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Poor Decision Making Among Older Adults Is Related to Elevated Levels of Neuroticism

  • Original Article
  • Published:
Annals of Behavioral Medicine

Abstract

Background

A well-studied index of reasoning and decision making is the Iowa Gambling Task (IGT). The IGT possesses many features important to medical decision making, such as weighing risks and benefits, dealing with unknown outcomes, and making decisions under uncertainty.

Purpose

There exists a great deal of individual variability on the IGT, particularly among older adults, and the present study examines the role of personality in IGT performance. We explored which of the five-factor model of personality traits were predictive of decision-making performance, after controlling for relevant demographic variables.

Methods

One hundred and fifty-two healthy cognitively intact adults (aged 26–85) were individually administered the IGT and the NEO Five-Factory Inventory.

Results

In the older adults, but not the younger, higher NEO neuroticism was associated with poorer IGT performance.

Conclusions

Our findings are discussed in the context of how stress may impact cognitive performance and cause dysfunction of neural systems in the brain important for decision making.

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Notes

  1. A borderline subgroup also exists, performing neither advantageously nor disadvantageously on the IGT, and, as a result, they have not been studied further.

References

  1. Karlamangla A, Tinetti M, Guralnik J, Studenski S, Wetle T, Reuben D. Comorbidity in older adults: Nosology of impairment, diseases, and conditions. J Gerontol Biol Sci Med Sci. 2007; 62: 296–300.

    Google Scholar 

  2. Yancik R, Ershler W, Satariano W, Hazzard W, Cohen HJ, Ferrucci L. Report of the national institute on aging task force on comorbidity. J Gerontol Biol Sci Med Sci. 2007; 62: 275–280.

    Google Scholar 

  3. West R. An application of prefrontal cortex function theory of cognitive aging. Psychol Bull. 1996; 120: 272–292.

    Article  PubMed  Google Scholar 

  4. Haaland KY, Price L, LaRue A. What does the WMS-III tell us about memory changes with normal aging. J Int Neuropsychol Soc. 2003; 9: 89–96.

    Article  PubMed  Google Scholar 

  5. Moscovitch M, Winocur G. The neuropsychology of memory and aging. In: Craik FIM, Salthouse TA, eds. The Handbook of Aging and Cognition. Hillsdale: Lawrence Erlbaum; 1992: 315–372.

    Google Scholar 

  6. Robbins TW, James M, Owen AM, et al. A study of performance on tests from the CANTAB battery sensitive to frontal lobe dysfunction in a large sample of normal volunteers: Implications for theories of executive functioning and cognitive aging. J Int Neuropsychol Soc. 1998; 4: 474–490.

    Article  PubMed  Google Scholar 

  7. West RL, Murphy KJ, Armilio ML, Craik FIM, Stuss D. Lapses in attention and performance variability reveal age-related increases in fluctuations in executive control. Brain Cogn. 2002; 49: 402–419.

    Article  PubMed  Google Scholar 

  8. Jernigan TL, Archibald SL, Fennema-Notestine C, et al. Effects of age on tissues and regions of the cerebrum and cerebellum. Neurobiol Aging. 2001; 22: 581–594.

    Article  PubMed  Google Scholar 

  9. Raz N, Lindenberger U, Rodrigue K, et al. Regional brain changes in aging healthy adults: General trends, individual differences and modifiers. Cereb Cortex. 2005; 15: 1676–1689.

    Article  PubMed  Google Scholar 

  10. Resnick SM, Pham DL, Kraut MA, Zonderman AB, Davatzikos C. Longitudinal magnetic resonance imaging studies of older adults: A shrinking brain. J Neurosci. 2003; 23: 3295–3301.

    PubMed  Google Scholar 

  11. Salat DH, Kaye JA, Janowsky JS. Selective preservation and degeneration within the prefrontal cortex in aging and Alzheimer's disease. Arch Neurol. 2001; 58: 1403–1408.

    Article  PubMed  Google Scholar 

  12. Gur RC, Gur RE, Orbist WD, Skolnick BE, Reivich M. Age and regional cerebral blood flow at rest and during cognitive activity. Arch Gen Psychiatry. 1987; 44: 617–621.

    PubMed  Google Scholar 

  13. Melamed E, Lavy S, Shlomo B, Cooper G, Rinot Y. Reduction in regional cerebral blood flow during normal aging in man. Stroke. 1980; 11: 31–34.

    PubMed  Google Scholar 

  14. Meyer BJF, Russo C, Talbot A. Discourse processing and problem solving: Decisions about the treatment of breast cancer by women across the life span. Psychol Aging. 1995; 10: 84–103.

