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Journal articles on the topic 'Cognitive ability'

To see the other types of publications on this topic, follow the link: Cognitive ability.

Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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1

von Stumm, Sophie. "Investment Trait, Activity Engagement, and Age: Independent Effects on Cognitive Ability." Journal of Aging Research 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/949837.

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In cognitive aging research, the “engagement hypothesis” suggests that the participation in cognitively demanding activities helps maintain better cognitive performance in later life. In differential psychology, the “investment” theory proclaims that age differences in cognition are influenced by personality traits that determine when, where, and how people invest their ability. Although both models follow similar theoretical rationales, they differ in their emphasis of behavior (i.e., activity engagement) versus predisposition (i.e., investment trait). The current study compared a cognitive activity engagement scale (i.e., frequency of participation) with an investment trait scale (i.e., need for cognition) and tested their relationship with age differences in cognition in 200 British adults. Age was negatively associated with fluid and positively with crystallized ability but had no relationship with need for cognition and activity engagement. Need for cognition was positively related to activity engagement and cognitive performance; activity engagement, however, was not associated with cognitive ability. Thus, age differences in cognitive ability were largely independent of engagement and investment.

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2

Portugal Barcellos, Leonardo, Ricardo Lopes Cardoso, and André Carlos Busanelli de Aquino. "AN ASSESSMENT OF PROFESSIONAL ACCOUNTANTS' COGNITIVE REFLECTION ABILITY." Advances in Scientific and Applied Accounting 9, no. 2 (August 31, 2016): 224–39. http://dx.doi.org/10.14392/asaa.2016090206.

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3

Pritchard, Duncan. "Cognitive ability and the extended cognition thesis." Synthese 175, S1 (March 12, 2010): 133–51. http://dx.doi.org/10.1007/s11229-010-9738-y.

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4

Saenz, Joseph L., Christopher R. Beam, and Elizabeth M. Zelinski. "The Association Between Spousal Education and Cognitive Ability Among Older Mexican Adults." Journals of Gerontology: Series B 75, no. 7 (January 24, 2020): e129-e140. http://dx.doi.org/10.1093/geronb/gbaa002.

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Abstract Objectives Education and cognition are closely associated, yet the role of spousal education is not well understood. We estimate the independent effects of own and spousal education on cognitive ability in late-life in Mexico, a developing country experiencing rapid aging. Method We analyzed 4,017 married dyads (age 50+) from the 2012 Mexican Health and Aging Study. Cognitive ability for married adults was a factor score from a single factor model. Using seemingly unrelated regression, we test whether spousal education influences older adults’ cognitive ability, whether associations are explained by couple-level socioeconomic position, health and health behaviors, and social support, and whether associations differed by gender. Results Education and cognitive ability were correlated within couples. Higher spousal education was associated with better cognitive ability. Associations between spousal education and cognitive ability were independent of own education, did not differ by gender, and remained significant even after adjustment for couple-level socioeconomic position, health and health behaviors, and perceived social support. Discussion In addition to own education, spousal education was associated with better cognitive ability, even at relatively low levels of education. We discuss the possibility that spousal education may improve cognition via transmission of knowledge and mutually reinforcing cognitively stimulating environments.

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5

Stankov, Lazar. "Conservatism and cognitive ability." Intelligence 37, no. 3 (May 2009): 294–304. http://dx.doi.org/10.1016/j.intell.2008.12.007.

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6

Bergman, Oscar, Tore Ellingsen, Magnus Johannesson, and Cicek Svensson. "Anchoring and cognitive ability." Economics Letters 107, no. 1 (April 2010): 66–68. http://dx.doi.org/10.1016/j.econlet.2009.12.028.

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7

Al-Heizan, Muhammad O., Gordon Giles, Timothy Wolf, and Dorothy Farrar Edwards. "Hierarchical Cognitive Contributions to Functional Cognitive Ability." American Journal of Occupational Therapy 72, no. 4_Supplement_1 (November 1, 2018): 7211500049p1. http://dx.doi.org/10.5014/ajot.2018.72s1-po6006.

