Evaluating the role of Clinical Associate Psychologists within mental health teams across Avon and Wiltshire Mental Health Partnership

Aim: The Clinical Associate Psychologist (CAP) role was developed to support the expansion of psychological workforces in the NHS (NHS Health Education England, 2021). Avon and Wiltshire Mental Health Partnership NHS Trust (AWP) started employing CAPs in May 2021 (BSW Partnership Board, 2021). This service evaluation sought feedback from clients who have worked with CAPs to evaluate the CAP role. Method: 17 CAPs working within adult and older adult services within AWP were approached to identify appropriate clients. 11 CAPs identified 64 clients. A mixed-methods questionnaire was sent to these clients. This questionnaire asked about the client’s overall experiences of working with a CAP, followed by questions exploring therapeutic alliance, benefits to their mental health and suggestions for change. Results: 12 clients completed the questionnaire. Quantitative analysis of the survey found all the clients had a ‘very good’ experience of working with a CAP, felt understood and were happy with how sessions were delivered. The majority of clients felt sessions helped them deal more effectively with their difficulties and that their views were included in care decisions. A thematic analysis of qualitative data found four themes: positive therapeutic alliance, person-centred care, CAPs improving accessibility and empowerment. Discussion: Findings indicate the introduction of CAPs improved access to psychological interventions, in turn reducing waitlists in community settings. Limitations were discussed in reference to the lack of representation from other services within the Trust, thus potentially limiting generalisability. Considerations were made for future service evaluation projects, including gathering feedback from other stakeholders, using a within subject design to gather feedback over a longer period, and adapting the questionnaire to include stakeholder views. These changes would reduce potential for selection bias and improve generalisability.