The co-production process of a Recovery College course in knowledge diversity: collective benefits!

Introduction: The knowledge complementarity work (experiential, clinical and theoretical) is a key ingredient of the Recovery College (RC) model (Repper and Perkins, 2017). In a Quebec RC, a team of trainers, accompanied by a resource person, co-produced a training course on eating attitudes and behaviors. With a committee of experts in knowledge complementarity, the team put in place an innovative process of co-production and co-validation. The aim of this presentation is to illustrate the co-production and co-validation process established specifically for this training course, as well as the benefits gained.

 

Methods: The teams of trainers deployed a two-stage process: co-production and co-validation. 1) Co-production stage: A collaborative work process, alternating between periods of collective work (trainers and resource person) and periods of independent work (trainers only), enabled the course to be co-produced. 2) Co-validation stage: To ensure validation of the course, a committee of experts in knowledge complementarity (including the training team) met for three periods of collective work. Various work-sharing, power-sharing, speaking-up, work preparation and structuring practices were implemented to bring out the full potential of all knowledge.

 

Results: Trainers report that they have learned and feel that co-production and co-validation process supports their recovery journey. They felt recognized and validated in their expertise.  Members of the expert committee report having learned from each other. While some people were unsure of their individual contribution, the sharing of experiential knowledge gave them a sense of collective contribution. 

 

Conclusion: Knowledge complementarity is an important element of co-production and co-partnership practices for the development of healthcare initiatives (Boivin et al., 2022; Loignon et al., 2022). This co-production and co-validation process deployed in RC maximizes the contribution of all those involved, regardless of their expertise, and ensures the integration of knowledge. These processes can be useful in other contexts than RC.