Mortality Salience Enhances Safety Attitudes Without Reducing Risk-Taking in Junior Firefighters

Mortality Salience Enhances Safety Attitudes Without Reducing Risk-Taking in Junior Firefighters | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Mortality Salience Enhances Safety Attitudes Without Reducing Risk-Taking in Junior Firefighters Róger Marcelo Martínez, Kah Kheng Goh, Yang-Teng Fan, Yu-Chun Chen, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7296428/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Objective To evaluate the association between MS, work experience, and risky decision making, including its psychological and behavioral effects, on field-firefighters. Methods cross-sectional study was conducted using a sample of field firefighters (n = 300). Half of the participants (n = 150) were randomly assigned to the MS priming condition and the other half to the negative affect priming condition. Before priming, the participants completed questionnaires to assess their demographic information, including age, gender, educational level, and job-related information. After priming, they performed a neuroeconomic lottery choice task to assess risk-taking behavior, and a safety work attitude survey. Variables such as work stress, burnout, work-family conflict, work engagement, and death anxiety were also evaluated. Results Risky behaviors correlated with shorter reaction times (RTs) in the neuroeconomic lottery choice task. We observed a moderating effect of MS on the relationship between RT speed and risky decision making dependent on working experience among senior firefighters, who showed increased RTs when making low-risk decisions under MS priming. MS did not reduce risk-taking among junior firefighters, but did increase their safety attitudes. Conclusion To the best of our knowledge, this is the first study to assess the effects of MS on risk-taking behaviors and safety attitudes in firefighters. It is important to devote more training to senior field-firefighters on the importance of PPE utilization, while aiming for more resources towards the development of a system that minimizes goal conflicts (e.g., self-protection vs. mission objective) and rewards safer choices for junior field-firefighters. Health sciences/Health care Health sciences/Health occupations Biological sciences/Neuroscience Biological sciences/Psychology Social science/Psychology Health sciences/Risk factors Firefighters Mortality salience Risk-taking behaviors Safety attitudes Risky decision-making Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Firefighters, alongside first responders and careers in tactical occupations, have one of the most physically and psychologically demanding professions 1 , 2 . In addition to extinguishing fires, firefighters’ tasks include, but are not limited to, saving lives during critical circumstances, which usually results in serious physical harm and/or even death. Moreover, in places like Taiwan, firefighters were also responsible for the transportation of COVID-19 positive cases to epidemic prevention hotels and hospitals during the COVID-19 pandemic 3 . In the US alone, it is estimated that approximately one million firefighters risk their lives each and every day 4 . Because of this unceasing proximity to life-threatening circumstances, field-firefighters constantly experience high levels of mortality salience (MS) cues –i.e., the awareness that life will end in death someday 5 , 6 – and ‘death anxiety,’ through both exposure to injury and death of others, as well as through threats to their own lives 7 , 8 . Moreover, despite the heightened sense of urgency and increasing MS vulnerability, field-firefighters must be capable of swift decision-making –based on their equally speedy risk evaluation– to either gain time for rescue (e.g., running a red light to rush into the fireground), to act accordingly and immediately, or both. Hence, the way MS interacts with safety attitudes and risk-taking in this specific population is an important venue of inquiry. Moreover, firefighters are an indispensable force in safe-keeping practices for the general population. Although scientific research has consistently observed that MS may exert negative psychological effects, such as anxiety, decreased satisfaction in life, loss of life meaning, and increased negative affect in the general population 9 ; findings regarding its effects on behavior are somewhat contradictory. Some studies have noted that the initial negative psychological consequences produced by MS may rapidly activate proximal defenses, subsequently suppressing initial fear and anxiety 10 and giving way to increased self-preserving attributions related to better emotional states and cognitive task performance 11 . Nevertheless, other research has observed that MS may induce and/or exacerbate social avoidance 9 , decrease neural responses to the suffering of others 12 , as well as is able to modulate the salience network of the brain –decreasing reward learning speed and inhibiting behaviors acting on risk-related information 13 . Equally contradictory is the relationship between risk-taking and MS. Several studies have observed an association between risk-taking and individual differences modulated by the loci of control, that is, the degree to which individuals attribute control over the events happening in their lives either to themselves (internal locus) or to others (external locus) 14 , with individuals possessing an internal locus being more prone to engage in risk-taking behaviors than those with an external locus. Nevertheless, such a relationship seems to switch direction when considering the working environment: individuals possessing an internal locus of control engage in less risky behaviors than those with an external locus. Similarly, when researchers introduced MS into the experimental design, they observed that the direction resembled that found when taking into account the working environment was considered. That is, individuals with an internal locus engaged in less risk-taking behavior, as they attributed what might happen to them to their own choices, perceiving themselves as the sole agents over their fate. Those with an external locus considered that they had no agency over what could transpire; hence, it was acceptable to engage in unsafe practices 15 ; nevertheless, in order to control their death anxiety, they tended to choose risky behaviors that carried a higher probability of leaving them unharmed 15 . Interestingly, MS has also been observed to increase risky decision-making when engaging in the Iowa gambling task (IGT), which leads to poor performance, as participants are drawn to maximize pleasure and overassign weight to positive emotional information as a way to defend against and neutralize threat-induced insecurities 16 . The present study aimed to assess the relationship between MS, work experience, and risky decision making, as well as its psychological and behavioral effects, in field firefighters. Considering that the effects of MS seem to depend on work experience 8 , field-firefighters were classified into two groups depending on service seniority for the analyses: a junior group with less than 10 years of work experience and a senior group with more than 11 years of work experience. The ten-year cut point of service seniority was based on previous firefighter studies 17 , 18 . We hypothesized that MS will yield different effect sizes on field-firefighters’ work safety attitudes, death anxiety, and risk evaluations as a function of work experience. More specifically, we hypothesized that a) risky behaviors would be negatively related to work experience, b) risky behaviors would be related to increased stress time and shorter reaction times, c) risky behaviors would be related to MS priming, and d) work experience would moderate the relationship between MS and risky behaviors, such that MS would exert stronger effects on senior field-firefighters to accommodate for time pressure; however, MS would be less effective in moderating the relationship between reaction times and risky decision-making for junior field-firefighters. METHODS Participants A cross-sectional survey was conducted among career field firefighters in Taipei City and New Taipei City. Convenience sampling was used to recruit fire departments that were accessible and in close proximity to researchers. Recruitment of firefighters involves two strategies. First, the research staff distributed study flyers with contact information from fire stations and fire training educational programs. Second, fire administrators disseminate study information to fire department members via email and mobile phone. A total of 371 firefighters were screened between January 2021 and December 2021. Among the screened participants, 300 completed the study. Thus, the final sample included 300 firefighters (18% women and 82% men) (Table 1 ). Half of the participants were randomly assigned to the mortality salience (MS) group and the other half to the negative affect priming (NA) group. The sample size was estimated using G*Power 19 prior to data collection. To detect a medium effect size for the main effects in the ANCOVA with 95% power (f = 0.25, alpha = 0.05, numerator df = 4, number of groups = 2, number of covariates = 1), a sample size of 150 participants per group was required. This study was approved by the Taipei Medical University Ethics Committee (N202104078) and the National Yang Ming Chiao Tung University Ethics Committee (YM111011EF) and was conducted in accordance with the Declaration of Helsinki. Data were collected between the two calendar dates, 01/01/2021 and 12/31/2021. Table 1 Demographic Characteristics of field-firefighter participants. Variables Mortality Salience (N = 150) Control group (N = 150) n (%) SD n (%) SD P value Gender 0.374 0.396 .549 Male 125(83) 121(81) Female 25(17) 29(19) Age 1.185 1.126 .454 20–30 46(30.6) 55(36.6) 31–40 88(58.7) 82(54.6) 41 and above 16(10.7) 13(8.7) Education level 1.155 1.214 .592 Associate Degree 120(80) 117(78) Bachelor 6(4) 5(3.3) Postgraduate 18(12) 22(14.7) Others 6(4) 6(4) Primary Role 1.21 1.066 .062 General squad 96(64) 109(72.7) Security inspection brigade 4(2.7) 6(4) Dedicated EMS team 25(16.7) 19(12.7) Special rescue squad 25(16.7) 16(10.7) Unit 0.14 0.115 .653 General fieldwork branches 147(98) 148(98.7) Corps 3(2) 2(1.3) Central Firefighter Bureau 0(0) 0(0) Position 0.354 0.473 .408 Team member 139(92.7) 135(90) Squad leader 8(5.3) 12(8) Branch head 3(2) 3(2) Work experiences 1.239 1.21 .742 Less than 10 years 69(46) 81(54) 10 years and above 75 (50) 75(50) Measures and procedure Before priming for MS or NA, participants completed questionnaires to assess their demographic information, including age, sex, educational attainment, and variables related to the job (Table 1 ). Mortality salience (MS) cues MS was assessed using 28 mortality salience statements, in which participants had to judge whether they agreed with each statement 12 . The materials used for MS and NA priming were constructed in a fashion similar to that used in previous studies 20 . The MS group read and judged 14 statements related to death (e.g., ‘I would no longer exist from the day my body died’) for MS priming. The NA group read 14 statements referring to negative but death-unrelated emotions such as fear (e.g., ‘the future fills me with fear’) and anxiety (‘I feel suffering that I cannot escape from in life’). Neuroeconomic lottery choice task Participants engaged in a lottery choice task in which they had to make choices between pairs of gambles. This modified economic lottery-choice task has been validated in several neuroeconomic studies 21 – 23 . Each gamble incurred a high or low monetary outcome with each outcome associated with a specific probability. The associations between the probabilities and outcomes are represented by the corresponding colors (blue or orange). Pie charts represent the probabilities associated with the potential payoffs. Each pie consisted of 10 slices, with each slice corresponding to 10% probability. Each participant was presented with slices representing the probability of receiving a high (orange) or low (blue) monetary outcome ( Fig. 1 a). Both monetary outcomes and probabilities varied across the trials. Coefficient of variation (CV) was used to measure the associated risk for each gamble. The CV is a scale-free metric calculated by dividing the standard deviation by the expected value. Previous research has noted that CV is a stronger method than standard economic measures of risk (e.g., standard deviation or variance) for predicting choice behavior, as risk calculations are often made relative to the average outcome 22 , 24 . Each pair of gambles always had one high-risk option (high CV) and one low-risk option (low CV). For performance incentive purposes, the compensation for each participant was based on actual winnings obtained from one randomly selected trial. Accordingly, participants were informed that each trial was independent of each other so that any trial was equally likely to be chosen to compensate for the participant. Each participant completed 40 trials in approximately 7 min. Mortality salience (MS) cues The MS group read and judged 