Constructive Biases in Clinical Judgment.
Clinical decision making
Constructive influences
Eating disorders
Evaluation bias
Quantum probability theory
Journal
Topics in cognitive science
ISSN: 1756-8765
Titre abrégé: Top Cogn Sci
Pays: United States
ID NLM: 101506764
Informations de publication
Date de publication:
07 2022
07 2022
Historique:
revised:
15
05
2021
received:
05
02
2021
accepted:
19
05
2021
pubmed:
4
6
2021
medline:
22
7
2022
entrez:
3
6
2021
Statut:
ppublish
Résumé
With a pair of oppositely valenced stimuli, rating the first one sometimes leads to a more extreme evaluation for the second (e.g., if the second is negatively valenced, rating the first stimulus would lead to a more negative rating for the second). We considered an evaluation bias in the case of clinical diagnosis relating to eating disorders. A population sample which included experienced clinical psychologists and psychiatrists showed partial evidence of an evaluation bias, when judging descriptions of individuals designed to be consistent with eating disorders or not. Quantum probability theory, the probability rules from quantum mechanics without any of the physics, is particularly well-suited to modeling the evaluation bias (and constructive influences generally), because a measurement (or judgment) can change the state of the system. We applied a previous quantum model to the present result, an extension of the model embodying noisy processes, and belief adjustment model. We discuss how model fits inform an examination of rationality in the observed behavior.
Types de publication
Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
508-527Informations de copyright
© 2021 Cognitive Science Society LLC.
Références
American Psychological Association Presidential Task Force on Evidence-Based Practice. (2006). Evidence-based practice in psychology. American Psychologist, 61(4), 271-285.
Ariely, D., & Norton, M. I. (2008). How actions create - not just reveal - preferences. Trends in Cognitive Sciences, 12, 13-16.
Arkes, H. R., & Harkness, A. R. (1980). Effect of making a diagnosis on subsequent recognition of symptoms. Journal of Experimental Psychology: Human Learning and Memory, 6, 568-575.
Bauer, R. M. (2007). Evidence-based practice in psychology: Implications for research and research training. Journal of Clinical Psychology, 63, 685-694.
Brehm, J. W. (1956). Post-decision changes in the desirability of choice alternatives. Journal of Abnormal and Social Psychology, 52, 384-389.
Broekaert, J. B., Busemeyer, J. R., & Pothos, E. M. (2020). The disjunction effect in two-stage simulated gambles. An experimental study and comparison of a heuristic logistic, Markov and quantum-like model. Cognitive Psychology, 117, 101262.
Busemeyer, J. R., & Bruza, P. D. (2012). Quantum models of cognition and decision. Cambridge: Cambridge University Press.
Busemeyer, J. R., Pothos, E., Franco, R., & Trueblood, J. S. (2011). A quantum theoretical explanation for probability judgment ‘errors’. Psychological Review, 118(2), 193-218.
Cierpiałkowska, L., & Sęk, H. (2016). Psychologia Kliniczna. Warszawa: Wydawnictwo Naukowe PWN.
Currin, L., Walter, G., Treasure, J., Nodder, J., Stone, C., & Yeomans, M. (2007). The use of guidelines for dissemination of 'best practice' in primary care of patients with eating disorders. International Journal of Eating Disorders, 40, 476-479.
Garb, H. N. (1998). Studying the clinician: Judgment research and psychological assessment. Washington, DC: American Psychological Association.
Garb, H. N. (2003). Clinical Judgment and Mechanical Prediction In J. R. Graham, J. C. Naglieri (Eds.), Handbook of Psychology. Chichester: John Wiley and Sons, 27-42.
Garner, D. (2004). EDI 3 Eating Disorder Inventory-3. Florida: Psychological Assessment Recources, Inc.
Gigerenzer, G., & Brighton, H. (2009). Homo heuristicus: Why biased minds make better inferences. Topics in Cognitive Science, 1(1), 107-143.
Gigerenzer, G., & Todd, P. (1999). Simple heuristics that make us smart.. Oxford University Press.
Gigerenzer, G., & Selten, R. (2001). Bounded rationality: The adaptive toolbox.. MIT Press.
Gloeckner, A., Betsch, T., & Schindler, N. (2009). Coherence shifts in probabilistic inference tasks. Journal of Behavioral Decision Making, 23, 439-462.
Goodman, N. D., & Frank, M. C. (2016). Pragmatic language interpretation as probabilistic inference. Trends in Cognitive Sciences, 20, 818-829.
Hermann, R. C., Ettner, S. L., Dorwart, R. A., Langman-Dorwart, N., & Kleinman, S. (1999). Diagnoses of patients treated with ECT: A comparison of evidence-based standards with reported use. Psychiatric Services, 50, 1059-1065.
Hogarth, R. M., & Einhorn, H. J. (1992). Order effects in belief updating: The belief-adjustment model. Cognitive Psychology, 24, 1-55.
Huppert, J. D., Fufka, L. F., Barlow, D. H., Gorman, J. M., Shear, M. K., & Woods, S. W. (2001). Therapist, therapist variables and cognitive-behavioral therapy outcome in a multicenter trial for panic disorder. Journal of Consulting and Clinical Psychology, 69, 747-755.
Icard, T., & Goodman, N. D. (2015). A resource-rational approach to the causal frame problem. In CogSci 2015.
