Abstract
Individuals interpret themselves as causal agents when executing an action to achieve an outcome, even when action and outcome are independent. How can illusion of control be managed? Once established, does it decay? This study aimed to analyze the effects of valence, probability of the outcome [p(O)] and probability of the actions performed by the participant [p(A)], on the magnitude of judgments of control and corresponding associative measures (including Rescorla–Wagner’s, Probabilistic Contrast, and Cheng’s Power Probabilistic Contrast models). A traffic light was presented on a computer screen to 81 participants who tried to control the green or red lights by pressing the spacebar, after instructions describing a productive or a preventive scenario. There were 4 blocks of 50 trials under all of 4 different p(O)s in random order (0.10, 0.30, 0.70, and 0.90). Judgments were assessed in a bidimensional scale. The 2 × 4 × 4 mixed experimental design was analyzed through General Linear Models, including factor group (between-subject valence), and block and p(O) (within subjects). There was a small effect of group and a large and direct effect of p(O) on judgments. Illusion was reported by 66% of the sample and was positive in the productive group. The oscillation of p(O) produced stronger illusions; decreasing p(O)s produced nil or negative illusions. Only Rescorla–Wagner’s could model causality properly. The reasons why p(A) and the other models could not generate significant results are discussed. The results help to comprehend the importance of keeping moderate illusions in productive and preventive scenarios.
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Notes
This situation does not make sense in many countries today. Despite legislation, in Brazil, it is still common for pedestrians not to have a preference between red and green lights. Pedestrians and vehicles often continue during the red light.
In a pre-analysis made immediately after the 18th participant’s session, a systematic sampling error was detected: Block 1 had unbalanced probabilities, with few cases of p(O) = 0.10 and 0.70 in the productive sample and few cases of p(O) = 0.30 and 0.90 in the preventive sample. The computer script was corrected, including compensation of the proportions. Unfortunately, after some days the script containing the error was put back into use by mistake. However, the chosen statistical models for the analysis were robust to unbalanced groups and were also calculated with the numeric probabilities recoded to the categorical values Low p(O), corresponding to p(O) = 0.10 and 0.30, and High p(O), corresponding to p(O) = 0.70 and 0.90, the conclusions were the same.
As participants used a mouse to click on a graphical scale without numerical labels, values from − 5 to 5 were counted as zero.
Schultz (1998) argued that dopamine neurons show activation–depression responses after liquid and food (unconditioned stimuli) reward information and conditioned reward-predicting stimuli, as well as new and salient ones, and consequently are involved in learning behavior. These neurons fail to discriminate between rewards, and emit alerting messages in situations where presence or absence of a reward is surprising: event predictability is necessary for rewarding responses. Events that are better than predicted activate dopamine neurons, events as good as predicted do not influence them, and events worse than predicted depress the neurons. So, dopamine systems are dependent on unpredictable events, and are related to reinforcement learning theories as they signalize prediction errors (both for better and for worse) through which learning occurs. Fully acquired behaviors are predictable and related events do not activate dopamine neurons.
References
Benvenuti, M. F. L., de Toledo, T. F. N., Simões, R. A. G., & Bizarro, L. (2017). Comparing illusion of control and superstitious behavior: rate of responding influences judgment of control in a free-operant procedure. Learning and Motivation. https://doi.org/10.1016/j.lmot.2017.10.002.
Biner, P., Johnston, B., Summers, A., & Chudzynski, E. (2009). Illusory control as a function of the motivation to avoid randomly determined preventive outcomes. Motivation & Emotion, 33(1), 32–41. https://doi.org/10.1007/s11031-008-9111-3.
Blanco, F., & Matute, H. (2015). Exploring the factors that encourage the illusions of control: the case of preventive illusions. Experimental Psychology, 62(2), 131. https://doi.org/10.1027/1618-3169/a000280.
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.
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, 1119–1140. https://doi.org/10.1037/0278-7393.29.6.1119.
Cheng, P. W. (1997). From covariation to causation: a causal power theory. Psychological Review, 104, 367–405. https://doi.org/10.1037/0033-295X.104.2.367.
Cheng, P. W., & Holyoak, K. J. (1995). Complex adaptive systems as intuitive statisticians: Causality contingency, and prediction. In J. -A. Meyer & H. Roitblat (Eds.), Comparative approaches to cognition (pp. 271–302). Cambridge, MA: MIT Press.
