Strategies for construction hazard recognition


Figure 4: Results of Case 2- Multiple baseline study on power plant project



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STRATEGIES FOR CONSTRUCTION HAZARD RECOGNITION
Figure 4: Results of Case 2- Multiple baseline study on power plant project
Table 4: Results of Study 2- Multiple baseline study on power plant project
Predictor Coefficient Std. Error t value p value Model test
(Fcritical = 3.682) r
2
D-W test p
H-M test
(α = 0.05) p
Levene's
(α = 0.05) p
A-D
(α = 0.05)
Crew Civil
Constant
37.528 3.123 12.016 0.000
Model Iii Fiiobt
= 5.931
0.935 2.381 0.728 0.937 0.532 Time
0.352 0.802 0.439 0.669 D
14.967 3.694 4.052 0.002 SC
0.910 0.883 1.030 0.323
Crew 2: Plumbing and Piping
Constant
29.812 1.277 23.349 0.000
Model II
Fobt = 1.000
0.920 1.760 0.363 0.846 0.611 D
22.932 1.806 12.700 0.000
Crew 3: Equipment operator
Constant
41.809 1.894 22.251 0.000
Model Iii Fiiobt
= 3.847
0.961 2.381 0.794 0.511 0.512 Time
0.357 0.303 1.180 0.261 D
18.137 2.737 6.625 0.000 SC
1.293 0.724 1.787 0.099

0 20 40 60 80 100 1
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Work Period (Time -->)
Crew Crew Crew Intervention


104
CONCLUSIONS
Hazard recognition is essential to developing and implementing effective safety programs, but past research indicates that a significant proportion of hazards remain unidentified (Carter and Smith 2006). As a result, workers maybe exposed to unanticipated hazardous conditions or may unintentionally engage in unsafe work-practices without understanding adverse consequences Wilson 1989). Current hazard recognition methods, although essential, are insufficient to ensure worker safety. In response, this study presents the first attempt to incorporate retrieval mnemonics into safety planning and to develop a maturity model that effectively assists workers in recognizing and communicating hazards. Experimental field testing of the aggregate strategy with six active crews on two construction sites revealed that the method improved hazard recognition and communication by 31%.

This study represents the first attempt to empirically test the effects of a devised hazard recognition strategy in any industry using rigorous quasi-experimental field studies. We efficiently employed the underutilized, but rigorous multiple-baseline testing approach to effectively control confounding factors and allow for causal inferences. Unlike common construction research methods, the longitudinal nature of this study, (e.g. cross-sectional research, pre-test-posttest methods) reduced systematic errors and, consequently, improved the reliability and validity of measurements (Fitzmaurice et al. 2004). It should be noted that this study was well funded and well-supported by a large industry group and that such methods may not be feasible when resources and support are limited. A critical problem in such intervention studies is the observer effect in which subjects alter behavior because of being observed by researchers. Although the use of cameras and voice


105 recorders have been suggested in literature to control the observer effect (Desai 2002), it was impossible to implement due to disclosure requirements and confidentiality reasons imposed by the participating contractors. Instead, we used other methods to control observer effect such as the inclusion of in-house safety managers who were familiar to the workforce and routinely conducted observations needed for data collection. Also, it is important to note that the results indicate an improvement in HRC index despite the researchers being present for several work periods during the baseline phase before the intervention was introduced. Hence, it is unlikely that this improvement may have occurred because of the ongoing study or the increased focus on safety. An improvement was also observed in the independent non-observational corroborative study where workers were tested for their ability in hazard recognition using photographs of construction scenarios. According to Chandler and Owen (2002), longitudinal studies such as the multiple baseline testing approach where the researchers make frequent visits reduce observer impacts overtime because the researchers become more familiar to the subjects. Further, unlike Roethlisberger and
Dickson’s study (1939) where productivity improved as a result of being watched it is unlikely that the ability (skill) of workers to recognize hazards may improve due to the presence of researcher, especially given that the HRC index at the pre-intervention phase was significantly lower. Similarly, it is unlikely for hazard recognition skills to improve as a result of workers understanding the purpose of the study and responding accordingly after having received the intervention.

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