Sociodemographic and work-related factors associated with psychological resilience in South African healthcare workers: a cross-sectional study

Sociodemographic and work-related factors associated with psychological resilience in South African healthcare workers: a cross-sectional study | 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 Research Article Sociodemographic and work-related factors associated with psychological resilience in South African healthcare workers: a cross-sectional study Thandokazi Mcizana, Shahieda Adams, Saajida Khan, Itumeleng Ntatamala This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4413230/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Aug, 2024 Read the published version in BMC Health Services Research → Version 1 posted 4 You are reading this latest preprint version Abstract Background: Psychological resilience facilitates adaptation in stressful environments and is an important personal characteristic that enables workers to navigate occupational challenges. Few studies have evaluated the factors associated with psychological resilience in healthcare workers. Objectives: To determine the prevalence and factors associated with psychological resilience in a group of South African medical doctors and ambulance personnel. Materials and Methods: This analytical cross-sectional study used secondary data obtained from studies conducted with healthcare workers. Factors associated with resilience, as measured by the Connor-Davidson Resilience Scale-10 (CD-RISC-10), were evaluated. Results: A total of 647 healthcare workers were included in the study. Resilience scores were low overall (27.6 ± 6.6) but higher for ambulance personnel (28.0 ±6.9) than for doctors (27.1 ± 6.0) (p=0.006). The factors associated with high resilience scores in doctors were male gender (p< 0.001), higher income (p=0.020), and current smoking (p=0.012), while for ambulance personnel, there was previous alcohol use (p=0.002). Significantly lower resilience was observed in participants with mental health conditions (doctors: p=0.037; ambulance personnel: p=0.010) who were receiving treatment for mental health conditions (ambulance personnel: p=0.029). Multivariable analysis confirmed that the protective factors for doctors were current smoking status (β= 3.52, p=0.009) and a higher salary (β= 5.11, p=0.006), while for ambulance personnel, the protective factor was previous alcohol use (β=3.22, p=0.003). Female gender (β=-1.77, p=0.032) and working overtime with doctors (β=-5.11 p=0.006) increased the likelihood of low resilience. Conclusions: Resilience was relatively low in this group of South African healthcare workers. The strong association between low resilience and individual and workplace factors provides avenues for early intervention and building resilience in healthcare workers. resilience healthcare workers ambulance personnel occupational doctors Figures Figure 1 INTRODUCTION Psychological resilience is an important personal characteristic that enables healthcare workers to navigate the challenges encountered in their occupation. [ 1 ] Herrman et al. (2011) explored the evolution of the term in their narrative review and concluded that fundamentally, resilience is the ‘inherent ability’ for one to adapt positively following adversity or stressful events. [ 2 ] As such, psychological resilience describes an individual's coping mechanism, optimism, self-efficacy, high levels of hope and thriving mental health amid adversity and challenging circumstances. [ 3 ] The healthcare systems of most low- and middle-income countries (LMICs) are under severe strain due to high patient load, significant burden of communicable and noncommunicable diseases, lack of human and financial resources, the brain drain phenomenon, corruption and poor administration. [ 4 , 5 , 6 , 7 ] South Africa faces similar challenges, with a quadruple burden of disease including HIV/AIDS and tuberculosis, high maternal and child mortality, high levels of violence and injuries and noncommunicable diseases. [ 8 ] Poor health outcomes and a disproportionate distribution of healthcare resources in the country may be ascribed to the legacy of an undemocratic political apartheid regime (1948–1993) compounded by ongoing challenges in managing the health system in a post-apartheid South Africa. [ 7 , 8 ] South Africa's government is currently in the process of implementing a National Health Insurance (NHI) scheme to address the tremendous challenges that plague the health system. However, the country’s preparedness remains uncertain, especially given the ongoing shortage of healthcare worker posts and rising unemployment in the health sector. [ 8 , 9 ] These challenges place immense pressure on employed healthcare workers, making psychological resilience an important inherent ability that can aid in supporting and protecting healthcare workers against adverse mental health outcomes and contributing to improved service delivery. Research on the role of psychological resilience as a protective factor in frontline healthcare workers has increased recently during the coronavirus disease (COVID-19) pandemic. Much of the research in this area has been conducted in high-income countries (HICs) and China, and little is known about the factors that predict psychological resilience in workers in LMICs, including South Africa, an upper middle-income country. Robertson et al. (2016), in their systematic review on resilience among primary healthcare workers, found that most research on the topic primarily frames resilience as an explanatory variable in relation to burnout. [ 10 ] This study therefore aimed to determine the prevalence and factors associated with the psychological resilience of healthcare workers practising in the South African healthcare system. METHODS This is an analytical cross-sectional study using secondary data obtained from two cross-sectional studies of healthcare workers in South Africa. The first study focused on ambulance personnel in the Western Cape province and the second study focused on medical doctors in the Eastern Cape province. [ 11 , 12 ] The present study included data on all healthcare workers who had completed the Connor-Davidson Resilience Scale-10 (CD-RISC-10) questionnaire and relevant sociodemographic and occupational questions. This study was approved by the University of Cape Town’s Human Research Ethics Committee (HREC 712/2023). Measurements This study used secondary data generated from self-administered questionnaires that consisted of sociodemographic factors, work-related factors, and the CD-RISC-10 questionnaire. Sociodemographic and work-related factors The data obtained from the questionnaires included information on age, gender, language, marital status, job category, professional qualifications, overtime work, salary, and length of service. In addition, data on mental health and medical history, including self-reported mental health conditions and substance use (smoking, alcohol use, illicit and prescription drugs), year of debut, and the use of substances to manage work-related stress, were obtained. 10-item Connor-Davidson Resilience Scale (CD-RISC-10) Psychological resilience (outcome variable) was measured using the 10-item CD-RISC questionnaire. The CD-RISC-10 is a self-administered 10-item questionnaire, which is a shorter version of the CD-RISC-25. Participants identified their adaptive behaviours in stressful situations and scored them on a 5-point Likert scale (0 = not at all true, 4 = true nearly all the time). 13 The resulting scores ranged between 0 and 40. This scale has previously been reported to be a reliable and efficient measure of psychological resilience for adults. [ 14 ] In addition, it has previously been validated for use in South Africa by Pretorius et al. (2022) as a measure of psychological resilience and has been used in several studies of South African healthcare workers. [ 6 , 11 , 12 , 15 , 16 , 17 ] Written permission to use the scale was previously obtained. [ 11 , 12 ] Statistical analysis After ethical approval, the secondary data were received and cleaned in password-protected Microsoft Excel. R statistical software (version 4.3.1) was used for analysing the data and performing the statistical tests. Descriptive statistics for continuous variables in this study are presented as the means (standard deviations) and medians (interquartile ranges) where appropriate. In addition, descriptive statistics for categorical variables are presented as proportions. Mann‒Whitney and Kruskal‒Wallis tests were used to determine significant differences in CD-RISC-10 scores. In addition, unadjusted logistic regression and adjusted logistic regression (adjusted for age and gender) were performed. Low resilience, as an outcome measure, was defined as a CD-RISC-10 score less than 25.5. [ 18 ] Variables from the adjusted logistic regression analysis with a p value less than 0.250 were selected for the multivariable linear regression model to investigate factors associated with increasing resilience scores. Due to the size of the dataset, multinomial logistic regression was not performed because it would not produce useful results. The beta statistics, odds ratios and 95% confidence intervals were calculated for both the univariable and multivariable analyses. A p value of less than 0.050 was considered the cut-off point for statistical significance. Missing data Only the age factor had missing data of more than 1% of the total recorded values and thus necessitated imputation (see Supplementary Table S1 and Supplementary Fig. S1 online). Age is also important when performing this regression analysis, as age has previously been reported to be an important confounder of psychological resilience and needs to be adjusted for when performing regression analysis. [ 19 , 20 , 21 ] Multiple imputation was chosen because it results in valid statistical inferences. [ 22 ] To assess the sensitivity of the results with respect to the multiple imputation method chosen, multiple imputation using the three methods available in the Multivariate Imputation by Chained Equation (MICE) package in R were performed (see Supplementary Table S2 online). The imputed data from the Classification and regression tree (CART) method was chosen for use in the following regression analysis, given its minimal impact on the distribution of the age factor. Supplementary Fig. S2 shows the distribution of the age factor before and after CART imputation. RESULTS From the original datasets received, only one record was removed because the participant indicated that they were gender nonconforming resulting in several skewed results. In total therefore, 647 questionnaires were included in the present analysis, of whom 259 were from doctors and 388 were from ambulance personnel. Sociodemographic and work-related characteristics Among the 259 doctors, the majority were female (57.9%), while most ambulance personnel were male (54.9%) ( Table 1 ). Most of the doctors were English speaking (66.0%) and were in the 20–29 years age group (42.5%), while most of the ambulance personnel were Afrikaans speaking (45.9%) and were in the 30–39 years age group (37.1%). Most respondents who worked for the ambulance service in operational roles had direct contact with patients (42.8%). Doctors' years of service in the current role were lower, with a median of 2 (IQR: 4), while ambulance personnel had a median of 7 (IQR: 9). A greater percentage of doctors reported working overtime (96.9%) than ambulance personnel (68.6%). Substance use, mental health, and work-related stress management The prevalence of smoking was greater among ambulance personnel (30.4%) than among doctors (8.9%), while current alcohol usage was greater for doctors (64.1%) than for ambulance personnel (51.5%) ( Table 2 ). Only 2.8% of the overall sample reported current use of illicit substances or drugs. A quarter (25.1%) of the doctors reported having been diagnosed with a mental health condition compared to 11.1% of the ambulance personnel. In addition, 17.4% of doctors reported being on treatment for a mental health condition, compared to 7.2% of ambulance personnel. Regarding managing work-related stress (WRS), more than a quarter (26.5%) of the ambulance personnel self-reported the need to smoke to manage WRS, while 20.5% of doctors reported the need to use alcohol to manage WRS. Interestingly, 4.5% of the overall sample felt the need to use illicit drugs to manage WRS, which is higher than the current prevalence of illicit drug use. Most participants supported the provision of psychological counselling (76.0%) and addressing staff shortages (74.7%) to assist with reducing WRS. Overall CD-RISC-10 score and level of resilience The overall average CD-RISC-10 score was 27.6 (±6.6) among the 647 healthcare workers in this study ( Table 2 ). The average CD-RISC-10 score for the ambulance personnel was 28.0 (±6.9), which was significantly greater than the average score of 27.1 (±6.0) for the doctors (p = 0.006). The total score for the CD-RISC-10 can be classified into a 4-level variable using quantiles: lowest (0–24), low (25–28), moderate (29–32), and highest (33–40). 