Cited by 53Cognitive Abilities and TestingAging and Gerontology ResearchRetirement, Disability, and Employment

Not your parents' test scores: Cohort reduces psychometric aging effects.

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Zelinski, Elizabeth M., Kennison, Robert F.·2007·Psychology and Aging

Abstract

Increases over birth cohorts in psychometric abilities may impact effects of aging. Data from 2 cohorts of the Long Beach Longitudinal Study, matched on age but tested 16 years apart, were modeled over ages 55-87 to test the hypothesis that the more fluid abilities of reasoning, list and text recall, and space would show larger cohort differences than vocabulary. This hypothesis was confirmed. At age 74, average performance estimates for people from the more recently born cohort were equivalent to those of people from the older cohort when they were up to 15 years younger. This finding suggests that older adults may perform like much younger ones from the previous generation on fluid measures, indicating higher levels of abilities than expected. This result could have major implications for the expected productivity of an aging workforce as well as for the quality of life of future generations. However, cohort improvements did not mitigate age declines.

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  • The rate of cognitive aging from age 55 to 87 on reasoning, spatial abilities, and vocabulary showed minimal if any differences between age-matched cohorts born 1893-1923 and 1908-1940.

    “Zelinski and Kennison (2007) applied growth models to data from the Long Beach Longitudinal Study (LBLS) and reported that the rate of cognitive aging from age 55 to age 87 on measures of reasoning, spatial abilities, and vocabulary showed minimal if any differences between age-matched cohorts born 1893–1923 and those born 1908–1940.”

    From Cohort differences in cognitive aging and terminal decline in the Seattle Longitudinal Study. (2011) · cites this paper as Zelinski and Kennison (2007)

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Research works printed but not linked: 57

