Evidence map›Paper›PMID 41792846›Full record

ArticleBMC psychology2026

Digital technology anxiety and teacher digital literacy development: a longitudinal examination of cognitive appraisal mechanisms.

Ruina Liu, Xian Li

Abstract read
In one paragraph

Article in BMC psychology, 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.

Ruina LiuFaculty of Education, Qufu Normal University, Qufu, Shandong, 273165, China. 15535121711@163.com.
Xian LiFaculty of Education, Qufu Normal University, Qufu, Shandong, 273165, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examines how teacher digital technology anxiety influences digital literacy development through cognitive appraisal mechanisms. Employing a three-wave longitudinal design spanning one academic year, we surveyed 1,247 in-service teachers across urban, suburban, and rural schools in China at six-month intervals. Cross-lagged panel modeling revealed that digital technology anxiety significantly predicted subsequent decreases in digital literacy development, with this relationship demonstrating temporal precedence over reverse pathways. Mediation analyses grounded in cognitive appraisal theory indicated that approximately 65% of anxiety’s total effect operated through interpretive mechanisms, specifically threat appraisals and resource appraisals, which subsequently shaped coping strategies. Teachers experiencing heightened anxiety more readily interpreted technological demands as threatening to professional competence while perceiving fewer available coping resources, ultimately constraining skill acquisition. These findings extend cognitive appraisal theory into technology acceptance contexts and illuminate affective-cognitive mechanisms often overlooked in digital literacy development models. Practical implications suggest multilevel interventions targeting cognitive reappraisal training, resource provision, and psychologically safe organizational environments to support teachers’ digital professional development.

Indexed as

AnxietyAttitude to ComputersCognitionComputer LiteracyDigital TechnologySchool TeachersAdaptation, PsychologicalAdultChinaCoping SkillsFemaleHumansLongitudinal StudiesMaleCognitive appraisal theoryDigital literacy developmentDigital technology anxietyLongitudinal studyMediation analysisTeacher professional development

Identifiers

PMID41792846
PMCPMC13078095

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.