Workplace bullying and turnover intention among male nurses: A cross-sectional study in Bangladesh

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Understanding this relationship is crucial for developing targeted interventions to improve retention and well-being among male nurses in Bangladesh. Thus, this study aimed to explore the relationship between WPB and TI among Bangladeshi male nurses. Method: We conducted a cross-sectional study among 379 Bangladeshi registered male nurses between April 26 and July 10, 2021. The study sites included indoor or outdoor settings where nurses provide healthcare. We used the Short Negative Acts Questionnaire-9 (S-NAQ-9) to measure WPB and the Turnover Intention Scale-6 (TIS-6) to assess TI. We performed a multiple linear regression model to explore the association of WPB and other variables with TI. Results: The study participants were predominantly young male nurses, with a significant proportion employed in urban settings and holding a Bachelor of Science (B.Sc.) degree. The study found a significant positive association between WPB and TI, suggesting that higher levels of WPB were related to increased TI. Likewise, some other factors such as educational degree, smoking status, job types, professional titles, timely payment, and violence-related training showed significant associations with TI. Conclusion: This study highlights the need for focused interventions to reduce WPB and enhance working conditions for male nurses in Bangladesh. Addressing WPB, as well as improving work satisfaction through targeted initiatives, is critical for reducing TI among this demographic. Male Nurse workplace healthcare bullying turnover intention Bangladesh. Introduction Nurses play a vital role in healthcare services in hospitals, clinics, communities, and other settings to continue the flow of healthcare services among the population [1]. The shortage of nurses, however, can have detrimental effects on the quality of care, as emphasized by Aiken et al. [2]. The World Health Organization (WHO) predicts a critical shortage of 12.9 million qualified nurses globally by 2035 [3]. Like many other regions, Bangladesh is grappling with a severe nursing shortage [4]. Recent research found a significant increase in nurse TI scores alongside a marginal rise in the number of available nurses [5, 6]. To address the challenges faced by healthcare systems, various studies, such as the one conducted by Aboshaiqah et al. sought to identify and address these obstacles [7]. A study reported that factors such as an unsafe workplace environment and bullying can exacerbate the nursing workforce shortage [8]. Workplace bullying (WPB) refers to repetitive and unjustifiable maltreatment towards a single employee or a group of employees that threatens their safety and well-being [9]. The nurses are frequently subject to WPB, which hampers nurses’ well-being and ability to perform their jobs effectively [10]. Studies reported that a significant number of nurses, ranging from 22.0% to 44.0%, experience WPB during their careers, including practices such as rejection, harassment, and insults [11][12]. The consequences of WPB can lead to poor job satisfaction, increased levels of anxiety, stress disorders, and other psychological complaints, potentially motivating individuals to consider leaving their jobs [13–16]. In Bangladesh, the prevalence of WPB is also a serious concern; a study reported that 61% of entry-level health workers experienced physical assault [17]. Nurses subjected to WPB may have difficulty in delivering high-quality healthcare services [18]. Addressing WPB is crucial for promoting nurses' overall well-being, engagement, and the provision of quality care. Turnover intention (TI) refers to the intention of an employee to leave their job due to dissatisfaction or specific job-related factors or due to the influence of other multiple factors. Important determinants of TI include factors related to the work environment, such as WPB, workload, stress, organizational structure, management, and individual factors [19]. Effective nursing staff retention strategies encompass appropriate compensation and career advancement opportunities [20]. However, according to the literature, negative workplace attitudes, activities, and behaviours such as WPB, violence, etc., may affect nurses' TI, burnout, depression, and poor job satisfaction [21–25]. Given the substantial responsibilities of nurses in the healthcare sector in fulfilling the needs of clients, colleagues, and other professionals, exploring the relationship between WPB and nurses' TI the profession is of utmost importance. Limited research has been conducted in Bangladesh regarding doctors' intention to leave, as evidenced by previous studies [26, 27]. To the best of our knowledge, no research is currently examining the relationship between WPB and intention to leave, specifically among male Bangladeshi nurses. This is particularly important as male nurses constitute a smaller proportion of the healthcare workforce compared to other genders [28]. In addition, male students make up a relatively small portion of the total number of nursing students in Bangladesh, ultimately leading to fewer male nurses being recruited by healthcare providers [29]. Consequently, having substantial evidence regarding their workplace conditions would become invaluable, shedding light on the experiences of this underrepresented cohort within the nursing profession. Acknowledging the gap in the existing literature, our study aimed to investigate the relationship between WPB and TI. Additionally, our research explored the factors associated with TI among male nurses in Bangladesh.This study has the potential to contribute to a comprehensive understanding of the workplace dynamics influencing the experiences of Bangladeshi male nurses and their potential impact on TI within the nursing profession. Methodology Study design, settings, and participants We conducted a cross-sectional study among Bangladeshi registered male nurses between April 26 and July 10, 2021. By assuming a 50% prevalence of TI among male nurses, a required sample size of 384 was determined based on a 95% confidence level and a 5% margin of error [30]. After the data collection and cleaning, a total of 379 male nurses were included in this study. The criteria of the study participants were directly involved in clinical care settings, registered nurse (RN) according to the Bangladesh Nursing and Midwifery Council (BNMC) [31], and had at least one year of work experience. The study sites included indoor or outdoor settings where nurses provide healthcare, such as private and non-private tertiary hospitals, secondary hospitals, upazila hospitals, community clinics, and other healthcare sites. Study questionnaire The questionnaire used in this study incorporated both the original English version and a translated version in Bengali to ensure a comprehensive understanding among respondents. The translation process involved two independent translators converting the questionnaire from English to Bengali. The translated version was carefully compared to the original English version by the authors, and any ambiguities or discrepancies were discussed with the translators to refine the Bengali version of the questionnaire. Face validation was conducted to enhance the validity and clarity of the questionnaire. Five nurse superintendents and five psychologists were involved in reviewing the questionnaire. Their valuable input, comments, and suggestions regarding the wording and layout were carefully considered. Based on the suggestions, slight modifications were made to the wording, meanings, and content of each item in the questionnaire. Following the refinement process, a pilot test was conducted among a group of 20 nurses to evaluate the suitability and comprehensibility of the revised questionnaire. This pilot testing helped identify any potential issues or challenges that needed to be addressed before the main data collection. The questionnaire consisted of three sections. The first section focused on collecting demographic information from the participants. The second section aimed to gather occupational characteristics. Finally, the third section contained items specifically related to WPB and TI measurement. Study variables The outcome variable of our study was the TI, while the main exposure variable was the WPB experienced by male nurses. After the literature review, we included demographic variables, including age, place of residence, educational degree, and smoking status, as well as work-related variables such as job type, professional titles, monthly salary, timely payments, availability of accommodation facilities, presence of sufficient equipment to perform work, rewards for good works, and training against workplace violence which was reported to be associated with the nurse TI [32–42]. WPB measurement To evaluate the workplace bullying (WPB) experienced by nurses, we utilized the "Short Negative Acts Questionnaire (S-NAQ-9)", which consists of nine items [43]. This questionnaire was employed to determine whether individuals have been subjected to WPB behaviours within the preceding six months. The scale encompasses various forms of personal and WPB, such as "there has been gossip or rumors spread about you", "necessary information was withheld that impeded your ability to do your job." Respondents were presented with response options ranging from 1 to 5, where 1 represented "never" and 5 represented "daily." Therefore, the overall score on the scale ranged from 9 to 45, with higher scores indicating a greater degree of WPB experienced. The internal consistency of the S-NAQ-9, as measured by ω (McDonald's omega), was determined to be 0.88 in the current sample, indicating good internal reliability. TI measurement We employed the Turnover Intention Scale-6 (TIS-6) to measure the TI among the nurses over a period of nine months. This scale, consisting of six items, has been widely utilized in prior studies focusing on nurses [44, 45]. Participants were instructed to respond on a five-point Likert scale, ranging from 1 to 5, to indicate their agreement with statements pertaining to the impact of their current job on their intention to leave, the frequency at which they consider alternative job options, and the extent of hesitation they experience when contemplating leaving their present position. A composite score ranging from 6 to 30 was calculated by summing the responses to all items, with higher scores indicating a greater degree of TI. The reliability coefficient of the scale, as determined by ω, was found to be 0.89. Data collection procedure The data collection process employed a convenience sampling method using the semi-structured self-reported questionnaire. We utilized both online and offline approaches to collect the data. For online data collection, eligible participants were invited to participate in the study by accessing an online questionnaire link, which was facilitated using "Google Form." This link was shared across various social media groups, such as Facebook, WhatsApp, and other relevant platforms, to reach out to nurses. Nurses willing to participate clicked on the provided link to complete the questionnaire. In addition to online data collection, in-person data collection was carried out by distributing printed copies of the questionnaire among male nurses in selected tertiary hospitals in two major divisions of Bangladesh ("Dhaka and Sylhet"). We allowed participants seven days to fill out the questionnaire, and after that, the research assistants collected completed questionnaires. After the participants filled out the questionnaires, the collected data were