The explanation of behaviors concerning telemedicine acceptance is an evolving area of study. This topic is currently more critical than ever, given that the COVID-19 pandemic is making resources scarcer within the health industry. The objective of this study is to determine which model, the Theory of Planned Behavior or the Technology Acceptance Model, provides greater explanatory power for the adoption of telemedicine addressing outlier-associated bias. We carried out an online survey of patients. The data obtained through the survey were analyzed using both consistent partial least squares path modeling (PLSc) and robust PLSc. The latter used a robust estimator designed for elliptically symmetric unimodal distribution. Both estimation techniques led to similar results, without inconsistencies in interpretation. In short, the results indicate that the Theory of Planned Behavior Model provides a significant explanatory power. Furthermore, the findings show that attitude has the most substantial direct effect on behavioral intention to use telemedicine systems.

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COVID-19 大流行期间的远程医疗接受：稳健一致的偏最小二乘路径建模的一个实证示例

对有关远程医疗接受行为的解释是一个不断发展的研究领域。鉴于 COVID-19 大流行使卫生行业内的资源变得更加稀缺，这个话题目前比以往任何时候都更加重要。本研究的目的是确定哪种模型（计划行为理论或技术接受模型）为采用远程医疗解决异常相关偏差提供了更大的解释力。我们对患者进行了在线调查。通过调查获得的数据使用一致的偏最小二乘路径建模 (PLSc) 和稳健的 PLSc 进行分析。后者使用为椭圆对称单峰分布设计的稳健估计器。两种估计技术都产生了相似的结果，在解释上没有不一致。简而言之，结果表明，计划行为模型理论提供了显着的解释力。此外，研究结果表明态度对使用远程医疗系统的行为意向具有最直接的影响。