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DO PARTICIPANTS UNDERSTAND A STATED PREFERENCE HEALTH SURVEY? A QUALITATIVE APPROACH TO ASSESSING VALIDITY

Published online by Cambridge University Press:  21 April 2004

Patricia Kenny ,
Jane Hall ,
Rosalie Viney  and
Marion Haas
Patricia Kenny
Affiliation:
University of Technology, Sydney
Jane Hall
Affiliation:
University of Technology, Sydney
Rosalie Viney
Affiliation:
University of Technology, Sydney
Marion Haas
Affiliation:
University of Technology, Sydney
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Abstract

Objectives: Examine the validity of using a self-completed Stated Preference Discrete Choice Modeling (SPDCM) questionnaire to measure parents' preferences for vaccinating their children against varicella.

Methods: A qualitative approach was used to assess the way parents understood the technical information in the questionnaire and the factors they considered to be important to the immunization decision. After completion of the SPDCM questionnaire, thirty-four participants completed a semistructured interview by telephone. Interview transcripts were analyzed by using content analysis. Comparisons were then made with the SPDCM questionnaire results.

Results: The technical information used to describe the program attributes appeared to be used appropriately by participants, although their explanations indicated that their understanding did not always come from the questionnaire information. Only one participant appeared to misunderstand the stated preference task, and a small number thought that the complexity and length should be reduced. The results of analysis of the questionnaire data were supported by the qualitative study, with the notable features of the model being reflected in the views commonly expressed about the immunization decision. Several additional factors were identified as important to the choice, including beliefs about vaccination generally and perceptions of the seriousness of varicella.

Conclusions: Although more research is required to investigate the validity of SPDCM for the measurement of preferences in health care, this study supports the validity of its use in childhood immunization where parents are familiar with the decision context.

Keywords

Stated preference discrete choice modelingValidityQualitative methodsImmunization
Type
GENERAL ESSAYS
Information
International Journal of Technology Assessment in Health Care , Volume 19 , Issue 4 , December 2003 , pp. 664 - 681
Copyright
© 2004 Cambridge University Press

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References

Australian Bureau of Statistics. 2000 Transition from education to work. Report No.: 6227.0. Canberra: Australian Bureau of Statistics
Australian Bureau of Statistics. 2001 Australian social trends. Report No.: 4102.0. Canberra: Australian Bureau of Statistics
Bennett J, Adamowicz V. 2001 Some fundamentals of environmental choice modelling. In: Bennett J, Blamey R, eds. The choice modelling approach to environmental valuation. Cheltenham: Edward Elgar
Bennett J, Blamey R. 2001 The strengths and weaknesses of environmental choice modelling. In: Bennett J, Blamey R, eds. The choice modelling approach to environmental valuation. Cheltenham: Edward Elgar
Booske BC, Sainfort F, Hundt AS. 1999 Eliciting consumer preferences for health plans. Health Serv Res. 34: 839- 854.Google Scholar
Bowling A, Ebrahim S. 2001 Measuring patients' preferences for treatment and perceptions of risk. Qual Health Care. 10: i2- i8.Google Scholar
Bryan S, Buxton M, Sheldon R, Grant A. 1998 Magnetic resonance imaging for the investigation of knee injuries: An investigation of preferences. Health Econ. 7: 595- 603.Google Scholar
Bryan S, Gold L, Sheldon R, Buxton M. 2000 Preference measurement using conjoint methods: An empirical investigation of reliability. Health Econ. 9: 385- 395.Google Scholar
Hall J, Kenny P, King M et al. 2002 Using stated preference discrete choice modelling to evaluate the introduction of varicella vaccination. Health Econ. 11: 457- 465.Google Scholar
Halloran ME, Cochi SL, Lieu TA, Wharton M, Fehrs L. 1994 Theoretical epidemiologic and morbidity effects of routine varicella immunization of preschool children in the United States. Am J Epidemiol. 140: 81- 104.Google Scholar
Jan S, Mooney G, Ryan M, Bruggemenn K, Alexander K. 2000 The use of conjoint analysis to elicit community preferences in public health research: A case study of hospital services in south Australia. Aust N Z J Public Health. 24: 64- 70.Google Scholar
Louviere J, Hensher D, Swait J. 2000 Stated choice methods: Theory methods and applications. Melbourne: Cambridge University Press
Mallinson S. 2002 Listening to participants: A qualitative assessment of the short-form 36 health status questionnaire. Soc Sci Med. 54: 11- 21.Google Scholar
Paterson C, Britten N. 2000 In pursuit of patient-centred outcomes: A qualitative evaluation of the “measure yourself medical outcome profile.” J Health Serv Res Policy. 5: 27- 36.Google Scholar
Patton MQ. 1990 Qualitative evaluation and research methods. 2nd ed. Newbury Park, California: Sage
Ryan M, Bate A, Eastmond CJ, Ludbrook A. 2001 Use of discrete choice experiments to elicit preferences. Qual Health Care. 10: i55- i60.Google Scholar
Ryan M, Hughes J. 1997 Using conjoint analysis to assess women's preferences for miscarriage management. Health Econ. 6: 261- 273.Google Scholar
Ryan M, McIntosh E, Shackley P. 1998 Methodological issues in the application of conjoint analysis in health care. Health Econ. 7: 373- 378.Google Scholar
Scientific Software Development. 1997 Atlas/ti visual qualitative data analysis management theory building: User's guide and reference. Berlin: Scientific Software Development
Tversky A, Kahneman D. 1982 Judgment under uncertainty: Heuristics and biases. In: Kahneman D, Slovic P, Tversky A, eds. Judgment under uncertainty: Heuristics and biases. Cambridge: Cambridge University Press
Van der Pol M, Cairns J. 1998 Establishing patient preferences for blood transfusion support: An application of conjoint analysis. J Health Serv Res Policy. 3: 70- 76.Google Scholar
Viney R, Lancsar E, Louviere J. 2002 Discrete choice experiments to measure consumer preferences for health and healthcare. Expert Rev Pharmacoeconomics Outcomes Res. 2: 319- 326.Google Scholar