Dataset Information

How people know their risk preference.

ABSTRACT: People differ in their willingness to take risks. Recent work found that revealed preference tasks (e.g., laboratory lotteries)-a dominant class of measures-are outperformed by survey-based stated preferences, which are more stable and predict real-world risk taking across different domains. How can stated preferences, often criticised as inconsequential "cheap talk," be more valid and predictive than controlled, incentivized lotteries? In our multimethod study, over 3,000 respondents from population samples answered a single widely used and predictive risk-preference question. Respondents then explained the reasoning behind their answer. They tended to recount diagnostic behaviours and experiences, focusing on voluntary, consequential acts and experiences from which they seemed to infer their risk preference. We found that third-party readers of respondents' brief memories and explanations reached similar inferences about respondents' preferences, indicating the intersubjective validity of this information. Our results help unpack the self perception behind stated risk preferences that permits people to draw upon their own understanding of what constitutes diagnostic behaviours and experiences, as revealed in high-stakes situations in the real world.

SUBMITTER: Arslan RC

PROVIDER: S-EPMC7505965 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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How people know their risk preference.

Arslan Ruben C RC Brümmer Martin M Dohmen Thomas T Drewelies Johanna J Hertwig Ralph R Wagner Gert G GG

Scientific reports 20200921 1

People differ in their willingness to take risks. Recent work found that revealed preference tasks (e.g., laboratory lotteries)-a dominant class of measures-are outperformed by survey-based stated preferences, which are more stable and predict real-world risk taking across different domains. How can stated preferences, often criticised as inconsequential "cheap talk," be more valid and predictive than controlled, incentivized lotteries? In our multimethod study, over 3,000 respondents from popul ...[more]

PMID: 32958788

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Project description:Multiple sclerosis (MS) has a varied and uncertain trajectory. The recent development of analytical processing tools that draw on large longitudinal patient databases facilitates personalised long-term prognosis estimates. This has the potential to improve both shared treatment decision-making and psychological adjustment. However, there is limited research on how people with MS feel about prognosis communication and forecasting. This study investigated the prognosis communication experiences and preferences of people with MS and explored whether clinical, demographic and psychological factors are associated with prognosis information preferences.3175 UK MS Register members (59% of those with active accounts) completed an online survey containing 17 questions about prognosis communication experiences, attitudes and preferences. Participants also completed validated questionnaires measuring coping strategies, tendencies to seek out ('monitor') or avoid ('blunt') information in threatening situations, and MS risk perceptions and reported their clinical and sociodemographic characteristics. Data already held on the MS Register about participants' quality of life, anxiety and depression symptoms and MS impact were obtained and linked to the survey data.53.1% of participants had never discussed long-term prognosis with healthcare professionals. 54.2% lacked clarity about their long-term prognosis. 76% had strong preferences for receiving long-term prognosis information. 92.8% were interested in using tools that generate personalised predictions. Most participants considered prognostication useful for decision-making. Participants were more receptive to receiving prognosis information at later time-points, versus at diagnosis. A comprehensive set of sociodemographic, clinical and psychological variables predicted only 7.9% variance in prognosis information preferences.People with MS have an appetite for individualised long-term prognosis forecasting and their need for information is frequently unmet. Clinical studies deploying and evaluating interventions to support prognostication in MS are now needed. This study indicates suitable contexts and patient preferences for initial trials of long-term prognosis tools in clinical settings.

Dataset Information

How people know their risk preference.

Publications

How people know their risk preference.

Similar Datasets

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