The development of a classification schema for arts-based approaches to knowledge translation

Area of Science:

• Health professions education
• Knowledge translation
• Arts-based research

Background:

• Arts-based approaches are emerging as effective interprofessional strategies for knowledge translation in healthcare.
• These methods can facilitate evidence uptake, communication, and behavior change among healthcare providers and consumers.
• A lack of a classification system hinders the development and evaluation of arts-based knowledge translation.

Purpose of the Study:

• To develop a classification schema for arts-based knowledge translation strategies.
• The schema is based on message precision and end-user participation.
• To demonstrate the schema's utility in exploring contextual influences on these strategies.

Main Methods:

• A classification schema was developed based on two key mechanisms: precision of message delivery and degree of end-user participation.
• The schema was conceptualized to facilitate exploration of context, time, and location's impact.
• The study outlines the foundational elements for this new classification system.

Main Results:

• A novel classification schema for arts-based knowledge translation strategies has been established.
• This schema categorizes strategies based on message precision and user engagement levels.
• The classification provides a framework for analyzing the influence of context on strategy effectiveness.

Conclusions:

• Classifying arts-based knowledge translation strategies enhances understanding of their suitability for diverse healthcare settings and populations.
• The schema can improve insights into the effectiveness of these approaches across various contexts.
• This classification may foster systematic research into the efficacy of arts-based knowledge translation in interprofessional settings.