manually entered into the same Excel sheet to ensure uniformity and consistency. By employing these combined methods, a total of 420 responses were collected, and subsequently, 379 completed responses were included in the analysis. Data Analysis The data analysis and management process involved the utilization of Stata 16 and Microsoft Excel 2016. Microsoft Excel was employed to compile the data obtained from both offline and online data collection methods. Subsequently, the compiled data sheet was imported into STATA for further analysis. Descriptive statistics, including percentages and frequencies, were calculated for categorical variables, while measures such as mean, standard deviation, minimum, and maximum were computed for continuous variables. Inferential statistical techniques, such as the t-test and one-way analysis of variance (ANOVA), were employed to assess mean differences in TI across different demographic and occupational characteristics. Pearson's correlation test was conducted to examine the relationships between age, monthly income, WPB, and TI. Multiple linear regression models were fitted to examine the adjusted association between WPB and TI while controlling for demographic and occupational characteristics. Three hierarchical regression models were developed to identify predictors. Model 1 included demographic variables, Model 2 incorporated occupational variables in addition to demographic variables, and Model 3 encompassed WPB, along with both demographic and occupational variables. The final multiple hierarchical regression models encompassed WPB, demographic variables, and occupational variables to explore the combined influence of the study variables. To assess multicollinearity, a post-estimation test known as the Variance Inflation Factor (VIF) was performed. In this study, statistical significance was determined using a threshold of p < 0.05. Ethical considerations Ethical considerations were duly addressed in our study by the Ethical Committee of Begum Rabeya Khatun Chowdhury Nursing College, Bangladesh, with approval ID BRKCNC-IRB-2021/5. Participants were asked to provide their informed consent before participating in the study. Participants were provided with the freedom to refuse participation, and they were informed of their right to withdraw from the study at any time. We ensured the confidentiality of participants' data and provided a comprehensive briefing on the aim and objectives of the study. Results Background characteristics of the study participants The background characteristics of the study participants are presented in Table 1 . The mean age of the participants was 27.73 years. We found that more than half (54.09%) of the participants were 25-29 years old, while the majority (86.02%) of the respondents were employed in urban settings. Furthermore, more than two-thirds (43.01%) of the nurses held a Bachelor of Science (BSc) degree. Regarding monthly income, more than half (59.37%) of nurses reported earning between 20000 BDT to 30000 BDT. More than two-thirds of the participants (70.18%) claimed to have never smoked. Additionally, more than half of the nurses (53.30%) were employed in the government sector. A considerable number of nurses (78.36%) did not have any accommodation. Moreover, more than half (53.83%) reported inadequate access to sufficient equipment, and more than one-third (82.59%) did not receive any awards for their commendable work. A large proportion of the nurses (78.1%) had yet to receive any training on workplace violence. TI scores across demographic and occupational variables In Table 2 , TI scores across demographic and occupational variables are presented. The TI was found to be significantly high among the MSc degree holders (p = 0.036). The TI was significantly high among the current smokers (p = 0.009). The TI of staff nurses was significantly higher than that of the nurse in-charge (p = 0.007). Those who did not receive timely payment (p < 0.001), accommodation facilities (p = 0.043), sufficient equipment (p = 0.003), rewards for good works (p = 0.001) and training against violence (p < 0.001), their TI was found significantly higher. Descriptive statistics of SNAQ-9 and TIS-6 Table 3 presents the descriptive statistics of two scales, the SNAQ-9 and TIS-6. The mean score of the SNAQ-9 scale was 15.95, and the range of scores was between 6 and 29. The mean score of the TIS-6 scale was 17.55, and the range of scores was between 9 and 45. Adjusted association of WPB, demographic, and occupational variables with TI Table 4 shows the adjusted association of WPB, demographic, and occupational variables with TI. We found a significantly positive association between WPB and TI (β = 0.25, 95% CI: 0.19, 0.31, p < 0.001). Diploma degree holders had a significantly lower TI than M.Sc. degree holders (β = -1.67, 95% CI: -2.86, -0.48, p = 0.006). TI was found significantly higher among the current smokers than the never smokers (β = 1.66, 95% CI: 0.54, 2.78, p = 0.004). TI was found significantly higher among nurses doing private jobs than the nurses doing government jobs (β = 1.67, 95% CI: 0.46, 2.88, p = 0.007). TI of staff nurses was significantly higher than that of charge-nurses (β = 3.57, 95% CI: 1.36, 5.79, p = 0.002). TI was found significantly higher among the nurses who were not paid their salary timely (β = 2.13, 95% CI: 0.82, 3.44, p = 0.002) and those who did not have any training against workplace violence (β = 1.46, 95% CI: 0.40, 2.52, p = 0.007). Predictive models for the TI In this study, we utilized three blocks of predictive hierarchical models ( Table 5 ), as described in the analysis. In our first model, we incorporated demographic information, which accounted for 3% of the variability in TI ( Block 1 ). Moving on to the second model, we introduced occupational variables, which increased the predictive power and explained a total of 15% of the variability in TI ( Block 2 ). Finally, in the last model, we included WPB, which further improved predictability. Overall, the demographic information, occupational variables, and WPB combined significantly explained 29% of the variability in TI ( Block 3 ). Discussion Nurses play a vital role in providing care to patients and dedicate a large portion of their workday to patient well-being. One study found that nurses faced excessive workloads in multiple healthcare facilities in Bangladesh [ 47 ]. Another qualitative study revealed that nurses encountered mental distress because of their high workloads, even during the COVID-19 pandemic in Bangladesh [ 48 ]. In the context of patient safety and avoiding detrimental occurrences, the critical importance of a supportive work environment for nurses cannot be ignored. Our study focused on this essential intersection, and we found a positive association between WPB and TI and various factors, including educational degree, smoking status, job types, professional titles, timely payment, and training against violence, were found significantly associated with male nurses’ TI. The finding of a significantly positive association between WPB and TI is consistent with earlier research conducted in other countries, which has consistently shown a positive association between WPB and TI. For example, Houck et al. found that WPB was significantly associated with detrimental outcomes among nurses in the USA, such as TI, work dissatisfaction, and intention to leave [ 49 ]. According to Kim et al. WPB showed a substantial relationship with TI, emotional exhaustion, depersonalization, and professional quality of life among South Korean nurses [ 50 ]. Shen et al. emphasized that nearly one in ten nurses experienced WPB, leading to a heightened desire to leave [ 51 ], while Muharraq et al. reported that in 31.7% of individuals engaging in the job, WPB behaviours resulted in a strong intention to leave [ 52 ]. Our study revealed significant associations of demographic and occupational characteristics of nurses with TI. Individuals with diploma degrees exhibited lower TI compared to those with higher degrees, such as B.Sc. and M.Sc. This finding aligns with previous research indicating that individuals with lower educational degrees tend to experience higher job satisfaction, possibly due to the expected level of wages and opportunities in Bangladesh [ 24 , 25 ]. On the other hand, nurses with advanced degrees may perceive more challenges, such as limited career prospects, inadequate wage increments relative to their academic degrees, and perceived exclusion due to societal perspectives on the nursing profession in Bangladesh [ 53 ]. We found that smoking habits significantly predicted the level of TI among male nurses. Although the exact underlying mechanism is unclear, previous research showed a positive relationship between smoking behaviour and stress levels [ 54 ]. Additionally, high levels of work-related stress have been associated with increased TI [ 55 ]. Thus, it may be inferred that the higher TI among participants may be attributed to stress, leading to the development of smoking habits. However, it is essential to acknowledge that the perception of this relationship may vary in different contexts [ 56 ]. Based on the findings of our study, there was a significant association between TI and nurses’ working sector, such as private or government. Nurses in the private sector exhibited a higher likelihood of TI than their government counterparts. This finding aligns with previous research by Mazumder et al. [ 57 ], who found that nurses working in public hospitals demonstrated higher job satisfaction and lower intention to leave. One possible explanation for this finding could be the timely and adequate compensation nurses receive. Our study revealed that nurses who received timely and satisfactory payments perceived lower TI. In Bangladesh, nurses employed by the government receive competitive and punctual remuneration. Timely payment is recognized as an essential factor in attracting and retaining top talent and is increasingly crucial in today's challenging global economy [ 58 ]. Ehsan et al. suggested emphasizing prompt payment as an approach to attract highly skilled employees, improve job satisfaction, and reduce TI [ 59 ]. Our study revealed a significant association between professional position and TI. Specifically, staff nurses exhibited a higher TI compared to nurse-in-charge counterparts, who possess more experience and higher designations. This finding is consistent with the research conducted by Kim et al. in South Korea, indicating that highly experienced nurses were less likely to leave their jobs [ 50 ]. The study emphasized the crucial role of nursing leadership in implementing interventions to prevent WPB and establish a supportive and positive work environment [ 50 ]. Creating such an environment for male nurses is essential for retaining nurses and reducing TI in the context of Bangladesh. We found no significant association between the availability of sufficient requirements and accommodation facilities in this study. However, previous research conducted by Yu et al. and Oh et al. [ 60 ] [ 61 ] found a positive relationship between TI and the availability of required equipment for nurses. Yu and Lee et al. highlighted that individuals reported a more positive view of their workplace when their needs were adequately met, indicating a lower TI [ 62 ]. The provision of necessary supplies contributes to a sense of value and importance among the employees, as reported by Basit et al. [ 63 ]. Our study found that male nurses who received rewards for their good work exhibited a lower TI. This finding aligns with the findings of other researchers, as reported by Kumari et al. [ 64 ], who emphasized the role of rewards in