Assessment, Intervention, and Training Needs of Service Providers for Children with Intellectual Disabilities or Autism Spectrum Disorders and Concurrent Problem Behaviours

This study documented the perceived needs of therapists, specialists, and managers who work with children with intellectual disabilities (ID) and/or autism spectrum disorders (ASD) and concurrent problem behaviours (PBs). Seventy-five respondents from specialized PB and early childhood programs within eight public rehabilitation centres were surveyed. They were asked to describe current practices and perceived needs in terms of assessment, intervention, and training with respect to the target population. Overall, the perceptions of staff were consistent with the results of previous studies examining families’ perspectives. Salient themes include the need for specialized assessments for PBs in young children, collaboration between multiple service providers and families, and additional staff training in child development and interventions for PBs. These findings underscore the importance of offering diversified services adapted to the needs of children with PBs, their families, and their service providers

Using interactive web training to teach parents to select function-based interventions for challenging behaviour : a preliminary study

Background: Children with developmental disability often engage in challenging behaviour, which may require that parents implement behavioural assessments and interventions. The purpose of our pilot study was to examine the effects of an interactive web training (IWT) to teach behavioural function identification and intervention selection to parents. Method: Twenty-six parents of children with developmental disability responded to function identification and intervention selection tasks on clinical vignettes before and following IWT. We also measured social validity and the duration of training. Results: Our results show that parents were more accurate in the identification of behavioural function and selected more adequate interventions following IWT. On average, parents spent less than 2.5hr to complete IWT and rated it positively. Conclusions: The IWT appears to be a viable tool to teach parents about function-based intervention, but additional research is needed to examine whether it translates to changes in parental practices and child behaviour

A comparison of video-based interventions to Ttach data entry to adults with intellectual disabilities : a replication and extension

Researchers have demonstrated that video-based interventions are effective at teaching a variety of skills to individuals with intellectual disabilities. To replicate and extend this line of research, we initially planned to compare the effects of video modeling and video prompting on the acquisition of a novel work skill (i.e., data entry) in two adults with moderate intellectual disabilities using an alternating treatment design. When both interventions failed to improve performance, the instructors sequentially introduced a least-to-most instructor-delivered prompting procedure. The results indicated that the introduction of instructor prompts considerably increased correct responding in one participant during video modeling and in both participants during video prompting. Overall, the study suggests that practitioners should consider incorporating instructor-delivered prompts from the onset, or at least when no improvements in performance are observed, when using video-based interventions to teach new work skills to individuals with intellectual disabilities

Active user blind detection through deep learning

International audienceActive user detection is a standard problem that concerns many applications using random access channels in cellular or ad hoc networks. Despite being known for a long time, such a detection problem is complex, and standard algorithms for blind detection have to trade between high computational complexity and detection error probability. Traditional algorithms rely on various theoretical frameworks, including compressive sensing and bayesian detection, and lead to iterative algorithms, e.g. orthogonal matching pursuit (OMP). However, none of these algorithms have been proven to achieve optimal performance. This paper proposes a deep learning based algorithm (NN-MAP) able to improve on the performance of state-of-the-art algorithm while reducing detection time, with a codebook known at training time