Evidence map›Paper›PMID 42305759›Full record

ArticleFrontiers in public health2026

Impact of artificial intelligence and work digitalization on mental health and occupational well-being: a scoping review.

Óscar Rabasa-Martín, Begoña Martínez-Jarreta

Abstract readScoping Review
In one paragraph

Article in Frontiers in public health, 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.

Óscar Rabasa-MartínFaculty of Medicine, University of Zaragoza, Zaragoza, Spain.
Begoña Martínez-JarretaFaculty of Medicine, University of Zaragoza, Zaragoza, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The rapid expansion of artificial intelligence (AI) and work digitalization is transforming occupational environments, introducing new psychosocial risks while also creating potential opportunities for improving workplace well-being. However, current evidence remains fragmented and heterogeneous. Objective: This scoping review aimed to map and synthesize the existing scientific and grey literature on the impact of AI and work digitalization on mental health, well-being, and psychosocial risks among adult workers. Methods: A scoping review was conducted following the Arksey and O'Malley framework and reported according to PRISMA-ScR guidelines. A comprehensive search was performed across multiple databases (PubMed, Scopus, Web of Science, ScienceDirect, Scielo, LILACS, Dialnet, and Google Scholar) and grey literature sources from international occupational health organizations. Studies published between 2016 and 2026 in English and Spanish were included. A total of 43 sources (23 scientific articles and 20 grey literature documents) were analyzed using thematic synthesis. The review explicitly distinguishes between AI-specific occupational exposures and broader digitalization processes to improve conceptual clarity. Results: AI and digitalization were consistently associated with multiple psychosocial risks, including technostress, work intensification, job insecurity, reduced autonomy, and blurred work-life boundaries. Algorithmic management and digital monitoring emerged as key drivers of stress, anxiety, and burnout. However, potential benefits were also identified, such as increased efficiency, flexibility, and professional development, particularly when supported by adequate training and organizational resources. The impact of digitalization was context-dependent and unevenly distributed, disproportionately affecting older workers, lower-skilled employees, and vulnerable groups. Digital and AI literacy emerged as key protective factors. Conclusion: AI and work digitalization represent complex and context-dependent determinants of occupational mental health, with both risks and opportunities depending on organizational, technological, and individual factors. These findings highlight the need for human-centered implementation strategies, strengthened regulatory frameworks, and targeted preventive interventions to mitigate psychosocial risks in digitalized work environments. Given the heterogeneity of the available evidence, findings should be interpreted as exploratory.

Indexed as

Artificial IntelligenceMental HealthOccupational HealthWorkplaceDigital HealthHumansPsychological Well-BeingWorking Conditionsartificial intelligencedigitalizationmental healthoccupational healthpsychosocial risktechnostressworkplace well-being

Identifiers

PMID42305759
PMCPMC13265473

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.