Aging and decision making: Differences in susceptibility to the risky-choice framing effect between older and younger adults in Japan

This article surveys the latest research on risky-choice framing effects, focusing on the implications for rational decision-making. An influential program of psychological research suggests that people’s judgements and decisions depend on the way in which information is presented, or ‘framed’. In a central choice paradigm, decision-makers seem to adopt different preferences, and different attitudes to risk, depending on whether the options specify the number of people who will be saved or the corresponding number who will die. It is standardly assumed that such responses violate a foundational tenet of rational decision-making, known as the principle of description invariance. We discuss recent theoretical and empirical research that challenges the dominant ‘irrationalist’ narrative. These approaches typically pay close attention to how decision-makers represent decision problems (including their interpretation of numerical quantifiers or predicate choice) and they highlight the need for a more robust characterization of the description invariance principle. We conclude by indicating avenues for future research that could bring us closer to a complete – and potentially rationalizing – explanation of framing effects.

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Teaching & Learning Guide for: Risky-choice framing and rational decision-making

10.31234/osf.io/2vz53 ◽

2021 ◽

Author(s):

Sarah A. Fisher ◽

David R. Mandel

Keyword(s):

Decision Making ◽

Psychological Research ◽

Risky Choice ◽

Decision Makers ◽

Rational Decision ◽

Rational Decision Making ◽

Alternative Approaches ◽

Learning Guide ◽

Choice Framing

An influential program of psychological research suggests that people’s judgements and decisions depend on the way in which information is presented, or ‘framed’. In a central choice paradigm, decision-makers seem to adopt different preferences, and different attitudes to risk, depending on whether the options specify the number of people who will be saved or the corresponding number who will die. It is standardly assumed that such responses violate a foundational tenet of rational decision-making, known as the principle of description invariance. However, recent theoretical and empirical research has begun to challenge the dominant ‘irrationalist’ narrative. The alternative approaches being developed typically pay close attention to how decision- makers represent decision problems (including their interpretation of numerical quantifiers or predicate choice). They also highlight the need for a more robust characterization of the description invariance principle itself.

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A Meta-Analytic Re-Appraisal of the Framing Effect

Zeitschrift für Psychologie ◽

10.1027/2151-2604/a000321 ◽

2018 ◽

Vol 226 (1) ◽

pp. 45-55 ◽

Cited By ~ 4

Author(s):

Alexander Steiger ◽

Anton Kühberger

Keyword(s):

Effect Size ◽

Meta Analysis ◽

Framing Effect ◽

Framing Effects ◽

Risky Choice ◽

Risky Decision ◽

Risk Framing ◽

Choice Framing ◽

The Many ◽

Gain Loss

Abstract. We reevaluated and reanalyzed the data of Kühberger’s (1998) meta-analysis on framing effects in risky decision making by using p-curve. This method uses the distribution of only significant p-values to correct the effect size, thus taking publication bias into account. We found a corrected overall effect size of d = 0.52, which is considerably higher than the effect reported by Kühberger (d = 0.31). Similarly to the original analysis, most moderators proved to be effective, indicating that there is not the risky-choice framing effect. Rather, the effect size varies with different manipulations of the framing task. Taken together, the p-curve analysis shows that there are reliable risky-choice framing effects, and that there is no evidence of intense p-hacking. Comparing the corrected estimate to the effect size reported in the Many Labs Replication Project (MLRP) on gain-loss framing (d = 0.60) shows that the two estimates are surprisingly similar in size. Finally, we conducted a new meta-analysis of risk framing experiments published in 2016 and again found a similar effect size (d = 0.56). Thus, although there is discussion on the adequate explanation for framing effects, there is no doubt about their existence: risky-choice framing effects are highly reliable and robust. No replicability crisis there.

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Replicating the Disease framing problem during the 2020 COVID-19 pandemic: A study of stress, worry, trust, and choice under risk

PLoS ONE ◽

10.1371/journal.pone.0257151 ◽

2021 ◽

Vol 16 (9) ◽

pp. e0257151

Author(s):

Nikolay R. Rachev ◽

Hyemin Han ◽

David Lacko ◽

Rebekah Gelpí ◽

Yuki Yamada ◽

...

