Human Computer Interaction and Design Lab, Seoul National University, Seoul, Republic of Korea.
Seoul National University, Seoul, Republic of Korea.
J Med Internet Res. 2021 Mar 29;23(3):e22099. doi: 10.2196/22099.
Prolonged time of computer use increases the prevalence of ocular problems, including eye strain, tired eyes, irritation, redness, blurred vision, and double vision, which are collectively referred to as computer vision syndrome (CVS). Approximately 70% of computer users have vision-related problems. For these reasons, properly designed interventions for users with CVS are required. To design an effective screen intervention for preventing or improving CVS, we must understand the effective interfaces of computer-based interventions.
In this study, we aimed to explore the interface elements of computer-based interventions for CVS to set design guidelines based on the pros and cons of each interface element.
We conducted an iterative user study to achieve our research objective. First, we conducted a workshop to evaluate the overall interface elements that were included in previous systems for CVS (n=7). Through the workshop, participants evaluated existing interface elements. Based on the evaluation results, we eliminated the elements that negatively affect intervention outcomes. Second, we designed our prototype system LiquidEye that includes multiple interface options (n=11). Interface options included interface elements that were positively evaluated in the workshop study. Lastly, we deployed LiquidEye in the real world to see how the included elements affected the intervention outcomes. Participants used LiquidEye for 14 days, and during this period, we collected participants' daily logs (n=680). Additionally, we conducted prestudy and poststudy surveys, and poststudy interviews to explore how each interface element affects participation in the system.
User data logs collected from the 14 days of deployment were analyzed with multiple regression analysis to explore the interface elements affecting user participation in the intervention (LiquidEye). Statistically significant elements were the instruction page of the eye resting strategy (P=.01), goal setting of the resting period (P=.009), compliment feedback after completing resting (P<.001), a mid-size popup window (P=.02), and CVS symptom-like effects (P=.004).
Based on the study results, we suggested design implications to consider when designing computer-based interventions for CVS. The sophisticated design of the customization interface can make it possible for users to use the system more interactively, which can result in higher engagement in managing eye conditions. There are important technical challenges that still need to be addressed, but given the fact that this study was able to clarify the various factors related to computer-based interventions, the findings are expected to contribute greatly to the research of various computer-based intervention designs in the future.
长时间使用计算机增加了眼部问题的发生率，包括眼疲劳、眼睛疲劳、刺激、发红、视力模糊和复视，这些统称为计算机视觉综合征（CVS）。大约 70%的计算机用户有与视力相关的问题。出于这些原因，需要为 CVS 患者设计适当的干预措施。为了设计有效的屏幕干预措施来预防或改善 CVS，我们必须了解基于计算机的干预措施的有效界面。
在这项研究中，我们旨在探讨基于计算机的 CVS 干预措施的界面元素，以便根据每个界面元素的优缺点制定设计指南。
我们通过迭代用户研究来实现研究目标。首先，我们举办了一个研讨会，以评估之前用于 CVS 的系统中包含的整体界面元素（n=7）。通过研讨会，参与者评估了现有的界面元素。根据评估结果，我们消除了那些对干预结果产生负面影响的元素。其次，我们设计了我们的原型系统 LiquidEye，该系统包含多个界面选项（n=11）。界面选项包括在研讨会研究中得到积极评价的界面元素。最后，我们将 LiquidEye 部署到现实世界中，以观察所包含的元素如何影响干预结果。参与者使用 LiquidEye 14 天，在此期间，我们收集了参与者的日常日志（n=680）。此外，我们进行了预研究和后研究调查，以及后研究访谈，以探讨每个界面元素如何影响他们对系统的参与。
通过多元回归分析对为期 14 天的部署中收集的用户数据日志进行了分析，以探讨影响用户参与干预（LiquidEye）的界面元素。具有统计学意义的元素是眼休息策略的说明页面（P=.01）、休息期目标设定（P=.009）、完成休息后的赞美反馈（P<.001）、中等大小的弹出窗口（P=.02）和 CVS 症状样效应（P=.004）。
根据研究结果，我们建议在设计用于 CVS 的基于计算机的干预措施时考虑设计要点。定制界面的复杂设计可以使用户更具交互性地使用系统，从而提高管理眼部状况的参与度。仍然存在一些重要的技术挑战需要解决，但鉴于本研究能够阐明与基于计算机的干预措施相关的各种因素，预计这些发现将对未来各种基于计算机的干预设计研究做出重大贡献。
