Coaching for recovery: a quality improvement project in mental healthcare

Approximately one in four adults in the UK will experience a mental health difficulty at some point in their life. This figure is approximately 400 million people worldwide.[1] Depression alone is currently estimated to cost the UK 1.7% of GDP and is one of the largest causes of ill health in the world.[2] For conditions like psychosis, evidence tells us that people have poorer quality of life outcomes, are more likely to die early, become obese, smoke, be unemployed, and have long term physical conditions than average.[3] People's social situation is also likely to be more complex, with housing needs, social isolation, stigma, and poverty.[4] All of these factors can make it hard for a person with a long-term mental health condition, or those supporting them, to hold onto a sense of hope that positive change is possible or that “recovery” towards a life that holds optimum meaning to them is achievable. An innovative “pop up” Recovery College model was co-produced, delivered, and evaluated by a team of people with lived experience of mental health difficulties, known as peer trainers. The Recovery College offered courses containing the best evidence-based knowledge about recovery in mental health, self-care and self-management. Each learning session included theory, personal testament from peer trainers, and volunteers and demonstrations of practical self-care skills and techniques. The courses were open to people experiencing mental health difficulties, their families, friends, and professionals. After the college course finished each student was offered up to three individual coaching sessions to help support putting the lessons learnt from the college into practice. The project aimed to test whether this innovative educational and coaching model could offer hope, knowledge and practical skills in self-management to support resilience and recovery. The project was underpinned by quality improvement methodologies to develop, deliver, and refine the model.