Zayim Neşe, Yıldız Hasibe, Yüce Yilmaz Kemal
Department of Biostatistics and Medical Informatics, Faculty of Medicine, Akdeniz University, Antalya, Türkiye.
Department of Computer Engineering, Alanya Alaaddin Keykubat University, Antalya, Türkiye.
Healthc Inform Res. 2023 Oct;29(4):367-376. doi: 10.4258/hir.2023.29.4.367. Epub 2023 Oct 31.
Mobile health applications that are designed without considering usability criteria can lead to cognitive overload, resulting in the rejection of these apps. To avoid this problem, the user interface of mobile health applications should be evaluated for cognitive load. This evaluation can contribute to the improvement of the user interface and help prevent cognitive overload for the user.
In this study, we evaluated a mobile personal health records application using the cognitive task analysis method, specifically the goals, operators, methods, and selection rules (GOMS) approach, along with the related updated GOMS model and gesture-level model techniques. The GOMS method allowed us to determine the steps of the tasks and categorize them as physical or cognitive tasks. We then estimated the completion times of these tasks using the updated GOMS model and gesture-level model.
All 10 identified tasks were split into 398 steps consisting of mental and physical operators. The time to complete all the tasks was 5.70 minutes and 5.45 minutes according to the updated GOMS model and gesture-level model, respectively. Mental operators covered 73% of the total fulfillment time of the tasks according to the updated GOMS model and 76% according to the gesture-level model. The inter-rater reliability analysis yielded an average of 0.80, indicating good reliability for the evaluation method.
The majority of the task execution times comprised mental operators, suggesting that the cognitive load on users is high. To enhance the application's implementation, the number of mental operators should be reduced.
未考虑可用性标准而设计的移动健康应用程序可能会导致认知过载，从而致使这些应用程序被用户拒绝。为避免此问题，应评估移动健康应用程序的用户界面的认知负荷。这种评估有助于改进用户界面，并有助于防止用户出现认知过载。
在本研究中，我们使用认知任务分析方法，特别是目标、操作、方法和选择规则（GOMS）方法，以及相关的更新后的GOMS模型和手势级模型技术，对一款移动个人健康记录应用程序进行了评估。GOMS方法使我们能够确定任务步骤，并将其分类为体力任务或认知任务。然后，我们使用更新后的GOMS模型和手势级模型估计这些任务的完成时间。
所有10项已识别的任务被分解为398个步骤，包括心理和体力操作。根据更新后的GOMS模型和手势级模型，完成所有任务的时间分别为5.70分钟和5.45分钟。根据更新后的GOMS模型，心理操作占任务总完成时间的73%，根据手势级模型则占76%。评分者间信度分析得出的平均值为0.80，表明该评估方法具有良好的信度。
大多数任务执行时间都包含心理操作，这表明用户的认知负荷较高。为了改进该应用程序的实施，应减少心理操作的数量。
