article

Methodological Review: The role of emotion in decision-making: A cognitive neuroeconomic approach towards understanding sexual risk behavior

Authors:

Lily A. Gutnik,

A. Forogh Hakimzada,

Nicole A. Yoskowitz,

Vimla L. PatelAuthors Info & Claims

Journal of Biomedical Informatics, Volume 39, Issue 6

Pages 720 - 736

https://doi.org/10.1016/j.jbi.2006.03.002

Published: 01 December 2006 Publication History

Abstract

Models of decision-making usually focus on cognitive, situational, and socio-cultural variables in accounting for human performance. However, the emotional component is rarely addressed within these models. This paper reviews evidence for the emotional aspect of decision-making and its role within a new framework of investigation, called neuroeconomics. The new approach aims to build a comprehensive theory of decision-making, through the unification of theories and methods from economics, psychology, and neuroscience. In this paper, we review these integrative research methods and their applications to issues of public health, with illustrative examples from our research on young adults' safe sex practices. This approach promises to be valuable as a comprehensively descriptive and possibly, better predictive model for construction and customization of decision support tools for health professionals and consumers.

References

[1]

Steinbrook, R., The AIDS epidemic in 2004. New Engl J Med. v351 i2. 115-117.

[2]

Patel VL, Gutnik LA, Yoskowitz NA, O'Sullivan LF, Kaufman DR. Patterns of reasoning and decision making about condom use by urban college students. AIDS Care. in press.

[3]

Hastie, R. and Dawes, R.M., Rational choice in an uncertain world: the psychology of judgment and decision making. Sage Publications, Inc, Thousand Oaks, CA, US.

[4]

Falzer, P.R., Cognitive schema and naturalistic decision making in evidence-based practices. J Biomed Informat. v37 i2. 86-98.

[5]

Beach, L.R. and Lipshitz, R., Why classical decision theory is an inappropriate standard for evaluating and aiding most human decision making. In: Klein, G.A., Orasanu, J. (Eds.), Decision making in action: models and methods, Ablex Publishing, Westport,US. pp. 21-35.

[6]

Patel, V.L., Kaufman, D.R. and Arocha, J.F., Emerging paradigms of cognition in medical decision-making. J Biomed Informat. v35 i1. 52-75.

[7]

Breakwell, G.M., Risk estimation and sexual behaviour: a longitudinal study of 16-21-year-olds. J Health Psychol. v1. 79-91.

[8]

Bakker, A.B., Buunk, B.P., Siero, F.W. and van Den Eijnden, R.J.J.M., Application of a modified health belief model to HIV preventive behavioral intentions among gay and bisexual men. Psychol Health. v12. 481-492.

[9]

Tversky, A. and Kahneman, D., Judgement under uncertainty: heuristics and biases. Science. v185. 1124-1131.

[10]

McNeil, B.J., Pauker, S., Sox Jr., H. and Tversky, A., On the elicitation of preferences for alternative therapies. New Engl J Med. v306. 1259-1262.

[11]

Chapman, G.B. and Elstein, A.S., Cognitive processes and biases in medical decision-making. Decision-making in health care: theory, psychology, and applications. 183-210.

[12]

Hardman, D.K. and Ayton, P., Arguments for qualitative risk assessment-the star risk adviser. Expert Syst. v14. 24-36.

[13]

Fischhoff, B., Risk perception and communication unplugged: twenty years of process. Addressing agencies' risk communication needs: next steps. Risk Anal. v15. 137-145.

[14]

Buchanan, A., Assessing risk: limits to the measurement of the target behaviours. Int Rev Psychiatr. v9. 195-200.

[15]

Holtzman, D., Mathis, M.P., Kann, L., Collins, J.L. and Kolbe, L.J., Trends in risk behaviors for HIV-infection among US high-school students, 1989-1991. AIDS Educ Prev. v7. 265-277.

[16]

Anderson, J.E., Cheney, R., Clatts, M., Faruque, S., Kipke, M. and Long, A., HIV risk behavior, street outreach, and condom use in eight high-risk populations. AIDS Educ Prev. v8. 191-204.

