Evidence map›Paper›PMID 41594985›Full record

ArticleBehavioral sciences (Basel, Switzerland)2025

A One-Year Longitudinal Study Examining the Direct and Indirect Effects of AI Dependence on Work Engagement and Gender Differences.

Jiani Wen, Yuju Lei, Qingqi Liu

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 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
–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

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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.

Jiani WenFaculty of Psychology, Beijing Normal University, Beijing 100875, China.
Yuju LeiSchool of Teacher Education, Hubei University of Arts and Science, Xiangyang 441053, China.
Qingqi LiuFaculty of Psychology, Beijing Normal University, Beijing 100875, China.ORCID 0000-0001-5169-8689

Funding

National Social Science Fund of China CBA200241
6 · The paper itself

Abstract

As artificial intelligence (AI) products become increasingly integrated into daily life, AI dependence has gained significant public and scholarly attention. While existing research has primarily examined its impact on students, few studies have investigated its association with employee career development, particularly work engagement. Our one-year longitudinal study involving 1108 employees aged 21-60 examined the long-term effect of AI dependence on work engagement, incorporating work self-efficacy as a mediator and gender as a moderator. Using three-wave survey data, we found that AI dependence at Time 1 (T1) directly predicted work engagement at Time 3 (T3), and also exerted a significant indirect effect through work self-efficacy at Time 2 (T2). While the mediating effect of T2 work self-efficacy showed no gender differences, the direct effect of T1 AI dependence on T3 work engagement was significantly stronger among male employees. These findings systematically address questions regarding the long-term, mediated, and gender-differentiated effects of AI dependence. They provide important warnings regarding AI dependence prevention and deliver practical implications for maintaining and enhancing employee self-efficacy and engagement in the AI era.

Indexed as

AI dependencegender differenceslongitudinal studywork engagementwork self-efficacy

Identifiers

PMID41594985
PMCPMC12837688

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.