Evidence map›Paper›PMID 41112536›Full record

ArticleFrontiers in psychology2025

Digital religion and Generation Z: an empirical study in the context of China.

Zhi Liu, Arsalan Mujahid Ghouri, Jing Wang, Changqing Lin

Abstract read
In one paragraph

Article in Frontiers in psychology, 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

4 authors.

Zhi LiuSchool of Culture and Communication, Putian University, Fujian Province, Putian, China.
Arsalan Mujahid GhouriSchool of Business, London South Bank University, London, United Kingdom.
Jing WangSchool of Culture and Communication, Putian University, Fujian Province, Putian, China.
Changqing LinSchool of Culture and Communication, Putian University, Fujian Province, Putian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study investigates the intersection of digital media and religious behavior among Chinese Generation Z, extending the Theory of Planned Behavior (TPB) by incorporating media content innovation and empathic willingness. It explores how platforms like Weibo and TikTok shape religious intentions and behaviors through visual and interactive features. Methods: A cross-sectional study was conducted with 534 Chinese Generation Z participants. Data were collected via surveys assessing the influence of media content innovation and empathic willingness on digital religious behavior, using the TPB framework. Structural equation modeling analyzed the relationships between these factors and religious intentions. Results: Findings indicate that media content innovation and empathic willingness significantly enhance digital religious behavior within the TPB framework. Vibrant, emotionally resonant content on social media platforms fosters emotional engagement and active participation, amplifying religious intentions among participants. Discussion: These results highlight social media's transformative role in redefining religious practices among Chinese Generation Z. Media content innovation and empathic willingness emerge as critical drivers of engagement. The findings offer insights for religious organizations, policymakers, and social media platforms to foster meaningful cultural and religious interactions. This study underscores the need for tailored digital strategies to promote spiritual engagement in the digital age.

Indexed as

Chinese youthdigital religionGeneration Zsocial media platformstheory of planned behavior

Identifiers

PMID41112536
PMCPMC12528061

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.