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8

Zhao, Xiangyu. "The Influence of Shadow Education on Cognitive Ability and Non-Cognitive Ability." Modern Economy 10, no. 03 (2019): 945–61. http://dx.doi.org/10.4236/me.2019.103063.

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9

Lu, Kirsty, Jennifer M. Nicholas, Jessica D. Collins, Sarah-Naomi James, Thomas D. Parker, Christopher A. Lane, Ashvini Keshavan, et al. "Cognition at age 70." Neurology 93, no. 23 (October 30, 2019): e2144-e2156. http://dx.doi.org/10.1212/wnl.0000000000008534.

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ObjectiveTo investigate predictors of performance on a range of cognitive measures including the Preclinical Alzheimer Cognitive Composite (PACC) and test for associations between cognition and dementia biomarkers in Insight 46, a substudy of the Medical Research Council National Survey of Health and Development.MethodsA total of 502 individuals born in the same week in 1946 underwent cognitive assessment at age 69–71 years, including an adapted version of the PACC and a test of nonverbal reasoning. Performance was characterized with respect to sex, childhood cognitive ability, education, and socioeconomic position (SEP). In a subsample of 406 cognitively normal participants, associations were investigated between cognition and β-amyloid (Aβ) positivity (determined from Aβ-PET imaging), whole brain volumes, white matter hyperintensity volumes (WMHV), and APOE ε4.ResultsChildhood cognitive ability was strongly associated with cognitive scores including the PACC more than 60 years later, and there were independent effects of education and SEP. Sex differences were observed on every PACC subtest. In cognitively normal participants, Aβ positivity and WMHV were independently associated with lower PACC scores, and Aβ positivity was associated with poorer nonverbal reasoning. Aβ positivity and WMHV were not associated with sex, childhood cognitive ability, education, or SEP. Normative data for 339 cognitively normal Aβ-negative participants are provided.ConclusionsThis study adds to emerging evidence that subtle cognitive differences associated with Aβ deposition are detectable in older adults, at an age when dementia prevalence is very low. The independent associations of childhood cognitive ability, education, and SEP with cognitive performance at age 70 have implications for interpretation of cognitive data in later life.

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10

Brick Larkin, Gabriella, and Daniel D. Kurylo. "Perceptual Grouping and High-Order Cognitive Ability." Journal of Individual Differences 34, no. 3 (August 1, 2013): 153–58. http://dx.doi.org/10.1027/1614-0001/a000110.

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High-order cognitive functions require the integration of information across functionally related modules. This relationship suggests that cognitive ability is related to the efficiency and processing speed of basic integrative function. In order to examine individual differences for this relationship, we compared standardized tests of intelligence to visual perceptual grouping abilities, which represents a basic process of integration. Sixty participants discriminated perceived grouping of dot patterns based upon similarity in luminance. Psychophysical measurements were made of the functional limits and processing speed of grouping. We assessed cognitive abilities with the Wechsler Abbreviated Scale of Intelligence (WASI) and found that measures of grouping efficiency as well as speed varied considerably across subjects, indicating substantial individual differences at this relatively early level of visual processing. Faster grouping speed was associated with higher scores on all WASI subtests, whereas grouping ability, when not restricted by time, was associated only with the performance IQ components. These results demonstrate an association between a basic integrative function, in which cognitive and motoric factors were minimized, with measures of high-order cognition, which include both verbal and spatial cognitive components.

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11

Zhou, Longjun. "Which Matters More, Cognitive or Non-cognitive Ability?" Science Insights Education Frontiers 12, no. 1 (June 30, 2022): 1607–9. http://dx.doi.org/10.15354/sief.22.co017.

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From a psychological perspective, both cognitive and non-cognitive abilities are significant drivers of human growth. The ability to gather, choose, and comprehend information is referred to as cognitive ability. To be more specific, it consists of human abilities to comprehend the nature and characteristics of objects, as well as how they relate to one another, fundamental laws, and the future course of the world. Any skill that is not cognitive is considered non-cognitive. Examples include emotional maturity, empathy, and interpersonal skills, which are essential for people to deal with various contexts.