    Article  PubMed  Google Scholar 

  15. Zwahr MD, Park DC, Shifren K. Judgments about estrogen replacement therapy: The role of age, cognitive abilities, and beliefs. Psychol Aging. 1999; 14: 179–191.

    Article  PubMed  Google Scholar 

  16. Meyer BJF, Talbot AP, Ranalli C. Why older adults make more immediate treatment decisions about cancer than younger adults. Psychol Aging. 2007; 22: 505–524.

    Article  PubMed  Google Scholar 

  17. Leventhal EA, Leventhal H, Schaefer P, Easterling D. Conservation of energy, uncertainty reduction, and swift utilization of medical care among the elderly. J Gerontol Psychol Sci. 1993; 48: 78–86.

    Google Scholar 

  18. Leventhal EA, Easterling D, Leventhal H, Cameron L. Conservation of energy, uncertainty reduction, and swift utilization of medical care among the elderly: Study II. Med Care. 1995; 33: 988–1000.

    Article  PubMed  Google Scholar 

  19. Bechara A, Damasio AR, Damasio H, Anderson SW. Insensitivity to future consequences following damage to human prefrontal cortex. Cognition. 1994; 50: 7–15.

    Article  PubMed  Google Scholar 

  20. Dunn BD, Dalgleish T, Lawrence AD. The somatic marker hypothesis: A critical evaluation. Neurosci Biobehav Rev. 2006; 30: 239–271.

    Article  PubMed  Google Scholar 

  21. Yechiam E, Busemeyer JR, Stout JC, Bechara A. Using cognitive models to map relations between neuropsychological disorders and human decision making deficits. Psychol Sci. 2006; 16: 973–978.

    Article  Google Scholar 

  22. Bechara A. Iowa Gambling Task (IGT) Professional Manual. Lutz: Psychological Assessment Resources; 2007.

    Google Scholar 

  23. Denburg NL, Cole CA, Hernandez M, et al. The orbitofrontal cortex, real-world decision-making, and normal aging. Ann N Y Acad Sci. 2007; 1121: 480–498.

    Article  PubMed  Google Scholar 

  24. Denburg NL, Recknor EC, Bechara A, Tranel D. Psychophysiological anticipation of positive outcomes promotes advantageous decision-making in normal older persons. Int J Psychophysiol. 2006; 61: 19–25.

    Article  PubMed  Google Scholar 

  25. Denburg NL, Tranel D, Bechara A. The ability to decide advantageously declines prematurely in some normal older persons. Neuropsychologia. 2005; 43: 1099–1106.

    Article  PubMed  Google Scholar 

  26. Fein G, McGillivray S, Finn P. Older adults make less advantageous decisions than younger adults: Cognitive and psychological correlates. J Int Neuropsychol Soc. 2007; 13: 480–489.

    Article  PubMed  Google Scholar 

  27. MacPherson SE, Phillips LH, Della Sala S. Age, executive function, and social decision making: A dorsolateral prefrontal theory of cognitive aging. Psychol Aging. 2002; 17: 598–609.

    Article  PubMed  Google Scholar 

  28. Bechara A, Tranel D, Damasio H. Characterization of the decision-making deficit of patients with ventromedial prefrontal cortex lesions. Brain. 2000; 123: 2189–2202.

    Article  PubMed  Google Scholar 

  29. Crone EA, Vendel I, van der Molen MW. Decision-making in disinhibited adolescents and adults: Insensitivity to future consequences or driven by immediate reward? Pers Individ Differ. 2003; 35: 1625–1641.

    Article  Google Scholar 

  30. Suhr JA, Tsanadis J. Affect and personality correlates of the Iowa Gambling Task. Pers Individ Differ. 2007; 43: 27–36.

    Article  Google Scholar 

  31. Casillas A. Personality and neuropsychological correlates of impulsivity (Doctoral dissertation, University of Iowa). Diss Abstr Int. 2005; 66: 4476.

    Google Scholar 

  32. Weller JA. The role of affect in decisions under varying levels of uncertainty: Converging evidence from neurological and temperament perspectives. Unpublished doctoral dissertation, University of Iowa; 2007.

  33. Digman JM. Personality structure: Emergence of the five-factor model. Annu Rev Psychol. 1990; 41: 417–440.

    Google Scholar 

  34. McCrae RR, Costa PT. Validation of a five-factor model of personality across instruments and observers. J Pers Soc Psychol. 1987; 52: 81–90.

    Article  PubMed  Google Scholar 

  35. McCrae RR, Costa PT. Personality in Adulthood. New York: Guilford; 1990.

    Google Scholar 

  36. Roberts BW, Walton KE, Viechtbauer W. Patterns of mean-level change in personality traits across the life course: A meta-analysis of longitudinal studies. Psychol Bull. 2006; 132: 1–25.

