International Construction Specialty Conference of the Canadian Society for Civil Engineering (ICSC) (5th : 2015)

New multimedia safety education program : impacts on emotions, risk perceptions, and learning Bhandari, Siddharth; Hallowell, Matthew 2015-06

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5th International/11th Construction Specialty Conference 5e International/11e Conférence spécialisée sur la construction    Vancouver, British Columbia June 8 to June 10, 2015 / 8 juin au 10 juin 2015   NEW MULTIMEDIA SAFETY EDUCATION PROGRAM: IMPACTS ON EMOTIONS, RISK PERCEPTIONS, AND LEARNING  Siddharth Bhandari1, 2, Matthew Hallowell1  1 University of Colorado Boulder, United States of America 2 siddharth.bhandari@colorado.edu   Abstract: Safety training is a vital component of any construction organization’s safety program. Training offers an opportunity for the transfer of explicit and tacit knowledge of safe work practices. Often, safety training focuses on core issues faced by the specific organization and links to desired worker behaviour. Unfortunately, the typical delivery modes involve PowerPoint presentations, written safety protocols, and classroom-style settings. Such teaching modes do not facilitate active, inductive, context-based learning that is essential for effective andragogy (i.e., adult learning) and, therefore, often fail to achieve their desired objectives. This study tests the hypotheses that a new method of risk-free safety training, Live Safety Demos, increases engagement through emotional response to training activities. The technique involves demonstrating the cause and effect of actual injuries to human hands, which are the most commonly injured body part in construction. The delivery of the demos include the following key components: (1) biologically-realistic replicas of human hands that include flesh, bones, and blood networks; (2) in-person demonstrations of common injuries to worker’s hands (e.g., pinch-points between sections of pipe); (3) videos showing injuries to the replicas recorded at over 2100 frames per second to show detail; and (4) worker-led activities to design work practices that would prevent each injury type. The research was achieved with a team that included one faculty member, three students, a senior manager from the owner organization, four safety managers, and an English-to-Spanish translator. To test the aforementioned hypothesis, the research team used field-validated methods from experimental psychology to measure emotional response to the training program. Using a longitudinal A+B experiment, the demos were tested over the course of a one-week period with approximately 1,200 workers who belonged to approximately 100 crews. The results indicate a very strong emotional response to the Live Safety Demos with statistically significant changes in almost every emotion category. There was a significant increase in negative emotions, which is known to increase risk perception and decrease risk tolerance. Increase in induced activating emotions lead to a more engaged learning commitment during safety training, which increases the ability of workers to recognize more hazards. Thus, this research shows that live safety demos, although resource-intensive, has the potential to transform safety training in the construction industry. Future research is suggested to broaden the sample population and to test additional elements such as retention levels, duration of these induced emotions, communication networks, and ability to respond ad hoc to new safety environments. 218-1 1 INTRODUCTION Carter and Smith (2006) and the Center for Disease Control and Prevention (CDC 2012) suggest that construction workers lack the necessary skill set to correctly identify potential hazards at the job-site. This is a valid claim because, despite constantly improving industry standards and years of extensive research to reduce injuries, there were 4,405 fatal work-related injuries during 2013 (Bureau of Labor Statistics 2013). Furthermore, although there was a modest decline in injury rates between 2011 and 2013, there was an overall increase in fatality rates and a dramatic 7% increase in injuries sand fatalities to Hispanic workers (Bureau of Labor Statistics 2013). These trends imply that the industry could benefit from more engaging safety-training that heightens awareness of potential hazards and addresses andragogical principles of learning (Wilkins 2011).   There has been extensive research conducted to understand how people learn in occupational contexts. For example, Baddeley (1992) suggested that the working memory uses both verbal and visuals channels to process and retain information. Hence, in contrast to generic presentation-based training programs, multimedia styles of learning are theoretically more effective as they engage both visual and verbal channels. Moreover, adults seek engaging learning approaches with significance to everyday life as a motivation for learning (Lindeman 1956). This study involved the development and empirical testing of Live Safety Demos, an experiential learning program built upon the principles of Generative Theory of Multimedia Learning (Mayer 1997). As Mayer (1997, p.4) suggests, “multimedia instruction affects the degree to which learners engage in the cognitive processes required for meaningful learning within the visual and verbal information processing systems.” The Live Safety Demos were designed within this theoretical context.  The Live Safety Demos included realistic simulations of commonly occurring injuries and a concurrent explanation of the cause and effect of those injuries. To enhance andragogy, the demos involved biologically accurate replications of human hands, realistic simulation of injuries on the artificial hands, a high-speed video of the injury to illustrate detail, and in-depth conversations with the workforce. To test the effectiveness of this new form of safety training, the research team aimed to measure the extent to which the participant’s emotions change as a result of the training program. There has been substantial research that suggests that emotions play a major role in a person’s decision-making process and, thus, affect an individual’s risk perception and tolerance (Clore et. al. 1994; Keller et. al. 2006). This is the first investigation to measure emotional response to an experiential safety program despite the empirical connections between emotional response, learning, and safe work behaviour. 2 LIVE SAFETY DEMONSTRATION CREATION AND DELIVERY Researchers have found that the only major factor that affects an individual’s risk tolerance is previous personal injury history (Hallowell 2010). That is, a past injury or witnessing a severe injury to a close co-worker is the only factor that has been shown to decrease risk tolerance. Unfortunately, the implication of this finding is that someone must be injured in order for risk tolerances to change. A major objective of this research was to create a hyper-realistic demonstration of an injury that gives participants the experience of an injury without the negative consequences. In this study, we gauge change in emotional response to measure the change in the risk perception/tolerance. Drevets and Raichle (1998) showed that blood supply to brain decreased near the risk-based decision-making sections during acute induced emotional moments and Loewenstein et. al.’s (2001) research found that specific emotions sway human response in adverse situations. Previous studies have shown that people with positive emotional state have more affinity for risk (Isen and Patrick 1983). This implies that if the demonstrations induce a negative emotional state, it should lower the participant’s affinity towards risk.  