Reviewers 2019

Editorial Office

doi:10.23749/mdl.v111i1.9289

Editorial Office

Keywords

Abstract 387 | PDF Downloads 234

PDF

Published

12-02-2020

DOI: https://doi.org/10.23749/mdl.v111i1.9289

How to Cite

Office E. Reviewers 2019. Med Lav. 2020;111(1):77-78. doi:10.23749/mdl.v111i1.9289

Issue

Vol. 111 No. 1 (2020)

Section

Acknowledgement to Scientific Reviewers

All Journal's articles are Open Access papers distributed under the terms of the Creative Commons Attribution License CC BY-NC 4.0 Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reproductions with commercial intent will require written permission and payment of royalties.

How to Cite

Office E. Reviewers 2019. Med Lav. 2020;111(1):77-78. doi:10.23749/mdl.v111i1.9289

Download Citation

Editor-in-Chief

Antonio Mutti

Journal Information

Language: English
Frequency: 6 issues/year
Format: 20 x 27 cm
ISSN: 0025-7818
eISSN: 2532-1080
2024 Impact Factor (Clarivate JCR): 2.0
2024 Scopus Cite Score: 4.3

Med Lav Vol 117 No 2 (2026)

Make a Submission

Information

Listed in:

Scopus coverage years:from 1947 to 1963, from 1965 to Present

Official Impact Factor 2024: 2.0

FAD

La FAD sarà online dal 19/01/2026 al 30/12/2026.
I Soci SIML in regola con la quota associativa riceveranno una mail di invito da Mattioli Academy con la quale accedere gratuitamente al corso.

News

Adoption of a new AI Policy (Effective 1^st January 2026)

La Medicina del Lavoro | Work, Environment and Health announces that, effective 1 January 2026, the journal will formally adopt the Editorial Policy on the Use of Artificial Intelligence in the Peer Review Process as outlined in the attached document.

This policy establishes clear principles and operational guidelines for the responsible use of AI tools by reviewers and editorial staff. It reaffirms the journal’s commitment to:

- Human accountability in all scientific judgments
- Transparency regarding the use of AI beyond basic editorial support
- Quality and rigor in the peer review process
- Strict confidentiality of submitted manuscripts

The policy introduces a structured framework defining acceptable and unacceptable uses of AI during peer review, ensuring that technological innovation enhances—rather than replaces—human expertise and ethical responsibility (see the 4th paragraph of our policies).

All reviewers invited from 1 January 2026 onward will be expected to comply with this policy and, where applicable, include the required transparency statement in their confidential comments to the editor.

La Medicina del Lavoro | Work, Environment and Health remains committed to safeguarding scientific integrity while embracing responsible innovation in scholarly publishing.

Publons Reviewer Recognition Service

Main Article Content

Keywords

Article Sidebar

Article Details

How to Cite

Download Citation

How to Cite