Security Measures to Protect Healthcare Workers and Patients Against Violence in Nursing Environments: A Comprehensive Review
Abstract
Background: Workplace violence against nurses is a critical global public health and occupational hazard. Ranging from verbal abuse to physical assault, the consequences of WPV are severe physical and psychological injuries, burnout, high staff turnover, and diminished quality of care for patients. High-risk areas include emergency and psychiatric units.
Aim: This review aims to synthesise literature from 2015 to 2025 and establish the effectiveness of various security measures instituted in clinical environments with the aim of protecting nurses and patients from violence.
Methods: A systematic search of PubMed, CINAHL, PsycINFO, and Scopus was conducted for peer-reviewed studies from 2015 to 2024 using keywords related to the topic, including "workplace violence," "nurses," "intervention," and "security measures." A total of 40 qualifying quantitative, qualitative, and mixed-methods studies were included and analyzed using the method of narrative synthesis.
Results: Interventions were categorized as primary (prevention), secondary (response), and tertiary (post-event) strategies. The most effective primary measures included comprehensive violence prevention programs, de-escalation training, and environmental designs, such as panic buttons. Secondary measures, including emergency response teams, were effective when deployed promptly. Tertiary support, such as debriefing and counseling, was crucial for mitigating long-term effects. Major implementation barriers included inconsistent training, underreporting, and cultural acceptance of violence.
Conclusions: What works is an integrated, multicomponent strategy that incorporates proactive, responsive, and supportive interventions. From the leadership perspective, a safety culture should be developed that emphasizes prevention, reporting, and support of staff. Recommendations for future research include standardization of outcomes, longitudinal analysis, and consideration of predictive technologies such as AI.
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Authors
Copyright (c) 2025 Khalid Tamim Aldawsari, Mujib Ali Al-Tamim, Abdulrahman Mubarak Aldawsari, Mohammed Mubarak Al-Shuraidah, Mihmas Saud Fahd Al Dawsari, Mohammed Majed Mohammed Al-Rashed Al-Dosari, Hadi Mohsen Mohamad Algarnin
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