The Digital Tree Drawing Test for Screening of Early Dementia: An Explorative Study Comparing Healthy Controls, Patients with Mild Cognitive Impairment, and Patients with Early Dementia of the Alzheimer Type

Robens, Sibylle; Heymann, Petra; Gienger, Regine; Hett, Andreas; Müller, Silke M.; Laske, Christoph; Loy, Roland; Ostermann, Thomas; Elbing, Ulrich

doi:10.3233/jad-181029

Cited by 28 publications

(31 citation statements)

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“…Out of a total of 20,136 studies, 20,088 were removed according to the exclusion criteria and, additionally, if they (a) assessed visuomotor abilities in patients with MCI in Parkinson's Disease (MCI-PD) because of the major motor impairment or (b) provided information about upper extremity functioning by self-report measures. The final set, therefore, consisted of 48 studies assessing the following issues: 16 studies assessed VSWM abilities [17,[25][26][27][28][29][30][31][32][33][34][35][36][37][38][39], 12 studies assessed anosognosia for memory deficits [40][41][42][43][44][45][46][47][48][49][50][51], 14 studies assessed visuomotor abilities [52][53][54][55][56][57][58][59][60][61][62][63][64][65], 2 studies investigated the relationship between VSWM and conversion [37,66], and 4 studies investigated the relationship between anosognosia for memory deficit...…”

Section: Data Extraction Results and Synthesismentioning

confidence: 99%

“…However, the majority of data available in the literature suggests that visuomotor abilities are compromised in MCI [52,[54][55][56][57][58][59][60][61][62][63][64][65] (Table 1). Particularly, hand movements of MCI patients were found to be less accurate [57,65], slower [57,60,61,64], and less coordinated [52, 54-56, 58, 59, 62, 63] as compared with healthy controls. Some studies suggested, moreover, a similar degree of visuomotor deterioration in patients with MCI and AD [55,[58][59][60]65].…”

Section: And Visuomotor Controlmentioning

confidence: 99%

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Neuropsychology of posteromedial parietal cortex and conversion factors from Mild Cognitive Impairment to Alzheimer’s disease: systematic search and state-of-the-art review

et al. 2021

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In the present review, we discuss the rationale and the clinical implications of assessing visuospatial working memory (VSWM), awareness of memory deficits, and visuomotor control in patients with mild cognitive impairment (MCI). These three domains are related to neural activity in the posteromedial parietal cortex (PMC) whose hypoactivation seems to be a significant predictor of conversion from MCI to Alzheimer’s disease (AD) as indicated by recent neuroimaging evidence. A systematic literature search was performed up to May 2021. Forty-eight studies were included: 42 studies provided analytical cross-sectional data and 6 studies longitudinal data on conversion rates. Overall, these studies showed that patients with MCI performed worse than healthy controls in tasks assessing VSWM, awareness of memory deficits, and visuomotor control; in some cases, MCI patients’ performance was comparable to that of patients with overt dementia. Deficits in VSWM and metamemory appear to be significant predictors of conversion. No study explored the relationship between visuomotor control and conversion. Nevertheless, it has been speculated that the assessment of visuomotor abilities in subjects at high AD risk might be useful to discriminate patients who are likely to convert from those who are not. Being able to indirectly estimate PMC functioning through quick and easy neuropsychological tasks in outpatient settings may improve diagnostic and prognostic accuracy, and therefore, the quality of the MCI patient’s management.

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Section: Data Extraction Results and Synthesismentioning

confidence: 99%

Section: And Visuomotor Controlmentioning

confidence: 99%

Neuropsychology of posteromedial parietal cortex and conversion factors from Mild Cognitive Impairment to Alzheimer’s disease: systematic search and state-of-the-art review

et al. 2021

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“…A digital cognitive test can capture behavioral data accurately. Some studies found that drawing time or drawing process can be a predictive factor for cognitive impairment [31,32]. In the last decade, some multidomain digital cognitive tests have been investigated, including Brain on Track [13] and Computerized Cognitive Screen [33].…”

Section: Principal Findingsmentioning

confidence: 99%

Electronic Cognitive Screen Technology for Screening Older Adults With Dementia and Mild Cognitive Impairment in a Community Setting: Development and Validation Study (Preprint)