promoting desirable and productive behaviours while discouraging negative conduct. In the healthcare industry, organizations face intense competition and the need to adapt swiftly to evolving client needs. Hence, effective reward management strategies can be employed to attract and retain skilled nursing staff, motivating them to perform at their best and fostering higher job retention [ 65 ]. In our study, we observed that nurses who did not receive training against violence were more prone to experiencing depression and exhibited higher TI. This finding is supported by the study of Al-Ali et al., who examined the perceptions of Jordanian nurses regarding workplace violence and the impact of training programs on their attitudes [ 66 ]. Al-Ali et al. also concluded that practical training significantly influenced nurses' attitudes, reducing work-related mental distress and increasing commitment to their jobs [ 66 ]. Similarly, Cicolini et al. reported a positive association between creative organizational arrangements in the workplace and nurses' job satisfaction [ 67 ]. Conclusions This study examined the relationship between WPB and TI, as well as associated demographic and professional factors among Bangladeshi male nurses. We found a significant association between WPB and TI, with an increase in WPB corresponding to higher TI. Our investigation found demographic and professional factors associated with TI, such as educational level, smoking status, job types, job title, timely payment, recognition for good work, and training against violence. It provided useful evidence for the context while implementing efforts to reduce the TI among male nurses in Bangladesh; all these factors must be considered. Moreover, our results may be useful in addressing WPB and implementing strategies to improve male nurses' workplace, ultimately reducing TI in the profession. Strength and Limitation To the best of our knowledge, this study is the first to explore the association between WPB and TI, specifically among Bangladeshi male nurses. Furthermore, this baseline evidence contributes to addressing this issue in the context of Bangladesh and similar developing countries. However, our study has certain limitations that should be acknowledged. Firstly, the study design was cross-sectional, which limits our ability to establish a causal association between WPB and TI. Secondly, the data collection method employed was not based on probability sampling, introducing the possibility of selection bias. Additionally, although the study accounted for various demographic and professional factors, there may be other unmeasured confounding variables that influence the relationship between WPB and TI. Consequently, the ability of our study to fully elucidate the observed relationships may be compromised if these potential confounders are not adequately considered. We recommend that future studies utilize longitudinal designs to identify causal relationships and sampling methods with probability to improve generalizability. In order to provide a more nuanced understanding of the association between WPB and TI, substantial efforts should be made to identify and measure relevant confounding variables. Recommendations Several recommendations can be made to address WPB and mitigate TI among male nurses in Bangladesh. Organizations should prioritize establishing a healthy and supportive work environment by implementing comprehensive anti-WPB policies and procedures. This includes raising awareness about WPB, training on recognizing and addressing WPB behaviors and fostering a culture of respect and inclusivity. Education institutions and professional bodies should also incorporate modules on WPB and its impact on nurses' well-being and job satisfaction into nursing curricula and continuing education programs. By equipping nurses with knowledge and skills to address WPB, they can better advocate for themselves and their colleagues and contribute to a positive work environment. Furthermore, healthcare organizations should prioritize providing nurses with the necessary resources, equipment, and accommodation facilities. This can help alleviate stress and improve job satisfaction, reducing the likelihood of TI. Recognizing and rewarding nurses for their hard work and achievements can enhance motivation and engagement, fostering a sense of belonging and loyalty. Lastly, training programs specifically addressing violence in the workplace can be beneficial. Organizations can improve their mental well-being and job satisfaction by equipping nurses with strategies to handle and prevent workplace violence, ultimately reducing TI. Abbreviations WPB: workplace bullying, TI: turnover intention, SNAQ-9: Short Negative Acts Questionnaire-9, TIS-6: Turnover Intention Scale-6 Declarations Ethical approval and consent to participate Ethical considerations were duly addressed in our study by the Ethical Committee of Begum Rabeya Khatun Chowdhury Nursing College, Bangladesh, with approval ID BRKCNC-IRB-2021/5. Participants were asked to provide their inform consent before the participation in the study. Consent for publication Not applicable. Competing interests The authors declare no competing interest in this study. Funding This study received no specific funding from public, commercial, or not-for-profit funders. Authors’ contributions AKR: Conceptualization, writing, review, and data collection. MA: Conceptualization, review, edit, and data collection. NA: Writing, review, and edit. MIH: Writing, review, and edit. SRC: Conceptualization, methodology, review, and edit. 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Tables Table 1: Background characteristics of the study participants (n= 379) Variables n (%)/mean (SD) Demographic variables Age (mean), years 27.73 (4.85) Age, years < 25 89 (23.48) 25 - 29 205 (54.09) ≥ 30 85 (22.43) Residence Rural 53 (13.98) Urban 326 (86.02) Degree Diploma 131 (34.56) Bachelor’s 163 (43.01) Master’s 85 (22.43) Monthly income, BDT 30000 72 (19.00) Smoking status Current smoker 61 (16.09) Past smoker 52 (13.72) Never smoke 266 (70.18) Occupational variables Job types Government 202 (53.30) Private 177 (46.70) Professional titles Staff nurse 366 (96.57) In-charge 13 (3.43) Received timely salary No 47 (12.40) Yes 332 (87.60) Had accommodation facilities No 297 (78.36) Yes 82 (21.64) Had sufficient equipment No 204 (53.83) Yes 175 (46.17) Have rewards for good works No 313 (82.59) Yes 66 (17.41) Have training against violence No 296 (78.10) Yes 83 (21.90) Footnote: SD: standard deviation, BDT: Bangladeshi Taka Table 2: TI scores across demographic and occupational variables Variables Turnover intention Mean ± SD F/t value p -value Demographic variables Age, years < 25 15.69 ± 4.80 0.55 0.453 25 - 29 16.87 ± 4.90 ≥ 30 16.39 ± 3.67 Residence Rural 15.50 ± 4.02 0.75 0.453 Urban 16.02 ± 4.71 Degree Diploma 15.26 ± 4.58 3.36 0.036 B.Sc. 15.99 ± 4.78 M.Sc. 16.92 ± 4.23 Monthly income 30000 15.53 (4.26) Smoking status Current smoker 17.54 ± 5.44 4.77 0.009 Past smoker 15.15 ± 3.97 Never smoke 15.15 ± 4.47 Occupational variables Job types Government 15.76 ± 4.58 -0.86 0.392 Private 16.17 ± 4.67 Professional titles Staff nurse 16.07 ± 4.57 -2.73 0.007 In-charge 12.54 ± 4.81 Get timely payment No 18.68 ± 4.82 -4.45 < 0.001 Yes 15.56 ± 4.61 Have accommodation facilities No 16.20 ± 4.57 -2.03 0.043 Yes 15.04 ± 4.71 Have sufficient equipment No 16.61 ± 4.80 -3.03 0.003 Yes 15.18 ± 4.30 Have rewards for good works No 16.30 ± 4.61 -3.29 0.001 Yes 14.27 ± 4.33 Have training against violence No 16.57 ± 4.59 -5.05 < 0.001 Yes 13.76 ± 4.06 Footnotes: SD: Standard deviation, TI: turnover intention Table 3: Descriptive statistics of SNAQ-9 and TIS-6 Scales Mean SD Minimum Maximum SNAQ-9 15.95 4.62 6 29 TIS-6 17.55 7.25 9 45 Footnotes: SNAQ-9: Short Negative Acts Questionnaire-9, TIS-6: Turnover Intention Scale-6, SD: Standard deviation Table 4: Multiple linear regression: adjusted association of WPB, demographic, and occupational variables with TI Variables Adjusted β 95% CI p- value UCI LCI WPB 0.25 0.19 0.31 < 0.001 Demographic variables Age < 25 Reference 25 – 29 0.50 -0.69 1.68 0.409 ≥ 30 0.72 -0.89 2.32 0.381 Residence Rural Reference Urban 0.56 -0.63 1.75 0.358 Degree Diploma -1.67 -2.86 -0.48 0.006 B.Sc. -0.67 -1.74 0.41 0.225 M.Sc. Reference Monthly income 30000 -0.40 -1.87 1.07 0.595 Smoking status Current smoker 1.66 0.54 2.78 0.004 Past smoker -0.21 -1.39 0.96 0.721 Never smoke Reference Occupational variables Job types Government Reference Private 1.67 0.46 2.88 0.007 Professional titles Staff nurse 3.57 1.36 5.79 0.002 In-charge Reference Get timely payment No 2.13 0.82 3.44 0.002 Yes Reference Have accommodation facilities No 0.30 -0.69 1.30 0.548 Yes Reference Have sufficient equipment No 0.07 -0.90 1.04 0.893 Yes Reference Have rewards for good works No 0.72 -0.40 1.84 0.207 Yes Reference Have training against violence No 1.46 0.40 2.52 0.007 Yes Reference Footnotes: β : beta coefficient, WPB: workplace bullying, TI: turnover intention Table 5: Predictive models for the TI Variables Block 1 ( β ) Block 2 ( β ) Block 3 ( β ) Age 0.21 0.52 0.36 Residence -0.18 -0.52 -0.44 Degree -0.84* -0.97** -0.80** Monthly income -0.69 -0.07 -0.23 Smoking status 0.12 0.13 0.13 Job types 1.45* 1.34* Professional titles 3.63** 3.62** Get timely payment 2.78*** 1.94** Have accommodation facilities 0.54 0.43 Have sufficient equipment 0.70 0.10 Have rewards for good works 0.75 0.72 Have training against violence 2.09*** 1.47** WPB 0.26*** F 1.95 6.34 12.78 R 2 0.03 0.17 0.32 ΔR 2 0.01 0.146 0.29 * p < 0.05, ** p < 0.01, *** p < 0.001 Footnotes: β : beta coefficient, WPB: workplace bullying, TI: turnover intention Cite Share Download PDF Status: Posted Version 1 posted 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. 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Department of Public Health, North South University, Dhaka 1229, Bangladesh","correspondingAuthor":false,"prefix":"","firstName":"Masuda","middleName":"","lastName":"Akter","suffix":""},{"id":287213473,"identity":"705fee16-e862-41c9-baca-89fb8b8adec7","order_by":2,"name":"Nahida Akter","email":"","orcid":"","institution":"Penn State Ross and Carol Nese College of Nursing, Penn State University, University Park, Pennsylvania, PA 16802, USA","correspondingAuthor":false,"prefix":"","firstName":"Nahida","middleName":"","lastName":"Akter","suffix":""},{"id":287213474,"identity":"de7f1369-6380-4082-bb52-71cd95b3ca61","order_by":3,"name":"Md Ikbal Hossain","email":"","orcid":"","institution":"School of Medical Sciences, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh; Department of Public Health, North South University, Dhaka 1229, Bangladesh","correspondingAuthor":false,"prefix":"","firstName":"Md","middleName":"Ikbal","lastName":"Hossain","suffix":""},{"id":287213475,"identity":"9488d477-74fa-48aa-9ca1-de204ff1c158","order_by":4,"name":"Shimpi Akter","email":"","orcid":"","institution":"Department of Medical Studies, Bangladesh University of Professionals, Dhaka 1216, Bangladesh","correspondingAuthor":false,"prefix":"","firstName":"Shimpi","middleName":"","lastName":"Akter","suffix":""},{"id":287213476,"identity":"e40c28ba-e62f-4837-be57-793176ca7fc2","order_by":5,"name":"Sopon Akter","email":"","orcid":"","institution":"Department of Economics, American International University-Bangladesh, Dhaka 1229, Bangladesh","correspondingAuthor":false,"prefix":"","firstName":"Sopon","middleName":"","lastName":"Akter","suffix":""},{"id":287213477,"identity":"3a803dd9-c191-4da3-895b-aed72a39edcf","order_by":6,"name":"Saifur Rahman Chowdhury","email":"","orcid":"","institution":"Department of Public Health, North South University, Dhaka 