An important component of the Live Safety Demos was the creation of a hyper-realistic demonstration of an injury. To achieve the goals artificial hands were created that look, feel, and respond like actual human hands (Figure 1). The hands were built using life-casting techniques primarily found in dentistry and prosthetics and include flesh with the exact properties of a human hand, an internal blood bladder and 218-2  blood network, and bones. To illustrate the level of realism achieved in the creation of the hands, Table 1 provides a complete comparison between the fabricated hand and the average adult human hand according to the Oxford Handbook of Clinical Medicine (Longmore et al. 2014). As one can see from Table 1 and Figure 1, the hands were sufficiently accurate to serve as a realistic proxy for a worker in dangerous situations.                              Figure 1: Artificial hands for Live Safety Demonstration    Table 1: Comparison between Real and Demo Hand  Properties Fabricated Hand Actual Human Hand Specific Gravity 1.07 g/cc 1.067 g/cc Hardness 10 A 10 A Tensile Strength 475 psi 421 psi Elongation at Tear 364% 245% Die B Tear Strength 102 pli 100 pli Shrinkage <0.001 in/in <0.001 in/in Bone Shear Strength 70 Mpa 52 Mpa Bone Breaking Force 280 lbs 267 lbs   To accompany the fabricated hand in a training demonstration, a video was created where the hand was injured in two modes: a falling concrete chisel and a pinch point between two sections of three inch steel pipe. A brief description of the two demonstrations is provided below.  Falling Concrete Chisel: This demonstration aimed to replicate an actual disabling injury where a carpenter dropped a one-kilogram concrete chisel when stripping concrete formwork. The falling chisel struck another worker who was working below the formwork and punctured his hand. Ultimately, there were three broken phalanges and nerve damage, which resulted in limited use of the hand. The first part of the demonstration involved educating the workers of the speed that the chisel was falling at time of impact (approximately 43 kilometers per hour), the impact area of the chisel (0.30 cm2), and the overall pressure on the hand (48 MPa). To achieve a memorable mnemonic, a discussion related to speed, sharpness, and weight was held among the workers as prompted by the instructors. Following this discussion, the resilience of the human hand was described. Specifically, the human hand can withstand approximately 1 MPa without significant damage. Given the load on and resistance of the hand, the 218-3  workers were asked to predict what would happen to a gloved and ungloved hand. Once this discussion was complete, a high-speed video was shown with both a gloved and ungloved hand, illustrating dramatic differences in outcome. The first demonstration session concluded with a discussion of the safe work practices for the type of work demonstrated.  Pinch Points between Two 3-Inch Steel Pipes: The second demonstration focused on an injury where a worker was in the process of connecting a 3-inch steel pipe to a pipe couple when the pipe sling shifted and the worker’s hand was pinched between the pipe and the couple. The result of the injury was a deep flesh wound and nerve damage. Similar to the falling chisel demo, the first step of the demonstration was to present the physics behind the injury. This included the momentum of the moving pipe, the contact area of the pipe, and the overall pressure on the hand. Once the resistance of the hand to pressure (1 MPa), the workers predicted the outcome for a gloved and ungloved hand and the associated videos were shown that depicted both scenarios. Also, a discussion was held regarding the potential outcomes of a heavier, sharper, or faster moving pipe. The session also concluded with a discussion of safe work practices for installing steel pipe.   Figure 2: Screen capture of a gloved hand being struck by a falling concrete chisel. 3 RESEARCH METHODS  As previously indicted, our research goal for this study was to measure emotional response to the active, experience-based demonstrations that incorporated theory of andragogy. In order to achieve this goal, we delivered the demos to 1,200 construction workers in a one-week period in Kenedy, Texas through sixteen different sessions (average of 75 workers per session). The same delivery technique and the same instructors were used in each session to ensure consistency. Additionally, a set script was followed to enhance reliability and replicability of the study and all instructors followed a set script.   In order to measure emotional response, we implemented a before and after (AB) experimental design where Rottenberg et al.’s (2007) emotional polarity questionnaire was used to survey workers before and after the Live Demos. On this questionnaire, the participants were asked to rate their emotions on 8-point scale. In addition to Rottenberg et al.’s (2007) questionnaire, we considered various alternative methods to gauge the emotional response such as the Balloon Analogue Risk Task (BART), which is a laboratory based computerized self-reporting risk assessment tool (Lejuez, C. W., et al. 2002). We decided to pursue the paper form of the Rottenberg et al. (2007) questionnaire because of our sample size and time and resource constraints in the field. The emotion questionnaire was quantitative with one optional qualitative question, which requested comments or other emotions.   218-4  Out of the 1200 workers, 489 (40%) participated in the surveys as participation was voluntary and uncompensated. The surveys were administered in paper form and all the participants were provided sufficient time and resources to complete the surveys both times. Surveys were provided to the participants immediately before and immediately after the Live Demonstrations and no more than a 3-minute time lag was allowed as suggested by Verduyn et. al. (2009 & 2011).   The following protocol was implemented when delivering the live safety demos and collecting data: 1. Introduction to the topic and welcome 2. Emotions survey with demographics 3. Delivery of dropped object demo or pinch point demo 4. Delivery of the second demo (one not delivered in step 3) 5. Emotions survey and open-ended qualitative question 6. Closing remarks  As previously indicated, all demos were delivered to workers in Kenedy, Texas. Subjects involved had no knowledge of the demos prior to the session. Some work crews in this region were Spanish-only-speaking while others were English-only-speaking. We delivered the demonstrations in both English and Spanish, as members of the research team were bilingual. The participants were allowed to choose between the English or Spanish session. Seventy-five percent of the participants attended English sessions and 25% attended Spanish sessions.  