Abstract
Background Social difficulties may add to the psychological burden experienced by cancer patients. Therefore identifying social difficulties in routine oncology practice may help prevent or alleviate distress. The Social Difficulties Inventory (SDI) is a short questionnaire developed for assessing social difficulties in cancer patients. Although well-validated, not enough is known about the clinical meaning and utility of the instrument or whether the items can be meaningfully summed to form a summary index of “Social Distress”. Purpose To determine, using Rasch analysis, whether the SDI could be used as a summary index of social distress specifically examining three fundamental criteria: item fit, unidimensionality and item invariance. Methods The Partial Credit Model was applied to a heterogeneous sample of cancer patients (n = 609) who had completed the SDI. Results Five items were identified as misfitting (infit mean square ≥ 1.3 and standardised t-statistic ≥ 2) and excluded from the subsequent analysis. The remaining items formed a unidimensional interval scale with no additional factors identified in a principal components analysis of the residuals. No differential item functioning was observed for age, gender, diagnosis, extent of disease or social deprivation. The 16-item SDI can be summed to produce an overall index of social distress, facilitating routine identification of social difficulties. Subsequent work is needed to evaluate whether the instrument is able to identify patients with high levels of social distress requiring intervention.
Similar content being viewed by others
References
MORI (1992). The social impact of cancer: Research study conducted for CANCER relief Macmillan Fund. London: Cancer Relief Macmillan Fund.
Wright, E. P., Kiely, M. A., Lynch, P., Cull, A., & Selby, P. J. (2002). Social problems in oncology. British Journal of Cancer, 87, 1099–1104.
Wright, P., Smith, A., Booth, L., Winterbottom, A., Kiely, M., Velikova, G., & Selby, P. (2005). Psychosocial difficulties, deprivation and cancer: three questionnaire studies involving 609 cancer patients. British Journal of Cancer, 93, 622–626.
Engel, G. L. (1977). The need for a medical model: A challenge for biomedicine. Science, 196, 129–136.
World Health Organization (2001). International classification of functioning, disability and health (ICF). Geneva: WHO.
National Institute for Clinical Excellence (2004). Guidance on cancer services improving supportive and palliative care for adults with cancer. London: National Health Service.
Newell, S., Girgis, A., Sanson-Fisher, R. W., & Stewart, J. (1997). Are touchscreen computer surveys acceptable to medical oncology patients? Journal of Psychosocial Oncology, 15, 37–46.
Velikova, G., Wright, E. P., Smith, A. B., Cull, A., Gould, A., Forman, D., Perren, T., Stead, M., Brown, J., & Selby, P. (1999). Automated collection of quality-of-life data: a comparison of paper and computer touch-screen questionnaires. Journal of Clinical Oncology, 17, 998–1007.
Wright, E. P., Selby, P. J., Crawford, M., Gillibrand, A., Johnston, C., Perren, T. J., Rush, R., Smith, A., Velikova, G., Watson, K., Gould, A., & Cull, A. (2003). Feasibility and compliance of automated measurement of quality of life in oncology practice. Journal of Clinical Oncology, 21, 374–382.
Wright, E. P., Kiely, M., Johnston, C., Smith, A. B., Cull, A., & Selby, P. J. (2005b). Development and evaluation of an instrument to assess social difficulties in routine oncology practice. Quality of Life Research, 14, 373–386.
Rasch, G. (1980). Probabilistic models for some intelligence and attainment test. Chicago: University of Chicago Press.
Bjorner, J. B., Petersen, M. A., Groenvold, M., Aaronson, N., Ahlner-Elmqvist, M., Arraras, J. I., Bredart, A., Fayers, P., Jordhoy, M., Sprangers, M., Watson, M., & Young, T. (2004). Use of item response theory to develop a shortened version of the EORTC QLQ-C30 emotional functioning scale. Quality of Life Research, 13, 1683–1697.
Lai, J.-S., Cella, D., Chang, C.-H., Bode, R. K., & Heinemann, A. W. (2003). Item banking to improve, shorten and computerize self-reported fatigue: An illustration of steps to create a core item bank from the FACIT-Fatigue Scale. Quality of Life Research, 12, 485–501.
Smith, A. B., Wright, E. P., Rush, R., Stark, D., Velikova, G., & Selby, P. J. (2006). Rasch analysis of the dimensional structure of the hospital anxiety and depression scale. Psycho-Oncology, 15, 817–827.
Carstairs, V., & Morris, R. (1991). Deprivation in Scotland. Aberdeen: Aberdeen University Press.
Census Dissemination Unit. (2004). Pre-calculated deprivation scores. http://www.census.ac.uk/cdu/.
Wright, B. D., Linacre, J. M., Gustafson, J.-E., & Martin-Loef, P. (1994). Reasonable mean-square fit values. Rasch Measurement Transactions, 8, 370.
Smith, R. M., Schumacker, R. E., & Bush, M. J. (1998). Using item mean squares to evaluate fit to the Rasch model. Journal of Outcome Measure, 2, 66–78.
Bond, T. G., & Fox, C. M. (2001). Applying the Rasch model: Fundamental measurement in the human sciences. London: Lawrence Erlbaum Associates.
Stucki, G., Daltroy, L., Katz, J. N, Johannesson, M., & Liang, M. H. (1996). Interpretation of change scores in ordinal clinical scales and health status measures: The whole may not equal the sum of the parts. Journal of Clinical Epidemiology, 49, 711–717.
Linacre, J. M. (2005). A user’s guide to Winsteps/Ministeps Rasch-model programs. Chicago: MESA Press.
Smith, R. M., & Suh, K. K. (2003). Rasch fit statistics as a test of the invariance of item parameter estimates. Journal of Applied Measurement, 4, 153–163.
Smith, E. V. (2002). Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals. Journal of Applied Measurement, 3, 205–231.
Petersen, M. A., Groenvold, M., Bjorner, J. B., Aaronson, N., Conroy, T., Cull, A., Fayers, P., Hjermstad, M., Sprangers, M., & Sullivan, M. (2003). Use of differential item functioning analysis to assess the equivalence of translations of a questionnaire. Quality of Life Research, 12, 373–385.
Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47, 149–174.
Acknowledgements
The authors would like to express their thanks to the patients who completed the questionnaires and interviews, and participated in the focus groups, as well as the team of research assistants who collected the data.
Author information
Authors and Affiliations
Corresponding author
Additional information
Peter Selby and Galina Velikova are joint senior authors.
Appendix
Appendix
Rights and permissions
About this article
Cite this article
Smith, A.B., Wright, P., Selby, P. et al. Measuring social difficulties in routine patient-centred assessment: a Rasch analysis of the social difficulties inventory. Qual Life Res 16, 823–831 (2007). https://doi.org/10.1007/s11136-007-9181-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11136-007-9181-9