Psychosocial impact of acute stroke in cancer patients and the role of emergency nursing interventions
Abstract
Advances in cancer detection and treatment have led to a growing population of individuals living with cancer who increasingly experience complex comorbid conditions. Acute stroke represents a particularly disruptive event within this context, occurring against a background of heightened biological vulnerability, psychological distress, and treatment burden. Although cancer patients face an elevated risk of both ischemic and haemorrhagic stroke, the psychosocial consequences of acute stroke in this population remain insufficiently synthesised, particularly within emergency care settings. This narrative review integrates interdisciplinary evidence from oncology, neurology, psychology, and nursing to examine psychological distress, quality of life implications, and psychosocial care needs among cancer patients presenting with acute stroke, with a specific focus on the role of emergency nursing. Using a structured narrative review framework, findings indicate that acute stroke in cancer patients is associated with intense anxiety, fear, uncertainty, loss of control, and communication barriers, often compounded by time-pressured decision making in emergency environments. Stroke-related impairments further disrupt quality of life, social roles, and continuity of cancer treatment, while families experience substantial emotional and decisional burden. Emergency nurses occupy a critical position in recognising distress, facilitating communication, supporting families, and integrating psycho-oncological principles into acute care. This review highlights the need to move beyond a purely biomedical model of emergency stroke management toward a holistic, patient-centred approach that explicitly addresses psychosocial well-being. Embedding psycho-oncology within emergency nursing practice may improve patient experiences and support adaptive coping during one of the most vulnerable phases of the cancer trajectory.
Copyright (c) 2026 Lei Shen, Ganying Huang, Rong Fu, Ting Li, Huijie Yang, Xiping Zhang
This work is licensed under a Creative Commons Attribution 4.0 International License.
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