedicine use in patients with diabetes in China.

METHODS

Patients with diabetes who are aged ≥18 years were surveyed from February 1 to February 7, 2023. We distributed the survey link in 3 WeChat groups including a total of 988 patients with diabetes from the outpatient department or patients discharged from Changsha Central Hospital. Structural equation modeling was used to understand the determinants of behavioral intention. A multivariate logistic regression analysis was used to identify the demographic factors associated with telemedicine use.

RESULTS

In total, 514 questionnaires were collected. Of the respondents, 186 (36.2%) were diagnosed with COVID-19. The measurement model showed acceptable reliability, convergent validity, discriminant validity, and data fit indices. The model explained 63.8% of the variance in behavioral intention. Social influence, performance expectancy, and facilitating conditions positively influenced behavioral intention (β=.463, P<.001; β=.153, P=.02; and β=.257, P=.004, respectively). Perceived susceptibility, perceived severity, and effort expectancy had no significant impact on behavioral intention (all P>.05). The overall use of telemedicine was 20.6% (104/514). After adjusting for the behavioral intention score, the multivariate regression analysis showed that age, education, and family income were associated with telemedicine use. Telemedicine use was higher in the 40 to 59 years and 18 to 39 years age groups than in the ≥60 years age group (odds ratio [OR] 4.35, 95% CI 1.84-10.29, P=.001; OR 9.20, 95% CI 3.40-24.88, P<.001, respectively). Telemedicine use was higher in the senior high school and the university and more groups than in junior high school education and less group (OR 2.45, 95% CI 1.05-5.73, P=.04; OR 2.63, 95% CI 1.11-6.23, P=.03, respectively). Patients with a higher family income used telemedicine more often than the patients who had an annual family income ≤¥10,000 (CNY ¥1=US $0.1398; ¥10,000-¥50,000 group: OR 3.90, 95% CI 1.21-12.51, P=.02; ¥50,000-¥100,000 group: OR 3.91, 95% CI 1.19-12.79, P=.02; >¥100,000 group: OR 4.63, 95% CI 1.41-15.27, P=.01).

CONCLUSIONS

Social influence, performance expectancy, and facilitating conditions positively affected the behavioral intention of patients with diabetes to use telemedicine. Young patients, highly educated patients, and patients with high family income use telemedicine more often. Promoting behavioral intention and paying special attention to the needs of older adult patients, patients with low income, and patients with low levels of education are needed to encourage telemedicine use.

Mobile Health Fitness Interventions: Impact of Features on Routine Use and Data Sharing Acceptability

Background

Mobile health (mHealth) interventions are increasingly being used for cardiovascular research and physical activity promotion.

Objectives

As a result, the authors aimed to evaluate which features facilitate and impede routine engagement with mobile fitness applications.

Methods

We distributed a pan-Canadian online questionnaire via the behavioral research platform Prolific.co to evaluate what features are associated with the use and routine engagement (ie, daily or weekly use) of mHealth fitness applications and attitudes about data sharing. Binary logistic regression was used to quantify the association between these endpoints and exploratory factors such as the perceived utility of various mHealth application features.

Results

The survey received 694 responses. Most people were women (62%), the median age was 28 years (range: 18-78 years), and most people reported current use of an mHealth fitness application (48%). The perceived importance of personal health (OR: 2.40; 95% CI: 1.34-4.50) was the factor most associated with the current use of an mHealth fitness application. The feature most associated with routine engagement was the ability to track progress toward a goal (OR: 5.10; 95% CI: 2.73-9.61) while the most significant barrier was the absence of goal customization features (OR: 0.44; 95% CI: 0.25-0.81). The acceptance of sharing health data for research was high (56%), and privacy concerns did not significantly affect routine engagement (OR: 0.81; 95% CI: 0.40-1.77). Results were consistent across race and gender.

Conclusions

mHealth interventions have the potential to be scaled across populations. Optimizing applications to improve self-monitoring and personalization could increase routine engagement and, thus, user retention and intervention effectiveness.

The behavioral intention to adopt mobile health services: The moderating impact of mobile self-efficacy

This study explored the moderating impact of mobile self-efficacy on the adoption of mobile health services. The UTAUT was used as the theoretical foundation for this study. The results have indicated that mobile self-efficacy was significant in moderating the impact of both performance expectancy (β = -0.005, p < 0.05) and effort expectancy (β = -010, p < 0.05) on the adoption of mobile health services. In addition, it was revealed to our surprise that both performance (β = 0.521, t = 9.311, p > 0.05) and effort expectancy (β = 0.406, t = 7.577, p > 0.05) do not determine the behavioral intention to use mobile health services. Effort expectancy and behavioral intention to use were also, respectively, not significant in influencing performance expectancy (β = 0.702, t = 12.601, p > 0.05) and intention to recommend the adoption of mobile health services (β = 0.866, t = 13.814, p > 0.05). Mobile self-efficacy, however, was found to significantly predict the citizen's intention to recommend the adoption of mobile health services (β = 0.139, t = 2.548, p < 0.05). The implications of these findings on mobile health are discussed.