1229, Bangladesh; Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada","correspondingAuthor":false,"prefix":"","firstName":"Saifur","middleName":"Rahman","lastName":"Chowdhury","suffix":""},{"id":287213478,"identity":"c8549372-cc05-4cfd-af3c-e40cce957512","order_by":7,"name":"Humayun Kabir","email":"data:image/png;base64,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","orcid":"","institution":"Department of Public Health, North South University, Dhaka 1229, Bangladesh; Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada","correspondingAuthor":true,"prefix":"","firstName":"Humayun","middleName":"","lastName":"Kabir","suffix":""}],"badges":[],"createdAt":"2023-11-02 09:44:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3542653/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3542653/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57667145,"identity":"bf8b601c-e6d6-49bb-a537-2c70dadd5a6c","added_by":"auto","created_at":"2024-06-04 05:24:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1119051,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3542653/v1/820da261-d2dd-4c96-8386-f8014860cd3f.pdf"}],"financialInterests":"","formattedTitle":"Workplace bullying and turnover intention among male nurses: A cross-sectional study in Bangladesh","fulltext":[{"header":"Introduction ","content":"\u003cp\u003eNurses play a vital role in healthcare services in hospitals, clinics, communities, and other settings to continue the flow of healthcare services among the population [1]. The shortage of nurses, however, can have detrimental effects on the quality of care, as emphasized by Aiken et al. [2]. The World Health Organization (WHO) predicts a critical shortage of 12.9 million qualified nurses globally by 2035 [3]. \u0026nbsp;Like many other regions, Bangladesh is grappling with a severe nursing shortage [4]. Recent research found a significant increase in nurse TI scores alongside a marginal rise in the number of available nurses [5, 6]. To address the challenges faced by healthcare systems, various studies, such as the one conducted by Aboshaiqah et al. sought to identify and address these obstacles [7]. A study reported that factors such as an unsafe workplace environment and bullying can exacerbate the nursing workforce shortage [8].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWorkplace bullying (WPB) refers to repetitive and unjustifiable maltreatment towards a single employee or a group of employees that threatens their safety and well-being [9]. The nurses are frequently subject to WPB, which hampers nurses’ well-being and ability to perform their jobs effectively [10]. Studies reported that a significant number of nurses, ranging from 22.0% to 44.0%, experience WPB during their careers, including practices such as rejection, harassment, and insults [11][12]. The consequences of WPB can lead to poor job satisfaction, increased levels of anxiety, stress disorders, and other psychological complaints, potentially motivating individuals to consider leaving their jobs [13–16].\u0026nbsp;In Bangladesh, the prevalence of WPB is also a serious concern; a study reported that 61% of entry-level health workers experienced physical assault [17]. Nurses subjected to WPB may have difficulty in delivering high-quality healthcare services [18]. Addressing WPB is crucial for promoting nurses' overall well-being, engagement, and the provision of quality care.\u003c/p\u003e\n\u003cp\u003eTurnover intention (TI) refers to the intention of an employee to leave their job due to dissatisfaction or specific job-related factors or due to the influence of other multiple factors. Important determinants of TI include factors related to the work environment, such as WPB, workload, stress, organizational structure, management, and individual factors [19]. Effective nursing staff retention strategies encompass appropriate compensation and career advancement opportunities [20]. However, according to the literature, negative workplace attitudes, activities, and behaviours such as WPB, violence, etc., may affect nurses' TI, burnout, depression, and poor job satisfaction [21–25].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven the substantial responsibilities of nurses in the healthcare sector in fulfilling the needs of clients, colleagues, and other professionals, exploring the relationship between WPB and nurses' TI the profession is of utmost importance. Limited research has been conducted in Bangladesh regarding doctors' intention to leave, as evidenced by previous studies [26, 27].\u0026nbsp;To the best of our knowledge, no research is currently examining the relationship between WPB and intention to leave, specifically among male Bangladeshi nurses. This is particularly important as male nurses constitute a smaller proportion of the healthcare workforce compared to other genders [28]. In addition, male students make up a relatively small portion of the total number of nursing students in Bangladesh, ultimately leading to fewer male nurses being recruited by healthcare providers [29].\u0026nbsp;Consequently, having substantial evidence regarding their workplace conditions would become invaluable, shedding light on the experiences of this underrepresented cohort within the nursing profession. Acknowledging the gap in the existing literature, our study aimed to investigate the relationship between WPB and TI. Additionally, our research explored the factors associated with TI among male nurses in Bangladesh.This study has the potential to contribute to a comprehensive understanding of the workplace dynamics influencing the experiences of Bangladeshi male nurses and their potential impact on TI within the nursing profession.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003e\u003cstrong\u003eStudy design, settings, and participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a cross-sectional study among Bangladeshi registered male nurses between April 26 and July 10, 2021. By assuming a 50% prevalence of TI among male nurses, a required sample size of 384 was determined based on a 95% confidence level and a 5% margin of error [30]. After the data collection and cleaning, a total of 379 male nurses were included in this study. The criteria of the study participants were directly involved in clinical care settings, registered nurse (RN) according to the Bangladesh Nursing and Midwifery Council (BNMC) [31], and had at least one year of work experience. The study sites included indoor or outdoor settings where nurses provide healthcare, such as private and non-private tertiary hospitals, secondary hospitals, upazila hospitals, community clinics, and other healthcare sites.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy questionnaire\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe questionnaire used in this study incorporated both the original English version and a translated version in Bengali to ensure a comprehensive understanding among respondents. The translation process involved two independent translators converting the questionnaire from English to Bengali. The translated version was carefully compared to the original English version by the authors, and any ambiguities or discrepancies were discussed with the translators to refine the Bengali version of the questionnaire. Face validation was conducted to enhance the validity and clarity of the questionnaire. Five nurse superintendents and five psychologists were involved in reviewing the questionnaire. Their valuable input, comments, and suggestions regarding the wording and layout were carefully considered. Based on the suggestions, slight modifications were made to the wording, meanings, and content of each item in the questionnaire. Following the refinement process, a pilot test was conducted among a group of 20 nurses to evaluate the suitability and comprehensibility of the revised questionnaire. This pilot testing helped identify any potential issues or challenges that needed to be addressed before the main data collection. The questionnaire consisted of three sections. The first section focused on collecting demographic information from the participants. The second section aimed to gather occupational characteristics. Finally, the third section contained items specifically related to WPB and TI measurement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe outcome variable of our study was the TI, while the main exposure variable was the WPB experienced by male nurses. After the literature review, we included demographic variables, including age, place of residence, educational degree, and smoking status, as well as work-related variables such as job type, professional titles, monthly salary, timely payments, availability of accommodation facilities, presence of sufficient equipment to perform work, rewards for good works, and training against workplace violence which was reported to be associated with the nurse TI [32–42].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWPB measurement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate the workplace bullying (WPB) experienced by nurses, we utilized the \"Short Negative Acts Questionnaire (S-NAQ-9)\", which consists of nine items [43]. This questionnaire was employed to determine whether individuals have been subjected to WPB behaviours within the preceding six months. The scale encompasses various forms of personal and WPB, such as \"there has been gossip or rumors spread about you\", \"necessary information was withheld that impeded your ability to do your job.\" Respondents were presented with response options ranging from 1 to 5, where 1 represented \"never\" and 5 represented \"daily.\" Therefore, the overall score on the scale ranged from 9 to 45, with higher scores indicating a greater degree of WPB experienced. The internal consistency of the S-NAQ-9, as measured by ω (McDonald's omega), was determined to be 0.88 in the current sample, indicating good internal reliability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTI measurement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe employed the Turnover Intention Scale-6 (TIS-6) to measure the TI among the nurses over a period of nine months. This scale, consisting of six items, has been widely utilized in prior studies focusing on nurses [44, 45]. Participants were instructed to respond on a five-point Likert scale, ranging from 1 to 5, to indicate their agreement with statements pertaining to the impact of their current job on their intention to leave, the frequency at which they consider alternative job options, and the extent of hesitation they experience when contemplating leaving their present position. A composite score ranging from 6 to 30 was calculated by summing the responses to all items, with higher scores indicating a greater degree of TI. The reliability coefficient of the scale, as determined by ω, was found to be 0.89.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data collection process employed a convenience sampling method using the semi-structured self-reported questionnaire. We utilized both online and offline approaches to collect the data. For online data collection, eligible participants were invited to participate in the study by accessing an online questionnaire link, which was facilitated using \"Google Form.