Advancing Digital Evaluation for Inter-Professional Education: A PROLIFERATE_AI Mixed-Methods Analysis.

Area of Science:

• Health Professions Education
• Allied Health
• Digital Health Evaluation

Background:

• Inter-professional learning (IPL) is crucial for developing a competent health workforce.
• Evaluating IPL effectiveness is essential for optimizing training programs.
• University-based allied health clinics offer unique settings for IPL research.

Purpose of the Study:

• To evaluate inter-professional learning (IPL) at the Health2GO university-based allied health clinic.
• To assess participant comprehension, engagement, motivation, and barriers within the IPL program.
• To utilize the PROLIFERATE_AI digital evaluation framework for a comprehensive assessment.

Main Methods:

• Employed a mixed-methods approach combining participatory co-design and digital evaluation.
• Utilized the PROLIFERATE_AI framework for data collection and analysis.
• Integrated Bayesian modeling of survey data with qualitative thematic coding.

Main Results:

• Participants demonstrated strong comprehension and high levels of motivation regarding IPL.
• Identified barriers included challenges with scheduling and accessing flexible learning resources.
• The digital evaluation framework provided integrated insights into the IPL experience.

Conclusions:

• IPL programs can foster significant understanding and motivation among health professionals.
• Addressing logistical barriers like scheduling and resource accessibility is key to enhancing IPL.
• Optimizing session clarity, flexibility, and digital access can improve future IPL initiatives.