1- Data

2- Experimental design, materials and methods

References

Abstract

This data article provided additional data related to the research article entitled “Brain structural abnormalities in emotional regulation and sensory processing regions associated with anxious depression” Peng et al.,2019. Correlation analyses were conducted for clinical information (HAMD total, anxiety/somatization scores, HAMA total and illness duration) and identified regional gray matter volumes in all patients with anxious depression and non-anxious depression. More detailed correlation analysis was applied for each item of anxiety factor and reginal gray matter volumes to find which items were more associated with structural alterations in patients. Data showed that mean values of regional gray matter volumes in left postcentral gyrus (PCG) were positively associated with HAMD total and anxiety factor scores in anxious depression group. More detailed correlation analysis considering each item of anxiety factor revealed that, item 10 (psychic anxiety) and Item15 (hypochondriasis) were most significantly and positively associated with regional gray matter volumes in left PCG in anxious group. While HAMA scores and illness duration showed no significant correlation with any regional gray matter volume in both patient groups. Sample size matched groups were selected to explore possible replicability of imaging results. It revealed that different gray matter volumes in right inferior frontal gyrus were most robust findings among three groups. And anxious group had larger gray matter volumes in left PCG than non-anxious depression, despite of not survived after multiple comparisons corrections.

Data

This Data in Brief provided detailed results of correlation analyses between clinical characteristics (HAMD total, anxiety/somatization score, HAMA total and illness duration) and extracted mean values of regional gray matter volumes in whole anxious depression and non-anxious depression groups (Tables 1e5) [1]. The raw individual values of correlation analyses for each patient were listed in Tables 8e9 In addition, this data article presented imaging results for matched groups (Tables 6e7) [1].

Data

According to Table 1, four hundred and ten (410) copies of questionnaire were administered to the employees of the selected Universities guesthouses in southwest, Nigeria. Three hundred and twenty-four (324) were returned and usable, which represented 79%, while the remaining eighty-six (86) were not returned, thus representing 21% of the total questionnaire administered. Based on the usable copies of questionnaire, Tables 2-5 and Figures 1-4 revealed the demographic profile of the respondents according to gender, age, marital status and educational qualification. The demographic data of the respondents revealed that 193 (59.6%) were male, while the female respondents were 131 (40.4%). Though, male respondents were more than the female respondents, but the opinion of both genders were adequately represented. Based on Table 3, ages 18-29 years were 184 (56.8%), ages between 30-39 were 98 (30.2%), and 42 (13.0%) were the respondents between ages 40-49 years. From Table 4, the singles among the respondents were 215 (66.4%), while the married were 109 (33.6%) of the total respondents. According to Table 5, 121 (37.3%) of the respondents were Senior Secondary School Certificate Examination (SSCE) holders, 127 (39.2%) of the respondents were Ordinary National Diploma (OND) and National Certificate in Education (NCE) certificate holders. Higher National Diploma (HND) and first degree holders from the University among the respondents were 68 (21.0%), Masters and Professional certificate holders among the respondents were 6 (1.9%), while 2 (0.6%) were Doctor of philosophy (Ph.D) holders among the respondents. The descriptive statistics evaluating the dimensions of transformational and transactional leadership styles and employees’ job satisfaction are as shown in Tables 6-12. In line with Table 6, 146 (45.1%) of the respondents strongly agree, 73 (22.5%) agree, 35 (10.7%) partially agree, 9 (2.8%) partially disagree, 53 (16.4%) disagree, and 8 (2.5%) strongly disagree, that idealised influence of their leader will have positive effect on their job satisfaction. According to Table 7, 134 (41.4%) strongly agree, 79(24.4%) agree, and 43 (13.3%) partially agree that the inspirational motivation of their leader will boost their job satisfaction, whereas, 20 (6.2%) partially disagree, 42 (13.0%) disagree, and 6 (1.9%) strongly disagree that inspirational motivation of the leader will boost their job satisfaction. In line with Table 8, 133 (41.0%) strongly agree, 72 (22.2%) agree, and 49 (15.1%) partially agree that their superior intellectual stimulation will improve their job satisfaction, while 8 (2.5%), partially disagree 48 (14.8%) disagree, and 14 (4.3%) strongly disagree that intellectual stimulation of their superior will improve their job satisfaction.

