Background The resilience, mental health, and wellbeing of paramedics is poor, even compared to other healthcare professionals. Student paramedics face a myriad of potential stressors during clinical placement. Curricula needs to consider how to help student paramedics cope with their experiences during placement and give them skills to cope with the stressors of the paramedic role once qualified. Peer support has been documented as a common informal coping strategy amongst paramedics, and evidence supports its use to buffer poor wellbeing. This study qualitatively evaluates the CARES Skills Framework, a structured peer support model, piloted in student paramedics at a single UK university.

Methods A convenience sample of 35 second- and third-year student paramedics were recruited from a single Paramedic Science programme who undertook the CARES Skills Framework. A modified nominal group technique was used to collect data. Qualitative data was ranked by participant voting. Data were analysed using Braun and Clarke’s Reflexive Thematic Analysis framework. Participant ranking was pooled to give a hierarchy of themes.

Results The qualitative analysis highlighted three themes from the paramedic students’ feedback. ‘Shared experience’ included participants feeling like they were not alone, feeling supported from others in the same situation, and having their feelings validated. ‘Safe space’ was typified by being able to be open and honest about feelings without judgement and developing trust with peers. ‘Structure of CARES’ highlighted the view that the structure of the session could be more flexible in terms of time and content.

Conclusion This study highlighted that participants experienced many of the wider benefits of peer support in the literature, such as connectedness, having a safe space and having feelings validated. There is potential for the CARES Skills Framework to be utilised to support student paramedics’ wellbeing. However, this was a small study conducted at one university, so further research is needed to understand its’ generalisability and optimal structure.