确定用户接受无人机送药的因素:以用户为中心的设计方法

IF 2.6 Q2 HEALTH CARE SCIENCES & SERVICES JMIR Human Factors Pub Date : 2024-04-30 DOI:10.2196/51587
Franziska Fink, Ivonne Kalter, Jenny-Victoria Steindorff, Hans Konrad Helmbold, Denny Paulicke, Patrick Jahn
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引用次数: 0

摘要

背景:在人口老龄化和熟练工人日益短缺的背景下,人们越来越多地讨论在医疗保健领域使用无人机的问题。特别是,在农村地区使用无人机提供医疗服务,可以为有护理需求和无护理需求的人提供护理服务。然而,目前几乎没有任何数据关注人类与无人机之间的互动:本研究旨在揭示和分析用户接受无人机送药的相关因素,从而为参与式技术开发(应用程序和无人机)提供与实践相关的指导要点:方法:开展了一项受控混合方法研究,以参与式研究设计为基础,支持无人机辅助给药应用程序设计的技术开发过程。在定量分析中,使用了既定的标准化调查工具来获取技术接受度,如系统可用性量表、技术使用清单(TUI)和用户体验动机、参与度和茁壮成长模型。为避免用户持续开发可能产生的偏差效应(如反应转变和学习效应),在 3 个迭代开发步骤中的每个步骤都成立了一个特设小组,随后将其与经历了所有 3 个迭代步骤的核心小组进行比较:研究发现,无人药店应用程序的可用性与参与者的使用意愿之间存在正相关(r=0.833)。参与者对实用性的感知对他们使用该应用程序的意愿有积极影响(r=0.487;TUI)。怀疑对感知可用性和使用意愿有负面影响(r=-0.542;系统可用性量表和 r=-0.446;TUI)。研究发现,有用性、怀疑和好奇心在很大程度上解释了使用该应用程序的意愿(F3,17=21.12;P2=0.788;调整后 R2=0.751)。核心组对无人药店应用程序使用意向的评分高于特设组。双尾 t 检验的结果显示,核心小组第三次迭代的可用性评分高于第一次迭代:结论:在参与式设计的帮助下,参与人员可以发现与无人机辅助给药有关的重要接受方面。例如,使用该技术的时间长短是影响使用该应用程序意愿的一个重要因素。用户友好度或好奇心等特定技术因素与无人机应用程序的使用接受度直接相关。研究结果表明,参与者对自己操作应用程序的能力感知越强,就越愿意使用这项技术,对应用程序的可用性评价也越高。
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Identifying Factors of User Acceptance of a Drone-Based Medication Delivery: User-Centered Design Approach.

Background: The use of drones in the health care sector is increasingly being discussed against the background of the aging population and the growing shortage of skilled workers. In particular, the use of drones to provide medication in rural areas could bring advantages for the care of people with and without a need for care. However, there are hardly any data available that focus on the interaction between humans and drones.

Objective: This study aims to disclose and analyze factors associated with user acceptance of drone-based medication delivery to derive practice-relevant guidance points for participatory technology development (for apps and drones).

Methods: A controlled mixed methods study was conducted that supports the technical development process of an app design for drone-assisted drug delivery based on a participatory research design. For the quantitative analysis, established and standardized survey instruments to capture technology acceptance, such as the System Usability Scale; Technology Usage Inventory (TUI); and the Motivation, Engagement, and Thriving in User Experience model, were used. To avoid possible biasing effects from a continuous user development (eg, response shifts and learning effects), an ad hoc group was formed at each of the 3 iterative development steps and was subsequently compared with the consisting core group, which went through all 3 iterations.

Results: The study found a positive correlation between the usability of a pharmacy drone app and participants' willingness to use it (r=0.833). Participants' perception of usefulness positively influenced their willingness to use the app (r=0.487; TUI). Skepticism had a negative impact on perceived usability and willingness to use it (r=-0.542; System Usability Scale and r=-0.446; TUI). The study found that usefulness, skepticism, and curiosity explained most of the intention to use the app (F3,17=21.12; P<.001; R2=0.788; adjusted R2=0.751). The core group showed higher ratings on the intention to use the pharmacy drone app than the ad hoc groups. Results of the 2-tailed t tests showed a higher rating on usability for the third iteration of the core group compared with the first iteration.

Conclusions: With the help of the participatory design, important aspects of acceptance could be revealed by the people involved in relation to drone-assisted drug delivery. For example, the length of time spent using the technology is an important factor for the intention to use the app. Technology-specific factors such as user-friendliness or curiosity are directly related to the use acceptance of the drone app. Results of this study showed that the more participants perceived their own competence in handling the app, the more they were willing to use the technology and the more they rated the app as usable.

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来源期刊
JMIR Human Factors
JMIR Human Factors Medicine-Health Informatics
CiteScore
3.40
自引率
3.70%
发文量
123
审稿时长
12 weeks
期刊最新文献
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