    Article  PubMed  Google Scholar 

  37. Tellegen A. Structures of mood and personality and their relevance to assessing anxiety, with an emphasis on self-report. In: Tuma AH, Maser JD, eds. Anxiety and the Anxiety Disorders. Hillsdale: Erlbaum; 1985: 681–706.

    Google Scholar 

  38. Eysenck HJ, Eysenck SBG. Manual of the Eysenck Personality Inventory. San Diego: Educational and Industrial Testing Service; 1975.

    Google Scholar 

  39. Carver CS, White TL. Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS scales. J Pers Soc Psychol. 1994; 67: 319–333.

    Article  Google Scholar 

  40. Gray JA. The psychophysiological basis of introversion–extraversion. Behav Res Ther. 1970; 8: 249–266.

    Article  PubMed  Google Scholar 

  41. Costa P, McCrae R. Revised NEO Personality Inventory-Revised (NEO PI-R) and NEO Five-Factor Inventory (NEO-FFI) Professional Manual. Lutz: Psychological Assessment Resources; 1992.

    Google Scholar 

  42. Lee K, Ashton MC. Further assessment of the HEXACO personality inventory: Two new facet scales and an observer report form. Psychol Assess. 2006; 18: 182–191.

    Article  PubMed  Google Scholar 

  43. Beck AT, Steer RA, Brown GK. Beck Depression Inventory Manual. 2nd ed. San Antonio: Psychological Corporation; 1996.

    Google Scholar 

  44. Tranel D, Benton A, Olson K. A 10-year longitudinal study of cognitive changes in elderly persons. Dev Neuropsychol. 1997; 13: 87–96.

    Article  Google Scholar 

  45. Tranel D. Theories of clinical neuropsychology and brain–behavior relationships: Luria and beyond. In: Morgan JE, Ricker JH, eds. Textbook of Clinical Neuropsychology. New York: Taylor and Francis; 2007: 27–39.

    Google Scholar 

  46. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”: A practical method for grading the mental state of patients for the clinician. J Psychiatr Res. 1993; 12: 189–198.

    Article  Google Scholar 

  47. Wilkinson GS. Wide Range Achievement Test-3. Wilmington: Jastak; 1993.

    Google Scholar 

  48. Wechsler DA. Wechsler Abbreviated Scale of Intelligence. New York: Psychological Corporation; 1999.

    Google Scholar 

  49. Wechsler DA. Wechsler Adult Intelligence Scale-III. New York: Psychological Corporation; 1997.

    Google Scholar 

  50. Crum RM, Anthony JC, Bassett SS, Folstein MF. Population-based norms for the Mini-Mental State Examination by age and educational level. JAMA. 1993; 12: 2386–2391.

    Article  Google Scholar 

  51. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale: Erlbaum; 1988.

    Google Scholar 

  52. Cohen J. A power primer. Psychol Bull. 1992; 112: 155–159.

    Article  PubMed  Google Scholar 

  53. Aiken LS, West SG. Multiple Regression Test and Interpreting Interactions. Thousand Oaks: Sage; 1991.

    Google Scholar 

  54. Clark LA, Watson D, Mineka S. Temperament, personality, and the mood and anxiety disorders. J Abnorm Psychol. 1994; 103: 103–116.

    Article  PubMed  Google Scholar 

  55. Bolger N, Shilling EA. Personality and the problems of everyday life: The role of neuroticism in exposure and reactivity to daily stressors. J Pers. 1991; 59: 355–386.

    Article  PubMed  Google Scholar 

  56. Mrozek DK, Almeida DM. The effect of daily stress, personality, and age on daily negative affect. J Pers. 2004; 72: 355–378.

    Article  Google Scholar 

  57. Watson D, Pennebaker J. Health complaints, stress, and distress: Exploring the central role of negative affectivity. Psychol Rev. 1989; 96: 234–254.

    Article  PubMed  Google Scholar 

  58. Jacobs N, Germeys I, Derom C, Delespaul P, van Os J, Nicolson N. A momentary assessment study of the relationship between affective and adrenocortical stress responses in daily life. Biol Psychol. 2007; 74: 60–66.

    Article  PubMed  Google Scholar 

  59. Miller GE, Cohen S, Rabin BS, Skoner DP, Doyle WJ. Personality and tonic cardiovascular, neuroendocrine, and immune parameters. Brain Behav Immun. 1999; 13: 109–123.

    Article  PubMed  Google Scholar 

  60. van Eck MM, Berkhof H, Nicolson N, Sulon J. The effects of perceived stress, traits, mood states and stressful daily events on salivary cortisol. Psychosom Med. 1996; 58: 447–458.

