Recent advances in the study of the illusion of causalitytheory, methods, and practical implications
- María Manuela Moreno-Fernández 1
- Fernando Blanco 2
- Helena Matute 1
-
1
Universidad de Granada
info
-
2
Universidad de Deusto
info
ISSN: 1576-8597
Año de publicación: 2023
Volumen: 44
Número: 2
Tipo: Artículo
Otras publicaciones en: Psicológica: Revista de metodología y psicología experimental
Resumen
Learning causal relations provides the knowledge that allows us to make accurate predictions. Some of these predictions may have a high value for survival, and some of them provide us with a body of knowledge that maximize context adaptation. This is why researchers have tried to understand how people make causal inferences and learn about the causal structures in their environment. In this article, we will outline some of the most recent advances in the understanding of causal learning, and specifically of the biases that often appear in decision-making.
Referencias bibliográficas
- Aeschleman, S. R., Rosen, C. C., & Williams, M. R. (2003). The effect of non-contingent negative and positive reinforcement operations on the acquisition of superstitious behaviors. Behavioural Processes, 61, 37–45. https://doi.org/10.1016/s0376-6357(02)00158-4
- Aitken, M. R. F. R., Larkin, M. J., & Dickinson, A. (2000). Super-learning of causal judgements. The Quarterly journal of experimental psychology. B, Comparative and physiological psychology, 53(1), 59-81. https://doi.org/10.1080/713932716
- Allan, L. G. (1980). A note on measurement of contingency between two binary variables in judgment tasks. Bulletin of the Psychonomic Society, 15(3), 147-149. https://doi.org/10.3758/BF03334492
- Allan, L. G., & Jenkins, H. M. (1980). The judgment of contingency and the nature of the response alternatives. Canadian Journal of Experimental Psychology, 34(1), 1-11. https://doi.org/10.1037/h0081013
- Allan, L. G., & Jenkins, H. M. (1983). The effect of representations of binary variables on judgment of influence. Learning and Motivation, 14(4), 381-405. https://doi.org/10.1016/0023-9690(83)90024-3
- Allan, L. G., Hannah, S. D., Crump, M. J. C., & Siegel, S. (2008). The psychophysics of contingency assessment. Journal of Experimental Psychology: General, 137(2), 226-243. https://doi.org/10.1037/0096-3445.137.2.226
- Alloy, L. B., & Abramson, L. Y. (1979). Judgment of contingency in depressed and nondepressed students: Sadder but wiser? Journal of experimental psychology. General, 108(4), 441-485. https://doi.org/10.1037/0096-3445.108.4.441
- Barberia, I., Blanco, F., & Rodríguez-Ferreiro, J. (2020). The more, the merrier: Treatment frequency influences effectiveness perception and further treatment choice. Psychonomic Bulletin & Review, 28, 665–675. https://doi.org/10.3758/s13423-020-01832-6
- Barberia, I., Blanco, F., Cubillas, C. P., & Matute, H. (2013). Implementation and Assessment of an Intervention to Debias Adolescents against Causal Illusions. PloS ONE, 8(8), e71303-e71303. https://doi.org/10.1371/journal.pone.0071303
- Barberia, I., Vadillo, M. A., & Rodríguez-Ferreiro, J. (2019). Persistence of causal illusions after extensive training. Frontiers in Psychology, 10(24), 1-9. https://doi.org/10.3389/fpsyg.2019.00024
