Two new studies offer ways to avert accidents and workplace injuries for American workers

outdoor worker
Credit: CC0 Public Domain

Human error is a causal factor in up to 80 percent of workplace accidents. A new study measuring the eye movements and cognitive processes for at-risk workers, sheds new light on the potential to avert accidents and possibly prevent workplace injuries. The study "Measuring attention, working memory, and visual perception to reduce risk of injuries in the construction industry," by Behzad Esmaeili, Ph.D., George Mason University challenges the conventional, reactionary paradigm of safety-risk management.

This study, and others exploring the hazards faced by the American workforce, will be featured on December 17, during the Focusing on Workers and Risk Decision-Making session at the 2020 Society for Risk Analysis virtual Annual Meeting, December 13-17, 2020.

Esmaeili's study used eye-tracking experiments to build an error-detection framework that computes the likelihood of human error in occupational settings. The researchers linked eye movement and workers' attention with research focused on working-memory load and decision making to understand how and why workers in a dynamic environment fail to detect, comprehend and/or respond to physical risks.

The experiment found that (1) can be used as precursors of workers' safety errors, (2) working-memory load and personality traits play a significant role in risk-taking behavior and (3) data mining classifier can be used to compute the likelihood of different types of human errors.

Other contributing factors to in the workplace are stress and complexity. In a second study, Vincent Paglioni, University of Maryland, analyzed the impacts of these compounding factors on the relationship between human failures in the operation of power plants. The ability to accurately model human reliability can improve safety analyses in numerous industries, including nuclear power and aviation.

The study, "Temporal behaviors of dependency relationships in human reliability analysis," fills a major technical gap in Human Reliability Analysis (HRA). "Current HRA models are incorrect in the way that they model time-dependent effects of factors such as stress and complexity. By melding research in psychology, reliability engineering and data science, we can develop more accurate HRA models," states Paglioni. "The results will improve methods to ensure the safety of complex engineering systems."

Firefighters are essential to the safety of our communities, but in addition to physical and mental stresses at work, firefighters are also subject to chemical exposures that can lead to disease and long-term health issues. Mary Fox, MPH, Ph.D., Johns Hopkins University, conducted a literature and narrative review of firefighter health from articles published in PubMed, Embase and PsycINFO.

The study, "Firefighter health: A case example of translating epidemiological data for public policy," revealed that firefighters face an increased risk of cardiovascular disease, asthma and PTSD. Fox's work informed updates to Virginia's workers' compensation policies.

Explore further

Women, workers of color filling most 'high-hazard/low-reward' jobs in Washington

Provided by Society for Risk Analysis
Citation: Two new studies offer ways to avert accidents and workplace injuries for American workers (2020, December 17) retrieved 23 January 2021 from
This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.

Feedback to editors

User comments