Evidence map›Paper›PMID 41854890›Full record

ArticleHuman factors2026

Investigation of Redundant Visual Patterns to Improve Usability of Labels.

Yuval Bitan, Abed El Hamid Fahoum, Greg Fukakusa, Cynthia Valdron, Paul Milgram

Abstract read
In one paragraph

Article in Human factors, 2026. 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
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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.

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

5 authors.

Yuval BitanBen-Gurion University of the Negev, Israel.ORCID 0000-0001-7053-7012
Abed El Hamid FahoumBen-Gurion University of the Negev, Israel.
Greg FukakusaUniversity of Toronto, Canada.
Cynthia ValdronUniversity of Toronto, Canada.
Paul MilgramUniversity of Toronto, Canada.ORCID 0000-0001-7174-9498

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ObjectiveTo examine whether adding well designed visual patterns to labels can increase efficiency of searching for labelled items.BackgroundErrors of substitution can occur when selecting among similarly appearing items, especially under adverse conditions and time pressure.MethodTwo consecutive studies investigated effects of adding visual patterns to simulated labels in a visual search task. Both studies attempted to objectively design distinctive patterns, based on normative constraints. Study 1 compared response times and accuracy for target items comprising Text+Patterns, Text-Only, or Pattern-Only, involving searching for target items (based on working memory recollection) within an array of distractors. Study 2 additionally addressed memorability and spatial frequency content of patterns.ResultsStudy 1 indicated longer response times for simulated labels without patterns. No significant effects were found due to spatial frequency of patterns, nor to Pattern-Only versus Text+Patterns. Study 2 also showed longer response times and more errors for non-patterned labels. Weaker evidence was found to support improved performance for lower effective spatial bandwidth content of patterns.ConclusionsEvidence was found for decreased response times, and possibly fewer errors, when searching for target labels containing redundant information using potentially familiar visual patterns. The need exists for objective tools for normatively designing such patterns, potentially based on spatial frequency content.ApplicationsIn addition to label reading in general, medication labels may particularly benefit from adding patterned labels, to assist paramedics, pharmacists, nurses, anaesthesiologists, as well as lay consumers.

Indexed as

Pattern Recognition, VisualReaction TimeAdultFemaleHumansMaleYoung Adultdisplay designlabellingvisual patternsvisual search

Identifiers

PMID41854890
PMCPMC13260749

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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.