- Beesley, T., & Le Pelley, M. E. (2010). The effect of predictive history on the learning of sub-sequence contingencies. Quarterly journal of experimental psychology, 63(1), 108-135. https://doi.org/10.1080/17470210902831767
- Blanco, F. (2017). Positive and negative implications of the causal illusion. Consciousness and Cognition, 50, 56-68. https://doi.org/10.1016/j.concog.2016.08.012
- Blanco, F., & Matute, H. (2015). Exploring the Factors That Encourage the Illusions of Control The Case of Preventive Illusions. Experimental Psychology, 62(2), 131-142. https://doi.org/10.1027/1618-3169/a000280
- Blanco, F., & Matute, H. (2019). Base-rate expectations modulate the causal illusion. PloS ONE, 14(3), e0212615-e0212615. https://doi.org/10.1371/journal.pone.0212615
- Blanco, F., & Matute, H. (2020). Diseases that resolve spontaneously can increase the belief that ineffective treatments work. Social Science & Medicine, 255, 113012-113012. https://doi.org/10.1016/J.SOCSCIMED.2020.113012
- Blanco, F., Barberia, I., & Matute, H. (2014). The lack of side effects of an ineffective treatment facilitates the development of a belief in its effectiveness. PLOS ONE, 9(1) : e84084. https://doi.org/10.1371/journal.pone.0084084
- Blanco, F., Barberia, I., & Matute, H. (2015). Individuals who believe in the paranormal expose themselves to biased information and develop more causal illusions than nonbelievers in the laboratory. PLOS ONE, 10(7): e0131378. https://doi.org/10.1371/journal.pone.0131378
- Blanco, F., Gómez-Fortes, B., & Matute, H. (2018). Causal illusions in the service of political attitudes in Spain and the United Kingdom. Frontiers in Psychology, 9, 1033-1033. https://doi.org/10.3389/fpsyg.2018.01033
- Blanco, F., Matute, H., & Vadillo, M. A. (2011). Making the uncontrollable seem controllable: The role of action in the illusion of control. Quarterly journal of experimental psychology, 64(7), 1290-1304. https://doi.org/10.1080/17470218.2011.552727
- Blanco, F., Matute, H., & Vadillo, M. A. (2012). Mediating Role of Activity Level in the Depressive Realism Effect. PloS ONE, 7(9). https://doi.org/10.1371/journal.pone.0046203
- Blanco, F., Matute, H., & Vadillo, M. A. (2013). Interactive effects of the probability of the cue and the probability of the outcome on the overestimation of null contingency. Learning & behavior, 41(4), 333-340. https://doi.org/10.3758/s13420-013-0108-8
- Blanco, F., Moreno-Fernández, M. M., & Matute, H. (2020). Are the symptoms really remitting? How the subjective interpretation of outcomes can produce an illusion of causality. Judgment & Decision Making, 15(4).
- Bloom, C. M., Venard, J., Harden, M., & Seetharaman, S. (2007). Non-contingent positive and negative reinforcement schedules of superstitious behaviors. Behavioural Processes, 75, 8–13. https://doi.org/10.1016/j.beproc.2007.02.010
- Buehner, M. J., Cheng, P. W., & Clifford, D. (2003). From covariation to causation: A test of the assumption of causal power. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29(6), 1119-1140. https://doi.org/10.1037/0278-7393.29.6.1119
- Busemeyer, J. R. (1991). Intuitive statistical estimation. In N. H. Anderson (Ed.), Contributions to information integration theory (pp. 187-205). Erlbaum.
