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Journal article
Digital Clock Drawing: Differentiating “Thinking” versus “Doing” in Younger and Older Adults with Depression
Journal of the International Neuropsychological Society, v 20(9), pp 920-928
01 Oct 2014
PMID: 25222513
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Psychomotor slowing has been documented in depression. The digital Clock Drawing Test (dCDT) provides: (i) a novel technique to assess both cognitive and motor aspects of psychomotor speed within the same task and (ii) the potential to uncover subtleties of behavior not previously detected with non-digitized modes of data collection. Using digitized pen technology in 106 participants grouped by Age (younger/older) and Affect (euthymic/unmedicated depressed), we recorded cognitive and motor output by capturing how the clock is drawn rather than focusing on the final product. We divided time to completion (TTC) for Command and Copy conditions of the dCDT into metrics of percent of drawing (%Ink) versus non-drawing (%Think) time. We also obtained composite Z-scores of cognition, including attention/information processing (AIP), to explore associations of %Ink and %Think times to cognitive and motor performance. Despite equivalent TTC, %Ink and %Think Command times (Copy n.s.) were significant (AgeXAffect interaction: p=.03)—younger depressed spent a smaller proportion of time drawing relative to thinking compared to the older depressed group. Command %Think time negatively correlated with AIP in the older depressed group (r=−.46; p=.02). Copy %Think time negatively correlated with AIP in the younger depressed (r=−.47; p=.03) and older euthymic groups (r=−.51; p=.01). The dCDT differentiated aspects of psychomotor slowing in depression regardless of age, while dCDT/cognitive associates for younger adults with depression mimicked patterns of older euthymics. (JINS, 2014, 20, 1–9)
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Details
- Title
- Digital Clock Drawing: Differentiating “Thinking” versus “Doing” in Younger and Older Adults with Depression
- Creators
- Jamie Cohen - University of Illinois at ChicagoDana L. Penney - Lahey Hospital and Medical CenterRandall Davis - MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MassachusettsDavid J. Libon - Drexel UniversityRodney A. Swenson - University of North DakotaOlusola Ajilore - University of Illinois at ChicagoAnand Kumar - University of Illinois at ChicagoMelissa Lamar - University of Illinois at Chicago
- Publication Details
- Journal of the International Neuropsychological Society, v 20(9), pp 920-928
- Publisher
- Cambridge University Press
- Number of pages
- 9
- Resource Type
- Journal article
- Language
- English
- Web of Science ID
- WOS:000344947600005
- Scopus ID
- 2-s2.0-84910640356
- Other Identifier
- 991021901014104721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Clinical Neurology
- Neurosciences
- Psychiatry
- Psychology