Introduction

Transformational leadership is no longer a new topic in leadership and change management but despite the attention paid to the practice, organisations still fail to understand and explain how leaders can encourage, inspire and motivate employees to innovate and create change that will help grow and shape the future success of the organisations. The theoretical, methodological as well as practical gaps churned out from extant literature are more applicable to the developed and transitional economies. Unfortunately, studies focusing on the contextual and organizational variables in developing economies, such as Nigeria, are still scarce. Hence, this paper adds to knowledge in the area of leadership research as it investigates leadership transformational attributes on employee satisfaction and engagement across hierarchical levels in Nigeria. This research broadens the scope of previous research and provides a more detailed examination of transformational leadership attributes by exploring the five traits –- Idealized influence (II), Inspirational motivation (IM), Intellectual stimulation (IS), Individualized consideration (IC) and Attributed charisma (AC) as presented in Table 1.

South Korea is one of the countries with the longest working hours in the Organization for Economic Cooperation and Development (OECD) countries. According to the OECD annual report, the OECD Employment Outlook 2017, the average number of working hours in South Korea in 2016 was 2069 h, the second highest rate after Mexico [1]. The average annual working hours in the OECD 35 countries is 1764 h, and Korean workers are working 305 more hours than the average number of worked by workers in all OECD countries. There are studies on the effects of long hours of work on health, and most studies report that long hours of work negatively affect workers’ health [2]. Long working hours can be a risk factor of mental illness as well as cardiovascular disease [3, 4]. On the other hand, previous research suggests that job stress increases during long working hours [5], and job stress is associated with depressive symptoms [6, 7]. People with high job demands due to excessive workload or time pressure had twice the risk of major depression or generalized anxiety disorder compared to those with low job demands [6]. Also, Job stress due to high effort and low reward has had a negative impact on mental health [7]. However, there are few studies that explored the role of job stress factors between long working hours and depressive symptoms [8]. The first purpose of this study is to evaluate the association of long working hours on depressive symptoms. The second purpose is to determine the magnitude of job stress factors explaining the pathways of long working hours affecting depressive symptoms, taking into account job stress as mediator. Figure 1 shows an outline of the relationship between working hours and depressive symptoms. Socioeconomic position and irregular working time were seen as confounders. Job stress is considered as a mediator because, as work hours increase, the hours for workers to be exposed to job stress become longer and stronger, and the characteristics of the job needing long or short working hours could be related to job stress.

Insomnia is the most common sleep disorder, having become one of the foremost health concerns for workers internationally. Over the previous 30 years, a large number of epidemiological studies have investigated and reported on the correlation between insomnia or sleep disturbance and stressors in the workplace. Knudsen [16] investigated 1715 full-time employees, identifying a close relationship between work overload and insomnia, while role conflict, as well as job latitude, was correlated with difficulty in maintaining sleep. A further investigation [25] involving 1786 workers from 8 electrical appliance factories, applying both DCS and ERI on the same population, illustrated the significant association between job stress and insomnia symptoms. Comparable conclusions have also been drawn in other research [13, 14, 26, 30, 31]. Nevertheless, the distinctions between these findings were readily apparent, while in certain studies, the estimated confidence intervals of effects were too wide to draw meaningful conclusions. Moreover, an array of instruments was adopted for measuring exposure and results among the literature, with the majority of studies being of a cross-sectional nature, where a sole study is believed to lack strength in terms of validity and dependability. In this research, we undertook a comprehensive search and analysis of the literature concerned with the correlation between insomnia symptoms measured by scales and job stress variables, as a means of producing evidence with greater reliability. Additionally, we used meta-analyses to summarize the varied literature from Europe and Asia that was both prospective and cross-sectional by design, accounting for the deficiencies in the breadth of evidence within previous research.

