Conectar
To synthesise evidence on the self-perceived consequences of workplace violence (WPV) among male nurses in hospital care settings.
Mixed-methods systematic review (PROSPERO: CRD420251041864).
Systematic searches were performed in PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, and China Biomedical Database. Quantitative, qualitative, and mixed-methods studies on registered male nurses were included. Methodological quality was assessed using the Mixed Methods Assessment Tool 2018. Data synthesis followed the Joanna Briggs Institute convergent integrated approach.
Six databases were searched from their inception to April 30, 2025.
Twenty six studies (18 quantitative, 6 qualitative, and 2 mixed-methods) from 12 countries (n = 2354 male nurses; 7 in psychiatric departments, 4 in emergency departments, 2 in psychiatric hospitals, 1 in an ICU, 1 in an operating room, and 11 unspecified department studies in hospital nursing settings) were included. Six themes emerged: (1) Physical health damage; (2) Mental health trauma; (3) Impediments to Career Advancement; (4) Deterioration of working environment and social relations; (5) Impaired Quality of Patient Care; and (6) Deficiencies in Violence Coping Mechanisms and Potential Risks.
WPV inflicts multidimensional harm on male nurses, spanning their health, career, social well-being, and care quality, compounded by systemic underreporting.
Urgent interventions are needed, including gender-sensitive training, improved reporting systems, mental health support, and safe workplaces. Addressing WPV is vital for nurse retention and patient safety.
This review highlights under-studied WPV toward male nurses, revealing profound personal and professional impacts. It informs healthcare policymakers, administrators, and clinicians, urging gender-inclusive prevention strategies to protect nurses and enhance global care quality.
This review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines.
No patient or public contribution was involved in this systematic review.
To investigate the risk factors associated with occipital pressure injury in patients with craniocerebral injury and to develop a risk prediction model for assessing the risk of occipital pressure injury in patients in this population.
We conducted a prospective cohort study with descriptive analysis. A cohort of 455 patients diagnosed with craniocerebral injury and treated in our neurosurgery department and NSICU of our hospital, who met the criteria, were selected for this study. We collected the clinical data in the neurosurgery ward and Neurosurgical Intensive Care Unit (NSICU) from October 2022 to September 2024. Using R randomisation, we established: Test group (n = 324), validation group (n = 131). Then we performed both univariate and multivariate regression analysis to identify the independent risk factors of occipital pressure injury and developed a predictive model based on these findings. H-L test (Hosmer-Lemeshow test) was used to evaluate the accuracy and specificity of the model.
Among the 455 patients with craniocerebral injury, 324 were randomly selected into the test group, within which 42 developed occipital pressure injuries, representing a 12.96% incidence rate. Univariate analysis showed that there were significant differences (p < 0.05) between terms of gender, Braden scale score, Glasgow score, APACHE II score, NRS2002, Barthel scale, presence of edema, use of vasoactive drugs, use of mechanical ventilator, ICU stay length, MDRO infection, hair friction, use of head circular dressing, surgical interventions, drainage tube placement, surgery duration, volume of red blood cell infusion and length of using mechanical ventilation. Multivariate logistic regression analysis showed that gender, APACHE II score, length of using mechanical ventilation, and use of head circular dressing were independent risk factors for the development of occipital pressure injuries. A nomogram predictive model was formulated based on these factors and demonstrated excellent discriminative ability (AUC = 0.888).
The occipital pressure injury risk predictive model for patients with craniocerebral injury performed strong predictive capacity in this study. It provides theoretical guidance for early formulation of predictive intervention strategies. We prepared this article in accordance with the STROBE checklist.
FreshRSS 