Bell, D;
Layton, N;
Smith, RO;
Scherer, MJ;
Smith, EM;
(2024)
Developing a Holistic Process to Measure Assistive Technology Outcomes.
Assistive Technology Outcomes and Benefits
, 18
pp. 1-19.
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Abstract
Assistive Technology Outcomes and Benefits | Looking Back and Moving Forward: 20 Years of ATOB Assistive technology (AT) outcomes research sits across different fields of practice and uses, diverse measures and methodologies. Instruments have been developed to measure AT outcomes, but data are not routinely collected nor published in most settings. This impedes the evaluation and development of policy in 1 the field and prevents the sharing of best practices across settings and countries. Aiming to summarize existing knowledge about assistive technology outcomes and propose directions for the future, we provide a broad narrative synthesis of existing literature about AT outcomes conceptualized through the people-centered 5P model of the WHO Global Cooperation on Assistive Technology initiative and the GAATO Assistive Technology Outcomes and Impacts Model. We conclude that the 5P system model operates as a viable, integrative framework which supports a holistic understanding of the challenges associated with measuring AT outcomes. The development of a process to measure AT outcomes is proposed.
Type: | Article |
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Title: | Developing a Holistic Process to Measure Assistive Technology Outcomes |
Open access status: | An open access version is available from UCL Discovery |
Publisher version: | https://www.atia.org/atobcurrentvolume/ |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | assistive technology, outcomes, 5P model, measurement |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10194303 |
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