Healthc Inform Res.  2023 Oct;29(4):367-376. 10.4258/hir.2023.29.4.367.

Estimating Cognitive Load in a Mobile Personal Health Record Application: A Cognitive Task Analysis Approach

Affiliations
  • 1Department of Biostatistics and Medical Informatics, Faculty of Medicine, Akdeniz University, Antalya, Türkiye
  • 2Department of Computer Engineering, Alanya Alaaddin Keykubat University, Antalya, Türkiye

Abstract


Objectives
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.
Methods
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.
Results
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.
Conclusions
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.

Keyword

Mental Health, Personal Health Records, Mobile Applications, Cognitive Science, User-Centered Design

Figure

  • Figure 1 Menu structure diagram of e-Nabız.

  • Figure 2 Average execution time for mental and physical operators in tasks according to the updated GOMS model and gesture-level model. GOMS: goals, operators, methods, selection rules.


Reference

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