14 statements related to death during MS priming. The NA group read 14 other statements referring to death-unrelated priming of negative affect. Safety work attitudes : Three work-related safety attitudes were measured using three 5-point Likert-type scales: personal protective equipment (PPE), safe work practices, and reporting and communication 4 . Cronbach’s alpha for the total score for safety-work attitudes was 0.9. Items related to safe work practices and PPE were derived from the recommended safety practices introduced in the NFPA 1500 Standard of the Fire Department Occupational Safety and Health Program 25 . PPE utilization was gauged using a six-item scale (e.g., ‘I correctly use the appropriate PPE during firefighting operations, I correctly inspect all my PPE on a regular basis, and I personally check my SCBA [self-contained breathing apparatus] at the start of each shift). Each item was rated using a 5-point Likert-type scale with answers ranging from “almost never” to “almost always.” The Cronbach’s alpha for this scale was 0.72. Safe work practices were evaluated using a five-item scale (e.g., ‘every time I find defective firefighting equipment, I report it in order for it to be repaired or removed from service, ‘ ‘I follow applicable SOP’s [standard operating procedures] during all emergency operations,’ etc.). Each item was rated using a 5-point Likert-type scale with answers ranging from “almost never” to “almost always.” The Cronbach’s alpha for this scale was 0.79. Reporting and communication were appraised using a six-item scale (e.g., ‘I communicate potential hazards and exposure to firefighter personnel “and ‘I speak up and encourage others to get involved in safety issues”). Each item was rated using a 5-point Likert-type scale with answers ranging from “almost never” to “almost always.” These items were constructed using measures associated with reporting and communication 26 , as well as communication and safety voice 27 . The Cronbach’s alpha for this scale was 0.91. Perceived work stress Occupational stress was measured by utilizing a six-item scale derived from the research of DeJoy and colleagues 4 , 28 (e.g., ‘in the last month, how often have you felt nervous and stressed because of work?’; ” In the last month, how often have you felt you were unable to control the important things at work?’, etc.). Each item was rated using a 5-point Likert-type scale with answers ranging from “almost never” to “almost always.” The Cronbach’s alpha for this scale was 0.87. Firefighter burnout Burnout was gauged using the Malach-Pines 10-item scale (for example, When you think about your work, overall, how often do you feel hopeless?’; ” When you think about your work, overall, how often do you feel disappointed with people?’, etc.) 29 . Each item was rated using a 5-point Likert-type scale with answers ranging from “almost never” to “almost always.” The Cronbach’s alpha for this scale was 0.92. Work-family conflict Work-family conflict was evaluated by utilizing a three-item scale adapted from the research of Carlson and colleagues 30 (e.g., ‘when I get home from work, I am often too frayed to participate in family activities/responsibilities’, ‘when I get home from work, I am often so emotionally drained, that it prevents me from contributing to my family’, and ‘when I come home, due to all the pressures at work, I am too stressed to do the things I enjoy’). Each item was rated on a 5-point Likert-type scale, with answers ranging from “strongly disagree” to “strongly agree.” Cronbach’s alpha for this scale was 0.86. Engagement : Work engagement was gauged using the short version of the Utrecht Work Engagement Scale 8 , 31 during the “Time 7” data collection. It is a nine-item scale that measures three interconnected dimensions of engagement: vigor (three items), dedication (three items), and absorption (three items). Each item was rated using a 5-point Likert scale, with answers ranging from “strongly disagree” to “strongly agree.” We tested our hypotheses using a composite measure of engagement (Cronbach’s alpha = .92). Death anxiety : Death anxiety was measured using the Revised DA Scale 8 , 32 . The measure is a 25-item scale which measures three interconnected facets of DA: anxieties over “not being” (e.g., ‘the total isolation of death is frightening to me’), fear of pain and helplessness (e.g., ‘the pain involved in dying frightens me’), and life after death and decomposition (e.g., ‘the subject of life after death troubles me greatly’). Furthermore, a composite measure was employed according to the recommendations of the authors (Cronbach’s alpha = .93). RESULTS Descriptive statistics for all variables are provided in Tables 1 and 2 . All demographic variables were independent of the experimental group assignment (MS vs. NA, all P > .05), confirming the validity of the randomized control procedure. Table 2 Means of dependent variables as a function of experimental groups. Variables Mortality Salience (n = 150) Control group (n = 150) Mean SD Mean SD P value Death anxiety 1.04 0.71 0.87 0.71 .038 Safety attitude total scores 50.05 10.02 47.21 10.71 .018 Personal protective equipment 18.72 3.54 17.81 4.07 .041 Safe work practices 15.35 3.23 14.78 3.13 .119 Reporting and communication 15.97 5.02 14.61 5.49 .026 Occupational stress 11.07 4.34 11.3 7.82 .756 Work-family conflict 5.44 3.12 5.86 3.09 .242 Work engagement 25.68 10.29 24.2 9.7 .201 Firefighter burnout 14.92 7.56 15.25 7.68 .711 Neuroeconomic behaviors High-risk items selected 14.29 9.36 14.23 9.08 .96 Low-risk items selected 24.75 9.52 24.79 9.3 .971 CV of high-risk items 0.5 0.13 0.49 0.12 .805 CV of low-risk items 0.1 0.01 0.1 0.01 .341 Total CV 0.26 0.1 0.26 0.1 .895 RTs of high-risk decisions (sec) 1.93 0.59 1.94 0.54 .882 RTs of low-risk decisions (sec) 1.88 0.52 1.89 0.46 .907 Total RTs (sec) 1.86 0.49 1.87 0.45 .857 Neuroeconomic lottery choice performance The 2 (PRIMING: MS vs. NA; a between-subjects factor) × 2 (WORK EXPERIENCE: junior vs. senior; a between-subjects factor) ANOVA on the percentage of high-risk decisions showed a main effect of work experience ( F 1, 296 = 4.34, P = 0.038, pη 2 = 0.014; junior vs. senior: 0.394 ± 0.019 vs. 0.338 ± 0.019, mean ± SE) and a marginal trend in the interaction between PRIMING and WORK EXPERIENCE ( F 1, 296 = 3.2, P = 0.075, pη 2 = 0.011) that approached significance, whereas there was no main effect of PRIMING ( F 1, 296 = 0.001, P = 0.969). The PRIMING effect on high-risk decisions had opposite directions depending on the factor of WORK EXPERIENCE, in which MS increased high-risk decisions in junior field-firefighters (MS vs. NA: 0.419 ± 0.027 vs. 0.37 ± 0.026) but decreased high-risk decisions in senior field-firefighters (MS vs. NA: 0.315 ± 0.027 vs. 0.362 ± 0.028), the preplanned experience-wise comparisons showed that junior field-firefighters made more high-risk decisions than senior field-firefighters after MS priming ( 0.419 ± 0.027 vs. 0.315 ± 0.026, t = 2.74, P = 0.007). But this effect was not found in the NA priming of the control condition (junior vs. senior: 0.37 ± 0.026 vs. 0.362 ± 0.028, t = 0.21, P = 0.835). The same pattern of risk performance results was identified by analysis using the coefficient of variation (CV) [MS: (junior vs. senior: 0.279 ± 0.012 vs. 0236 ± 0.011, t = 2.55, P = 0.012) and NA: (junior vs. senior: 0.259 ± 0.011 vs. 0255 ± 0.012, t = 0.24, P = 0.808)] (Fig. 1 ). previous studies have shown differences in how older and younger adults process MS 33 , the aforementioned experience-modulating effect on risk performance was further confirmed by an ANCOVA model with the same 2 (PRIMING) × 2 (WORK EXPERIENCE) design and an additional covariate of age (the interaction between PRIMING and WORK EXPERIENCE: F 1, 295 = 3.185, P = 0.075, pη 2 = 0.011). However, the main effect of work experience was no longer significant after controlling for age ( F 1, 295 = 2.445, P = 0.119, pη 2 = 0.008). While the ANOVA analysis of the reaction times did not yield any effect of PRIMING, WORK EXPERIENCE, or their interaction (all P > 0.4), the speed of risky decision-making was found to be negatively correlated with the frequency of risky decisions (r = -0.309, P < 0.001) and CV (r = -0.310, P < 0.001), indicating that a quicker response predicted riskier decisions. This speed-risk association stood after controlling for the effect of work experience and age (CV: β = -0.312, P < 0.001; risky decisions: β = -0.31, P < 0.001). To test the hypotheses and dissect the effect of work experience from the effect of age, which were both highly correlated (r = 0.726, P < 0.001), hierarchical moderated multiple regression was used. First, we entered control variables (age). Second, we entered the predictor and moderator variables (work experience, MS priming, and reaction time). In the third step, we entered the cross product of the predictor and moderator variables. All variables were standardized before the model was computed using cross-product terms. Finally, we examined the change in R 2 from Steps 2 to 3 to determine whether the moderating variable had a significant effect. Table 3 shows the regression results. Table 3 Moderating effect of work experience on the response to mortality salience in field-firefighters. Variables Step 1 Step 2 Step 3 DV: risky decisions (%) Age − .079 − .029 − .021 Work experience − .061 − .614** Reaction times − .31*** − .53*** MS priming .009 .168 Work experience × Reaction times .724*** Work experience × Reaction times × MS priming − .207* R 2 .006 .103 .145 Δ R 2 .006 .097*** .042** Note. Beta weights provided are in their standardized form. DV = dependent variable; MS = mortality salience. * p < .1. ** p < .01. *** p < .001. Hypothesis a, risky decisions related negatively to work experience, was not supported (β = -0.061, P = 0.458). Hypothesis b, risky behaviors related to time pressure and shortened reaction times, was supported (β = -0.31, P < 0.001). Hypothesis c, risky decisions related to MS priming, was not supported (β = 0.009, P = 0.875). Hypothesis d examined the moderating effect of work experience on the relationship between MS priming, reaction times, and risky behavior. The significant interaction terms explained 4.2% of the additional variance in risky decisions above and beyond work experience, reaction times, and MS priming. This relationship was plotted (see Fig. 2 ) and, consistent with our predictions, the moderating effect of MS (simple slope = -0.237, P = .042) was higher than that of NA (simple slope = 0.023, ns) on the speed-risk relationship, which was only found in senior firefighters but not in junior field-firefighters (MS: simple slope = -0.079, ns; NA: simple slope = − .187, ns). MS priming modulated the speed-risk relationship in senior firefighters, and increased RTs were associated with reduced risk. However, this modulating effect of MS was not observed in the junior firefighters. Safety work attitudes results The 2 (PRIMING: MS vs. NA; a between-subject factor) × 2 (WORK EXPERIENCE: junior vs. senior; a between-subject factor) ANCOVA (with a covariate of age) on PPE showed a main effect of PRIMING ( F 1, 295 = 4.057, P = 0.045, pη 2 = 0.014; MS vs. NA: 18.71 ± 0.311 vs. 17.823 ± 0.312, mean ± se), and a marginal trend in the interaction between PRIMING and WORK EXPERIENCE ( F 1, 295 = 2.974, P = 0.086, pη 2 = 0.01) that approached significance. Preplanned experience-wise comparisons showed that MS significantly increased (compared to NA) the PPE attitude in junior field-firefighters (MS: 19.33 ± 0.378; NA: 17.68 ± 0.436, t = 2.849, P = 0.005) but not in senior field-firefighters (MS: 18.11 ± 0.429; NA: 17.97 ± 0.514, t = 0.204, P = 0.839) (Fig. 3 ). The same ANCOVA model on safe work practices revealed a main effect of age as a covariate ( F 1, 295 = 6.25, P = 0.013, pη 2 = 0.021), whereas there was no effect of PRIMING, WORK EXPERIENCE, or their interaction. Attitudes towards safe work practices were positively associated with age (simple slope = 0.154, P = .008). Regarding reporting and communication attitudes, ANCOVA results showed a main effect of PRIMING ( F 1, 295 = 4.546, P = 0.034, pη 2 = 0.015), with a higher score in the MS condition (MS: 15.943 ± 0.429; NA: 14.649 ± 0.43) after controlling for age as a covariate ( F 1, 295 = 2.916, P = 0.089, pη 2 = 0.01). The other variables did not reach statistical significance (all P > .4). Results of perceived work stress, firefighter burnout, work-family conflict, and work engagement The 2 (PRIMING: MS vs. NA, a between-subjects factor) × 2 (WORK EXPERIENCE: junior vs. senior; a between-subjects factor) ANCOVA (with a covariate of age) on occupational stress did not show any effect of PRIMING ( F 1, 295 = 0.15, P = 0.698), WORK EXPERIENCE ( F 1, 295 = 0.204, P = 0.625), or their interactions ( F 1, 295 = 0.586, P = 0.444). Additionally, applying the same model to firefighter burnout and work-family conflict did not show any effect on targeted variables or their interaction (all P > .1). Regarding the work engagement, the ANCOVA results showed a main effect of WORK EXPERIENCE ( F 1, 295 = 8.399, P = 0.004, pη 2 = 0.028; junior vs. senior: 27.035 ± 0.928 vs. 22.624 ± 0.976, mean ± se) with higher engagement found in junior