\" This link was shared across various social media groups, such as Facebook, WhatsApp, and other relevant platforms, to reach out to nurses. Nurses willing to participate clicked on the provided link to complete the questionnaire. In addition to online data collection, in-person data collection was carried out by distributing printed copies of the questionnaire among male nurses in selected tertiary hospitals in two major divisions of Bangladesh (\"Dhaka and Sylhet\"). We allowed participants seven days to fill out the questionnaire, and after that, the research assistants collected completed questionnaires. After the participants filled out the questionnaires, the collected data were manually entered into the same Excel sheet to ensure uniformity and consistency. By employing these combined methods, a total of 420 responses were collected, and subsequently, 379 completed responses were included in the analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data analysis and management process involved the utilization of Stata 16 and Microsoft Excel 2016. Microsoft Excel was employed to compile the data obtained from both offline and online data collection methods. Subsequently, the compiled data sheet was imported into STATA for further analysis. Descriptive statistics, including percentages and frequencies, were calculated for categorical variables, while measures such as mean, standard deviation, minimum, and maximum were computed for continuous variables. Inferential statistical techniques, such as the t-test and one-way analysis of variance (ANOVA), were employed to assess mean differences in TI across different demographic and occupational characteristics. Pearson's correlation test was conducted to examine the relationships between age, monthly income, WPB, and TI. Multiple linear regression models were fitted to examine the adjusted association between WPB and TI while controlling for demographic and occupational characteristics. Three hierarchical regression models were developed to identify predictors. Model 1 included demographic variables, Model 2 incorporated occupational variables in addition to demographic variables, and Model 3 encompassed WPB, along with both demographic and occupational variables. The final multiple hierarchical regression models encompassed WPB, demographic variables, and occupational variables to explore the combined influence of the study variables. To assess multicollinearity, a post-estimation test known as the Variance Inflation Factor (VIF) was performed. In this study, statistical significance was determined using a threshold of p \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical considerations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical considerations were duly addressed in our study by the Ethical Committee of Begum Rabeya Khatun Chowdhury Nursing College, Bangladesh, with approval ID BRKCNC-IRB-2021/5. Participants were asked to provide their informed consent before participating in the study. Participants were provided with the freedom to refuse participation, and they were informed of their right to withdraw from the study at any time. We ensured the confidentiality of participants' data and provided a comprehensive briefing on the aim and objectives of the study.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBackground characteristics of the study participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe background characteristics of the study participants are presented in \u003cstrong\u003eTable 1\u003c/strong\u003e. The mean age of the participants was 27.73 years. We found that more than half (54.09%) of the participants were 25-29 years old, while the majority (86.02%) of the respondents were employed in urban settings. Furthermore, more than two-thirds (43.01%) of the nurses held a Bachelor of Science (BSc) degree. Regarding monthly income, more than half (59.37%) of nurses reported earning between 20000 BDT to 30000 BDT. More than two-thirds of the participants (70.18%) claimed to have never smoked. Additionally, more than half of the nurses (53.30%) were employed in the government sector. A considerable number of nurses (78.36%) did not have any accommodation. Moreover, more than half (53.83%) reported inadequate access to sufficient equipment, and more than one-third (82.59%) did not receive any awards for their commendable work. A large proportion of the nurses (78.1%) had yet to receive any training on workplace violence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTI scores across demographic and occupational variables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn \u003cstrong\u003eTable 2\u003c/strong\u003e, TI scores across demographic and occupational variables are presented. The TI was found to be significantly high among the MSc degree holders (p = 0.036). The TI was significantly high among the current smokers (p = 0.009). The TI of staff nurses was significantly higher than that of the nurse in-charge (p = 0.007). Those who did not receive timely payment (p \u0026lt; 0.001), accommodation facilities (p = 0.043), sufficient equipment (p = 0.003), rewards for good works (p = 0.001) and training against violence (p \u0026lt; 0.001), their TI was found significantly higher.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDescriptive statistics of SNAQ-9 and TIS-6\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e presents the descriptive statistics of two scales, the SNAQ-9 and TIS-6. The mean score of the SNAQ-9 scale was 15.95, and the range of scores was between 6 and 29. The mean score of the TIS-6 scale was 17.55, and the range of scores was between 9 and 45.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdjusted association of WPB, demographic, and occupational variables with TI\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e shows the adjusted association of WPB,\u0026nbsp;demographic, and occupational variables\u0026nbsp;with\u0026nbsp;TI. We found a significantly positive association between WPB and TI (β = 0.25, 95% CI: 0.19, 0.31, p \u0026lt; 0.001). Diploma degree holders had a significantly lower TI than M.Sc. degree holders (β = -1.67, 95% CI: -2.86, -0.48, p = 0.006). TI was found significantly higher among the current smokers than the never smokers (β = 1.66, 95% CI: 0.54, 2.78, p = 0.004). TI was found significantly higher among nurses doing private jobs than the nurses doing government jobs (β = 1.67, 95% CI: 0.46, 2.88, p = 0.007). TI of staff nurses was significantly higher than that of charge-nurses (β = 3.57, 95% CI: 1.36, 5.79, p = 0.002). TI was found significantly higher among the nurses who were not paid their salary timely (β = 2.13, 95% CI: 0.82, 3.44, p = 0.002) and those who did not have any training against workplace violence (β = 1.46, 95% CI: 0.40, 2.52, p = 0.007).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePredictive models for the TI\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, we utilized three blocks of predictive hierarchical models (\u003cstrong\u003eTable 5\u003c/strong\u003e), as described in the analysis. In our first model, we incorporated demographic information, which accounted for 3% of the variability in TI (\u003cstrong\u003eBlock 1\u003c/strong\u003e). Moving on to the second model, we introduced occupational variables, which increased the predictive power and explained a total of 15% of the variability in TI (\u003cstrong\u003eBlock 2\u003c/strong\u003e). Finally, in the last model, we included WPB, which further improved predictability. Overall, the demographic information, occupational variables, and WPB combined significantly explained 29% of the variability in TI (\u003cstrong\u003eBlock 3\u003c/strong\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eNurses play a vital role in providing care to patients and dedicate a large portion of their workday to patient well-being. One study found that nurses faced excessive workloads in multiple healthcare facilities in Bangladesh [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Another qualitative study revealed that nurses encountered mental distress because of their high workloads, even during the COVID-19 pandemic in Bangladesh [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. In the context of patient safety and avoiding detrimental occurrences, the critical importance of a supportive work environment for nurses cannot be ignored. Our study focused on this essential intersection, and we found a positive association between WPB and TI and various factors, including educational degree, smoking status, job types, professional titles, timely payment, and training against violence, were found significantly associated with male nurses\u0026rsquo; TI.\u003c/p\u003e \u003cp\u003eThe finding of a significantly positive association between WPB and TI is consistent with earlier research conducted in other countries, which has consistently shown a positive association between WPB and TI. For example, Houck et al. found that WPB was significantly associated with detrimental outcomes among nurses in the USA, such as TI, work dissatisfaction, and intention to leave [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. According to Kim et al. WPB showed a substantial relationship with TI, emotional exhaustion, depersonalization, and professional quality of life among South Korean nurses [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Shen et al. emphasized that nearly one in ten nurses experienced WPB, leading to a heightened desire to leave [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], while Muharraq et al. reported that in 31.7% of individuals engaging in the job, WPB behaviours resulted in a strong intention to leave [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study revealed significant associations of demographic and occupational characteristics of nurses with TI. Individuals with diploma degrees exhibited lower TI compared to those with higher degrees, such as B.Sc. and M.Sc. This finding aligns with previous research indicating that individuals with lower educational degrees tend to experience higher job satisfaction, possibly due to the expected level of wages and opportunities in Bangladesh [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. On the other hand, nurses with advanced degrees may perceive more challenges, such as limited career prospects, inadequate wage increments relative to their academic degrees, and perceived exclusion due to societal perspectives on the nursing profession in Bangladesh [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe found that smoking habits significantly predicted the level of TI among male nurses. Although the exact underlying mechanism is unclear, previous research showed a positive relationship between smoking behaviour and stress levels [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Additionally, high levels of work-related stress have been associated with increased TI [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Thus, it may be inferred that the higher TI among participants may be attributed to stress, leading to the development of smoking habits. However, it is essential to acknowledge that the perception of this relationship may vary in different contexts [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBased on the findings of our study, there was a significant association between TI and nurses\u0026rsquo; working sector, such as private or government. Nurses in the private sector exhibited a higher likelihood of TI than their government counterparts. This finding aligns with previous research by Mazumder et al. [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], who found that nurses working in public hospitals demonstrated higher job satisfaction and lower intention to leave. One possible explanation for this finding could be the timely and adequate compensation nurses receive. Our study revealed that nurses who received timely and satisfactory payments perceived lower TI. In Bangladesh, nurses employed by the government receive competitive and punctual remuneration. Timely payment is recognized as an essential factor in attracting and retaining top talent and is increasingly crucial in today's challenging global economy [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Ehsan et al. suggested emphasizing prompt payment as an approach to attract highly skilled employees, improve job satisfaction, and reduce TI [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study revealed a significant association between professional position and TI. Specifically, staff nurses exhibited a higher TI compared to nurse-in-charge counterparts, who possess more experience and higher designations. This finding is consistent with the research conducted by Kim et al. in South Korea, indicating that highly experienced nurses were less likely to leave their jobs [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. The study emphasized the crucial role of nursing leadership in implementing interventions to prevent WPB and establish a supportive and positive work environment [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Creating such an environment for male nurses is essential for retaining nurses and reducing TI in the context of Bangladesh.