This seminar aims to help Faculty colleagues who are planning a TDG project or who are just interested in medical education research. It will help provide insight into the design and thinking behind successful HKUMed TDG projects through the sharing by Dr Cecilia Sit, Dr Elaine Lee and Dr Joni Zhang.

TDG projects:

Evaluate the Learning Satisfaction and Performance of Focused Client Interview and the User Experiences on Using Semi-humanoid Robot as Simulated Patient, Supplemented with Smartphone-based Voicebots in Nursing Undergraduates

Dr Cecilia Tin Yan Sit, School of Nursing

Communication skills is essential for nursing students when they collect subjective data during focused client interview, effective skills in communication can facilitate clinical reasoning in terms of noticing, interpreting, and responding to client’s complaints. In previous study, we explored the effectiveness of using conversation-oriented chatbot via semi-humanoid robot in learning focused client interview, it was found that the semi-humanoid robot, who acted as a simulated patient, can supplement the existing modalities of learning, and enhance students’ self-efficacy when face-to-face clinical learning is not possible, this alternative platform also promoted students’ clinical reasoning process. However, some promising drawbacks were identified when robot is used solely, like the venue restriction to campus, technical problem etc.,

Building on earlier work of using chatbot, this project explores the effectiveness and experiences of an additional smartphone-based voicebot using students’ own smartphones after practicing with the simulated patient in school. The smartphone-based voicebot is more convenient which enables students to practice communication regardless of time and geographical constraints. Students can have self-practices after teacher’s in-class comment without any pressure at their own time and place. This study aims to study the learning satisfaction and performance as well a the user experience of focused client interview by using both simulated patient and smartphone-based voicebot.

Dr Elaine Yuen Phin Lee, Department of Diagnostic Radiology, School of Clinical Medicine

Ultrasound is increasingly used as an adjunct in clinical skills training and management. Riding on that, the HKU Faculty of Medicine recently introduced a new undergraduate ultrasound curriculum to provide bedside ultrasound training. However, feedback on the clinical skills training places significant time pressure on limited trained faculty members, not to mention the inability to provide “on-demand” feedback and scaling up of the curriculum.

This TDG application aims at developing a fully automated feedback system using artificial intelligence through deep learning algorithm to overcome this shortcoming.

As proof-of-concept, we will use images from renal ultrasound from existing databases to train the deep learning algorithm to grade the quality of the ultrasound images based on a 3-point grading scale. This will then be tested on images submitted by medical students during their bedside ultrasound training to provide feedback to students. The performance of the deep learning algorithm will be compared with assessment provided by experienced ultrasound instructors. Students’ experiences will be explored and compared to evaluate the impact on learning and self-reflection. With this, the deep learning algorithm can provide feedback on students’ learning on bedside ultrasound and facilitate self-assessment; supplement the current feedback system to allow ultrasound instructors to concentrate on more challenging areas that students struggle and hence, more efficient use of the student-instructor interaction time.

Curriculum and Pedagogical Innovation: Enhancement of Interdisciplinary Professional Skills in Physical Activity (PA) Counselling

Dr Joni H Zhang, School of Public Health

There is a global call on the necessity to strengthen our health professionals’ ability in providing patient assessment and counselling on increasing physical activity and reducing sedentary behviour (WHO, 2019). It is well established that increased physical activity is beneficial for at least 26chronic diseases (Pedersen & Saltin, 2015), as well as the cost effectiveness of primary care (Garett et al. 2011).

Doctors are a credible and respected source of health-related information, therefore conversations between doctors and their patients offer a vital intervention opportunity to provide physical activity (PA) counselling to patients, thereby increasing their PA and/or decreasing physical inactivity./p>

However, the current MBBS curriculum provides little to no formal training in this aspect. It is therefore important that we develop effective teaching and learning strategies to teach this subject matter to equip our future doctors with the necessary skills and confidence to provide PA advice and counselling.

Speakers:

Dr Cecilia Tin Yan Sit, School of Nursing, HKU

Dr Elaine Yuen Phin Lee, School of Clinical Medicine, HKU

Dr Joni H Zhang, School of Public Health, HKU

Moderator:

Dr Fred Ganotice, BIMHSE, HKU