To ensure anonymity, the participants were not required to enter their names or any direct identification. Instead, workers used a personal password that was not linked to their name, trade, or employer. For demographic questions, we also offered participants the opportunity to decline to answer a question if they felt uncomfortable providing the information. In our sample, 69% were married, 50% had witnessed a severe injury first-hand, 23% had been injured (recordable injury), 6% have a bachelor’s degree or more, 32% have some college education, 57% completed high school, 4% have no education, 70% were Hispanic, and 30% were Caucasian. The average age of the participants was 38 years and, interestingly, less than 5% of the workers were female. Figure 3 illustrates the overall research process including development, data collection, statistical comparisons, and conclusions. 4 RESULTS  In order to study the emotional responses, the data were analyzed using paired t-tests. Paired t-tests were used because we have two nominal variables and one measurement variable (McDonald, J.H. 2014). One nominal variable represents the participant and other is the “pre” and “post” emotional state recorded via their responses. Table 2 shows the results of the emotional change for the entire sample. We considered the change to be significant at 95% confidence (p <0.05). Based on the results shown in Table 2, there was a large and statistically significant change in the following emotions: confusion, disgust, guilt, fear, happiness, joy, love, pride, sadness, surprise, and unhappiness. The greatest change occurred in fear and surprise. We can also say here that the ‘negative’ emotions or those associated with being serious, sombre, and vulnerable increased significantly.    Table 3 shows the emotional response of Caucasians and Hispanic workers separately. It also shows that Caucasians showed a significant change in confusion, fear, happiness, joy, love, pride, sadness, shame, and surprise whereas Hispanic workers had a significant change in anger, confusion, fear, guilt, happiness, joy, love, pride, sadness, surprise, and unhappiness. This is further discussed in the next section in the context of this paper.         218-5                     Figure 3: Overview of research process     Table 2: Changes in Emotional State due to Live Safety Demo Note: The plus and minus sign represent the increase and decrease of that particular emotion.    Emotion Average Before Average After Difference P-value Amusement 4.06 4.16 2%  0.319 Anger 1.65 1.53 -7%  0.154 Anxiety 1.82 1.94 7%  0.092 Confusion 1.68 1.45 -14%  <0.01 Disgust 1.44 1.62 12%  0.044 Embarrassment 1.52 1.45 -4%  0.401 Fear 1.45 2.13 47%          <0.01 Guilt 1.36 1.54 13%  0.013 Happiness 5.68 4.05 -29%          <0.01 Interest 6.11 6.00 -2%  0.322 Joy 5.43 4.07 -25%  <0.01 Love 5.29 3.73 -29%  <0.01 Pride 5.61 4.33 -23%  <0.01 Sadness 1.51 2.15 43%  <0.01 Shame 1.57 1.69 7%  0.277 Surprise 2.66 3.91 47%  <0.01 Unhappiness 1.47 1.74 18%  0.007 Survey participant’s perturbed condition Evaluate past injuries Re-create injuries in live demos Survey participant’s baseline condition Deliver live safety demos Perform statistical comparison Interpret results in light of psychology and learning literature 218-6   Table 3: Results from English and Spanish Surveys  Emotions Average Before (Caucasian) Average After (Caucasian) Difference (%) P-value Average Before (Hispanic) Average After (Hispanic) Difference (%) P-value Amusement 3.97 3.79 -5% 0.80 4.10 4.29 5% 0.20 Anger 1.64 1.59 -3% 0.91 1.63 1.45 -11% 0.04 Anxiety 1.85 2.01 9% 0.13 1.78 1.64 4% 0.40 Confusion 1.65 1.38 -16% 0.009 1.44 2.20 -12% 0.01 Disgust 1.50 1.71 14% 0.17 1.38 1.53 11% 0.15 Embarrassment 1.36 1.28 -6% 0.42 1.57 1.46 -7% 0.36 Fear 1.31 2.25 72% <0.001 1.49 2.04 36% <0.001 Guilt 1.26 1.39 10% 0.12 1.37 1.57 14% 0.04 Happiness 5.52 3.85 -30% <0.001 5.78 4.23 -27% <0.001 Interest 6.00 5.96 -1% 0.77 6.19 6.05 -2% 0.31 Joy 4.90 3.58 -27% <0.001 5.66 4.40 -22% <0.001 Love 5.00 3.31 -34% <0.001 5.41 3.95 -27% <0.001 Pride 6.12 4.80 -22% <0.001 5.40 4.15 -23% <0.001 Sadness 1.52 2.11 39%   0.001 1.48 2.08 40% <0.001 Shame 1.30 1.68 30%   0.004 1.66 1.66 0% 0.62 Surprise 2.28 3.89 71% <0.001 2.76 3.97 44% <0.001 Unhappiness 1.54 1.69 10% 0.28 1.40 1.67 20% 0.012   218-7  5 DISCUSSION AND CONCLUSIONS Key takeaways from the data are that emotions such as anger, anxiety, confusion, disgust, embarrassment, fear, guilt, happiness, joy, pride, sadness, love, surprise, and unhappiness showed a fluctuation in the same direction. Both Hispanic and Caucasian workers registered an aggregate decrease in their positive emotions such as happiness (-29%), joy (-25%), love (-29%), and pride (-23%) and an increase in negative emotions unhappiness (18%), fear (47%), surprise (47%), and sadness (43%). When viewed separately, Caucasian surveys showed statistically significant change in ‘fear’ and Hispanic surveys showed statistically significant change in ‘anger’ and ‘fear’ (activating).   The implications of the observed emotional changes on learning are significant. Pekrun (2006) explains that negative emotions increase extrinsic motivation to learn and avoid failure. Specifically, Pekrun et. al. (2002, p.97) claims that “Emotions may trigger, sustain, or reduce academic motivation and related volitional processes.” They also suggest that changes in positive emotions (happiness, joy) and negative emotions (anxiety, anger) can be activating and may facilitate learning. Bless et. al. (1996) further proposed that negative emotions lead to more detail-oriented and cautious approach towards solving problems, which could be preferable to construction safety. Thus, it can be concluded that Live Safety Demos is an improvement over the current training style for the construction crews because workers will be more detail-oriented and cautious as they troubleshoot safety problems and plan for safe work.   In addition to enhanced learning, the changes in emotions are linked to decreased risk taking. As mentioned in the introduction, it is overwhelmingly accepted that negative emotions lead to a less affinity towards taking risk (Öhman and Mineka 2001; Clore et. al. 1994; Keller et. al. 2006). Taylor and Brown (1988) claimed that “false optimism” leads to a fake sense of security towards any situation thus, making them less cautious and oblivious to hidden risks. Additionally, it should be noted that negative emotional states are strongly associated with an increase in risk perception (i.e., workers perceive greater risk in their environment) and reductions in risk-taking behaviour (Gruber et. al. 2011). Results in Tables 3 and 4 also show that there is a significant decrease in joy and interest emotions, which leads a decrease in safety valuations of situations (Izard 1977). Based on these established theories, we believe that the Live Safety Demos makes construction workers perceive more risk, which should decrease sense of false optimism and risk taking behavior.   