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Thirty-Five Years of Computerized Cognitive Assessment of Aging-Where Are We Now?

ABSTRACT: Over the past 35 years, the proliferation of technology and the advent of the internet have resulted in many reliable and easy to administer batteries for assessing cognitive function. These approaches have great potential for affecting how the health care system monitors and screens for cognitive changes in the aging population. Here, we review these new technologies with a specific emphasis on what they offer over and above traditional 'paper-and-pencil' approaches to assessing cognitive function. Key advantages include fully automated administration and scoring, the interpretation of individual scores within the context of thousands of normative data points, the inclusion of 'meaningful change' and 'validity' indices based on these large norms, more efficient testing, increased sensitivity, and the possibility of characterising cognition in samples drawn from the general population that may contain hundreds of thousands of test scores. The relationship between these new computerized platforms and existing (and commonly used) paper-and-pencil tests is explored, with a particular emphasis on why computerized tests are particularly advantageous for assessing the cognitive changes associated with aging.

SUBMITTER: Sternin A

PROVIDER: S-EPMC6787729 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Thirty-Five Years of Computerized Cognitive Assessment of Aging-Where Are We Now?

Sternin Avital A Burns Alistair A Owen Adrian M AM

Diagnostics (Basel, Switzerland) 20190906 3

Over the past 35 years, the proliferation of technology and the advent of the internet have resulted in many reliable and easy to administer batteries for assessing cognitive function. These approaches have great potential for affecting how the health care system monitors and screens for cognitive changes in the aging population. Here, we review these new technologies with a specific emphasis on what they offer over and above traditional 'paper-and-pencil' approaches to assessing cognitive funct ...[more]

PMID: 31489940

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Project description:BackgroundCognitive assessment using tangible objects can measure fine motor and hand-eye coordination skills along with other cognitive domains. Administering such tests is often expensive, labor-intensive, and error prone owing to manual recording and potential subjectivity. Automating the administration and scoring processes can address these difficulties while reducing time and cost. e-Cube is a new vision-based, computerized cognitive assessment tool that integrates computational measures of play complexity and item generators to enable automated and adaptive testing. The e-Cube games use a set of cubes, and the system tracks the movements and locations of these cubes as manipulated by the player.ObjectiveThe primary objectives of the study were to validate the play complexity measures that form the basis of developing the adaptive assessment system and evaluate the preliminary utility and usability of the e-Cube system as an automated cognitive assessment tool.MethodsThis study used 6 e-Cube games, namely, Assembly, Shape-Matching, Sequence-Memory, Spatial-Memory, Path-Tracking, and Maze, each targeting different cognitive domains. In total, 2 versions of the games, the fixed version with predetermined sets of items and the adaptive version using the autonomous item generators, were prepared for comparative evaluation. Enrolled participants (N=80; aged 18-60 years) were divided into 2 groups: 48% (38/80) of the participants in the fixed group and 52% (42/80) in the adaptive group. Each was administered the 6 e-Cube games; 3 subtests of the Wechsler Adult Intelligence Scale, Fourth Edition (WAIS-IV; Block Design, Digit Span, and Matrix Reasoning); and the System Usability Scale (SUS). Statistical analyses at the 95% significance level were applied.ResultsThe play complexity values were correlated with the performance indicators (ie, correctness and completion time). The adaptive e-Cube games were correlated with the WAIS-IV subtests (r=0.49, 95% CI 0.21-0.70; P<.001 for Assembly and Block Design; r=0.34, 95% CI 0.03-0.59; P=.03 for Shape-Matching and Matrix Reasoning; r=0.51, 95% CI 0.24-0.72; P<.001 for Spatial-Memory and Digit Span; r=0.45, 95% CI 0.16-0.67; P=.003 for Path-Tracking and Block Design; and r=0.45, 95% CI 0.16-0.67; P=.003 for Path-Tracking and Matrix Reasoning). The fixed version showed weaker correlations with the WAIS-IV subtests. The e-Cube system showed a low false detection rate (6/5990, 0.1%) and was determined to be usable, with an average SUS score of 86.01 (SD 8.75).ConclusionsThe correlations between the play complexity values and performance indicators supported the validity of the play complexity measures. Correlations between the adaptive e-Cube games and the WAIS-IV subtests demonstrated the potential utility of the e-Cube games for cognitive assessment, but a further validation study is needed to confirm this. The low false detection rate and high SUS scores indicated that e-Cube is technically reliable and usable.

