Evidence map›Paper›PMID 36927193›Full record

ArticleDisability and rehabilitation. Assistive technology2024

The BLV App Arcade: a new curated repository and evaluation rubric for mobile applications supporting blindness and low vision.

Bennett M Liu, Mahya Beheshti, Tahareh Naeimi, Zhigang Zhu, Rajesh Vedanthan, William Seiple, John-Ross Rizzo

Abstract read
In one paragraph

Article in Disability and rehabilitation. Assistive technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 97% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 4 institutions in 1 country.

Bennett M LiuDepartment of Rehabilitation Medicine, NYU Langone Health, New York, NY, USA.ORCID 0000-0001-8056-5033
Mahya BeheshtiDepartment of Rehabilitation Medicine, NYU Langone Health, New York, NY, USA.ORCID 0000-0001-5615-8542
Tahareh NaeimiDepartment of Rehabilitation Medicine, NYU Langone Health, New York, NY, USA.ORCID 0000-0002-2138-5793
Zhigang ZhuDepartment of Computer Science, The CUNY City College, New York, NY, USA.
Rajesh VedanthanDepartment of Population Health, NYU Langone Health, New York, NY, USA.ORCID 0000-0001-7138-2382
William SeipleLighthouse Guild, New York, NY, USA.ORCID 0000-0002-5750-650X
John-Ross RizzoDepartment of Rehabilitation Medicine, NYU Langone Health, New York, NY, USA.ORCID 0000-0002-4084-0085
NYU Langone Health · USCity College of New York · USLighthouse Guild · USThe Graduate Center, CUNY · US

Funding

VIS4ION-Thailand (Visually Impaired Smart Service System for Spatial Intelligence and Onboard Navigation) - Resub - 1R21EY033689 · NEI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI RIZZO, JOHN ROSS, VEDANTHAN, RAJESH · 2021 to 2022
$358k
NEI NIH HHS R21 EY033689
6 · The paper itself

Abstract

purposeVisual impairment-related disabilities have become increasingly pervasive. Current reports estimate a total of 36 million persons with blindness and 217 million persons with moderate to severe visual impairment worldwide. Assistive technologies (AT), including text-to-speech software, navigational/spatial guides, and object recognition tools have the capacity to improve the lives of people with blindness and low vision. However, access to such AT is constrained by high costs and implementation barriers. More recently, expansive growth in mobile computing has enabled many technologies to be translated into mobile applications. As a result, a marketplace of accessibility apps has become available, yet no framework exists to facilitate navigation of this voluminous space. MATERIALS AND

methodsWe developed the BLV (Blind and Low Vision) App Arcade: a fun, engaging, and searchable curated repository of app AT broken down into 11 categories spanning a wide variety of themes from entertainment to navigation. Additionally, a standardized evaluation metric was formalized to assess each app in five key dimensions: reputability, privacy, data sharing, effectiveness, and ease of use/accessibility. In this paper, we describe the methodological approaches, considerations, and metrics used to find, store and score mobile applications.

conclusionThe development of a comprehensive and standardized database of apps with a scoring rubric has the potential to increase access to reputable tools for the visually impaired community, especially for those in low- and middle-income demographics, who may have access to mobile devices but otherwise have limited access to more expensive technologies or services.

Indexed as

BlindnessMobile ApplicationsSelf-Help DevicesVision, LowHumansPersons with Visual Disabilitiesapplication evaluation metricdatabaselow-cost ATlow vision toolsmobile applicationsVisual impairment

Identifiers

PMID36927193
PMCPMC12862782
OpenAlexW4327575224

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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.