Abstracts – Browse Results
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Aroke, O M (2022) Measuring attention, working memory and visual perception to reduce the risk of injuries in the construction industry, Unpublished PhD Thesis, , George Mason University.
- Type: Thesis
- Keywords: failure; hazards; residential; injury; monitoring; safety; training; construction worker; roofer; experiment
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/2637317707
- Abstract:
The construction industry has consistently held one of the highest injury rates among all sectors and failure to recognize hazards due to poor selective attention, cognitive overload, and distractibility have been identified as critical human factors that lead to accidents. Considering that falls are the leading cause of deaths in the construction industry and accountable for over 33% of all construction worker deaths, this project investigated the extent to which worker characteristics (work experience, safety training, and previous injury involvement), personality dimensions (extraversion, neuroticism, conscientiousness, agreeableness, and openness to experience), working memory load and workplace conditions (e.g.time pressure) interact to influence visual attention and the identification of fall hazards. By continuously monitoring the eye movements of participants using eye-tracking technology, this study identified precursors of human error by carrying out a batch of visual search tasks to: (i) evaluate the influence of worker characteristics on visual attention and hazard identification as workers viewed 35 construction-scenario images containing 115 fall hazard areas of interests (AOIs); ii) investigate the effect of working memory load on hazard recognition for various personality traits while performing a visual attention task of identifying fall hazards across 231 AOIs and memorizing 3-digit and 6-digit strings of numbers (simulating low and high memory load conditions respectively) in a secondary cognitive task, and iii) examine the impact of time pressure on attention to fall and hand injury hazards as participants installed 27 pieces of 40 ft2 shingles standing on a low-sloped roof model 4ft wide, 6ft long and 3ft high in two experimental conditions—a baseline study without time pressure and a second manipulation with a 7-minute time limit. Multilevel analyses of data revealed that work experience, safety training and individual differences in the conscientiousness, agreeableness and openness to experience personality dimensions demonstrated significant direct associations with visual attention and superior hazard identification performance. Furthermore, residential roofers may be at a heightened risk of slip, trip, fall and hand injury hazards as a result of impaired visual attention due to time pressure. Findings have wide implications for improving safety performance and would assist organizations to assign workers to suitable tasks based on a combination of their cognitive abilities and personality variables to reduce the risk of injury among vulnerable workers whose attention may become impaired when handling multiple tasks in dynamic environments. In addition, this research is a proof of concept to construction managers on the need to prevent tight work schedules that induce time pressure and promote risk-taking, impact hazard awareness and increase workers’ susceptibility to fall and hand injury hazards.
Ceran, N (2002) Private participation in infrastructure: A risk analysis of long-term contracts in power sector, Unpublished PhD Thesis, , George Mason University.
Checherita, C D (2009) A macroeconomic analysis of investment under public-private partnerships and its policy implications—the case of developing countries, Unpublished PhD Thesis, , George Mason University.
Gholizadeh, P (2022) Analyzing accidents among specialty contractors: A data mining approach, Unpublished PhD Thesis, , George Mason University.
Hassan, M E (2013) Assessing the impact of lean/integrated project delivery system on final project success, Unpublished PhD Thesis, , George Mason University.
John Samuel, I (2023) A human-centered infrastructure asset management framework using BIM and augmented reality, Unpublished PhD Thesis, , George Mason University.
Li, Y (2023) Integrated multi-stage decision-support for enhanced infrastructure restoration under uncertainty, Unpublished PhD Thesis, , George Mason University.
Momtaz, M (2023) Damage life cycle analysis for present and future condition assessments using statistical and machine learning techniques, Unpublished PhD Thesis, , George Mason University.
Solomon, T (2021) Change blindness in the construction industry, Unpublished PhD Thesis, , George Mason University.
Zhou, W (2023) Condition state-based decision making in evolving systems: Applications in asset management and delivery, Unpublished PhD Thesis, , George Mason University.