- Catena, A., Maldonado, A., & Cándido, A. (1998). The effect of frequency of judgement and the type of trials on covariation learning. Journal of Experimental Psychology: Human Perception and Performance, 24(2), 481. https://doi.org/10.1037/0096-1523.24.2.481
- Cheng, P. W. (1997). From covariation to causation: A causal power theory. Psychological Review, 104(2), 367-405. https://doi.org/10.1037/0033-295X.104.2.367
- Cheng, P. W., & Novick, L. R. (1990). A probabilistic contrast model of causal induction. Journal of personality and social psychology, 58(4), 545-567. https://doi.org/10.1037/0022-3514.58.4.545
- Chow, J. Y. L., Colagiuri, B., & Livesey, E. J. (2019). Bridging the divide between causal illusions in the laboratory and the real world: The effects of outcome density with a variable continuous outcome. Cognitive research: principles and implications, 4(1), 1-1. https://doi.org/10.1186/s41235-018-0149-9
- Collins, D. J., & Shanks, D. R. (2002). Momentary and integrative response strategies in causal judgment. Memory & Cognition, 30, 1138-1147. https://doi.org/10.3758/bf03194331
- Crocker, J. (1982). Biased questions in judgment of covariation studies. Personality and Social Psychology Bulletin, 8, 214-220. https://doi.org/10.1177/0146167282082005
- Danks, D. (2003). Equilibria of the Rescorla–Wagner model. Journal of Mathematical Psychology, 47(2), 109-121. https://doi.org/10.1016/S0022-2496(02)00016-0
- Denniston, J. C., Savastano, H. I., & Miller, R. R. (2001). The extended comparator hypothesis: Learning by contiguity, responding by relative strength. In R. R. Mowrer & S. B. Klein (Eds.), Handbook of contemporary learning theories (pp. 65-117). Hillsdale, NJ: Erl-baum.
- Don, H., & Livesey, E. Is the blocking effect sensitive to causal model? It depends how you ask. In T. T. Rogers, M. Rau, X. Zhu, & C. W. Kalish (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 1630–1635). Austin, TX: Cognitive Science Society.
- Double, K. S., Chow, J. Y. L., Livesey, E. J., & Hopfenbeck, T. N. (2020). Causal illusions in the classroom: How the distribution of student outcomes can promote false instructional beliefs. Cognitive Research: Principles and Implications, 5, Article 34. https://doi.org/10.1186/s41235-020-00237-2
- Ecker, U. K. H., Lewandowsky, S., Cook, J., Schmid, P., Fazio, L. K., Brashier, N., Kendeou, P., Vraga, E. K., & Amazeen, M. A. (2022). The psychological drivers of misinformation belief and its resistance to correction. Nature Reviews Psychology, 1(1), Article 1. https://doi.org/10.1038/s44159-021-00006-y
- Elk, M. van. (2013). Paranormal believers are more prone to illusory agency detection than skeptics. Consciousness and Cognition, 22(3), 1041-1046. https://doi.org/10.1016/j.concog.2013.07.004
- Fugelsang, J. A., & Thompson, V. A. (2003). A dual-process model of belief and evidence interactions in causal reasoning. Memory & Cognition 31, 800–815. https://doi.org/10.3758/BF03196118
- Gibbon, J., Berryman, R., & Thompson, R. L. (1974). Contingency spaces and measures in classical and instrumental conditioning. Journal of the Experimental Analysis of Behavior, 21(3), 585-605. https://doi.org/10.1901/jeab.1974.21-585
- Griffiths, O., & Thorwart, A. (2017). Effects of Outcome Predictability on Human Learning. Frontiers in Psychology, 8. https://www.frontiersin.org/articles/10.3389/fpsyg.2017.00511
- Griffiths, O., Livesey, E., & Thorwart, A. (2019). Learned biases in the processing of outcomes: A brief review of the outcome predictability effect. Journal of Experimental Psychology: Animal Learning and Cognition, 45(1), 1-16. https://doi.org/10.1037/xan0000195
- Griffiths, O., Shehabi, N., Murphy, R. A., & Le Pelley, M. E. (2019). Superstition predicts perception of illusory control. British Journal of Psychology, 110(3), 499–518. https://doi.org/10.1111/bjop.12344
- Hannah, S. D., & Beneteau, J. L. (2009). Just tell me what to do: Bringing back experimenter control in active contingency tasks with the command-performance procedure and finding cue density effects along the way. Canadian Journal of Experimental Psychology 63(1), 59–73. https://doi.org/10.1037/a0013403
- Hannah, S. D., Crump, M. J. C., Allan, L. G., & Siegel, S. (2009). Cue-interaction effects in contingency judgments using the streamed-trial procedure. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale, 63(2), 103-112. https://doi.org/10.1037/a0013521
- Hume, D. (1748). An enquiry concerning human understanding. Clarendon.