13 More than half of the doctors (58.7%) were classified as having the lowest or lowest resilience. However, for ambulance personnel, the majority (54.2%) were classified as having moderate or high resilience. Table 1: Sociodemographic and work-related characteristics Participant characteristics Doctors Ambulance personnel Overall N % N % N % Gender Male 109 42.1% 213 54.9% 322 49.8% Female 150 57.9% 175 45.1% 325 50.2% Age 20 – 29 110 42.5% 52 13.4% 162 25.0% 30 – 39 73 28.2% 144 37.1% 217 33.5% 40 – 49 50 19.3% 106 27.3% 156 24.1% > 50 26 10.0% 37 9.5% 63 9.7% Missing 0 0.0% 49 12.6% 49 7.6% Home language English 171 66.0% 122 31.4% 293 45.3% Afrikaans 54 20.8% 178 45.9% 232 35.9% IsiXhosa 31 12.0% 84 21.6% 115 17.8% Other 3 1.2% 4 1.0% 7 1.1% Relationship Status Married 117 45.2% 174 44.8% 291 45.0% Never married 127 49.0% 172 44.3% 299 46.2% Divorced/Separated/Widowed 15 5.8% 42 10.8% 57 8.8% Professional health qualification Yes 259 100.0% 322 83.0% 581 89.8% No 0 0.0% 66 17.0% 66 10.2% Job category Operational services/EMS 0 0.0% 277 71.4% 277 42.8% Support staff/EMS 0 0.0% 111 28.6% 111 17.2% Junior doctors 85 32.8% 0 0.0% 85 13.1% Senior doctors 174 67.2% 0 0.0% 174 26.9% Years employed in current role † 2 (4) 7 (9) 5 (8) Missing (%) 0 0.0% 5 1.3% 5 0.8% Over-time work Yes 251 96.9% 266 68.6% 517 79.9% No 8 3.1% 122 31.4% 130 20.1% Monthly Salary (ZAR) R0 - R15 000 0 0.0% 165 42.5% 165 25.5% R15 001 - R30 000 0 0.0% 193 49.7% 193 29.8% R30 001 - R50 000 88 34.0% 30 7.7% 118 18.2% > R50 001 171 66.0% 0 0.0% 171 26.4% † Data are presented as the median (interquartile range) EMS: Emergency medical services; ZAR/R: South African Rand Table 2. Frequency and distribution of general and mental health-specific variables Participant characteristics Doctors Ambulance personnel Overall N % N % N % Age started smoking (m, SD) † 20.1 3.7 18.6 4.6 18.9 4.4 Age started illicit drugs (m, SD) † 20.1 3.8 21.4 6.6 21.0 6.0 Smoking history Never used 213 82.2% 235 60.6% 448 69.2% Previous smoker 23 8.9% 35 9.0% 58 9.0% Current smoker ‡ 23 8.9% 118 30.4% 141 21.8% Alcohol history Never used 54 20.8% 110 28.4% 164 25.3% Previous alcohol user 39 15.1% 78 20.1% 117 18.1% Current drinker ‡ 166 64.1% 200 51.5% 366 56.6% Illicit drug use Never used 239 92.3% 342 88.1% 581 89.8% Previous illicit drug user 13 5.0% 35 9.0% 48 7.4% Current illicit drug user ‡ 7 2.7% 11 2.8% 18 2.8% Substance use to manage WRS Feel need to smoke to manage WRS 45 17.4% 103 26.5% 148 22.9% Feel need to drink alcohol to manage WRS ‡ 53 20.5% 44 11.3% 97 15.0% Feel need to use illicit drugs to manage WRS ‡ 13 5.0% 16 4.1% 29 4.5% Mental health Ever diagnosed with a mental health condition ‡ 65 25.1% 43 11.1% 108 16.7% Currently on treatment for mental health condition 45 17.4% 28 7.2% 73 11.3% Resilience, CD-RISC-10 score (m, SD) † 27.1 6.0 28.0 6.9 27.6 6.6 Lowest (0 - 24) 75 29.0% 101 26.0% 176 27.2% Low (25 - 28) 77 29.7% 77 19.8% 154 23.8% Moderate (29 - 32) 63 24.3% 105 27.1% 168 26.0% Highest (33 - 40) 44 17.0% 105 27.1% 149 23.0% Which intervention would assist most with reducing WRS? Address staff shortages 240 92.7% 243 62.6% 483 74.7% Lessen workload 102 39.4% 119 30.7% 221 34.2% Have more supportive management 171 66.0% 242 62.4% 413 63.8% Rotate shifts to allow enough rest 115 44.4% 82 21.1% 197 30.4% Provide psychological counselling 104 40.2% 388 100.0% 492 76.0% † Data are presented as the mean and standard deviation ‡ Missing data (see Supplementary Table S1 online for details) CD-RISC-10: Connor-Davidson Resilience Scale-10; WRS: work-related stress Inferential analysis Bivariable analysis was performed to examine differences in CD-RISC-10 scores across several sociodemographic and work-related variables ( Table 3 ). Compared with female doctors, male doctors had significantly greater resilience scores (p < 0.001). Those in certain job categories, such as senior doctors and ambulance personnel, had significantly greater resilience than did junior doctors (p = 0.019). In addition, doctors who earned in the highest salary bracket demonstrated greater resilience than did those who earned less (p = 0.020). Doctors who were current smokers had greater resilience (30.7) than those who had never smoked (27.2) or were previous smokers (26.7) (p = 0.012). In addition, a history of alcohol use significantly increased resilience for ambulance personnel (30.5) compared to current users (27.6) and never users (27.1) (p = 0.002). Participants who self-reported having been diagnosed with a mental health condition had significantly lower resilience scores compared to those who did not, and this association was observed for doctors (p = 0.037) and ambulance personnel (p = 0.010). In addition, ambulance personnel currently receiving treatment for mental health conditions had significantly lower resilience scores (p = 0.029). Finally, participants who felt the need to drink alcohol to manage WRS had significantly lower resilience scores among doctors (p = 0.034) and ambulance personnel (p = 0.048). Unadjusted (see Supplementary Table S3 online) and adjusted logistic regression analyses were also performed. Table 4 provides a summary of the statistically significant results for the adjusted logistic regression analysis, and Supplementary Table S4 online shows the complete results for the analysis performed. Current smoking status significantly reduced the odds of doctors having low resilience (aOR: 0.21, 95% CI: 0.03–0.77, p = 0.042). Interestingly, previous alcohol use was also found to be protective against low resilience for ambulance personnel (aOR: 0.39, 95% CI: 0.18 - 0.78, p = 0.010). Being diagnosed with a mental health condition (aOR: 1.77, 95% CI: 1.15 - 2.70, p = 0.009) and being currently receiving treatment for a mental health condition (aOR: 1.70, 95% CI: 1.03 - 2.80, p = 0.037) significantly increased the odds of having low resilience for the overall sample. The three multivariable linear regression CD-RISC-10 models were found to be statistically significant, with p < 0.050 (F-statistic) ( Table 5 ). However, their predictors explained between 3.7% and 10.0% of the variation in the CD-RISC-10 score. Table 3: Comparison of CD-RISC-10 score across independent variables Doctors Ambulance personnel Overall Variable Group N Mean * P value * Mean * P value * Mean * P value * Gender Female 325 25.84 50 69 29.19 27.93 28.41 Home language English 293 27.22 0.748 b 27.67 0.478 b 27.41 0.152 b Afrikaans 232 27.50 28.47 28.24 IsiXhosa 115 25.90 27.54 27.10 Other 7 22.00 28.50 25.71 Relationship Status Married 291 27.80 0.143 b 27.65 0.374 b 27.71 0.743 b Never married 299 26.29 28.30 27.44 Divorced/Separated/Widowed 57 27.73 28.38 28.21 Professional health qualification Yes 581 27.06 N/A 27.92 0.775 a 27.54 0.276 a No 66 N/A 28.48 28.48 Job category Operational services/EMS 277 N/A 0.159 b 27.78 0.561 b 27.78 0.019 b Support staff/EMS 111 N/A 28.60 28.60 Junior doctors 85 26.40 N/A 26.40 Senior doctors 174 27.38 N/A 27.38 Over-time work Yes 517 26.98 0.257 a 27.97 0.942 a 27.49 0.186 a No 130 29.50 28.11 28.19 Monthly Salary (ZAR) R0 - R15 000 165 N/A 0.020 b 27.65 0.945 b 27.65 0.054 b R15 001 - R30 000 193 N/A 28.22 28.22 R30 001- R50 000 118 25.91 28.73 26.63 > R50 001 171 27.65 N/A 27.65 Smoking history Never used 448 26.65 0.012 b 28.07 0.806 b 27.39 0.079 b Previous smoker 58 27.17 27.17 27.17 Current smoker 141 30.74 28.16 28.58 Alcohol history Never used 164 26.67 0.618 b 27.11 0.002 b 26.96 0.020 b Previous alcohol user 117 26.59 30.47 29.18 Current drinker 366 27.30 27.56 27.44 Illicit drug use Never used 581 26.94 0.607 b 28.02 0.431 b 27.57 0.475 b Previous illicit drug user 48 28.00 28.34 28.25 Current illicit drug user 18 29.43 26.91 27.89 Ever diagnosed with a mental health condition Yes 108 25.66 0.037 a 25.47 0.010 a 25.58 <0.001 a No 539 27.47 28.33 28.02 Currently on treatment for mental health condition Yes 73 25.58 0.088 a 25.54 0.029 a 25.56 0.002 a No 574 27.37 28.21 27.90 Substance use to manage work WRS Feel need to smoke to manage WRS Yes 148 28.44 0.194 a 27.56 0.286 a 27.83 0.765 a No 499 26.77 28.18 27.57 Feel need to drink alcohol to manage WRS Yes 97 25.36 0.034 a 26.36 0.048 a 25.81 0.002 a No 550 27.45 28.23 27.94 Feel need to use illicit drugs to manage WRS Yes 29 26.00 0.488 a 28.44 0.875 a 27.34 0.570 a No 618 27.16 28.00 27.67 * Statistically significant results are indicated in bold; a Mann–Whitney test; b Kruskal–Wallis test EMS: Emergency medical services; N/A: not applicable; WRS: work-related stress; ZAR: South African Rand Table 4: Adjusted multivariable regression analysis of the predictors of CD-RISC-10 score (significant variables only) Doctors Ambulance personnel Overall Predictors aOR † * 95% CI P value * aOR † * 95% CI P value * aOR † * 95% CI P value * Smoking history (Never used) Previous smoker 1.68 0.66 4.25 0.273 1.06 0.48 2.27 0.873 1.26 0.69 2.24 0.442 Current Smoker 0.21 0.03 0.77 0.042 0.91 0.55 1.49 0.714 0.77 0.45 1.09 0.127 Alcohol history (Never used) Previous alcohol user 0.78 0.32 1.84 0.568 0.39 0.18 0.78 0.010 0.52 0.30 0.88 0.015 Current drinker 0.64 0.33 1.23 0.180 1.12 0.68 1.88 0.657 0.91 0.62 1.36 0.654 Ever diagnosed with a mental health condition (No) Yes 1.56 0.87 2.81 0.136 1.75 0.90 3.35 0.095 1.77 1.15 2.70 0.009 Currently on treatment for mental health condition (No) Yes 1.38 0.70 2.69 0.348 1.80 0.80 3.95 0.145 1.70 1.03 2.80 0.037 *Statistically significant results are indicated in bold; † Data adjusted for age and genders Note: Content in brackets is the reference or base group Table 5: Multivariable linear regression models for predictors of the CD-RISC-10 score Doctors Ambulance personnel Overall Predictor Β * 95% CI P value * Β * 95% CI P value * Β * 95% CI P value * Gender (Male) Female -1.77 -3.39 -0.15 0.032 -0.23 -1.80 1.33 0.769 -0.88 -2.01 0.24 0.124 Age (20 - 29) 30 – 39 0.38 -1.87 2.64 0.737 -0.74 -2.87 1.38 0.490 -0.11 -1.67 1.45 0.889 40 – 49 -0.26 -2.98 2.45 0.850 -2.12 -4.47 0.22 0.076 -1.29 -3.07 0.48 0.152 > 50 1.18 -2.87 5.23 0.567 -0.55 -3.75 2.66 0.737 0.51 -1.94 2.96 0.682 Home language (English) Afrikaans 1.09 -0.75 2.92 0.244 0.34 -1.29 1.96 0.685 0.34 -0.86 1.55 0.573 IsiXhosa -1.37 -3.69 0.95 0.247 -0.24 -2.29 1.81 0.819 -0.40 -1.90 1.11 0.606 Other -5.63 -12.38 1.13 0.102 0.81 -6.05 7.66 0.817 -1.33 -6.17 3.52 0.591 Job category (Operational services/EMS) Support staff/EMS 0.47 -1.17 2.12 0.572 0.71 -0.80 2.23 0.357 Junior doctors † -2.18 -5.23 0.87 0.161 Senior doctors -4.45 -8.54 -0.36 0.033 -4.99 -9.59 -0.39 0.034 Years employed in current role -0.02 -0.22 0.18 0.851 -0.11 -0.24 0.02 0.093 -0.08 -0.19 0.02 0.124 Over-time work (No) Yes -5.11 -9.42 0.80 0.020 -0.10 -1.46 1.65 0.901 -0.04 -1.42 1.35 0.958 Monthly Salary (ZAR) (R0 - R15 000) R15 001 - R30 000 0.79 -0.83 2.41 0.336 0.35 -1.11 1.82 0.636 R30 001 - R50 000 † 1.27 -1.65 4.18 0.393 0.68 -1.97 3.34 0.614 > R50 001 5.11 1.46 8.77 0.006 5.24 0.45 10.03 0.032 Smoking history (Never used) Previous smoker -0.21 -2.93 2.52 0.882 -0.81 -3.36 1.75 0.536 -0.34 -2.22 1.54 0.721 Current smoker 3.52 0.89 6.16 0.009 -0.06 -1.82 1.70 0.947 0.53 -0.88 1.94 0.460 Alcohol history (Never used) Previous alcohol user 0.45 -2.03 2.93 0.719 3.22 1.10 5.34 0.003 2.32 0.70 3.93 0.005 Current drinker 0.89 -1.08 2.85 0.375 0.15 -1.73 2.03 0.876 0.45 -0.92 1.83 0.516 Illicit drug use (Never used) Previous illicit drug user -0.31 -3.70 3.07 0.855 0.49 -2.04 3.02 0.703 0.19 -1.83 2.20 0.855 Current illicit drug user 2.33 -2.26 6.93 0.318 -0.55 -4.95 3.86 0.808 0.86 -2.33 4.05 0.597 Substance use to manage WRS Feel need to drink alcohol to manage WRS (No) Yes -1.87 -3.81 0.06 0.058 -0.43 -2.82 1.97 0.728 -1.22 -2.76 0.32 0.120 Mental health Ever diagnosed with a mental health condition (No) Yes -0.99 -3.73 1.75 0.477 -2.57 -5.31 0.17 0.066 -1.87 -3.81 0.07 0.059 Currently on treatment for mental health condition (No) Yes -0.45 -3.53 2.63 0.773 -1.41 -4.66 1.85 0.396 -0.94 -3.15 1.27 0.405 F-statistic 2.413 1.690 2.227 P Value <0.001 0.030 <0.001 Adjusted R-squared 0.100 0.037 0.044 * Statistically significant results are indicated in bold; † Reference or base group for doctor EMS: Emergency medical services; WRS: Work-related stress, ZAR/R: South African Rand Note: Content in brackets is the reference or base group It should also be noted that the statistically significant regression coefficients reported in Table 5 are consistent with the average CD-RISC-10 scores from the bivariable analysis in Table 3 , except for job category ( Supplementary Table S5 online). Job category was statistically significant, with senior doctors negatively impacting the resilience scores of doctors after adjusting for other predictors (β: -4.45, 95% CI: -8.54 - -0.36, p = 0.033). Conversely, being in the highest salary bracket was significantly and positively associated with resilience scores (β: 5.11, 95% CI: 1.46 - 8.77, p = 0.006). For doctors, female gender and overtime work were statistically significant predictors of the CD-RISC-10 score, with a negative impact on resilience (β: -1.77, 95% CI: -3.39 - -0.15, p = 0.032 and β: -5.11, 95% CI: -9.42 - -0.80, p = 0.020, respectively), while current smoking status had a positive impact on resilience (β: 3.52, 95% CI: 0.89 - 6.16, p = 0.009). In addition, for ambulance personnel, only previous alcohol use was a statistically significant predictor of the CD-RISC-10 score, with a positive impact on resilience (β: 3.22, 95% CI: 1.10 - 5.34, p = 0.003). DISCUSSION This study aimed to estimate the prevalence and determinants of psychological resilience among a group of healthcare workers in South Africa comprising doctors and ambulance personnel. A summary of the factors associated with psychological resilience in participants who formed part of this study is provided in Fig. 1 . The study found the prevalence of psychological resilience among healthcare workers was relatively low, at 27.6 (± 6.6). The average score of the ambulance personnel (28.0 ± 6.9) was greater than that of the doctors (27.1 ± 6.0). Kang et al. (2018) reported an overall average score of 29.0 (± 6.8) for a group of ambulance personnel in China, which is higher than the overall average score obtained in this study. [ 23 ] Mantas-Jiménez et al. (2022), in their study comparing doctors and ambulance technicians in Spain, reported an overall average score of 30.6 (± 5.0), which was higher than that obtained in the present study. [ 24 ] Cook et al. (2021), in their longitudinal study on healthcare workers in South Africa, reported average scores of 26.7 (± 8.8) and 30 (± 6.7) for the two time points considered. [ 6 ] The average resilience score for the second time point of the longitudinal study was greater than that of the present study. Xuan et al. (2021) and Elkudssiah Ismail et al. (2022) furthermore reported overall average scores of 28.6 (± 6.3) and 30.0 (± 6.3), respectively, in their studies on Malaysian healthcare workers, both of which were higher than those in the present study. [ 20 , 25 ] Zhou et al. (2022), however, reported an overall average score of 23.2 (± 9.3) in their study of Chinese resident doctors, which is lower than that obtained in the present study. [ 26 ] This variability in the level of resilience observed may be due to differences in the study context (population sampled, time when the study was conducted), resources available in the healthcare system and differences in cultural values and norms, which may result in different coping styles among healthcare workers. [ 1 ] Overall, the results from this study were consistent with results from comparative studies on the resilience of healthcare workers when considering the standard deviations reported. The study revealed a statistically significant association between psychological resilience and gender, with females having significantly lower resilience than males. These results are consistent with previous studies on psychological resilience showing that female gender is associated with lower resilience scores. [ 10 , 20 , 27 , 28 ] This could be attributed to females assuming multiple roles at home and in the workplace, experiencing more emotional exhaustion and being more sensitive and susceptible to stress. [ 10 , 27 ] The difference could also be due to social desirability bias, with males answering in a way that portrays an image of being able to manage pressure better. [ 20 ] We observed that