[17]

O'Sullivan, L.F. and Byers, E.S., Gender differences in responses to discrepancies in desired level of sexual intimacy. J Psychol Hum Sex. v8. 49-67.

[18]

Rotheram-Borus, M.J., Lee, M., Zhou, S., O'Hara, P., Birnbaum, J.M. and Swendeman, D., Variation in health and risk behavior among youth living with HIV. AIDS Educ Prev. v13. 42-54.

[19]

Irwin, J.R., Jones, L.E. and Mundo, D., Risk Perception and Victim Perception - the Judgment Of HIV Cases. J Behav Decis Mak. v9. 1-22.

[20]

Campbell, C.A. and Peck, M.D., Issues in HIV/AIDS service delivery to high risk youth. Harrington Park Press/Haworth Press, New York.

[21]

Bowler, S., Sheon, A.R., D'Angelo, L.J. and Vermund, S.H., HIV and AIDS among adolescents in the United States: increasing risk in the 1990s. Special Issue: HIV/AIDS and adolescents: an international perspective. J Adolesc. v15. 345-371.

[22]

Geney, K.L., Lewis, S.Y., Henderson, R. and Castillo, S., Youth and HIV antibody testing: building skills for risk assessment and counseling. Int Conf AIDS. v11. 4915

[23]

Blanton, H. and Gerrard, M., Effect of sexual motivation on men's risk perception of sexually transmitted disease: there must be 50 ways to justify a lover. Health Pyschol. v16. 374-379.

[24]

Whaley, A.L., Differential risk perceptions for unintended pregnancy, STDs, and HIV/AIDS among urban adolescents: some preliminary findings. J Genet Psychol. v161 i4. 435-452.

[25]

Raghubir, P. and Menon, G., AIDS and me, never the twain shall meet: the effects of information accessibility on judgments of risk and advertising effectiveness. J Consum Res. v25 i1. 52-63.

[26]

McCall, M., DePalma, M.T., English, G. and Potts, K., Perceived self- and other-vulnerability to AIDS: false consensus biases. Am J Health Behav. v20 i6. 400-405.

[27]

Medin, D.L. and Bazerman, M.H., Broadening behavioral decision research: multiple levels of cognitive processing. Psychon Bull Rev. v6 i4. 533-546.

[28]

Patel, V.L., Arocha, J.F. and Kaufman, D.R., Diagnostic reasoning and medical expertise. Psychol Learning Motiv. v31. 187-252.

[29]

Lesgold, A.M., Rubinson, H., Feltovich, P., Glaser, R., Klopfer, D. and Wang, Y., Expertise in a complex skill: diagnosing x-ray pictures. In: Chi, M.T.H., Glaser, R., Farr, M. (Eds.), The Nature of Expertise, Erlbaum, Hillsdale, NJ.

[30]

Sivaramakrishnan, M. and Patel, V.L., Reasoning about childhood nutritional deficiencies by mothers in rural India: a cognitive analysis. Social Sci Med. v37. 937-952.

[31]

Patel, V.L., Kaufman, D.R. and Arocha, J.F., Conceptual change in the biomedical and health sciences domain. In: Glaser, R. (Ed.), Advances in instructional psychology: educational design and cognitive science, Lawrence Erlbaum Associates, Mahwah, NJ. pp. 329-392.

[32]

Eisemon, T.O., Patel, V.L. and Ole Sena, S., Uses of formal and informal knowledge in the comprehension of instructions for oral rehydration therapy in Kenya. Social Sci Med. v25. 1225-1234.

[33]

Rogoff B, Lave J, editors. Everyday cognition: Its development in social context; 1984.

[34]

Klein, G.A. and Calderwood, R., Decision models: some lessons from the field. IEEE Trans Syst Man Cybern. v21 i5. 1018-1026.

[35]

Leprohon, J. and Patel, V.L., Decision-making strategies for telephone triage in emergency medical services. Med Decis Mak. v15. 240-253.

