Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Acute Coronary Syndrome III: Diagnostic Studies

Acute Coronary Syndrome III: Diagnostic Studies

Diagnosing acute coronary syndrome or ACS begins with a thorough patient history. Notable symptoms include central, crushing chest pain radiating to the left arm, neck, jaw, or back, along with shortness of breath, sweating (diaphoresis), nausea, vomiting, dizziness, and palpitations.It is crucial to note any history of cardiac illnesses and assess risk factors, including age, gender, smoking, hypertension, diabetes, hyperlipidemia, and a sedentary lifestyle.During physical examination, vital...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

New paradigms and adaptations in times of rapid technological changes.

Families, systems & health : the journal of collaborative family healthcare·2026

Same author

Technology in integrated health care and family systems: Expansive innovation and important considerations.

Families, systems & health : the journal of collaborative family healthcare·2026

Same author

"We're All in This Together": A Mixed-Methods Study of Provider and Patient Perceptions of Emergency Care for Opioid Use Disorder.

Journal of advanced nursing·2026

Same author

Exploring Common and Novel Actualized Affordances of Fitbit: Mixed Methods Study.

JMIR human factors·2026

Same author

"It's so scary, and you're so alone with it": Clinicians' perspectives on suicide risk management in integrated primary care.

PLOS mental health·2026

Same author

Personality-Driven Variations in Fitness App Affordance Actualization Among Adults: Quantitative Survey Study.

JMIR formative research·2025

Same journal

Predicting Chemotherapy Response from Staging Laparoscopy Images.

medRxiv : the preprint server for health sciences·2026

Same journal

Development and External Validation of a Machine Learning Model for 10-Year Ischemic Stroke Risk Prediction in Diverse Populations.

medRxiv : the preprint server for health sciences·2026

Same journal

MCH-Guard: Multimodal Machine Learning Framework for Risk Stratification of Cerebral Microhemorrhage Risk in the Alzheimer's Disease Neuroimaging Initiative.

medRxiv : the preprint server for health sciences·2026

Same journal

Genetic and maternal environmental contributions to estimated fetal weight at 20 weeks gestation compared with birthweight.

medRxiv : the preprint server for health sciences·2026

Same journal

Better immediate declarative memory is associated with forgetting during locomotor adaptation in chronic stroke and in older adults.

medRxiv : the preprint server for health sciences·2026

Same journal

An empirical Bayes framework for burden and dispersion association tests helps prioritize rare variants associated with Alzheimer's disease.

medRxiv : the preprint server for health sciences·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 9, 2026

Eye Tracking Young Children with Autism

Eye Tracking Young Children with Autism

Published on: March 27, 2012

Clinicians' Visual Attention During Suicide Screening Encounters: An Exploratory Eye-Tracking Study.

Doaa Alrefaei^1,2, Kaidi Huang², Ashwin Sukumar²

¹King Abdulaziz University, KSA.

Medrxiv : the Preprint Server for Health Sciences

|February 27, 2026

Summary

This summary is machine-generated.

Primary care clinicians using electronic health records (EHRs) show increased visual attention on the EHR, impacting patient communication. This eye-tracking study reveals EHRs can delay crucial suicide-related discussions.

Keywords:

CAT-MH®Cognitive workload Electronic health records Eye tracking Primary care Suicide screening

More Related Videos

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Published on: April 4, 2025

Related Experiment Videos

Last Updated: May 9, 2026

Eye Tracking Young Children with Autism

Eye Tracking Young Children with Autism

Published on: March 27, 2012

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

Published on: March 18, 2019

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Published on: April 4, 2025

Area of Science:

Clinical Informatics
Human-Computer Interaction
Cognitive Science

Background:

Eye tracking is a validated method for assessing visual attention and cognitive load.
Electronic Health Records (EHRs) are integral to modern primary care but can create dual demands for clinicians.
Understanding how clinicians interact with EHRs during patient encounters is crucial for optimizing workflows.

Purpose of the Study:

To investigate how primary care providers' visual attention is allocated between patient communication and EHR navigation.
To examine the impact of EHR-embedded suicide risk screening tools on clinical decision-making and encounter flow.
To analyze the interplay between eye movements and verbalized thought processes during simulated patient visits.

Main Methods:

Utilized wearable eye tracking to capture visual information processing behavior.
Employed a retrospective think-aloud protocol to gather qualitative insights into clinicians' cognitive processes.
Conducted simulated patient visits incorporating an EHR-embedded suicide risk assessment tool (CAT-MH®).

Main Results:

Eye-movement data indicated significant visual attention directed towards the EHR interface.
Clinicians frequently navigated multiple EHR sections to verify suicide risk indicators.
Retrospective data revealed a tendency to postpone suicide-related discussions until information verification was complete.

Conclusions:

EHR design and embedded tools can significantly influence clinical attention distribution and communication timing.
The integration of screening tools within EHRs introduces information-processing demands that affect encounter dynamics.
Further research is needed to optimize EHR usability and minimize disruptions to patient-clinician communication.