Application of Eye-Tracking in Nursing Research: A Scoping Review

Aims: To map the themes and methods of nursing researches involving eye-tracking as a measurement, and offer suggestion for future nursing research using eye-tracking. Design: We conducted a scoping review following the methodology outlined in the JBI Manual for Evidence Synthesis on scoping reviews. Methods: Eligibility criteria were established based on Population (involving nursing or nursing students), Concept (utilizing eye-tracking as a research method), and Context (in any setting). Articles were retrieved from the PubMed, Web of Science, Embase, CINAHL, APA PsycInfo, and Scopus databases, spanning from database inception to November 17, 2023. The included studies were analysed using descriptive statistics and content analysis. Results: After duplicates were removed, 815 citations were identified from searches of electronic databases and other resources, and 66 met the inclusion criteria finally. Thirty-eight studies were conducted in a simulated environment. Five application domains were identified, and most of the studies (N = 50) were observational. The domains found in our review did not cover all topics of nursing research in the same depth. Additionally, 39 studies did not solely explicate eye-tracking data but instead integrated behavioural measures, scales/questionnaires, or other physiological data. Conclusions: Eye-tracking emerges as a significant research tool in uncovering visual behaviour, particularly in nursing research focused on nursing education. This study not only summarized the application and interpretation of eye-tracking data but also recognized its potential in advancing clinical nursing research and practice. To effectively harness the capabilities of eye-tracking in elucidating cognitive processes, future research should aim for a clearer grasp of the theoretical underpinnings of the addressed research problems and methodological choices. It is crucial to emphasize the standardization of eye-tracking method reporting and ensuring data quality. No Patient or Public Contribution.