[36]

Benner, P. and Tanner, C., Clinical judgment: how expert nurses use intuition. Am J Nurs. 23-31.

[37]

Crandall, B. and Calderwood, R., Clinical Assessment skills of experienced neonatal intensive care nurses: national center for nursing research. National Institutes of Health.

[38]

Patel VL, Branch T, Gutnik L, Arocha J. Shaping understanding of HIV through negotiation and conflict resolution during peer group discussion. Adv Health Sci Educ in press.

[39]

Krawczyk, D.C., Contributions of the prefrontal cortex to the neural basis of human decision making. Neurosci Biobehav Rev. v26 i6. 631-664.

[40]

Fellows, L.K., The cognitive neuroscience of human decision making: a review and conceptual framework. Behav Cognit Neurosci Rev. v3 i3. 159-172.

[41]

Bechara, A., Damasio, H. and Damasio, A.R., Emotion, decision making and the orbitofrontal cortex. Cerebral Cortex. v10 i3. 295-307.

[42]

Bechara, A., Damasio, H., Tranel, D. and Damasio, A.R., Deciding advantageously before knowing the advantageous strategy. Science. v275 i5304. 1293-1294.

[43]

Goldstein, R.Z. and Volkow, N.D., Drug addiction and its underlying neurobiological basis: neuroimaging evidence for the involvement of the frontal cortex. Am J Psychiatr. v159 i10. 1642-1652.

[44]

Volkow, N.D. and Fowler, J.S., Addiction, a disease of compulsion and drive: involvement of the orbitofrontal cortex. Cerebral Cortex. v10 i3. 318-325.

[45]

Maia, T.V. and McClelland, J.L., A reexamination of the evidence for the somatic marker hypothesis: what participants really know in the Iowa gambling task. Proc Natl Acad Sci USA. v101 i45. 16075-16080.

[46]

Baron, J., In defense of the not-so-old-time religion. Organ Behav Hum Decis Process. v65. 293-295.

[47]

Fischhoff, B., The real world: what good is it?. Organ Behav Hum Decis Process. v65. 232-248.

[48]

Loewenstein, G., Out of control: visceral influences on behavior. Organ Behav Hum Decis Process. v65. 272-292.

[49]

Strack, F. and Neumann, R., "The spirit is willing, but the flesh is weak": beyond mind-body interactions in human decision-making. Organ Behav Hum Decis Process. v65. 300-304.

[50]

Gold, R.S., AIDS education for gay men: towards a more cognitive approach. AIDS Care. v12. 267-272.

[51]

Gold, R.S., Karmiloff-Smith, A., Skinner, M.J. and Morton, J., Situational factors and thought processes associated with unprotected intercourse in heterosexual students. AIDS Care. v4. 305-323.

[52]

Epstein, S., Integration of the cognitive and the psychodynamic unconscious. Am Psychol. v49 i8. 709-724.

[53]

Slovic, P., Finucane, M.L., Peters, E. and MacGregor, D.G., Risk as analysis and risk as feelings: some thoughts about affect, reason, risk, and rationality. Risk Anal. v24 i2. 311-322.

[54]

Lerner, J.S. and Keltner, D., Beyond valence: Toward a model of emotion-specific influences on judgement and choice. Cognit Emotion. v14 i4. 473-493.

[55]

Metcalfe, J. and Mischel, W., A hot/cool-system analysis of delay of gratification: dynamics of willpower. Psychol Rev. v106 i1. 3-19.

[56]

Shiv, B. and Fedorikhin, A., Heart and mind in conflict: The interplay of affect and cognition in consumer decision making. J Consum Res. v26 i3. 278-292.

[57]

Puri, R., Measuring and modifying consumer impulsiveness: a cost-benefit accessibility framework. J Consum Psychol. v5 i2. 87-113.

[58]

Zajonc, R.B., Feeling and thinking: closing the debate over the independence of affect. In: Forgas, J.P. (Ed.), Feeling and thinking: the role of affect in social cognition. Studies in emotion and social interaction, Cambridge University Press, NY, USA.

