Video-based Simulations: Considerations for Teaching Students with Developmental Disabilities

The use of video-based multimedia simulations for teaching functional skills to persons with developmental disabilities remains an unexplored application of technology for this group. This article examines the historical literature in this area, and discusses future considerations, design issues, and implications of using multimedia simulations. Implementation issues are presented, and suggestions regarding design, development, and application of multimedia simulations are offered. Considerations address the importance of appropriate role modeling and the combination of video-based simulation and in vivo training to foster generalization and maintenance in the context of transition to the real world.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Development and Validation of the Minnesota Borderline Personality Disorder Scale

Although large epidemiological data sets can inform research on the etiology and development of borderline personality disorder (BPD), they rarely include BPD measures. In some cases, however, proxy measures can be constructed using instruments already in these data sets. In this study, the authors developed and validated a self-report measure of BPD from the Multidimensional Personality Questionnaire (MPQ). Items for the new instrument—the Minnesota BPD scale (MBPD) —were identified and refined using three large samples: undergraduates, community adolescent twins, and urban substance users. The authors determined the construct validity of the MBPD scale by examining its association with (a) diagnosed BPD, (b) questionnaire-reported BPD symptoms, and (c) clinical variables associated with BPD: suicidality, trauma, disinhibition, internalizing distress, and substance use. The authors also tested the MBPD scale in two prison inmate samples. Across samples, the MBPD scores correlated with BPD indices and external criteria and showed incremental validity above measures of negative affect, thus supporting its construct validity as a measure of BPD

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes <sup>1</sup> . Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel <sup>2</sup> ) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries