Evidence map›Paper›PMID 25222513›Full record

ArticleJournal of the International Neuropsychological Society : JINS2014

Digital Clock Drawing: differentiating "thinking" versus "doing" in younger and older adults with depression.

Jamie Cohen, Dana L Penney, Randall Davis, David J Libon, Rodney A Swenson, Olusola Ajilore, Anand Kumar, Melissa Lamar

Registry-linked trialAbstract read
In one paragraph

Article in Journal of the International Neuropsychological Society : JINS, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03238001 (Evaluation of DCTclock™ as a Cognitive Assessment Aid), which is not on this map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT03238001 nacompletednot on this mapstarted 2017, after this paper: background citation

Evaluation of DCTclock™ as a Cognitive Assessment Aid

TypeinterventionalSponsorDigital Cognition TechnologiesRan2017 to 2017Enrolled450ConditionsCognitive FunctionArmsDCTclock
3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

  1. Generational differences in clock drawing test performance.Journal of the International Neuropsychological Society : JINS · 2026
    Article
  2. Article
  3. Article
  4. Review
  5. Modeling Users' Cognitive Performance Using Digital Pen Features.Frontiers in artificial intelligence · 2022
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Observational
  18. Technology and Dementia: The Future is Now.Dementia and geriatric cognitive disorders · 2019
    Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jamie Cohen1Department of Psychiatry,University of Illinois at Chicago,Chicago,Illinois.
Dana L Penney2The Lahey Clinic,Burlington,Massachusetts.
Randall Davis3MIT Computer Science and Artificial Intelligence Laboratory,Cambridge,Massachusetts.
David J Libon4Department of Neurology,Drexel University,Philadelphia,Pennsylvania.
Rodney A Swenson5University of North Dakota School of Medicine and Health Sciences,Grand Forks,North Dakota.
Olusola Ajilore1Department of Psychiatry,University of Illinois at Chicago,Chicago,Illinois.
Anand Kumar1Department of Psychiatry,University of Illinois at Chicago,Chicago,Illinois.
Melissa Lamar1Department of Psychiatry,University of Illinois at Chicago,Chicago,Illinois.

Funding

Myelin Glia and Depression in Type 2 DiabetesR01MH063764 · NIMH · UNIVERSITY OF ILLINOIS AT CHICAGO · PI KUMAR, ANAND · 2002 to 2012
$4.6M
Cortical/Subcortical Circuits in Late-Life DepressionR01MH073989 · NIMH · UNIVERSITY OF ILLINOIS AT CHICAGO · PI KUMAR, ANAND · 2006 to 2010
$2.6M
Brain Metabolites in Type 2 Diabetes and Major Depression Using MRSK23MH081175 · NIMH · UNIVERSITY OF ILLINOIS AT CHICAGO · PI AJILORE, OLUSOLA A. · 2009 to 2013
$825k
NIMH NIH HHS 7R01MH063764NIMH NIH HHS K23 MH081175NIMH NIH HHS K23MH081175-01A2NIMH NIH HHS R01 MH063764NIMH NIH HHS R01 MH073989NIMH NIH HHS R01MH073989
6 · The paper itself

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.

Indexed as

AgingAdultAgedAnalysis of VarianceCognition DisordersDepressionFemaleHumansMaleMiddle AgedNeuropsychological TestsPsychomotor DisordersRisk FactorsStatistics as TopicStrokeThinking

Identifiers

PMID25222513
PMCPMC4310546

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.