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The extent to which mobile applications support independence among the visually impaired - a pilot study.

Milla Emilia JärveläAura Aino Kaarina FalckMira Maaret RajalaHelvi Aulikki KyngäsHeidi Johanna Siira
Published in: Disability and rehabilitation. Assistive technology (2020)
Background and aim: Visual impairment (VI) problems are increasing as the global aging population grows. Mobile devices have become essential to interacting with friends and society. Because the visually impaired are no exception, it would be useful to determine the functionalities that best support the independence of people with VI. The currently available functionalities and applications were analysed to provide insight about which features the visually impaired value most.Materials and methods: A Webropol survey with structured and open-ended questions was carried out. The participants (n = 26) were asked about their use of mobile applications and opinions regarding the usefulness of certain applications in promoting independent functioning. An instrument was developed for this study based on previous literature, and its quality was assured through an expert panel evaluation and pre-testing. The collected data were analysed statistically and by inductive content analysis.Results: A majority of the participants were active users of mobile devices. Substantial variation was observed in the evaluations of how useful various applications are to different everyday tasks. The participants suggested numerous improvements, such as additional customization, to the current mobile devices and applications.Implications for RehabilitationPeople with VI benefit from the use of mobile devices in the same way that the population with normal vision does, and mobile devices and applications can be pivotal to supporting their independence.The participants offered innovative ideas and suggestions for how mobile devices and applications could be designed to better meet the needs of the visually impaired.
Keyphrases
  • systematic review
  • machine learning
  • minimally invasive
  • working memory
  • electronic health record
  • big data
  • deep learning
  • artificial intelligence