There were some interesting differences in the emotional reactions between Hispanic and Caucasian workers. Firstly, Caucasian workers experienced greater increases in anxiety, fear, surprise, shame, and disgust than their Hispanic counterparts. Hispanic workers, on the other hand, experienced greater relative changes (increase) in amusement unhappiness, and guilt. Hispanic workers were less angry and less happy while Caucasian workers were much more fearful and surprised. Matsumoto et. al. 1988 showed that there are cultural differences in self-reporting of any emotional experience, which include intensity, control, and duration of emotion. However, these induced emotions though varying in intensity, need to correlate positively with cognition among these workers. Since the changes in emotions are all in the same direction, there is no indication that the differences in emotional response would have any serious implications for risk taking or safety learning. Figure 4 outlines some of the major changes due to Live Safety Demos on the participants and the implications of those changes.            218-8 Baddeley, A.1992. Working memory: The interface between memory and cognition. Journal of cognitive neuroscience, 4(3), 281-288. United States of America. United States Department of Labor. Bureau of Labor Statistics. Census of Fatal Occupational Injuries Summary, 2013. N.p., 11 Sept. 2014. Web. 6 Jan. 2015. <http://www.bls.gov/news.release/cfoi.nr0.htm>. Carter, G., and Smith, S. D. 2006. Safety hazard identification on construction projects. Journal of Construction Engineering and Management, 132(2), 197-205. Clore, G. L., Schwarz, N., and Conway, M. 1994. Affective causes and consequences of social information processing. Handbook of social cognition,1, 323-417. Drevets, W. C., and Raichle, M. E. 199). Reciprocal suppression of regional cerebral blood flow during emotional versus higher cognitive processes: Implications for interactions between emotion and cognition. Cognition and emotion, 12(3), 353-385. Gruber, J., Mauss, I. B., and Tamir, M. 2011. A dark side of happiness? How, when, and why happiness is not always good. Perspectives on Psychological Science, 6(3), 222-233. Hallowell, M. 2010. Safety risk perception in construction companies in the Pacific Northwest of the USA. Construction management and economics, 28(4), 403-413. Izard, C. E. (1977). Human emotions (Vol. 17). C. E. Izard (Ed.). New York: Plenum Press. Isen, A. M., and Patrick, R. 1983. The effect of positive feelings on risk taking: When the chips are down. Organizational Behavior and Human Performance, 31(2), 194-202. Keller, C., Siegrist, M., and Gutscher, H. 2006. The role of the affect and availability heuristics in risk communication. Risk Analysis, 26(3), 631-639. Lejuez, C. W. Read, J. P. Kahler, C. W. Richards, J. B. Ramsey, S. E. Stuart, G. L. Strong, D. R. and Brown, R. A. 2002. Evaluation of a behavioral measure of risk taking: the Balloon Analogue Risk Task (BART). Journal of Experimental Psychology: Applied, 8(2), 75. Lindeman, E. C., Gessner, R., and Otto, M. (956. The democratic man: The selected writings of Eduard C. Lindeman (R. Gessner, Ed.). Boston: Beacon, USA. Loewenstein, G. F., Weber, E. U., Hsee, C. K., and Welch, N. 2001. Risk as feelings. Psychological bulletin, 127(2), 267-286. Longmore, M., Wilkinson, I., Baldwin, A., & Wallin, E. (2014). Oxford handbook of clinical medicine. Oxford University Press. Mayer, R. E. 1997. Multimedia learning: Are we asking the right questions? Educational psychologist, 32(1), 1-19. Matsumoto, D., Kudoh, T., Scherer, K., and Wallbott, H. 1988. Antecedents of and reactions to emotions in the United States and Japan. Journal of Cross-Cultural Psychology, 19(3), 267-286. McDonald, J.H. 2014. Handbook of Biological Statistics. 3rd ed., Sparky House Publishing, Baltimore,  Maryland, USA. This web page contains the content of pages 180-185 in the printed version. Öhman, A., and Mineka, S. 2001. Fears, phobias, and preparedness: toward an evolved module of fear and fear learning. Psychological review, 108(3), 483. Pekrun, R. 2006. The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18(4), 315-341. Pekrun, R., Goetz, T., Titz, W., and Perry, R. P. (2002). Academic emotions in students' self-regulated learning and achievement: A program of qualitative and quantitative research. Educational psychologist, 37(2), 91-105. Rottenberg, J., Ray, R. D., & Gross, J. J. (2007). Emotion elicitation using films.The handbook of emotion elicitation and assessment; London: Oxford University Press, 9. Taylor, S. E., and Brown, J. D. 1988. Illusion and well-being: a social psychological perspective on mental health. Psychological bulletin, 103(2), 193-210. Wilkins, J. R. 2011. Construction workers’ perceptions of health and safety training programmes. Construction Management and Economics, 29(10), 1017-1026. Verduyn, P., Van Mechelen, I., and Tuerlinckx, F. 2011. The relation between event processing and the duration of emotional experience. Emotion, 11(1), 20-28. Verduyn, P., Van Mechelen, I., Tuerlinckx, F., Meers, K., and Van Coillie, H. 2009. Intensity profiles of emotional experience over time. Cognition and Emotion, 23(7), 1427-1443.   218-10   5th International/11th Construction Specialty Conference 5e International/11e Conférence spécialisée sur la construction    Vancouver, British Columbia June 8 to June 10, 2015 / 8 juin au 10 juin 2015   NEW MULTIMEDIA SAFETY EDUCATION PROGRAM: IMPACTS ON EMOTIONS, RISK PERCEPTIONS, AND LEARNING  Siddharth Bhandari1, 2, Matthew Hallowell1  1 University of Colorado Boulder, United States of America 2 siddharth.bhandari@colorado.edu   Abstract: Safety training is a vital component of any construction organization’s safety program. Training offers an opportunity for the transfer of explicit and tacit knowledge of safe work practices. Often, safety training focuses on core issues faced by the specific organization and links to desired worker behaviour. Unfortunately, the typical delivery modes involve PowerPoint presentations, written safety protocols, and classroom-style settings. Such teaching modes do not facilitate active, inductive, context-based learning that is essential for effective andragogy (i.e., adult learning) and, therefore, often fail to achieve their desired objectives. This study tests the hypotheses that a new method of risk-free safety training, Live Safety Demos, increases engagement through emotional response to training activities. The technique involves demonstrating the cause and effect of actual injuries to human hands, which are the most commonly injured body part in construction. The delivery of the demos include the following key components: (1) biologically-realistic replicas of human hands that include flesh, bones, and blood networks; (2) in-person demonstrations of common injuries to worker’s hands (e.g., pinch-points between sections of pipe); (3) videos showing injuries to the replicas recorded at over 2100 frames per second to show detail; and (4) worker-led activities to design work practices that would prevent each injury type. The research was achieved with a team that included one faculty member, three students, a senior manager from the owner organization, four safety managers, and an English-to-Spanish translator. To