Publications

Purpose

Explicitly monitoring the need, use and satisfaction of assistive product (AP) provision is essential to support population health and healthy longevity in ageing/aged countries, like Korea. We present findings from the 2017 Korea National Disability Survey (NDS) on AP access and compare them to international averages, introducing Korea’s data into the wider coherence of global AP research.

Materials and methods

Using data from Korea’s 2017 NDS, surveying 91,405 individuals, we extracted and calculated AP access indicators, including needing, having, using and being satisfied with 76 unique APs, by functional difficulty and product type. We compared satisfaction and unmet need between the National Health Insurance System (NHIS) and alternative provision services.

Results

Prosthetics and orthotics had high rates of under-met need, and lower satisfaction rates, from 46.9% to 80.9%. Mobility APs overall had higher rates of under-met need. There was either low (<5%) or no reported need for most digital/technical APs. Among main products, those provided through the NHIS had lower unmet need (26.4%) than through alternative providers (63.1%), though satisfaction rates were similar (p < .001).

Conclusions

The Korean survey findings align with global averages calculated in the Global Report on Assistive Technology. Low reported needs for certain APs may reflect low awareness about how these products could benefit users, emphasizing the importance of data collection at each stage of the AP provision process. Recommendations to expand access to APs are given for people, personnel, provision, products, and policy.

Implications for rehabilitation

• Access to assistive products (APs) is an essential part of physical and occupational therapy services and rehabilitation. Monitoring population-level data on disability and AP access can inform policymakers about a key aspect of population health and healthy ageing, and demonstrate the need to expand access by including APs and associated services in primary/universal healthcare packages.
• Stratifying findings about AP access by type of functional difficulty and further by specific device helps identify the populations for whom needs are not being met. These domain-level and device-level indicators inform efforts to support specific groups within the population of people with disabilities, which has implications for how rehabilitation services are provisioned, targeted and made more accessible.

Jamie Danemayer & Myung-Joon Lim (2023)

Assistive technology in Korea: Findings from the 2017 National Disability Survey, Disability and Rehabilitation: Assistive Technology,

DOI: 10.1080/17483107.2023.2225565

Artificial Intelligence (AI) in Education has been said to have the potential for building more personalised curricula, as well as democratising education worldwide and creating a Renaissance of new ways of teaching and learning. Millions of students are already starting to benefit from the use of these technologies, but millions more around the world are not. If this trend continues, the first delivery of AI in Education could be greater educational inequality, along with a global misallocation of educational resources motivated by the current technological determinism narrative. In this paper, we focus on speculating and posing questions around the future of AI in Education, with the aim of starting the pressing conversation that would set the right foundations for the new generation of education that is permeated by technology. This paper starts by synthesising how AI might change how we learn and teach, focusing specifically on the case of personalised learning companions, and then move to discuss some socio-technical features that will be crucial for avoiding the perils of these AI systems worldwide (and perhaps ensuring their success). This paper also discusses the potential of using AI together with free, participatory and democratic resources, such as Wikipedia, Open Educational Resources and open-source tools. We also emphasise the need for collectively designing human-centered, transparent, interactive and collaborative AI-based algorithms that empower and give complete agency to stakeholders, as well as support new emerging pedagogies. Finally, we ask what would it take for this educational revolution to provide egalitarian and empowering access to education, beyond any political, cultural, language, geographical and learning ability barriers.

Disability stigma in many low- and middle-income countries represents one of the most pervasive barriers preventing people with disabilities from accessing equal rights and opportunities, including the uptake of available assistive technology (AT). Previous studies have rarely examined how disability stigma may be shaped through factors endemic to social interactions, including how the use of assistive technology itself may precipitate or alleviate disability stigma. Through two strands of work, we address this gap. Via a series of focus groups with Kenyans without disabilities (Study 1) and secondary data analysis of consultations with Kenyans with disabilities and their allies (Study 2), we identify shared and divergent understandings of what shapes disability stigma and discrimination. Specifically, Kenyans with and without disabilities were cognizant of how religious/spiritual interpretations of disability, conceptions of impairments as “different” from the norm, and social stereotypes about (dis)ability shaped the experience of stigma and discrimination. Moreover, both groups highlighted assistive technology as an influential factor that served to identify or “mark” someone as having a disability. However, whereas participants without disabilities saw assistive technology purely as an enabler to overcome stigma, participants with disabilities also noted that, in some cases, use of assistive technologies would attract stigma from others.

Barbareschi G, Carew MT, Johnson EA, Kopi N, Holloway C. “When They See a Wheelchair, They’ve Not Even Seen Me”—Factors Shaping the Experience of Disability Stigma and Discrimination in Kenya. International Journal of Environmental Research and Public Health. 2021; 18(8):4272. https://doi.org/10.3390/ijerph...

Johan Borg, Wei Zhang, Emma M. Smith & Cathy Holloway (2021) Introduction to the companion papers to the global report on assistive technology, Assistive Technology, 33:sup1, 1-2, DOI: 10.1080/10400435.2021.2003658

The supply of and market demand for assistive products (APs) are complex and influenced by diverse stakeholders. The methods used to collect AP population-level market data are similarly varied. In this paper, we review current population-level AP supply and demand estimation methods for five priority APs and provide recommendations for improving national and global AP market evaluation. Abstracts resulting from a systematic search were double-screened. Extracted data include WHO world region, publication year, age-groups, AP domain(s), study method, and individual assessment approach.497 records were identified. Vision-related APs comprised 65% (n = 321 studies) of the body of literature; hearing (n = 59), mobility (n = 24), cognitive (n = 2), and studies measuring multiple domains (n = 92) were proportionately underrepresented. To assess individual AP need, 4 unique approaches were identified among 392 abstracts; 45% (n = 177) used self-report and 84% (n = 334) used clinical evaluation. Study methods were categorized among 431 abstracts; Cross-sectional studies (n = 312, 72%) and secondary analyses of cross-sectional data (n = 61, 14%) were most common. Case studies illustrating all methods are provided. Employing approaches and methods in the contexts where they are most well-suited to generate standardized AP indicators will be critical to further develop comparable population-level research informing supply and demand, ultimately expanding sustainable access to APs.

Jamie Danemayer, Dorothy Boggs, Emma M. Smith, Vinicius Delgado Ramos, Linamara Rizzo Battistella, Cathy Holloway & Sarah Polack (2021) Measuring assistive technology supply and demand: A scoping review, Assistive Technology, 33:sup1, S35-S49, DOI: 10.1080/10400435.2021.1957039