doctors who were current smokers had greater average resilience scores than did those who had previously smoked and those who had never smoked before. These results contrast with the results of previous studies in which current smokers were found to have significantly lower psychological resilience. [ 29 ] It is probable that current smoking may be reflective of a coping mechanism and could mask low levels of resilience among current smokers. Substance use and medication use have been used as maladaptive coping mechanisms to address mental health issues and work-related stress. [ 12 , 30 ] Similarly, in ambulance personnel, a significant relationship was found between psychological resilience and alcohol history, with previous alcohol use being protective against low resilience. These results are in line with guidelines for rehabilitation programs (alcohol and smoking), which consider improving resilience to be necessary for preventing substance use onset, abuse problems and relapse. [ 29 , 31 , 32 ] In addition, Yamashita et al. (2021) reported that a lower relapse risk was associated with greater resilience (p < 0.010). [ 33 ] This study found no significant associations between psychological resilience and other sociodemographic or lifestyle factors, such as age, home language and relationship status. This is consistent with the results of Rossouw et al. (2013), Wang et al. (2021) and Yue et al. (2022). [ 16 , 34 , 35 ] Herman et al. (2011) noted that these inconsistencies observed between psychological resilience and predictive factors may be due to differences in study methodologies and the definition of resilience used by the investigators. [ 2 ] The results were somewhat contradictory for job category. The initial bivariable analysis and logistic regression analysis suggested that job category was protective, with senior doctors having greater average resilience than junior doctors. However, the multivariable linear regression revealed job category to be a risk factor. This can also be observed when looking at the average resilience score of the healthcare workers by job category, salary, and overtime work (see Supplementary Table S5 online). This suggests that once salary and overtime work are adjusted for, junior doctors have greater resilience than senior doctors in this sample. This finding contradicts prior research which suggests that greater experience and professional training result in greater resilience. [ 19 , 36 ] In addition, years in the current role and professional qualifications were not found to be significant predictors of the CD-RISC-10 score in the present study. Wang et al. (2020) argued that senior healthcare workers have better experience and professional skills to address complex situations that arise in the workplace. [ 19 ] Wang et al. (2020) and Hamdan et al. (2023) reported that years in practice was positively associated with psychological resilience (p < 0.050 and p = 0.013, respectively). [ 19 , 21 ] Afshari et al. (2021) noted that an increase in healthcare workers’ education and work experience may be linked to the progression of skills, which results in the development of positive coping strategies, leading to greater resilience.[ 36 ] Notably, the average resilience of paramedic personnel was significantly greater than that of doctors in this study, similar to the findings of Mantas-Jiménez et al. (2022), who compared doctors and ambulance technicians in Spain (p = 0.039). [ 24 ] Overtime work was found to be a significant negative predictor of resilience among doctors in the present study. These results are in line with the interventions recommended by the healthcare workers in the present study to reduce WRS, with most of the participants indicating that addressing staff shortages was important for reducing WRS. Zhao et al. (2023), in their study on nurses in China, also found that working longer hours a day resulted in significantly lower psychological resilience (p = 0.008). [ 37 ] However, Rossouw et al. (2013) did not find any significant relationship between resilience and overtime hours in their study of healthcare workers in Cape Town. [ 16 ] Alameddine et al. (2021) observed that high workload and occupational stressors were likely to lead to low job satisfaction, poor work performance and high job turnover for healthcare workers, resulting in a vicious cycle and ultimately leading to burnout and low resilience. [ 28 ] The present study revealed a significant negative association between psychological resilience and self-reported mental health conditions and treatment for mental health conditions. Keragholi et al. (2022) and Liang et al. (2023) noted that psychological resilience has been identified to have a protective role against mental health issues. [ 38 , 39 ] Ramadianto et al. (2022), in their study of Indonesian medical students, reported that higher resilience was moderately correlated with lower scores for depressive and anxious symptoms (p < 0.001). [ 40 ] In addition, Keragholi et al. (2022), in their study of Iranian ambulance personnel, also reported that mental health status was negatively associated with resilience (p = 0.001). [ 39 ] Rossouw et al. (2013) reported that healthcare workers using medication or other forms of treatment for their anxiety or depression symptoms had significantly lower resilience than did those not using medication (p = 0.030). [ 16 ] Furthermore, stigma and denial related to mental health might impact the ability of healthcare workers to seek help, which could also lead to underreporting in research studies. [ 16 ] The resilience score of participants who reported needing to use alcohol to manage WRS was significantly lower than that of participants who reported not needing to use alcohol. In addition, the preference of most participants (76.7%) was for the provision of psychological counselling as an intervention that could be provided by institutions to assist with reducing WRS. This is a positive coping strategy compared to substance use, which is recognised as a maladaptive coping mechanism used by those with mental health issues or WRS. [ 30 ] In addition, Alim et al. (2012) reported that resilience interacts with stress to impact the development of addiction and relapse. [ 31 ] Other studies have also identified the protective role of psychological resilience on WRS. [ 41 ] STRENGTHS AND LIMITATIONS The primary strength of this study was that it included a large population of healthcare workers in South Africa. In addition, both previous surveys used to collect data for this study had good response rates. The study also used a validated and standardised questionnaire to measure the outcome variable, which provides an opportunity to compare the results of this study with those of previous studies. This study had several limitations. First, as a secondary data analysis was undertaken, the information available was limited to what had been provided and collected from the previous two studies. Second, causation cannot be inferred via a cross-sectional study design, and the risk factors identified need to be interpreted accordingly. Third, as self-reported data were used, the risk of social desirability bias was high, as respondents may have been influenced by stigma associated with substance use and mental health. In addition, recall bias may have occurred during the initial data collection phase where the participants’ memory was relied upon. Most questions used in this study, however, did not require recall over many months. Fourth, selection bias was largely unavoidable, as participation in the initial surveys was voluntary, and those who had been experiencing problems such as PTSD or burnout may have been more likely to complete the survey. In addition, confidentiality concerns may also affect participation and contribute to bias. The initial investigators had put in place measures to mitigate this bias, including introductory letters to explain the data handling procedure and the preservation of confidentiality. Last, the healthy worker effect may result in the overestimation of healthcare workers' resilience status since those with low levels of resilience may have already left active work. CONCLUSION AND RECOMMENDATIONS Resilience was relatively low in this group of South African healthcare workers compared to similar studies globally, highlighting the need to build resilience among healthcare workers in South Africa. This study demonstrated that resources need to be directed towards building resilience among female healthcare workers and those working long hours and earning lower income. In addition, support such as psychological counselling should be offered to healthcare workers who have been diagnosed with mental health conditions. Further research is needed to better characterise the sociodemographic and work-related factors impacting the psychological resilience of healthcare workers in South Africa to improve the support of healthcare workers. This will assist in building psychological resilience in the healthcare workforce in South Africa and may protect against burnout while supporting the delivery of healthcare services. Abbreviations aOR: Adjusted Odds Ratio CART: Classification and regression tree CD-RISC: Connor-Davidson Resilience Scale CD-RISC-10: Connor-Davidson Resilience Scale 10 CD-RISC-25: Connor-Davidson Resilience Scale 25 CI/ 95%CI: 95% Confidence Interval COVID-19: Coronavirus disease EMS: Emergency medical services HCWs: Healthcare Workers HICs: High-income countries HIV/AIDS: Human Immunodeficiency Virus/Acquired Immune Deficiency Syndrome HREC: Human Research Ethics Committee IQR: Interquartile Range LMICs: Low- and middle-income countries m: Mean MICE: Multivariate Imputation by Chained Equation N: Number N/A: Not applicable NHI: National Health Insurance OR: Odds ratio p/ p value: Probability Value PTSD: Posttraumatic stress disorder SD: Standard deviation WRS: Work-Related Stress ZAR/R: South African Rand β: Standard Regression Coefficient Declarations COMPETING INTERESTS The authors declare that there are no conflicting interests. AUTHORS’ CONTRIBUTIONS T.M. conceptualised the study and was responsible for the data analysis, initial write-up and subsequent manuscript revisions. I.N. provided part of the dataset and assisted with study conceptualisation, data analysis and write-up of this study. S.A. assisted with study conceptualisation, data analysis and write-up of this study. S.K. provided part of the dataset and made editorial manuscript revisions. ACKNOWLEDGEMENTS Not applicable FUNDING INFORMATION This research was partly funded by an award granted by the University of Cape Town Faculty Research Committee. DATA AVAILABILITY STATEMENT The data are available upon reasonable request from the corresponding author. DISCLAIMER The views and opinions expressed in this manuscript are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors. References Cheng CKT, Chua JH, Cheng LJ, Ang WHD, Lau Y. 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Burnout Among Medical Staff 1 Year After the Beginning of the Major Public Health Emergency in Wuhan, China. Frontiers in Psychology. 2022;13. Available from: https://doi.org/10.3389/fpsyg.2022.893389. Additional Declarations No competing interests reported. Supplementary Files SUPPLEMENTARYINFORMATION.docx Cite Share Download PDF Status: Published Journal Publication published 24 Aug, 2024 Read the published version in BMC Health Services Research → Version 1 posted Editorial decision: Revision requested 17 May, 2024 Editor assigned by journal 16 May, 2024 Submission checks completed at journal 15 May, 2024 First submitted to journal 13 May, 2024 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-4413230","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":303566734,"identity":"bff05ea3-e975-4283-b09f-4e6f16d9f22c","order_by":0,"name":"Thandokazi Mcizana","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYJACZgYGCR429gbidTA2MzDYyPHxHABxDIjWkmYsJ5FApBbd9uPPHxfUHE5sk3ydJs1T84eBv/0A84cfeLSYnUlIbJ5xDKhFOnebNM8xAwaJMwkMhj34tNxgONjMwwbVwtsAdNgNBoYEHrxaGBubef6BHHYWokUeqOXgH7xamBmbedvSjNkkeCFaDG4AAwSvLWfSGGfz9tnIsfHkbracc8yYx/BMYjOzDD4tx48/+MzzTYJHvv3sxhtvauTk5I4fPvzxDR4tyIBFAkgAncTYQKQGYML5QLTSUTAKRsEoGFEAAP7VSP75ASksAAAAAElFTkSuQmCC","orcid":"","institution":"University of Cape Town","correspondingAuthor":true,"prefix":"","firstName":"Thandokazi","middleName":"","lastName":"Mcizana","suffix":""},{"id":303566736,"identity":"a6a1d004-c2b7-45f5-b790-aaf583034390","order_by":1,"name":"Shahieda Adams","email":"","orcid":"","institution":"University of Cape Town","correspondingAuthor":false,"prefix":"","firstName":"Shahieda","middleName":"","lastName":"Adams","suffix":""},{"id":303566737,"identity":"227eddc3-76a4-44da-8352-3af0ebd5f107","order_by":2,"name":"Saajida Khan","email":"","orcid":"","institution":"University of Cape Town","correspondingAuthor":false,"prefix":"","firstName":"Saajida","middleName":"","lastName":"Khan","suffix":""},{"id":303566738,"identity":"f90e40b6-0677-4dc7-ab42-86e78bba66ea","order_by":3,"name":"Itumeleng Ntatamala","email":"","orcid":"","institution":"University of Cape Town","correspondingAuthor":false,"prefix":"","firstName":"Itumeleng","middleName":"","lastName":"Ntatamala","suffix":""}],"badges":[],"createdAt":"2024-05-13 12:29:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4413230/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4413230/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12913-024-11430-0","type":"published","date":"2024-08-24T15:56:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57435676,"identity":"b8ae7b6e-c298-49a3-980f-b9822b2104f5","added_by":"auto","created_at":"2024-05-30 16:02:13","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":71104,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSummary of identified protective and risk factors associated with psychological resilience of healthcare workers\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4413230/v1/baa4cf288ba94adcbd035d7c.jpg"},{"id":63300281,"identity":"52c59b8a-a9bf-4813-adc3-d765ffcd6b24","added_by":"auto","created_at":"2024-08-26 16:13:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2075340,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4413230/v1/200b2960-8107-4bae-8974-c1df626e763a.pdf"},{"id":57435677,"identity":"073ed14a-e3ce-483c-b81b-9df3746f0cd9","added_by":"auto","created_at":"2024-05-30 16:02:13","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":240712,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLEMENTARYINFORMATION.docx","url":"https://assets-eu.researchsquare.com/files/rs-4413230/v1/e15d5e1d4219ac8eb2cfc920.