ArticleOptometry and vision science : official publication of the American Academy of Optometry2020
The Mind Cannot Go Blind: Effects of Central Vision Loss on Judging One's Crossing Time.
Article in Optometry and vision science : official publication of the American Academy of Optometry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled 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.
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
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Topical Review: Impact of Central Vision Loss on Navigation and Obstacle Avoidance while Walking.Optometry and vision science : official publication of the American Academy of Optometry · 2022Pooled it
- Article
- Gaze Scanning at Street Crossings by Pedestrians With Homonymous Hemianopia With and Without Hemispatial Neglect.Investigative ophthalmology & visual science · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
significanceThis study explored whether people with AMD can accurately judge the time they need to cross the street. The results suggest that AMD-related vision loss does not affect a person's ability to estimate his/her own street-crossing time, whereas familiarity with the street does. PURPOSE: The purpose of this study was to assess whether people with AMD could judge accurately their street-crossing time.
methodsFifty-one AMD subjects and 47 age-matched normally sighted subjects (controls) estimated their time to cross a single-lane, one-way street four times (pre-estimate). Then, subjects actually crossed the street four times and subsequently estimated their crossing time four additional times (post-estimate). A linear mixed model with repeated measures for subject was used to determine if the ratio between subjects' estimated and actual crossing times changed as a function of subject group (AMD vs. control) and whether estimates changed before and after actually crossing the street. Univariate correlations and multiple regression analyses were also performed to determine which of the measured experimental variables were the best predictors of a subject's ability to estimate his/her crossing time.
resultsNo significant difference in crossing ratios were found between the AMD (average, 1.05) and control (average, 1.16) subjects (P = .11). This was true for both the pre-crossing (AMD, 1.09; controls, 1.23; P = .11) and post-crossing ratios (AMD, 1.01; controls, 1.09; P = .17). Both subject groups' crossing ratios, however, decreased significantly going from pre to post (P < .0001). Increased age, longer actual crossing time, and experience gained from previously crossing the street resulted in less overestimation of one's crossing time.
conclusionsOur data suggest that familiarity with the street as opposed to central vision loss from AMD affects a person's ability to estimate his/her crossing time.
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.