Abstract
Effective pain management and time to treatment is essential in patient care. Despite scientific evidence supporting the need to treat pain and an emphasis on addressing pain as a priority, pain management continues to be an unresolved issue. As a member of the health care team, nurses are integral to optimal pain management. Currently, nursing schools have limited innovative or alternative methods for teaching pain assessment and management. Simulation in nursing education provides a unique opportunity to expose students to realistic patient situations and allow them to learn and make mistakes without causing harm. However, modern low- and high-fidelity simulation technology is unable to display emotion, pain, or any facial expression. This limits training and education of conditions that may partially rely on the identification of symptoms based on the alteration of facial appearance, such as pain or stroke. This research explored student nurses’ perception of new technology that displayed computer-generated faces, each expressing varying degrees of physical expressions of pain. A total of 15 nursing students participated in the study. Students were asked to interpret the level of pain in four sequential faces using a numeric rating scale of 0-10, with 0 indicating no pain, and 10 the most severe pain possible. After scoring the faces, students were asked to answer four open-ended questions addressing the technology. Results of the study indicate a majority of nursing students believe the technology should be implemented into nursing curriculum and interacting with the projected faces was more beneficial than traditional teaching methods. Eventually, the potential for increased identification of conditions requiring observation of subtle facial changes will be explored.
Thesis Completion
2016
Semester
Spring
Thesis Chair/Advisor
Allred, Kelly
Degree
Bachelor of Science in Nursing (B.S.N.)
College
College of Nursing
Degree Program
Nursing
Location
Orlando (Main) Campus
Language
English
Access Status
Open Access
Length of Campus-only Access
1 year
Release Date
5-1-2017
Recommended Citation
Grace, Justin C., "Recognizing Pain Using Novel Simulation Technology" (2016). Honors Undergraduate Theses. 2.
https://stars.library.ucf.edu/honorstheses/2
Included in
Anesthesia and Analgesia Commons, Critical Care Commons, Critical Care Nursing Commons, Diagnosis Commons, Family Practice Nursing Commons, Geriatric Nursing Commons, Maternal, Child Health and Neonatal Nursing Commons, Other Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons, Other Nursing Commons, Palliative Care Commons, Pediatric Nursing Commons, Perioperative, Operating Room and Surgical Nursing Commons, Preventive Medicine Commons, Robotics Commons, Trauma Commons