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Measuring depression: comparison and integration of three scales in the GENDEP study

Published online by Cambridge University Press:  09 October 2007

R. Uher ,
A. Farmer ,
W. Maier ,
M. Rietschel ,
J. Hauser ,
A. Marusic ,
O. Mors ,
A. Elkin ,
R. J. Williamson  and
C. Schmael
...Show all authors
R. Uher*
Affiliation:
Medical Research Council (MRC) Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, King's College London, UK
A. Farmer
Affiliation:
Medical Research Council (MRC) Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, King's College London, UK
W. Maier
Affiliation:
Rheinische Friedrich-Wilhelms-Universität Bonn, Germany
M. Rietschel
Affiliation:
Central Institute of Mental Health, Division of Genetic Epidemiology in Psychiatry, Mannheim, Germany
J. Hauser
Affiliation:
Laboratory of Psychiatric Genetics, Department of Psychiatry, Poznan University of Medical Sciences, Poland
A. Marusic
Affiliation:
Institute of Public Health, Ljubljana, Slovenia
O. Mors
Affiliation:
Aarhus University Hospital, Risskov, Denmark
A. Elkin
Affiliation:
Medical Research Council (MRC) Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, King's College London, UK
R. J. Williamson
Affiliation:
Medical Research Council (MRC) Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, King's College London, UK
C. Schmael
Affiliation:
Central Institute of Mental Health, Division of Genetic Epidemiology in Psychiatry, Mannheim, Germany
N. Henigsberg
Affiliation:
Croatian Institute for Brain Research, Medical School, University of Zagreb, Croatia
J. Perez
Affiliation:
Biological Psychiatry Unit and Dual Diagnosis Ward IRCCS, Centro San Giovanni di Dio, FBF, Brescia, Italy
J. Mendlewicz
Affiliation:
Free University of Brussels, Department of Psychiatry, Belgium
J. G. E. Janzing
Affiliation:
Department of Psychiatry, Nijmegen, The Netherlands
A. Zobel
Affiliation:
Rheinische Friedrich-Wilhelms-Universität Bonn, Germany
M. Skibinska
Affiliation:
Laboratory of Psychiatric Genetics, Department of Psychiatry, Poznan University of Medical Sciences, Poland
D. Kozel
Affiliation:
Institute of Public Health, Ljubljana, Slovenia
A. S. Stamp
Affiliation:
Aarhus University Hospital, Risskov, Denmark
M. Bajs
Affiliation:
Croatian Institute for Brain Research, Medical School, University of Zagreb, Croatia
A. Placentino
Affiliation:
Biological Psychiatry Unit and Dual Diagnosis Ward IRCCS, Centro San Giovanni di Dio, FBF, Brescia, Italy
M. Barreto
Affiliation:
Free University of Brussels, Department of Psychiatry, Belgium
P. McGuffin
Affiliation:
Medical Research Council (MRC) Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, King's College London, UK
K. J. Aitchison
Affiliation:
Medical Research Council (MRC) Social, Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, King's College London, UK Division of Psychological Medicine and Psychiatry, Institute of Psychiatry, King's College London, UK
*
*Address for correspondence: R. Uher, PO80 SGDP, Institute of Psychiatry, 16 De Crespigny Park, London SE5 8AF, UK. (Email: [email protected])
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Abstract

Background

A number of scales are used to estimate the severity of depression. However, differences between self-report and clinician rating, multi-dimensionality and different weighting of individual symptoms in summed scores may affect the validity of measurement. In this study we examined and integrated the psychometric properties of three commonly used rating scales.

Method

The 17-item Hamilton Depression Rating Scale (HAMD-17), the Montgomery–Asberg Depression Rating Scale (MADRS) and the Beck Depression Inventory (BDI) were administered to 660 adult patients with unipolar depression in a multi-centre pharmacogenetic study. Item response theory (IRT) and factor analysis were used to evaluate their psychometric properties and estimate true depression severity, as well as to group items and derive factor scores.

Results

The MADRS and the BDI provide internally consistent but mutually distinct estimates of depression severity. The HAMD-17 is not internally consistent and contains several items less suitable for out-patients. Factor analyses indicated a dominant depression factor. A model comprising three dimensions, namely ‘observed mood and anxiety’, ‘cognitive’ and ‘neurovegetative’, provided a more detailed description of depression severity.

Conclusions

The MADRS and the BDI can be recommended as complementary measures of depression severity. The three factor scores are proposed for external validation.

Keywords

Depressionitem response theoryrandomized controlled trialrating scales
Type
Original Articles
Information
Psychological Medicine , Volume 38 , Issue 2 , February 2008 , pp. 289 - 300
Copyright
Copyright © Cambridge University Press 2007

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References

Bagby, RM, Ryder, AG, Schuller, DR, Marshall, MB (2004). The Hamilton Depression Rating Scale: has the gold standard become a lead weight? American Journal of Psychiatry 161, 2163–2177.CrossRefGoogle ScholarPubMed
Baker, F (2001). The Basics of Item Response Theory. ERIC Clearing house on Assessment and Evaluation: University of Maryland College Park, MD.Google Scholar
Bech, P, Cialdella, P, Haugh, MC, Birkett, MA, Hours, A, Boissel, JP, Tollefson, GD (2000). Meta-analysis of randomised controlled trials of fluoxetine v. placebo and tricyclic antidepressants in the short-term treatment of major depression. British Journal of Psychiatry 176, 421–428.Google Scholar
Bech, P, Gram, LF, Dein, E, Jacobsen, O, Vitger, J, Bolwig, TG (1975). Quantitative rating of depressive states. Acta Psychiatrica Scandinavica 51, 161–170.CrossRefGoogle ScholarPubMed
Beck, AT, Ward, CH, Mendelson, M, Mock, J, Erbaugh, J (1961). An inventory for measuring depression. Archives of General Psychiatry 4, 561–571.Google Scholar
Brown, TA (2006). Confirmatory Factor Analysis for Applied Research. Guilford Press: New York.Google Scholar
Browne, C, Schulberg, HC, Madonia, MJ (1995). Assessing depression in primary care practice with the Beck Depression Inventory and Hamilton Rating Scale for Depression. Psychological Assessment 7, 59–65.CrossRefGoogle Scholar
Carmody, TJ, Rush, AJ, Bernstein, I, Warden, D, Brannan, S, Burnham, D, Woo, A, Trivedi, MH (2006). The Montgomery Asberg and the Hamilton ratings of depression: a comparison of measures. European Neuropsychopharmacology 16, 601–611.CrossRefGoogle ScholarPubMed
Edwards, BC, Lambert, MJ, Moran, PW, McCully, T, Smith, KC, Ellingson, AG (1984). A meta-analytic comparison of the Beck Depression Inventory and the Hamilton Rating Scale for Depression as measures of treatment outcome. British Journal of Clinical Psychology 23, 93–99.CrossRefGoogle ScholarPubMed
Elkin, I, Shea, MT, Watkins, JT, Imber, SD, Sotsky, SM, Collins, JF, Glass, DR, Pilkonis, PA, Leber, WR, Docherty, JP (1989). National Institute of Mental Health Treatment of Depression Collaborative Research Program. General effectiveness of treatments. Archives of General Psychiatry 46, 971–982.CrossRefGoogle ScholarPubMed
Embretson, SE, Reise, S (2000). Item Response Theory for Psychologists. Lawrence Erlbaum Associates: Mahwah, NJ.Google Scholar
Evans, KR, Sills, T, DeBrota, DJ, Gelwicks, S, Engelhardt, N, Santor, D (2004). An item response analysis of the Hamilton Depression Rating Scale using shared data from two pharmaceutical companies. Journal of Psychiatric Research 38, 275–284.CrossRefGoogle ScholarPubMed
Faries, D, Herrera, J, Rayamajhi, J, DeBrota, D, Demitrac, M, Potter, WZ (2000). The responsiveness of the Hamilton Depression Rating Scale. Journal of Psychiatric Research 34, 3–10.CrossRefGoogle ScholarPubMed
Feinberg, M, Carroll, BJ, Smouse, PE, Rawson, SG (1981). The Carroll rating scale for depression. III. Comparison with other rating instruments. British Journal of Psychiatry 138, 205–209.Google Scholar
Flora, DB, Curran, PJ (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods 9, 466–491.Google Scholar
Flora, DB, Thissen, D (2002). User's Guide for RTScore. L. L. Thurstone Psychometric Laboratory University of North Carolina: Chapel Hill, NC.Google Scholar
Floyd, FJ, Widaman, KF (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment 7, 286–299.Google Scholar
Gibbons, RD, Clark, DC, Kupfer, DJ (1993). Exactly what does the Hamilton Depression Rating Scale measure? Journal of Psychiatric Research 27, 259–273.CrossRefGoogle ScholarPubMed
