Modeling eye gaze patterns in clinician-patient interaction with lag sequential analysis.

OBJECTIVE: The aim of this study was to examine whether lag sequential analysis could be used to describe eye gaze orientation between clinicians and patients in the medical encounter. This topic is particularly important as new technologies are implemented into multiuser health care settings in which trust is critical and nonverbal cues are integral to achieving trust. This analysis method could lead to design guidelines for technologies and more effective assessments of interventions.
BACKGROUND: Nonverbal communication patterns are important aspects of clinician-patient interactions and may affect patient outcomes.
METHOD: The eye gaze behaviors of clinicians and patients in 110 videotaped medical encounters were analyzed using the lag sequential method to identify significant behavior sequences. Lag sequential analysis included both event-based lag and time-based lag.
RESULTS: Results from event-based lag analysis showed that the patient's gaze followed that of the clinician, whereas the clinician's gaze did not follow the patient's. Time-based sequential analysis showed that responses from the patient usually occurred within 2 s after the initial behavior of the clinician.
CONCLUSION: Our data suggest that the clinician's gaze significantly affects the medical encounter but that the converse is not true. APPLICATION: Findings from this research have implications for the design of clinical work systems and modeling interactions. Similar research methods could be used to identify different behavior patterns in clinical settings (physical layout, technology, etc.) to facilitate and evaluate clinical work system designs.

RCT Entities:   Population Interventions Outcomes