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Sociodemographic and work-related factors associated with psychological resilience in South African healthcare workers: a cross-sectional study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003ePsychological resilience is an important personal characteristic that enables healthcare workers to navigate the challenges encountered in their occupation. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] Herrman et al. (2011) explored the evolution of the term in their narrative review and concluded that fundamentally, resilience is the \u0026lsquo;inherent ability\u0026rsquo; for one to adapt positively following adversity or stressful events. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] As such, psychological resilience describes an individual's coping mechanism, optimism, self-efficacy, high levels of hope and thriving mental health amid adversity and challenging circumstances. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe healthcare systems of most low- and middle-income countries (LMICs) are under severe strain due to high patient load, significant burden of communicable and noncommunicable diseases, lack of human and financial resources, the brain drain phenomenon, corruption and poor administration. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] South Africa faces similar challenges, with a quadruple burden of disease including HIV/AIDS and tuberculosis, high maternal and child mortality, high levels of violence and injuries and noncommunicable diseases. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] Poor health outcomes and a disproportionate distribution of healthcare resources in the country may be ascribed to the legacy of an undemocratic political apartheid regime (1948\u0026ndash;1993) compounded by ongoing challenges in managing the health system in a post-apartheid South Africa. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] South Africa's government is currently in the process of implementing a National Health Insurance (NHI) scheme to address the tremendous challenges that plague the health system. However, the country\u0026rsquo;s preparedness remains uncertain, especially given the ongoing shortage of healthcare worker posts and rising unemployment in the health sector. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] These challenges place immense pressure on employed healthcare workers, making psychological resilience an important inherent ability that can aid in supporting and protecting healthcare workers against adverse mental health outcomes and contributing to improved service delivery.\u003c/p\u003e \u003cp\u003eResearch on the role of psychological resilience as a protective factor in frontline healthcare workers has increased recently during the coronavirus disease (COVID-19) pandemic. Much of the research in this area has been conducted in high-income countries (HICs) and China, and little is known about the factors that predict psychological resilience in workers in LMICs, including South Africa, an upper middle-income country. Robertson et al. (2016), in their systematic review on resilience among primary healthcare workers, found that most research on the topic primarily frames resilience as an explanatory variable in relation to burnout. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] This study therefore aimed to determine the prevalence and factors associated with the psychological resilience of healthcare workers practising in the South African healthcare system.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThis is an analytical cross-sectional study using secondary data obtained from two cross-sectional studies of healthcare workers in South Africa. The first study focused on ambulance personnel in the Western Cape province and the second study focused on medical doctors in the Eastern Cape province. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] The present study included data on all healthcare workers who had completed the Connor-Davidson Resilience Scale-10 (CD-RISC-10) questionnaire and relevant sociodemographic and occupational questions. This study was approved by the University of Cape Town\u0026rsquo;s Human Research Ethics Committee (HREC 712/2023).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMeasurements\u003c/h2\u003e \u003cp\u003eThis study used secondary data generated from self-administered questionnaires that consisted of sociodemographic factors, work-related factors, and the CD-RISC-10 questionnaire.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic and work-related factors\u003c/h2\u003e \u003cp\u003eThe data obtained from the questionnaires included information on age, gender, language, marital status, job category, professional qualifications, overtime work, salary, and length of service. In addition, data on mental health and medical history, including self-reported mental health conditions and substance use (smoking, alcohol use, illicit and prescription drugs), year of debut, and the use of substances to manage work-related stress, were obtained.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e10-item Connor-Davidson Resilience Scale (CD-RISC-10)\u003c/h2\u003e \u003cp\u003ePsychological resilience (outcome variable) was measured using the 10-item CD-RISC questionnaire. The CD-RISC-10 is a self-administered 10-item questionnaire, which is a shorter version of the CD-RISC-25. Participants identified their adaptive behaviours in stressful situations and scored them on a 5-point Likert scale (0\u0026thinsp;=\u0026thinsp;not at all true, 4\u0026thinsp;=\u0026thinsp;true nearly all the time).\u003csup\u003e13\u003c/sup\u003e The resulting scores ranged between 0 and 40. This scale has previously been reported to be a reliable and efficient measure of psychological resilience for adults. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] In addition, it has previously been validated for use in South Africa by Pretorius et al. (2022) as a measure of psychological resilience and has been used in several studies of South African healthcare workers. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] Written permission to use the scale was previously obtained. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003e After ethical approval, the secondary data were received and cleaned in password-protected Microsoft Excel. R statistical software (version 4.3.1) was used for analysing the data and performing the statistical tests. Descriptive statistics for continuous variables in this study are presented as the means (standard deviations) and medians (interquartile ranges) where appropriate. In addition, descriptive statistics for categorical variables are presented as proportions.\u003c/p\u003e \u003cp\u003eMann‒Whitney and Kruskal‒Wallis tests were used to determine significant differences in CD-RISC-10 scores. In addition, unadjusted logistic regression and adjusted logistic regression (adjusted for age and gender) were performed. Low resilience, as an outcome measure, was defined as a CD-RISC-10 score less than 25.5. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] Variables from the adjusted logistic regression analysis with a p value less than 0.250 were selected for the multivariable linear regression model to investigate factors associated with increasing resilience scores. Due to the size of the dataset, multinomial logistic regression was not performed because it would not produce useful results. The beta statistics, odds ratios and 95% confidence intervals were calculated for both the univariable and multivariable analyses. A p value of less than 0.050 was considered the cut-off point for statistical significance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMissing data\u003c/h2\u003e \u003cp\u003eOnly the age factor had missing data of more than 1% of the total recorded values and thus necessitated imputation (see \u003cb\u003eSupplementary Table S1\u003c/b\u003e and \u003cb\u003eSupplementary Fig. S1\u003c/b\u003e online). Age is also important when performing this regression analysis, as age has previously been reported to be an important confounder of psychological resilience and needs to be adjusted for when performing regression analysis. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] Multiple imputation was chosen because it results in valid statistical inferences. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] To assess the sensitivity of the results with respect to the multiple imputation method chosen, multiple imputation using the three methods available in the Multivariate Imputation by Chained Equation (MICE) package in R were performed (see \u003cb\u003eSupplementary Table S2\u003c/b\u003e online). The imputed data from the Classification and regression tree (CART) method was chosen for use in the following regression analysis, given its minimal impact on the distribution of the age factor. \u003cb\u003eSupplementary Fig. S2\u003c/b\u003e shows the distribution of the age factor before and after CART imputation.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eFrom the original datasets received, only one record was removed because the participant indicated that they were gender nonconforming resulting in several skewed results. In total therefore, 647 questionnaires were included in the present analysis, of whom 259 were from doctors and 388 were from ambulance personnel.\u003c/p\u003e\n\u003ch3\u003eSociodemographic and work-related characteristics\u003c/h3\u003e\n\u003cp\u003eAmong the 259 doctors, the majority were female (57.9%), while most ambulance personnel were male (54.9%) (\u003cstrong\u003eTable 1\u003c/strong\u003e). Most of the doctors were English speaking (66.0%) and were in the 20\u0026ndash;29 years age group (42.5%), while most of the ambulance personnel were Afrikaans speaking (45.9%) and were in the 30\u0026ndash;39 years age group (37.1%). Most respondents who worked for the ambulance service in operational roles had direct contact with patients (42.8%). Doctors\u0026apos; years of service in the current role were lower, with a median of 2 (IQR: 4), while ambulance personnel had a median of 7 (IQR: 9). A greater percentage of doctors reported working overtime (96.9%) than ambulance personnel (68.6%).\u003c/p\u003e\n\u003ch3\u003eSubstance use, mental health, and work-related stress management\u003c/h3\u003e\n\u003cp\u003eThe prevalence of smoking was greater among ambulance personnel (30.4%) than among doctors (8.9%), while current alcohol usage was greater for doctors (64.1%) than for ambulance personnel (51.5%) (\u003cstrong\u003eTable 2\u003c/strong\u003e). Only 2.8% of the overall sample reported current use of illicit substances or drugs. A quarter (25.1%) of the doctors reported having been diagnosed with a mental health condition compared to 11.1% of the ambulance personnel. In addition, 17.4% of doctors reported being on treatment for a mental health condition, compared to 7.2% of ambulance personnel.\u003c/p\u003e\n\u003cp\u003eRegarding managing work-related stress (WRS), more than a quarter (26.5%) of the ambulance personnel self-reported the need to smoke to manage WRS, while 20.5% of doctors reported the need to use alcohol to manage WRS. Interestingly, 4.5% of the overall sample felt the need to use illicit drugs to manage WRS, which is higher than the current prevalence of illicit drug use. Most participants supported the provision of psychological counselling (76.0%) and addressing staff shortages (74.7%) to assist with reducing WRS.\u003c/p\u003e\n\u003ch3\u003eOverall CD-RISC-10 score and level of resilience\u003c/h3\u003e\n\u003cp\u003eThe overall average CD-RISC-10 score was 27.6 (\u0026plusmn;6.6) among the 647 healthcare workers in this study (\u003cstrong\u003eTable 2\u003c/strong\u003e). The average CD-RISC-10 score for the ambulance personnel was 28.0 (\u0026plusmn;6.9), which was significantly greater than the average score of 27.1 (\u0026plusmn;6.0) for the doctors (p = 0.006). The total score for the CD-RISC-10 can be classified into a 4-level variable using quantiles: lowest (0\u0026ndash;24), low (25\u0026ndash;28), moderate (29\u0026ndash;32), and highest (33\u0026ndash;40).\u003csup\u003e13\u003c/sup\u003e More than half of the doctors (58.7%) were classified as having the lowest or lowest resilience. However, for ambulance personnel, the majority (54.2%) were classified as having moderate or high resilience.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Sociodemographic and work-related characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"673\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParticipant characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDoctors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmbulance personnel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20 \u0026ndash; 29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30 \u0026ndash; 39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40 \u0026ndash; 49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt; 50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHome language\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEnglish\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAfrikaans\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIsiXhosa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRelationship Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNever married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDivorced/Separated/Widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional health qualification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e83.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e89.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eJob category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOperational services/EMS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e71.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSupport staff/EMS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJunior doctors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSenior doctors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYears employed in current role\u0026nbsp;\u003c/strong\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMissing (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOver-time work\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e96.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e68.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e79.