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Assistive technology access in longitudinal datasets: a global review

Functional limitations become more prevalent as populations age, emphasising an increasingly urgent need for assistive technology (AT). Critical to meeting this need trajectory is understanding AT access in older ages. Yet few publications examine this from a longitudinal perspective. This review ai...

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Autores principales: Danemayer, Jamie, Mitra, Sophie, Holloway, Cathy, Hussein, Shereen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Swansea University 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10448602/
https://www.ncbi.nlm.nih.gov/pubmed/37636834
http://dx.doi.org/10.23889/ijpds.v8i1.1901
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author Danemayer, Jamie
Mitra, Sophie
Holloway, Cathy
Hussein, Shereen
author_facet Danemayer, Jamie
Mitra, Sophie
Holloway, Cathy
Hussein, Shereen
author_sort Danemayer, Jamie
collection PubMed
description Functional limitations become more prevalent as populations age, emphasising an increasingly urgent need for assistive technology (AT). Critical to meeting this need trajectory is understanding AT access in older ages. Yet few publications examine this from a longitudinal perspective. This review aims to identify and collate what data exist globally, seeking all population-based cohorts and repeated cross-sectional surveys through the Maelstrom Research Catalogue (searched May 10, 2022) and the Disability Data Report (published 2022), respectively. Datasets incorporating functional limitations modules and question(s) dedicated to AT, with a wave of data collection since 2009, were included. Of 81 cohorts and 202 surveys identified, 47 and 62 meet inclusion criteria, respectively. Over 40% of cohorts were drawn from high-income countries which have already experienced significant population ageing. Cohorts often exclude participants based on pre-existing support needs. For surveys, Africa is the most represented region (40%). Globally, 73% of waves were conducted since 2016. ’Use’ is the most collected AT access indicator (69% of cohorts and 85% of surveys). Glasses (78%) and hearing aids (77%) are the most represented AT. While gaps in data coverage and representation are significant, collating existing datasets highlights current opportunities for analyses and methods for improving data collection across the sector.
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spelling pubmed-104486022023-08-25 Assistive technology access in longitudinal datasets: a global review Danemayer, Jamie Mitra, Sophie Holloway, Cathy Hussein, Shereen Int J Popul Data Sci Population Data Science Functional limitations become more prevalent as populations age, emphasising an increasingly urgent need for assistive technology (AT). Critical to meeting this need trajectory is understanding AT access in older ages. Yet few publications examine this from a longitudinal perspective. This review aims to identify and collate what data exist globally, seeking all population-based cohorts and repeated cross-sectional surveys through the Maelstrom Research Catalogue (searched May 10, 2022) and the Disability Data Report (published 2022), respectively. Datasets incorporating functional limitations modules and question(s) dedicated to AT, with a wave of data collection since 2009, were included. Of 81 cohorts and 202 surveys identified, 47 and 62 meet inclusion criteria, respectively. Over 40% of cohorts were drawn from high-income countries which have already experienced significant population ageing. Cohorts often exclude participants based on pre-existing support needs. For surveys, Africa is the most represented region (40%). Globally, 73% of waves were conducted since 2016. ’Use’ is the most collected AT access indicator (69% of cohorts and 85% of surveys). Glasses (78%) and hearing aids (77%) are the most represented AT. While gaps in data coverage and representation are significant, collating existing datasets highlights current opportunities for analyses and methods for improving data collection across the sector. Swansea University 2023-03-16 /pmc/articles/PMC10448602/ /pubmed/37636834 http://dx.doi.org/10.23889/ijpds.v8i1.1901 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
spellingShingle Population Data Science
Danemayer, Jamie
Mitra, Sophie
Holloway, Cathy
Hussein, Shereen
Assistive technology access in longitudinal datasets: a global review
title Assistive technology access in longitudinal datasets: a global review
title_full Assistive technology access in longitudinal datasets: a global review
title_fullStr Assistive technology access in longitudinal datasets: a global review
title_full_unstemmed Assistive technology access in longitudinal datasets: a global review
title_short Assistive technology access in longitudinal datasets: a global review
title_sort assistive technology access in longitudinal datasets: a global review
topic Population Data Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10448602/
https://www.ncbi.nlm.nih.gov/pubmed/37636834
http://dx.doi.org/10.23889/ijpds.v8i1.1901
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