Orientation: Peer support and resilience are crucial for mental health, particularly in high-stress occupations such as healthcare and emergency services. Existing interventions primarily focus on reactive measures, leaving a gap in proactive mental health strategies.

Research purpose: This study aimed to investigate the effectiveness of the Resilience First Aid (RFA) programme, incorporating the Predictive 6 Factor Resilience (PR6) model and the ALL Protocol, in enhancing resilience and peer support.

Motivation for the study: There is a pressing need for primary prevention strategies to address the growing mental health challenges in high-stress professions. These challenges include burnout, post-traumatic stress disorder (PTSD), and suicide, among others. This study addresses the knowledge gap by exploring a strength-based, proactive approach to peer support.

Research approach/design and method: A literature review was conducted to examine gaps in peer support and explore the theoretical framework of RFA. The study draws on neurobiological insights and integrates psychotherapeutic principles to develop a resilience-focused intervention.

Main findings: Resilience First Aid training significantly improved participants’ personal resilience, peer support skills and ability to recognise suicide risk factors. The ALL Protocol facilitated emotional regulation and constructive problem-solving in peer support interactions, aligning with neuroscience-based insights.

Implications for practice: Implementing RFA in high-stress environments could enhance workforce resilience and reduce the prevalence of acute mental health crises. The programme’s structured, proactive approach addresses current gaps in mental health support systems.

Contribution/value-add: This study contributes by presenting a comprehensive, proactive model for peer support and resilience, offering a structured conversational tool (ALL Protocol) that can be applied across various professional settings.

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Journal of Applied Neurosciences    |    ISSN: 2959-5118 (PRINT)    |    ISSN: 2958-0951 (ONLINE)