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonthly Salary (ZAR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eR0 - R15 000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eR15 001 - R30 000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eR30 001 - R50 000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt; R50 001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e Data are presented as the median (interquartile range)\u003c/p\u003e\n\u003cp\u003eEMS: Emergency medical services; ZAR/R: South African Rand\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Frequency and distribution of general and mental health-specific variables\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"687\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eParticipant characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDoctors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmbulance personnel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge started smoking (m, SD)\u0026nbsp;\u003c/strong\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge started illicit drugs (m, SD)\u0026nbsp;\u003c/strong\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNever used\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e82.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e60.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrevious smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCurrent smoker\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNever used\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrevious alcohol user\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCurrent drinker \u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e64.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e51.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e56.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIllicit drug use\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNever used\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e92.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e88.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e89.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrevious illicit drug user\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCurrent illicit drug user \u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubstance use to manage WRS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFeel need to smoke to manage WRS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFeel need to drink alcohol to manage WRS \u0026Dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFeel need to use illicit drugs to manage WRS \u0026Dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMental health\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEver diagnosed with a mental health condition \u0026Dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCurrently on treatment for mental health condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eResilience, CD-RISC-10 score (m, SD)\u0026nbsp;\u003c/strong\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLowest (0 - 24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLow (25 - 28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModerate (29 - 32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHighest (33 - 40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhich intervention would assist most with reducing WRS?\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAddress staff shortages\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e92.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e62.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e74.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLessen workload\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHave more supportive management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e62.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e63.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRotate shifts to allow enough rest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e44.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eProvide psychological counselling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e76.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e Data are presented as the mean and standard deviation\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026Dagger;\u003c/sup\u003e Missing data (see Supplementary\u0026nbsp;Table S1 online for details)\u003c/p\u003e\n\u003cp\u003eCD-RISC-10: Connor-Davidson Resilience Scale-10; WRS: work-related stress\u003c/p\u003e\n\u003ch3\u003eInferential analysis\u003c/h3\u003e\n\u003cp\u003eBivariable analysis was performed\u0026nbsp;to examine differences in CD-RISC-10 scores across several sociodemographic and work-related variables (\u003cstrong\u003eTable 3\u003c/strong\u003e). Compared with female doctors, male doctors had significantly greater resilience scores (p \u0026lt; 0.001). Those in certain job categories, such as senior doctors and ambulance personnel, had significantly greater resilience than did junior doctors (p = 0.019). In addition, doctors who earned in the highest salary bracket demonstrated greater resilience than did those who earned less (p = 0.020). Doctors who were current smokers had greater resilience (30.7) than those who had never smoked (27.2) or were previous smokers (26.7) (p = 0.012). In addition, a history of alcohol use significantly increased resilience for ambulance personnel (30.5) compared to current users (27.6) and never users (27.1) (p = 0.002). Participants who self-reported having been diagnosed with a mental health condition had significantly lower resilience scores compared to those who did not, and this association was observed for doctors (p = 0.037) and ambulance personnel (p = 0.010). In addition, ambulance personnel currently receiving treatment for mental health conditions had significantly lower resilience scores (p = 0.029). Finally, participants who felt the need to drink alcohol to manage WRS had significantly lower resilience scores among doctors (p = 0.034) and ambulance personnel (p = 0.048).\u003c/p\u003e\n\u003cp\u003eUnadjusted (see \u003cstrong\u003eSupplementary\u003c/strong\u003e \u003cstrong\u003eTable S3\u003c/strong\u003e online) and adjusted logistic regression analyses were also performed. \u003cstrong\u003eTable 4\u003c/strong\u003e provides a summary of the statistically significant results for the adjusted logistic regression analysis, and \u003cstrong\u003eSupplementary\u003c/strong\u003e \u003cstrong\u003eTable S4\u0026nbsp;\u003c/strong\u003eonline shows\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ethe complete results for the analysis performed. Current smoking status significantly reduced the odds of doctors having low resilience (aOR: 0.21, 95% CI: 0.03\u0026ndash;0.77, p = 0.042). Interestingly, previous alcohol use was also found to be protective against low resilience for ambulance personnel (aOR: 0.39, 95% CI: 0.18 - 0.78, p = 0.010). Being diagnosed with a mental health condition (aOR: 1.77, 95% CI: 1.15 - 2.70, p = 0.009) and being currently receiving treatment for a mental health condition (aOR: 1.70, 95% CI: 1.03 - 2.80, p = 0.037) significantly increased the odds of having low resilience for the overall sample.\u003c/p\u003e\n\u003cp\u003eThe three multivariable linear regression CD-RISC-10 models were found to be statistically significant, with p \u0026lt; 0.050 (F-statistic) (\u003cstrong\u003eTable 5\u003c/strong\u003e). However, their predictors explained between 3.7% and 10.0% of the variation in the CD-RISC-10 score.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Comparison of CD-RISC-10 score across independent variables\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1022\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.233104799216456%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.253672869735553%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.928501469147895%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.887365328109697%\" colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eDoctors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.789422135161606%\" colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmbulance personnel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.907933398628796%\" colspan=\"5\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e*\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e*\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e*\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e25.84\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e0.595\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.035\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.73\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e27.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003e20 - 29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e26.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e0.337\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e29.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e0.150\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e0.309\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003e30 - 39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e28.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003e40 - 49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e26.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e26.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003e\u0026gt; 50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e29.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e27.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e28.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\n \u003cp\u003eHome language\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eEnglish\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e0.748\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e27.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e0.478\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e0.152\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eAfrikaans\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e28.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eIsiXhosa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e25.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e27.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e22.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e25.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\n \u003cp\u003eRelationship Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e0.143\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e27.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e0.374\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e0.743\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eNever married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e26.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eDivorced/Separated/Widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e28.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\n \u003cp\u003eProfessional health qualification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e27.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e0.775\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e0.276\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e28.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\n \u003cp\u003eJob category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eOperational services/EMS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e0.159\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e27.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e0.561\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.78\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.019\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eSupport staff/EMS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eJunior doctors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e26.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e26.40\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eSenior doctors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\n \u003cp\u003eOver-time work\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e26.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e0.257\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e27.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e0.942\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e0.186\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e29.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e28.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\n \u003cp\u003eMonthly Salary (ZAR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eR0 - R15 000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN/A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.020\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e27.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e0.945\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e0.054\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eR15 001 - R30 000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN/A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e28.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eR30 001- R50 000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e25.91\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e26.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003e\u0026gt; R50 001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.65\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003eN/A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\n \u003cp\u003eSmoking history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eNever used\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e26.65\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.012\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e0.806\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e0.079\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003ePrevious smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e27.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eCurrent smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e30.74\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e28.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\n \u003cp\u003eAlcohol history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eNever used\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e26.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e0.618\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e26.96\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.020\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003ePrevious alcohol user\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e26.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e30.47\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e29.18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eCurrent drinker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.56\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\n \u003cp\u003eIllicit drug use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eNever used\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e26.