Evaluating STORM skills training for managing people at risk of suicide

Aim. This paper reports a study evaluating the Skills Training On Risk Management (STORM) training initiative in three mental health services in the North-West of England, UK. Background. Training for health workers has been widely advocated as a key route to suicide prevention. However, reports of evaluations are scarce in the literature. In previous research, we have demonstrated that the STORM intervention results in acquisition of new skills and can be disseminated in a community setting. Method. The training was delivered during a 6-month period in 2002 by three mental health nurses who were seconded part-time to the project. The quantitative evaluation, which assessed change in attitudes, confidence, acquisition of skills and satisfaction, used a pretest/post-test design, with participants acting as their own controls. Qualitative interviews were conducted with a purposive sample of 16 participants to explore the impact on clinical practice, and with the three trainers at the end of the study. Findings. Data from 458 staff members were collected during a 6-month period. Positive changes in attitudes and confidence were shown, but previous evidence of skill acquisition was not replicated. Qualitative interviews revealed important insights into changes in clinical practice, particularly for less experienced or unqualified nursing staff, but also concerns about the lack of an educational culture to foster and support such interventions in practice within the organizations. Conclusion. STORM training for the assessment and management of suicide risk is both feasible and acceptable in mental health trusts. However, we remain uncertain of its longer-term impact, given the lack of engagement of senior staff in the enterprise and the absence of linked supervision and support from the organizational management to reinforce skill acquisition and development. We consider that regular supervision that links STORM training to actual clinical experience would be the ideal