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Patients' aggressive behaviours towards nurses: Development and psychometric properties of the hospital aggressive behaviour scale- users

机译:患者对护士的攻击行为:医院攻击行为量表的开发和心理特征

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Aim: This article is to report the development and psychometric testing of the Hospital Aggressive Behaviour Scale - Users. Background: Workplace violence is present in many work spheres, but in the healthcare sector, nurses in particular are at more risk due to the close contact they maintain with users and clients and the special characteristics of this relationship. Design: Using qualitative and quantitative methodology, an instrument was applied to a sample of 1,489 nurses from 11 public hospitals. Data collection was carried out in 2010 and 2011. Results: Exploratory factor analysis yielded a 10-item instrument distributed in two factors (non-physical violence and physical violence), which was validated by means of confirmatory factor analysis. Both the resulting questionnaire and the factors identified present high internal consistency and adequate external validity, analysed by means of statistically significant correlations between the Hospital Aggressive Behaviour Scale and job satisfaction, burnout components, and psychological well-being. Conclusions: The results indicate that, in nursing personnel, higher exposure to user violence leads to lower job satisfaction, more emotional exhaustion and more cynicism, and to a lower level of psychological well-being. The instrument developed in this study may be very useful in the sphere of assessment and prevention of psychosocial risks for the early detection of the problem of user violence in its two facets.
机译:目的:本文旨在报告医院积极行为量表(用户)的开发和心理测试。背景:工作场所暴力行为存在于许多工作领域,但在医疗保健领域,尤其是护士,由于他们与用户和客户保持密切联系以及这种关系的特殊特征,其风险更大。设计:使用定性和定量方法,将一种仪器应用于来自11家公立医院的1489名护士的样本。在2010年和2011年进行了数据收集。结果:探索性因素分析产生了一个分布在两个因素(非身体暴力和身体暴力)中的10项工具,并通过验证性因素分析进行​​了验证。问卷调查表和确定的因素均具有较高的内部一致性和足够的外部有效性,并通过医院积极行为量表与工作满意度,倦怠成分和心理健康之间的统计学显着相关性进行分析。结论:结果表明,在护理人员中,较高的使用者暴力暴露导致较低的工作满意度,更多的精神疲惫和玩世不恭,以及较低的心理健康水平。本研究开发的工具在评估和预防社会心理风险方面可能非常有用,可以从两个方面对用户暴力问题进行早期检测。

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