Article

A commentary on influences on selection of assistive technology for young children in South Africa: perspectives from rehabilitation professionals

Authors:
  • David Banes Access and Inclusion Services
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Abstract

This commentary explores the issues raised in the original article and seeks to suggest how the systems and processes that the professionals utilize shape the challenges and issues they face. Furthermore, it asks the question as to the extent to which self-determination in the selection of many forms of assistive technology would address and resolve the barriers identified. • IMPLICATIONS FOR REHABILITATION • The implications of the study and experiences of the professionals are highly relevant for the planning of future rehabilitation services. With increasing global demand for service, and an associated understanding that the client carries significant knowledge and experience it could be suggested that the underlying client/provider relationship is changing and will continue to change. • There is potential for a shift from community-based rehabilitation services, to community led rehabilitation services, where the self-determination of solutions to need is led by the individual, with curated input from the professional, mediated through machine learning and artificial intelligence. Such a model of delivery could effectively support many of those with a disability, where the client has extensive experience, allowing the professional to spend increased resources on those who lack the experience to engage confidently in decision making. • The recognition and validation of the knowledge held by clients, against which options can be mapped could ensure extended reach and reduce the cost and efficiency of future services.

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... For this reason, it is important to see the role of the professional as joining the AT user on their journey. Most AT Process models are focused on the actions of the system and professionals that support the supply and use of AT (Banes, 2019). ...
... For this reason, it is important to see the role of the professional as joining the AT user on their journey. Most AT Process models are focused on the actions of the system and professionals that support the supply and use of AT (Banes, 2019). ...
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... Fragmentation of knowledge and information, inconsistency in assessment methodology and heterogeneity in the competence of assistive technology professionals, has led to a growing interest in the opportunities that data sciences, including AI, hold for the future of the assistive technology sector, as a supportive and constructive mechanism in any decision-making process [14]. ...
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Introduction The impact of assistive technology use on the lives of people with disabilities has long been demonstrated in the literature. Despite the need for assistive technologies, and a wealth of innovative, afford-able, and accessible products, a low rate of assistive technology uptake is globally maintained. One of the reasons for this gap is related to data and knowledge formation and management. Low access to information and a lack of assessment services is evident. Fragmentation of data, inconsistency in assessment methodology and heterogeneity in the competence of assistive technology professionals, has led to a growing interest in the opportunities that data sciences, including AI, hold for the future of the assistive technology sector, as a supportive and constructive mechanism in any decision-making process. Objectives In this short paper, we seek to describe some of the principles that such an AI-based recommendation system should be built upon, using the Atvisor platform as a case study. Atvisor.ai is an AI-based digital platform that supports assistive technology assessments and the decision-making process. Recommendations Our recommendations represent the aggregated insights from two pilots held in Israel, testing the platform in multiple environments and with different stakeholders. These recommendations include ensuring the continuum of care and providing a full user journey, incorporating shared decision making and self-assessment features, providing data personalisation and a holistic approach, building a market network infrastructure and designing the tool within a wider service delivery model design. Assessment and decision-making processes, crucial to optimal uptake, cab be leveraged by technology to become more accessible and personalised. • IMPLICATIONS FOR REHABILITATION • Provides principles for the development of an AI-based recommendation system for assistive technology decision making. • Promotes the use of artificial intelligence to support users and professionals in the assistive technology decision making process. • Personalization of data regarding assistive technology, according to functional, holistic and client centered profiles of users, ensures optimal match and better use of assistive technology. • Self-assessment and professional assessment components are important for enabling multiple access points to the assistive technology decision making process, based on the preferences and needs of users.
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