Kahneman and Tversky's 1979 article on Prospect Theory is one of the most influential papers across all of the behavioural sciences. The study tested a series of binary financial (risky) choices, ultimately concluding that judgments formed under uncertainty deviate significantly from those presumed by expected utility theory, which was the prevailing theoretical construct at the time. In the forty years since publication, this study has had a remarkable impact on science, policy, and other real-world applications. At the same time, a number of critiques have been raised about its conclusions and subsequent constructs that were founded on it, such as loss aversion. In an era where such presumed canonical theories have increasingly drawn scrutiny for inability to replicate, we attempted a multinational study of N = 4,099 participants from 19 countries and 13 languages. The same methods and procedures were used as in the original paper, adjusting only currencies to make them relative to current values, and requiring all participants to respond to all items. Overall, we found that results replicated for 94% of the 17 choice items tested. At most, results from the 1979 study were attenuated in our findings, which is most likely due to a more robust sample. Twelve of the 13 theoretical contrasts presented by Kahneman and Tversky also replicated, with a further 89% replication rate of the total contrasts possible when separating by location, up to 100% replication in some countries. We conclude that the principles of Prospect Theory replicate beyond any reasonable thresholds, and provide a number of important insights about replications, attenuation, and implications for the study of human decision-making at population-level.

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Kahneman and Tversky’s 1979 article on Prospect Theory is one of the most influential papers across all of the behavioural sciences. The study tested a series of binary financial (risky) choices, ultimately concluding that judgments formed under uncertainty deviate significantly from those presumed by expected utility theory, which was the prevailing theoretical construct at the time. In the forty years since publication, this study has had a remarkable impact on science, policy, and other real-world applications. At the same time, a number of critiques have been raised about its conclusions and subsequent constructs that were founded on it, such as loss aversion. In an era where such presumed canonical theories have increasingly drawn scrutiny for inability to replicate, we attempted a multinational study of N = 4,099 participants from 19 countries and 13 languages. The same methods and procedures were used as in the original paper, adjusting only currencies to make them relative to current values, and requiring all participants to respond to all items. Overall, we found that results replicated for 94% of the 17 choice items tested. At most, results from the 1979 study were attenuated in our findings, which is most likely due to a more robust sample. Twelve of the 13 theoretical contrasts presented by Kahneman and Tversky also replicated, with a further 89% replication rate of the total contrasts possible when separating by location, up to 100% replication in some countries. We conclude that the principles of Prospect Theory replicate beyond any reasonable thresholds, and provide a number of important insights about replications, attenuation, and implications for the study of human decision-making at population-level.

BackgroundAdvances in genetics and digital phenotyping in psychiatry have given rise to testing services targeting young people, which claim to predict psychiatric outcomes before difficulties emerge. These services raise several ethical challenges surrounding data sharing and information privacy.ObjectivesThis study aimed to investigate young people’s interest in predictive testing for mental health challenges and their attitudes towards sharing biological, psychosocial and digital data for such purpose.MethodsEighty UK adolescents aged 16–18 years took part in a digital role-play where they played the role of clients of a fictional predictive psychiatry company and chose what sources of personal data they wished to provide for a risk assessment. After the role-play, participants reflected on their choices during a peer-led interview.FindingsParticipants saw multiple benefits in predictive testing services, but were highly selective with regard to the type of data they were willing to share. Largely due to privacy concerns, digital data sources such as social media or Google search history were less likely to be shared than psychosocial and biological data, including school grades and one’s DNA. Participants were particularly reluctant to share social media data with schools (but less so with health systems).ConclusionsEmerging predictive psychiatric services are valued by young people; however, these services must consider privacy versus utility trade-offs from the perspective of different stakeholders, including adolescents.Clinical implicationsRespecting adolescents’ need for transparency, privacy and choice in the age of digital phenotyping is critical to the responsible implementation of predictive psychiatric services.

Due to the prevalence and importance of choices with uncertain outcomes, it is essential to establish what interventions improve risky decision-making, how they work, and for whom. Two types of low-intensity behavioural interventions are promising candidates: nudges and boosts. Nudges guide people to better decisions by altering how a choice is presented, without restricting any options or modifying the underlying payoff matrix. Boosts, on the other hand, teach people decision strategies that focus their attention on key aspects of the choice, which allows them to make more informed decisions. A recent study compared these two types of interventions and found that boosts worked better for risky choices aimed at maximising gains, whereas nudges worked best for choices aimed at minimising losses. Though intriguing, these findings could not be easily interpreted because of a limitation in the items used. Here we replicate that study, with an extended item set. We find that boosts work by promoting risk-taking when it is beneficial, whereas nudges have a consistent (lesser) impact, regardless of whether risk-taking is beneficial or not. These results suggest that researchers and policymakers should consider the base rate risk propensity of the target population when designing decision-support systems.