field-firefighters even after controlling for the covariate of age ( F 1, 295 = 3.62, P = 0.058, pη 2 = 0.012). The other variables did not reach statistical significance (all P > .1) Death anxiety results ANCOVA on death anxiety showed a main effect of age as a covariate ( F 1, 295 = 4.589, P = 0.033, pη 2 = 0.015), as well as a main effect of PRIMING ( F 1, 295 = 4.88, P = 0.028, pη 2 = 0.016). Death anxiety significantly increased after MS priming (MS: 1.049 ± 0.058; NA: 0.869 ± 0.058), while it was negatively associated with age in our field firefighter samples (simple slope = -0.169, P = .003). Preplanned experience-wise comparisons showed that MS significantly increased (compared to NA) death anxiety in junior field-firefighters (MS: 1.171 ± 0.083; NA: 0.922 ± 0.086, t = 2.066, P = 0.04) but not in senior field-firefighters (MS: 0.918 ± 0.079; NA: 0.814 ± 0.075, t = 0.94, P = 0.349) (Fig. 3 ). DISCUSSION The objective of the present study was to assess the relationship between mortality salience (MS), work experience, and risky decision making, as well as the psychological and behavioral effects of the association on field-firefighters, all of which included demographic information such as gender, age, education level, and job-related variables as covariates. Regarding our previously stated hypotheses, we found that Hypothesis a), which stated that risky behaviors would be negatively related to work experience, was not supported, as there was no significant relationship between these two variables; Hypothesis b) was supported, as risky behaviors were correlated with shorter reaction times (RTs) regarding the neuroeconomic lottery choice task; Hypothesis c), which stated that risky behaviors would be related to MS priming, was not supported, as there was no significant association between MS and risky decision-making; and Hypothesis d) was partially supported, as the analyses yielded a moderating effect of MS on the relationship between the speed of RTs and risky decision-making, but only among senior field-firefighters, who showed increased RTs when making low-risk decisions under MS priming. Interestingly, although this modulating effect was not found in junior firefighters, an increase in safety attitudes was observed in this group. Originally, researchers concluded that time pressure increases risk aversion 34 – 37 . The explanation, based on the dual-system model of decision-making 38 , posited that this was probably due to time pressure interrupting the engagement of System 2 (i.e., involved in reasoning), thus leaving System 1 (i.e., involved in high-speed automatic processes) to dominate the decision-making process 34 . Nevertheless, recent research reevaluating said studies have found that this may be due to errors in experimental design 39 . This is in line with the findings of the present study, which showed that field-firefighters’ risky choices correlated with shorter RTs. Nevertheless, the relationship between time constraints and risky choices may be less related to a change in risk preference and more related to a decrease in choice consistency. This is because of the time pressure incurred in a speed-accuracy tradeoff, meaning that higher RTs in decision-making processes prompt less consistency and/or increase errors 39 . Paradoxically, the finding that the relationship between risky behaviors and work experience was not significant is both surprising and expected. It is surprising that researchers might be inclined to use work experience as a proxy for MS. It is logical, given that we might be tempted to reason that the greater the work experience, the greater the exposure to life-threatening circumstances encountered by firefighters; thus, MS incurs a cumulative effect. Nevertheless, once the other variables are included, this is expected. Studies assessing risky decision-making in the firefighter population have observed that firefighter safety performance tends to be modulated by work-family conflict and work stress, which in turn predict burnout, and it is the occurrence of burnout that contributes significantly to faulty risk assessment and subsequent risky choices 4 . Hence, we can observe that risky firefighter decision-making might be tied to factors such as time of rest and recovery from the demands of the job, reduced ability and physical health, diminished performance motivation 40 , reduced information processing, and cognitive impairment 41 , 42 , as well as decreased levels of commitment towards the job 43 , which at the same time are all, once more, related to burnout 4 . Additionally, our findings did not reveal any interactions between MS and work stress, work-family conflict, work engagement, or burnout. Furthermore, even if work experience equated with MS in some way, our analyses of the relationship between risky choices and MS priming yielded no significant associations. Considering the contradictory findings of previous studies on this relationship 9 – 13 , it is not difficult to see that other factors might contribute to this association (similar to the relationship between risky choices and work experience). Even when other studies have narrowed down to possible modulators between MS and risky behaviors, such as the loci of control 15 , there still appears to be a complex interaction between the loci of control and other factors, such as different professions 44 or whether the decision-making process occurs in the military domain 45 , among many others 15 . Therefore, future studies with more robust and stricter experimental designs are required. However, when assessing the moderating effect of MS on the relationship between the speed of RTs and risky decision-making dependent on work experience, we found that MS priming modulated the speed-risk relationship, but only in senior field-firefighters, who showed increased RTs when making low-risk decisions under MS priming. However, this effect was not observed in the junior-field firefighter group. These findings contrast with previous research showing that older adults tend to be less influenced by MS because of possessing an increased awareness of death, greater susceptibility to physical ailments, and probably substantially more experience of having lost loved ones 33 . Nevertheless, this discrepancy may be partially attributed to the locus of control. First, owing to the fact it seems that the locus of control tends to become increasingly internal as a person ages 46 , 47 . Second, because of their interaction with MS, it has been observed that MS increases actual risk-taking in individuals with an external locus, whereas it decreases risk-taking in individuals with an internal locus. However, regardless of possessing an internal or external locus of control, it appears that both groups equally maintained an increased assessed level of risk under MS-priming conditions 15 . Accordingly, the increased risk-taking behaviors found in junior firefighters as an effect of MS priming may be ascribed to the external locus of control associated with work experience 48 . This might also be related to the finding that field-junior firefighters increased their safety attitudes despite not reducing their risk-taking behaviors. Whereas senior field-firefighters develop an internal locus of control capable of conveying a greater sense of agency in regards to their own mortality, hence, developing a more risk averse attitude overall; the junior field-firefighters’ external locus of control might yield a disposition to engage in risky decision-making, all while their heightened risk assessment urges them to engage in extraneous safety attitudes –such as the utilization of PPE– in order to mitigate injury and/or death, and in spite of still engaging in risk-taking behaviors. However, it is important to note that previous research has also observed that the nature of the risk greatly influences the extent to which those with an internal or external locus become greater risk takers 15 , as it appears that those with an internal locus tend to take greater risks on skill tasks, whereas those with an external locus tend to take greater risks on tasks involving chance. This is because those with an internal locus are more likely to believe that what happens to them is a result of their own skills, whereas those with an external locus are more likely to believe that chance is the determining factor over what happens to them. As such, future research delving into the interactions between the loci of control, risk-taking behaviors, and considering the nature of risk, specifically in the firefighter population, is highly warranted, as it is a profession where a combination of skill (e.g., tactical preparation) and chance (e.g., critical and rapidly changing conditions at the emergency scene) seems to converge in a significant manner. To the best of our knowledge, this is the first study to assess the effects of mortality salience on risk-taking behaviors and safety attitudes by taking into account factors such as working experience, work stress, burnout, work-family conflict, and work engagement, alongside demographic factors in a population of field-firefighters. Our findings show that risky choices are modulated by time constraints, and that MS modulates RTs when engaging in risky decision-making among senior field firefighters. Furthermore, although MS did not reduce risk-raking behaviors in junior firefighters, it did increase their safety attitudes such as PPE utilization. Consequently, it is important to devote more training to senior field-firefighters on the importance of PPE utilization, while aiming for more resources towards the development of a system that minimizes goal conflicts (e.g., self-protection vs. mission objective) 49 and rewards safer choices 50 , when it comes to junior field-firefighters. Declarations Ethics approval and consent to participate This study was approved by the Taipei Medical University Ethics Committee (N202104078) and the National Yang Ming Chiao Tung University Ethics Committee (YM111011EF), and was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all the participants. At the end of the study, all the participants received monetary compensation for their participation. Authors’ contributions R.M.M., K. K. G., and C.C. conceived and conceptualized the study. T.H.P. and C. M. C. collected and analyzed the data. R.M.M., K.K.G., and C.C. reviewed the literature and drafted the first manuscript. All authors contributed to the writing and revision of the final draft. Conflict of interest statement The authors declare that this research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest. Funding This work was financially supported by grants from Wan-Fang Hospital, Taipei Medical University (112TMU-WFH-15), and the National Science and Technology Council (112-2410-H-038-029 -; 112-2636-H-038-005 -), Taiwan. Open practices statement The data, code, and materials for this study have not been made publicly available; however, requests for said data, code, and/or materials can be made to the corresponding authors. References Obuobi-Donkor, G. et al. , . A Scoping Review on the Prevalence and Determinants of Post-Traumatic Stress Disorder among Military Personnel and Firefighters: Implications for Public Policy and Practice. Int J. Environ. Res. Public. Health 19 . (2022). Tramel, W. et al. , . An Examination of Subjective and Objective Measures of Stress in Tactical Populations: A Scoping Review. Healthcare (Basel) 11 . (2023). Lee, S. C., Lin, C. Y. & Chuang, Y. J. 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Distinguishing three effects of time pressure on risk taking: Choice consistency, risk preference, and strategy selection. J. Behav. Decis. Mak. 34 , 541–554 (2021). Shirom, A. Job-related burnout: A review of major research foci and challenges. In Handbook of occupational health psychology, 2nd ed. : 223–241. Washington, DC, US: American Psychological Association. (2011). Golonka, K. et al. Cognitive Impairments in Occupational Burnout - Error Processing and Its Indices of Reactive and Proactive Control. Front. Psychol. 8 , 676 (2017). He, S. C. et al. Burnout and cognitive impairment: Associated with serum BDNF in a Chinese Han population. Psychoneuroendocrinology 77 , 236–243 (2017). Maslach, C., Schaufeli, W. B. & Leiter, M. P. Job burnout. Annu. Rev. Psychol. 52 , 397–422 (2001). Salminen, S. & Klen, T. Accident locus of control and risk taking among forestry and construction workers. Percept. Mot Skills . 78 , 852–854 (1994). Higbee, K. L. Perceived control and military riskiness. Percept. Mot Skills . 34 , 95–100 (1972). Gatz, M. & Karel, M. J. Individual change in perceived control over 20 years. Int. J. Behav. Dev. 16 , 305–322 (1993). Hovenkamp-Hermelink, J. H. M. et al. Differential associations of locus of control with anxiety, depression and life-events: A five-wave, nine-year study to test stability and change. J. Affect. Disord . 253 , 26–34 (2019). Galvin, B. M. et al. Changing the focus of locus (of control): A targeted review of the locus of control literature and agenda for future research. J. Organizational Behav. 