Reducing occupational injuries attributed to inattentional blindness in the construction industry

Liao, Chia-Wen; Chiang, Tung Liang

doi:10.1016/j.ssci.2016.06.010

Cited by 25 publications

(9 citation statements)

References 25 publications

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“…When broken down by participants, approximately 45% (n = 17) of participants in the control condition indicated that they had noticed an unusual item or individual, other than the victims, in the hallway. This detection rate fits with existing literature that suggests about half of all participants would be expected to notice an unexpected stimulus when not under high cognitive load (e.g., Chabris et al, 2011;Liao & Chiang, 2016;Näsholm et al, 2014). However, when asked to provide details of what participants had seen in the video, only one participant indicated that they had noticed the scenario-relevant unexpected stimulus (i.e., the suitcase), while 69% (n = 11) noted that they saw something unusual about the victims or the shooter, 12.5% (n = 2) indicated seeing an unusual item that was not the suitcase, and 19% (n = 3) noted seeing other unusual or unexpected stimuli (e.g., a mannequin and identifying tags worn by volunteers in the video).…”

Section: Datasupporting

confidence: 90%

“…Approximately 45% of participants in the control condition indicated that they had noticed an unusual item or individual, other than the victims, in the hallway. This detection rate fits with previous literature that suggests about half of participants would be expected to notice an unexpected stimulus when not under high cognitive load (e.g., Chabris et al, 2011;Liao & Chiang, 2016;Näsholm et al, 2014). Despite this high detection rate however, only two control condition participants were able to notice and correctly identify the scenario-relevant unexpected stimulus (i.e., the suitcase), with other control condition participants noticing scene-irrelevant items.…”

Section: An Examination Of Inattentional Blindness In Law Enforcement 25supporting

confidence: 88%

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An Examination of Inattentional Blindness in Law Enforcement in High Stress Situations

Lee¹,

O’Neill²,

Houlihan³

2018

LEEF

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Inattentional blindness, or the inability to visually detect an unexpected stimulus while attending to a task or situation, can have detrimental effects on those who are subject to the phenomenon. This may be particularly true for law enforcement officers, who are often engaged in cognitively demanding tasks that draw their attention away from potentially deadly hazards. This study aimed to look at the effects of inattentional blindness within a group of officers of varying degrees of experience and expertise. The officers were presented with a video-based scenario in which an unexpected stimulus was placed. The control group was asked to attend to a general task, while the experimental group was asked to attend to a specific and more demanding task. Within the context of an active shooter situation, the officers' ability to detect a large black suitcase in a hallway during the video was assessed. Overall rates of unexpected stimuli detection was consistent with existing literature, however detection of the scene-relevant stimulus was lower than expected.

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Section: Datasupporting

confidence: 90%

Section: An Examination Of Inattentional Blindness In Law Enforcement 25supporting

confidence: 88%

An Examination of Inattentional Blindness in Law Enforcement in High Stress Situations

Lee¹,

O’Neill²,

Houlihan³

2018

LEEF

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“…Another safety risk assessment model was proposed to analyze different construction site layouts with various safety risk levels (Ning et al, 2018). Studies were conducted to investigate the similarities between the safety and risk perceptions of the stakeholders of construction projects and those of OHS professionals (Zhang et al, 2015;Zhao et al, 2016;Liao & Chiang, 2016). As the research discussed above, understanding the correlations between the attributes is critical to preventing accidents proactively since the OHS professionals should learn how to overcome the safety risks and how to manage risk assessment in advance.…”

Section: Safety Risksmentioning

confidence: 99%

An Association Rule Mining Model for the Assessment of the Correlations Between the Attributes of Severe Accidents

Ayhan

Doğan

Tokdemir

2020

Journal of Civil Engineering and Management

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Identifying the correlations between the attributes of severe accidents could be vital to preventing them. If such relationships were known dynamically, it would be possible to take preventative actions against accidents. The paper aims to develop an analytical model that is adaptable for each type of data to create preventative measures that will be suitable for any computational systems. The present model collectively shows the relationships between the attributes in a coherent manner to avoid severe accidents. In this respect, Association Rule Mining (ARM) is used as the technique to identify the correlations between the attributes. The research adopts a positivist approach to adhere to the factual knowledge concerning nine different accident types through case studies and quantitative measurements in an objective nature. ARM was exemplified with nine different types of construction accidents to validate the adaptability of the proposed model. The results show that each accident type has different characteristics with varying combinations of the attribute, and analytical model accomplished to accommodate variation through the dataset. Ultimately, professionals can identify the cause-effect relationships effectively and set up preventative measures to break the link between the accident causing factors.

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“…Indications of use of defective or inappropriate equipment or occurrence of incidents involving misjudgment, inattention, or deliberate action do not help to discriminate fatal from nonfatal injuries. Other research [22] has identified "inattentional blindness"when workers focused on their main task ignore other dangers in their environmentas a persistent safety problem in the construction workplace.…”

Section: Human Factorsmentioning

confidence: 99%

Severity of U.S. Construction Worker Injuries, 2015-2017

et al. 2019

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Workers in the U.S. construction industry experience workplace hazards that can lead to work-related injuries that sometimes are fatal. Reported in this paper is a case-control study of risks factors associated with 4,845 injured workers and their work environments that led to fatal rather than nonfatal injuries during 2015-2017. These injury data originally were assembled from information collected by the U.S. Bureau of Labor Statistics that were used in a machine learning competition, but were repurposed for this secondary analysis of injury risks. Sixty-one percent of workers recorded in this dataset were injured fatally. Multiple logistic regression was applied to model the probability of a fatal injury as a function of the nature of the injury, part of body injured, human factors involved, whether the injured worker was carrying out a regularly assigned task at the time of the injury, and the manner in which the injury was inflicted. Related positively, relative to benchmarks, to the probability of a fatality injury were: falls and strikes; electrocution; asphyxiation and drowning; injury to the head and neck; and working at a task not regularly assigned. Negatively related to the probability of a fatal injury were: chemical/temperature burns; amputation and crushing; fractures and dislocations; injuries to fingers, hands, wrists, and other extremities; and falls from an elevation or to the same level, although this last negative relationship is anomalous in the light of independent research findings. Findings of this study do not necessarily culpable causes of work-related death. Rather these findings identify risk factors that might prove fruitful for further analysis of the incidence, severity, and costs of construction injuries.

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Reducing occupational injuries attributed to inattentional blindness in the construction industry

Cited by 25 publications

References 25 publications

An Examination of Inattentional Blindness in Law Enforcement in High Stress Situations

An Examination of Inattentional Blindness in Law Enforcement in High Stress Situations

An Association Rule Mining Model for the Assessment of the Correlations Between the Attributes of Severe Accidents

Severity of U.S. Construction Worker Injuries, 2015-2017

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