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12

Zhou, Longjun. "Which Matters More, Cognitive or Non-cognitive Ability?" Science Insights Education Frontiers 12, no. 1 (June 30, 2022): 1607–9. http://dx.doi.org/10.15354/sief.v12i1.781.

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From a psychological perspective, both cognitive and non-cognitive abilities are significant drivers of human growth. The ability to gather, choose, and comprehend information is referred to as cognitive ability. To be more specific, it consists of human abilities to comprehend the nature and characteristics of objects, as well as how they relate to one another, fundamental laws, and the future course of the world. Any skill that is not cognitive is considered non-cognitive. Examples include emotional maturity, empathy, and interpersonal skills, which are essential for people to deal with various contexts.

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13

Piks, Bruna. "Interplay of Cognitive Efficiency, Cognitive Ability and Motivation." Interdisciplinary Description of Complex Systems 12, no. 4 (2014): 293–304. http://dx.doi.org/10.7906/indecs.12.4.3.

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14

McHutchison, Caroline A., Francesca M. Chappell, Stephen Makin, Kirsten Shuler, Joanna M. Wardlaw, and Vera Cvoro. "Stability of Estimated Premorbid Cognitive Ability over Time after Minor Stroke and Its Relationship with Post-Stroke Cognitive Ability." Brain Sciences 9, no. 5 (May 22, 2019): 117. http://dx.doi.org/10.3390/brainsci9050117.

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Considering premorbid or “peak” adult intelligence (IQ) is important when examining post-stroke cognition. The stability of estimated premorbid IQ and its relationship to current cognitive ability in stroke is unknown. We investigated changes in estimated premorbid IQ and current cognitive ability up to three years post-stroke. Minor stroke patients (NIHSS < 8) were assessed at one to three months, one and three years’ post-stroke. The National Adult Reading Test (NART) and Addenbrooke’s Cognitive Examination-Revised (ACE-R) were used to estimate premorbid IQ (NART IQ) and current cognitive ability respectively at each time-point. Baseline demographics, vascular and stroke characteristics were included. Of the 264 patients recruited (mean age 66), 158 (60%), 151 (57%), and 153 (58%) completed cognitive testing at each time-point respectively. NART IQ initially increased (mean difference (MD) = 1.32, 95% CI = 0.54 to 2.13, p < 0.001) before decreasing (MD = −4.269, 95% CI = −5.12 to −3.41, p < 0.001). ACE-R scores initially remained stable (MD = 0.29, 95% CI = −0.49 to 1.07, p > 0.05) before decreasing (MD = −1.05, 95% CI = −2.08 to −0.01, p < 0.05). Adjusting for baseline variables did not change the relationship between NART IQ and ACE-R with time. Increases in NART IQ were associated with more education. For ACE-R, older age was associated with declines, and higher NART IQ and more education was associated with increases. Across 3 years, we observed fluctuations in estimated premorbid IQ and minor changes in current cognitive ability. Future research should aim to identify variables associated with these changes. However, studies of post-stroke cognition should account for premorbid IQ.

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15

León, Federico. "Altitude’s effects on complex cognitive ability." Propósitos y Representaciones 1, no. 2 (2013): 31–56. http://dx.doi.org/10.20511/pyr2013.v1n2.26.

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16

Growney, Claire, and Tammy English. "AGE AND COGNITIVE ABILITY AS PREDICTORS OF EMOTION REGULATION STRATEGY USE." Innovation in Aging 6, Supplement_1 (November 1, 2022): 489. http://dx.doi.org/10.1093/geroni/igac059.1883.

