The Impact of Artificial Intelligence Usage on Affective Work Well-Being: A Self-Determination Theory Perspective.

Chi Zhang, Shuping Chen, Dianru Zhang, Qichao Zhang

Abstract read

In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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.

Enhancing Employee Innovation Through Dependence on AI: The Mediating Role of Cognitive Flexibility and Moderating Effect of Job Complexity.Behavioral sciences (Basel, Switzerland) · 2026
Article

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

4 authors.

Chi ZhangMental Health Education Center, Beijing Jiaotong University, Beijing 100044, China.

Shuping ChenSchool of Economics and Management, Beijing Jiaotong University, Beijing 100044, China.

Dianru ZhangHSBC Business School, Peking University, Beijing 100871, China.

Qichao ZhangBusiness School, Beijing Information Science and Technology University, Beijing 102206, China.

Funding

National Social Science Foundation of China No. 24CGL122

6 · The paper itself

Abstract

Despite the growing integration of artificial intelligence (AI) into workplace operations, how AI usage influences employees' affective work well-being remains underexplored. To address this gap, this study draws on self-determination theory to propose a moderated mediation model. We conducted a three-wave time-lagged survey of 360 employees and our results indicate that AI usage positively predicts affective work well-being, and this relationship is fully mediated through two parallel paths-work meaningfulness and work engagement. Moreover, human-AI collaboration quality positively moderates these indirect effects. Collectively, these findings extend self-determination theory to AI-augmented work contexts, clarify the psychological mechanisms linking AI usage to employee affective well-being, and provide actionable insights for human-centered AI implementation.

Indexed as

affective work well-beingAI usagehuman–AI collaboration qualityself-determination theorywork engagementwork meaningfulness

Identifiers

PMID42193549

DOI10.3390/bs16050670

PMCPMC13203233

What OpenQuestion holds

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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.