Keyword(s):

Risk Aversion ◽

Perceived Stress ◽

Large Scale ◽

Framing Effect ◽

Risky Choice ◽

Safety Measures ◽

Risky Choices ◽

Large Scale Survey ◽

Choice Framing ◽

Practical Implications

In the risky-choice framing effect, different wording of the same options leads to predictably different choices. In a large-scale survey conducted from March to May 2020 and including 88,181 participants from 47 countries, we investigated how stress, concerns, and trust moderated the effect in the Disease problem, a prominent framing problem highly evocative of the COVID-19 pandemic. As predicted by the appraisal-tendency framework, risk aversion and the framing effect in our study were larger than under typical circumstances. Furthermore, perceived stress and concerns over coronavirus were positively associated with the framing effect. Contrary to predictions, however, they were not related to risk aversion. Trust in the government’s efforts to handle the coronavirus was associated with neither risk aversion nor the framing effect. The proportion of risky choices and the framing effect varied substantially across nations. Additional exploratory analyses showed that the framing effect was unrelated to reported compliance with safety measures, suggesting, along with similar findings during the pandemic and beyond, that the effectiveness of framing manipulations in public messages might be limited. Theoretical and practical implications of these findings are discussed, along with directions for further investigations.

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How Cues of Being Watched Promote Risk Seeking in Fund Investment in Older Adults

Frontiers in Psychology ◽

10.3389/fpsyg.2021.765632 ◽

2022 ◽

Vol 12 ◽

Author(s):

Meijia Li ◽

Huamao Peng

Keyword(s):

Older Adults ◽

Decision Making ◽

Eye Tracking ◽

Dwell Time ◽

Framing Effect ◽

Attention Allocation ◽

Future Research ◽

Younger Adults ◽

Risk Seeking ◽

Fund Investment

Social cues, such as being watched, can subtly alter fund investment choices. This study aimed to investigate how cues of being watched influence decision-making, attention allocation, and risk tendencies. Using decision scenarios adopted from the “Asian Disease Problem,” we examined participants’ risk tendency in a financial scenario when they were watched. A total of 63 older and 66 younger adults participated. Eye tracking was used to reveal the decision-maker’s attention allocation (fixations and dwell time per word). The results found that both younger and older adults tend to seek risk in the loss frame than in the gain frame (i.e., framing effect). Watching eyes tended to escalate reckless gambling behaviors among older adults, which led them to maintain their share in the depressed fund market, regardless of whether the options were gain or loss framed. The eye-tracking results revealed that older adults gave less attention to the sure option in the eye condition (i.e., fewer fixations and shorter dwell time). However, their attention was maintained on the gamble options. In comparison, images of “watching eyes” did not influence the risk seeking of younger adults but decreased their framing effect. Being watched can affect financial risk preference in decision-making. The exploration of the contextual sensitivity of being watched provides us with insight into developing decision aids to promote rational financial decision-making, such as human-robot interactions. Future research on age differences still requires further replication.

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Training in statistical analysis reduces the framing effect on medical students and residentsinArgentina

Journal of Educational Evaluation for Health Professions ◽

10.3352/jeehp.2020.17.25 ◽

2020 ◽

Vol 17 ◽

pp. 25

Author(s):

Raúl A. Borracci ◽

Eduardo B. Arribalzaga ◽

Jorge Thierer

Keyword(s):

Decision Making ◽

Medical Students ◽

Effect Size ◽

Framing Effect ◽

Framing Effects ◽

Risky Choice ◽

Medical Decision ◽

Post Intervention ◽

Different Types ◽

Second Year

Purpose:The framing effect refers to a phenomenon whereby, when the same problem is presented using different representations of information, people make significant changes in their decisions.Itaimed to explore whether theframingeffect could be reduced in medical students and residents by teaching them the statistical concepts of effect size, probability, and sampling to be used in the medical decision-making process.MethodsNinety-five second-year medical students and 100 second-year medical residentsof Austral University and Buenos Aires University, Argentina were invited to participate in the study between March and June 2017. A questionnaire was developed to assess the different types of framing effects in medical situations. After an initial administration of the survey, students and residents were taught statistical concepts including effect size, probability, and sampling during two individual independent official biostatistics courses. After these interventions, the same questionnaire was randomly applied again, and pre- and post-intervention outcomes were compared for students and residents. Results: Almost every type of framing effect was reproduced either in the students or in the resident population. After teaching medical students and residents the analytical process behind statistical notions, a significant reduction in sample-size, risky-choice, pseudo-certainty, number-size, attribute, goal, and probabilistic formulation framing effects was observed. Conclusions Decision-making of medical students and residents in simulated medical situations may be affected by different frame descriptions, and these framing effects can be partially reduced by training individuals in probability analysis and statistical sampling methods.

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