- Katagiri, M., Kao, S.-F., Simon, A. M., Castro, L., & Wasserman, E. A. (2007). Judgments of causal efficacy under constant and changing interevent contingencies. Behavioural Processes, 74(2), 251-264. https://doi.org/10.1016/j.beproc.2006.09.001
- Kunda, Z. (1990). The case for motivated reasoning. Psychological Bulletin, 108(3), 480-498. https://doi.org/10.1037/0033-2909.108.3.480
- Liu, W., Livesey, E. J., Lachnit, H., Don, H. J., & Thorwart, A. (2020). Does learning history shape the associability of outcomes? Further tests of the outcome predictability effect. PloS ONE, 15(12), e0243434. https://doi.org/10.1371/journal.pone.0243434
- Livesey, E. J., & McLaren, I. P. L. (2007). Elemental associability changes in human discrimination learning. Journal of Experimental Psychology. Animal Behavior Processes, 33(2), 148-159. https://doi.org/10.1037/0097-7403.33.2.14
- Lu, H., Yuille, A. L., Liljeholm, M., Cheng, P. W., & Holyoak, K. J. (2008). Bayesian generic priors for causal learning. Psychological Review, 115(4), 955-984. https://doi.org/10.1037/a0013256
- MacFarlane, D., Hurlstone, M. J., & Ecker, U. K. H. (2018). Reducing demand for ineffective health remedies: Overcoming the illusion of causality. Psychology and Health, 33(12), 1472-1489. https://doi.org/10.1080/08870446.2018.1508685
- Mandel, D. R., & Vartanian, O. (2009). Weighting of contingency information in causal judgement: Evidence of hypothesis dependence and use of a positive-test strategy. The Quarterly Journal Of Experimental Psychology, 62(12), 2388-2408. https://doi.org/10.1080/17470210902794148
- Marcu, A., Muller, C., Ream, E., & Whitaker, K. L. (2019). Online Information-Seeking About Potential Breast Cancer Symptoms: Capturing Online Behavior With an Internet Browsing Tracking Tool. Journal of medical Internet research, 21(2), e12400-e12400. https://doi.org/10.2196/12400
- Martínez, N., Rodríguez-Ferreiro, J., Barberia, I., & Matute, H. (2023). A debiasing intervention to reduce the causality bias in undergraduates: The role of a bias induction phase. Current psychology, 42, 32456-32468. https://doi.org/10.1007/s12144-022-04197-2
- Matute, H. (1995). Human reactions to uncontrollable outcomes: Further evidence for superstitions rather than helplessness. The Quarterly Journal Of Experimental Psychology, 48B(2), 142-157. https://doi.org/10.1080/14640749508401444
- Matute, H. (1996). Illusion of control: Detecting response-outcome independence in analytic but not in naturalistic conditions. Psychological Science, 7(5), 289-293. https://doi.org/10.1111/j.1467-9280.1996.tb00376.x
- Matute, H., & Blanco, F. (2014). Reducing the illusion of control when an action is followed by an undesired outcome. Psychonomic Bulletin & Review, 21(4), 1087-1093. https://doi.org/10.3758/s13423-014-0584-7
- Matute, H., Arcediano, F., & Miller, R. R. (1996). Test question modulates cue competition between causes and between effects. Journal of Experimental Psychology: Learning Memory and Cognition, 22(1), 182–196. https://doi.org/10.1037/0278-7393.22.1.182
- Matute, H., Blanco, F., & Díaz-Lago, M. (2019). Learning Mechanisms Underlying Accurate and Biased Contingency Judgments. Journal of Experimental Psychology: Animal Learning and Cognition, 45(4), 373-389. https://doi.org/10.1037/xan0000222
- Matute, H., Blanco, F., Yarritu, I., Díaz-Lago, M., Vadillo, M. A., & Barberia, I. (2015). Illusions of causality: How they bias our everyday thinking and how they could be reduced. Frontiers in psychology, 6, 888. https://doi.org/10.3389/fpsyg.2015.00888
