Evidence map›Paper›PMID 41450678›Full record

ArticleFrontiers in psychology2025

From screens to minds: the mediating role of psychological well-being between digital reading and AI anxiety.

Uğur Özbilen, Emrullah Banaz, Tuğrul Gökmen Şahin

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Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

5 · Who and what money

Authors and funding

3 authors.

Uğur ÖzbilenIndependent Researcher, Antalya, Türkiye.
Emrullah BanazDepartment of Educational Sciences, Bayburt University, Bayburt, Türkiye.
Tuğrul Gökmen ŞahinDepartment of Social Sciences and Turkish Language Education, Ataturk University, Erzurum, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study investigates the mediating role of psychological well-being in the relationship between digital reading disposition and artificial intelligence (AI) anxiety among Turkish teachers. Addressing the growing concern of technology-related anxiety in education, the research explores how digital literacy and psychological resilience interact within a single structural model. Methods: A correlational research design was employed with data collected from 324 teachers. Participants completed the Digital Reading Disposition Scale, the Psychological Well-Being Scale, and the Artificial Intelligence Anxiety Scale. Bootstrapped structural equation modeling (SEM) was used to test the measurement model and the hypothesized mediation effect. Prior to SEM analysis, confirmatory factor analysis (CFA) was conducted to establish construct validity of the scales. Results: Findings revealed that digital reading disposition was positively associated with psychological well-being and negatively linked with AI anxiety. Psychological well-being was also negatively related to AI anxiety. Moreover, psychological well-being partially mediated the relationship between digital reading disposition and AI anxiety. Discussion: The results suggest that teachers with stronger digital reading dispositions experience higher psychological well-being, which in turn buffers against AI-related anxiety. These findings contribute novel theoretical insights to educational literature by integrating digital reading, psychological well-being, and AI anxiety into a single model. Practically, the study underscores the importance of fostering digital literacy and psychological resilience to mitigate technology-related anxiety in educational settings.

Indexed as

artificial intelligence anxietydigital reading dispositionpsychological well-beingstructural equation modelingteacher education

Identifiers

PMID41450678
PMCPMC12727563

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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.