\u003c/p\u003e \u003cp\u003eWe found no significant association between the availability of sufficient requirements and accommodation facilities in this study. However, previous research conducted by Yu et al. and Oh et al. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] found a positive relationship between TI and the availability of required equipment for nurses. Yu and Lee et al. highlighted that individuals reported a more positive view of their workplace when their needs were adequately met, indicating a lower TI [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. The provision of necessary supplies contributes to a sense of value and importance among the employees, as reported by Basit et al. [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study found that male nurses who received rewards for their good work exhibited a lower TI. This finding aligns with the findings of other researchers, as reported by Kumari et al. [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e], who emphasized the role of rewards in promoting desirable and productive behaviours while discouraging negative conduct. In the healthcare industry, organizations face intense competition and the need to adapt swiftly to evolving client needs. Hence, effective reward management strategies can be employed to attract and retain skilled nursing staff, motivating them to perform at their best and fostering higher job retention [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our study, we observed that nurses who did not receive training against violence were more prone to experiencing depression and exhibited higher TI. This finding is supported by the study of Al-Ali et al., who examined the perceptions of Jordanian nurses regarding workplace violence and the impact of training programs on their attitudes [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Al-Ali et al. also concluded that practical training significantly influenced nurses' attitudes, reducing work-related mental distress and increasing commitment to their jobs [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Similarly, Cicolini et al. reported a positive association between creative organizational arrangements in the workplace and nurses' job satisfaction [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study examined the relationship between WPB and TI, as well as associated demographic and professional factors among Bangladeshi male nurses. We found a significant association between WPB and TI, with an increase in WPB corresponding to higher TI. Our investigation found demographic and professional factors associated with TI, such as educational level, smoking status, job types, job title, timely payment, recognition for good work, and training against violence. It provided useful evidence for the context while implementing efforts to reduce the TI among male nurses in Bangladesh; all these factors must be considered. Moreover, our results may be useful in addressing WPB and implementing strategies to improve male nurses' workplace, ultimately reducing TI in the profession.\u003c/p\u003e"},{"header":"Strength and Limitation","content":"\u003cp\u003eTo the best of our knowledge, this study is the first to explore the association between WPB and TI, specifically among Bangladeshi male nurses. Furthermore, this baseline evidence contributes to addressing this issue in the context of Bangladesh and similar developing countries. However, our study has certain limitations that should be acknowledged. Firstly, the study design was cross-sectional, which limits our ability to establish a causal association between WPB and TI. Secondly, the data collection method employed was not based on probability sampling, introducing the possibility of selection bias. Additionally, although the study accounted for various demographic and professional factors, there may be other unmeasured confounding variables that influence the relationship between WPB and TI. Consequently, the ability of our study to fully elucidate the observed relationships may be compromised if these potential confounders are not adequately considered. We recommend that future studies utilize longitudinal designs to identify causal relationships and sampling methods with probability to improve generalizability. In order to provide a more nuanced understanding of the association between WPB and TI, substantial efforts should be made to identify and measure relevant confounding variables.\u003c/p\u003e\n\u003ch3\u003eRecommendations\u003c/h3\u003e\n\u003cp\u003eSeveral recommendations can be made to address WPB and mitigate TI among male nurses in Bangladesh. Organizations should prioritize establishing a healthy and supportive work environment by implementing comprehensive anti-WPB policies and procedures. This includes raising awareness about WPB, training on recognizing and addressing WPB behaviors and fostering a culture of respect and inclusivity. Education institutions and professional bodies should also incorporate modules on WPB and its impact on nurses' well-being and job satisfaction into nursing curricula and continuing education programs. By equipping nurses with knowledge and skills to address WPB, they can better advocate for themselves and their colleagues and contribute to a positive work environment. Furthermore, healthcare organizations should prioritize providing nurses with the necessary resources, equipment, and accommodation facilities. This can help alleviate stress and improve job satisfaction, reducing the likelihood of TI. Recognizing and rewarding nurses for their hard work and achievements can enhance motivation and engagement, fostering a sense of belonging and loyalty. Lastly, training programs specifically addressing violence in the workplace can be beneficial. Organizations can improve their mental well-being and job satisfaction by equipping nurses with strategies to handle and prevent workplace violence, ultimately reducing TI.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eWPB: workplace bullying, TI: turnover intention, SNAQ-9: Short Negative Acts Questionnaire-9, TIS-6: Turnover Intention Scale-6\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical considerations were duly addressed in our study by the Ethical Committee of Begum Rabeya Khatun Chowdhury Nursing College, Bangladesh, with approval ID BRKCNC-IRB-2021/5. Participants were asked to provide their inform consent before the participation in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interest in this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study received no specific funding from public, commercial, or not-for-profit funders.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAKR: Conceptualization, writing, review, and data collection. MA: Conceptualization, review, edit, and data collection. NA: Writing, review, and edit. MIH: Writing, review, and edit. SRC: Conceptualization, methodology, review, and edit. HK: Conceptualization, methodology, analysis, interpretation, writing, review, edit, and project administration.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the nursing students who volunteered their time to take part in this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets of the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMondal MSA, Kabir H, Hasan MK. Psychological effects of COVID-19 on children of frontline nurses. Popul Med. 2021;3 October:1\u0026ndash;2.\u003c/li\u003e\n\u003cli\u003eAiken LH, Sermeus W, den Heede K, Sloane DM, Busse R, McKee M, et al. 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Work, Employment and Society. 2004;18:349\u0026ndash;68.\u003c/li\u003e\n\u003cli\u003eKabir H, Tonmon TT, Hasan MdK, Biswas L, Chowdhury MdAH, Islam MD, et al. Association between preference and e-learning readiness among the Bangladeshi female nursing students in the COVID-19 pandemic: a cross-sectional study. Bulletin of the National Research Centre 2022 46:1. 2022;46:1\u0026ndash;10.\u003c/li\u003e\n\u003cli\u003eSample size determination in health studies : a practical manual / S. K. Lwanga and S. Lemeshow. https://iris.who.int/handle/10665/40062. Accessed 17 Feb 2024.\u003c/li\u003e\n\u003cli\u003eKabir H, Chowdhury SR, Roy AK, Chowdhury SA, Islam MN, Chomon RJ, et al. Association of workplace bullying and burnout with nurses\u0026rsquo; suicidal ideation in Bangladesh. Scientific Reports 2023 13:1. 2023;13:1\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eMcEvoy GM, Cascio WF. Strategies for Reducing Employee Turnover. A Meta-Analysis. 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Factors influencing the turnover of intensive care nurses. Intensive Crit Care Nurs. 2001;17:348\u0026ndash;55.\u003c/li\u003e\n\u003cli\u003eHart SE. Hospital ethical climates and registered nurses\u0026rsquo; turnover intentions. J Nurs Scholarsh. 2005;37:173\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eLee E-K, Kim J-S. Nursing stress factors affecting turnover intention among hospital nurses. Int J Nurs Pract. 2020;26:e12819.\u003c/li\u003e\n\u003cli\u003eMosallam R, Hamidi S, Elrefaay M. Turnover intention among intensive care unit nurses in Alexandria, Egypt. J Egypt Public Health Assoc. 2015;90:46\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eLabrague LJ, Gloe DS, McEnroe-Petitte DM, Tsaras K, Colet PC, LJ L, et al. Factors influencing turnover intention among registered nurses in Samar Philippines. Appl Nurs Res. 2018;39 September 2017:200\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eLabrague LJ, McEnroe-Petitte DM, Gloe D, Tsaras K, Arteche DL, Maldia F. Organizational politics, nurses\u0026rsquo; stress, burnout levels, turnover intention and job satisfaction. Int Nurs Rev. 2017;64:109\u0026ndash;16.\u003c/li\u003e\n\u003cli\u003eNotelaers G, van der Heijden B, Hoel H, Einarsen S. Measuring bullying at work with the short-negative acts questionnaire: identification of targets and criterion validity. Work Stress. 2018;33:58\u0026ndash;75.\u003c/li\u003e\n\u003cli\u003eNashwan AJ, Abujaber AA, Villar RC, Nazarene A, Al-Jabry MM, Fradelos EC. Comparing the Impact of COVID-19 on Nurses\u0026rsquo; Turnover Intentions before and during the Pandemic in Qatar. J Pers Med. 2021;11.\u003c/li\u003e\n\u003cli\u003eWells-English D, Giese J, Price J. Compassion fatigue and satisfaction: influence on turnover among oncology nurses at an urban cancer center. Clin J Oncol Nurs. 2019;23:487\u0026ndash;93.\u003c/li\u003e\n\u003cli\u003eLiu J, Zheng J, Liu K, Liu X, Wu Y, Wang J, et al. 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The Role of Needs-Supplies Fit and Job Satisfaction in Predicting Employee Engagement. Jurnal Pengurusan. 2016;47:3\u0026ndash;12.