Evidence map›Paper›PMID 41602722›Full record

ArticleFrontiers in psychology2025

To embrace or to avoid: the dual path effects of digital technology requirements on employees with different digital literacy.

Shuang Li, Yumei Wang, Xiao Wang

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

3 authors.

Shuang LiCollege of Digital Economics & Management, Mianyang Teachers' College, Mianyang, China.
Yumei WangSchool of Business Administration, Southwestern University of Finance and Economics, Chengdu, China.
Xiao WangCollege of Digital Economics & Management, Mianyang Teachers' College, Mianyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whether and how enterprise digital technology requirements affect employees constitutes a pivotal scholarly inquiry in the digital economy landscape. Grounded in the Cognitive Appraisal Theory of Stress and integrating the Job Demands-Resources (JD-R) Model with the Conservation of Resources (CoR) Theory, this study proposes employees may appraise enterprise digital technology requirements as either challenge stressors-proactively embracing demands to catalyze positive outcomes in proactive behaviors-or hindrance stressors-cognitively avoiding requirements thus eliciting negative consequences in turnover intention. Moreover, employees' digital literacy levels fundamentally reconfigure their cognitive appraisals of these technological demands, thereby triggering differential behavioral cascades. Utilizing a three-wave longitudinal survey design with 332 validated responses from employees undergoing digital transformation, this study employed AMOS 23.0 for confirmatory factor analysis, SPSS 23.0 for hierarchical regression modeling, and the PROCESS macro for bootstrap mediation tests to substantiate the proposed theoretical framework. This study advances the dual-path framework of enterprise digital technology implementation by elucidating how digital literacy-as a personal resource-shapes divergent outcomes stemming from organizational digital demands. Furthermore, it extends the application of the Cognitive Appraisal Theory of Stress to digital contexts through empirical validation, and also to provide some inspiration and reference for relevant management practices.

Indexed as

challenge stressdigital literacyenterprise digital technology requirementshindrance stressproactive behaviorthe Cognitive Appraisal Theory of Stressturnover intention

Identifiers

PMID41602722
PMCPMC12832773

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.