39 , 820–833 (2018). Hagemann, V., L. Heinemann, C. Peifer, et al. 2022. Risky Decision Making Due to Goal Conflicts in Firefighting—Debriefing as a Countermeasure to Enhance Safety Behavior. In Safety , Vol. 8. Hinnant, J. B. & Stavrinos, D. Rewards decrease risky decisions for adolescent drivers: Implications for crash prevention. Transp. Res. Part. F: Traffic Psychol. Behav. 74 , 272–279 (2020). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 26 Sep, 2025 Reviews received at journal 25 Sep, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviews received at journal 01 Sep, 2025 Reviewers agreed at journal 26 Aug, 2025 Reviewers invited by journal 26 Aug, 2025 Editor invited by journal 07 Aug, 2025 Editor assigned by journal 06 Aug, 2025 Submission checks completed at journal 06 Aug, 2025 First submitted to journal 05 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7296428","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":508249917,"identity":"c199da8e-9646-4e87-b5df-7a6babec20ce","order_by":0,"name":"Róger Marcelo Martínez","email":"","orcid":"","institution":"Taipei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Róger","middleName":"Marcelo","lastName":"Martínez","suffix":""},{"id":508249918,"identity":"653468b3-8081-4623-bf9f-68fe33021560","order_by":1,"name":"Kah Kheng Goh","email":"","orcid":"","institution":"Taipei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Kah","middleName":"Kheng","lastName":"Goh","suffix":""},{"id":508249919,"identity":"70962d36-3c39-4c19-a76a-7f99a219e3da","order_by":2,"name":"Yang-Teng Fan","email":"","orcid":"","institution":"Yuan Ze University","correspondingAuthor":false,"prefix":"","firstName":"Yang-Teng","middleName":"","lastName":"Fan","suffix":""},{"id":508249920,"identity":"23724b74-6b77-4c04-acf4-1f5cdc5b0d18","order_by":3,"name":"Yu-Chun Chen","email":"","orcid":"","institution":"National Taiwan University of Sport","correspondingAuthor":false,"prefix":"","firstName":"Yu-Chun","middleName":"","lastName":"Chen","suffix":""},{"id":508249921,"identity":"a2ef8cb5-d5bc-4b0c-9c57-16b1e3f9707c","order_by":4,"name":"Ting-Hao Pan","email":"","orcid":"","institution":"Taipei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ting-Hao","middleName":"","lastName":"Pan","suffix":""},{"id":508249923,"identity":"86780c04-a2d6-4c25-b0c1-9d05a9facbc1","order_by":5,"name":"Che-Ming Chang","email":"","orcid":"","institution":"Taipei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Che-Ming","middleName":"","lastName":"Chang","suffix":""},{"id":508249924,"identity":"300939b3-ccef-4f45-a407-ab9dc6af7ee3","order_by":6,"name":"Cheng-Ta Yang","email":"","orcid":"","institution":"National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"Cheng-Ta","middleName":"","lastName":"Yang","suffix":""},{"id":508249926,"identity":"43f6fcfe-954d-46f1-a36b-627596788a95","order_by":7,"name":"Ting-Ting Chang","email":"","orcid":"","institution":"National Chengchi University","correspondingAuthor":false,"prefix":"","firstName":"Ting-Ting","middleName":"","lastName":"Chang","suffix":""},{"id":508249927,"identity":"9d14cec4-c2e8-444b-a784-46ad1cf490bb","order_by":8,"name":"Chenyi Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYDACCRBhwCAH4bGRoMWYB6aFhzgtDAyJPURr4Z/dfOwxT4Fd+n6xMwYMH8oOM9hLJBCw5M6xdGMeg+TcHukcA8YZ5w4z8BDSYiCRYybNY3AArIWZtw2oRZqglvxvIC3pPCAtf4nTksMG0pIA1sJIjBaJG2lmknMMkg17bqcVHOw5l87Dc/8Bfi38M5KfSbz5YyfPPjt544MfZdZy7D0H8GsBASZYVIDUEo5JEGD8QZSyUTAKRsEoGLEAAMCMOJhjWnjhAAAAAElFTkSuQmCC","orcid":"","institution":"Taipei Medical University","correspondingAuthor":true,"prefix":"","firstName":"Chenyi","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2025-08-05 05:08:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7296428/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7296428/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90541736,"identity":"a91fa952-9e41-4a44-a2f3-341c2e1ed4f7","added_by":"auto","created_at":"2025-09-03 23:57:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":7530246,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea.\u003c/strong\u003e In the economic lottery choice task, firefighters chose between pairs of uncertain gambles. For each trial, there was a high and low monetary outcome, each associated with a specific probability. The monetary outcomes and probabilities were presented using different colors. \u003cstrong\u003eb. \u003c/strong\u003eEach trial included a decision phase and an outcome\u0026nbsp;\u0026nbsp; phase (where the result of the participant’s choice was shown), and a jittered intertrial interval (ITI). \u003cstrong\u003ec. \u003c/strong\u003eViolin plots showing means (large dots), s.d. (bars) and distributions of risky propensity. *P \u0026lt; 0.05; **P \u0026lt; 0.01. The 2 (PRIMING: MS vs. NA; a between-subject factor) x 2 (WORK EXPERIENCE: junior vs. senior; a between-subject factor) ANCOVA on the percentage of high-risk decisions showed a marginal trend of an interaction between PRIMING and WORK EXPERIENCE (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 3.185,\u0026nbsp;\u003cem\u003eP\u003c/em\u003e = 0.075,\u0026nbsp;pη\u003csup\u003e2\u003c/sup\u003e =\u0026nbsp;0.011) that approach significance even after controlling for the covariate of age. Junior field-firefighters made more high-risk decisions than what senior field-firefighters did after the MS priming (0.419 ± 0.027 vs. 0.315 ± 0.026, \u003cem\u003et\u003c/em\u003e = 2.74, \u003cem\u003eP\u003c/em\u003e = 0.007). But this effect was not found in the NA priming of control condition (junior vs. senior: 0.37 ± 0.026 vs. 0.362 ± 0.028, \u003cem\u003et\u003c/em\u003e = 0.21, \u003cem\u003eP\u003c/em\u003e = 0.835).\u003cstrong\u003e d. \u003c/strong\u003eThe same pattern of risk performance results was identified by the analysis using the coefficient of variation (CV) [MS: (junior vs. senior: 0.279 ± 0.012 vs. 0236 ± 0.011, \u003cem\u003et\u003c/em\u003e = 2.55, \u003cem\u003eP\u003c/em\u003e = 0.012); NA: (junior vs. senior: 0.259 ± 0.011 vs. 0255 ± 0.012, \u003cem\u003et\u003c/em\u003e = 0.24, \u003cem\u003eP\u003c/em\u003e = 0.808)].\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7296428/v1/0c257f998be93891eaf17a0e.png"},{"id":90542628,"identity":"6c882584-8491-4b17-beb7-9c32ab75ae6e","added_by":"auto","created_at":"2025-09-04 00:05:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5870438,"visible":true,"origin":"","legend":"\u003cp\u003eModerating effect of work experience in the relationship between MS priming, reaction times, and risky behavior. MS priming modulated the speed-risk relationship in senior field-firefighters (simple slope = -0.237, p = .042), by which increased RTs were associated with reduced risk. NA priming did not show this modulating effect (simple slope = 0.023, ns). This double dissociation of MS was not found in junior field-firefighters (MS: simple slope = -0.079, ns; NA: simple slope = -.187, ns).\u003c/p\u003e","description":"","filename":"Figure2new.png","url":"https://assets-eu.researchsquare.com/files/rs-7296428/v1/b9dc8ab217bdb500a61c7335.png"},{"id":90541735,"identity":"139effc7-69e8-43f9-b8cd-86ad57c0a469","added_by":"auto","created_at":"2025-09-03 23:57:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":7475692,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea. \u003c/strong\u003eViolin plots showing means (large dots), s.d. (bars) and distributions of PPE attitude. **P \u0026lt; 0.01. The 2 (PRIMING: MS vs. NA; a between-subject factor) x 2 (WORK EXPERIENCE: junior vs. senior; a between-subject factor) ANCOVA (with a covariate of age) on the PPE showed a main effect of PRIMING (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 4.057,\u0026nbsp;\u003cem\u003eP\u003c/em\u003e = 0.045,\u0026nbsp;pη\u003csup\u003e2\u003c/sup\u003e =\u0026nbsp;0.014; MS vs. NA: 18.71 ± 0.311 vs. 17.823 ± 0.312, mean ± se) and a marginal trend of an interaction between PRIMING and WORK EXPERIENCE (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 2.974,\u0026nbsp;\u003cem\u003eP\u003c/em\u003e = 0.086,\u0026nbsp;pη\u003csup\u003e2\u003c/sup\u003e =\u0026nbsp;0.01) that approach significance. MS significantly increased (compared to NA) the PPE attitude in junior field-firefighters (MS: 19.33 ± 0.378; NA: 17.68 ± 0.436, \u003cem\u003et\u003c/em\u003e = 2.849, \u003cem\u003eP\u003c/em\u003e = 0.005) but not in senior field-firefighters (MS: 18.11 ± 0.429; NA: 17.97 ± 0.514, \u003cem\u003et\u003c/em\u003e = 0.204, \u003cem\u003eP\u003c/em\u003e = 0.839). \u003cstrong\u003eb.\u003c/strong\u003e Violin plots showing means (large dots), s.d. (bars) and distributions of death anxiety. *P \u0026lt; 0.05. MS significantly increased (compared to NA) death anxiety in junior field-firefighters (MS: 1.171 ± 0.083; NA: 0.922 ± 0.086, \u003cem\u003et\u003c/em\u003e = 2.066, \u003cem\u003eP\u003c/em\u003e = 0.04) but not in senior field-firefighters (MS: 0.918 ± 0.079; NA: 0.814 ± 0.075, \u003cem\u003et\u003c/em\u003e = 0.94, \u003cem\u003eP\u003c/em\u003e = 0.349).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7296428/v1/b6943a4d18859396f91e5962.png"},{"id":90543697,"identity":"03204978-c673-43dc-ac3c-e77b3024894d","added_by":"auto","created_at":"2025-09-04 00:14:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":17669268,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7296428/v1/13e1b961-6e71-414e-9645-ca3f70014207.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mortality Salience Enhances Safety Attitudes Without Reducing Risk-Taking in Junior Firefighters","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eFirefighters, alongside first responders and careers in tactical occupations, have one of the most physically and psychologically demanding professions \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. In addition to extinguishing fires, firefighters\u0026rsquo; tasks include, but are not limited to, saving lives during critical circumstances, which usually results in serious physical harm and/or even death. Moreover, in places like Taiwan, firefighters were also responsible for the transportation of COVID-19 positive cases to epidemic prevention hotels and hospitals during the COVID-19 pandemic \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In the US alone, it is estimated that approximately one million firefighters risk their lives each and every day\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eBecause of this unceasing proximity to life-threatening circumstances, field-firefighters constantly experience high levels of mortality salience (MS) cues \u0026ndash;i.e., the awareness that life will end in death someday \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u0026ndash; and \u0026lsquo;death anxiety,\u0026rsquo; through both exposure to injury and death of others, as well as through threats to their own lives \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Moreover, despite the heightened sense of urgency and increasing MS vulnerability, field-firefighters must be capable of swift decision-making \u0026ndash;based on their equally speedy risk evaluation\u0026ndash; to either gain time for rescue (e.g., running a red light to rush into the fireground), to act accordingly and immediately, or both. Hence, the way MS interacts with safety attitudes and risk-taking in this specific population is an important venue of inquiry. Moreover, firefighters are an indispensable force in safe-keeping practices for the general population.\u003c/p\u003e\u003cp\u003eAlthough scientific research has consistently observed that MS may exert negative psychological effects, such as anxiety, decreased satisfaction in life, loss of life meaning, and increased negative affect in the general population \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e; findings regarding its effects on behavior are somewhat contradictory.