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Recognizing Pain Using Novel Simulation Technology

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.

Identiferoai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:honorstheses-1027
Date01 January 2016
CreatorsGrace, Justin C
PublisherSTARS
Source SetsUniversity of Central Florida
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceHonors Undergraduate Theses

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