首页> 美国卫生研究院文献>International Journal of Environmental Research and Public Health >Integrating Qualitative and Quantitative Data in the Development of Outcome Measures: The Case of the Recovering Quality of Life (ReQoL) Measures in Mental Health Populations
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Integrating Qualitative and Quantitative Data in the Development of Outcome Measures: The Case of the Recovering Quality of Life (ReQoL) Measures in Mental Health Populations

机译:将定性和定量数据整合到结果度量的制定中:以心理健康人群的生活质量恢复(ReQoL)度量为例

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摘要

While it is important to treat symptoms, there is growing recognition that in order to help people with mental health problems lead meaningful and fulfilling lives, it is crucial to capture the impact of their conditions on wider aspects of their social lives. We constructed two versions of the Recovering Quality of Life (ReQoL) measure—ReQoL-10 and ReQoL-20—for use in routine settings and clinical trials from a larger pool of items by combining qualitative and quantitative evidence covering six domains. Qualitative evidence was gathered through interviews and focus groups with over 76 service users, clinicians, and a translatability assessment. Psychometric evidence generated from data from over 6200 service users was obtained from confirmatory factor models and item response theory analyses. In this paper we present an approach based on a traffic light pictorial format that was developed to present qualitative and quantitative evidence to a group of service users, clinicians, and researchers to help to make the final selection. This work provides a pragmatic yet rigorous approach to combining qualitative and quantitative evidence to ensure that ReQoL is psychometrically robust and has high relevance to service users and clinicians. This approach can be extended to the development of patient reported outcome measures in general.
机译:尽管治疗症状很重要,但越来越多的人认识到,为了帮助患有精神疾病的人们过上有意义而充实的生活,至关重要的是要了解他们的状况对其社会生活的广泛影响。我们结合了涵盖六个领域的定性和定量证据,构建了两种版本的“生活质量恢复(ReQoL)”度量标准-ReQoL-10和ReQoL-20,用于更大范围的项目的常规设置和临床试验。定性证据是通过与76位服务使用者,临床医生进行的访谈和焦点小组以及可翻译性评估而收集的。从验证性因素模型和项目响应理论分析中获得了来自6200多个服务用户的数据生成的心理计量学证据。在本文中,我们提出了一种基于交通信号灯图形格式的方法,该方法旨在为一组服务用户,临床医生和研究人员提供定性和定量证据,以帮助进行最终选择。这项工作提供了一种务实而严谨的方法,以结合定性和定量证据,以确保ReQoL在心理上具有鲁棒性,并与服务使用者和临床医生高度相关。一般而言,这种方法可以扩展到患者报告结局指标的制定。

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