ArticleBMJ open2025
Use of machine learning in occupational risk communication for healthcare workers: protocol for scoping review.
Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionWith the development of technology, the use of machine learning (ML), a branch of computer science that aims to transform computers into decision-making agents through algorithms, has grown exponentially. This protocol arises from the need to explore the best practices for applying ML in the communication and management of occupational risks for healthcare workers. METHODS AND ANALYSIS: This scoping review protocol details a search to be conducted in the academic databases, Public Medical Literature Analysis and Retrieval System Online, through the Virtual Health Library: Medical Literature Analysis and Retrieval System, Latin American and Caribbean Literature in Health Sciences, West Pacific Region Index Medicus, Nursing Database and Scientific Electronic Library Online, Scopus, Web of Science and IEEE Xplore Digital Library and Excerpta Medica Database. This scoping review protocol outlines the objectives, methods and timeline for a review that will explore and map the existing scientific evidence and knowledge on the use of ML in risk communication for healthcare workers. This protocol follows the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews and Joanna Briggs Institute guidelines for conducting scoping reviews. The guiding question of the review is: how is ML used in risk communication for healthcare workers? The search will use Population, Concept and Context terms and the specific descriptors defined by each database. The narrative synthesis will describe the main themes and findings of the review.The results of this scoping review will be disseminated through publication in an international peer-reviewed scientific journal. ETHICS AND DISSEMINATION: Ethical approval is not required; data will rely on published articles. Findings will be published open access in an international peer-reviewed journal. TRIAL REGISTRATION NUMBER: The protocol for this review was registered in the Open Science Framework under DOI 10.17605/OSF.IO/92SK4 (available at https://osf.io/92SK4).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.