- Matute, H., Vadillo, M. a, Vegas, S., & Blanco, F. (2007). Illusion of control in Internet users and college students. CyberPsychology & Behavior, 10(2), 176-181. https://doi.org/10.1089/cpb.2006.9971
- Matute, H., Vegas, S., & De Marez, P.-J. J. (2002). Flexible Use of Recent Information in Causal and Predictive Judgments. Journal of Experimental Psychology: Learning Memory and Cognition, 28(4), 714-725. https://doi.org/10.1037/0278-7393.28.4.714
- Matute, H., Yarritu, I., & Vadillo, M. A. (2011). Illusions of causality at the heart of pseudoscience. British journal of psychology, 102(3), 392-405. https://doi.org/10.1348/000712610X532210
- Moreno-Fernández, M. M., & Matute, H. (2020). Biased Sampling and Causal Estimation of Health-Related Information: Laboratory-Based Experimental Research. Journal of medical Internet research, 22(7), e17502-e17502. https://doi.org/10.2196/17502
- Moreno-Fernández, M. M., Blanco, F., & Matute, H. (2017). Causal illusions in children when the outcome is frequent. PloS ONE, 12(9), e0184707. https://doi.org/10.1371/journal.pone.0184707
- Moreno-Fernández, M. M., Blanco, F., & Matute, H. (2021). The tendency to stop collecting information is linked to illusions of causality. Scientific Reports, 11(1), 3942. https://doi.org/10.1038/s41598-021-82075-w
- Murphy, R. a, Schmeer, S., Vallée-Tourangeau, F., Mondragón, E., & Hilton, D. (2011). Making the illusory correlation effect appear and then disappear: The effects of increased learning. Quarterly journal of experimental psychology, 64(1), 24-40. https://doi.org/10.1080/17470218.2010.493615
- Neunaber, D. J., & Wasserman, E. A. (1986). The effects of unidirectional versus bidirectional rating procedures on college students’ judgments of response-outcome contingency. Learning and Motivation, 17(2), 162-179. https://doi.org/10.1016/0023-9690(86)90008-1
- Ng, D. W., Lee, J. C., & Lovibond, P. F. (2023). Unidirectional rating scales overestimate the illusory causation phenomenon. Quarterly journal of experimental psychology (2006). Advance online publication. https://doi.org/10.1177/17470218231175003
- Perales, J. C., & Shanks, D. R. (2007). Models of covariation-based causal judgment: A review and synthesis. Psychonomic Bulletin & Review, 14(4), 577-596. https://doi.org/10.3758/bf03196807
- Pineño, O. (2007). A response rule for positive and negative stimulus interaction in associative learning and performance. Psychonomic Bulletin & Review, 14(6), 1115-1124. https://doi.org/10.3758/bf03193100
- Rescorla, R. A., & Wagner, A. R. (1972). A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. En A. H. Black & W. F. Prokasy (Eds.), Classical Conditioning II: current research and theory (pp. 64-99). Appleton-Century-Crofts.
- Rodríguez-Ferreiro, J., Vadillo, M. A., & Barberia, I. (2023). Debiasing Causal Inferences: Over and Beyond Suboptimal Sampling. Teaching of Psychology, 50(3), 230-236. https://doi.org/10.1177/00986283211048394
- Saltor, J., Barberia, I., & Rodríguez-Ferreiro, J. (2023). Thinking disposition, thinking style, and susceptibility to causal illusion predict fake news discriminability. Applied Cognitive Psychology, 37(2), 360-368. https://doi.org/10.1002/acp.4008
- Shanks, D. R., & Dickinson, A. (1987). Associative accounts of causality judgment. In The psychology of learning and motivation: Advances in research and theory, Vol. 21 (pp. 229-261). Academic Press.
