Overview
Rebekah is a PhD student based in the Health Economics Group. Her research centres around the elicitation of preferences towards cancer diagnostic testing and screening.
Prior to beginning her PhD, Rebekah worked as a Graduate Trainee Assistant in the department and worked on a mixture of projects relating to health economics.
Qualifications
- BSc (Hons) Economics
- MSc Health Economics and Decision Modelling
Research
Research interests
My primary research interests focus around methods used to elicit preferences towards healthcare interventions, specifically discrete choice experiments and best-worst scaling.
Research projects
- Thesis title: Exploring preferences towards testing for ovarian cancer
Publications
Key publications | Publications by category | Publications by year
Publications by category
Journal articles
Hall R, Medina-Lara A, Hamilton W, Spencer A (In Press). Attributes used for cancer screening discrete choice experiments: a systematic review. The Patient: Patient Centered Outcomes Research
Hall R, Medina-Lara A, Hamilton W, Spencer AE (2022). Correction to: Attributes Used for Cancer Screening Discrete Choice Experiments: a Systematic Review.
Patient,
15(3), 379-381.
Author URL.
Hall R, Medina-Lara A, Hamilton W, Spencer A (2022). Women’s priorities towards ovarian cancer testing: a best–worst scaling study.
BMJ Open,
12(9), e061625-e061625.
Abstract:
Women’s priorities towards ovarian cancer testing: a best–worst scaling study
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.
Abstract.
Publications by year
In Press
Hall R, Medina-Lara A, Hamilton W, Spencer A (In Press). Attributes used for cancer screening discrete choice experiments: a systematic review. The Patient: Patient Centered Outcomes Research
2022
Hall R, Medina-Lara A, Hamilton W, Spencer AE (2022). Correction to: Attributes Used for Cancer Screening Discrete Choice Experiments: a Systematic Review.
Patient,
15(3), 379-381.
Author URL.
Hall R, Medina-Lara A, Hamilton W, Spencer A (2022). Women’s priorities towards ovarian cancer testing: a best–worst scaling study.
BMJ Open,
12(9), e061625-e061625.
Abstract:
Women’s priorities towards ovarian cancer testing: a best–worst scaling study
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.
Abstract.
Rebekah_Hall_ Details from cache as at 2022-12-01 22:38:58
Refresh publications