\u003c/p\u003e\u003cp\u003eSome studies have noted that the initial negative psychological consequences produced by MS may rapidly activate proximal defenses, subsequently suppressing initial fear and anxiety \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e and giving way to increased self-preserving attributions related to better emotional states and cognitive task performance \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Nevertheless, other research has observed that MS may induce and/or exacerbate social avoidance \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, decrease neural responses to the suffering of others \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, as well as is able to modulate the salience network of the brain \u0026ndash;decreasing reward learning speed and inhibiting behaviors acting on risk-related information \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eEqually contradictory is the relationship between risk-taking and MS. Several studies have observed an association between risk-taking and individual differences modulated by the loci of control, that is, the degree to which individuals attribute control over the events happening in their lives either to themselves (internal locus) or to others (external locus)\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, with individuals possessing an internal locus being more prone to engage in risk-taking behaviors than those with an external locus. Nevertheless, such a relationship seems to switch direction when considering the working environment: individuals possessing an internal locus of control engage in less risky behaviors than those with an external locus. Similarly, when researchers introduced MS into the experimental design, they observed that the direction resembled that found when taking into account the working environment was considered. That is, individuals with an internal locus engaged in less risk-taking behavior, as they attributed what might happen to them to their own choices, perceiving themselves as the sole agents over their fate. Those with an external locus considered that they had no agency over what could transpire; hence, it was acceptable to engage in unsafe practices \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e; nevertheless, in order to control their death anxiety, they tended to choose risky behaviors that carried a higher probability of leaving them unharmed \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eInterestingly, MS has also been observed to increase risky decision-making when engaging in the Iowa gambling task (IGT), which leads to poor performance, as participants are drawn to maximize pleasure and overassign weight to positive emotional information as a way to defend against and neutralize threat-induced insecurities \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe present study aimed to assess the relationship between MS, work experience, and risky decision making, as well as its psychological and behavioral effects, in field firefighters. Considering that the effects of MS seem to depend on work experience \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, field-firefighters were classified into two groups depending on service seniority for the analyses: a \u003cem\u003ejunior group\u003c/em\u003e with less than 10 years of work experience and a \u003cem\u003esenior group\u003c/em\u003e with more than 11 years of work experience. The ten-year cut point of service seniority was based on previous firefighter studies \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. We hypothesized that MS will yield different effect sizes on field-firefighters\u0026rsquo; work safety attitudes, death anxiety, and risk evaluations as a function of work experience. More specifically, we hypothesized that a) risky behaviors would be negatively related to work experience, b) risky behaviors would be related to increased stress time and shorter reaction times, c) risky behaviors would be related to MS priming, and d) work experience would moderate the relationship between MS and risky behaviors, such that MS would exert stronger effects on senior field-firefighters to accommodate for time pressure; however, MS would be less effective in moderating the relationship between reaction times and risky decision-making for junior field-firefighters.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cb\u003eParticipants\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA cross-sectional survey was conducted among career field firefighters in Taipei City and New Taipei City. Convenience sampling was used to recruit fire departments that were accessible and in close proximity to researchers. Recruitment of firefighters involves two strategies. First, the research staff distributed study flyers with contact information from fire stations and fire training educational programs. Second, fire administrators disseminate study information to fire department members via email and mobile phone. A total of 371 firefighters were screened between January 2021 and December 2021. Among the screened participants, 300 completed the study. Thus, the final sample included 300 firefighters (18% women and 82% men) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Half of the participants were randomly assigned to the mortality salience (MS) group and the other half to the negative affect priming (NA) group. The sample size was estimated using G*Power \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e prior to data collection. To detect a medium effect size for the main effects in the ANCOVA with 95% power (f\u0026thinsp;=\u0026thinsp;0.25, alpha\u0026thinsp;=\u0026thinsp;0.05, numerator df\u0026thinsp;=\u0026thinsp;4, number of groups\u0026thinsp;=\u0026thinsp;2, number of covariates\u0026thinsp;=\u0026thinsp;1), a sample size of 150 participants per group was required. This study was approved by the Taipei Medical University Ethics Committee (N202104078) and the National Yang Ming Chiao Tung University Ethics Committee (YM111011EF) and was conducted in accordance with the Declaration of Helsinki. Data were collected between the two calendar dates, 01/01/2021 and 12/31/2021.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic Characteristics of field-firefighter participants.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMortality Salience (N\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eControl group (N\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.374\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.396\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.549\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e125(83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e121(81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25(17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e29(19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.454\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u0026ndash;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46(30.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e55(36.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e31\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e88(58.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e82(54.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e41 and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16(10.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13(8.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.592\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAssociate Degree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e120(80)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e117(78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBachelor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6(4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5(3.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePostgraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18(12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22(14.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6(4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6(4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary Role\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.062\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGeneral squad\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e96(64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e109(72.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecurity inspection brigade\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4(2.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6(4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDedicated EMS team\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25(16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19(12.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpecial rescue squad\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25(16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e16(10.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.653\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGeneral fieldwork branches\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e147(98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e148(98.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCorps\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3(2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2(1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCentral Firefighter Bureau\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0(0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0(0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePosition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.473\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.408\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTeam member\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e139(92.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e135(90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSquad leader\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8(5.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e12(8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBranch head\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3(2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3(2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWork experiences\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.239\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.742\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLess than 10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e69(46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e81(54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10 years and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e75 (50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e75(50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eMeasures and procedure\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBefore priming for MS or NA, participants completed questionnaires to assess their demographic information, including age, sex, educational attainment, and variables related to the job (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMortality salience (MS) cues\u003c/strong\u003e\u003cp\u003eMS was assessed using 28 mortality salience statements, in which participants had to judge whether they agreed with each statement \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The materials used for MS and NA priming were constructed in a fashion similar to that used in previous studies \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The MS group read and judged 14 statements related to death (e.g., \u0026lsquo;I would no longer exist from the day my body died\u0026rsquo;) for MS priming. The NA group read 14 statements referring to negative but death-unrelated emotions such as fear (e.g., \u0026lsquo;the future fills me with fear\u0026rsquo;) and anxiety (\u0026lsquo;I feel suffering that I cannot escape from in life\u0026rsquo;).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNeuroeconomic lottery choice task\u003c/strong\u003e\u003cp\u003eParticipants engaged in a lottery choice task in which they had to make choices between pairs of gambles. This modified economic lottery-choice task has been validated in several neuroeconomic studies \u003csup\u003e\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Each gamble incurred a high or low monetary outcome with each outcome associated with a specific probability. The associations between the probabilities and outcomes are represented by the corresponding colors (blue or orange). Pie charts represent the probabilities associated with the potential payoffs. Each pie consisted of 10 slices, with each slice corresponding to 10% probability. Each participant was presented with slices representing the probability of receiving a high (orange) or low (blue) monetary outcome ( Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Both monetary outcomes and probabilities varied across the trials. Coefficient of variation (CV) was used to measure the associated risk for each gamble. The CV is a scale-free metric calculated by dividing the standard deviation by the expected value. Previous research has noted that CV is a stronger method than standard economic measures of risk (e.g., standard deviation or variance) for predicting choice behavior, as risk calculations are often made relative to the average outcome \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Each pair of gambles always had one high-risk option (high CV) and one low-risk option (low CV). For performance incentive purposes, the compensation for each participant was based on actual winnings obtained from one randomly selected trial. Accordingly, participants were informed that each trial was independent of each other so that any trial was equally likely to be chosen to compensate for the participant. Each participant completed 40 trials in approximately 7 min.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMortality salience (MS) cues\u003c/strong\u003e\u003cp\u003eThe MS group read and judged 14 statements related to death during MS priming. The NA group read 14 other statements referring to death-unrelated priming of negative affect.