Project description:ObjectiveParkinson's disease (PD) is an age-related neurodegenerative condition characterized mostly by motor symptoms. Although a wide range of non-motor symptoms (NMS) are frequently experienced by PD patients. One of the important and common NMS is cognitive impairment, which is measured using different cognitive scales. Monitoring cognitive impairment and its decline in PD is essential for patient care and management. In this study, our goal is to identify the most effective cognitive scale in predicting cognitive decline over a 5-year timeframe initializing clinical biomarkers and DAT SPECT.MethodsMachine Learning has previously shown superior performance in image and clinical data classification and detection. In this study, we propose to use machine learning with different types of data, such as DAT SPECT and clinical biomarkers, to predict PD-CD based on various cognitive scales. We collected 330 DAT SPECT images and their clinical data in baseline, years 2,3,4, and 5 from Parkinson's Progression Markers Initiative (PPMI). We then designed a 3D Autoencoder to extract deep radiomic features (DF) from DAT SPECT images, and we then concatenated it with 17 clinical features (CF) to predict cognitive decline based on Montreal Cognitive Assessment (MoCA) and The Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS-I).ResultsThe utilization of MoCA as a cognitive decline scale yielded better performance in various years compared to MDS-UPDRS-I. In year 4, the application of the deep radiomic feature resulted in the highest achievement, with a cross-validation AUC of 89.28, utilizing the gradient boosting classifier. For the MDS-UPDRS-I scale, the highest achievement was obtained by utilizing the deep radiomic feature, resulting in a cross-validation AUC of 81.34 with the random forest classifier.ConclusionsThe study findings indicate that the MoCA scale may be a more effective predictor of cognitive decline within 5 years compared to MDS-UPDRS-I. Furthermore, deep radiomic features had better performance compared to sole clinical biomarkers or clinical and deep radiomic combined. These results suggest that using the MoCA score and deep radiomic features extracted from DAT SPECT could be a promising approach for identifying individuals at risk for cognitive decline in four years. Future research is needed to validate these findings and explore their utility in clinical practice.

Project description:ObjectivesDefine clinical spectrum and long-term outcomes of gut malrotation. With new insights, an innovative procedure was introduced and predictive models were established.MethodsOver 30-years, 500 patients were managed at 2 institutions. Of these, 274 (55%) were children at time of diagnosis. At referral, 204 (41%) patients suffered midgut-loss and the remaining 296 (59%) had intact gut with a wide range of digestive symptoms. With midgut-loss, 189 (93%) patients underwent surgery with gut transplantation in 174 (92%) including 16 of 31 (16%) who had autologous gut reconstruction. Ladd's procedure was documented in 192 (38%) patients with recurrent or de novo volvulus in 41 (21%). For 80 patients with disabling gastrointestinal symptoms, gut malrotation correction (GMC) surgery "Kareem's procedure" was offered with completion of the 270° embryonic counterclockwise-rotation, reversal of vascular-inversion, and fixation of mesenteric-attachments. Concomitant colonic dysmotility was observed in 25 (31%) patients.ResultsThe cumulative risk of midgut-loss increased with volvulus, prematurity, gastroschisis, and intestinal atresia whereas reduced with Ladd's and increasing age. Transplant cumulative survival was 63% at 10-years and 54% at 20-years with best outcome among infants and liver-containing allografts. Autologous gut reconstruction achieved 78% and GMC had 100% 10-year survival. Ladd's was associated with 21% recurrent/de novo volvulus and worsening (P > 0.05) of the preoperative National Institute of Health patient-reported outcomes measurement information system gastrointestinal symptom scales. GMC significantly (P ≤ 0.001) improved all of the symptomatology domains with no technical complications or development of volvulus. GMC improved quality of life with restored nutritional autonomy (P < 0.0001) and daily activities (P < 0.0001).ConclusionsGut malrotation is a clinicopathologic syndrome affecting all ages. The introduced herein definitive correction procedure is safe, effective, and easy to perform. Accordingly, the current standard of care practice should be redefined in this orphan population.

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Thirty-Five Years of Computerized Cognitive Assessment of Aging-Where Are We Now?

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Thirty-Five Years of Computerized Cognitive Assessment of Aging-Where Are We Now?

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