Determinants of preferences for genetic counselling in Jewish women

Fam Cancer. 2006;5(2):159-67. doi: 10.1007/s10689-005-3871-7.


Introduction: Patient preferences are central to the economic appraisal of health services. Cancer genetic services are relatively new, and little is known about clients' preferences. We sought to determine clients' preferences for genetic service delivery, and to identify factors that predict those preferences.

Methods: We studied female participants in the Australian Jewish Breast Cancer Study who were offered a test for ancestral mutations in the BRCA1 and BRCA2 genes. Questionnaires, asking respondents to rank their preferences for functions, or attributes, of genetic counselling were received from 256 women (76% response rate).

Results: Sixty-two per cent of the respondents gave their highest preference for information on cancer and genetic risk; 19% gave it to breast and ovarian cancer surveillance; 14% gave it to preparation for testing; and, 5% gave it to direction with decision making. Most ranked direction as their least preferred attribute (53%). Women with a strong cancer family history were less likely to give highest preference to information (52%) and more likely to give highest preference to preparation for testing (22%) (P=0.04; 0.01, respectively). Women with a university degree were less likely to give highest preference to surveillance (15%) (P=0.04).

Conclusion: Most women offered testing had highest preference for information and lowest preference for direction. We have identified factors that predict highest preference for information, preparation, and surveillance attributes. Understanding preferences and their predictors may assist cancer genetic services to provide clients with greater benefits from counselling.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Breast Neoplasms / genetics*
  • Female
  • Genes, BRCA1*
  • Genes, BRCA2*
  • Genetic Counseling*
  • Humans
  • Logistic Models
  • Middle Aged
  • Patient Satisfaction*