    PubMed  Google Scholar 

  61. Lupien SJ, Maheu F, Tu M, Fiocco A, Schramek TE. The effects of stress and stress hormones on human cognition: Implications for the field of brain and cognition. Brain Cogn. 2007; 65: 209–237.

    Article  PubMed  Google Scholar 

  62. Baradell JG, Klein K. Relationship of life stress and body consciousness to hypervigilant decision making. J Pers Soc Psychol. 1993; 64: 267–273.

    Article  Google Scholar 

  63. Klein K, Boals A. The relationship of life event stress and working memory capacity. Appl Cogn Psychol. 2001; 15: 565–579.

    Article  Google Scholar 

  64. Yee PL, Edmonson B, Santoro KE, Begg AE, Hunter CD. Cognitive effects of life stress and learned helplessness. Anxiety Stress Coping. 1996; 9: 301–319.

    Article  Google Scholar 

  65. Neupert SD, Almeida DM, Mroczek DK, Spiro A. Daily stressors and memory failures in a naturalistic setting: Findings from the VA normative aging study. Psychol Aging. 2006; 21: 424–429.

    Article  PubMed  Google Scholar 

  66. Sliwinski MJ, Smyth JM, Hofer SM, Stawski RS. Intraindividual coupling of daily stress and cognition. Psychol Aging. 2006; 21: 545–557.

    Article  PubMed  Google Scholar 

  67. Mooradian AD. Effect of ageing on the blood–brain barrier. Neurobiol Aging. 1988; 9: 31–39.

    Article  PubMed  Google Scholar 

  68. Wardlaw JM, Sandercock PAG, Dennis MS, Starr J. Is breakdown of the blood–brain barrier responsible for lacunar stroke, leukoaraiosis, and dementia? Stroke. 2003; 34: 806–812.

    Article  PubMed  Google Scholar 

  69. Lupien SJ, de Leon M, de Santi S, et al. Cortisol levels during human aging predict hippocampal atrophy and memory deficits. Nat Neurosci. 1998; 1: 69–73.

    Article  PubMed  Google Scholar 

  70. Sapolsky RM, Krey LC, McEwen BS. The neuroendocrinology of stress and aging; The glucocorticoid cascade hypothesis. Endocr Rev. 1986; 7: 284–301.

    Article  PubMed  Google Scholar 

  71. Wolf OT, Convit A, de Leon MJ, Caraos C, Qadri SF. Basal hypothalamo–pituitary–adrenal axis activity and corticotrophin feedback in young and older men: Relationships to magnetic resonance imaging-derived hippocampus and cingulate gyrus volumes. Neuroendocrinology. 2002; 75: 241–249.

    Article  PubMed  Google Scholar 

  72. Damasio AR. Descartes’ Error: Emotion, Reason, and the Human Brain. New York: Grosset/Putnam; 1994.

    Google Scholar 

  73. Wright CI, Feczko E, Dickerson B, Williams D. Neuroanatomical correlates of personality in the elderly. Neuroimage. 2007; 35: 263–272.

    Article  PubMed  Google Scholar 

  74. Knutson B, Momenan R, Rawlings R, Fong GW, Hommer D. Negative association of neuroticism with brain volume ratio in healthy humans. Biol Psychiatry. 2001; 50: 685–690.

    Article  PubMed  Google Scholar 

  75. Clark LA. Schedule for Nonadaptive and Adaptive Personality: Manual for Administration, Scoring, and Interpretation. Minneapolis: University of Minnesota Press; 1993.

    Google Scholar 

  76. John OP, Srivastava S. The big five trait taxonomy: History, measurement, and theoretical perspectives. In: Pervin LA, John OP, eds. Handbook of Personality: Theory and Research. 2nd ed. New York: Guilford; 1999: 102–138.

    Google Scholar 

  77. Williams PG, Wiebe DJ. Individual differences in self-assessed health: Gender, neuroticism and physical symptom reports. Pers Individ Differ. 2000; 28: 823–835.

    Article  Google Scholar 

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Acknowledgements

Preparation of this article was supported by a National Institute on Aging Career Development Award to Natalie L. Denburg (K01 AG022033), by fellowship funding from the Iowa Scottish Rite Masonic Foundation, and by an Agency for Healthcare Research and Quality (AHRQ) Centers for Education and Research on Therapeutics cooperative agreement #5 U18 HSO16094.

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Denburg, N.L., Weller, J.A., Yamada, T.H. et al. Poor Decision Making Among Older Adults Is Related to Elevated Levels of Neuroticism. ann. behav. med. 37, 164–172 (2009). https://doi.org/10.1007/s12160-009-9094-7

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  • DOI: https://doi.org/10.1007/s12160-009-9094-7

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