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e0.607\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e0.431\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e0.475\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003ePrevious illicit drug user\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e28.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e28.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eCurrent illicit drug user\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e29.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e26.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\n \u003cp\u003eEver diagnosed with a mental health condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e25.66\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.037\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e25.47\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.010\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e25.58\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.47\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.33\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\n \u003cp\u003eCurrently on treatment for mental health condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e25.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e0.088\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e25.54\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.029\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e25.56\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e574\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.87952987267385%\" colspan=\"16\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubstance use to manage work WRS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\" rowspan=\"2\"\u003e\n \u003cp\u003eFeel need to smoke to manage WRS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e28.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e0.194\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e27.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e0.286\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e0.765\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.364438839848678%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.64564943253468%\"\u003e\n \u003cp\u003e499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.32282471626734%\" colspan=\"2\"\u003e\n \u003cp\u003e26.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.718789407313997%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.19672131147541%\" colspan=\"2\"\u003e\n \u003cp\u003e28.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.844892812105927%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.32282471626734%\" colspan=\"2\"\u003e\n \u003cp\u003e27.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.583858764186633%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\" rowspan=\"2\"\u003e\n \u003cp\u003eFeel need to drink alcohol to manage WRS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e25.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.034\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e26.36\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.048\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e25.81\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.364438839848678%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.64564943253468%\"\u003e\n \u003cp\u003e550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.32282471626734%\" colspan=\"2\"\u003e\n \u003cp\u003e27.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.718789407313997%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.19672131147541%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.844892812105927%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.32282471626734%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.94\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.583858764186633%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.254901960784313%\" rowspan=\"2\"\u003e\n \u003cp\u003eFeel need to use illicit drugs to manage WRS\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.274509803921568%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.941176470588236%\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e26.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.333333333333334%\" colspan=\"2\"\u003e\n \u003cp\u003e0.488\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.372549019607843%\" colspan=\"2\"\u003e\n \u003cp\u003e28.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.431372549019608%\" colspan=\"2\"\u003e\n \u003cp\u003e0.875\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.470588235294118%\" colspan=\"2\"\u003e\n \u003cp\u003e27.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.450980392156863%\" colspan=\"2\"\u003e\n \u003cp\u003e0.570\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.364438839848678%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.64564943253468%\"\u003e\n \u003cp\u003e618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.32282471626734%\" colspan=\"2\"\u003e\n \u003cp\u003e27.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.718789407313997%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.19672131147541%\" colspan=\"2\"\u003e\n \u003cp\u003e28.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.844892812105927%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.32282471626734%\" colspan=\"2\"\u003e\n \u003cp\u003e27.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.583858764186633%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* Statistically significant results are indicated in bold; \u003csup\u003ea\u003c/sup\u003e Mann\u0026ndash;Whitney test; \u003csup\u003eb\u003c/sup\u003e Kruskal\u0026ndash;Wallis test\u003c/p\u003e\n\u003cp\u003eEMS: Emergency medical services; N/A: not applicable; WRS: work-related stress; ZAR: South African Rand\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Adjusted multivariable regression analysis of the predictors of CD-RISC-10 score (significant variables only)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"985\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.121951219512194%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.93089430894309%\" colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eDoctors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.760162601626018%\" colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmbulance personnel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.1869918699187%\" colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eaOR\u0026nbsp;\u003c/strong\u003e\u003csup\u003e\u0026dagger;\u003cstrong\u003e*\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u0026nbsp;\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eaOR\u0026nbsp;\u003c/strong\u003e\u003csup\u003e\u0026dagger;\u003cstrong\u003e*\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u0026nbsp;\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eaOR\u0026nbsp;\u003c/strong\u003e\u003csup\u003e\u0026dagger;\u003cstrong\u003e*\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u0026nbsp;\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking history (Never used)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePrevious smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.873\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.442\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCurrent Smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.77\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.042\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol history (Never used)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePrevious alcohol user\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.568\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.39\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.78\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.52\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.88\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCurrent drinker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.654\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eEver diagnosed with a mental health condition (No)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.77\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.70\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrently on treatment for mental health condition (No)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.348\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.70\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.80\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.037\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Statistically significant results are indicated in bold; \u003csup\u003e\u0026dagger;\u003c/sup\u003eData adjusted for age and genders\u003c/p\u003e\n\u003cp\u003eNote: Content in brackets is the reference or base group\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5: Multivariable linear regression models for predictors of the CD-RISC-10 score\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"954\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.746331236897273%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.769392033542978%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eDoctors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.746331236897273%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmbulance personnel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.737945492662472%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Beta;\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u0026nbsp;\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Beta;\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u0026nbsp;\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Beta;\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u0026nbsp;\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender (Male)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.77\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-3.39\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.032\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge 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width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-4.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003e\u0026gt; 50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n 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width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.573\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eIsiXhosa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e-3.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e0.247\u003c/p\u003e\n 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\u003cp\u003e3.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.591\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.34309623430963%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eJob category (Operational services/EMS)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eSupport staff/EMS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.357\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eJunior doctors\u0026nbsp;\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-5.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eSenior doctors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-4.45\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-8.54\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.36\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.033\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-4.99\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-9.59\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.39\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.034\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYears employed in current role\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e-0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e0.851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOver-time work (No)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-5.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e-9.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.901\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.97489539748954%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonthly Salary (ZAR) (R0 - R15 000)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eR15 001 - R30 000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e2.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.636\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eR30 001 - R50 000\u0026nbsp;\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e4.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.614\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003e\u0026gt; R50 001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.46\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.77\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.45\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.032\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.97489539748954%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking history (Never used)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003ePrevious smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e-2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e2.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-3.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.721\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eCurrent smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.52\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.89\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.460\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol history (Never used)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003ePrevious alcohol user\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e-2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e0.719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.34\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.32\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.70\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.93\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eCurrent drinker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e-1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e0.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-1.