  1. Akaike H. Factor analysis and AIC. Psychometrika. 1987;52:317–332. [Google Scholar]
  2. Alwin DF. Family of origin and cohort differences in verbal ability. American Sociological Review. 1991;56:625–638. [Google Scholar]
  3. Alwin DF, McCammon RJ. Aging, cohorts, and verbal ability. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences. 2001;56:S151–S161. doi: 10.1093/geronb/56.3.s151. [DOI] [PubMed] [Google Scholar] · DOI · Paper page
  4. Barber N. Educational and ecological correlates of IQ: A cross-national investigation. Intelligence. 2005;33:273–284. [Google Scholar]
  5. Blair C, Gamson D, Thorne S, Baker D. Rising mean IQ: Cognitive demand of mathematics education for young children, population exposure to formal schooling, and the neurobiology of the pre-frontal cortex. Intelligence. 2005;33:93–106. [Google Scholar]
  6. Bond TG, Fox CM. Applying the Rasch model. Mahwah, NJ: Erlbaum; 2001. [Google Scholar]
  7. Bowles RP, Grimm KJ, McArdle JJ. A structural factor analysis of vocabulary knowledge and relations to age. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences. 2005;60:234–241. doi: 10.1093/geronb/60.5.p234. [DOI] [PubMed] [Google Scholar] · DOI · Paper page
  8. Browne MW, Cudeck R. Alternative ways of assessing model fit. In: Bollen KA, Long JS, editors. Testing structural equation models. Newbury Park, CA: Sage; 1993. pp. 136–162. [Google Scholar]
  9. Cooney TM, Schaie KW, Willis SL. The relationship between prior functioning on cognitive and personality dimensions and subject attrition in longitudinal research. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences. 1988;43:12–17. doi: 10.1093/geronj/43.1.p12. [DOI] [PubMed] [Google Scholar] · DOI
  10. Dickens WT, Flynn JR. Heritability estimates versus large environmental effects: The IQ paradox resolved. Psychological Review. 2001;108:346–369. doi: 10.1037/0033-295x.108.2.346. [DOI] [PubMed] [Google Scholar] · DOI · Paper page
  11. Embretson SE. Item response theory models and spurious interaction effects in factorial ANOVA designs. Applied Psychological Assessment. 1996;20:201–212. [Google Scholar]
  12. Flynn JR. Massive IQ gains in 14 nations: What IQ tests really measure. Psychological Bulletin. 1987;101:171–191. [Google Scholar]
  13. Flynn JR. IQ gains over time: Toward finding the causes. In: Neisser U, editor. The rising curve: Long-term gains in IQ and related measures. Washington, DC: American Psychological Association; 1998. pp. 25–66. [Google Scholar]
  14. Flynn JR. Movies about intelligence: The limitations of g. Psychological Science. 2003;12:95–99. [Google Scholar]
  15. Freedman VA, Aykan H, Martin LG. Aggregate changes in cognitive impairment among older Americans: 1993 and 1998. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences. 2001;56:S100–S111. doi: 10.1093/geronb/56.2.s100. [DOI] [PubMed] [Google Scholar] · DOI
  16. Gottfredson LS, Deary IJ. Intelligence predicts health and longevity, but why? Current Directions in Psychological Science. 2001;13:1–4. [Google Scholar]
  17. Greenfield PM. The cultural evolution of IQ. In: Neisser U, editor. The rising curve: Long-term gains in IQ and related measures. Washington, DC: American Psychological Association; 1998. pp. 81–123. [Google Scholar]
  18. Hertzog C, Lindenberger U, Ghisletta P, von Oertzen T. On the power of multivariate latent growth curve models to detect individual differences in change. Psychological Methods. 2006;11:244–252. doi: 10.1037/1082-989X.11.3.244. [DOI] [PubMed] [Google Scholar] · DOI · Paper page
  19. Hertzog C, Nesselroade JR. Assessing psychological changes in adulthood: An overview of methodological issues. Psychology and Aging. 2003;18:639–657. doi: 10.1037/0882-7974.18.4.639. [DOI] [PubMed] [Google Scholar] · DOI · Paper page
  20. Horn JL, Cattell RB. Age differences in fluid and crystallized intelligence. Acta Psychologica. 1967;26:107–129. doi: 10.1016/0001-6918(67)90011-x. [DOI] [PubMed] [Google Scholar] · DOI · Paper page
  21. Kennison RF, Zelinski EM. Estimating age change in 7-year list recall in AHEAD: The roles of independent predictors of missing-ness and dropout. Psychology and Aging. 2005;20:460–475. doi: 10.1037/0882-7974.20.3.460. [DOI] [PubMed] [Google Scholar] · DOI
