Evidence map›Paper›PMID 42245363›Full record

ArticleFrontiers in public health2026

From information literacy to health literacy: AI-driven transformation in university libraries under digital public health-a perspective.

Ya-Xin Sun, Li-Ying Wu

Abstract read
In one paragraph

Article 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

2 authors.

Ya-Xin SunDepartment of Library, Mudanjiang Medical University, Mudanjiang, China.
Li-Ying WuDepartment of Library, Mudanjiang Medical University, Mudanjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the context of digital public health, the growing integration of artificial intelligence (AI) into health information environments challenges the adequacy of traditional information literacy frameworks in academic libraries. This perspective article argues for a transition from information literacy to AI-mediated health literacy education. It clarifies the conceptual distinctions between these two constructs, analyzes the AI-driven mechanisms reshaping educational paradigms, and identifies key institutional, technological, professional, and evaluative challenges. The article further proposes practical pathways that include mission reorientation, professional capacity building, platform development, collaborative governance, and evaluation system construction. This study advances existing literature by proposing an integrated, AI-mediated framework. This framework reconceptualizes health literacy within the context of digital public health. It also operationalizes this transformation through three interconnected dimensions: technological, educational, and governance-related. By outlining a theoretical framework and actionable strategies, it positions academic libraries as essential infrastructure for health literacy cultivation, contributing to health promotion and equity in an increasingly digital age.

Indexed as

Artificial IntelligenceHealth LiteracyInformation LiteracyPublic HealthDigital HealthHumansUniversitiesartificial intelligencedigital public healthhealth communicationhealth literacyinformation literacyuniversity library

Identifiers

PMID42245363
PMCPMC13229875

What OpenQuestion holds

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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.