An introduction to the Rasch measurement model: an example using the Hospital Anxiety and Depression Scale (HADS).

OBJECTIVES To demonstrate the use of Rasch analysis by assessing the appropriateness of utilizing the Hospital Anxiety and Depression Scale (HADS) total score (HADS-14) as a measure of psychological distress. DESIGN Cross-sectional, using Rasch analysis. METHODS The HADS was administered to 296 patients attending an out-patient musculoskeletal rehabilitation program. Rasch analysis was conducted using RUMM2020 software to assess the overall fit of the model, the response scale used, individual item fit, differential item functioning (DIF) and person separation. RESULTS Rasch analysis supported the viability of the HADS-14 as a measure of psychological distress. It showed good person separation, little disordering of the thresholds and no evidence of DIE One anxiety item (item 11) showed some misfit to the model. The residuals patterned into the two subscales (anxiety and depression), but the person estimate derived from these two subscales was not statistically different to that derived from all items taken together, supporting the assumption of unidimensionality. A cut-point of 12 on the HADS-14 identified all cases that were classified as both anxious and depressed on the original individual HADS subscales. CONCLUSIONS The results of Rasch analysis support the use of the HADS-14 as a global measure of psychological distress. The study demonstrates the usefulness of Rasch analysis in assessing the psychometric properties of a scale and suggests that further use of this technique to assess the HADS-14 in other clinical groups is warranted.

[1]  S. Stouffer,et al.  Measurement and Prediction , 1954 .

[2]  D. Altman,et al.  Multiple significance tests: the Bonferroni method , 1995, BMJ.

[3]  H. Wainer,et al.  Differential Item Functioning. , 1994 .

[4]  Higher-order factor analysis of an instrument with dichotomous data. , 2005, Research in nursing & health.

[5]  C. Crombie,et al.  Normative data for the HADS from a large non-clinical sample. , 2001, The British journal of clinical psychology.

[6]  Julie F Pallant,et al.  Assessment of the structure of the Hospital Anxiety and Depression Scale in musculoskeletal patients , 2005, Health and quality of life outcomes.

[7]  G. Masters.  A rasch model for partial credit scoring , 1982 .

[8]  Christian Even,et al.  Three-dimensional structure of the Hospital Anxiety and Depression Scale in a large French primary care population suffering from major depression , 2001, Psychiatry Research.

[9]  R. Lange,et al.  Depressive Response Sets due to gender and culture-based Differential Item Functioning , 2002 .

[10]  D. Razavi,et al.  Screening for Adjustment Disorders and Major Depressive Disorders in Cancer In-Patients , 1990, British Journal of Psychiatry.

[11]  Derek C. Briggs,et al.  An introduction to multidimensional measurement using Rasch models. , 2003, Journal of applied measurement.

[12]  G. Der,et al.  A confirmatory factor analysis of the Hospital Anxiety and Depression scale: comparing empirically and theoretically derived structures. , 2000, The British journal of clinical psychology.

[13]  A. Mykletun,et al.  Hospital Anxiety and Depression (HAD) scale: Factor structure, item analyses and internal consistency in a large population , 2001, British Journal of Psychiatry.

[14]  R. M. Smith,et al.  Dimensionality of an early childhood scale using rasch analysis and confirmatory factor analysis. , 1997, Journal of outcome measurement.

[15]  G. Karabatsos,et al.  The Rasch model, additive conjoint measurement, and new models of probabilistic measurement theory. , 2001, Journal of applied measurement.

[16]  E. Svensson.  Guidelines to statistical evaluation of data from rating scales and questionnaires. , 2001, Journal of rehabilitation medicine.

[17]  J. Linacre,et al.  Sample size and item calibration stability , 1994 .

[18]  Everett V. Smith.  Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals. , 2002, Journal of applied measurement.

[19]  J. Thonnard,et al.  Assessing and Adjusting for Cross-Cultural Validity of Impairment and Activity Limitation Scales Through Differential Item Functioning Within the Framework of the Rasch Model: The PRO-ESOR Project , 2004, Medical care.

[20]  Education Division.  Studies in social psychology in World War II , 1949 .

[21]  D. Andrich.  A rating formulation for ordered response categories , 1978 .

[22]  R. Newell,et al.  Factor structure of the Hospital Anxiety and Depression Scale in individuals with facial disfigurement , 2004 .

[23]  T. T. Haug,et al.  The validity of the Hospital Anxiety and Depression Scale. An updated literature review. , 2002, Journal of psychosomatic research.

[24]  B. Wright,et al.  Best test design , 1979 .

[25]  Colin R. Martin,et al.  A psychometric evaluation of the Hospital Anxiety and Depression Scale in patients diagnosed with end-stage renal disease. , 2004, The British journal of clinical psychology.

[26]  K. Abromeit.  Music Received , 2023, Notes.

[27]  G. Huston.  The Hospital Anxiety and Depression Scale. , 1987, The Journal of rheumatology.

[28]  A. Tennant,et al.  Adaptation of the Functional Independence Measure for use in Turkey , 2001, Clinical rehabilitation.

[29]  Colin R. Martin.  What does the Hospital Anxiety and Depression Scale (HADS) Really Measure in Liaison Psychiatry Settings , 2005 .

[30]  J M Linacre,et al.  Investigating rating scale category utility. , 1999, Journal of outcome measurement.

[31]  Georg Rasch,et al.  Probabilistic Models for Some Intelligence and Attainment Tests , 1981, The SAGE Encyclopedia of Research Design.

[32]  A Hasman,et al.  Likert or Rasch? Nothing is more applicable than good theory. , 1994, Journal of advanced nursing.

[33]  R. M. Smith,et al.  Fit analysis in latent trait measurement models. , 2000, Journal of applied measurement.

[34]  M. Johnston,et al.  Construct validation of the hospital anxiety and depression scale with clinical populations. , 2000, Journal of psychosomatic research.

[35]  D. Cella,et al.  Health status assessment for the twenty-first century: item response theory, item banking and computer adaptive testing , 1997, Quality of Life Research.