[59]

Forgas, J.P., Feeling and thinking: the role of affect in social cognition. Cambridge University Press, New York, NY, US.

[60]

Salovey, P., Rothman, A.J. and Rodin, J., Health behavior. In: Gilbert, D.T., Fiske, S.T. (Eds.), The handbook of social psychology, McGraw-Hill, NY, USA.

[61]

Ellis, H., Varner, L. and Becker, A., Cognition and emotion: theories, implications, and educational applications. In: Penner, L., Batsche, G., Knoff, H., Nelson, D. (Eds.), The challenge in mathematics and science education: psychology's response, APA, Washington, DC. pp. 83-111.

[62]

Scherer, K.R., Psychological models of emotion. In: Borod, J.C. (Ed.), The neuropsychology of emotion Series in affective science, Oxford University Press, London. pp. 137-162.

[63]

Yerkes, R.M. and Dodson, J.D., The relation of strength of stimulus to rapidity of habit formation. J Comp Neurol Psychol. v18. 459-482.

[64]

Broadhurst, P.L., Emotionality and the Yerkes-Dodson Law. J Exp Psychol. v54. 345-352.

[65]

Easterbrook, J.A., The effect of emotion on cue utilization and the organization of behavior. Psychol Rev. v66. 183-201.

[66]

Martin, J., Neuroanatomy: Text and atlas. 3rd ed. McGraw-Hill Companies Inc, USA.

[67]

Armony, J.L. and LeDoux, J.E., How the brain processes emotional information. Ann N Y Acad Sci. v21 i821. 259-270.

[68]

Bechara, A., Neurobiology of decision-making: risk and reward. Semin Clin Neuropsychiatr. v6 i3. 205-216.

[69]

Damasio, A.R., Descartes' error: emotion, reason, and the human brain. Putnam, New York.

[70]

Sanfey, A.G., Rilling, J.K., Aronson, J.A., Nystrom, L.E. and Cohen, J.D., The neural basis of economic decision-making in the Ultimatum Game. Science. v300 i5626. 1755-1758.

[71]

Denton, D., Shade, R., Zamarippa, F., Egan, G., Blair-West, J. and McKinley, M., Neuroimaging of genesis and satiation of thirst and an interoceptor-driven theory of origins of primary consciousness. Proc Natl Acad Sci USA. v96 i9. 5304-5309.

[72]

Tataranni, P., Gautier, J., Chen, K., Uecker, A., Bandy, D. and Salbe, A., Neuroanatomical correlates of hunger and satiation in humans using positron emission tomography. Proc Natl Acad Sci USA. v96 i8. 4569-4574.

[73]

Botvinick, M., Nystrom, L.E., Fissell, K., Carter, C.S. and Cohen, J.D., Conflict monitoring versus selection-for-action in anterior cingulate cortex. Nature. v402 i6758. 179-181.

[74]

MacDonald III, A., Cohen, J., Stenger, V. and Carter, C., Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. Science. v288 i5472. 1835-1838.

[75]

Glimcher, P.W. and Rustichini, A., Neuroeconomics: the consilience of brain and decision. Science. v306 i5695. 447-452.

[76]

Zak, P.J., . Neuroeconomics. 1737-1748.

[77]

Bernoulli, D., Exposition of a new theory on the measurement of risk. Econometrica. v22. 23-36.

[78]

. In: Kahneman, D., Tversky, A. (Eds.), Choices, values, and frames, Cambridge University Press, New York, NY.

[79]

Newsome, W., Britten, K., Salzman, C. and Movshon, J., Neuronal mechanisms of motion perception. Cold Spring Harbor Symp Quant Biol. v55. 697-705.

[80]

Ellsberg, D., Risk, ambiguity, and the Savage axioms. Q J Econ. v75. 643-669.

[81]

Thaler, R.H., The Ultimatum Game. J Econ Perspect. v2. 195-206.

[82]

Camerer, C.F., Loewenstein, G. and Prelec, D., Neuroeconomics: why economics needs brains. Scand J Econ. v106 i3. 555-579.

