Empathy Training for Healthcare Students Through Combined Didactic, Practical and AI-based Methods
Overview
- Phase
- Not Applicable
- Status
- Recruiting
- Enrollment
- 108
- Locations
- 1
- Primary Endpoint
- Interpersonal Reactivity Index
Overview
Brief Summary
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.
Detailed Description
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 Design
- Study Type
- Interventional
- Allocation
- Randomized
- Intervention Model
- Parallel
- Primary Purpose
- Other
- Masking
- Single (Outcomes Assessor)
Eligibility Criteria
- Ages
- 18 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- Yes
Inclusion Criteria
- •undergraduate students enrolled in a healthcare-related program
- •no previous experience with empathy-related training
- •no previous experience working in healthcare settings
- •age 18 years or above
- •native Chinese speakers.
Exclusion Criteria
- •\- are or were the main carers of people who are disabled or chronically ill because empathy may be promoted through experience.
Arms & Interventions
Control
Intervention
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 first training session consists of a 4-hour didactic component focused on empathy frameworks and communication strategies. The second training session includes a 2-hour mindfulness training component followed by a 2-hour AI demonstration and practice component where participants engage with virtual client scenarios.
Intervention: Empathy training (Other)
Outcomes
Primary Outcomes
Interpersonal Reactivity Index
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).
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.
Secondary Outcomes
- Consultation and Relational Empathy(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(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).)
Investigators
Dr Liu Tai Wa
Associate Professor
Hong Kong Metropolitan University