Population Health Solutions for Assessing Cognitive Impairment in Geriatric Patients.

In December 2017, the National Academy of Neuropsychology convened an interorganizational Summit on Population Health Solutions for Assessing Cognitive Impairment in Geriatric Patients in Denver, Colorado. The Summit brought together representatives of a broad range of stakeholders invested in the care of older adults to focus on the topic of cognitive health and aging. Summit participants specifically examined questions of who should be screened for cognitive impairment and how they should be screened in medical settings. This is important in the context of an acute illness given that the presence of cognitive impairment can have significant implications for care and for the management of concomitant diseases as well as pose a major risk factor for dementia. Participants arrived at general principles to guide future screening approaches in medical populations and identified knowledge gaps to direct future research. Key learning points of the summit included: recognizing the importance of educating patients and healthcare providers about the value of assessing current and baseline cognition;emphasizing that any screening tool must be appropriately normalized and validated in the population in which it is used to obtain accurate information, including considerations of language, cultural factors, and education; andrecognizing the great potential, with appropriate caveats, of electronic health records to augment cognitive screening and tracking of changes in cognitive health over time

The Index Of Narrative Microstructure: A Clinical Tool For Analyzing School-Age Children's Narrative Performances

Purpose: This research was conducted to develop a clinical tool-the Index of Narrative Microstructure (INMIS)-that would parsimoniously account for important microstructural aspects of narrative production for school-age children. The study provides field test age- and grade-based INMIS values to aid clinicians in making normative judgments about microstructural aspects of pupils' narrative performance. Method: Narrative samples using a single-picture elicitation context were collected from 250 children age 5-12 years and then transcribed and segmented into T-units. A T-unit consists of a single main clause and any dependent constituents. The narrative transcripts were then coded and analyzed to document a comprehensive set of microstructural indices. Results: Factor analysis indicated that narrative microstructure consisted of 2 moderately related factors. The Productivity factor primarily comprised measures of word output, lexical diversity, and T-unit output. The Complexity factor comprised measures of syntactic organization, with mean length of T-units in words and proportion of complex T-units loading most strongly. Principal components analysis was used to provide a linear combination of 8 variables to approximate the 2 factors. Formulas for calculating a student's performance on the 2 factors using 8 narrative measures are provided. Conclusions: This study provided a method for professionals to calculate INMIS scores for narrative Productivity and Complexity for comparison against field test data for age (5- to 12-year-old) or grade (kindergarten to Grade 6) groupings. INMIS scores complement other tools in evaluating a child's narrative performance specifically and language abilities more generally.Communication Sciences and Disorder

The Composition Of Normative Groups And Diagnostic Decision Making: Shooting Ourselves In The Foot

Purpose: The normative group of a norm-referenced test is intended to provide a basis for interpreting test scores. However, the composition of the normative group may facilitate or impede different types of diagnostic interpretations. This article considers who should be included in a normative sample and how-this decision must be made relative to the purpose for which a test is intended. Method: The way in which the composition of the normative sample affects classification accuracy is demonstrated through a test review followed by a simulation study. The test review examined the descriptions of the normative group in a sample of 32 child language tests. The mean performance reported in the test manual for the sample of language impaired children was compared with the sample's norms, which either included or excluded children with language impairment. For the simulation, 2 contrasting normative procedures were modeled. The first procedure included a mixed group of representative cases (language impaired and normal cases). The second procedure excluded the language impaired cases from the norm. Results: Both the data obtained from test manuals and the data simulation based on population characteristics supported our claim that use of mixed normative groups decreases the ability to accurately identify language impairment. Tests that used mixed norms had smaller differences between the normative and language impaired groups in comparison with tests that excluded children with impairment within the normative sample. The simulation demonstrated mixed norms that lowered the group mean and increased the standard deviation, resulting in decreased classification accuracy. Conclusions: When the purpose of testing is to identify children with impaired language skills, including children with language impairment in the normative sample can reduce identification accuracy.Communication Sciences and Disorder

The Man Who Mistook His Neuropsychologist For a Popstar: When Configural Processing Fails in Acquired Prosopagnosia