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Abstract Emotion regulation (ER) is viewed as a cognitively demanding process and involves selecting and implementing specific strategies in support of one’s emotional goals. Older adults are theorized to maintain emotional wellbeing by selecting ER strategies that are consistent with their available resources, which may involve engaging more with lower-arousal stimuli and less with higher-arousal stimuli, especially when cognitive resources are limited. The aim of this study was to examine relationships between age, cognitive ability, and use of different types of ER strategies. Participants (N = 287) aged 25-85 (M = 54.33, SD = 17.19) completed assessments of cognitive ability from the NIH Toolbox Cognitive Battery. In a laboratory task, participants viewed a series of film clips eliciting low-arousal emotions (sadness, contentment) and high-arousal emotions (disgust, amusement) under instructions to regulate pro-hedonically using any available strategy. They reported their use of disengagement (e.g., distraction, suppression), engagement (e.g., perspective-taking, awareness), and positive-focus strategies (e.g., savoring, positive reappraisal). Results from multilevel models revealed that with low-arousal stimuli, age was associated with higher engagement and lower disengagement, regardless of fluid cognitive ability. With high-arousal stimuli, a fluid cognition X age interaction indicated that there was an age-related increase in engagement among individuals with higher fluid cognitive ability, but not lower fluid cognitive ability. Findings support the idea that older adults tend to engage with emotional stimuli, which may aid with processing and support emotional memory for future regulation attempts. Fluid cognitive ability may be an important resource supporting older adults’ engagement with high-arousal stimuli.

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17

Asamura, Akihiko, Koichi Kaketa, Takuya Miyazaki, and Iwao Yoshino. "Cognitive Failures and Metacognitive Ability." Proceedings of the Annual Convention of the Japanese Psychological Association 78 (September 10, 2014): 3EV—1–046–3EV—1–046. http://dx.doi.org/10.4992/pacjpa.78.0_3ev-1-046.

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18

ASAMURA, Akihiko, Iwao YOSHINO, Koichi KAKETA, and Takuya MIYAZAKI. "Cognitive Failures and Metacognitive Ability." Proceedings of the Annual Convention of the Japanese Psychological Association 74 (September 20, 2010): 1AM042. http://dx.doi.org/10.4992/pacjpa.74.0_1am042.

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19

Lasker, Jordan, Bryan J. Pesta, John G. R. Fuerst, and Emil O. W. Kirkegaard. "Global Ancestry and Cognitive Ability." Psych 1, no. 1 (August 30, 2019): 431–59. http://dx.doi.org/10.3390/psych1010034.

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Using data from the Philadelphia Neurodevelopmental Cohort, we examined whether European ancestry predicted cognitive ability over and above both parental socioeconomic status (SES) and measures of eye, hair, and skin color. First, using multi-group confirmatory factor analysis, we verified that strict factorial invariance held between self-identified African and European-Americans. The differences between these groups, which were equivalent to 14.72 IQ points, were primarily (75.59%) due to difference in general cognitive ability (g), consistent with Spearman’s hypothesis. We found a relationship between European admixture and g. This relationship existed in samples of (a) self-identified monoracial African-Americans (B = 0.78, n = 2,179), (b) monoracial African and biracial African-European-Americans, with controls added for self-identified biracial status (B = 0.85, n = 2407), and (c) combined European, African-European, and African-American participants, with controls for self-identified race/ethnicity (B = 0.75, N = 7,273). Controlling for parental SES modestly attenuated these relationships whereas controlling for measures of skin, hair, and eye color did not. Next, we validated four sets of polygenic scores for educational attainment (eduPGS). MTAG, the multi-trait analysis of genome-wide association study (GWAS) eduPGS (based on 8442 overlapping variants) predicted g in both the monoracial African-American (r = 0.111, n = 2179, p < 0.001), and the European-American (r = 0.227, n = 4914, p < 0.001) subsamples. We also found large race differences for the means of eduPGS (d = 1.89). Using the ancestry-adjusted association between MTAG eduPGS and g from the monoracial African-American sample as an estimate of the transracially unbiased validity of eduPGS (B = 0.124), the results suggest that as much as 20%–25% of the race difference in g can be naïvely explained by known cognitive ability-related variants. Moreover, path analysis showed that the eduPGS substantially mediated associations between cognitive ability and European ancestry in the African-American sample. Subtest differences, together with the effects of both ancestry and eduPGS, had near-identity with subtest g-loadings. This finding confirmed a Jensen effect acting on ancestry-related differences. Finally, we confirmed measurement invariance along the full range of European ancestry in the combined sample using local structural equation modeling. Results converge on genetics as a potential partial explanation for group mean differences in intelligence.