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSafety work attitudes\u003c/b\u003e: Three work-related safety attitudes were measured using three 5-point Likert-type scales: personal protective equipment (PPE), safe work practices, and reporting and communication \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Cronbach\u0026rsquo;s alpha for the total score for safety-work attitudes was 0.9. Items related to safe work practices and PPE were derived from the recommended safety practices introduced in the NFPA 1500 Standard of the Fire Department Occupational Safety and Health Program \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. PPE utilization was gauged using a six-item scale (e.g., \u0026lsquo;I correctly use the appropriate PPE during firefighting operations, I correctly inspect all my PPE on a regular basis, and I personally check my SCBA [self-contained breathing apparatus] at the start of each shift). Each item was rated using a 5-point Likert-type scale with answers ranging from \u0026ldquo;almost never\u0026rdquo; to \u0026ldquo;almost always.\u0026rdquo; The Cronbach\u0026rsquo;s alpha for this scale was 0.72. Safe work practices were evaluated using a five-item scale (e.g., \u0026lsquo;every time I find defective firefighting equipment, I report it in order for it to be repaired or removed from service, \u0026lsquo; \u0026lsquo;I follow applicable SOP\u0026rsquo;s [standard operating procedures] during all emergency operations,\u0026rsquo; etc.). Each item was rated using a 5-point Likert-type scale with answers ranging from \u0026ldquo;almost never\u0026rdquo; to \u0026ldquo;almost always.\u0026rdquo; The Cronbach\u0026rsquo;s alpha for this scale was 0.79. Reporting and communication were appraised using a six-item scale (e.g., \u0026lsquo;I communicate potential hazards and exposure to firefighter personnel \u0026ldquo;and \u0026lsquo;I speak up and encourage others to get involved in safety issues\u0026rdquo;). Each item was rated using a 5-point Likert-type scale with answers ranging from \u0026ldquo;almost never\u0026rdquo; to \u0026ldquo;almost always.\u0026rdquo; These items were constructed using measures associated with reporting and communication \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, as well as communication and safety voice \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. The Cronbach\u0026rsquo;s alpha for this scale was 0.91.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003ePerceived work stress\u003c/strong\u003e\u003cp\u003eOccupational stress was measured by utilizing a six-item scale derived from the research of DeJoy and colleagues \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e (e.g., \u0026lsquo;in the last month, how often have you felt nervous and stressed because of work?\u0026rsquo;; \u0026rdquo; In the last month, how often have you felt you were unable to control the important things at work?\u0026rsquo;, etc.). Each item was rated using a 5-point Likert-type scale with answers ranging from \u0026ldquo;almost never\u0026rdquo; to \u0026ldquo;almost always.\u0026rdquo; The Cronbach\u0026rsquo;s alpha for this scale was 0.87.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eFirefighter burnout\u003c/strong\u003e\u003cp\u003eBurnout was gauged using the Malach-Pines 10-item scale (for example, When you think about your work, overall, how often do you feel hopeless?\u0026rsquo;; \u0026rdquo; When you think about your work, overall, how often do you feel disappointed with people?\u0026rsquo;, etc.) \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Each item was rated using a 5-point Likert-type scale with answers ranging from \u0026ldquo;almost never\u0026rdquo; to \u0026ldquo;almost always.\u0026rdquo; The Cronbach\u0026rsquo;s alpha for this scale was 0.92.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eWork-family conflict\u003c/strong\u003e\u003cp\u003eWork-family conflict was evaluated by utilizing a three-item scale adapted from the research of Carlson and colleagues \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e (e.g., \u0026lsquo;when I get home from work, I am often too frayed to participate in family activities/responsibilities\u0026rsquo;, \u0026lsquo;when I get home from work, I am often so emotionally drained, that it prevents me from contributing to my family\u0026rsquo;, and \u0026lsquo;when I come home, due to all the pressures at work, I am too stressed to do the things I enjoy\u0026rsquo;). Each item was rated on a 5-point Likert-type scale, with answers ranging from \u0026ldquo;strongly disagree\u0026rdquo; to \u0026ldquo;strongly agree.\u0026rdquo; Cronbach\u0026rsquo;s alpha for this scale was 0.86.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eEngagement\u003c/b\u003e: Work engagement was gauged using the short version of the Utrecht Work Engagement Scale \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e during the \u0026ldquo;Time 7\u0026rdquo; data collection. It is a nine-item scale that measures three interconnected dimensions of engagement: vigor (three items), dedication (three items), and absorption (three items). Each item was rated using a 5-point Likert scale, with answers ranging from \u0026ldquo;strongly disagree\u0026rdquo; to \u0026ldquo;strongly agree.\u0026rdquo; We tested our hypotheses using a composite measure of engagement (Cronbach\u0026rsquo;s alpha\u0026thinsp;=\u0026thinsp;.92).\u003c/p\u003e\u003cp\u003e\u003cb\u003eDeath anxiety\u003c/b\u003e: Death anxiety was measured using the Revised DA Scale \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. The measure is a 25-item scale which measures three interconnected facets of DA: anxieties over \u0026ldquo;not being\u0026rdquo; (e.g., \u0026lsquo;the total isolation of death is frightening to me\u0026rsquo;), fear of pain and helplessness (e.g., \u0026lsquo;the pain involved in dying frightens me\u0026rsquo;), and life after death and decomposition (e.g., \u0026lsquo;the subject of life after death troubles me greatly\u0026rsquo;). Furthermore, a composite measure was employed according to the recommendations of the authors (Cronbach\u0026rsquo;s alpha\u0026thinsp;=\u0026thinsp;.93).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eDescriptive statistics for all variables are provided in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. All demographic variables were independent of the experimental group assignment (MS vs. NA, all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.05), confirming the validity of the randomized control procedure.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMeans of dependent variables as a function of experimental groups.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMortality Salience (n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eControl group (n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDeath anxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.038\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSafety attitude total scores\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e47.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePersonal protective equipment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.041\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSafe work practices\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.119\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReporting and communication\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.026\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupational stress\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.756\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWork-family conflict\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.242\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWork engagement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.201\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFirefighter burnout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.711\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNeuroeconomic behaviors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh-risk items selected\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.96\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow-risk items selected\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.971\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCV of high-risk items\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.805\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCV of low-risk items\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.341\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal CV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.895\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRTs of high-risk decisions (sec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.882\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRTs of low-risk decisions (sec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.907\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal RTs (sec)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.857\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eNeuroeconomic lottery choice performance\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe 2 (PRIMING: MS vs. NA; a between-subjects factor) \u0026times; 2 (WORK EXPERIENCE: junior vs. senior; a between-subjects factor) ANOVA on the percentage of high-risk decisions showed a main effect of work experience (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 296\u003c/sub\u003e = 4.34, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.038, pη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.014; junior vs. senior: 0.394\u0026thinsp;\u0026plusmn;\u0026thinsp;0.019 vs. 0.338\u0026thinsp;\u0026plusmn;\u0026thinsp;0.019, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE) and a marginal trend in the interaction between PRIMING and WORK EXPERIENCE (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 296\u003c/sub\u003e = 3.2, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.075, pη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.011) that approached significance, whereas there was no main effect of PRIMING (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 296\u003c/sub\u003e = 0.001, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.969). The PRIMING effect on high-risk decisions had opposite directions depending on the factor of WORK EXPERIENCE, in which MS increased high-risk decisions in junior field-firefighters (MS vs. NA: 0.419\u0026thinsp;\u0026plusmn;\u0026thinsp;0.027 vs. 0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.026) but decreased high-risk decisions in senior field-firefighters (MS vs. NA: 0.315\u0026thinsp;\u0026plusmn;\u0026thinsp;0.027 vs. 0.362\u0026thinsp;\u0026plusmn;\u0026thinsp;0.028), the preplanned experience-wise comparisons showed that junior field-firefighters made more high-risk decisions than senior field-firefighters after MS priming ( 0.419\u0026thinsp;\u0026plusmn;\u0026thinsp;0.027 vs. 0.315\u0026thinsp;\u0026plusmn;\u0026thinsp;0.026, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.74, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007). But this effect was not found in the NA priming of the control condition (junior vs. senior: 0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.026 vs. 0.362\u0026thinsp;\u0026plusmn;\u0026thinsp;0.028, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.21, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.835). The same pattern of risk performance results was identified by analysis using the coefficient of variation (CV) [MS: (junior vs. senior: 0.279\u0026thinsp;\u0026plusmn;\u0026thinsp;0.012 vs. 0236\u0026thinsp;\u0026plusmn;\u0026thinsp;0.011, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.55, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012) and NA: (junior vs. senior: 0.259\u0026thinsp;\u0026plusmn;\u0026thinsp;0.011 vs. 0255\u0026thinsp;\u0026plusmn;\u0026thinsp;0.012, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.24, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.808)] (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eprevious studies have shown differences in how older and younger adults process MS \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, the aforementioned experience-modulating effect on risk performance was further confirmed by an ANCOVA model with the same 2 (PRIMING) \u0026times; 2 (WORK EXPERIENCE) design and an additional covariate of age (the interaction between PRIMING and WORK EXPERIENCE: \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 3.185, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.075, pη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.011). However, the main effect of work experience was no longer significant after controlling for age (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 2.445, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.119, pη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.008). While the ANOVA analysis of the reaction times did not yield any effect of PRIMING, WORK EXPERIENCE, or their interaction (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.4), the speed of risky decision-making was found to be negatively correlated with the frequency of risky decisions (r = -0.309, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and CV (r = -0.310, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that a quicker response predicted riskier decisions. This speed-risk association stood after controlling for the effect of work experience and age (CV: β = -0.312, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; risky decisions: β = -0.31, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eTo test the hypotheses and dissect the effect of work experience from the effect of age, which were both highly correlated (r\u0026thinsp;=\u0026thinsp;0.726, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), hierarchical moderated multiple regression was used. First, we entered control variables (age). Second, we entered the predictor and moderator variables (work experience, MS priming, and reaction time). In the third step, we entered the cross product of the predictor and moderator variables. All variables were standardized before the model was computed using cross-product terms. Finally, we examined the change in R\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e from Steps 2 to 3 to determine whether the moderating variable had a significant effect. