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

Anju Devianee Keetharuth, Elizabeth Taylor Buck, Catherine Acquadro, Katrin Conway, Janice Connell, Michael Barkham, Jill Carlton, Thomas Ricketts, Rosemary Barber and John Brazier
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Anju Devianee Keetharuth: School of Health and Related Research, University of Sheffield, S14DA Sheffield, UK
Elizabeth Taylor Buck: School of Health and Related Research, University of Sheffield, S14DA Sheffield, UK
Catherine Acquadro: Mapi Research Trust, 27 Rue de la Villette, 69003 Lyon, France
Katrin Conway: Mapi Research Trust, 27 Rue de la Villette, 69003 Lyon, France
Janice Connell: School of Health and Related Research, University of Sheffield, S14DA Sheffield, UK
Michael Barkham: Centre for Psychological Services Research, Department of Psychology, University of Sheffield, S102TN Sheffield, UK
Jill Carlton: School of Health and Related Research, University of Sheffield, S14DA Sheffield, UK
Thomas Ricketts: School of Health and Related Research, University of Sheffield, S14DA Sheffield, UK
Rosemary Barber: School of Health and Related Research, University of Sheffield, S14DA Sheffield, UK
John Brazier: School of Health and Related Research, University of Sheffield, S14DA Sheffield, UK

IJERPH, 2018, vol. 15, issue 7, 1-14

Abstract: 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.

Keywords: measuring outcomes; mental health; mixed methods; PROM; quality of life; recovery (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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