Considering Trends Among Industrial Accidents: A Preliminary Meta Analysis of HFACS Causal Factors Across Industries

Katherine A. Berry; Paris F. Strongfellow; Scott A. Shappell

doi:10.1177/154193120905302007

Considering Trends Among Industrial Accidents: A Preliminary Meta Analysis of HFACS Causal Factors Across Industries

Katherine A. Berry, Paris F. Strongfellow, Scott A. Shappell

Clemson University

Research output: Contribution to conference › Presentation

Abstract

This study investigated human error across a variety of industry types utilizing the Human Factors Classification and Analysis System [Human Factors Analysis and Classification System] (HFACS). One of the goals of the present study was to determine any similarities or disparities across industry type in regards to HFACS causal categories. Seven data sources represented five different industry types were collected and analyzed for percentage of cases associated with a causal factor at each HFACS causal category. Skill-based errors were found to dominate the unsafe acts tier regardless of industry type. Different statistical methods for determining population differences yielded conflicting results. Significant differences were found among certain data source pairings when the traditional two-proportion z-test was applied; however, the differences were found to be non-significant when the false discovery rate method was applied.

Original language	American English
DOIs	https://doi.org/10.1177/154193120905302007
State	Published - Oct 2009
Externally published	Yes
Event	53rd Annual Meeting of the Human Factors and Ergonomics Society - San Antonio, TX Duration: Oct 1 2009 → …

Conference

Conference	53rd Annual Meeting of the Human Factors and Ergonomics Society
Period	10/1/09 → …

Keywords

Human Factors Analysis and Classification System (HFACS)
human error
industrial accidents
safety

Disciplines

Other Psychology

Access to Document

10.1177/154193120905302007License: Unspecified

Cite this

@conference{230ec532cc2049049c732e6d3e9e4e6c,

title = "Considering Trends Among Industrial Accidents: A Preliminary Meta Analysis of HFACS Causal Factors Across Industries",

abstract = " This study investigated human error across a variety of industry types utilizing the Human Factors Classification and Analysis System [Human Factors Analysis and Classification System] (HFACS). One of the goals of the present study was to determine any similarities or disparities across industry type in regards to HFACS causal categories. Seven data sources represented five different industry types were collected and analyzed for percentage of cases associated with a causal factor at each HFACS causal category. Skill-based errors were found to dominate the unsafe acts tier regardless of industry type. Different statistical methods for determining population differences yielded conflicting results. Significant differences were found among certain data source pairings when the traditional two-proportion z-test was applied; however, the differences were found to be non-significant when the false discovery rate method was applied.",

keywords = "Human Factors Analysis and Classification System (HFACS), human error, industrial accidents, safety",

author = "Berry, {Katherine A.} and Strongfellow, {Paris F.} and Shappell, {Scott A.}",

year = "2009",

month = oct,

doi = "10.1177/154193120905302007",

language = "American English",

note = "53rd Annual Meeting of the Human Factors and Ergonomics Society ; Conference date: 01-10-2009",

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T1 - Considering Trends Among Industrial Accidents: A Preliminary Meta Analysis of HFACS Causal Factors Across Industries

AU - Berry, Katherine A.

AU - Strongfellow, Paris F.

AU - Shappell, Scott A.

PY - 2009/10

Y1 - 2009/10

N2 - This study investigated human error across a variety of industry types utilizing the Human Factors Classification and Analysis System [Human Factors Analysis and Classification System] (HFACS). One of the goals of the present study was to determine any similarities or disparities across industry type in regards to HFACS causal categories. Seven data sources represented five different industry types were collected and analyzed for percentage of cases associated with a causal factor at each HFACS causal category. Skill-based errors were found to dominate the unsafe acts tier regardless of industry type. Different statistical methods for determining population differences yielded conflicting results. Significant differences were found among certain data source pairings when the traditional two-proportion z-test was applied; however, the differences were found to be non-significant when the false discovery rate method was applied.

AB - This study investigated human error across a variety of industry types utilizing the Human Factors Classification and Analysis System [Human Factors Analysis and Classification System] (HFACS). One of the goals of the present study was to determine any similarities or disparities across industry type in regards to HFACS causal categories. Seven data sources represented five different industry types were collected and analyzed for percentage of cases associated with a causal factor at each HFACS causal category. Skill-based errors were found to dominate the unsafe acts tier regardless of industry type. Different statistical methods for determining population differences yielded conflicting results. Significant differences were found among certain data source pairings when the traditional two-proportion z-test was applied; however, the differences were found to be non-significant when the false discovery rate method was applied.

KW - Human Factors Analysis and Classification System (HFACS)

KW - human error

KW - industrial accidents

KW - safety

U2 - 10.1177/154193120905302007

DO - 10.1177/154193120905302007

M3 - Presentation

T2 - 53rd Annual Meeting of the Human Factors and Ergonomics Society

Y2 - 1 October 2009

ER -