Viana Pereira Filipe, Tavares Jorge, Oliveira Tiago
NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa, Campus de Campolide, 1070-312 Lisboa, Portugal.
Internet Interv. 2023 Mar;31:100602. doi: 10.1016/j.invent.2023.100602. Epub 2023 Jan 20.
Video consultations have the potential to play a significant role for the future of healthcare by solving some of the imminently arising healthcare challenges, as pointed by the European Commission in Europe and the National Academy of Medicine in the United States of America. This technology can improve quality, efficiency, and enhance access to healthcare.
The aim of this study is to explore and understand individual video consultations acceptance drivers.
An extended technology acceptance model was created based on the diffusion of innovation theory (DOI), unified theory of acceptance and use of technology (UTAUT), health belief model (HBM), and concerns for information privacy framework (CFIP). 346 valid responses were collected through an online questionnaire, and the partial least squares (PLS) modeling approach was used to test the model.
The model explained 77.6 % (R2) of the variance on intention to use, and 71.4 % (R2) of the variance in attitude. The predictors of intention to use are attitude (beta = 0.504, -value<0.001), performance expectancy (beta = 0.196, -value = 0.002), and COVID-19 (beta = 0.151, -value<0.001). The predictors of attitude are performance expectancy (beta = 0.643, p-value>0.001), effort expectancy (beta = 0.138, p-value = 0.001), and COVID-19 (beta = 0.170, p-value<0.001).
This research model highlights the importance of creating extended acceptance models to capture the specificities of each technology in healthcare. The model created helps to understand the most important drivers of video consultation acceptance, highlighting the importance of the COVID-19 pandemic and perceived health risks.
正如欧洲委员会在欧洲以及美国国家医学院所指出的，视频会诊有潜力通过解决一些迫在眉睫的医疗保健挑战，在医疗保健的未来发挥重要作用。这项技术可以提高医疗质量、效率，并增加获得医疗保健的机会。
本研究的目的是探索和理解个人对视频会诊的接受驱动因素。
基于创新扩散理论（DOI）、技术接受与使用统一理论（UTAUT）、健康信念模型（HBM）和信息隐私关注框架（CFIP）创建了一个扩展的技术接受模型。通过在线问卷收集了346份有效回复，并使用偏最小二乘法（PLS）建模方法对模型进行了测试。
该模型解释了使用意愿方差的77.6%（R2）和态度方差的71.4%（R2）。使用意愿的预测因素是态度（β = 0.504，p值<0.001）、绩效期望（β = 0.196，p值 = 0.002）和新冠疫情（β = 0.151，p值<0.001）。态度的预测因素是绩效期望（β = 0.643，p值>0.001）、努力期望（β = 0.138，p值 = 0.001）和新冠疫情（β = 0.170，p值<0.001）。
本研究模型强调了创建扩展接受模型以捕捉医疗保健中每种技术特殊性的重要性。所创建的模型有助于理解视频会诊接受的最重要驱动因素，突出了新冠疫情大流行和感知健康风险的重要性。
