Investigation of Redundant Visual Patterns to Improve Usability of Labels
Yuval Bitan et al.
What the paper says
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.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.