Evidence map›Paper›PMID 39841733›Full record

ArticlePloS one2025

How telepresence and perceived enjoyment mediate the relationship between interaction quality and continuance intention: Evidence from China Zisha-ware Digital Museum.

Mengjie Shi, Liyuan Deng, Mingshan Zhang, Yanghuan Long

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

4 authors.

Mengjie ShiSchool of Design, Jiangnan University, Wuxi, China.
Liyuan DengSchool of Design, Jiangnan University, Wuxi, China.
Mingshan ZhangSchool of Design, Jiangnan University, Wuxi, China.ORCID 0009-0000-7544-2709
Yanghuan LongCollege of Art & Design, Nanjing Forestry University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid development of digital technologies and the diversification of user needs have made digital museums significant platforms for cultural dissemination and education, attracting unprecedented attention. This study aims to investigate how interaction quality influences users' psychological responses and their continuance intention to use digital museums. By integrating the Stimulus-Organism-Response (S-O-R) model and telepresence theory, this study proposes a novel model to examine users' continuance intention. A questionnaire survey of visitors to the China Zisha-ware Digital Museum (CZDM) yielded 414 valid responses, which were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that: 1) The interaction quality of digital museums (i.e., interactivity, vividness, and authenticity) and users' psychological responses (i.e., telepresence, perceived enjoyment) significantly affect users' continuance intention to varying degrees. 2) Telepresence significantly mediates the relationship between interaction quality and continuance intention. 3) Perceived enjoyment serves as an important mediator between interactivity, vividness, and continuance intention, while its mediating role between authenticity and continuance intention is not significant. This study offers theoretical and practical insights for optimizing digital museum user experience design to enhance continuance intention, while also promoting the dissemination of digital culture and supporting educational efforts.

Indexed as

IntentionMuseumsPleasureAdultChinaFemaleHumansMaleMiddle AgedSurveys and QuestionnairesYoung Adult

Identifiers

PMID39841733
PMCPMC11753657

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.