Over the past 30 years, researchers have shown that human choices are highly sensitive to the ways in which alternatives are presented. For example, when individuals face a choice between a sure and a risky option, their willingness to take risks varies depending on whether the alternatives are framed in terms of gain or loss. The current major hypothesis that explains such a framing effect predicts that compared with an equivalent risky option, sure gains are emotionally attractive and sure losses are emotionally aversive. Using a behavioural paradigm, the main objective of the current study was to experimentally observe the extent to which the emotional attraction to sure gains and aversion to sure losses are at the core of framing susceptibility. First, our results showed that, as the literature suggests, the emotional attraction to sure gains and aversion to sure losses underpin the framing effect. Second, our results showed that methodological factors moderated the role of these emotional mechanisms in the framing effect. Implications and directions for future studies are discussed.
AartsE.VerhageM.VeenvlietJ. V.DolanC. V.van der SluisS. (2014). A solution to dependency: Using multilevel analysis to accommodate nested data. Nature Neuroscience, 17, 491–496.
2.
AikenL. S.WestS. G. (1991). Multiple regressions: Testing and interpreting interactions. Newbury Park, CA: SAGE.
3.
BaronR. M.KennyD. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173–1182.
4.
BradleyM. M.LangP. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. Journal of Behavior Therapy and Experimental Psychiatry, 25, 49–59.
5.
CampbellM.GrimshawJ.SteenN. (2000). Sample size calculations for cluster randomised trials. Changing professional practice in Europe Group (EU BIOMED II Concerted Action). Journal of Health Services Research & Policy, 5, 12–16.
6.
CassottiM.HoudéO.MoutierS.HabibM.PoirelN.AïteA. (2012). Positive emotional context eliminates the framing effect in decision-making. Emotion, 12, 926–931.
7.
CheungE.MikelsJ. A. (2011). I’m feeling lucky: The relationship between affect and risk-seeking in the framing effect. Emotion, 11, 852–859.
8.
DamasioA. (1994). Descartes’ error: Emotion, reason, and the human brain. New York, NY: G.P. Putnam’s Sons.
9.
DambacherM.HaffkeP.GrobD.HübnerR. (2016). Graphs versus numbers: How information format affects risk aversion in gambling. Judgment and Decision Making, 11, 223–242.
10.
De MartinoB.HarrisonN. A.KnafoS.BirdG.DolanR. J. (2008). Explaining enhanced logical consistency during decision making in autism. Journal of Neuroscience, 28, 10746–10750.
11.
De MartinoB.KumaranD.SeymourB.DolanR. J. (2006). Frames, biases, and rational decision-making in the human brain. Science, 313, 684–687.
12.
De NeysW. (2006). Dual processing in reasoning: Two systems but one reasoner. Psychological Science, 17, 428–433.
13.
DruckmanJ. N.McDermottR. (2008). Emotion and the framing of risky choice. Political Behavior, 30, 297–321.
14.
EvansJ. S. (2008). Dual-processing accounts of reasoning, judgment and social cognition. Annual Review of Psychology, 59, 255–278.
15.
GoslingC. J.MoutierS. (2017). High but not low probability of gain elicits a positive feeling leading to the framing effect. Frontiers in Psychology, 8, 81.
16.
GoslingC. J.MoutierS. (2018). Brief report: Risk-aversion and rationality in autism spectrum disorders. Journal of Autism and Developmental Disorders. Advance online publication. doi:10.1007/s10803-018-3616-8
17.
GreenwaldM. K.CookE. W.LangP. J. (1989). Affective judgment and psychophysiological response: Dimensional covariation in the evaluation of pictorial stimuli. Journal of Psychophysiology, 3, 51–64.
18.
HabibM.CassottiM.MoutierS.HoudéO.BorstG. (2015). Fear and anger have opposite effects on risk seeking in the gain frame. Frontiers in Psychology, 6, 253.
19.
HawardM. F.MurphyR. O.LorenzJ. M. (2008). Message framing and perinatal decisions. Pediatrics, 122, 109–118.
20.
HayesA. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based perspective. New York, NY: Guilford Press.
21.
HayesA. F. (2018). Partial, conditional, and moderated moderated mediation: Quantification, inference, and interpretation. Communication Monographs, 85, 4–40.
22.
HogarthR. M.EinhornH. J. (1990). Venture theory: A model of decision weights. Management Science, 36, 780–803.
23.
IacobucciD. (2012). Mediation analysis and categorical variables: The final frontier. Journal of Consumer Psychology, 22, 582–594.
JouJ.ShanteauJ.HarrisR. J. (1996). An information processing view of framing effects: The role of causal schemas in decision making. Memory & Cognition, 24, 1–15.
26.
KahnemanD.FrederickS. (2007). Frames and brains: Elicitation and control of response tendencies. Trends in Cognitive Sciences, 11, 45-46.
27.
KühbergerA.GradlP. (2013). Choice, rating and rankings: Framing effects with different response modes. Journal of Behavioral Decision Making, 26, 109–117.