test the aforementioned hypothesis, the research team used field-validated methods from experimental psychology to measure emotional response to the training program. Using a longitudinal A+B experiment, the demos were tested over the course of a one-week period with approximately 1,200 workers who belonged to approximately 100 crews. The results indicate a very strong emotional response to the Live Safety Demos with statistically significant changes in almost every emotion category. There was a significant increase in negative emotions, which is known to increase risk perception and decrease risk tolerance. Increase in induced activating emotions lead to a more engaged learning commitment during safety training, which increases the ability of workers to recognize more hazards. Thus, this research shows that live safety demos, although resource-intensive, has the potential to transform safety training in the construction industry. Future research is suggested to broaden the sample population and to test additional elements such as retention levels, duration of these induced emotions, communication networks, and ability to respond ad hoc to new safety environments. 218-1 1 INTRODUCTION Carter and Smith (2006) and the Center for Disease Control and Prevention (CDC 2012) suggest that construction workers lack the necessary skill set to correctly identify potential hazards at the job-site. This is a valid claim because, despite constantly improving industry standards and years of extensive research to reduce injuries, there were 4,405 fatal work-related injuries during 2013 (Bureau of Labor Statistics 2013). Furthermore, although there was a modest decline in injury rates between 2011 and 2013, there was an overall increase in fatality rates and a dramatic 7% increase in injuries sand fatalities to Hispanic workers (Bureau of Labor Statistics 2013). These trends imply that the industry could benefit from more engaging safety-training that heightens awareness of potential hazards and addresses andragogical principles of learning (Wilkins 2011).   There has been extensive research conducted to understand how people learn in occupational contexts. For example, Baddeley (1992) suggested that the working memory uses both verbal and visuals channels to process and retain information. Hence, in contrast to generic presentation-based training programs, multimedia styles of learning are theoretically more effective as they engage both visual and verbal channels. Moreover, adults seek engaging learning approaches with significance to everyday life as a motivation for learning (Lindeman 1956). This study involved the development and empirical testing of Live Safety Demos, an experiential learning program built upon the principles of Generative Theory of Multimedia Learning (Mayer 1997). As Mayer (1997, p.4) suggests, “multimedia instruction affects the degree to which learners engage in the cognitive processes required for meaningful learning within the visual and verbal information processing systems.” The Live Safety Demos were designed within this theoretical context.  The Live Safety Demos included realistic simulations of commonly occurring injuries and a concurrent explanation of the cause and effect of those injuries. To enhance andragogy, the demos involved biologically accurate replications of human hands, realistic simulation of injuries on the artificial hands, a high-speed video of the injury to illustrate detail, and in-depth conversations with the workforce. To test the effectiveness of this new form of safety training, the research team aimed to measure the extent to which the participant’s emotions change as a result of the training program. There has been substantial research that suggests that emotions play a major role in a person’s decision-making process and, thus, affect an individual’s risk perception and tolerance (Clore et. al. 1994; Keller et. al. 2006). This is the first investigation to measure emotional response to an experiential safety program despite the empirical connections between emotional response, learning, and safe work behaviour. 2 LIVE SAFETY DEMONSTRATION CREATION AND DELIVERY Researchers have found that the only major factor that affects an individual’s risk tolerance is previous personal injury history (Hallowell 2010). That is, a past injury or witnessing a severe injury to a close co-worker is the only factor that has been shown to decrease risk tolerance. Unfortunately, the implication of this finding is that someone must be injured in order for risk tolerances to change. A major objective of this research was to create a hyper-realistic demonstration of an injury that gives participants the experience of an injury without the negative consequences. In this study, we gauge change in emotional response to measure the change in the risk perception/tolerance. Drevets and Raichle (1998) showed that blood supply to brain decreased near the risk-based decision-making sections during acute induced emotional moments and Loewenstein et. al.’s (2001) research found that specific emotions sway human response in adverse situations. Previous studies have shown that people with positive emotional state have more affinity for risk (Isen and Patrick 1983). This implies that if the demonstrations induce a negative emotional state, it should lower the participant’s affinity towards risk.  An important component of the Live Safety Demos was the creation of a hyper-realistic demonstration of an injury. To achieve the goals artificial hands were created that look, feel, and respond like actual human hands (Figure 1). The hands were built using life-casting techniques primarily found in dentistry and prosthetics and include flesh with the exact properties of a human hand, an internal blood bladder and 218-2  blood network, and bones. To illustrate the level of realism achieved in the creation of the hands, Table 1 provides a complete comparison between the fabricated hand and the average adult human hand according to the Oxford Handbook of Clinical Medicine (Longmore et al. 2014). As one can see from Table 1 and Figure 1, the hands were sufficiently accurate to serve as a realistic proxy for a worker in dangerous situations.                              Figure 1: Artificial hands for Live Safety Demonstration    Table 1: Comparison between Real and Demo Hand  Properties Fabricated Hand Actual Human Hand Specific Gravity 1.07 g/cc 1.067 g/cc Hardness 10 A 10 A Tensile Strength 475 psi 421 psi Elongation at Tear 364% 245% Die B Tear Strength 102 pli 100 pli Shrinkage <0.001 in/in <0.001 in/in Bone Shear Strength 70 Mpa 52 Mpa Bone Breaking Force 280 lbs 267 lbs   To accompany the fabricated hand in a training demonstration, a video was created where the hand was injured in two modes: a falling concrete chisel and a pinch point between two sections of three inch steel pipe. A brief description of the two demonstrations is provided below.  