Improving the occupational health and well-being of customer contact employees (CCEs) to provide customers with better service is becoming an increasingly important priority for many firms. The demanding boundary spanning role of CCEs has long been recognized in the marketing literature (e.g., Kim et al. 2012; Singh 1998, 2000). CCEs are ‘‘at the heart of service provision’’ (Surprenant and Solomon 1987) because they greatly influence customers’ perceptions of service quality through the key components of relatedness, assurance, tangibles, empathy, and reliability (An and Noh 2009; Parasuraman et al. 1985). Customers’ service experiences are therefore largely contingent upon CCEs’ job-related attitudes and behaviors (Kim et al. 2012; Jeon 2016; Bitner et al. 1994). Accordingly, researchers continue to highlight the need to identify effective managerial interventions that promote CCE occupational health and well-being (Gilbert et al. 2011; Rayburn 2014; Smith et al. 2012) and improve customer service experiences (Ostrom et al. 2010; Schneider and Bowen 2010). The current research draws on equity theory to assess the relative influence of alternative types of rewarding on CCE job stress and work affect. Job stress—the sense of time pressure, anxiety, and worry associated with jobrelated activities that can lead to strain, hostility, and depression (Motowidlo et al. 1986)—has a particularly detrimental influence on CCEs’ ability to provide highquality service that satisfies customers (Teng and Liu 2014; Kim et al. 2012, Babakus et al. 2009; Varca 1999). Research studies indicate that insufficient resource allocation (Gillespie et al. 2001) and predominantly cost-driven approaches to service provision (Marinova et al. 2008) increase employee job stress. Such work-related stress has a pervasive influence on CCE occupational health and performance (Fisk and Neville 2011). In contrast, effective work design (Rayburn 2014), human resource management (Schneider and Bowen 1993), and developmental interventions (Ellinger et al. 2008; Elmadag˘ et al. 2008) all favorably influence service employee work affect. Researchers therefore contend that job stress must be effectively mitigated to improve service worker attitudes that influence the quality of service provision (Singh 2000; Taris 2006). However, most examinations of CCE job stress are focused on the causes and outcomes of job stress (e.g., Teng and Liu 2014; Johnson and Sohi 2014; Varca 1999), rather than on identifying remedies.

A great amount of carbon is emitted directly or indirectly into the atmosphere by construction sections (Yusof et al. 2016a; Esmaeilifar et al. 2015). The high amount of carbon dioxide (CO2) in the atmosphere has been thought to raise an urgent problem. This has worsened environmental dangers (Zailani et al. 2014). One of main greenhouse emitters is the construction industry, which has been criticised for violating the rules of carbon emission management (Wang 2014; Yusof et al. 2016b). Concerning an increasing pressure on the dangers related to the climate change, construction companies should advocate cutting back on the carbon emission if they intend to achieve emission controls (Sharrard et al. 2007; Hajibabai et al. 2011; Wong et al. 2013). Implementing low carbon waste (LCW) practices is a vital solution for reducing waste caused by construction activities (Yusof et al. 2017; Begum et al. 2006). Therefore, implementing LCW practices is of such importance that there has been an increased attention towards it in research and practices recently carried out on construction (Ding et al. 2016; Vieira et al. 2016). A large amount of research has been undertaken on sustainable construction in terms of the infuence of the rapid growth of the infrastructure on the environment (Shen and Zhang 2002; Zhang et al. 2000), consideration of the fow of waste and construction site control (Tam et al. 2007; Shen et al. 2004), examination of the sustainable operation of construction sites, and contractor performances (Liyin et al. 2006; Shen and Tam 2002; Shen et al. 2005; Tam et al. 2006). These studies demonstrated the negative impacts of construction activities on the environment, sought proper practices to reduce site waste and emission generation, and showed the positive relationship between implementing LCW practices and the environmental performance of construction companies. However, the principle of LCW practices irrespective of the substantial advantages has still been controversial with regards to the well-being of humans (Shen et al. 2004). Stress in the workplace or job stress (Bergerman et al. 2009) is described as the response people may have when ‘‘presented with work demands and pressures that are not matched to their knowledge and abilities, and which challenge their ability to cope’’ (Leka et al. 2003, p. 3). The volume of work required of an employee and the perception that there is too much to do during a given period is listed as the most common sources of stress (Torres 2016). Research supports the direct efect of workload level on specifc forms of workplace deviance, such as absenteeism (Bakker et al. 2000), as well as on the job dissatisfaction (Rössler 2012), and turnover (Torres 2016). There is a potentially persistent discrepancy between LCW practices and job satisfaction from the workload and job demand perspectives. Besides completing their own tasks, site managers might need to work hard overtime to fulfll the demands of the LCW practices. Site managers’ job stress is likely to rise due to such issues as process reconfguration, infrastructure initiation, and redesigned jobs (Haynes and Love 2004; Liu and Low 2011; Gatti et al. 2010; Leung et al. 2009), which could result in job dissatisfaction (Bohle et al. 2011; Macklin et al. 2006; Lee 1995). As an important issue, particularly to the construction industry in Malaysia, job satisfaction could be mentioned due to the high rate of employee turnover (Ismail et al. 2012). Thus, job stress may be one of the major issues in implementing LCW practices. However, little, if any, research has been undertaken on the impacts of LCW management activities on site manager’s job satisfaction and job stress. The current research intends to resolve this gap through the efect of LCW management activities on job satisfaction via job stress. The results are expected to be useful for site managers whose job appears to be one of the most stressful careers.