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the regression results.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eModerating effect of work experience on the response to mortality salience in field-firefighters.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStep 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStep 2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStep 3\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eDV: risky decisions (%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.079\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWork experience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.061\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.614**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReaction times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.31***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.53***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMS priming\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.168\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWork experience \u0026times; Reaction times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.724***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWork experience \u0026times; Reaction times \u0026times; MS priming\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.207*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.103\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.145\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΔ\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.097***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.042**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eNote. Beta weights provided are in their standardized form. DV\u0026thinsp;=\u0026thinsp;dependent variable; MS\u0026thinsp;=\u0026thinsp;mortality salience. * p\u0026thinsp;\u0026lt;\u0026thinsp;.1. ** p\u0026thinsp;\u0026lt;\u0026thinsp;.01. *** p\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eHypothesis a, risky decisions related negatively to work experience, was not supported (β = -0.061, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.458). Hypothesis b, risky behaviors related to time pressure and shortened reaction times, was supported (β = -0.31, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Hypothesis c, risky decisions related to MS priming, was not supported (β\u0026thinsp;=\u0026thinsp;0.009, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.875). Hypothesis d examined the moderating effect of work experience on the relationship between MS priming, reaction times, and risky behavior. The significant interaction terms explained 4.2% of the additional variance in risky decisions above and beyond work experience, reaction times, and MS priming. This relationship was plotted (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and, consistent with our predictions, the moderating effect of MS (simple slope = -0.237, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.042) was higher than that of NA (simple slope\u0026thinsp;=\u0026thinsp;0.023, ns) on the speed-risk relationship, which was only found in senior firefighters but not in junior field-firefighters (MS: simple slope = -0.079, ns; NA: simple slope\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.187, ns). MS priming modulated the speed-risk relationship in senior firefighters, and increased RTs were associated with reduced risk. However, this modulating effect of MS was not observed in the junior firefighters.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSafety work attitudes results\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe 2 (PRIMING: MS vs. NA; a between-subject factor) \u0026times; 2 (WORK EXPERIENCE: junior vs. senior; a between-subject factor) ANCOVA (with a covariate of age) on PPE showed a main effect of PRIMING (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 4.057, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.045, pη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.014; MS vs. NA: 18.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.311 vs. 17.823\u0026thinsp;\u0026plusmn;\u0026thinsp;0.312, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;se), and a marginal trend in the interaction between PRIMING and WORK EXPERIENCE (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 2.974, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.086, pη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.01) that approached significance. Preplanned experience-wise comparisons showed that MS significantly increased (compared to NA) the PPE attitude in junior field-firefighters (MS: 19.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.378; NA: 17.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.436, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.849, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005) but not in senior field-firefighters (MS: 18.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.429; NA: 17.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.514, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.204, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.839) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe same ANCOVA model on safe work practices revealed a main effect of age as a covariate (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 6.25, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013, pη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.021), whereas there was no effect of PRIMING, WORK EXPERIENCE, or their interaction. Attitudes towards safe work practices were positively associated with age (simple slope\u0026thinsp;=\u0026thinsp;0.154, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.008). Regarding reporting and communication attitudes, ANCOVA results showed a main effect of PRIMING (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 4.546, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.034, pη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.015), with a higher score in the MS condition (MS: 15.943\u0026thinsp;\u0026plusmn;\u0026thinsp;0.429; NA: 14.649\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43) after controlling for age as a covariate (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 2.916, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.089, pη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.01). The other variables did not reach statistical significance (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.4).\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults of perceived work stress, firefighter burnout, work-family conflict, and work engagement\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe 2 (PRIMING: MS vs. NA, a between-subjects factor) \u0026times; 2 (WORK EXPERIENCE: junior vs. senior; a between-subjects factor) ANCOVA (with a covariate of age) on occupational stress did not show any effect of PRIMING (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 0.15, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.698), WORK EXPERIENCE (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 0.204, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.625), or their interactions (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 0.586, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.444). Additionally, applying the same model to firefighter burnout and work-family conflict did not show any effect on targeted variables or their interaction (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.1).\u003c/p\u003e\u003cp\u003eRegarding the work engagement, the ANCOVA results showed a main effect of WORK EXPERIENCE (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 8.399, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004, pη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.028; junior vs. senior: 27.035\u0026thinsp;\u0026plusmn;\u0026thinsp;0.928 vs. 22.624\u0026thinsp;\u0026plusmn;\u0026thinsp;0.976, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;se) with higher engagement found in junior field-firefighters even after controlling for the covariate of age (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 3.62, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.058, pη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.012). The other variables did not reach statistical significance (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.1)\u003c/p\u003e\u003cp\u003e\u003cb\u003eDeath anxiety results\u003c/b\u003e\u003c/p\u003e\u003cp\u003eANCOVA on death anxiety showed a main effect of age as a covariate (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 4.589, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.033, pη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.015), as well as a main effect of PRIMING (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1, 295\u003c/sub\u003e = 4.88, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028, pη\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.016). Death anxiety significantly increased after MS priming (MS: 1.049\u0026thinsp;\u0026plusmn;\u0026thinsp;0.058; NA: 0.869\u0026thinsp;\u0026plusmn;\u0026thinsp;0.058), while it was negatively associated with age in our field firefighter samples (simple slope = -0.169, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.003). Preplanned experience-wise comparisons showed that MS significantly increased (compared to NA) death anxiety in junior field-firefighters (MS: 1.171\u0026thinsp;\u0026plusmn;\u0026thinsp;0.083; NA: 0.922\u0026thinsp;\u0026plusmn;\u0026thinsp;0.086, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.066, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04) but not in senior field-firefighters (MS: 0.918\u0026thinsp;\u0026plusmn;\u0026thinsp;0.079; NA: 0.814\u0026thinsp;\u0026plusmn;\u0026thinsp;0.075, \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.94, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.349) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe objective of the present study was to assess the relationship between mortality salience (MS), work experience, and risky decision making, as well as the psychological and behavioral effects of the association on field-firefighters, all of which included demographic information such as gender, age, education level, and job-related variables as covariates. Regarding our previously stated hypotheses, we found that Hypothesis a), which stated that risky behaviors would be negatively related to work experience, was not supported, as there was no significant relationship between these two variables; Hypothesis b) was supported, as risky behaviors were correlated with shorter reaction times (RTs) regarding the neuroeconomic lottery choice task; Hypothesis c), which stated that risky behaviors would be related to MS priming, was not supported, as there was no significant association between MS and risky decision-making; and Hypothesis d) was partially supported, as the analyses yielded a moderating effect of MS on the relationship between the speed of RTs and risky decision-making, but only among senior field-firefighters, who showed increased RTs when making low-risk decisions under MS priming. Interestingly, although this modulating effect was not found in junior firefighters, an increase in safety attitudes was observed in this group.