Evidence map›Paper›PMID 41696707›Full record

ArticleFrontiers in public health2025

Assessing the impact of waterfront trail aesthetics on psychological restoration in urban environments: a deep learning and random forest approach.

Yongshu Wu, Yuhan Wang, Juan Wang, Junyi Li, Yinghong Ding, Yaqin Ding, Yuxuan Wu, Zhipeng Zhu, Xiaoling Xu

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. 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
–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

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

9 authors.

Yongshu WuCollege of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou, China.
Yuhan WangCollege of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou, China.
Juan WangCollege of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou, China.
Junyi LiCollege of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou, China.
Yinghong DingCollege of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou, China.
Yaqin DingCollege of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou, China.
Yuxuan WuCollege of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou, China.
Zhipeng ZhuCollege of Architecture and Planning, Fujian University of Technology, Fuzhou, China.
Xiaoling XuCollege of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urban waterfront trails can promote psychological restoration, yet how specific landscape attributes shape scenic beauty and multidimensional restorative perception across different revetment types remains unclear. This study quantified 15 landscape variables (F1-F15) across 30 urban waterfront trail sites and examined their associations with scenic beauty estimation (SBE) and four restorative dimensions (emotional, cognitive, physiological, and behavioral). Spearman correlation analysis, non-parametric group comparisons, and Random Forest modeling were applied to identify key predictors, with variable importance interpreted as predictive contributions rather than causal mechanisms. Partial-mediation structural equation models (SEM) were then constructed for the overall sample and for artificial, mixed, and natural revetment types. Results indicated that F4 was the most influential predictor of SBE, followed by F7, F13, F2, and F5. SEM analyses showed that SBE functioned as a central mediator linking landscape attributes to restorative outcomes: F4 was positively associated with SBE (

Indexed as

Deep LearningEstheticsCitiesHumansRandom Forestaesthetic preferencepsychological restorationrandom Forest analysissemantic segmentationwaterfront trails

Identifiers

PMID41696707
PMCPMC12901393

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.