ArticleTranslational vision science & technology2025
Performance on Activities of Daily Living and User Experience When Using Artificial Intelligence by Individuals With Vision Impairment.
Article in Translational vision science & technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Article
- Advances in Technology-Assisted Visual Rehabilitation Therapies: Scoping Review.Journal of medical systems · 2026Article
- The Evolving Landscape of Vision Rehabilitation: Current Status and Future Directions.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026Review
- AI-Enabled Smart Glasses for Active Aging: Scoping Review.JMIR aging · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: This study assessed objective performance, usability, and acceptance of artificial intelligence (AI) by people with vision impairment. The goal was to provide evidence-based data to enhance technology selection for people with vision loss (PVL) based on their loss and needs. Methods: Using a cross-sectional, counterbalanced, cross-over study involving 25 PVL, we compared performance using two smart glasses (OrCam and Envision Glasses) and two AI apps (Seeing AI and Google Lookout). We refer to these as assistive artificial intelligence implementations (AAIIs). Completion and timing were quantified for three task categories: text, text in columns, and searching and identifying. Usability was evaluated with the System Usability Scale (SUS). Results: The odds ratios (ORs) of being able to complete Text tasks were significantly higher when using AAIIs compared to the baseline. OR when performing "Searching and Identifying" tasks varied among AAIIs, with Seeing AI and Envision improving the performance of more tasks than Lookout or OrCam. Participants expressed high satisfaction with the AAIIs. Conclusions: Despite the findings that performance on some tasks and when using some AAIIs did not result in a greater number of PVL being able to complete the tasks, there was overall high satisfaction, reflecting an acceptance of AI as an assistive technology and the promise of this developing technology. Translational Relevance: This evidence-based performance data provide guidelines for clinicians when recommending an AAII to PVL.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.