\u003c/p\u003e\u003cp\u003eOriginally, researchers concluded that time pressure increases risk aversion \u003csup\u003e\u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. The explanation, based on the dual-system model of decision-making \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, posited that this was probably due to time pressure interrupting the engagement of System 2 (i.e., involved in reasoning), thus leaving System 1 (i.e., involved in high-speed automatic processes) to dominate the decision-making process \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Nevertheless, recent research reevaluating said studies have found that this may be due to errors in experimental design \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. This is in line with the findings of the present study, which showed that field-firefighters\u0026rsquo; risky choices correlated with shorter RTs. Nevertheless, the relationship between time constraints and risky choices may be less related to a change in risk preference and more related to a decrease in choice consistency. This is because of the time pressure incurred in a speed-accuracy tradeoff, meaning that higher RTs in decision-making processes prompt less consistency and/or increase errors \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eParadoxically, the finding that the relationship between risky behaviors and work experience was not significant is both surprising and expected. It is surprising that researchers might be inclined to use work experience as a proxy for MS. It is logical, given that we might be tempted to reason that the greater the work experience, the greater the exposure to life-threatening circumstances encountered by firefighters; thus, MS incurs a cumulative effect. Nevertheless, once the other variables are included, this is expected. Studies assessing risky decision-making in the firefighter population have observed that firefighter safety performance tends to be modulated by work-family conflict and work stress, which in turn predict burnout, and it is the occurrence of burnout that contributes significantly to faulty risk assessment and subsequent risky choices \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Hence, we can observe that risky firefighter decision-making might be tied to factors such as time of rest and recovery from the demands of the job, reduced ability and physical health, diminished performance motivation \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, reduced information processing, and cognitive impairment \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, as well as decreased levels of commitment towards the job \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, which at the same time are all, once more, related to burnout \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Additionally, our findings did not reveal any interactions between MS and work stress, work-family conflict, work engagement, or burnout.\u003c/p\u003e\u003cp\u003eFurthermore, even if work experience equated with MS in some way, our analyses of the relationship between risky choices and MS priming yielded no significant associations. Considering the contradictory findings of previous studies on this relationship \u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11 CR12\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, it is not difficult to see that other factors might contribute to this association (similar to the relationship between risky choices and work experience). Even when other studies have narrowed down to possible modulators between MS and risky behaviors, such as the loci of control \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, there still appears to be a complex interaction between the loci of control and other factors, such as different professions \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e or whether the decision-making process occurs in the military domain \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, among many others \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Therefore, future studies with more robust and stricter experimental designs are required.\u003c/p\u003e\u003cp\u003eHowever, when assessing the moderating effect of MS on the relationship between the speed of RTs and risky decision-making dependent on work experience, we found that MS priming modulated the speed-risk relationship, but only in senior field-firefighters, who showed increased RTs when making low-risk decisions under MS priming. However, this effect was not observed in the junior-field firefighter group. These findings contrast with previous research showing that older adults tend to be less influenced by MS because of possessing an increased awareness of death, greater susceptibility to physical ailments, and probably substantially more experience of having lost loved ones \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Nevertheless, this discrepancy may be partially attributed to the locus of control. First, owing to the fact it seems that the locus of control tends to become increasingly internal as a person ages \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Second, because of their interaction with MS, it has been observed that MS increases actual risk-taking in individuals with an external locus, whereas it decreases risk-taking in individuals with an internal locus. However, regardless of possessing an internal or external locus of control, it appears that both groups equally maintained an increased assessed level of risk under MS-priming conditions \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Accordingly, the increased risk-taking behaviors found in junior firefighters as an effect of MS priming may be ascribed to the external locus of control associated with work experience \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. This might also be related to the finding that field-junior firefighters increased their safety attitudes despite not reducing their risk-taking behaviors. Whereas senior field-firefighters develop an internal locus of control capable of conveying a greater sense of agency in regards to their own mortality, hence, developing a more risk averse attitude overall; the junior field-firefighters\u0026rsquo; external locus of control might yield a disposition to engage in risky decision-making, all while their heightened risk assessment urges them to engage in extraneous safety attitudes \u0026ndash;such as the utilization of PPE\u0026ndash; in order to mitigate injury and/or death, and in spite of still engaging in risk-taking behaviors. However, it is important to note that previous research has also observed that the nature of the risk greatly influences the extent to which those with an internal or external locus become greater risk takers \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, as it appears that those with an internal locus tend to take greater risks on skill tasks, whereas those with an external locus tend to take greater risks on tasks involving chance. This is because those with an internal locus are more likely to believe that what happens to them is a result of their own skills, whereas those with an external locus are more likely to believe that chance is the determining factor over what happens to them. As such, future research delving into the interactions between the loci of control, risk-taking behaviors, and considering the nature of risk, specifically in the firefighter population, is highly warranted, as it is a profession where a combination of skill (e.g., tactical preparation) and chance (e.g., critical and rapidly changing conditions at the emergency scene) seems to converge in a significant manner.\u003c/p\u003e\u003cp\u003eTo the best of our knowledge, this is the first study to assess the effects of mortality salience on risk-taking behaviors and safety attitudes by taking into account factors such as working experience, work stress, burnout, work-family conflict, and work engagement, alongside demographic factors in a population of field-firefighters. Our findings show that risky choices are modulated by time constraints, and that MS modulates RTs when engaging in risky decision-making among senior field firefighters. Furthermore, although MS did not reduce risk-raking behaviors in junior firefighters, it did increase their safety attitudes such as PPE utilization. Consequently, it is important to devote more training to senior field-firefighters on the importance of PPE utilization, while aiming for more resources towards the development of a system that minimizes goal conflicts (e.g., self-protection vs. mission objective) \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e and rewards safer choices \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e, when it comes to junior field-firefighters.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Taipei Medical University Ethics Committee (N202104078) and the National Yang Ming Chiao Tung University Ethics Committee (YM111011EF), and was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all the participants. At the end of the study, all the participants received monetary compensation for their participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eR.M.M., K. K. G., and C.C. conceived and conceptualized the study. T.H.P. and C. M. C. collected and analyzed the data. R.M.M., K.K.G., and C.C. reviewed the literature and drafted the first manuscript. All authors contributed to the writing and revision of the final draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that this research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was financially supported by grants from Wan-Fang Hospital, Taipei Medical University (112TMU-WFH-15), and the National Science and Technology Council (112-2410-H-038-029 -; 112-2636-H-038-005 -), Taiwan.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOpen practices statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data, code, and materials for this study have not been made publicly available; however, requests for said data, code, and/or materials can be made to the corresponding authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eObuobi-Donkor, G. et al. ,\u003cem\u003e. 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Behav.\u003c/em\u003e \u003cb\u003e74\u003c/b\u003e, 272\u0026ndash;279 (2020).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Firefighters, Mortality salience, Risk-taking behaviors, Safety attitudes, Risky decision-making","lastPublishedDoi":"10.21203/rs.3.rs-7296428/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7296428/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo evaluate the association between MS, work experience, and risky decision making, including its psychological and behavioral effects, on field-firefighters.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003ecross-sectional study was conducted using a sample of field firefighters (n\u0026thinsp;=\u0026thinsp;300). Half of the participants (n\u0026thinsp;=\u0026thinsp;150) were randomly assigned to the MS priming condition and the other half to the negative affect priming condition. Before priming, the participants completed questionnaires to assess their demographic information, including age, gender, educational level, and job-related information. After priming, they performed a neuroeconomic lottery choice task to assess risk-taking behavior, and a safety work attitude survey. Variables such as work stress, burnout, work-family conflict, work engagement, and death anxiety were also evaluated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eRisky behaviors correlated with shorter reaction times (RTs) in the neuroeconomic lottery choice task. We observed a moderating effect of MS on the relationship between RT speed and risky decision making dependent on working experience among senior firefighters, who showed increased RTs when making low-risk decisions under MS priming. MS did not reduce risk-taking among junior firefighters, but did increase their safety attitudes.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eTo the best of our knowledge, this is the first study to assess the effects of MS on risk-taking behaviors and safety attitudes in firefighters. It is important to devote more training to senior field-firefighters on the importance of PPE utilization, while aiming for more resources towards the development of a system that minimizes goal conflicts (e.g., self-protection vs. mission objective) and rewards safer choices for junior field-firefighters.\u003c/p\u003e","manuscriptTitle":"Mortality Salience Enhances Safety Attitudes Without Reducing Risk-Taking in Junior Firefighters","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-03 23:57:41","doi":"10.21203/rs.3.rs-7296428/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-26T08:34:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-25T13:37:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"117842725094410764642719329673352178412","date":"2025-09-25T05:33:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-01T04:59:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"222867009214508249764308135176757147035","date":"2025-08-27T03:00:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-27T01:46:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-07T09:53:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-06T06:56:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-06T04:11:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-08-05T04:58:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"30688456-4e8e-4968-9f4c-30573301c3d5","owner":[],"postedDate":"September 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":53973274,"name":"Health sciences/Health care"},{"id":53973275,"name":"Health sciences/Health occupations"},{"id":53973276,"name":"Biological sciences/Neuroscience"},{"id":53973277,"name":"Biological sciences/Psychology"},{"id":53973278,"name":"Social science/Psychology"},{"id":53973279,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-03-12T08:09:57+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-03 23:57:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7296428","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7296428","identity":"rs-7296428","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}