Falling Concrete Chisel: This demonstration aimed to replicate an actual disabling injury where a carpenter dropped a one-kilogram concrete chisel when stripping concrete formwork. The falling chisel struck another worker who was working below the formwork and punctured his hand. Ultimately, there were three broken phalanges and nerve damage, which resulted in limited use of the hand. The first part of the demonstration involved educating the workers of the speed that the chisel was falling at time of impact (approximately 43 kilometers per hour), the impact area of the chisel (0.30 cm2), and the overall pressure on the hand (48 MPa). To achieve a memorable mnemonic, a discussion related to speed, sharpness, and weight was held among the workers as prompted by the instructors. Following this discussion, the resilience of the human hand was described. Specifically, the human hand can withstand approximately 1 MPa without significant damage. Given the load on and resistance of the hand, the 218-3  workers were asked to predict what would happen to a gloved and ungloved hand. Once this discussion was complete, a high-speed video was shown with both a gloved and ungloved hand, illustrating dramatic differences in outcome. The first demonstration session concluded with a discussion of the safe work practices for the type of work demonstrated.  Pinch Points between Two 3-Inch Steel Pipes: The second demonstration focused on an injury where a worker was in the process of connecting a 3-inch steel pipe to a pipe couple when the pipe sling shifted and the worker’s hand was pinched between the pipe and the couple. The result of the injury was a deep flesh wound and nerve damage. Similar to the falling chisel demo, the first step of the demonstration was to present the physics behind the injury. This included the momentum of the moving pipe, the contact area of the pipe, and the overall pressure on the hand. Once the resistance of the hand to pressure (1 MPa), the workers predicted the outcome for a gloved and ungloved hand and the associated videos were shown that depicted both scenarios. Also, a discussion was held regarding the potential outcomes of a heavier, sharper, or faster moving pipe. The session also concluded with a discussion of safe work practices for installing steel pipe.   Figure 2: Screen capture of a gloved hand being struck by a falling concrete chisel. 3 RESEARCH METHODS  As previously indicted, our research goal for this study was to measure emotional response to the active, experience-based demonstrations that incorporated theory of andragogy. In order to achieve this goal, we delivered the demos to 1,200 construction workers in a one-week period in Kenedy, Texas through sixteen different sessions (average of 75 workers per session). The same delivery technique and the same instructors were used in each session to ensure consistency. Additionally, a set script was followed to enhance reliability and replicability of the study and all instructors followed a set script.   In order to measure emotional response, we implemented a before and after (AB) experimental design where Rottenberg et al.’s (2007) emotional polarity questionnaire was used to survey workers before and after the Live Demos. On this questionnaire, the participants were asked to rate their emotions on 8-point scale. In addition to Rottenberg et al.’s (2007) questionnaire, we considered various alternative methods to gauge the emotional response such as the Balloon Analogue Risk Task (BART), which is a laboratory based computerized self-reporting risk assessment tool (Lejuez, C. W., et al. 2002). We decided to pursue the paper form of the Rottenberg et al. (2007) questionnaire because of our sample size and time and resource constraints in the field. The emotion questionnaire was quantitative with one optional qualitative question, which requested comments or other emotions.   218-4  Out of the 1200 workers, 489 (40%) participated in the surveys as participation was voluntary and uncompensated. The surveys were administered in paper form and all the participants were provided sufficient time and resources to complete the surveys both times. Surveys were provided to the participants immediately before and immediately after the Live Demonstrations and no more than a 3-minute time lag was allowed as suggested by Verduyn et. al. (2009 & 2011).   The following protocol was implemented when delivering the live safety demos and collecting data: 1. Introduction to the topic and welcome 2. Emotions survey with demographics 3. Delivery of dropped object demo or pinch point demo 4. Delivery of the second demo (one not delivered in step 3) 5. Emotions survey and open-ended qualitative question 6. Closing remarks  As previously indicated, all demos were delivered to workers in Kenedy, Texas. Subjects involved had no knowledge of the demos prior to the session. Some work crews in this region were Spanish-only-speaking while others were English-only-speaking. We delivered the demonstrations in both English and Spanish, as members of the research team were bilingual. The participants were allowed to choose between the English or Spanish session. Seventy-five percent of the participants attended English sessions and 25% attended Spanish sessions.  To ensure anonymity, the participants were not required to enter their names or any direct identification. Instead, workers used a personal password that was not linked to their name, trade, or employer. For demographic questions, we also offered participants the opportunity to decline to answer a question if they felt uncomfortable providing the information. In our sample, 69% were married, 50% had witnessed a severe injury first-hand, 23% had been injured (recordable injury), 6% have a bachelor’s degree or more, 32% have some college education, 57% completed high school, 4% have no education, 70% were Hispanic, and 30% were Caucasian. The average age of the participants was 38 years and, interestingly, less than 5% of the workers were female. Figure 3 illustrates the overall research process including development, data collection, statistical comparisons, and conclusions. 4 RESULTS  In order to study the emotional responses, the data were analyzed using paired t-tests. Paired t-tests were used because we have two nominal variables and one measurement variable (McDonald, J.H. 2014). One nominal variable represents the participant and other is the “pre” and “post” emotional state recorded via their responses. Table 2 shows the results of the emotional change for the entire sample. We considered the change to be significant at 95% confidence (p <0.05). Based on the results shown in Table 2, there was a large and statistically significant change in the following emotions: confusion, disgust, guilt, fear, happiness, joy, love, pride, sadness, surprise, and unhappiness. The greatest change occurred in fear and surprise. We can also say here that the ‘negative’ emotions or those associated with being serious, sombre, and vulnerable increased significantly.    Table 3 shows the emotional response of Caucasians and Hispanic workers separately. It also shows that Caucasians showed a significant change in confusion, fear, happiness, joy, love, pride, sadness, shame, and surprise whereas Hispanic workers had a significant change in anger, confusion, fear, guilt, happiness, joy, love, pride, sadness, surprise, and unhappiness. This is further discussed in the next section in the context of this paper.         