Cheng, P. W., Park, J., Yarlas, A. S., & Holyoak, K. J. (1996). A causal-power theory of focal sets. In D. R. Shanks, K. J. Holyoak & D. L. Medin (Eds.), The psychology of learning and motivation: causal learning (Vol (34, pp. 313–355). San Diego: Academic Press.
Chou, Y. M., Polansky, A. M., & Mason, R. L. (1998). Transforming nonnormal data to normality in statistical process control. Journal of Quality Technology, 30(2), 133.
Collins, D. J., & Shanks, D. R. (2006). Short article: conformity to the power PC theory of causal induction depends on the type of probe question. Quarterly Journal of Experimental Psychology, 59(2), 225–232. https://doi.org/10.1080/17470210500370457.
Coventry, K. R., & Norman, A. C. (1998). Arousal, erroneous verbalizations and the illusion of control during a computer-generated gambling task. British Journal of Psychology, 89(4), 629–645. https://doi.org/10.1111/j.2044-8295.1998.tb02707.x.
Eitam, B., Kennedy, P. M., & Higgins, E. T. (2013). Motivation from control. Experimental Brain Research, 229(3), 475–484. https://doi.org/10.1007/s00221-012-3370-7.
Fast, N. J., Gruenfeld, D. H., Sivanathan, N., & Galinsky, A. D. (2009). Illusory control: a generative force behind power’s far-reaching effects. Psychological Science (Wiley-Blackwell), 20(4), 502–508. https://doi.org/10.1111/j.1467-9280.2009.02311.x.
Gazzaniga, M. S. (2010). Neuroscience and the correct level of explanation for understanding mind. Trends in Cognitive Sciences, 14(7), 297. https://doi.org/10.1016/j.tics.2010.04.005.
Hannah, S., Allan, L. G., & Siegel, S. (2007). The consequences of surrendering a degree of freedom to the participant in a contingency assessment task. Behavioural Processes, 74, 265–273. https://doi.org/10.1016/j.beproc.2006.09.007.
Hollis, K. L. (1997). Contemporary research on pavlovian conditioning: a “new” functional analysis. American Psychologist, 52(9), 956–965. https://doi.org/10.1037/0003-066X.52.9.956.
Hoover, A., Singh, A., Fishel-Brown, S., & Muth, E. (2012). Real-time detection of workload changes using heart rate variability. Biomedical Signal Processing and Control, 7(4), 333–341. https://doi.org/10.1016/j.bspc.2011.07.004.
Jenkins, H. M., & Ward, W. C. (1965). Judgment of contingency between responses and outcomes. Psychological Monographs, 79(1), 1–17. https://doi.org/10.1037/h0093874.
Karsh, N., & Eitam, B. (2015). I control therefore I do: judgments of agency influence action selection. Cognition, 138, 122–131. https://doi.org/10.1016/j.cognition.2015.02.002.
Karsh, N., Eitam, B., Mark, I., & Higgins, E. T. (2016). Bootstrapping agency: how control-relevant information affects motivation. Journal of Experimental Psychology: General, 145(10), 1333–1350. https://doi.org/10.1037/xge0000212.
Langer, E. J. (1975). The Illusion of control. Journal of Personality & Social Psychology, 32(2), 311–328. https://doi.org/10.1037/0022-3514.32.2.311.
Langer, E. J., & Roth, J. (1975). Heads I win, tails it’s chance: the illusion of control as a function of the sequence of outcomes in a purely chance task. Journal of Personality & Social Psychology, 32(6), 951–955. https://doi.org/10.1037/0022-3514.32.6.951.
Lober, K., & Shanks, D. R. (1999). Experimental falsification of Cheng’s (1997) power PC theory of causal induction. Psychological Review. Retrieved from ftp://ftp.repec.org/opt/ReDIF/RePEc/els/esrcls/PowerPC.pdf.
Lober, K., & Shanks, D. R. (2000). Is causal induction based on causal power? Critique of Cheng (1997). Psychological Review, 107(1), 195. https://doi.org/10.1037/0033-295X.107.1.195.
Matute, H. (1996). Illusion of control: detecting response-outcome independence in analytic but not in naturalistic conditions. Psychological Science, 7, 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., 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., Blanco, F., & Musca, S. C. (2007, January). Either greedy or well informed: The reward maximization–unbiased evaluation trade-off. In Proceedings of the European Cognitive Science Conference (pp. 341–346). Hove, UK: Erlbaum.
Msetfi, R. M., Murphy, R. A., Simpson, J., & Kornbrot, D. E. (2005). Depressive realism and outcome density bias in contingency judgments: the effect of the context and intertrial interval. Journal of Experimental Psychology: General, 134, 10–22. https://doi.org/10.1037/0096-3445.134.1.10.
Perales, J. C., & Shanks, D. R. (2003). Normative and descriptive accounts of the influence of power and contingency on causal judgment. Quarterly Journal of Experimental Psychology, 56A, 977–1007. https://doi.org/10.1080/02724980244000738.
Presson, P. K., & Benassi, V. A. (1996). Illusion of control: A meta-analytic review. Journal of Social Behavior & Personality, 11(3), 493–510.
Rescorla, R. A. (1966). Predictability and number of pairings in Pavlovian fear conditioning. Psychonomic Science, 4(11), 383–384. https://doi.org/10.3758/BF03342350.
Rescorla, R. A., & Wagner, A. R. (1972). A theory of pavlovian conditioning: variations in the effectiveness of reinforcement and nonreinforcement. Classical conditioning II: Current research and theory, 2, 64–99.
Schultz, W. (1998). Predictive reward signal of dopamine neurons. Journal of neurophysiology, 80(1), 1–27. https://doi.org/10.1152/jn.1998.80.1.1.
Stefan, S., & David, D. (2013). Recent developments in the experimental investigation of the illusion of control. A meta-analytic review. Journal of Applied Social Psychology, 43(2), 377–386. https://doi.org/10.1111/j.1559-1816.2013.01007.x.
Taylor, S. E., & Brown, J. D. (1988). Illusion and well-being: a social psychological perspective on mental health. Psychological bulletin, 103(2), 193. https://doi.org/10.1037/0033-2909.103.2.193.
Vadillo, M. A., Blanco, F., Yarritu, I., & Matute, H. (2016). Single-and dual-process models of biased contingency detection. Experimental psychology, 63, 3–19. https://doi.org/10.1027/1618-3169/a000309.
Visser, I., Raijmakers, M. E., & Molenaar, P. (2002). Fitting hidden Markov models to psychological data. Scientific Programming, 10(3), 185–199. https://doi.org/10.1155/2002/874560.
Wohl, M. J. a, & Enzle, M. E. (2003). The effects of near wins and near losses on self-perceived personal luck and subsequent gambling behavior. Journal of Experimental Social Psychology, 39, 184–191. https://doi.org/10.1016/S0022-1031(02)00525-5.
Yarritu, I., Matute, H., & Vadillo, M. A. (2014). Illusion of control: The role of personal involvement. Experimental Psychology, 61(1), 38–47. https://doi.org/10.1027/1618-3169/a000225.
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This study was financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001, grant number 1,364,428. The content is associated with and the published results are part of the doctoral thesis of the first author, Behavioral and psychophysiological measures on illusion of control in productive and preventive scenarios and in the context of safety risks in Programa de Pós-Graduação em Psicologia of Universidade Federal do Rio Grande do Sul and in Programa de Doctorado em Psicología de Universidad de Granada. The authors declare that they have no conflict of interest. The study has been approved by the UFRGS Instituto de Psicologia Research Ethics Committee and has been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Informed consent was obtained from all individual participants included in the study. Any original materials used to conduct the research (including all primary data) will be made available to the journal and other researchers for purposes of replicating the procedure or reproducing the results; they can be obtained from the first author upon reasonable request (via email to: reinaldoags@gmail.com). The authors would like to thank Fernando Blanco and Helena Matute, who kindly provided the original E-Prime light bulb task script to be adapted for the current experiment; and Adriane Ribeiro Teixeira and Pricila Sleifer, from Laboratório de Audiologia do Curso de Fonoaudiologia da UFRGS, where data were collected.
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Simões, R.A.G., Benvenuti, M.F.L., Rodrigues, A.d.S. et al. Persistence of repeated self-reported illusion of control as a product of action and outcome association in productive and preventive scenarios. Psychological Research 84, 1184–1197 (2020). https://doi.org/10.1007/s00426-019-01147-9
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DOI: https://doi.org/10.1007/s00426-019-01147-9