[83]

McClure, S.M., Laibson, D.I., Loewenstein, G. and Cohen, J.D., Separate neural systems value immediate and delayed monetary rewards. Science. v306 i5695. 503-507.

[84]

Gimpl, G. and Fahrenholz, F., The oxytocin receptor system: structure, function, and regulation. Physiol Rev. v81 i2. 629-683.

[85]

Kosfeld, M., Heinrichs, M., Zak, P.J., Fischbacher, U. and Fehr, E., Oxytocin increases trust in humans. Nature. v435 i7042. 673-676.

[86]

Breiter, H., Aharon, I., Kahneman, D., Dale, A. and Shizgal, P., Functional imaging of neural responses to expectancy and experience of monetary gains and losses. Neuron. v30 i2. 619-639.

[87]

Knutson, B., Westdorp, A., Kaiser, E. and Hommer, D., FMRI visualization of brain activity during a monetary incentive delay task. Neuroimage. v12 i1. 20-27.

[88]

Elliott, R., Rees, G. and Dolan, R.J., Ventromedial prefrontal cortex mediates guessing. Neuropsychologia. v37 i4. 403-411.

[89]

Berns, G.S., McClure, S.M., Pagnoni, G. and Montague, P., Predictability modulates human brain response to reward. J Neurosci. v21 i8. 2793-2798.

[90]

Rolls, E.T., The orbitofrontal cortex and reward. Cerebral Cortex. v10 i3. 284-294.

[91]

Robin, N. and Holyoak, K.J., Relational complexity and the functions of prefrontal cortex. In: Gazzaniga, M.S. (Ed.), The cognitive neurosciences, The MIT Press, Cambridge, MA. pp. 987-997.

[92]

Fletcher, P., Frith, C. and Rugg, M., The functional neuroanatomy of episodic memory. Trends Neurosci. v20 i5. 213-218.

[93]

Schultz, W., Getting formal with dopamine and reward. Neuron. v36 i2. 241-263.

[94]

Wise, R., Brain reward circuitry: insights from unsensed incentives. Neuron. v36 i2. 229-240.

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Rostami MVardasbi AAliannejadi MOussalah M(2024)Emotional Insights for Food RecommendationsAdvances in Information Retrieval10.1007/978-3-031-56060-6_16(238-253)Online publication date: 24-Mar-2024
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Methodological Review: The role of emotion in decision-making: A cognitive neuroeconomic approach towards understanding sexual risk behavior

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Copyright © Elsevier Inc. © 2006.

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Published: 01 December 2006

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Cited By

Rostami MVardasbi AAliannejadi MOussalah M(2024)Emotional Insights for Food RecommendationsAdvances in Information Retrieval10.1007/978-3-031-56060-6_16(238-253)Online publication date: 24-Mar-2024
https://dl.acm.org/doi/10.1007/978-3-031-56060-6_16
Fleming KKouassi AOndula EWaweru P(2016)Toward farmer decision profiles to improve food security in KenyaIBM Journal of Research and Development10.1147/JRD.2016.259227860:5-6(6:1-6:10)Online publication date: 1-Sep-2016
https://dl.acm.org/doi/10.1147/JRD.2016.2592278
Zhou JSun JChen FWang YTaib RKhawaji ALi Z(2015)Measurable Decision Making with GSR and Pupillary Analysis for Intelligent User InterfaceACM Transactions on Computer-Human Interaction10.1145/268792421:6(1-23)Online publication date: 14-Jan-2015
https://dl.acm.org/doi/10.1145/2687924
Patel VKannampallil T(2015)Cognitive informatics in biomedicine and healthcareJournal of Biomedical Informatics10.1016/j.jbi.2014.12.00753:C(3-14)Online publication date: 1-Feb-2015
https://dl.acm.org/doi/10.1016/j.jbi.2014.12.007
Hoorn JPontier MSiddiqui G(2008)When the User Is Instrumental to Robot GoalsProceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 0210.1109/WIIAT.2008.113(296-301)Online publication date: 9-Dec-2008
https://dl.acm.org/doi/10.1109/WIIAT.2008.113

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