Strategies for construction hazard recognition


Independent validation using image analysis



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STRATEGIES FOR CONSTRUCTION HAZARD RECOGNITION

Independent validation using image analysis
To obtain corroborative evidence and validate the multiple baseline results, we conducted a pre- and post-test in the periods before and after the SMQM model was introduced and integrated. We measured the proportion of hazards identified in a slide deck of construction photographs. We were careful to follow a specific and consistent data collection protocol with all 6 crews to ensure that the results were comparable. A construction scenario image with examples of identifiable hazards is shown in Figure 2.
Figure 2: Construction scenario image with examples of identifiable hazards
A random sample of 16 photographs representing varying construction scenarios was selected from a pool of more than a thousand photographs. A comprehensive list of hazards was pre- identified by the expert panel of professionals for each of the photographs. These photographs were randomly sorted into two groups one for the pretest and the other for the post-test. The proportion of hazards identified before and after the intervention was calculated as shown in Chemical – Smoke and fumes Electrical – Electrical cables Gravity – Trip potential Chemical – Propane in hose Gravity – Support stability Temperature – Fire potential from sparks Gravity – Unsupported angle Radiation – Intense light Temperature – Heat generated/Hot surfaces Pressure – Gas under pressure


97 Equation 4 and this proportion was tested for equality using the two-sample t-test for independent measures.
𝐻𝑅𝐶 =
𝐻
𝑐𝑟𝑒𝑤
𝐻
𝑐𝑟𝑒𝑤
+𝐻
𝑝𝑎𝑛𝑒𝑙
(4) Where H
crew is the number of hazards identified by the crew, and H
crew
+ H
panel is the total number of hazards identified by the crew and the research expert panel.
RESULTS
Case 1 description Modular construction project
Our first case was an in-house industrial modular construction project located in the Southeastern United States. The contracted price of the modular unit under construction was $13 million, which was about 95% complete during the time of visit. The project had accumulated more than
82,000 worker-hours and had 14 work-crews actively involved in the project during the study. During the visit upper-management assigned two safety personnel with a total of 18 years of experience to facilitate data collection and the integration of the SMQM intervention. Three crews specializing in three different trades (structural, electrical, and piping) were selected from a stratified population to participate in the multiple baseline testing. The size of each crew ranged between 8 and 14.

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