scholarly journals Women’s Benefits and Harms Trade-Offs in Breast Cancer Screening: Results from a Discrete-Choice Experiment

2018 ◽  
Vol 21 (1) ◽  
pp. 78-88 ◽  
Author(s):  
Jonathan Sicsic ◽  
Nathalie Pelletier-Fleury ◽  
Nora Moumjid
Keyword(s):  
Breast Cancer ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Trade Offs

Provider preferences for attributes of artificial intelligence in breast cancer screening: A discrete choice experiment.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e14118-e14118
Author(s):  
Nathaniel Hendrix ◽  
A. Brett Hauber ◽  
Christoph I. Lee ◽  
Aasthaa Bansal ◽  
David Leroy Veenstra
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Qualitative Interviews ◽  
Primary Care Providers ◽  
Care Providers

e14118 Background: One of the emerging medical applications of artificial intelligence (AI) is the interpretation of mammograms for breast cancer screening. It is uncertain what attributes would result in acceptance of AI for breast cancer screening (AI BCS) among ordering clinicians. Methods: We performed qualitative interviews to identify the most important attributes of AI BCS for ordering clinicians. We then invited US-based primary care providers (PCPs) to participate in a discrete choice experiment (DCE). The experiment featured 15 choices between radiologist alone and two AI BCS alternatives where respondents traded better metrics on some attributes for worse metrics on others. Responses were analyzed using a mixed logit model adjusting for preference heterogeneity to determine the probability of recommending AI BCS. Results: In qualitative interviews, the six most important attributes to PCPs were AI sensitivity, specificity, radiologist involvement, understandability of AI decision-making, supporting evidence, and diversity of training data. Forty PCPs completed the DCE. Sensitivity was the most important attribute: a 4 percentage point improvement in sensitivity over the average radiologist increased the probability of recommending AI by 0.41 (95% confidence interval (CI), 0.38-0.42). Specificity was approximately half as important. Respondents were indifferent to whether radiologists confirmed all or only screens likely to be abnormal. However, no radiologist involvement reduced the probability of recommendation by 0.31 (95% CI, 0.29-0.31). An AI developed using data from diverse populations increased the probability of recommendation by 0.38 (95% CI, 0.36-0.39). Lastly, an AI that is transparent in the rationale for its decisions increased the probability of recommendation by 0.41 (95% CI, 0.39-0.41). Conclusions: PCPs prefer AI BCS that improves sensitivity versus specificity, and involves radiologists in the confirmation of abnormal screens. Improving sensitivity alone, however, will likely not be sufficient to support widespread PCP acceptance – algorithms will need to be developed with diverse data and more transparent explanations of their decisions.

scholarly journals Population preferences for breast cancer screening policies: Discrete choice experiment in Belarus

PLoS ONE ◽  
2019 ◽  
Vol 14 (11) ◽  
pp. e0224667
Author(s):  
Olena Mandrik ◽  
Alesya Yaumenenka ◽  
Rolando Herrero ◽  
Marcel F. Jonker
Keyword(s):  
Breast Cancer ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Population Preferences

scholarly journals Men's preferences and trade-offs for prostate cancer screening: a discrete choice experiment

2014 ◽  
Vol 18 (6) ◽  
pp. 3123-3135 ◽  
Author(s):  
Kirsten Howard ◽  
Glenn P. Salkeld ◽  
Manish I. Patel ◽  
Graham J. Mann ◽  
Michael P. Pignone
Keyword(s):  
Prostate Cancer ◽  
Cancer Screening ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Prostate Cancer Screening ◽  
Trade Offs

INDIVIDUALS' PREFERENCES FOR ESOPHAGEAL CANCER SCREENING STRATEGIES: A DISCRETE CHOICE EXPERIMENT

2019 ◽  
Author(s):  
Y Peters ◽  
E van Grinsven ◽  
M van de Haterd ◽  
D van Lankveld ◽  
J Verbakel ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Cancer Screening ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Screening Strategies

scholarly journals Discrete choice experiment for eliciting preference for health services for patients with ALS and their informal caregivers

