Evidence map›Paper›PMID 30386682›Full record

ArticleTranslational vision science & technology2018

Improvement in Patient-Reported Quality of Life Outcomes in Severely Visually Impaired Individuals Using the Aira Assistive Technology System.

Brian J Nguyen, Yeji Kim, Kathryn Park, Allison J Chen, Scarlett Chen, Donald Van Fossan, Daniel L Chao

Open access · goldAbstract read
In one paragraph

Article in Translational vision science & technology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 30 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Iterative Design and Prototyping of Computer Vision Mediated Remote Sighted Assistance.ACM transactions on computer-human interaction : a publication of the Association for Computing Machinery · 2022
    Article
  7. Article
  8. Article
  9. Opportunities for Human-AI Collaboration in Remote Sighted Assistance.IUI. International Conference on Intelligent User Interfaces · 2022
    Article
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Brian J NguyenShiley Eye Institute, Department of Ophthalmology, University of California, San Diego, La Jolla, CA, USA.
Yeji KimShiley Eye Institute, Department of Ophthalmology, University of California, San Diego, La Jolla, CA, USA.
Kathryn ParkShiley Eye Institute, Department of Ophthalmology, University of California, San Diego, La Jolla, CA, USA.
Allison J ChenShiley Eye Institute, Department of Ophthalmology, University of California, San Diego, La Jolla, CA, USA.
Scarlett ChenShiley Eye Institute, Department of Ophthalmology, University of California, San Diego, La Jolla, CA, USA.
Donald Van FossanShiley Eye Institute, Department of Ophthalmology, University of California, San Diego, La Jolla, CA, USA.
Daniel L ChaoShiley Eye Institute, Department of Ophthalmology, University of California, San Diego, La Jolla, CA, USA.
University of California, San Diego · US

Funding

Ophthalmology and Visual Sciences Career Development K12 ProgramK12EY024225 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI WEINREB, ROBERT N · 2015 to 2025
$4.3M
NEI NIH HHS K12 EY024225
6 · The paper itself

Abstract

purposeWe evaluate patient-reported quality of life outcomes in severely visually impaired (SVI) individuals using the Aira system, an on demand assistive wearable technology.

methodsAira is an on-demand assistive wearable technology designed for the severely visually impaired (visual acuity of better eye <20/200). The user wears glasses with a video camera mounted that, when activated, livestreams to a human agent who assists the user in the specified task. Aira subscribers were recruited consecutively and administered the 28-item Impact of Vision Impairment-Very Low Vision (IVI-VLV) Questionnaire, a previously validated survey for vision-related quality of life specifically for low vision individuals. The questionnaire was administered by phone before starting Aira and at 3-month follow-up. Total score as well as validated subset scores of activities of daily living, mobility and safety (ADLMS) and emotional wellbeing (EWB) were assessed.

resultsA total of 69 participants (mean age, 52.1; 35 female, 34 male) were recruited with a mean of 108 (SD = 19.7) days to follow-up. Mean total minutes used over the interval were 334.1 (SD = 318.5). Initial total score (mean 51.7 ± 18.6) significantly improved at follow-up (mean 62.2 ± 15.0;

conclusionsIn this exploratory study, regardless of minutes used, the use of Aira significantly improves IVI-VLV total score and ADLMS and EWB subscores for SVI individuals. This improvement is not correlated with total minutes used. TRANSLATIONAL RELEVANCE: The Aira assistive technology system may provide improvement in quality of life for low vision patients and is worthy of further study to assess the use of this technology to assist SVI patients.

Indexed as

adaptive technologysevere vision impairmentwearable technology

Identifiers

PMID30386682
PMCPMC6205681
OpenAlexW2899065054

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.