02211nas a2200301   4500000000100000008004100001653000900042653002300051653001800074653001800092653002000110653001300130100001800143700001800161700001500179700001300194700001400207700001400221700001400235700001500249700001300264700001400277245018000291856004800471490000700519520136900526022001401895       2018                            d10aPROM10aMeasuring outcomes10aMental Health10aMixed methods10aQuality of Life10aRecovery1 aKeetharuth AD1 aTaylor Buck E1 aAcquadro C1 aConway K1 aConnell J1 aBarkham M1 aCarlton J1 aRicketts T1 aBarber R1 aBrazier J00aIntegrating qualitative and quantitative data in the development of outcome measures: The case of the recovering quality of life (ReQoL) measures in mental health populations.  uhttp://www.mdpi.com/1660-4601/15/7/1342/pdf0 v153 a<p>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.</p>
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