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.516\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIllicit drug use (Never used)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003ePrevious illicit drug user\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e-3.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e0.855\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e3.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.703\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.855\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eCurrent illicit drug user\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e-2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e6.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-4.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e3.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.597\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.97489539748954%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubstance use to manage WRS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.34309623430963%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eFeel need to drink alcohol to manage WRS (No)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e-3.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-2.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-2.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMental health\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.931937172774866%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eEver diagnosed with a mental health condition (No)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.528795811518325%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2356020942408374%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.026178010471204%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.397905759162303%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.06282722513089%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.282722513089006%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2356020942408374%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2356020942408374%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.06282722513089%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e-3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e0.477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-2.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-5.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-3.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.931937172774866%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrently on treatment for mental health condition (No)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.528795811518325%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2356020942408374%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.026178010471204%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.397905759162303%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.06282722513089%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.282722513089006%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2356020942408374%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2356020942408374%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.06282722513089%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\"\u003e\n \u003cp\u003e-3.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\n \u003cp\u003e2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\n \u003cp\u003e0.773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\n \u003cp\u003e-4.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\n \u003cp\u003e1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.396\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e-0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e-3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\n \u003cp\u003e0.405\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003e\u003cstrong\u003eF-statistic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.413\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.690\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.227\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.030\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.698744769874477%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted R-squared\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.368200836820083%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.648535564853557%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.518828451882845%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.02092050209205%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.393305439330544%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.2761506276150625%\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"5.2301255230125525%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.05439330543933%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e*\u003c/sup\u003eStatistically significant results are indicated in bold; \u003csup\u003e\u0026dagger;\u003c/sup\u003eReference or base group for doctor\u003c/p\u003e\n\u003cp\u003eEMS: Emergency medical services; WRS: Work-related stress, ZAR/R: South African Rand\u003c/p\u003e\n\u003cp\u003eNote: Content in brackets is the reference or base group\u003c/p\u003e\n\u003cp\u003eIt should also be noted that the statistically significant regression coefficients reported in \u003cstrong\u003eTable 5\u0026nbsp;\u003c/strong\u003eare consistent with the average CD-RISC-10 scores from the bivariable analysis in \u003cstrong\u003eTable 3\u003c/strong\u003e, except for\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ejob category\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(\u003cstrong\u003eSupplementary\u003c/strong\u003e \u003cstrong\u003eTable S5\u003c/strong\u003e online). Job category was statistically significant, with senior doctors negatively impacting the resilience scores of doctors after adjusting for other predictors (\u0026beta;: -4.45, 95% CI: -8.54 - -0.36, p = 0.033). Conversely, being in the highest salary bracket was significantly and positively associated with resilience scores (\u0026beta;: 5.11, 95% CI: 1.46 - 8.77, p = 0.006). For doctors, female gender and overtime work were statistically significant predictors of the CD-RISC-10 score, with a negative impact on resilience (\u0026beta;: -1.77, 95% CI: -3.39 - -0.15, p = 0.032 and \u0026beta;: -5.11, 95% CI: -9.42 - -0.80, p = 0.020, respectively), while current smoking status had a positive impact on resilience (\u0026beta;: 3.52, 95% CI: 0.89 - 6.16, p = 0.009). In addition, for ambulance personnel, only previous alcohol use was a statistically significant predictor of the CD-RISC-10 score, with a positive impact on resilience (\u0026beta;: 3.22, 95% CI: 1.10 - 5.34, p = 0.003).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study aimed to estimate the prevalence and determinants of psychological resilience among a group of healthcare workers in South Africa comprising doctors and ambulance personnel. A summary of the factors associated with psychological resilience in participants who formed part of this study is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe study found the prevalence of psychological resilience among healthcare workers was relatively low, at 27.6 (± 6.6). The average score of the ambulance personnel (28.0 ± 6.9) was greater than that of the doctors (27.1 ± 6.0). Kang et al. (2018) reported an overall average score of 29.0 (± 6.8) for a group of ambulance personnel in China, which is higher than the overall average score obtained in this study. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] Mantas-Jiménez et al. (2022), in their study comparing doctors and ambulance technicians in Spain, reported an overall average score of 30.6 (± 5.0), which was higher than that obtained in the present study. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] Cook et al. (2021), in their longitudinal study on healthcare workers in South Africa, reported average scores of 26.7 (± 8.8) and 30 (± 6.7) for the two time points considered. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] The average resilience score for the second time point of the longitudinal study was greater than that of the present study. Xuan et al. (2021) and Elkudssiah Ismail et al. (2022) furthermore reported overall average scores of 28.6 (± 6.3) and 30.0 (± 6.3), respectively, in their studies on Malaysian healthcare workers, both of which were higher than those in the present study. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] Zhou et al. (2022), however, reported an overall average score of 23.2 (± 9.3) in their study of Chinese resident doctors, which is lower than that obtained in the present study. [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] This variability in the level of resilience observed may be due to differences in the study context (population sampled, time when the study was conducted), resources available in the healthcare system and differences in cultural values and norms, which may result in different coping styles among healthcare workers. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] Overall, the results from this study were consistent with results from comparative studies on the resilience of healthcare workers when considering the standard deviations reported.\u003c/p\u003e \u003cp\u003eThe study revealed a statistically significant association between psychological resilience and gender, with females having significantly lower resilience than males. These results are consistent with previous studies on psychological resilience showing that female gender is associated with lower resilience scores. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] This could be attributed to females assuming multiple roles at home and in the workplace, experiencing more emotional exhaustion and being more sensitive and susceptible to stress. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] The difference could also be due to social desirability bias, with males answering in a way that portrays an image of being able to manage pressure better. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eWe observed that doctors who were current smokers had greater average resilience scores than did those who had previously smoked and those who had never smoked before. These results contrast with the results of previous studies in which current smokers were found to have significantly lower psychological resilience. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] It is probable that current smoking may be reflective of a coping mechanism and could mask low levels of resilience among current smokers. Substance use and medication use have been used as maladaptive coping mechanisms to address mental health issues and work-related stress. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eSimilarly, in ambulance personnel, a significant relationship was found between psychological resilience and alcohol history, with previous alcohol use being protective against low resilience. These results are in line with guidelines for rehabilitation programs (alcohol and smoking), which consider improving resilience to be necessary for preventing substance use onset, abuse problems and relapse. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] In addition, Yamashita et al. (2021) reported that a lower relapse risk was associated with greater resilience (p \u0026lt; 0.010). [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThis study found no significant associations between psychological resilience and other sociodemographic or lifestyle factors, such as age, home language and relationship status. This is consistent with the results of Rossouw et al. (2013), Wang et al. (2021) and Yue et al. (2022). [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] Herman et al. (2011) noted that these inconsistencies observed between psychological resilience and predictive factors may be due to differences in study methodologies and the definition of resilience used by the investigators. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe results were somewhat contradictory for job category. The initial bivariable analysis and logistic regression analysis suggested that job category was protective, with senior doctors having greater average resilience than junior doctors. However, the multivariable linear regression revealed job category to be a risk factor. This can also be observed when looking at the average resilience score of the healthcare workers by job category, salary, and overtime work (see \u003cb\u003eSupplementary Table S5\u003c/b\u003e online). This suggests that once salary and overtime work are adjusted for, junior doctors have greater resilience than senior doctors in this sample. This finding contradicts prior research which suggests that greater experience and professional training result in greater resilience. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eIn addition, years in the current role and professional qualifications were not found to be significant predictors of the CD-RISC-10 score in the present study. Wang et al. (2020) argued that senior healthcare workers have better experience and professional skills to address complex situations that arise in the workplace. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] Wang et al. (2020) and Hamdan et al. (2023) reported that years in practice was positively associated with psychological resilience (p \u0026lt; 0.050 and p = 0.013, respectively). [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] Afshari et al. (2021) noted that an increase in healthcare workers’ education and work experience may be linked to the progression of skills, which results in the development of positive coping strategies, leading to greater resilience.[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] Notably, the average resilience of paramedic personnel was significantly greater than that of doctors in this study, similar to the findings of Mantas-Jiménez et al. (2022), who compared doctors and ambulance technicians in Spain (p = 0.039). [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eOvertime work was found to be a significant negative predictor of resilience among doctors in the present study. These results are in line with the interventions recommended by the healthcare workers in the present study to reduce WRS, with most of the participants indicating that addressing staff shortages was important for reducing WRS. Zhao et al. (2023), in their study on nurses in China, also found that working longer hours a day resulted in significantly lower psychological resilience (p = 0.008). [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] However, Rossouw et al. (2013) did not find any significant relationship between resilience and overtime hours in their study of healthcare workers in Cape Town. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] Alameddine et al. (2021) observed that high workload and occupational stressors were likely to lead to low job satisfaction, poor work performance and high job turnover for healthcare workers, resulting in a vicious cycle and ultimately leading to burnout and low resilience. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe present study revealed a significant negative association between psychological resilience and self-reported mental health conditions and treatment for mental health conditions. Keragholi et al. (2022) and Liang et al. (2023) noted that psychological resilience has been identified to have a protective role against mental health issues. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] Ramadianto et al. (2022), in their study of Indonesian medical students, reported that higher resilience was moderately correlated with lower scores for depressive and anxious symptoms (p \u0026lt; 0.001). [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] In addition, Keragholi et al. (2022), in their study of Iranian ambulance personnel, also reported that mental health status was negatively associated with resilience (p = 0.001). [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] Rossouw et al. (2013) reported that healthcare workers using medication or other forms of treatment for their anxiety or depression symptoms had significantly lower resilience than did those not using medication (p = 0.030). [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] Furthermore, stigma and denial related to mental health might impact the ability of healthcare workers to seek help, which could also lead to underreporting in research studies. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe resilience score of participants who reported needing to use alcohol to manage WRS was significantly lower than that of participants who reported not needing to use alcohol. In addition, the preference of most participants (76.7%) was for the provision of psychological counselling as an intervention that could be provided by institutions to assist with reducing WRS. This is a positive coping strategy compared to substance use, which is recognised as a maladaptive coping mechanism used by those with mental health issues or WRS. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] In addition, Alim et al. (2012) reported that resilience interacts with stress to impact the development of addiction and relapse. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] Other studies have also identified the protective role of psychological resilience on WRS. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSTRENGTHS AND LIMITATIONS\u003c/h2\u003e \u003cp\u003eThe primary strength of this study was that it included a large population of healthcare workers in South Africa. In addition, both previous surveys used to collect data for this study had good response rates. The study also used a validated and standardised questionnaire to measure the outcome variable, which provides an opportunity to compare the results of this study with those of previous studies.\u003c/p\u003e \u003cp\u003eThis study had several limitations. First, as a secondary data analysis was undertaken, the information available was limited to what had been provided and collected from the previous two studies. Second, causation cannot be inferred via a cross-sectional study design, and the risk factors identified need to be interpreted accordingly. Third, as self-reported data were used, the risk of social desirability bias was high, as respondents may have been influenced by stigma associated with substance use and mental health. In addition, recall bias may have occurred during the initial data collection phase where the participants’ memory was relied upon. Most questions used in this study, however, did not require recall over many months. Fourth, selection bias was largely unavoidable, as participation in the initial surveys was voluntary, and those who had been experiencing problems such as PTSD or burnout may have been more likely to complete the survey. In addition, confidentiality concerns may also affect participation and contribute to bias. The initial investigators had put in place measures to mitigate this bias, including introductory letters to explain the data handling procedure and the preservation of confidentiality. Last, the healthy worker effect may result in the overestimation of healthcare workers' resilience status since those with low levels of resilience may have already left active work.\u003c/p\u003e \u003c/div\u003e "},{"header":"CONCLUSION AND RECOMMENDATIONS","content":"\u003cp\u003eResilience was relatively low in this group of South African healthcare workers compared to similar studies globally, highlighting the need to build resilience among healthcare workers in South Africa. This study demonstrated that resources need to be directed towards building resilience among female healthcare workers and those working long hours and earning lower income. In addition, support such as psychological counselling should be offered to healthcare workers who have been diagnosed with mental health conditions. Further research is needed to better characterise the sociodemographic and work-related factors impacting the psychological resilience of healthcare workers in South Africa to improve the support of healthcare workers. This will assist in building psychological resilience in the healthcare workforce in South Africa and may protect against burnout while supporting the delivery of healthcare services.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eaOR:\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Adjusted Odds Ratio\u003c/p\u003e\n\u003cp\u003eCART: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Classification and regression tree\u003c/p\u003e\n\u003cp\u003eCD-RISC: \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Connor-Davidson Resilience Scale\u003c/p\u003e\n\u003cp\u003eCD-RISC-10: \u0026nbsp;Connor-Davidson Resilience Scale 10\u003c/p\u003e\n\u003cp\u003eCD-RISC-25:\u0026nbsp;\u0026nbsp;Connor-Davidson Resilience Scale 25\u003c/p\u003e\n\u003cp\u003eCI/ 95%CI:\u0026nbsp; \u0026nbsp; \u0026nbsp;95% Confidence Interval\u003c/p\u003e\n\u003cp\u003eCOVID-19: \u0026nbsp; \u0026nbsp;\u0026nbsp;Coronavirus disease\u003c/p\u003e\n\u003cp\u003eEMS: \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Emergency medical services\u003c/p\u003e\n\u003cp\u003eHCWs: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Healthcare Workers\u003c/p\u003e\n\u003cp\u003eHICs: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;High-income countries\u003c/p\u003e\n\u003cp\u003eHIV/AIDS: \u0026nbsp; \u0026nbsp;\u0026nbsp;Human Immunodeficiency Virus/Acquired Immune Deficiency Syndrome HREC:\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Human Research Ethics Committee\u003c/p\u003e\n\u003cp\u003eIQR: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Interquartile Range\u003c/p\u003e\n\u003cp\u003eLMICs: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Low- and middle-income countries\u003c/p\u003e\n\u003cp\u003em:\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Mean\u003c/p\u003e\n\u003cp\u003eMICE:\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Multivariate Imputation by Chained Equation\u003c/p\u003e\n\u003cp\u003eN:\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Number\u003c/p\u003e\n\u003cp\u003eN/A: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Not applicable\u003c/p\u003e\n\u003cp\u003eNHI:\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;National Health Insurance\u003c/p\u003e\n\u003cp\u003eOR: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Odds ratio\u003c/p\u003e\n\u003cp\u003ep/ p value:\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Probability Value\u003c/p\u003e\n\u003cp\u003ePTSD:\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Posttraumatic stress disorder\u003c/p\u003e\n\u003cp\u003eSD: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Standard deviation\u003c/p\u003e\n\u003cp\u003eWRS: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Work-Related Stress\u003c/p\u003e\n\u003cp\u003eZAR/R: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;South African Rand\u003c/p\u003e\n\u003cp\u003e\u0026beta;: \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Standard Regression Coefficient\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCOMPETING INTERESTS\u003c/h2\u003e\n\u003cp\u003eThe authors declare that there are no conflicting interests.\u003c/p\u003e\n\u003ch2\u003eAUTHORS’ CONTRIBUTIONS\u003c/h2\u003e\n\u003cp\u003eT.M. conceptualised the study and was responsible for the data analysis, initial write-up and subsequent manuscript revisions. I.N. provided part of the dataset and assisted with study conceptualisation, data analysis and write-up of this study. S.A. assisted with study conceptualisation, data analysis and write-up of this study. S.K. provided part of the dataset and made editorial manuscript revisions.\u003c/p\u003e\n\u003ch2\u003eACKNOWLEDGEMENTS\u003c/h2\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch2\u003eFUNDING INFORMATION\u003c/h2\u003e\n\u003cp\u003eThis research was partly funded by an award granted by the \u0026nbsp;University of Cape Town Faculty Research Committee.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eDATA AVAILABILITY STATEMENT\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe data are available upon reasonable request from the corresponding author.\u003c/p\u003e\n\u003ch2\u003eDISCLAIMER\u003c/h2\u003e\n\u003cp\u003eThe views and opinions expressed in this manuscript are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCheng CKT, Chua JH, Cheng LJ, Ang WHD, Lau Y. 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Mental Health and Resilience in Emergency Medical Services Practitioners During the COVID-19 Pandemic. Iranian Journal of Psychiatry and Behavioral Sciences. 2022; 16(2).\u003c/li\u003e\n\u003cli\u003eLiang ZY, Wang Y, Wei XY, Wen WY, et al. Prevalence and associated factors of depressive and anxiety symptoms among healthcare workers in the post-pandemic era of COVID-19 at a tertiary hospital in Shenzhen, China: A cross-sectional study. Frontiers in Public Health. 2023; 11.\u003c/li\u003e\n\u003cli\u003eRamadianto AS, Kusumadewi I, Agiananda F, Raharjanti NW. Symptoms of depression and anxiety in Indonesian medical students: association with coping strategy and resilience. BMC Psychiatry. 2022; 22(1):92. Available from: https://doi.org/10.1186/s12888-022-03745-1.\u003c/li\u003e\n\u003cli\u003eFu WN, Liu YF, Zhang K, Zhang P, et al. Burnout Among Medical Staff 1 Year After the Beginning of the Major Public Health Emergency in Wuhan, China. Frontiers in Psychology. 2022;13. Available from: https://doi.org/10.3389/fpsyg.2022.893389.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"resilience, healthcare workers, ambulance personnel, occupational, doctors","lastPublishedDoi":"10.21203/rs.3.rs-4413230/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4413230/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Psychological resilience facilitates adaptation in stressful environments and is an important personal characteristic that enables workers to navigate occupational challenges. Few studies have evaluated the factors associated with psychological resilience in healthcare workers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives:\u003c/strong\u003e To determine the prevalence and factors associated with psychological resilience in a group of South African medical doctors and ambulance personnel.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and Methods:\u003c/strong\u003e This analytical cross-sectional study used secondary data obtained from studies conducted with healthcare workers. Factors associated with resilience, as measured by the Connor-Davidson Resilience Scale-10 (CD-RISC-10), were evaluated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eA total of 647 healthcare workers were included in the study. Resilience scores were low overall (27.6 ± 6.6) but higher for ambulance personnel (28.0 ±6.9) than for doctors (27.1 ± 6.0) (p=0.006). The factors associated with high resilience scores in doctors were male gender (p\u0026lt; 0.001), higher income (p=0.020), and current smoking (p=0.012), while for ambulance personnel, there was previous alcohol use (p=0.002). Significantly lower resilience was observed in participants with mental health conditions (doctors: p=0.037; ambulance personnel: p=0.010) who were receiving treatment for mental health conditions (ambulance personnel: p=0.029). Multivariable analysis confirmed that the protective factors for doctors were current smoking status (β= 3.52, p=0.009) and a higher salary (β= 5.11, p=0.006), while for ambulance personnel, the protective factor was previous alcohol use (β=3.22, p=0.003). Female gender (β=-1.77, p=0.032) and working overtime with doctors (β=-5.11 p=0.006) increased the likelihood of low resilience.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Resilience was relatively low in this group of South African healthcare workers. The strong association between low resilience and individual and workplace factors provides avenues for early intervention and building resilience in healthcare workers.\u003c/p\u003e","manuscriptTitle":"Sociodemographic and work-related factors associated with psychological resilience in South African healthcare workers: a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-30 16:02:08","doi":"10.21203/rs.3.rs-4413230/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-17T07:57:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-16T04:27:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-15T08:21:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2024-05-13T12:27:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9f65c562-0113-4bcc-83df-ce48e4ce9ddf","owner":[],"postedDate":"May 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-26T16:03:33+00:00","versionOfRecord":{"articleIdentity":"rs-4413230","link":"https://doi.org/10.1186/s12913-024-11430-0","journal":{"identity":"bmc-health-services-research","isVorOnly":false,"title":"BMC Health Services Research"},"publishedOn":"2024-08-24 15:56:58","publishedOnDateReadable":"August 24th, 2024"},"versionCreatedAt":"2024-05-30 16:02:08","video":"","vorDoi":"10.1186/s12913-024-11430-0","vorDoiUrl":"https://doi.org/10.1186/s12913-024-11430-0","workflowStages":[]},"version":"v1","identity":"rs-4413230","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4413230","identity":"rs-4413230","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}