Skip to main content
StreamVetree
Sign in
BehaviorStudy2 min read · distilled by Vetree AI

Between awe and despair: recognising risk in veterinary suicide.

May C · The Veterinary record · 1 May 2026

Clinical bottom line

Recognising existential fatigue as a distinct pathway may enable earlier identification and intervention for at-risk veterinary professionals.

Summary

This article by Chris May addresses the critical issue of suicide risk among veterinary professionals, proposing a conceptual framework to identify individuals at heightened risk through recognition of a novel psychological mechanism termed 'existential fatigue.' The veterinary profession has well-documented elevated rates of suicide compared to the general population and many other professions, attributed to factors including access to euthanasia drugs, high occupational stress, compassion fatigue, financial pressures, and the emotional burden of routine euthanasia procedures. May's pathway concept suggests that repeated exposure to morally and emotionally challenging experiences within veterinary practice can progressively erode a clinician's sense of purpose and meaning, culminating in existential fatigue — a state distinct from burnout or depression, though potentially overlapping. This fatigue represents a profound disengagement from the values and motivations that originally drew individuals to the profession. By identifying the stages and markers of this pathway, the framework aims to enable earlier recognition of at-risk colleagues, facilitate timely intervention, and ultimately reduce suicide incidence within the profession. The article underscores the need for workplace cultures that normalize mental health discussions, encourage peer support, and provide accessible psychological resources. This commentary contributes to the growing body of literature advocating for systemic and individual-level approaches to veterinary mental health and suicide prevention.

BehaviorInternal MedicineSmall AnimalLarge Animal

This summary was distilled by AI and may occasionally misinterpret data. Confirm critical details with the primary literature before clinical application.