Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, Maastricht, The Netherlands.
Department of Marketing and Supply Chain Management, Maastricht University, Maastricht, The Netherlands.
BMC Health Serv Res. 2022 Jul 9;22(1):890. doi: 10.1186/s12913-022-08189-7.
Technological progress in artificial intelligence has led to the increasing popularity of virtual assistants, i.e., embodied or disembodied conversational agents that allow chatting with a technical system in a natural language. However, only little comprehensive research is conducted about patients' perceptions and possible applications of virtual assistant in healthcare with cancer patients. This research aims to investigate the key acceptance factors and value-adding use cases of a virtual assistant for patients diagnosed with cancer.
Qualitative interviews with eight former patients and four doctors of a Dutch radiotherapy institute were conducted to determine what acceptance factors they find most important for a virtual assistant and gain insights into value-adding applications. The unified theory of acceptance and use of technology (UTAUT) was used to structure perceptions and was inductively modified as a result of the interviews. The subsequent research model was triangulated via an online survey with 127 respondents diagnosed with cancer. A structural equation model was used to determine the relevance of acceptance factors. Through a multigroup analysis, differences between sample subgroups were compared.
The interviews found support for all factors of the UTAUT: performance expectancy, effort expectancy, social influence and facilitating conditions. Additionally, self-efficacy, trust, and resistance to change, were added as an extension of the UTAUT. Former patients found a virtual assistant helpful in receiving information about logistic questions, treatment procedures, side effects, or scheduling appointments. The quantitative study found that the constructs performance expectancy (ß = 0.399), effort expectancy (ß = 0.258), social influence (ß = 0.114), and trust (ß = 0.210) significantly influenced behavioral intention to use a virtual assistant, explaining 80% of its variance. Self-efficacy (ß = 0.792) acts as antecedent of effort expectancy. Facilitating conditions and resistance to change were not found to have a significant relationship with user intention.
Performance and effort expectancy are the leading determinants of virtual assistant acceptance. The latter is dependent on a patient's self-efficacy. Therefore, including patients during the development and introduction of a VA in cancer treatment is important. The high relevance of trust indicates the need for a reliable, secure service that should be promoted as such. Social influence suggests using doctors in endorsing the VA.
人工智能技术的进步导致虚拟助手越来越受欢迎，即具有或不具有实体的会话代理，允许用户用自然语言与技术系统进行聊天。然而，对于虚拟助手在癌症患者中的应用，只有很少的综合研究涉及患者的看法和潜在应用。本研究旨在调查患者对诊断为癌症的患者使用虚拟助手的关键接受因素和增值用例。
对荷兰放射治疗研究所的 8 名前患者和 4 名医生进行了定性访谈，以确定他们认为对虚拟助手最重要的接受因素，并深入了解增值应用。采用统一技术接受和使用理论（UTAUT）来构建感知，并根据访谈结果进行归纳修改。随后的研究模型通过对 127 名诊断为癌症的患者进行在线调查进行了三角验证。结构方程模型用于确定接受因素的相关性。通过多组分析，比较了样本子组之间的差异。
访谈结果支持 UTAUT 的所有因素：绩效预期、努力预期、社会影响和便利条件。此外，自我效能、信任和抵制变革也被添加为 UTAUT 的扩展。前患者发现虚拟助手在获取有关后勤问题、治疗程序、副作用或预约方面的信息方面很有帮助。定量研究发现，绩效预期（β=0.399）、努力预期（β=0.258）、社会影响（β=0.114）和信任（β=0.210）这四个构念显著影响使用虚拟助手的行为意图，解释了 80%的方差。自我效能（β=0.792）是努力预期的前因。便利条件和抵制变革与用户意图没有发现显著关系。
绩效和努力预期是虚拟助手接受的主要决定因素。后者取决于患者的自我效能。因此，在癌症治疗中开发和引入虚拟助手时，让患者参与进来非常重要。信任的高度相关性表明需要一个可靠、安全的服务，并应以此作为宣传重点。社会影响表明可以利用医生来支持虚拟助手。
