Evidence map›Paper›PMID 40417428›Full record

ArticleJournal of eye movement research2025

Natural or Human Landscape Beauty? Quantifying Aesthetic Experience at Longji Terraces Through Eye-Tracking.

Ting Zhang, Yue Jiang, Donghong Liu, Shijie Zeng, Pengjin Sheng

Abstract read
In one paragraph

Article in Journal of eye movement research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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.

Ting ZhangCollege of Tourism & Landscape Architecture, Guilin University of Technology, Guilin 541004, China; 15116612918@163.com (Y.J.); 13398493137@163.com (S.Z.); shengpengjin888@163.com (P.S.).ORCID https://orcid.org/0000-0001-8261-9947
Yue JiangCollege of Tourism & Landscape Architecture, Guilin University of Technology, Guilin 541004, China; 15116612918@163.com (Y.J.); 13398493137@163.com (S.Z.); shengpengjin888@163.com (P.S.).
Donghong LiuGuangxi Natural Resources Vocational and Technical College, Nanning 530000, China.
Shijie ZengCollege of Tourism & Landscape Architecture, Guilin University of Technology, Guilin 541004, China; 15116612918@163.com (Y.J.); 13398493137@163.com (S.Z.); shengpengjin888@163.com (P.S.).
Pengjin ShengCollege of Tourism & Landscape Architecture, Guilin University of Technology, Guilin 541004, China; 15116612918@163.com (Y.J.); 13398493137@163.com (S.Z.); shengpengjin888@163.com (P.S.).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigated tourists' visual perception, aesthetic experience, and behavioral intentions across four types of landscapes. A total of 353 questionnaires were distributed on-site, and the SOR model was used to examine the visual stimuli and aesthetic responses perceived by tourists, followed by laboratory eye-tracking to observe tourists' points of attention on the Longji Terraced Fields landscape Key findings reveal that different residences and revisiting conditions affect tourists' visual attention, with the most attention given at the intersections of landscape elements. Furthermore, although landscape visual stimuli do not significantly affect the intention response, eye movement parameters are positively correlated with aesthetic experience. The study contributes to understanding tourist aesthetic perception in terraced rice field landscapes and provides Chinese cases for the aesthetic appreciation of the terrace landscape.

Indexed as

aesthetic experienceeye movement experimentsLongji Terrace landscapeSOR modeling

Identifiers

PMID40417428
PMCPMC12101349

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.