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PROTECT: Relational safety based suicide prevention training frameworks.

Manaan Kar RayMarianne WyderDavid CromptonAntonis A KousoulisArensman EllaSepehr HafiziTine Van BortelChiara Lombardo
Published in: International journal of mental health nursing (2019)
Preventing suicide is a global priority, and staff training is a core prevention strategy. However, frontline pressures make translating training into better care and better outcomes difficult. The aim of the paper was to highlight challenges in suicide risk assessment and management and introduce training frameworks to assist with mindful practice so professionals can strike a balance between risk and recovery. We combined the scientific literature with contemporary practice from two successful initiatives from Cambridgeshire, UK: 333 - a recovery-oriented model of inpatient/community crisis care and PROMISE - a programme to reduce coercion in care by enhancing patient experience. The resulting PROTECT (PROactive deTECTion) frameworks operationalize ongoing practice of relational safety in these programmes. PROTECT is a combination of novel concepts and adaptations of well-established therapeutic approaches. It has four training frameworks: AWARE for reflection on clinical decisions; DESPAIR for assessment; ASPIRE for management; and NOTES for documentation. PROTECT aims to improve self-awareness of mental shortcuts and risk-taking thresholds and increase rigour through time-efficient cross-checks. The training frameworks should support a relational approach to self-harm/suicide risk detection, mitigation, and documentation, making care safer and person-centred. The goal is to enthuse practitioners with recovery-oriented practice that draws on the strengths of the person in distress and their natural circle of support. It will provide the confidence to engage in participatory approaches to seek out unique individualized solutions to the overwhelming psychological pain of suicidal distress. Future collaborative research with people with lived and carer experience is needed for fine-tuning.
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