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

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dc.authorid0000-0003-1971-5164
dc.authorid0000-0003-3133-2692
dc.contributor.authorZayim, Nese
dc.contributor.authorYildiz, Hasibe
dc.contributor.authorYuce, Yilmaz Kemal
dc.date.accessioned2026-01-24T12:26:40Z
dc.date.available2026-01-24T12:26:40Z
dc.date.issued2023
dc.departmentAlanya Alaaddin Keykubat Üniversitesi
dc.description.abstractObjectives: 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.
dc.description.sponsorshipAkdeniz University Scientific Research Project Administration Division [5416]
dc.description.sponsorshipThis study was supported by the Akdeniz University Scientific Research Project Administration Division (Project ID. 5416).
dc.identifier.doi10.4258/hir.2023.29.4.367
dc.identifier.endpage376
dc.identifier.issn2093-3681
dc.identifier.issn2093-369X
dc.identifier.issue4
dc.identifier.pmid37964458
dc.identifier.scopus2-s2.0-85176452957
dc.identifier.scopusqualityQ2
dc.identifier.startpage367
dc.identifier.urihttps://doi.org/10.4258/hir.2023.29.4.367
dc.identifier.urihttps://hdl.handle.net/20.500.12868/4849
dc.identifier.volume29
dc.identifier.wosWOS:001104128600009
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherKorean Soc Medical Informatics
dc.relation.ispartofHealthcare Informatics Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20260121
dc.subjectUser-Computer Interface
dc.subjectPersonal Health Records
dc.subjectMobile Applications
dc.subjectCognition
dc.subjectCognitive Science
dc.titleEstimating Cognitive Load in a Mobile Personal Health Record Application: A Cognitive Task Analysis Approach
dc.typeArticle

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