218-5                     Figure 3: Overview of research process     Table 2: Changes in Emotional State due to Live Safety Demo Note: The plus and minus sign represent the increase and decrease of that particular emotion.    Emotion Average Before Average After Difference P-value Amusement 4.06 4.16 2%  0.319 Anger 1.65 1.53 -7%  0.154 Anxiety 1.82 1.94 7%  0.092 Confusion 1.68 1.45 -14%  <0.01 Disgust 1.44 1.62 12%  0.044 Embarrassment 1.52 1.45 -4%  0.401 Fear 1.45 2.13 47%          <0.01 Guilt 1.36 1.54 13%  0.013 Happiness 5.68 4.05 -29%          <0.01 Interest 6.11 6.00 -2%  0.322 Joy 5.43 4.07 -25%  <0.01 Love 5.29 3.73 -29%  <0.01 Pride 5.61 4.33 -23%  <0.01 Sadness 1.51 2.15 43%  <0.01 Shame 1.57 1.69 7%  0.277 Surprise 2.66 3.91 47%  <0.01 Unhappiness 1.47 1.74 18%  0.007 Survey participant’s perturbed condition Evaluate past injuries Re-create injuries in live demos Survey participant’s baseline condition Deliver live safety demos Perform statistical comparison Interpret results in light of psychology and learning literature 218-6   Table 3: Results from English and Spanish Surveys  Emotions Average Before (Caucasian) Average After (Caucasian) Difference (%) P-value Average Before (Hispanic) Average After (Hispanic) Difference (%) P-value Amusement 3.97 3.79 -5% 0.80 4.10 4.29 5% 0.20 Anger 1.64 1.59 -3% 0.91 1.63 1.45 -11% 0.04 Anxiety 1.85 2.01 9% 0.13 1.78 1.64 4% 0.40 Confusion 1.65 1.38 -16% 0.009 1.44 2.20 -12% 0.01 Disgust 1.50 1.71 14% 0.17 1.38 1.53 11% 0.15 Embarrassment 1.36 1.28 -6% 0.42 1.57 1.46 -7% 0.36 Fear 1.31 2.25 72% <0.001 1.49 2.04 36% <0.001 Guilt 1.26 1.39 10% 0.12 1.37 1.57 14% 0.04 Happiness 5.52 3.85 -30% <0.001 5.78 4.23 -27% <0.001 Interest 6.00 5.96 -1% 0.77 6.19 6.05 -2% 0.31 Joy 4.90 3.58 -27% <0.001 5.66 4.40 -22% <0.001 Love 5.00 3.31 -34% <0.001 5.41 3.95 -27% <0.001 Pride 6.12 4.80 -22% <0.001 5.40 4.15 -23% <0.001 Sadness 1.52 2.11 39%   0.001 1.48 2.08 40% <0.001 Shame 1.30 1.68 30%   0.004 1.66 1.66 0% 0.62 Surprise 2.28 3.89 71% <0.001 2.76 3.97 44% <0.001 Unhappiness 1.54 1.69 10% 0.28 1.40 1.67 20% 0.012   218-7  5 DISCUSSION AND CONCLUSIONS Key takeaways from the data are that emotions such as anger, anxiety, confusion, disgust, embarrassment, fear, guilt, happiness, joy, pride, sadness, love, surprise, and unhappiness showed a fluctuation in the same direction. Both Hispanic and Caucasian workers registered an aggregate decrease in their positive emotions such as happiness (-29%), joy (-25%), love (-29%), and pride (-23%) and an increase in negative emotions unhappiness (18%), fear (47%), surprise (47%), and sadness (43%). When viewed separately, Caucasian surveys showed statistically significant change in ‘fear’ and Hispanic surveys showed statistically significant change in ‘anger’ and ‘fear’ (activating).   The implications of the observed emotional changes on learning are significant. Pekrun (2006) explains that negative emotions increase extrinsic motivation to learn and avoid failure. Specifically, Pekrun et. al. (2002, p.97) claims that “Emotions may trigger, sustain, or reduce academic motivation and related volitional processes.” They also suggest that changes in positive emotions (happiness, joy) and negative emotions (anxiety, anger) can be activating and may facilitate learning. Bless et. al. (1996) further proposed that negative emotions lead to more detail-oriented and cautious approach towards solving problems, which could be preferable to construction safety. Thus, it can be concluded that Live Safety Demos is an improvement over the current training style for the construction crews because workers will be more detail-oriented and cautious as they troubleshoot safety problems and plan for safe work.   In addition to enhanced learning, the changes in emotions are linked to decreased risk taking. As mentioned in the introduction, it is overwhelmingly accepted that negative emotions lead to a less affinity towards taking risk (Öhman and Mineka 2001; Clore et. al. 1994; Keller et. al. 2006). Taylor and Brown (1988) claimed that “false optimism” leads to a fake sense of security towards any situation thus, making them less cautious and oblivious to hidden risks. Additionally, it should be noted that negative emotional states are strongly associated with an increase in risk perception (i.e., workers perceive greater risk in their environment) and reductions in risk-taking behaviour (Gruber et. al. 2011). Results in Tables 3 and 4 also show that there is a significant decrease in joy and interest emotions, which leads a decrease in safety valuations of situations (Izard 1977). Based on these established theories, we believe that the Live Safety Demos makes construction workers perceive more risk, which should decrease sense of false optimism and risk taking behavior.   There were some interesting differences in the emotional reactions between Hispanic and Caucasian workers. Firstly, Caucasian workers experienced greater increases in anxiety, fear, surprise, shame, and disgust than their Hispanic counterparts. Hispanic workers, on the other hand, experienced greater relative changes (increase) in amusement unhappiness, and guilt. Hispanic workers were less angry and less happy while Caucasian workers were much more fearful and surprised. Matsumoto et. al. 1988 showed that there are cultural differences in self-reporting of any emotional experience, which include intensity, control, and duration of emotion. However, these induced emotions though varying in intensity, need to correlate positively with cognition among these workers. Since the changes in emotions are all in the same direction, there is no indication that the differences in emotional response would have any serious implications for risk taking or safety learning. Figure 4 outlines some of the major changes due to Live Safety Demos on the participants and the implications of those changes.            218-8 Baddeley, A.1992. Working memory: The interface between memory and cognition. Journal of cognitive neuroscience, 4(3), 281-288. United States of America. United States Department of Labor. Bureau of Labor Statistics. Census of Fatal Occupational Injuries Summary, 2013. N.p., 11 Sept. 2014. Web. 6 Jan. 2015. <http://www.bls.gov/news.release/cfoi.nr0.htm>. Carter, G., and Smith, S. D. 2006. Safety hazard identification on construction projects. Journal of Construction Engineering and Management, 132(2), 197-205. Clore, G. L., Schwarz, N., and Conway, M. 1994. Affective causes and consequences of social information processing. Handbook of social cognition,1, 323-417. Drevets, W. C., and Raichle, M. E. 199). Reciprocal suppression of regional cerebral blood flow during emotional versus higher cognitive processes: Implications for interactions between emotion and cognition. Cognition and emotion, 12(3), 353-385. Gruber, J., Mauss, I. B., and Tamir, M. 2011. A dark side of happiness? How, when, and why happiness is not always good. Perspectives on Psychological Science, 6(3), 222-233. Hallowell, M. 2010. Safety risk perception in construction companies in the Pacific Northwest of the USA. Construction management and economics, 28(4), 403-413. Izard, C. E. (1977). Human emotions (Vol. 17). C. E. Izard (Ed.). New York: Plenum