SynthesisBMJ open2022
Women's priorities towards ovarian cancer testing: a best-worst scaling study.
Synthesis in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Comparing patient and healthcare professional preferences for patient-centered integrated care in China: a best-worst scaling study.BMC health services research · 2026Article
- Prognostic and therapeutic implications of BRCA1 and BRCA2 mutations in ovarian cancer.Frontiers in oncology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo investigate the importance of key characteristics relating to diagnostic testing for ovarian cancer and to understand how previous test experience influences priorities.
designCase 1 best-worst scaling embedded in an online survey.
settingPrimary care diagnostic testing in England and Wales.
participants150 women with ovaries over 40 years old living in England and Wales.
methodsWe 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 measuresRelative 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'.
conclusionsThe 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.