Evidence map›Paper›PMID 36981662›Full record

ArticleInternational journal of environmental research and public health2023

How Do Repeated Viewings in Forest Landscapes Influence Young People's Visual Behaviors and Cognitive Evaluations?

Mengyun Wu, Yu Gao, Zhi Zhang, Bo Zhang, Huan Meng, Weikang Zhang, Tong Zhang

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Article in International journal of environmental research and public health, 2023. 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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5 · Who and what money

Authors and funding

7 authors.

Mengyun WuLandscape Planning Laboratory, Forestry College, Shenyang Agricultural University, Shenyang 110161, China.
Yu GaoLandscape Planning Laboratory, Forestry College, Shenyang Agricultural University, Shenyang 110161, China.
Zhi ZhangLandscape Planning Laboratory, Forestry College, Shenyang Agricultural University, Shenyang 110161, China.
Bo ZhangShenyang Construction Engineering Project Management Center Co., Ltd., Shenyang 110032, China.
Huan MengLandscape Planning Laboratory, Forestry College, Shenyang Agricultural University, Shenyang 110161, China.
Weikang ZhangLandscape Planning Laboratory, Forestry College, Shenyang Agricultural University, Shenyang 110161, China.ORCID 0000-0001-7269-3393
Tong ZhangLandscape Planning Laboratory, Forestry College, Shenyang Agricultural University, Shenyang 110161, China.ORCID 0000-0003-0673-0111

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the spread of the COVID-19 epidemic, it has gradually become normal to periodically visit and enjoy forest landscape resources in the suburbs of cities. For designers and managers of forest landscapes, exploring change in the visual behaviors and cognitive evaluations of people who repeatedly view forest landscapes and the characteristics of this change will aid the design and sustainable utilization of forest landscape resources in the suburbs of cities. PURPOSE: From the perspective of users' preferences for forest landscape space, this study explored the changes in visual behavior characteristics and psychological preference characteristics for individuals who repeatedly view forest landscapes and their drivers under different preferences.

methodsThis study collected data from 52 graduate and undergraduate students. We used a difference test to compare the differences in the visual behavior coincidence degree and the changes in psychological evaluations; a descriptive statistical analysis to explore young peoples' likes and dislikes of landscape elements; and Spearman correlation analysis to explore the correlation between the psychological evaluations and visual behaviors. MAIN

results1. At the second viewing, the participants' regression behavior tended to decrease for various spaces, and they were more inclined to view areas that they had not viewed before. In addition, at the second viewing, the degree of fixation behavior coincidence was generally low, and there were obvious differences across spaces; 2. The participants' feature evaluations and comprehensive evaluations for landscapes did not change significantly with their increased familiarity with the spaces; 3. There was a significant positive correlation between the participants' psychological evaluations of landscape stimuli and the degree of fixation coincidence when viewing the spaces, among which the rate of distant clarity and the degree of fixation behavior coincidence were significantly and positively correlated. Meanwhile, at the second viewing, the number of favorite elements in the lookout space, which belongs to high-preference spaces, noticeably increased.

Indexed as

COVID-19AdolescentCitiesCognitionEmotionsForestsHumanscross-recurrence analysisforest environmentpsychological evaluationrepeated viewingsvisual behavior

Identifiers

PMID36981662
PMCPMC10048908

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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.