Press. Isen, A. M., and Patrick, R. 1983. The effect of positive feelings on risk taking: When the chips are down. Organizational Behavior and Human Performance, 31(2), 194-202. Keller, C., Siegrist, M., and Gutscher, H. 2006. The role of the affect and availability heuristics in risk communication. Risk Analysis, 26(3), 631-639. Lejuez, C. W. Read, J. P. Kahler, C. W. Richards, J. B. Ramsey, S. E. Stuart, G. L. Strong, D. R. and Brown, R. A. 2002. Evaluation of a behavioral measure of risk taking: the Balloon Analogue Risk Task (BART). Journal of Experimental Psychology: Applied, 8(2), 75. Lindeman, E. C., Gessner, R., and Otto, M. (956. The democratic man: The selected writings of Eduard C. Lindeman (R. Gessner, Ed.). Boston: Beacon, USA. Loewenstein, G. F., Weber, E. U., Hsee, C. K., and Welch, N. 2001. Risk as feelings. Psychological bulletin, 127(2), 267-286. Longmore, M., Wilkinson, I., Baldwin, A., & Wallin, E. (2014). Oxford handbook of clinical medicine. Oxford University Press. Mayer, R. E. 1997. Multimedia learning: Are we asking the right questions? Educational psychologist, 32(1), 1-19. Matsumoto, D., Kudoh, T., Scherer, K., and Wallbott, H. 1988. Antecedents of and reactions to emotions in the United States and Japan. Journal of Cross-Cultural Psychology, 19(3), 267-286. McDonald, J.H. 2014. Handbook of Biological Statistics. 3rd ed., Sparky House Publishing, Baltimore,  Maryland, USA. This web page contains the content of pages 180-185 in the printed version. Öhman, A., and Mineka, S. 2001. Fears, phobias, and preparedness: toward an evolved module of fear and fear learning. Psychological review, 108(3), 483. Pekrun, R. 2006. The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18(4), 315-341. Pekrun, R., Goetz, T., Titz, W., and Perry, R. P. (2002). Academic emotions in students' self-regulated learning and achievement: A program of qualitative and quantitative research. Educational psychologist, 37(2), 91-105. Rottenberg, J., Ray, R. D., & Gross, J. J. (2007). Emotion elicitation using films.The handbook of emotion elicitation and assessment; London: Oxford University Press, 9. Taylor, S. E., and Brown, J. D. 1988. Illusion and well-being: a social psychological perspective on mental health. Psychological bulletin, 103(2), 193-210. Wilkins, J. R. 2011. Construction workers’ perceptions of health and safety training programmes. Construction Management and Economics, 29(10), 1017-1026. Verduyn, P., Van Mechelen, I., and Tuerlinckx, F. 2011. The relation between event processing and the duration of emotional experience. Emotion, 11(1), 20-28. Verduyn, P., Van Mechelen, I., Tuerlinckx, F., Meers, K., and Van Coillie, H. 2009. Intensity profiles of emotional experience over time. Cognition and Emotion, 23(7), 1427-1443.   218-10   Matthew HallowellBeavers Endowed Associate Professor of Construction EngineeringMatthew.hallowell@Colorado.eduLive Safety Demonstrations: Investing the impact of naturalistic demonstrations on emotion and situational interestWhen you think of safety training, what do you think of?Hazard recognitionRisk perceptionRisk toleranceBehavior & PerformanceHazard recognitionRisk perceptionRisk toleranceBehavior & Performance“Knowledge is not equipped until someone gets hurt. And that’s a damn shame.”-Worker following a fatalityResearch has found that there is only one factor that impacts risk tolerance.EXPERIENCESo, how do we give workers the experience of being injured without injuring them?Engage. Learn. Remember. Apply.Our hypothesized solution.This effort involves the continuum of research to practiceDevelop demos Run experiment        Implement solutionsCharacteristics of the demos.Develop demos Run experiment        Implement 1. Based on real events2. Medically accurate3. Grounded in science4. Engaging deliveryHere is an example.“During the installation of formwork, a 3-lb concrete chisel fell 10 feet severing the radial artery and breaking 3 metatarsals”Develop demos Run experiment        Implement Based on real events.Step 1: We need a hyper-realistic hand…Easier said than doneMaterial: Addition-cure silicone rubber with liquid PVC and latex additive Key Properties (measured 7 days after cure): Fabricated Hand Actual Human HandSpecific Gravity: 1.07 g/cc 1.067 g/ccHardness: 10A 10ATensile Strength: 475 psi 421 psiElongation at tear: 364% 245%Die B tear strength: 102 pli 100 pliShrinkage: <0.001 in/in <0.001 in/inDevelop demos Run experiment        Implement Medically accurate.Step 2: Explain simple scientific principlesDevelop demos Run experiment        Implement The severity of the injury is related to:1. How heavy?2. How fast?3. How sharp?Pressure is dangerous.Potential energy  Momentum  ForceContact area  pressureGrounded in scienceStep 2: Explain simple scientific principlesDevelop demos Run experiment        Implement VSGrounded in scienceStep 2: Explain simple scientific principlesDevelop demos Run experiment        Implement VSGrounded in scienceStep 2: Explain simple scientific principlesDevelop demos Run experiment        Implement VSGrounded in scienceStep 3: Make the delivery engaging.Develop demos Run experiment        Implement Engaging deliveryStep 3: Make the delivery engaging.Develop demos Run experiment        Implement Engaging deliveryStep 3: Make the delivery engaging.Develop demos Run experiment        Implement Engaging deliveryOnce developed, we scientifically tested the impactsDevelop demos Run experiment        Implement solutionsOur experimental design.Develop demos Run experiment        Implement n = 1,213all n = 727n = 486What did we study?Emotion Situational InterestDevelop demos Run experiment        Implement Positive emotionsDevelop demos Run experiment        Implement Why study emotion?Pessimism, less risk taking, More motivation to learn(Öhman and Mineka 2001; Clore et. al. 1994; Keller et. al. 2006)Negative emotionsSense of security, more risk taking(Gruber et al. 2011; Taylor and Brown; 1998))Why situational interest?Develop demos Run experiment        Implement Triggered situational interest: “The temporary interest that arises spontaneously due to environmental factors or engaging presentation.”Maintained situational interest: “The long-term interest sustained after an engaging experience.”From the fields of educational and applied psychology -14%12%-4%47%13%-29%-25%-29%-23%43%47%-40%-30%-20%-10%0%10%20%30%40%50%60%Difference in emotion (before -after)Impact of demos on emotional state compared with control group (p-value < 0.05 only)Develop demos Run experiment        Implement Impact of demos on situational interest compared with control (p-value < 0.05 only)15% 15%38%42%17%22%15%20%8%6%38%28%0%5%10%15%20%25%30%35%40%45%Percent ImprovementDevelop demos Run experiment        Implement Pinch PointDropped ObjectPipe  Rack – Finger smashLid Falling Finger SmashImplementationDevelop demos Run experiment        Implement ImplementationDevelop demos Run experiment        Implement Pinch PointsDropped ObjectBox CuttersPipe PressureHearing LossChemical BurnsSoil CollapseEye InjuriesWork at HeightWe now have a suite of demosThank you for your time and interest!Please let me answer your questions.www.livesafetydemos.com

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