- Shanks, D. R., & Dickinson, A. (1988). Associative Accounts of Causality Judgment. The psychology of learning and motivation: Advances in research and theory, 21, 229-261. https://doi.org/10.1016/S0079-7421(08)60030-4
- Sulik, J., Ross, R. M., Balzan, R., & McKay, R. (2023). Delusion-Like Beliefs and Data Quality: Are Classic Cognitive Biases Artifacts of Carelessness? Journal of Psychopathology and Clinical Science, 6(132), 794-760. https://doi.org/10.1037/abn0000844
- Sulik, J., Ross, R., & Mckay, R. (2020). The contingency illusion bias as a potential driver of science denial. In S. Denison., M. Mack, Y. Xu, & B.C. Armstrong (Eds.), Proceedings of the 42nd Annual Conference of the Cognitive Science Society (pp. 829-835). Austin, TX: Cognitive Science Society.
- Thorwart, A., Livesey, E. J., Wilhelm, F., Liu, W., & Lachnit, H. (2017). Learned predictiveness and outcome predictability effects are not simply two sides of the same coin. Journal of Experimental Psychology. Animal Learning and Cognition, 43(4), 341-365. https://doi.org/10.1037/xan0000150
- Torres, M. N., Barberia, I., & Rodriguez-Ferreiro, J. (2020). Causal illusion as a cognitive basis of pseudoscientific beliefs. British journal of psychology, 111(4), 840-852. https://doi.org/10.1111/bjop.12441
- Vadillo, M. A., & Matute, H. (2007). Predictions and causal estimations are not supported by the same associative structure. Quarterly journal of experimental psychology, 60(3), 433-447. https://doi.org/10.1080/17470210601002520
- Vadillo, M. A., Matute, H., & Blanco, F. (2013). Fighting the Illusion of Control: How to Make Use of Cue Competition and Alternative Explanations. Universitas Psychologica, 12(1), 261-270. Vadillo, M. A., Musca, S. C., Blanco, F., & Matute, H. (2011). Contrasting cue-density effects in causal and prediction judgments. Psychonomic bulletin & review, 18, 110-115. https://doi.org/10.3758/s13423-010-0032-2
- Vadillo, M. A., Vegas, S., & Matute, H. (2004). Frequency of judgment as a context-like determinant of predictive judgments. Memory & cognition, 32(7), 1065-1075. https://doi.org/10.3758/BF03196882
- Vicente, L., Blanco, F., & Matute, H. (2023). I want to believe: Prior beliefs influence judgments about the effectiveness of both alternative and scientific medicine. Judgment and Decision Making, 18, 1-1.
- Wasserman, E. A. (1990). Detecting Response-Outcome Relations: Toward an Understanding of the Causal Texture of the Environment. Psychology of Learning and Motivation - Advances in Research and Theory, 26(C), 27-82. https://doi.org/10.1016/S0079-7421(08)60051-1
- Wasserman, E. A., Dorner, W. W., & Kao, S. (1990). Contributions of Specific Cell Information to Judgments of Interevent Contingency. Cognition, 16(3), 509-521.
- White, P. A. (2004). Causal judgment from contingency information: A systematic test of the pCI rule. Memory & cognition, 32, 353-368. https://doi.org/10.3758/bf03195830
- Willett, C. L., & Rottman, B. M. (2021). The Accuracy of Causal Learning Over Long Timeframes: An Ecological Momentary Experiment Approach. Cognitive Science, 45(7), e12985. https://doi.org/10.1111/cogs.12985
- Yarritu, I., & Matute, H. (2015). Previous knowledge can induce an illusion of causality through actively biasing behavior. Frontiers in Psychology, 6, 389-389. https://doi.org/10.3389/fpsyg.2015.00389