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20

Pittelli, S. J. "Genetic research on cognitive ability." British Journal of Psychiatry 180, no. 2 (February 2002): 186. http://dx.doi.org/10.1192/bjp.180.2.186.

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21

Knight, Margaret M. "Cognitive ability and functional status." Journal of Advanced Nursing 31, no. 6 (June 2000): 1459–68. http://dx.doi.org/10.1046/j.1365-2648.2000.01446.x.

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22

Ronnber, Jerke. "Cognitive ability and communicative disability." Scandinavian Journal of Psychology 39, no. 3 (September 1998): 125–29. http://dx.doi.org/10.1111/1467-9450.393066.

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23

Verney, Steven P., Eric Granholm, Sandra P. Marshall, Vanessa L. Malcarne, and Dennis P. Saccuzzo. "Culture-Fair Cognitive Ability Assessment." Assessment 12, no. 3 (September 2005): 303–19. http://dx.doi.org/10.1177/1073191105276674.

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24

Rae, Caroline, Richard B. Scott, Martin Lee, Judy M. Simpson, Nicola Hines, Caroline Paul, Mike Anderson, Annette Karmiloff-Smith, Peter Styles, and George K. Radda. "Brain Bioenergetics and Cognitive Ability." Developmental Neuroscience 25, no. 5 (2003): 324–31. http://dx.doi.org/10.1159/000073509.

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25

Schweizer, Karl. "Preattentive processing and cognitive ability." Intelligence 29, no. 2 (March 2001): 169–86. http://dx.doi.org/10.1016/s0160-2896(00)00049-0.

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26

Schweizer, Karl, and Wolfgang Koch. "Perceptual processes and cognitive ability." Intelligence 31, no. 3 (May 2003): 211–35. http://dx.doi.org/10.1016/s0160-2896(02)00117-4.

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27

Plomin, R., and I. Craig. "Genetic research on cognitive ability." British Journal of Psychiatry 180, no. 2 (February 2002): 186. http://dx.doi.org/10.1192/s0007125000270992.

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28

Schellenberg, Glenn. "Musical ability and cognitive abilities." Journal of the Acoustical Society of America 126, no. 4 (2009): 2278. http://dx.doi.org/10.1121/1.3249333.

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29

Mieda, Takahiro, Kanako Taku, and Atsushi Oshio. "Dichotomous thinking and cognitive ability." Personality and Individual Differences 169 (February 2021): 110008. http://dx.doi.org/10.1016/j.paid.2020.110008.

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30

Lubinski, David. "Exceptional Cognitive Ability: The Phenotype." Behavior Genetics 39, no. 4 (May 8, 2009): 350–58. http://dx.doi.org/10.1007/s10519-009-9273-0.

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31

Jürges, Hendrik, and Sophie-Charlotte Meyer. "Cognitive ability and teen smoking." European Journal of Health Economics 21, no. 2 (October 28, 2019): 287–96. http://dx.doi.org/10.1007/s10198-019-01127-1.

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32

Sakuma, Michael, Anne L. Hoff, and Lynn E. DeLisi. "Functional laterality and cognitive ability." Schizophrenia Research 18, no. 2-3 (February 1996): 213–14. http://dx.doi.org/10.1016/0920-9964(96)85658-1.

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33

Starr, John M., and Catherine Quinn. "GSTZ1 Genotype and Cognitive Ability." European Neurological Review 3, no. 2 (2008): 15. http://dx.doi.org/10.17925/enr.2008.03.02.15.

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34

Asamura, Akihiko, Koichi Kaketa, Takuya Miyazaki, and Iwao Yoshino. "Cognitive Failures and Metacognitive Ability." Proceedings of the Annual Convention of the Japanese Psychological Association 79 (September 22, 2015): 1EV—089–1EV—089. http://dx.doi.org/10.4992/pacjpa.79.0_1ev-089.

