Measuring quality of life in autistic adults: the reliability and validity of the Brief Version of the World Health Organization Quality of Life scale

David Mason, J. Rodgers, Deborah Garland, Colin Wilson, J. Parr, H. McConachie
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引用次数: 2

Abstract

Background: Measurement of the Quality of Life (QoL) of autistic adults is receiving increasing empirical attention. The World Health Organisation (WHO) QoL measure (WHOQoL-BREF) has been utilised in several studies. Autistic adults report significantly lower QoL compared to neurotypical adults across several domains. However, no studies have investigated the suitability of WHOQoL-BREF as a tool to measure the QoL of autistic adults. Methods: This study explored the validity and reliability of WHOQoL-BREF with a mixed methods approach. Quantitatively, structural validity was explored by an exploratory factor analysis of WHOQoL-BREF data from 352 autistic adults aged 18-80 years. Qualitatively, four discussion groups (n=20 autistic people) were conducted to explore the face validity of the items of WHOQoL-BREF. Results: The five factor structure was conceptually similar to the WHO formulation of QoL, with adequate to good internal consistency of domains; however, some items loaded in an unexpected way. The reasons for these unexpected loadings were explored in the transcripts from the discussion groups. Conclusions: The findings suggest that the WHOQoL-BREF has acceptable validity and reliability for use with autistic adults; however caution is needed when interpreting data from the social domain and some other items
测量自闭症成年人的生活质量:世界卫生组织生活质量量表简本的可靠性和有效性
背景:自闭症成年人生活质量(QoL)的测量正受到越来越多的实证关注。世界卫生组织(世界卫生组织)生活质量测量(WHOQoL-BREF)已用于多项研究。在几个领域,自闭症成年人的生活质量明显低于神经正常成年人。然而,没有研究调查WHOQoL BREF作为衡量自闭症成年人生活质量的工具的适用性。方法:采用混合方法探讨WHOQoL BREF的有效性和可靠性。从数量上讲,通过对352名18-80岁自闭症成年人的WHOQoL BREF数据进行探索性因素分析,探讨了结构有效性。定性地,我们进行了四个讨论小组(n=20名自闭症患者)来探索WHOQoL BREF项目的面孔有效性。结果:五因素结构在概念上与世界卫生组织的QoL配方相似,具有足够的内部一致性;但是,有些项目以意外的方式加载。讨论小组的记录中探讨了这些意外负载的原因。结论:研究结果表明,WHOQoL BREF对自闭症成年人的使用具有可接受的有效性和可靠性;然而,在解释来自社交领域和其他项目的数据时需要谨慎
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