Chan¹,

Wong²,

Yiu³

et al. 2019

Preprint

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BACKGROUND A digital cognitive test can be a useful and quick tool for the screening of cognitive impairment. Previous studies have shown that the diagnostic performance of digital cognitive tests is comparable with that of conventional paper-and-pencil tests. However, the use of commercially available digital cognitive tests is not common in Hong Kong, which may be due to the high cost of the tests and the language barrier. Thus, we developed a brief and user-friendly digital cognitive test called the Electronic Cognitive Screen (EC-Screen) for the detection of mild cognitive impairment (MCI) and dementia of older adults. OBJECTIVE The aim of this study was to evaluate the performance of the EC-Screen for the detection of MCI and dementia in older adults. METHODS The EC-Screen is a brief digital cognitive test that has been adapted from the Rapid Cognitive Screen test. The EC-Screen uses a cloud-based platform and runs on a tablet. Participants with MCI, dementia, and cognitively healthy controls were recruited from research clinics and the community. The outcomes were the performance of the EC-Screen in distinguishing participants with MCI and dementia from controls, and in distinguishing participants with dementia from those with MCI and controls. The cohort was randomly split into derivation and validation cohorts based on the participants’ disease group. In the derivation cohort, the regression-derived score of the EC-Screen was calculated using binomial logistic regression. Two predictive models were produced. The first model was used to distinguish participants with MCI and dementia from controls, and the second model was used to distinguish participants with dementia from those with MCI and controls. Receiver operating characteristic curves were constructed and the areas under the curves (AUCs) were calculated. The performances of the two predictive models were tested using the validation cohorts. The relationship between the EC-Screen and paper-and-pencil Montreal Cognitive Assessment-Hong Kong version (HK-MoCA) was evaluated by the Pearson correlation coefficient. RESULTS A total of 126 controls, 54 participants with MCI, and 63 participants with dementia were included in the study. In differentiating participants with MCI and dementia from controls, the AUC of the EC-Screen in the derivation and validation cohorts was 0.87 and 0.84, respectively. The optimal sensitivity and specificity in the derivation cohorts were 0.81 and 0.80, respectively. In differentiating participants with dementia from those with MCI and controls, the AUC of the derivation and validation cohorts was 0.90 and 0.88, respectively. The optimal sensitivity and specificity in the derivation cohort were 0.83 and 0.83, respectively. There was a significant correlation between the EC-Screen and HK-MoCA (<i>r</i>=–0.67, <i>P</i><.001). CONCLUSIONS The EC-Screen is suggested to be a promising tool for the detection of MCI and dementia. This test can be self-administered or assisted by a nonprofessional staff or family member. Therefore, the EC-Screen can be a useful tool for case finding in primary health care and community settings.

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“…In die statistische Analyse gingen dabei insgesamt 19 digital erfasste Kenngrößen ein. Eine ausführliche Beschreibung dieser Studie findet sich bei Robens et al [12].…”

Section: Fazit Und Ausblickunclassified

“…Farb-(b) und Strichstärkenwechseln (c), getrennt nach kognitiv gesund und leichter Alzheimer-Demenz [12].…”

Section: Abb 4 Anzahl Und Prozentanteil Der Personen Mit Einer Bestiunclassified

Der digitale Baumzeichentest – Ein kunsttherapeutischer Ansatz für das Demenz-Screening

Robens¹,

Ostermann²

2020

Zeitschrift für Komplementärmedizin

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SummaryFür die Frühdiagnostik von Demenz bestehtder Bedarf an zuverlässigen Screeningverfahren.Der Uhrentest nach Shulman weistlaut S3-Leitlinie „Demenz“ für Patientinnenund Patienten mit leichten kognitiven Einschränkungenkeine ausreichende Sensitivitätauf. Einen neuen Ansatz bietet der digitaleBaumzeichentest, der von einem multidisziplinärenTeam aus Wissenschaftlerinnenund Wissenschaftlern zusammen mit Kunsttherapeutinnenund -therapeuten entwickeltwurde. Das Zeichnen des Baummotivs erfolgthier mithilfe eines Tablets mit digitalemStift und einem einfachen Malprogramm.Durch eine softwaregestützte Berechnungund statistische Analyse wirdanhand bestimmter Zeichenmerkmale derGrad der kognitiven Beeinträchtigung erfasst.Die Forscherinnen und Forscher versprechensich durch das innovative Verfahren, neben einem diagnostischen Mehrwertzur frühen Identifizierung kognitiv eingeschränkterPersonen, eine weniger mitScham und Stress verbundene Testung, diezu einer erhöhten Motivation führt, an einemScreening teilzunehmen.

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The Digital Tree Drawing Test for Screening of Early Dementia: An Explorative Study Comparing Healthy Controls, Patients with Mild Cognitive Impairment, and Patients with Early Dementia of the Alzheimer Type

Cited by 28 publications

References 28 publications

Neuropsychology of posteromedial parietal cortex and conversion factors from Mild Cognitive Impairment to Alzheimer’s disease: systematic search and state-of-the-art review

Neuropsychology of posteromedial parietal cortex and conversion factors from Mild Cognitive Impairment to Alzheimer’s disease: systematic search and state-of-the-art review

Electronic Cognitive Screen Technology for Screening Older Adults With Dementia and Mild Cognitive Impairment in a Community Setting: Development and Validation Study (Preprint)

Der digitale Baumzeichentest – Ein kunsttherapeutischer Ansatz für das Demenz-Screening

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