The dollars and sense of restraints and seclusion.

The dollars and sense of restraints and seclusion

The role of immunotherapy in fusion-driven lung cancer

The role of immunotherapy in fusion-driven lung cance

The dollars and sense of restraints and seclusion.

Restraints and seclusion are a common practice in many human service settings despite the increasing evidence questioning their efficacy and appropriateness. There are many detrimental effects on people subject to these practices, such as falls, injury, psychological trauma and even death. In addition to the impact on people being served, there is also a range of negative effects on organisations and the workforce. This article outlines and discusses the costs to organisations in implementing restraints and seclusion, and the economic cost-benefits to be gained in working towards the safe elimination of restraints and seclusion. A brief outline of ethical alternatives to restraints and seclusion is explored. The emerging research evidence suggests that it is possible to achieve the safe elimination of restraints and seclusion in a human service organisation

Restrictive interventions for people with a disability exhibiting challenging behaviours : analysis of a population database

Background: People with an intellectual disability whose behaviours are perceived to be of serious harm to themselves or others are at risk of being subjected to restrictive interventions. Prevalence rates are difficult to determine, as most research is unable to draw on the results of population-level data.Method: The current study reports on the use of chemical and mechanical restraint and seclusion in the State of Victoria, Australia, over a 12-month period.Results: The majority of people included were subjected to chemical restraint. The use of restraint was found to be routine rather than a strategy of last resort. Consistent with findings in the UK and USA, those subjected to restrictive interventions were more likely to be young males with multiple disabilities, including autism.Conclusions: Systemic policy and procedural developments are needed to address current use of restrictive interventions, together with a longitudinal study to evaluate the effectiveness, of alternative, non-restrictive strategies.<br

Multi-attention graph neural networks for city-wide bus travel time estimation using limited data

Multi-attention graph neural networks for city-wide bus travel time estimation using limited dat

Multi-attention graph neural networks for city-wide bus travel time estimation using limited data

Multi-attention graph neural networks for city-wide bus travel time estimation using limited dat

Applying the CRPD to Safeguard the Rights of People with a Disability in Contact with the Criminal Justice System

Applying the CRPD to Safeguard the Rights of People with a Disability in Contact with the Criminal Justice Syste

Bus travel time prediction with real-time traffic information

© 2019 Elsevier Ltd An important aspect of Intelligent Public Transportation Systems (IPTS) is providing accurate travel time information. Knowing arrival times of public vehicles in advance can reduce waiting times of passengers and attract more people to take public transport. Existing approaches have two main limitations in the field of bus travel time prediction. First, influenced by increasingly complex real-time traffic factors and sparsity of real-time data, bus travel times can be difficult to predict accurately in modern cities. Second, bus dwelling and transit times are predominantly affected by different factors and hence have different patterns, but little research focuses on how to divide dwelling and transit areas and to build independent models for them. Consequently, we propose a novel segment-based approach to predict bus travel times using a combination of real-time taxi and bus datasets, that can automatically divide bus routes into dwelling and transit segments. Two models are built to predict them separately by incorporating different impact traffic factors. We evaluate our approach using real-world trajectory datasets, collected in Xi'an, China during June 2017. Compared to existing methods, the experimental results reveal that our approach improves the accuracy of bus travel time prediction, especially under abnormal traffic conditions

Multi-attention 3D residual neural network for origin-destination crowd flow prediction

To provide effective services for intelligent transportation systems (ITS), such as optimizing ride services and recommending trips, it is important to predict the distributions of passenger flows from various origins to destinations. However, existing crowd flow prediction models have not sufficiently addressed this problem, and most methods have only focused on in and out flows of individual regions. The main challenges of origin-destination (OD) crowd flow prediction are diverse flow patterns across city networks and data sparsity. To solve these problems, we propose a Multi Attention 3D Residual Network (MAThR) to predict city-wide OD crowd flows. In particular, we develop a multi-component 3D residual structure with a novel global self-attention mechanism to dynamically aggregate the OD spatial-temporal dependencies, by modeling three components: contextual information of the region, and long and short term periodic crowd flows. For each component, we design a tensor criss-cross self-attention block, which can simultaneously discover the global and local correlation of spatial (where), temporal (when) and contextual (which) information between all OD pairs. Evaluation on real-world crowd flow data demonstrates the advantages of our MAThR method on prediction accuracy, compared to other existing state-of-the-art methods

Factors influencing quality of behaviour support plans and the impact of plan quality on restrictive intervention use

Background: The quality and effectiveness of the support provided to people with disability who show challenging behaviour can be influenced by the design and content of their behaviour support plans (BSPs). This study examined some of the factors that might influence the quality of behaviour support plans and the impact of quality of BSPs on the use of restrictive intervention.Method: An audit of the quality of a sample of BSPs submitted to the Senior Practitioner in Victoria in the years 2009 and 2010 was conducted using the Behavior Support Plan Quality Evaluation, 2nd Edition (BSP-QE II).Results: Factors found to positively influence quality of BSPs included: involvement of behaviour consultants and involvement of clinicians from the Office of the Senior Practitioner (Office). Overall quality of plans was also negatively related to restrictive intervention use over time.Conclusions: The findings support the need for behaviour intervention and provision of clinical support. The findings also provide tentative support for the notion that the inclusion of evidence-based quality components into behaviour support plan formats may reduce the use of restrictive interventions.<br