  22. Langa KM, Chermew ME, Kabeto MW, Herzog AR, Ofstedal MB, Willis RJ, et al. National estimates of the quantity and cost of informal caregiving for the elderly with dementia. Journal of General Internal Medicine. 2001;16:770–777. doi: 10.1111/j.1525-1497.2001.10123.x. [DOI] [PMC free article] [PubMed] [Google Scholar] · DOI
  23. Linacre JM. A user’s guide to WINSTEPS MINISTEP Rasch-model computer programs [Computer software and manual] Chicago: Winsteps; 2006. [Google Scholar]
  24. Loehlin JC. The IQ Paradox: Resolved? Still an open question. Psychological Review. 2002;109:754–758. doi: 10.1037/0033-295x.109.4.754. [DOI] [PubMed] [Google Scholar] · DOI
  25. McArdle JJ, Bell RQ. An introduction to latent growth models for developmental data analysis. In: Little TD, Schnabel KU, Baumert J, editors. Modeling longitudinal and multilevel data: Practical issues, applied approaches, and specific examples. Mahwah, NJ: Erlbaum; 2000. pp. 69–107. [Google Scholar]
  26. McArdle JJ, Ferrer-Caja E, Hamagami F, Woodcock RW. Comparative longitudinal structural analyses of the growth and decline of multiple intellectual abilities over the life span. Developmental Psychology. 2002;38:115–142. [PubMed] [Google Scholar]
  27. McArdle JJ, Hamagami F. Modeling incomplete longitudinal and cross-sectional data using latent growth structural models. Experimental Aging Research. 1991;18:145–166. doi: 10.1080/03610739208253917. [DOI] [PubMed] [Google Scholar] · DOI
  28. McArdle JJ, Hamagami F, Meredith W, Bradway KP. Modeling the dynamic hypotheses of Gf-Gc theory using longitudinal life-span data. Learning and Individual Differences. 2000;12:53–79. [Google Scholar]
  29. Muthén LK, Muthén BO. Software manual. 4. Los Angeles: Author; 1998–2007. Mplus user’s guide. [Google Scholar]
  30. Neugarten BL. The future and the young-old. Gerontologist. 1975;15:4–9. doi: 10.1093/geront/15.1_part_2.4. [DOI] [PubMed] [Google Scholar] · DOI
  31. Rabbitt PMA, Watson P, Donlan C, McInnes L, Horan M, Pendleton N, Clague J. Effects of death within 11 years on cognitive performance in old age. Psychology and Aging. 2002;17:468–481. doi: 10.1037//0882-7974.17.3.468. [DOI] [PubMed] [Google Scholar] · DOI
  32. Rasch G. An item analysis which takes individual differences into account. British Journal of Mathematical and Statistical Psychology. 1966;19:49–57. doi: 10.1111/j.2044-8317.1966.tb00354.x. [DOI] [PubMed] [Google Scholar] · DOI
  33. Raven J. The Raven’s Progressive Matrices: Change and stability over culture and time. Cognitive Psychology. 2000;41:1–48. doi: 10.1006/cogp.1999.0735. [DOI] [PubMed] [Google Scholar] · DOI · Paper page
  34. Rodgers JL. A critique of the Flynn effect: Massive IQ gains, methodological artifacts, or both? Intelligence. 1999;26:337–356. [Google Scholar]
  35. Rönnlund M, Nyberg L, Bäckman L, Nilsson LG. Stability, growth, and decline in adult life span development of declarative memory: Cross-sectional and longitudinal data from a population-based study. Psychology and Aging. 2005;20:3–18. doi: 10.1037/0882-7974.20.1.3. [DOI] [PubMed] [Google Scholar] · DOI · Paper page
  36. Rowe DC, Rodgers JL. Expanding variance and the case of historical changes in IQ means: A critique of Dickens and Flynn (2001) Psychological Review. 2002;109:759–763. doi: 10.1037/0033-295x.109.4.759. [DOI] [PubMed] [Google Scholar] · DOI
  37. Salthouse TA. What and when of cognitive aging. Current Directions in Psychological Science. 2004;13:140–144. doi: 10.1177/0963721414535212. [DOI] [PMC free article] [PubMed] [Google Scholar] · DOI · Paper page
  38. Schafer J. Analysis of incomplete multivariate data. London: Chapman & Hall; 1997. [Google Scholar]
  39. Schaie KW. A general model for the study of developmental problems. Psychological Bulletin. 1965;64:92–107. doi: 10.1037/h0022371. [DOI] [PubMed] [Google Scholar] · DOI · Paper page
  40. Schaie KW. Schaie–Thurstone Adult Mental Abilities Test. Palo Alto, CA: Consulting Psychologists Press; 1985. [Google Scholar]
  41. Schaie KW. Intellectual development in adulthood. Cambridge, England: Cambridge University Press; 1996. [Google Scholar]
  42. Singer T, Verhaeghen P, Ghisletta P, Lindenberger U, Baltes PB. The fate of cognition in very old age: Six-year longitudinal findings in the Berlin Aging Study (BASE) Psychology and Aging. 2003;18:318–331. doi: 10.1037/0882-7974.18.2.318. [DOI] [PubMed] [Google Scholar] · DOI
  43. Sliwinski MJ, Hofer SM, Hall C, Buschke H, Lipton RB. Modeling memory decline in older adults: The importance of preclinical dementia, attrition, and chronological age. Psychology and Aging. 2003;18:658–671. doi: 10.1037/0882-7974.18.4.658. [DOI] [PubMed] [Google Scholar] · DOI
  44. Sundet JM, Barlaug DG, Torjussen TM. The end of the Flynn effect? A study of secular trends in mean intelligence test scores of Norwegian conscripts during half a century. Intelligence. 2004;32:349–362. [Google Scholar]
  45. Teasdale TW, Owen DR. A long-term rise and recent decline in intelligence test performance: The Flynn Effect in reverse. Personality and Individual Differences. 2005;39:837–843. [Google Scholar]
  46. Turner A, Greene E. Tech Rep No 63. Boulder: Department of Psychology, University of Colorado; 1977. The construction and use of a propositional text base. [Google Scholar]
  47. Verhaeghen P. Aging and vocabulary score: A meta-analysis. Psychology and Aging. 2003;18:332–339. doi: 10.1037/0882-7974.18.2.332. [DOI] [PubMed] [Google Scholar] · DOI
  48. Wicherts JM, Dolan CV, Hessen DJ, Oosterveld P, Van Baal G, Caroline M, et al. Are intelligence tests measurement invariant over time? Investigating the nature of the Flynn effect. Intelligence. 2004;32:509–537. [Google Scholar]
  49. Williams WM. Are we raising smarter children today? School-and home-related influences on IQ. In: Neisser U, editor. The rising curve: Long-term gains in IQ and related measures. Washington, DC: American Psychological Association; 1998. pp. 125–154. [Google Scholar]
  50. Wilson JA, Gove WR. The intercohort decline in verbal ability: Does it exist? American Sociological Review. 1999;64:253–266. [Google Scholar]
  51. Wright BD, Stone MH. Best test design: Rasch measurement. Chicago: MESA Press; 1979. [Google Scholar]
  52. Zelinski EM, Burnight KP. Sixteen-year longitudinal and time lag changes in memory and cognition in older adults. Psychology and Aging. 1997;12:503–513. doi: 10.1037//0882-7974.12.3.503. [DOI] [PubMed] [Google Scholar] · DOI
  53. Zelinski EM, Burnight KP, Lane CJ. The relationship between subjective and objective memory in the oldest-old: Comparisons of findings from a representative and a convenience sample. Journal of Aging and Health. 2001;13:248–266. doi: 10.1177/089826430101300205. [DOI] [PubMed] [Google Scholar] · DOI
  54. Zelinski EM, Crimmins E, Reynolds S, Seeman T. Do medical conditions affect cognition in older adults? Health Psychology. 1998;17:504–512. doi: 10.1037//0278-6133.17.6.504. [DOI] [PubMed] [Google Scholar] · DOI
  55. Zelinski EM, Gilewski MJ. Effects of demographic and health variables on Rasch scaled cognitive scores. Journal of Aging and Health. 2003;15:435–464. doi: 10.1177/0898264303253499. [DOI] [PubMed] [Google Scholar] · DOI
  56. Zelinski EM, Lewis KL. Adult age differences in multiple cognitive functions: Differentiation, dedifferentiation, or process-specific change? Psychology and Aging. 2003;18:727–745. doi: 10.1037/0882-7974.18.4.727. [DOI] [PubMed] [Google Scholar] · DOI
  57. Zelinski EM, Stewart S. Individual differences in 16-year memory changes. Psychology and Aging. 1998;13:622–630. doi: 10.1037//0882-7974.13.4.622. [DOI] [PubMed] [Google Scholar] · DOI · Paper page

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Authors
Zelinski, E. M., & Kennison, R. F.
Affiliations
  • University of Southern California (US)
  • California State University Los Angeles (US)
Venue
Psychology and Aging
Published
2007-09
Volume
22
Issue
3
Pages
546-557
ISSN
  • 0882-7974 (ISSN-L)
  • 1939-1498
OpenAlex
W1993776270
Cited by
53
References
2
Citations by year
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FWCI
2.79
Type
journal article
Language
en
Open access
Locations
  • Psychology and Aging (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Institute on Aging (R01 AG10569; T32 AG00037)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
  • Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Aging and Gerontology Research
  • Social Sciences › Demography › Retirement, Disability, and Employment
Keywords
cohort effects, fluid intelligence, cognitive aging, older adults, vocabulary, reasoning, memory retrieval, spatial ability, aging workforce, intergenerational comparison
MeSH terms
Aged, Aged, 80 and over, Aging, Aptitude, California, Female, Health Surveys, Humans, Longitudinal Studies, Male, Middle Aged, Neuropsychological Tests, Parents, Psychometrics, Cohort Studies

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