Leveraging AI and customer reviews to evaluate technology used by people with disabilities.
Background: Mainstream and assistive technologies play a critical role in enhancing the independence and quality of life for people with disabilities. However, selecting appropriate technology for specific patients requires AT practitioners to navigate a vast number of available products. This study...
| Publicado en: | Disability & Rehabilitation: Assistive Technology Vol. 20; no. 6; pp. 1668 - 1677 |
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| Autores principales: | , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Aug2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=187408881&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 187408881 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 17483107 1X04 jtl: Disability & Rehabilitation: Assistive Technology issn: 17483107 maglogo: Y pubinfo: dt: Aug2025 vid: 20 iid: 6 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 187408881 183049322 187408881 187408881 10.1080/17483107.2025.2465603 187408881 ppf: 1668 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Leveraging AI and customer reviews to evaluate technology used by people with disabilities. aug: au: Allen, Taylor Horwitz, Ari Sprigle, Stephen affil: Rehabilitation Engineering and Applied Research Lab, Georgia Institute of Technology, Atlanta, Georgia, USA sug: subj: Artificial Intelligence, Generative Utilization Assistive Technology Evaluation Persons with Disabilities Psychosocial Factors Consumer Attitudes Natural Language Processing Utilization Product Evaluation Health Personnel Information Technology Evaluation Human Functional Status Sociodemographic Factors Equipment Design Funding Source Ergonomics Comfort Software Descriptive Statistics Male Female Male Female ab: Background: Mainstream and assistive technologies play a critical role in enhancing the independence and quality of life for people with disabilities. However, selecting appropriate technology for specific patients requires AT practitioners to navigate a vast number of available products. This study investigates the application of large language models (LLMs) to assist AT practitioners in identifying valuable product insights and informing technology recommendations. Methods: Keplo, an AI-driven customer review analysis platform, was utilized to evaluate six product categories: three mainstream products and three assistive technologies. Using Amazon product reviews, Keplo's initial analysis provides key product information including user demographics, usage patterns, strengths, weaknesses, and potential design improvements. This initial report was subsequently input into a custom GPT, developed by Keplo, to further extract valuable data. Results: After applying prompt engineering, the GPT generated design considerations, product comparisons, and tailored suggestions for individuals with certain functional limitations, offering AT practitioners a detailed and comprehensive guide for product recommendations. Conclusion: These findings demonstrate that LLMs can effectively identify and extract product insights from customer reviews, streamlining the process of prescribing products for individuals with disabilities. The results also reflect limitations of LLM analysis and the need for AT Practitioners to critically review customer reviews for applicability to their clients. IMPLICATIONS FOR REHABILITATION: The study demonstrates that Large Language Models (LLMs) can effectively analyze customer reviews and provide valuable product insights for both mainstream and assistive technology. By leveraging the tools employed in this article, clinicians can extract detailed information about the strengths, weaknesses, and usability of a cohort of products. This improves the prescription of effective technology for patients with a wide range of functional limitations. The product insights identified through this approach can also inform future improvements in assistive technology product design, ensuring that devices are more user-friendly and suitable for people with disabilities. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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