Michael Callihan

Assistant Professor

The University of Alabama

United States

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About

Michael Callihan is an Assistant Professor at the University of Alabama. His research areas include emergency department staffing patterns, wearable technology monitoring, clinical decision making in obstetrical emergencies, and patient handling interventions. With a focus on the intersection of technology and emergency nursing practice, his recent work explores clinical judgment, bias experienced by nurses, and biomechanical dynamics.

Articles (14)

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2025

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2024

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2024

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2024

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2022

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2021

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2021

Collaborators (8)

Ellen Benjamin

University of Massachusetts Boston

UNITED STATES

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Savannah Olmstead

Graduate Teaching Assistant

The University of Alabama

UNITED STATES

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Stephanie Frisch

University of Pittsburgh

UNITED STATES

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Jonghwa Oh

Assistant Professor

The University of Alabama

UNITED STATES

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Michael D. Moon

Professor

University of the Incarnate Word

UNITED STATES

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Nathan Jeong

The University of Alabama

UNITED STATES

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Seongcheol Jeong

Korea Electronics Technology Institute

SOUTH KOREA

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Edward Sazonov

Professor

The University of Alabama

UNITED STATES

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Michael Callihan

Research Interests

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About

Articles (14)

Perceived Relationships Between Emergency Department Staffing Patterns and Missed Care, Missed Decompensation, and Delays in Care

Reliability of Wearable Technology to Monitor Core Temperature Among Helicopter-Based EMS Crews

Save Your Back: Comparison of the Compressive Force on the Lower Back Based on Differences in the Training Techniques

Translation of Research to Practice

What if It Were Me? A Qualitative Exploratory Study of Emergency Nurses’ Clinical Decision Making Related to Obstetrical Emergencies in the Context of a Post-Roe Environment

Proof of Concept Testing of Safe Patient Handling Intervention Using Wearable Sensor Technology

Determining Clinical Judgment Among Emergency Nurses During a Complex Simulation

The Experiences of United States Emergency Nurses Related to Witnessed and Experienced Bias: A Mixed-Methods Study

Comparison of Slate Safety Wearable Device to Ingestible Pill and Wearable Heart Rate Monitor

Lower Body Joint Angle Prediction Using Machine Learning and Applied Biomechanical Inverse Dynamics

Role and Training of Emergency Department Charge Nurses: A Mixed Methods Analysis of Processes, Needs, and Expectations

Empirical Study on Human Movement Classification Using Insole Footwear Sensor System and Machine Learning

Ankle Angle Prediction Using a Footwear Pressure Sensor and a Machine Learning Technique

Calories and control: Eating habits, behaviors, and motivations of Generation Z females

Collaborators (8)

Ellen Benjamin

Savannah Olmstead

Stephanie Frisch

Jonghwa Oh

Michael D. Moon

Nathan Jeong

Seongcheol Jeong

Edward Sazonov

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