Brandon Frank, Sabyasachi Bandyopadhyay, Catherine Dion, Erin Formanski, Emily Matusz, Dana Penney, Randall Davis, Maureen K O'Connor, Rhoda Au, Shawna Amini, Parisa Rashidi, Patrick Tighe, David J Libon, Catherine C Price
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Using a Bayesian hill-climbing algorithm and bootstrapping (10,000 samples), we derived directed acyclic graphs (DAGs) to examine network structure for command and copy dCDT variables. Although the command condition showed moderate associations between variables (<math><mrow><msub><mrow><mi>μ</mi></mrow><mrow><mo>|</mo><mi>β</mi><mi>z</mi><mo>|</mo></mrow></msub></mrow></math>= 0.34) relative to the copy condition (<math><mrow><msub><mrow><mi>μ</mi></mrow><mrow><mo>|</mo><mi>β</mi><mi>z</mi><mo>|</mo></mrow></msub></mrow></math> = 0.25), the copy condition network had more connections (18/18 versus 15/18 command). Network connectivity across command and copy was most influenced by five of the 18 variables. The direction of dependencies followed the order of instructions better in the command condition network. Digitally acquired clock variables relate to one another but differ in network structure when derived from command or copy conditions. Continued analyses of clock drawing production should improve understanding of quintessential normal features to aid in early neurodegenerative disease detection.</p>","PeriodicalId":8577,"journal":{"name":"Assessment","volume":" ","pages":"119-129"},"PeriodicalIF":3.5000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11408704/pdf/","citationCount":"0","resultStr":"{\"title\":\"A Network Analysis of Digital Clock Drawing for Command and Copy Conditions.\",\"authors\":\"Brandon Frank, Sabyasachi Bandyopadhyay, Catherine Dion, Erin Formanski, Emily Matusz, Dana Penney, Randall Davis, Maureen K O'Connor, Rhoda Au, Shawna Amini, Parisa Rashidi, Patrick Tighe, David J Libon, Catherine C Price\",\"doi\":\"10.1177/10731911241236336\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Graphomotor and time-based variables from the digital Clock Drawing Test (dCDT) characterize cognitive functions. However, no prior publications have quantified the strength of the associations between digital clock variables as they are produced. We hypothesized that analysis of the production of clock features and their interrelationships, as suggested, will differ between the command and copy test conditions. Older adults aged 65+ completed a digital clock drawing to command and copy conditions. Using a Bayesian hill-climbing algorithm and bootstrapping (10,000 samples), we derived directed acyclic graphs (DAGs) to examine network structure for command and copy dCDT variables. Although the command condition showed moderate associations between variables (<math><mrow><msub><mrow><mi>μ</mi></mrow><mrow><mo>|</mo><mi>β</mi><mi>z</mi><mo>|</mo></mrow></msub></mrow></math>= 0.34) relative to the copy condition (<math><mrow><msub><mrow><mi>μ</mi></mrow><mrow><mo>|</mo><mi>β</mi><mi>z</mi><mo>|</mo></mrow></msub></mrow></math> = 0.25), the copy condition network had more connections (18/18 versus 15/18 command). Network connectivity across command and copy was most influenced by five of the 18 variables. The direction of dependencies followed the order of instructions better in the command condition network. Digitally acquired clock variables relate to one another but differ in network structure when derived from command or copy conditions. 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A Network Analysis of Digital Clock Drawing for Command and Copy Conditions.
Graphomotor and time-based variables from the digital Clock Drawing Test (dCDT) characterize cognitive functions. However, no prior publications have quantified the strength of the associations between digital clock variables as they are produced. We hypothesized that analysis of the production of clock features and their interrelationships, as suggested, will differ between the command and copy test conditions. Older adults aged 65+ completed a digital clock drawing to command and copy conditions. Using a Bayesian hill-climbing algorithm and bootstrapping (10,000 samples), we derived directed acyclic graphs (DAGs) to examine network structure for command and copy dCDT variables. Although the command condition showed moderate associations between variables (= 0.34) relative to the copy condition ( = 0.25), the copy condition network had more connections (18/18 versus 15/18 command). Network connectivity across command and copy was most influenced by five of the 18 variables. The direction of dependencies followed the order of instructions better in the command condition network. Digitally acquired clock variables relate to one another but differ in network structure when derived from command or copy conditions. Continued analyses of clock drawing production should improve understanding of quintessential normal features to aid in early neurodegenerative disease detection.
期刊介绍:
Assessment publishes articles in the domain of applied clinical assessment. The emphasis of this journal is on publication of information of relevance to the use of assessment measures, including test development, validation, and interpretation practices. The scope of the journal includes research that can inform assessment practices in mental health, forensic, medical, and other applied settings. Papers that focus on the assessment of cognitive and neuropsychological functioning, personality, and psychopathology are invited. Most papers published in Assessment report the results of original empirical research, however integrative review articles and scholarly case studies will also be considered.