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35

ASAMURA, Akihito, Koichi KAKETA, Takuya MIYAZAKI, and Iwao YOSHINO. "Cognitive Failures and Metacognitive Ability." Proceedings of the Annual Convention of the Japanese Psychological Association 75 (September 15, 2011): 1AM141. http://dx.doi.org/10.4992/pacjpa.75.0_1am141.

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ASAMURA, Akihiko, Koichi KAKETA, Takuya MIYAZAKI, and Iwao YOSHINO. "Cognitive Failures and Metacognitive Ability." Proceedings of the Annual Convention of the Japanese Psychological Association 76 (September 11, 2012): 3AMA45. http://dx.doi.org/10.4992/pacjpa.76.0_3ama45.

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37

Plomin, Robert. "Genetics and general cognitive ability." Nature 402, S6761 (December 1999): C25—C29. http://dx.doi.org/10.1038/35011520.

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38

Starr, John M., Helen Fox, Sarah E. Harris, Ian J. Deary, and Lawrence J. Whalley. "GSTz1 genotype and cognitive ability." Psychiatric Genetics 18, no. 4 (August 2008): 211–12. http://dx.doi.org/10.1097/ypg.0b013e328304dea8.

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39

Konek, Jason. "Probabilistic Knowledge and Cognitive Ability." Philosophical Review 125, no. 4 (October 2016): 509–87. http://dx.doi.org/10.1215/00318108-3624754.

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40

Bishop, D. V. M. "Handedness, Clumsiness and Cognitive Ability." Developmental Medicine & Child Neurology 22, no. 5 (November 12, 2008): 569–79. http://dx.doi.org/10.1111/j.1469-8749.1980.tb04370.x.

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41

Räsänen, Pirkko, Reijo Hirvenoja, Helinä Hakko, and Erkki Vä Isänen. "Cognitive functioning ability of arsonists." Journal of Forensic Psychiatry 5, no. 3 (December 1994): 615–20. http://dx.doi.org/10.1080/09585189408410855.

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42

James, Russell N. "Charitable giving and cognitive ability." International Journal of Nonprofit and Voluntary Sector Marketing 16, no. 1 (January 24, 2011): 70–83. http://dx.doi.org/10.1002/nvsm.402.

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43

Carpenter, Jeffrey, Michael Graham, and Jesse Wolf. "Cognitive ability and strategic sophistication." Games and Economic Behavior 80 (July 2013): 115–30. http://dx.doi.org/10.1016/j.geb.2013.02.012.

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44

Gleser, Leon Jay. "Assessing familiality of cognitive ability." Intelligence 9, no. 4 (October 1985): 375–85. http://dx.doi.org/10.1016/0160-2896(85)90021-2.

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Coon, Hilary, Gregory Carey, and David W. Fulker. "Community influences on cognitive ability." Intelligence 16, no. 2 (April 1992): 169–88. http://dx.doi.org/10.1016/0160-2896(92)90003-a.

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46

Koenig, Katherine A., Meredith C. Frey, and Douglas K. Detterman. "ACT and general cognitive ability." Intelligence 36, no. 2 (March 2008): 153–60. http://dx.doi.org/10.1016/j.intell.2007.03.005.

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47

Galvin, James E., Catherine M. Roe, Mary A. Coats, and John C. Morris. "Patient's Rating of Cognitive Ability." Archives of Neurology 64, no. 5 (May 1, 2007): 725. http://dx.doi.org/10.1001/archneur.64.5.725.

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48

Brancucci, Alfredo. "Neural correlates of cognitive ability." Journal of Neuroscience Research 90, no. 7 (March 16, 2012): 1299–309. http://dx.doi.org/10.1002/jnr.23045.

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49

Christopher Auld, M., and Nirmal Sidhu. "Schooling, cognitive ability and health." Health Economics 14, no. 10 (2005): 1019–34. http://dx.doi.org/10.1002/hec.1050.

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Roth, Wolff-Michael, and Michelle K. McGinn. "Graphing: Cognitive ability or practice?" Science Education 81, no. 1 (January 1997): 91–106. http://dx.doi.org/10.1002/(sici)1098-237x(199701)81:1<91::aid-sce5>3.0.co;2-x.

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