Evidence map›Paper›PMID 42729122›Full record

ArticleFrontiers in psychology2026

When does working with AI empower or entrap university faculty? A dualistic passion perspective on job crafting.

Jin Zhu, Yifei Zhang

Abstract read
In one paragraph

Article in Frontiers in 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.

Jin ZhuSchool of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang, China.
Yifei ZhangSchool of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Generative AI is now widely used in teaching, research, and academic writing, leading university faculty to engage in more sustained human-AI collaboration. However, existing research has largely focused on tool-related outcomes, offering limited insight into the psychological experiences and academic work practices associated with such collaboration. Methods: We conducted two survey-based studies using independent samples of Chinese university faculty. Study 1 ( Results: Across both studies, human-AI collaboration engagement was positively associated with both harmonious and obsessive passion. Independent self-construal strengthened the association between collaboration engagement and harmonious passion, but not the association with obsessive passion. Study 2 further showed that harmonious passion was positively related to job crafting, whereas obsessive passion was negatively related to job crafting. Discussion: Human-AI collaboration may involve different psychological experiences among university faculty, depending on how such collaboration is internalized. Specifically, harmonious passion and greater job crafting reflect an empowerment-related pattern, whereas obsessive passion and reduced job crafting reflect a more constraining pattern of AI collaboration. These results point to the importance of motivational quality in explaining variation in academic work behavior beyond a tool-centered perspective.

Indexed as

dualistic passionhuman-AI collaborationindependent self-construaljob craftinguniversity faculty

Identifiers

PMID42729122
PMCPMC13561786

What OpenQuestion holds

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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.