Cited by 158Attention Deficit Hyperactivity DisorderMind wandering and attentionNeural and Behavioral Psychology Studies

The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.

Development of Sustained Attention Assessed Using the Continuous Performance Test among Children 6–15 Years of Age

Lin, Chaucer C. H., Hsiao, Chuhsing K., Chen, Wei J.·1999·Journal of Abnormal Child Psychology

Abstract

The Continuous Performance Test (CPT) is a widely used measure of sustained attention, which may rely on the efficiency of cognitive inhibition. We examined the relationships of age and sex with CPT performance among 341 randomly selected school children 6-15 years of age. Multiple regression analyses revealed that the hit rate, false alarm rate, and sensitivity of both the undegraded and the degraded CPT were associated with age by a quadratic relationship. The age-development curves for the hit rate and sensitivity were convex, whereas that for the false alarm rate was concave. Sex was associated with the hit rate and sensitivity on the degraded CPT only. Our findings are consistent with the hypothesis that sustained attention develops during the primary school ages. The data reported are essential for identifying children with conditions associated with sustained attention deficit, such as attention-deficit hyperactivity disorder, as well as those at an increased risk for developing schizophrenia.

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Crossref · 10.1023/a:1021932119311

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49 of 49 references verified0 citation errors · 0 not checkable

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  • Sustained attention measured by continuous performance tests increases significantly from 3 to 6 years and continues developing into late childhood and adolescence, reaching adult-like levels around age 12.

    “Sustained attention abilities, as measured by the CPT, increase significantly from 3 to 6 years of age (Akshoomoff, 2002; Kerns & Rondeau, 1998; Levy, 1980) and continue to develop into late childhood and adolescence, reaching adult-like levels around the age of 12 years (Lin, Hsiao, & Chen, 1999).”

    From Atypical attentional networks and the emergence of autism (2013) · cites this paper as Lin et al., 1999

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Research works printed but not linked: 2

  1. Cornblatt, B. A., & Erlenmeyer-Kimling, L. (1984). Early attentional predictors of adolescent behavioral disturbances in children at risk for schizophrenia. In N. F. Watt, E. J. Anthony, L. C. Wynne, & J. E. Rolf (Eds.), Children at risk for schizophrenia: A longitudinal perspective (pp. 198–211). New York: Cambridge University Press.
  2. SAS Institute, Inc. (1989). SAS/STAT User's Guide, Version 6. Cary, NC: SAS Institute.

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Metadata

Authors
Lin, C. C. H., Hsiao, C. K., & Chen, W. J.
Affiliations
National Taiwan University (TW)
Venue
Journal of Abnormal Child Psychology
Published
1999-10
Volume
27
Issue
5
Pages
403-412
ISSN
  • 0091-0627 (ISSN-L)
  • 1573-2835
OpenAlex
W1561946342
Cited by
158
References
49
Citations by year
2026: 1 · 2025: 3 · 2024: 6 · 2023: 9 · 2022: 8 · 2021: 7 · 2020: 10 · 2019: 7 · 2018: 6 · 2017: 9 · 2016: 5 · 2015: 4 · 2014: 5 · 2013: 7 · 2012: 11
FWCI
2.14
Type
journal article
Language
en
Open access
closed
Locations
  • Research on Child and Adolescent Psychopathology (publishedVersion)
  • PubMed (publishedVersion)
  • AH-Scopus to ORCID
Funders
National Science Council
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Attention Deficit Hyperactivity Disorder
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Mind wandering and attention
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Keywords
sustained attention, continuous performance test, cognitive inhibition, age differences, sex differences, developmental trajectories, hit rate, false alarm rate, sensitivity, attention deficit hyperactivity disorder, schizophrenia risk, elementary school students
MeSH terms
Adolescent, Age Factors, Attention, Child, Child Development, Female, Humans, Male, Neuropsychological Tests, Psychometrics, Reference Values, Sensitivity and Specificity, Taiwan, Multivariate Analysis, Likelihood Functions, Linear Models, Signal Detection, Psychological

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