Multidisciplinary Teamwork in Autism: Can One Size Fit All?

Multidisciplinary practice has become an accepted approach in many education and social and health care fields. In fact, the right to a multidisciplinary assessment is enshrined in the United Nations Convention of the Rights for Persons with Disabilities (United Nations, 2007). In order to avert a 'one size fits all' response to particularly heterogeneous diagnoses, such as autism spectrum disorders (ASD), the National Institute for Clinical Excellence (NICE) recommends multidisciplinary input. Yet, multidisciplinarity lacks empirical evidence of effectiveness, is fraught with conceptual difficulties and methodological incompatibilities, and therefore there is a danger of resorting to an ill-defined eclectic 'hodgepodge' of interventions. Virtually all evidence-based interventions in autism and intellectual disabilities are behaviourally based. Not surprisingly, therefore, professionals trained in behaviour analysis to international standards are increasingly becoming key personnel in multidisciplinary teams. In fact, professionals from a range of disciplines seek training in behaviour analysis. In this article we brought together a multidisciplinary group of professionals from education, health, and social care, most of whom have a dual qualification in an allied health, social care, or educational profession, as well as in behaviour anlaysis. Together we look at the initial training in these professions and explore how behaviour analysis can offer a common and coherent conceptual framework for true multidisciplinarity, based on sound scientific knowledge about behaviour, without resort to reifying theories. We illustrate how this unifying approach can enhance evidence-based multidisciplinary practice so that 'one size' will fit all. Copyright © Australian Psychological Society Ltd 2014.

(Re)-Introducing Themes of Religion and Spirituality to Professional Social Work Training in the Land of ‘Saints and Scholars’.

This chapter begins by alluding to Ireland’s historical reputation as the land of “Saints and Scholars” and then briefly charts its demise from this position. A parallel process in relation to religiously motivated provision of health and social care is outlined. The inclusion of themes of religion and spirituality within the current professional social work codes in the USA and Britain and the framework for social work training in Northern Ireland is noted. In this context the lack of any substantive inclusion of themes of religion and/or spirituality within the Bachelor of Social Work (BSW) degree at Queens University Belfast will be situated. A series of intersecting reasons for this lack of inclusion are proposed in terms of the experience of living through the recent troubled history of Northern Ireland and a variety of biases in academic thought.
A rationale for the re-introduction of inputs on religion and spirituality is articulated in terms of the widespread resurgence of these themes within health and social care and psychotherapy literature and the new emphasis on practicing in culturally sensitive ways in Britain. The first steps to re-introduce these themes under the higher context marker of “culturally competent practice” are described and an analysis of data from the students’ feedback presented along with illustrative quotations. The dissonance between the initial misgivings of staff and the overwhelmingly positive responses of students are highlighted. The chapter concludes with a discussion of lessons learned through the process with an emphasis on how the inclusion of these themes can result in better practice for service users, including those impacted by “the Troubles” in Northern Ireland.

Massive MIMO with Optimal Power and Training Duration Allocation

We consider the uplink of massive multicell multiple-input multiple-output systems, where the base stations (BSs), equipped with massive arrays, serve simultaneously several terminals in the same frequency band. We assume that the BS estimates the channel from uplink training, and then uses the maximum ratio combining technique to detect the signals transmitted from all terminals in its own cell. We propose an optimal resource allocation scheme which jointly selects the training duration, training signal power, and data signal power in order to maximize the sum spectral efficiency, for a given total energy budget spent in a coherence interval. Numerical results verify the benefits of the optimal resource allocation scheme. Furthermore, we show that more training signal power should be used at low signal-to-noise ratio (SNRs), and vice versa at high SNRs. Interestingly, for the entire SNR regime, the optimal training duration is equal to the number of terminals.