Grayson, D, Bridges, K, Cook, D, Goldberg, D (1990). The validity of diagnostic systems for common mental disorders: a comparison between the ID-CATEGO and the DSM-III systems. Psychological Medicine 20, 209–218.CrossRefGoogle ScholarPubMed
Greenberg, RP, Bernstein, RF, Greenberg, MD, Fisher, S (1992). A meta-analysis of antidepressant outcome under ‘blinder’ conditions. Journal of Consulting and Clinical Psychology 60, 664–669.Google Scholar
Gullion, CM, Rush, AJ (1998). Toward a generalizable model of symptoms in major depressive disorder. Biological Psychiatry 44, 959–972.Google Scholar
Hamilton, M (1960). A rating scale for depression. Journal of Neurology, Neurosurgery and Psychiatry 23, 56–62.Google Scholar
Hamilton, M (1967). Development of a rating scale for primary depressive illness. British Journal of Clinical Psychology 6, 278–296.Google ScholarPubMed
Humphreys, LG, Montanelli, RG (1975). An investigation of the parallel analysis criterion for determining the number of common factors. Multivariate Behavioral Research 10, 193–206.Google Scholar
Korszun, A, Moskvina, V, Brewster, S, Craddock, N, Ferrero, F, Gill, M, Jones, IR, Jones, LA, Maier, W, Mors, O, Owen, MJ, Preisig, M, Reich, T, Rietschel, M, Farmer, A, McGuffin, P (2004). Familiality of symptom dimensions in depression. Archives of General Psychiatry 61, 468–474.Google Scholar
Moller, HJ (2001). Methodological aspects in the assessment of severity of depression by the Hamilton Depression Scale. European Archives of Psychiatry and Clinical Neuroscience 251 (Suppl. 2), II13–II20.Google Scholar
Montgomery, SA, Asberg, M (1979). A new depression scale designed to be sensitive to change. British Journal of Psychiatry 134, 382–389.CrossRefGoogle ScholarPubMed
Muthen, LK, Muthen, BO (2006). Mplus User's Guide: Statistical Analysis with Latent Variables, 4th edn.Muthen & Muthen: Los Angeles.Google Scholar
Orlando, M, Sherbourne, CD, Thissen, D (2000). Summed-score linking using item response theory: application to depression measurement. Psychological Assessment 12, 354–359.CrossRefGoogle ScholarPubMed
Prusoff, BA, Klerman, GL, Paykel, ES (1972). Concordance between clinical assessments and patients' self-report in depression. Archives of General Psychiatry 26, 546–552.CrossRefGoogle ScholarPubMed
Rehm, LP, O'Hara, MW (1985). Item characteristics of the Hamilton Rating Scale for Depression. Journal of Psychiatric Research 19, 31–41.Google Scholar
Ruhe, HG, Dekker, JJ, Peen, J, Holman, R, de Jonghe, F (2005). Clinical use of the Hamilton Depression Rating Scale: is increased efficiency possible? A post hoc comparison of Hamilton Depression Rating Scale, Maier and Bech subscales, Clinical Global Impression, and Symptom Checklist-90 scores. Comprehensive Psychiatry 46, 417–427.Google Scholar
Rush, AJ, Trivedi, MH, Carmody, TJ, Ibrahim, HM, Markowitz, JC, Keitner, GI, Kornstein, SG, Arnow, B, Klein, DN, Manber, R, Dunner, DL, Gelenberg, AJ, Kocsis, JH, Nemeroff, CB, Fawcett, J, Thase, ME, Russell, JM, Jody, DN, Borian, FE, Keller, MB (2005). Self-reported depressive symptom measures: sensitivity to detecting change in a randomized, controlled trial of chronically depressed, nonpsychotic outpatients. Neuropsychopharmacology 30, 405–416.CrossRefGoogle Scholar
Samejima, F (1969). Estimation of latent ability using a response pattern of graded responses. Psychometrika Monograph Supplement, No. 17.Google Scholar
Santor, DA, Coyne, JC (2001). Examining symptom expression as a function of symptom severity: item performance on the Hamilton Rating Scale for Depression. Psychological Assessment 13, 127–139.CrossRefGoogle ScholarPubMed
Shafer, AB (2006). Meta-analysis of the factor structures of four depression questionnaires: Beck, CES-D, Hamilton, and Zung. Journal of Clinical Psychology 62, 123–146.Google Scholar
Thissen, D, Chen, WH, Bock, D (2003). MULTILOG 7. SSI Scientific Software International: Lincolnwood, USA.Google Scholar
Williams, JB (1988). A structured interview guide for the Hamilton Depression Rating Scale. Archives of General Psychiatry 45, 742–747.Google Scholar