This study aims to examine the effects of a newly developed training program on the empathy of healthcare students. The objectives are: (i) designing and implementing an User Interface (UI) using Unity featuring 3D virtual clients representing individuals with physical disabilities, bodily discomforts, and psychosocial disturbances, paired with a chatbot interface for interactive questions-and-answers; (ii) developing a brief empathy training program incorporating AI-generated virtual clients into traditional teaching methods, including didactic lectures, skills rehearsal, mindfulness-based training, and practice with AI-generated virtual clients; and (iii) assessing the impact of this training program on the empathetic attitude, empathetic communication skills, and cognitive flexibility of healthcare students.
Various traditional pedagogies have been used in empathy training for healthcare students. For instance, didactic lectures often aim at introducing the scientific information of empathy, while experiential learning, such as role-playing and standardized patient interactions, are used to facilitate learning through reflection on doing and minimizing stereotypes. Additionally, mindfulness-based training is employed to promote self-awareness and cultivate essential traits in healthcare students and clinicians, such as being nonjudgmental, kind, compassionate, and altruistic. However, a previous systematic review revealed inconsistent findings about the effects of traditional pedagogies and highlighted the need for innovative teaching approaches from healthcare educators. Perspective-taking is a crucial empathy-related phenomenon that refers to the capability of comprehending the intentions of others. Despite the use of experiential learning strategies in previous empathy training, previous studies are not without limitations. For instance, role-play and standardized patients in developing clinical empathy have been criticized for limited authenticity, variations in skills and consistency of participants, inadequate quality feedback, and resource intensity. Recent studies have also explored the use of virtual reality as an experiential learning component to render experiences of immersion, presence, and embodiment. However, these strategies cannot cover a wide range of clinical situations or provide timely feedback. In recent years, technological advancements have provided new opportunities for innovative educational strategies. One such promising approach is the use of artificial intelligence (AI)-generated virtual clients in empathy training. AI-generated virtual clients can simulate a wide range of client interactions, offering a repeatable environment to practice and cultivate empathy. The integration of virtual clients into empathy training programs has the potential to revolutionize healthcare education. Thus, this research proposal aims to examine the effects of a brief empathy training program utilizing AI-generated virtual clients and traditional pedagogies on the empathy levels of healthcare students. By incorporating AI-generated virtual clients into newly developed empathy training protocol, along with elements of didactic lectures and mindfulness-based training, the investigators hypothesize that students will experience a significant improvement in empathetic attitude, and then leading to better empathetic communication skills and cognitive flexibility.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
SINGLE
Enrollment
108
Participants in the intervention group will undertake two sessions, each lasting four hours, of empathy training over a one-week period with group size of 6 to 8 participants. The empathy training will base on our newly developed protocol, including: (i) didactic lectures; (ii) practical skills demonstration and role-play, (iii) a mindfulness-based training; and (iv) practice of empathic skills in two different randomly selected scenarios with feedback from the AI system. Each participants will encounter different scenarios that simulate diverse clinical challenges.
Hong Kong Metropolitan University
Ho Man Tin, Kowloon, Hong Kong
Interpersonal Reactivity Index
The Interpersonal Reactivity Index (IRI) will be used to assess self-reported empathetic attitude. IRI consists of 4 subscale with 28 items rating on a 5 - point Likert scale (0 - 4). Score ranges from 0 - 112, higher score means better empathy.
Time frame: Baseline assessment (prior to any training), (ii) immediate post-training assessment (immediately after the final training session, end of week 1), and (iii) 1-month follow-up assessment (approximately 4 weeks after the final training session).
Consultation and Relational Empathy
The Consultation and Relational Empathy (CARE) measure will be used to assess participants' empathic communication skills, focusing on patient-perceived empathy during clinical interactions. CARE consists of 10 items rating on a 5 point Likert scale. Score ranges from 10 - 50, higher score means better perceived relational empathy.
Time frame: Baseline assessment (prior to any training), (ii) immediate post-training assessment (immediately after the final training session, end of week 1), and (iii) 1-month follow-up assessment (approximately 4 weeks after the final training session).
Cognitive Flexibility Inventory
Cognitive Flexibility Inventory (CFI) will be used to assess self-reported cognitive flexibility. CFI consists of 20 items rating on 1-7 Likert scale (score range 20 - 140), higher score means greater flexibiity and lower score means more cognitive rigidity.
Time frame: Baseline assessment (prior to any training), (ii) immediate post-training assessment (immediately after the final training session, end of week 1), and (iii) 1-month follow-up assessment (approximately 4 weeks after the final training session).
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