\u003c/li\u003e\n\u003cli\u003eKumari K, Barkat Ali S, un Nisa Khan N, Abbas J. Examining the Role of Motivation and Reward in Employees\u0026rsquo; Job Performance through Mediating Effect of Job Satisfaction: An Empirical Evidence. International Journal of Organizational Leadership. 2021;10:401\u0026ndash;20.\u003c/li\u003e\n\u003cli\u003eBoychuk Duchscher JE. Out in the Real World: Newly Graduated Nurses in Acute-care Speak Out. JONA: The Journal of Nursing Administration. 2001;31.\u003c/li\u003e\n\u003cli\u003eAl-Ali NM, Al Faouri I, Al-Niarat TF. The impact of training program on nurses\u0026rsquo; attitudes toward workplace violence in Jordan. Applied Nursing Research. 2016;30:83\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eCicolini G, Comparcini D, Simonetti V. Workplace empowerment and nurses\u0026rsquo; job satisfaction: a systematic literature review. J Nurs Manag. 2013;22:855\u0026ndash;71.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1: Background characteristics of the study participants (n= 379)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003en (%)/mean (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eDemographic variables\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (mean), years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e27.73 (4.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e89 (23.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e25 - 29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e205 (54.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge; 30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e85 (22.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e53 (13.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e326 (86.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDegree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eDiploma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e131 (34.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eBachelor\u0026rsquo;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e163 (43.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eMaster\u0026rsquo;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e85 (22.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonthly income, BDT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 20000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e82 (21.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e20000 - 30000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e225 (59.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt; 30000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e72 (19.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eCurrent smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e61 (16.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003ePast smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e52 (13.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eNever smoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e266 (70.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOccupational variables\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eJob types\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eGovernment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e202 (53.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e177 (46.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional titles\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eStaff nurse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e366 (96.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eIn-charge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e13 (3.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eReceived timely salary\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e47 (12.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e332 (87.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHad accommodation facilities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e297 (78.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e82 (21.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHad sufficient equipment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e204 (53.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e175 (46.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHave rewards for good works\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e313 (82.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e66 (17.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHave training against violence\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e296 (78.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.286384976525824%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.713615023474176%\" valign=\"top\"\u003e\n \u003cp\u003e83 (21.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eFootnote: SD: standard deviation, BDT: Bangladeshi Taka\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: TI scores across demographic and occupational variables\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"81%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.31313131313131%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"68.68686868686869%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTurnover intention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.776119402985074%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u0026nbsp;\u003c/strong\u003e\u0026plusmn;\u003cstrong\u003e\u0026nbsp;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.850746268656717%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eF/t value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.37313432835821%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eDemographic variables\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e15.69 \u0026plusmn; 4.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.453\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003e25 - 29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e16.87 \u0026plusmn; 4.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge; 30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e16.39 \u0026plusmn; 3.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e15.50 \u0026plusmn; 4.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.453\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e16.02 \u0026plusmn; 4.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDegree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eDiploma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e15.26 \u0026plusmn; 4.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e3.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.036\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003eB.Sc.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e15.99 \u0026plusmn; 4.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003eM.Sc.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e16.92 \u0026plusmn; 4.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonthly income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 20000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e16.34 (4.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.558\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003e2000 - 30000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e15.94 (4.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt; 30000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e15.53 (4.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eCurrent smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e17.54 \u0026plusmn; 5.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e4.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" rowspan=\"3\" valign=\"top\"\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 width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003ePast smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e15.15 \u0026plusmn; 3.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003eNever smoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e15.15 \u0026plusmn; 4.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOccupational variables\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eJob types\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eGovernment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e15.76 \u0026plusmn; 4.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e-0.86\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.392\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e16.17 \u0026plusmn; 4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional titles\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eStaff nurse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e16.07 \u0026plusmn; 4.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e-2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003eIn-charge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e12.54 \u0026plusmn; 4.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGet timely payment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e18.68 \u0026plusmn; 4.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e-4.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e15.56 \u0026plusmn; 4.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHave accommodation facilities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e16.20 \u0026plusmn; 4.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e-2.03\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.043\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e15.04 \u0026plusmn; 4.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHave sufficient equipment \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e16.61 \u0026plusmn; 4.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e-3.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e15.18 \u0026plusmn; 4.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHave rewards for good works\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e16.30 \u0026plusmn; 4.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003e-3.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e14.27 \u0026plusmn; 4.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHave training against violence\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.632653061224488%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.612244897959183%\" valign=\"top\"\u003e\n \u003cp\u003e16.57 \u0026plusmn; 4.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e-5.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.346938775510203%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.81967213114754%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.18032786885246%\" valign=\"top\"\u003e\n \u003cp\u003e13.76 \u0026plusmn; 4.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eFootnotes: SD: Standard deviation, TI: turnover intention \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Descriptive statistics of SNAQ-9 and TIS-6\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.54882154882155%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eScales\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.023569023569024%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.993265993265993%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.54882154882155%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMinimum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.885521885521886%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaximum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.54882154882155%\" valign=\"top\"\u003e\n \u003cp\u003eSNAQ-9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.023569023569024%\" valign=\"top\"\u003e\n \u003cp\u003e15.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.993265993265993%\" valign=\"top\"\u003e\n \u003cp\u003e4.