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Facing the Silent Crisis: Suicidal Ideation and Suicide in the Nursing Profession
Alyssa M Schutz1, Susan McKee2, Paul Thomas Clements3
1Alyssa M. Schutz, MSN APRN FNP-C PMHNP-BC, College of Nursing, Texas A&M University, Bryan, TX, USA.
Background:
This manuscript explores the silent yet urgent crisis of suicidal ideation and suicide within the nursing profession. Despite being one of the most trusted and essential health care roles, nurses face disproportionately high risks for psychological distress, moral injury, and suicide.
Aims:
The paper aims to synthesize existing evidence on prevalence, risk factors, and theoretical frameworks to guide prevention and intervention efforts, while emphasizing the critical need for trauma-informed, organizational, and policy-level responses.
Methods:
Using Joiner's Interpersonal Theory of Suicide, the Job Demand-Control-Support (JDCS) model, and trauma-informed care (TIC) principles, the manuscript illustrates how feelings of burdensomeness, thwarted belonging, and exposure to trauma converge to elevate suicide risk.
Results:
Key contributing factors to nurse suicide include chronic occupational stress, compassion fatigue, workplace bullying, moral distress, and limited autonomy, all compounded by a pervasive stigma around mental health help-seeking. A poignant case study underscores how institutional silence and lack of systemic support following medical errors can lead to devastating outcomes. Barriers such as fear of licensure consequences and lack of confidential services further discourage early intervention.
Conclusions:
The suicide crisis among nurses necessitates a comprehensive, multi-level response. Nurse leaders must foster psychologically safe environments, promote peer support, and integrate mental health education into all levels of practice. System-level changes-such as confidential reporting systems, national suicide surveillance, licensure reform, and culturally competent outreach-are essential to prevent further loss. Future research must examine longitudinal risk trajectories, intervention efficacy, and artificial intelligence (AI)-driven early warning tools tailored to the nursing workforce.
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