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A hierarchy of distress: Mokken scaling of the GHQ-30

Published online by Cambridge University Press:  29 January 2008

R. Watson ,
I. J. Deary  and
B. Shipley
R. Watson*
Affiliation:
School of Nursing and Midwifery, The University of Sheffield, UK
I. J. Deary
Affiliation:
Department of Psychology, The University of Edinburgh, UK
B. Shipley
Affiliation:
Department of Psychology, The University of Edinburgh, UK
*
*Address for correspondence: Dr R. Watson, School of Nursing and Midwifery, The University of Sheffield, Sheffield S10 2TN, UK. (Email: roger.watson@sheffield.ac.uk)
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Abstract

Background

Hierarchical cumulative scales are common and informative in psychology. The General Health Questionnaire (GHQ) does not appear to have been subjected to an analysis that examines the hierarchical and cumulative nature of its items. We report an analysis of data from the 30-item GHQ (GHQ-30) as part of the Health and Lifestyle Survey (HALS).

Method

Data from 6317 participants who completed the GHQ-30 as part of the HALS were analysed using the Mokken Scaling Procedure (MSP), which is a computer program that searches polychotomous data for hierarchical and cumulative scales on the basis of a range of diagnostic criteria.

Results

A final scale consisting of nine items from the GHQ-30 was obtained that, according to the criteria for a Mokken scale, was a reliable and very strong scale. The least difficult item in the scale is ‘been (un)able to face up to your problems?’ and the most difficult item is ‘felt that life isn't worth living?'

Conclusions

Items from the GHQ-30 form a short hierarchical and cumulative scale. The majority of these items also appear in the GHQ-12. The nine-item GHQ shows better distribution properties than the GHQ-30 and compares very favourably with the GHQ-12.

Keywords

General healthitem response theoryMokken scaling
Type
Original Articles
Information
Psychological Medicine , Volume 38 , Issue 4 , April 2008 , pp. 575 - 579
Copyright
Copyright © Cambridge University Press 2008

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References

Barkow, K, Heun, R, Üstün, TB, Maier, W (2001). Identification of items which predict later development of depression in primary care. European Archives of Psychiatry and Clinical Neuroscience 251 (Suppl. 2), II21–II26.CrossRefGoogle Scholar
Cox, BD, Blaxter, M, Buckle, ALJ, Fenner, NP, Golding, JF, Gore, M, Huppert, FA, Nickson, J, Roth, M, Stark, J, Wadsworth, MEJ, Whichelow, M (1987). The Health and Lifestyle Survey: A Preliminary Report. Health Promotion Trust: London.Google Scholar
Goldberg, DP, Hillier, VF (1979). A scaled version of the General Health Questionnaire. Psychological Medicine 9, 139–145.CrossRefGoogle ScholarPubMed
Hosenfeld, B, van den Boom, DC, Resing, WCM (1997). Constructing geometric analogies for the longitudinal testing of elementary school children. Journal of Educational Measurement 34, 367–372.CrossRefGoogle Scholar
Kempen, GIJM, Suurmeijer, ThPBM (1991). Factors influencing professional home care utilization among the elderly. Social Science and Medicine 32, 77–81.CrossRefGoogle ScholarPubMed
Kingsott, R, Douglas, N, Deary, I (1998). Mokken scaling of the Epworth Sleepiness Scale items in patients with sleep apnoea/hypopnoea syndrome. Journal of Sleep Research 7, 293–294.CrossRefGoogle Scholar
Mergl, R, Seidscheck, I, Allgaier, A-K, Möller, H-J, Hegerl, U, Henkel, V (2007). Depressive, anxiety, and somatoform disorders in primary care: prevalence and recognition. Depression and Anxiety 24, 185–195.CrossRefGoogle ScholarPubMed
Mokken, RJ, Lewis, C (1982). A nonparametric approach to the analysis of dichotomous item responses. Applied Psychological Measurement 6, 417–430.CrossRefGoogle Scholar
Molenaar, IW, Sijtsma, K (2000). MSP5 for Windows. Groningen: iec ProGAMMA.Google Scholar
Moorer, P, Suurmeijer, TPBM (1994). A study of the unidimensionality and cumulativeness of the MOS Short-Form General Health Survey. Psychological Reports 74, 467–470.CrossRefGoogle ScholarPubMed
Moorer, P, Suurmeijer, ThPBM, Foets, M, Molenaar, IW (2001). Psychometric properties of the RAND-36 among three chronic diseases (multiple sclerosis, rheumatic diseases and COPD) in the Netherlands. Quality of Life Research 10, 637–645.CrossRefGoogle ScholarPubMed
Niemöller, K, van Schuur, W (1983). Stochastic models for unidimensional scaling: Mokken and Rasch. In Data Analysis and the Social Sciences (ed. McKay, D., Schofield, N. and Whiteley, P.), pp. 120–170. Francis Pinter: London.Google Scholar
Ringdall, GI, Jordhøy, MS, Kaasa, S (2003). Measuring quality of palliative care: psychometric properties of the FAMCARE Scale. Quality of Life Research 12, 167–176.CrossRefGoogle Scholar
Sijtsma, K, Debets, P, Molenaar, IW (1990). Mokken scale analysis for polychotomous items: theory, a computer program and an empirical application. Quality and Quantity 24, 173–188.CrossRefGoogle Scholar
Sijtsma, K, Junker, BW (1996). A survey of theory and methods of invariant item ordering. British Journal of Mathematical Statistics and Psychology 49, 79–105.CrossRefGoogle ScholarPubMed
Stouffer, SA, Guttman, L, Suchman, EA, Lazarsfeld, PF, Star, SA, Clausen, JA (1950). Measurement and Prediction, vol. 4. Princeton University Press: Princeton, NJ.Google Scholar
Watson, R (1996). The Mokken scaling procedure (MSP) applied to the measurement of feeding difficulty in elderly people with dementia. International Journal of Nursing Studies 33, 385–393.CrossRefGoogle Scholar
Watson, R, Deary, IJ, Austin, E (2007). Are personality trait items reliably more or less ‘difficult’? Mokken scaling of the NEO-FFI. Personality and Individual Differences 43, 1460–1469.CrossRefGoogle Scholar