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.54882154882155%\" valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.885521885521886%\" valign=\"top\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.54882154882155%\" valign=\"top\"\u003e\n \u003cp\u003eTIS-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.023569023569024%\" valign=\"top\"\u003e\n \u003cp\u003e17.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.993265993265993%\" valign=\"top\"\u003e\n \u003cp\u003e7.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.54882154882155%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.885521885521886%\" valign=\"top\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eFootnotes: SNAQ-9: Short Negative Acts Questionnaire-9, TIS-6: Turnover Intention Scale-6, SD: Standard deviation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Multiple linear regression: adjusted association of WPB, demographic, and occupational variables with TI\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted \u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.401349072512645%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50.490196078431374%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"49.509803921568626%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLCI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWPB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eDemographic variables\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.32040472175379%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003e25 \u0026ndash; 29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e-0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e0.409\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge; 30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e-0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e2.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e0.381\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.32040472175379%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e-0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e0.358\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDegree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eDiploma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e-1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e-2.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e-0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eB.Sc.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e-0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e-1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eM.Sc.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.32040472175379%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonthly income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 20000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.32040472175379%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003e2000 - 30000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e-0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt; 30000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e-0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e-1.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e0.595\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eCurrent smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e2.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003ePast smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e-0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e-1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e0.721\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eNever smoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.32040472175379%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOccupational variables\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eJob types\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eGovernment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.32040472175379%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional titles\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eStaff nurse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e3.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e5.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eIn-charge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.32040472175379%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGet timely payment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e2.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.32040472175379%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHave accommodation facilities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e-0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e0.548\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.32040472175379%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHave sufficient equipment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e-0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.32040472175379%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHave rewards for good works\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e-0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.32040472175379%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHave training against violence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.898819561551434%\" valign=\"top\"\u003e\n \u003cp\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.36930860033727%\" valign=\"top\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.032040472175378%\" valign=\"top\"\u003e\n \u003cp\u003e2.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.020236087689714%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.679595278246207%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"70.32040472175379%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eReference\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eFootnotes:\u003cem\u003e\u0026nbsp;\u0026beta;\u003c/em\u003e: beta coefficient, WPB: workplace bullying, TI: turnover intention \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5: Predictive models for the TI\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"595\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBlock 1 (\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBlock 2\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBlock 3 (\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e-0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e-0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e-0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003eDegree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e-0.84*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e-0.97**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e-0.80**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003eMonthly income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e-0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e-0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003eSmoking status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003eJob types\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e1.45*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e1.34*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003eProfessional titles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e3.63**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e3.62**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003eGet timely payment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e2.78***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e1.94**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003eHave accommodation facilities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003eHave sufficient equipment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003eHave rewards for good works\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003eHave training against violence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e2.09***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e1.47**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003eWPB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e0.26***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e6.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e12.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.93288590604027%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;R\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.630872483221477%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.63758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.798657718120804%\" valign=\"top\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e* p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001\u003c/p\u003e\n\u003cp\u003eFootnotes:\u003cem\u003e\u0026nbsp;\u0026beta;\u003c/em\u003e: beta coefficient, WPB: workplace bullying, TI: turnover intention \u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Male Nurse, workplace, healthcare, bullying, turnover intention, Bangladesh.","lastPublishedDoi":"10.21203/rs.3.rs-3542653/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3542653/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eWorkplace bullying (WPB) and nurses’ turnover intention (TI) are important challenges in the healthcare sector, particularly in developing countries like Bangladesh. Understanding this relationship is crucial for developing targeted interventions to improve retention and well-being among male nurses in Bangladesh. Thus, this study aimed to explore the relationship between WPB and TI among Bangladeshi male nurses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod: \u003c/strong\u003eWe conducted a cross-sectional study among 379 Bangladeshi registered male nurses between April 26 and July 10, 2021. The study sites included indoor or outdoor settings where nurses provide healthcare. We used the Short Negative Acts Questionnaire-9 (S-NAQ-9) to measure WPB and the Turnover Intention Scale-6 (TIS-6) to assess TI. We performed a multiple linear regression model to explore the association of WPB and other variables with TI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe study participants were predominantly young male nurses, with a significant proportion employed in urban settings and holding a Bachelor of Science (B.Sc.) degree. The study found a significant positive association between WPB and TI, suggesting that higher levels of WPB were related to increased TI. Likewise, some other factors such as educational degree, smoking status, job types, professional titles, timely payment, and violence-related training showed significant associations with TI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThis study highlights the need for focused interventions to reduce WPB and enhance working conditions for male nurses in Bangladesh. Addressing WPB, as well as improving work satisfaction through targeted initiatives, is critical for reducing TI among this demographic.\u003c/p\u003e","manuscriptTitle":"Workplace bullying and turnover intention among male nurses: A cross-sectional study in Bangladesh","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-05 14:53:44","doi":"10.21203/rs.3.rs-3542653/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"de6d3161-9e45-4cac-8772-1c71247cd23a","owner":[],"postedDate":"April 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-04T05:15:33+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-05 14:53:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3542653","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3542653","identity":"rs-3542653","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}