Cognitive Drawing Test

[Jen Ondrey]

TheClock-Drawing Test (CDT) is a simple and effective cognitive test used to assess executive function and visual-spatial function. It is a reliable screening tool for cognitive dysfunction, particularly for dementia. However, it lacks sensitivity for the diagnosis of early or mild dementia. The CDT can also be used to reveal neurological syndromes such as hemispatial neglect.

The CDT is useful as a quick screening cognitive test for dementia, but is generally less useful for detecting mild cognitive impairment. It tests for multiple domains of cognition, including executive function, attention, language skills, frontal lobe function, and visuospatial skills. To successfully do a clock drawing, and individual must be able to understand verbal instructions, encode instructions in short-term memory, and use visual constructive skills to draw a clock.

In individuals with conceptual deficits, they will have a loss or impairment in the ability to retrieve knowledge about the features and/or meaning of a clock. For example, they may draw something that does not look like a clock, or draw the hour and minute hands in a way that does not actually communicate time. Conceptual deficits are thought to be due to impairments in semantic memory (i.e. - the lateral temporal lobes).[8]

There are no standardized norms or scoring system for assessing the CDT. Various systems used in the literature but no one scoring system shows superior validity or predictive value. In addition to any existing neurocognitive disorder, age, educational-level, and psychiatric disorders (e.g. - depression) can also affect the clock drawing. The main aspects of the clock drawing to consider are:

There is a growing concern globally for mild cognitive impairment (MCI) and dementia due to the increasing aging population. Dementia is a syndrome in which there is progressive deterioration of cognitive function such as memory, visuospatial abilities, executive functions, and thinking (World Health Organization, 2019). MCI is recognized as the intermediate stage between normal aging and dementia (Petersen et al., 1999; Winblad et al., 2004). Early detection of MCI and dementia by cognitive screening tests can help patients and their family members to receive timely proper dementia-related care and support from health care professionals (Prince et al., 2011)

Due to the weakness of paper-and-pencil drawing tests and the advancement of technology, digital drawing tests have evolved over the past decade. Digital drawing tests can record and assess drawing characteristics such as total time spent, contour, and drawing methods, which can be considered when discriminating between MCI and dementia (Heymann et al., 2018). Studies showed that on-air movements can enhance the sensitivity of identifying patients with MCI (Garre-Olmo et al., 2017; Mller et al., 2017). The pressure applied when drawing can be another indicator to discriminate elders with MCI and healthy aging (Faundez-Zanuy et al., 2013).

A meta-analysis found that the diagnostic performance of digital cognitive tests and paper-and-pencil cognitive tests are comparable (Chan et al., 2018). However, previous studies seldom compare the diagnostic performance of digital drawing tests and paper-and-pencil drawing tests specifically. Therefore, the objective of this study was to evaluate the diagnostic performance of different types of digital drawing tests and paper-in-pencil drawing tests for the screening of MCI and dementia.

The current study was performed according to the standard guidelines for the systematic review of diagnostic studies, including the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Moher et al., 2009) and the guidelines proposed by the Cochrane Diagnostic Test Accuracy Working Group (Leeflang et al., 2008; Macaskill et al., 2010). This study is registered as CRD42020166750 in PROSPERO.

The Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) instrument (Whiting et al., 2011) was used to evaluate the potential risks of bias (ROB). The assessment areas included, 1. selection of patient, 2. execution of the screening tests, 3. execution of the reference standard, and 4. presentation on the patient flow and timing to have the reference standard and index tests. The methodology section of the STARD statement (Standards for Reporting of Diagnostic Accuracy) (Bossuyt et al., 2003) was used to evaluate the study quality. An 8-point scale was designed to evaluate the study quality, which included: 1. a clear definition on study population, 2. adequate details of recruitment of participants, 3. description of sampling of participant selection, 4. description of data collection plan, 5. description of reference standard and its rationale, 6. specifications of the drawing tests, 7. rationales for cutoff values, and 8. methods of calculation of diagnostic performance.

The primary outcome of this study was the diagnostic performance of the CDT for the screening of MCI and dementia. The secondary outcome was the diagnostic performance of other types of drawing tests.

This systematic review and meta-analysis included 90 studies and compared different types of digital drawing tests and paper-and-pencil drawing tests. The CDT is the most commonly used drawing test. In the screening of MCI, the digital CDT demonstrated better diagnostic performance than the paper-and-pencil CDT. Comparable performance was shown between the digital and paper-and-pencil CDT in the screeing of dementia. The diagnostic performance of other types of digital drawing tests and their paper-and-pencil formats was also comparable. Therefore, digital drawing tests can used as an alternative tool for the screening of MCI and dementia.

There are similarities between the digital CDT and paper-and-pencil CDT. Both methods require participants to draw the clock face as well as the hands of the clock that point to a specific time. The digital CDT uses a digital pen to draw on a tablet instead of drawing on a paper. Previous meta-analyses showed the diagnostic performance of paper-and-pencil CDT is fair in the screening of MCI, no matter the complexity of the scoring system (Ehreke et al., 2010; Pinto & Peters, 2009; Tsoi et al., 2017). This study showed similar results, however, the digital CDT showed better diagnostic performance than paper-and-pencil CDT in the screening of MCI. It may be due to the fact that deterioration of cognitive abilities such as executive function and visuospatial abilities found in patients with MCI are not yet clearly reflected in the final product of the paper drawing. However, decline in cognitive functions may be reflected in the drawing process captured in digital drawing tests (Mller et al., 2017; Garre-Olmo et al., 2017). Among different drawing characteristics, drawing time, pressure acceleration, and velocity are shown to be the behaviour markers for the discrimination of MCI from healthy aging (Garre-Olmo et al., 2017). Mller et al. (2019) further found that drawing time and velocity, such as time-in-air, total time strokes per minute are more sensitive maker than drawing pressure. Mller et al. (2017) suggested that time-in-air was a more sensitive marker than other time factors such as time-on-surface and total time (Muller et al., 2017). Additionally, the digital systems can automatically divide the drawing surface into different segments and sub-regions, and then analyze the strokes and angular differences of the drawing in the calculation of the final score (Davis et al., 2014; Shigemoria, et al., 2015). This combination of visual features and behavioural data can contribute to the identification of patients and enhance the accuracy of the digital CDT (Muller et al., 2019). Therefore, the use of digital CDT can improve the sensitivity and specificity in the screening of MCI. Past work suggests that machine-learning methods can enhance the ability to produce accurate predictive models of the drawing tests to classify MCI and dementia when the models trained on a large amount of data (Davis et al., 2014, Souillard-Mandar et al., 2016; Muller et al., 2017, 2019). Besides digital CDT, some other digital drawing tests have been suggested in the literature. The digital pentagon drawing test (Garre-Olmo et al., 2017; Tsoi et al., 2018) and digital ROCF (Cheah et al., 2019; Kokubo et al., 2018) are adapted from paper-and-pencil versions. The digital tree drawing test and digital house drawing test are adopted new approaches (Robens et al., 2019; Garre-Olmo et al., 2017). The digital tree drawing test and digital house drawing test are free-hand drawing tests which do not require the participants to draw any specific features. Thus, only drawing behaviour are used in the classification of disease.

The current study revealed that digital CDT can enhance the identification of deficits in the screening of MCI. Digital and paper-and-pencil CDT have a comparable performance in the screening of dementia. Other types of drawing tests in digital formats showed comparable to paper-in-pencil formats. Therefore, digital drawing tests can be a potential tool to use as an alternative for the screening of MCI and dementia.

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