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Katy Tobin ◽  
Sinead Maguire ◽  
Bernie Corr ◽  
Charles Normand ◽  
Orla Hardiman ◽  
...  
Keyword(s):  
Health Services ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Strong Preference ◽  
Multidisciplinary Teams ◽  
Relative Importance ◽  
Trade Offs ◽  
Als Patients ◽  
The Impact

Abstract Background Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative condition with a mean life expectancy of 3 years from first symptom. Understanding the factors that are important to both patients and their caregivers has the potential to enhance service delivery and engagement, and improve efficiency. The Discrete Choice Experiment (DCE) is a stated preferences method which asks service users to make trade-offs for various attributes of health services. This method is used to quantify preferences and shows the relative importance of the attributes in the experiment, to the service user. Methods A DCE with nine choice sets was developed to measure the preferences for health services of ALS patients and their caregivers and the relative importance of various aspects of care, such as timing of care, availability of services, and decision making. The DCE was presented to patients with ALS, and their caregivers, recruited from a national multidisciplinary clinic. A random effects probit model was applied to estimate the impact of each attribute on a participant’s choice. Results Patients demonstrated the strongest preferences about timing of receiving information about ALS. A strong preference was also placed on seeing the hospice care team later rather than early on in the illness. Patients also indicated their willingness to consider the use of communication devices. Grouping by stage of disease, patients who were in earlier stages of disease showed a strong preference for receipt of extensive information about ALS at the time of diagnosis. Caregivers showed a strong preference for engagement with healthcare professionals, an attribute that was not prioritised by patients. Conclusions The DCE method can be useful in uncovering priorities of patients and caregivers with ALS. Patients and caregivers have different priorities relating to health services and the provision of care in ALS, and patient preferences differ based on the stage and duration of their illness. Multidisciplinary teams must calibrate the delivery of care in the context of the differing expectations, needs and priorities of the patient/caregiver dyad.

scholarly journals Understanding public preferences and trade-offs for government responses during a pandemic: a protocol for a discrete choice experiment in the UK

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e043477
Author(s):  
Mesfin G Genie ◽  
Luis Enrique Loría-Rebolledo ◽  
Shantini Paranjothy ◽  
Daniel Powell ◽  
Mandy Ryan ◽  
...  
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Online Survey ◽  
Research Unit ◽  
Media Analysis ◽  
Moral Foundation ◽  
Trade Offs ◽  
Ethics Research ◽  
The Uk

IntroductionSocial distancing and lockdown measures are among the main government responses to the COVID-19 pandemic. These measures aim to limit the COVID-19 infection rate and reduce the mortality rate of COVID-19. Given we are likely to see local lockdowns until a treatment or vaccine for COVID-19 is available, and their effectiveness depends on public acceptability, it is important to understand public preference for government responses.Methods and analysisUsing a discrete choice experiment (DCE), this study will investigate the public’s preferences for pandemic responses in the UK. Attributes (and levels) are based on: (1) lockdown measures described in policy documents; (2) literature on preferences for lockdown measures and (3) a social media analysis. Attributes include: lockdown type; lockdown length; postponement of usual non-urgent medical care; number of excess deaths; number of infections; impact on household spending and job losses. We will prepilot the DCE using virtual think aloud interviews with respondents recruited via Facebook. We will collect preference data using an online survey of 4000 individuals from across the four UK countries (1000 per country). We will estimate the relative importance of the attributes, and the trade-offs individuals are willing to make between attributes. We will test if respondents’ preferences differ based on moral attitudes (using the Moral Foundation Questionnaire), socioeconomic circumstances (age, education, economic insecurity, health status), country of residence and experience of COVID-19.Ethics and disseminationThe University of Aberdeen’s College Ethics Research Board (CERB) has approved the study (reference: CERB/2020/6/1974). We will seek CERB approval for major changes from the developmental and pilot work. Peer-reviewed papers will be submitted, and results will be presented at public health and health economic conferences nationally and internationally. A lay summary will be published on the Health Economics Research Unit blog.

scholarly journals Preferences for colorectal cancer screening strategies: a discrete choice experiment

2010 ◽  
Vol 102 (6) ◽  
pp. 972-980 ◽  
Author(s):  
L Hol ◽  
E W de Bekker-Grob ◽  
L van Dam ◽  
B Donkers ◽  
E J Kuipers ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Screening Strategies
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