Gregor Liegl1, Inka Wahl2, Anne Berghöfer3, Sandra Nolte4, Christoph Pieh5, Matthias Rose6, Felix Fischer7. 1. Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany; Department for Psychotherapy and Biopsychosocial Health, Danube University Krems, Dr.-Karl-Dorrek-Straße 30, 3500 Krems, Austria. Electronic address: gregor.liegl@charite.de. 2. Department of Psychosomatic Medicine and Psychotherapy, University Medical Center Hamburg-Eppendorf & Schön Klinik Hamburg Eilbek, Martinistraße 52, 20246 Hamburg & Dehnhaide 120, 22081 Hamburg, Germany. 3. Institute for Social Medicine, Epidemiology and Health Economics, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany. 4. Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany; Population Health Strategic Research Centre, School of Health and Social Development, Deakin University, 221 Burwood Highway, Burwood, VIC 3125, Australia. 5. Department for Psychotherapy and Biopsychosocial Health, Danube University Krems, Dr.-Karl-Dorrek-Straße 30, 3500 Krems, Austria. 6. Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany; Department of Quantitative Health Sciences, Outcomes Measurement Science, University of Massachusetts Medical School, 368 Plantation Street, The Albert Sherman Center, Worcester, MA 01605, USA. 7. Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany; Institute for Social Medicine, Epidemiology and Health Economics, Charité Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.
Abstract
OBJECTIVES: To investigate the validity of a common depression metric in independent samples. STUDY DESIGN AND SETTING: We applied a common metrics approach based on item-response theory for measuring depression to four German-speaking samples that completed the Patient Health Questionnaire (PHQ-9). We compared the PHQ item parameters reported for this common metric to reestimated item parameters that derived from fitting a generalized partial credit model solely to the PHQ-9 items. We calibrated the new model on the same scale as the common metric using two approaches (estimation with shifted prior and Stocking-Lord linking). By fitting a mixed-effects model and using Bland-Altman plots, we investigated the agreement between latent depression scores resulting from the different estimation models. RESULTS: We found different item parameters across samples and estimation methods. Although differences in latent depression scores between different estimation methods were statistically significant, these were clinically irrelevant. CONCLUSION: Our findings provide evidence that it is possible to estimate latent depression scores by using the item parameters from a common metric instead of reestimating and linking a model. The use of common metric parameters is simple, for example, using a Web application (http://www.common-metrics.org) and offers a long-term perspective to improve the comparability of patient-reported outcome measures.
OBJECTIVES: To investigate the validity of a common depression metric in independent samples. STUDY DESIGN AND SETTING: We applied a common metrics approach based on item-response theory for measuring depression to four German-speaking samples that completed the Patient Health Questionnaire (PHQ-9). We compared the PHQ item parameters reported for this common metric to reestimated item parameters that derived from fitting a generalized partial credit model solely to the PHQ-9 items. We calibrated the new model on the same scale as the common metric using two approaches (estimation with shifted prior and Stocking-Lord linking). By fitting a mixed-effects model and using Bland-Altman plots, we investigated the agreement between latent depression scores resulting from the different estimation models. RESULTS: We found different item parameters across samples and estimation methods. Although differences in latent depression scores between different estimation methods were statistically significant, these were clinically irrelevant. CONCLUSION: Our findings provide evidence that it is possible to estimate latent depression scores by using the item parameters from a common metric instead of reestimating and linking a model. The use of common metric parameters is simple, for example, using a Web application (http://www.common-metrics.org) and offers a long-term perspective to improve the comparability of patient-reported outcome measures.
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Authors: Gregor Liegl; Barbara Gandek; H Felix Fischer; Jakob B Bjorner; John E Ware; Matthias Rose; James F Fries; Sandra Nolte Journal: Arthritis Res Ther Date: 2017-03-21 Impact factor: 5.156