Evidence map›Paper›PMID 42352746›Full record

ArticleBehavioral sciences (Basel, Switzerland)2026

Sweet Round, Spicy Sharp: How Chinese Typeface Features Trick the Tongue into Tasting Five Flavors.

Chunfa Sha, Yunxiao Zhang, Qi Zhong, Haojing Guo, Rong Han

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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.

Chunfa ShaDepartment of Industrial Design, Jiangsu University, Zhenjiang 212000, China.ORCID 0000-0001-7652-8723
Yunxiao ZhangDepartment of Industrial Design, Jiangsu University, Zhenjiang 212000, China.ORCID 0009-0008-2703-9323
Qi ZhongDepartment of Industrial Design, Jiangsu University, Zhenjiang 212000, China.ORCID 0000-0001-8426-318X
Haojing GuoDepartment of Design, North Carolina State University, Raleigh, NC 27606, USA.
Rong HanDepartment of Industrial Design, Jiangsu University, Zhenjiang 212000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cross-modal correspondence, a cross-sensory cognitive phenomenon, reveals the link between visual forms and taste experiences. Although research on Western alphabetic typography is extensive, the Chinese character system has received less attention. This study systematically examines Chinese typeface categories (Song, Hei, Yuan, and Calligraphic) and stroke thickness (bold, medium, thin) in a real packaging context. The effects on the expectancies of the five flavors-sour, sweet, bitter, spicy, and salty-were measured. The results showed a significant interaction effect between typeface category and stroke thickness for all five flavor dimensions. The rounded Yuan typeface with thin strokes tended toward sweetness. Bold Song typefaces tend toward bitterness or spiciness, while bold Hei typefaces tend toward saltiness. The Calligraphic typeface, with its complex visual features, is strongly associated with bitterness and spiciness only when paired with bold strokes. Sourness shows a reverse modulation pattern. These findings reveal that the visual features of Chinese typefaces shape gustatory crossmodal correspondences through interactive modulation rather than simple linear addition. This confirms the common cross-modal perceptual pattern of 'curvature-sweetness, angularity-non-sweetness' across Chinese and English writing systems while also reflecting the culturally specific patterns driven by Chinese typographic features (such as the bifeng structure at stroke terminals) and the unique phenomenon of cross-modal correspondence with spiciness. This provides an empirically grounded and culturally adaptive reference for the marketing application of Chinese typefaces in packaging contexts.

Indexed as

Chinese typographycross-modal correspondencefood packagingtaste expectancy

Identifiers

PMID42352746
PMCPMC13295811

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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.