Evidence map›Paper›PMID 39851816›Full record

ArticleBehavioral sciences (Basel, Switzerland)2024

Epitome of the Region-Regional Nostalgia Design Based on Digital Twins.

Liling Chen, Yicong Song, Xiaojing Niu, Xin Luan, Liu Yang, Shengfeng Qin

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2024. 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Liling ChenSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.
Yicong SongSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.
Xiaojing NiuSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.
Xin LuanSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.
Liu YangSchool of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China.
Shengfeng QinSmart Design Lab, School of Design, Northumbria University, Newcastle upon Tyne NE1 8ST, UK.ORCID 0000-0001-8538-8136

Funding

Key Project of Higher Education Research Foundation of Northwestern Polytechnical University No. GJJZ202301Key Research Project of Higher Education Teaching Reform of Shaanxi Provincial Education Department No. 21BZ009the Fundamental Research Funds for the Central Universities No. D5000220094
6 · The paper itself

Abstract

Nostalgic scenes can trigger nostalgia to a considerable extent and can be effectively used as a nostalgic trigger that contributes to the psychological comfort of the elderly and immigrant populations, but a design system has not been adequately studied. Therefore, the design principles and digital twin (DT) design system of nostalgic scenes is proposed in this study. It focuses on the construction of a nostalgic scene DT model based on the system of system (SoS) theory. Nostalgic scenes related to farm work are selected and photos of this DT model from a particular perspective are generated for presentation. Co-occurrence analysis is used to verify the correlation between elements within the scene. We invited two groups of residents in Xi'an, the regional group and the non-regional group, a total of 68 people, as participants to rate three photos with different degrees of design on the Likert scale. The results of data analysis show that systematic and well-composed nostalgic scene images, which incorporate relevant elements, are more likely to evoke participants' nostalgic emotions than ones without those elements mentioned above. Likewise, a series of nostalgic scene images spanning various periods can stimulate participants' nostalgic emotions more effectively than a single image. Furthermore, region-specific nostalgic scene images that resonate with participants sharing similar lifestyles can trigger their nostalgic feelings more effectively. The digital twin model of the nostalgia scene contains multi-source data, which can be dynamically visualised to represent regional nostalgic experiences. The design system can be used to design nostalgic scenes to improve emotional health, social bonding, tourism, and sustainable urban and rural development.

Indexed as

design for emotional wellbeingdigital twinnostalgia designregional public memoriesscene model

Identifiers

PMID39851816
PMCPMC11762173

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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.