Evidence map›Paper›PMID 42688205›Full record

ReviewFrontiers in public health2026

AI-mediated participatory reading and relational well-being: a conceptual framework from contemporary China.

Bingnan Li

Abstract readReview
In one paragraph

Review in Frontiers in public health, 2026. 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

1 author.

Bingnan LiSchool of Journalism and Communication, Shaanxi Normal University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article develops a conceptual model of how AI-mediated reading practices reshape the social and relational conditions through which reading may contribute to well-being in contemporary China. Focusing on new mass literature and arts, it examines reading not only as textual reception but also as a practice increasingly connected to algorithmic selection, generative response, editorial mediation, and reading-centered community interaction. Through a theory-synthesis and model-building conceptual analysis based on a purposive narrative review, the article proposes the "AI-mediated participatory reading ecology": a bounded framework that traces a sequential relationship among reading-centered encounters, generative responses, mediating publishing, participatory interaction, and possible relational outcomes. The framework does not claim that AI-mediated reading directly improves mental health. Instead, it specifies the conditions under which reading-related participation may support relational well-being through recognition, perceived belonging, expression, and meaningful social connection. It formulates four analytically examinable propositions concerning textual anchoring, mediated visibility, interaction quality, and stratified participation. The Chinese case is significant because platformized cultural circulation, intelligent publishing, commercial infrastructures, and public cultural agendas converge with particular intensity. At the same time, AI-mediated reading may intensify content overload, homogenization, unequal visibility, attention capture, and the exclusion of less connected groups. The article's contribution lies in clarifying how AI-mediated infrastructures reshape the psychological and relational conditions under which reading may support social connection and well-being, while converting a broad descriptive category into a bounded mechanism model with explicit conditions, limits, and an empirical research agenda.

Indexed as

Artificial IntelligenceReadingChinaHumansMental HealthPsychological Well-BeingAI-mediated participatory reading ecologyChinacultural participationdigital readingpublic mental healthrelational well-beingsocial connection

Identifiers

PMID42688205
PMCPMC13533819

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.