Women’s priorities towards ovarian cancer testing: a best–worst scaling study

OBJECTIVE: To investigate the importance of key characteristics relating to diagnostic testing for ovarian cancer and to understand how previous test experience influences priorities. DESIGN: Case 1 best–worst scaling embedded in an online survey. SETTING: Primary care diagnostic testing in England and Wales. PARTICIPANTS: 150 women with ovaries over 40 years old living in England and Wales. METHODS: We used best–worst scaling, a preference-based survey method, to elicit the relative importance of 25 characteristics relating to ovarian cancer testing following a systematic review. Responses were modelled using conditional logit regression. Subgroup analysis investigated variations based on testing history. MAIN OUTCOME MEASURES: Relative importance scores. RESULTS: ‘Chance of dying from ovarian cancer’ (0.380, 95% CI 0.26 to 0.49) was the most important factor to respondents, closely followed by ‘test sensitivity’ (0.308, 95% CI 0.21 to 0.40). In contrast, ‘time away from usual activities’ (−0.244, 95% CI −0.33 to −0.15) and ‘gender of healthcare provider’ (−0.243, 95% CI −0.35 to −0.14) were least important to respondents overall. Women who had previously undergone testing placed higher importance on certain characteristics including ‘openness of healthcare providers’ and ‘chance of diagnosing another condition’ at the expense of reduced emphasis on characteristics such as ‘pain and discomfort’ and ‘time away from usual activities’. CONCLUSIONS: The results clearly demonstrated items at the extreme, which were most and least important to women considering ovarian cancer testing. Differences in priorities by testing history demonstrate an experience effect, whereby preferences adapt over time based on evidence and experience. Acknowledging these differences helps to identify underlying barriers and facilitators for women with no test experience as well as shortcomings of current service based on women with experience.