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Volume: 35 | Article ID: VDA-399
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Computer-supported expert-guided experiential learning-based tools for healthcare skills
  DOI :  10.2352/EI.2023.35.1.VDA-399  Published OnlineJanuary 2023
Abstract
Abstract

Healthcare professionals, just like any other community, can exhibit implicit biases. These biases adversely impact patients’ health outcomes. Promoting awareness of both social determinants of health (SDH) and the impact of implicit/explicit biases assists healthcare professionals to understand their patients well and improve care experiences. In addition, it helps to augment the long-lasting empathy and compassion in healthcare professionals towards patients for care treatments while maintaining better healthcare professional-patient relationships. Thus, this research provides Computer-Supported Expert-Guided Experiential Learning (CSEGEL) tools or mobile applications that facilitate healthcare professionals with a first-person learning experience to augment advanced healthcare skills (e.g., professional communication, cultural humility, awareness of both SDH and impact of biases on health outcomes). The CSEGEL tools in the form of mobile applications incorporate virtual reality-based serious role-playing scenarios along with a novel Life Course module to deliver first-person experiential learning capability to augment the advanced healthcare skills of healthcare professionals and public awareness. Finally, a preliminary data analysis is provided to demonstrate the positive influence of CSEGEL tools and measure the required number of sample sizes for concrete evidence to show effective results.

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  Cite this article 

Dixit Bharatkumar Patel, Thomas Wischgoll, Yong Pei, Angie Castle, Anne Proulx, Danielle Gainer, Timothy Crawford, Autumn James, Ashutosh Shivakumar, Colleen Elizabeth Pennington, Hanna Peterson, Carolina Beatriz Nadal Medina, Sindhu Kumari, Mark Alow, Sri Lekha Koppaka, Cassandra Mae Patel, Joshua Patel, Neha Priyadarshani, Paul J. Hershberger, "Computer-supported expert-guided experiential learning-based tools for healthcare skillsin Electronic Imaging,  2023,  pp 399-1 - 399-11,  https://doi.org/10.2352/EI.2023.35.1.VDA-399

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