We report the case of an individual with acquired prosopagnosia who experiences extreme difficulties in recognizing familiar faces in everyday life despite excellent object recognition skills. Formal testing indicates that he is also severely impaired at remembering pre-experimentally unfamiliar faces and that he takes an extremely long time to identify famous faces and to match unfamiliar faces. Nevertheless, he performs as accurately and quickly as controls at identifying inverted familiar and unfamiliar faces and can recognize famous faces from their external features. He also performs as accurately as controls at recognizing famous faces when fracturing conceals the configural information in the face. He shows evidence of impaired global processing but normal local processing of Navon figures. This case appears to reflect the clearest example yet of an acquired prosopagnosic patient whose familiar face recognition deficit is caused by a severe configural processing deficit in the absence of any problems in featural processing. These preserved featural skills together with apparently intact visual imagery for faces allow him to identify a surprisingly large number of famous faces when unlimited time is available. The theoretical implications of this pattern of performance for understanding the nature of acquired prosopagnosia are discussed.DY, Avery Braun, Jacob Waite, and Nadine Wanke, Bruno Rossion, Thomas Busigny and the grant awarded by AJ by the Experimental Psychology Society (EPS

Graduate Student Impairment: The Impact on Counselor Training Programs

This article focuses on the issue of student impairment in graduate level counselor training programs and the factors that affect it, including: A definition of graduate student impairment; the prevalence of student impairment in counselor training programs; an explanation of the legal consequences when addressing student impairment; organizational issues in universities dealing with this issue; and, the impact of graduate student impairment on the counseling professions

The white matter connectome as an individualized biomarker of language impairment in temporal lobe epilepsy.

ObjectiveThe distributed white matter network underlying language leads to difficulties in extracting clinically meaningful summaries of neural alterations leading to language impairment. Here we determine the predictive ability of the structural connectome (SC), compared with global measures of white matter tract microstructure and clinical data, to discriminate language impaired patients with temporal lobe epilepsy (TLE) from TLE patients without language impairment.MethodsT1- and diffusion-MRI, clinical variables (CVs), and neuropsychological measures of naming and verbal fluency were available for 82 TLE patients. Prediction of language impairment was performed using a robust tree-based classifier (XGBoost) for three models: (1) a CV-model which included demographic and epilepsy-related clinical features, (2) an atlas-based tract-model, including four frontotemporal white matter association tracts implicated in language (i.e., the bilateral arcuate fasciculus, inferior frontal occipital fasciculus, inferior longitudinal fasciculus, and uncinate fasciculus), and (3) a SC-model based on diffusion MRI. For the association tracts, mean fractional anisotropy was calculated as a measure of white matter microstructure for each tract using a diffusion tensor atlas (i.e., AtlasTrack). The SC-model used measurement of cortical-cortical connections arising from a temporal lobe subnetwork derived using probabilistic tractography. Dimensionality reduction of the SC was performed with principal components analysis (PCA). Each model was trained on 49 patients from one epilepsy center and tested on 33 patients from a different center (i.e., an independent dataset). Randomization was performed to test the stability of the results.ResultsThe SC-model yielded a greater area under the curve (AUC; .73) and accuracy (79%) compared to both the tract-model (AUC: .54, p < .001; accuracy: 70%, p < .001) and the CV-model (AUC: .59, p < .001; accuracy: 64%, p < .001). Within the SC-model, lateral temporal connections had the highest importance to model performance, including connections similar to language association tracts such as links between the superior temporal gyrus to pars opercularis. However, in addition to these connections many additional connections that were widely distributed, bilateral and interhemispheric in nature were identified as contributing to SC-model performance.ConclusionThe SC revealed a white matter network contributing to language impairment that was widely distributed, bilateral, and lateral temporal in nature. The distributed network underlying language may be why the SC-model has an advantage in identifying sub-components of the complex fiber networks most relevant for aspects of language performance

Special educational needs and disability : Understanding local variation in prevalence, service provision and support

There is a growing recognition of the variation between local authorities in the proportions of children with SEN, the apparent composition of these groups, and the nature and quality of services provided to support them. Local area data collected on children with SEN, particularly the termly School Census and the annual SEN2 return by local authorities, show differences in the number of children with SEN, the nature of their recorded conditions and the Code of Practice level of support they are receiving. This variation was highlighted by the House of Commons Education and Skills Select Committee which commented on a ‘postcode lottery’ or a ‘lottery of provision’, and reports by the Audit Commission and Ofsted which also highlighted variation in provision and standards