Izydorczyk, B. (2011a). A psychological diagnosis of the structure of the body self in a group of selected young Polish females without eating or the mental disorders. Archives of Psychiatry and Psychotherapy, 2, 21-36.
Izydorczyk, B. (2011b). A psychological profile of the bodily self characteristics in women suffering from bulimia nervosa. In P. Hay (Ed.), New insights into the prevention and treatment of bulimia nervosa (pp. 147-167). Croatia: Intech Open Access Publisher.
Izydorczyk, B. (2013). Selected psychological traits and body image characteristics in females suffering from binge eating disorder. Archives of Psychiatry and Psychotherapy, 1, 19-33.
Jones, M., & Love, B. C. (2011). Bayesian fundamentalism or enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition. Behavioral and Brain Sciences, 34, 169, 231.
Kahneman, D. (2001). Thinking fast and slow. London: Penguin.
Kass, R. E., & Raftery, A. E. (1995). Bayes factors. Journal of the American Statistical Association, 90(430), 773-795.
Kayne, N. T., & Alloy, L. B. (1988). Clinician and patient as aberrant actuaries: Expectation-based distortions in assessment of covariation. In L. Y. Abramson (Ed.), Social cognition and clinical psychology: A synthesis (pp. 295-365). New York: Guilford Press.
Kemp, C., Perfors, A., & Tenenbaum, J. B. (2007). Learning overhypotheses with hierarchical Bayesian models. Developmental Science, 10(3), 307-321.
Kvam, P. D., & Pleskac, T. J. (2017). A quantum information architecture for cue-based heuristics. Decision, 4, 197.
Lieder, F., & Griffiths, T. L. (2019). Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources. Behavioral and Brain Sciences, 43, 1-85.
Lieder, F., Griffiths, T. L., & Hsu, M. (2018). Overrepresentation of extreme events in decision making reflects rational use of cognitive resources. Psychological Review, 125, 1-32.
Lilienfeld, S. O., Ritschel, L. O., Lynn, S. J., Brown, A. P., Cautin, R. L., & Latzman, R. D. (2013). The research-practice gap: Bridging the schism between eating disorder researchers and practitioners. International Journal of Eating Disorders, 46, 386-394.
Muller, M. J., & Davids, E. (1999). Relationship of psychiatric experience and inter-rater reliability in assessment of negative symptoms. Journal of Nervous and Mental Diseases, 187, 316-318.
Norcross, J. C. (2002). Psychotherapy relationships that work: Therapist contributions and responsiveness to patient needs. New York: Oxford University Press.
Oaksford, M., & Chater, N. (2009). Précis of Bayesian rationality: The probabilistic approach to human reasoning. Behavioral and Brain Sciences, 32, 69-120.
Pothos, E. M., & Busemeyer, J. R. (2009). A quantum probability explanation for violations of 'rational' decision theory. Proceedings of the Royal Society B, 276, 2171-2178.
Pothos, E. M., & Busemeyer, J. R. (2013). Can quantum probability provide a new direction for cognitive modeling? Behavioral & Brain Sciences, 36, 255-327.
Pothos, E. M., Busemeyer, J. R., & Trueblood, J. S. (2013). A quantum geometric model of similarity. Psychological Review, 120, 679-696.
Pothos, E. M., Busemeyer, J. R., Shiffrin, R. M., & Yearsley, J. M. (2017). The rational status of quantum cognition. Journal of Experimental Psychology: General, 146, 968-987.
Sharot, T., Velasquez, C. M., & Dolan, R. J. (2010). Do decisions shape preference?: Evidence from blind choice. Psychological Science, 21, 1231-1235.
Shepard, R. N. (1992). The perceptual organization of colors: An adaptation to regularities of the terrestial world? In J. H. Barkow, L. Cosmides, & J. Tooby (Eds.), The adapted mind. Oxford: Oxford University Press, 495-532.
Simons, D. J., Shoda, Y., & Lindsay, D. S. (2017). Constraints on generality (COG): A proposed addition to all empirical papers. Perspectives on Psychological Science, 12(6), 1123-1128.
Straus, S. E., Glasziou, P., Richardson, W. S., & Haynes, R. B. (2011). Evidence-based medicine: How to practice and teach EBM. New York: Churchill Livingstone.
Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. (2011). How to grow a mind: Statistics, structure, and abstraction. Science, 331, 1279-1285.
Wang, Z., Solloway, T., Shiffrin, R. M., & Busemeyer, J. R. (2014). Context effects produced by question orders reveal quantum nature of human judgments. Proceedings of the National Academy of Sciences, 111, 9431-9436.
White, L. C., Pothos, E. M., & Busemeyer, J. R. (2014). Sometimes it does hurt to ask: The constructive role of articulating impressions. Cognition, 133, 48-64.
White, L. C., Barque-Duran, A., & Pothos, E. M. (2015). An investigation of a quantum probability model for the constructive effect of affective evaluation. Philosophical Transactions of the Royal Society A, 374, 20150142.
White, L. C., Pothos, E. M., & Jarrett, M. (2020). The cost of asking: How evaluations bias subsequent judgments. Decision, 7, 259-286.
Youngstrom, E. A. (2013). Future directions in psychological assessment: Combining evidence-based medicine innovations with psychology's historical strengths to enhance utility. Journal of Clinical Child and Adolescent Psychology, 42, 139-159.