28.
KühbergerA.Schulte-MecklenbeckM.PernerJ. (1999). The effects of framing, reflection, probability, and payoff on risk preference in choice tasks. Organizational Behavior and Human Decision Processes, 78, 204–231.
29.
KühbergerA.Schulte-MecklenbeckM.PernerJ. (2002). Framing decisions: Hypothetical and real. Organizational Behavior and Human Decision Processes, 89, 1162–1175.
30.
KühbergerA.TannerC. (2010). Risky choice framing: Task versions and a comparison of prospect theory and Fuzzy-Trace Theory. Journal of Behavioral Decision Making, 23, 314–329.
31.
LernerJ. S.KeltnerD. (2000). Beyond valence: Toward a model of emotion-specific influences on judgement and choice. Cognition & Emotion, 14, 473–493.
32.
LernerJ. S.KeltnerD. (2001). Fear, anger, and risk. Journal of Personality and Social Psychology, 811, 146–159.
33.
LevinI. P.GaethG. J.SchreiberJ.LauriolaM. (2002). A new look at framing effects: Distribution of effect sizes, individual differences, and independence of types of effects. Organizational Behavior and Human Decision Processes, 88, 411–429.
34.
LevinI. P.SchneiderS.GaethG. (1998). All frames are not created equal: A typology and critical analysis of framing effects. Organizational Behavior and Human Decision Processes, 76, 149–188.
35.
LiuY. F.BiY. F.WangH. Y. (2010). The effects of emotions and task frames on risk preferences in self decision making and anticipating others’ decisions. Acta Psychologica Sinica, 42, 317–324.
36.
LoewensteinG.LernerJ. S. (2003). The role of affect in decision making. In DavidsonR. J.SchererK. R.GoldsmithH. H. (Eds.), Handbook of affective sciences (pp. 619–642). New York, NY: Oxford University Press.
MacKinnonD. P. (2008). Introduction to statistical mediation analysis. Mahwah, NJ: Lawrence Erlbaum.
39.
MacKinnonD. P.LockwoodC. M.WilliamsJ. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39, 99–128.
40.
MillerP. M.FagleyN. S. (1991). The effects of framing, problem variations, and providing rationale on choice. Personality and Social Psychology Bulletin, 17, 517–522.
41.
MuthénL. K.MuthénB. O. (1998-2017). Mplus user’s guide (8th ed.). Los Angeles, CA: Author.
42.
PodevijnG.O’GradyR.MathewsN.GillesA.Fantini-HauwelC.DorigoM. (2016). Investigating the effect of increasing robot group sizes on the human psychophysiological state in the context of human–swarm interaction. Swarm Intelligence, 10, 193–210.
43.
PreacherK. J.SeligJ. P. (2012). Advantages of Monte Carlo confidence intervals for indirect effects. Communication Methods and Measures, 6, 77–98.
44.
ReynaV. F. (2004). How people make decisions that involve risk: A dual-processes approach. Current Directions in Psychological Science, 13, 60–66.
45.
ReynaV. F.BrainerdC. J. (1991). Fuzzy-Trace Theory and framing effects in choice: Gist extraction, truncation, and conversion. Journal of Behavioral Decision Making, 4, 249–262.
46.
ReynaV. F.EstradaS. M.DeMarinisJ. A.MyersR. M.StaniszJ. M.MillsB. A. (2011). Neurobiological and memory models of risky decision making in adolescents versus young adults. Journal of Experimental Psychology: Learning, Memory, and Cognition, 375, 1125–1142.
47.
SeligJ. P.PreacherK. J. (2008, June). Monte Carlo method for assessing mediation: An interactive tool for creating confidence intervals for indirect effects [Computer software]. Retrieved from http://quantpsy.org/medmc/medmc.htm
48.
SlovicP.FinucaneM.PetersE.MacGregorD. G. (2002). Rational actors or rational fools: Implications of the affect heuristic for behavioral economics. Journal of Socio-Economics, 31, 329–342.
49.
StantonS.ReeckC.HuettelS. A.LaBarK. S. (2014). Effects of induced moods on economic choices. Judgment and Decision Making, 9, 167–175.
50.
TalmiD.HurlemannR.PatinA.DolanR. J. (2010). Framing effect following bilateral amygdala lesion. Neuropsychologia, 48, 1823–1827.
51.
TverskyA.KahnemanD. (1981). The framing of decisions and the psychology of choice. Science, 211, 453–458.
52.
TverskyA.KahnemanD. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5, 292–323.
53.
Von NeumannJ.MorgensternO. (1944). Theory of games and economic behavior. Princeton, NJ: Princeton University Press.
54.
XuP.GuR.BrosterL. S.WuR.Van DamN. T.JiangY.. . . LuoY. J. (2013). Neural basis of emotional decision making in trait anxiety. Journal of Neuroscience, 33, 18641–18653.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