Occupational stress occurs during the performance of one’s duties and is defined as harmful physical and emotional responses that occur when job requirements do not match a worker’s capabilities, resources, or demands [1]. Therefore, although there may be some differences in occupational stress levels, depending on types of work required of individuals, all humans who work experience physiological effects arising from stress. As workers’ health problems, such as industrial incidents and occupational diseases, have recently become important, occupational stress, which may also damage workers’ health, has also received attention as a risk factor. Mental-health problems, such as depression [2] and sleep disorders [3], as well as physical illnesses, such as cardiovascular [4] and musculoskeletal diseases [5], are also known to be associated with occupational stress. In particular, mood disorders, such as depression, are common in adult populations, including workers. In Europe, the one-year prevalence of depression is 6.9% [6]. In South Korea, the estimated lifetime prevalence and one-year prevalence of major depression is 5.0 and 1.5%, respectively, which indicates that the number of people who have experienced depression during the previous year is estimated to reach 610,000. It has also been reported that 15.4% of adults have seriously considered suicide more than once in their lifetime [7]. Therefore, there has been a growing interest in occupational stress and depression, and many studies on this topic have been conducted since the Korean Occupational Stress Scale was developed. Increases in relationship conflicts and problems related to organizational culture have been reported to be associated with a higher risk of depression, and 1 out of 10 workers has a high likelihood of suffering from depression [8]. Additionally, a variety of studies have found that among small and medium enterprise workers, male white-collar workers in automobile companies, immigrant workers, female workers in traditional markets, and dentists have higher occupational stress, which is associated with a higher risk of depressive symptoms [9–13]. However, none of those studies have revealed causal relationships between their independent and dependent variables due to the limitations of the studies’ cross-sectional designs; thus, the need for longitudinal studies is raised frequently. Although studies have used explanatory models to examine occupational stress [14, 15], these studies are difficult to be applied straightforwardly in Korea on account of not targeting Korean workers and without considering Korean occupational climate. Therefore, longitudinal study using Korean occupational stress scale is needed. This prospective study was intended to investigate whether changes in (i.e., greater or less) occupational stress significantly affects the risk for developing depressive symptom in addition to that occupational stress influences the risk for depression. The results of this study can be used: (a) to emphasize the importance of occupational stress management in the prevention of mental-illnesses among workers, (b) as evidence for reducing the prevalence of depression through workers’ effective stress management, and (c) as knowledge to help improve workers’ health and corporate productivity more efficiently when selecting and managing employees who are vulnerable to depression.

Job stress is a topic of active research because a stressed-workforce can be a burden to organizational performance. Having said so, the cost of workplace stress includes but is not limited to reduced productivity (Singh, 2000), absenteeism (Gray, 2007), compensation claims (Keegel et al., 2009) and direct medical expenses (Guthrie et al., 2010). Job stress can also discourage employees’ intention to stay (Vong and Tang, 2017). Unlike other types of stress-induced managerial costs, which are specific measurable expenditures, the cost of losing an invaluable employee cannot be easily measured in quantitative terms. Managing workplace stress is therefore important for business organizations not only because money matters but also because retaining talents is the prerequisite condition to achieving long term corporate success. This is even truer in a tight labor market in which skilled and professional workers always have the upper hand to choose between multiple employment offers. Organizations that fail to address the problem of workplace stress may find themselves on the defensive when it comes to attracting and retaining talents. For these reasons, academicians and practitioners alike have strived to identify those aspects of the work environment such as work overload, management style and role ambiguity that are the probable sources of job stress, hence to tackle the problem at its root. While it is absolutely appropriate and necessary to combat the stress problem by resolving the stressors (i.e. the antecedents of job stress), job stress can have multiple sources so much so that it is intuitively impossible to eradicate job stress by simply attending to the stressors. Because of this, it is equally important for organizations to come up with effective interventions that can mitigate job stress’ negative consequences at the workplace. This means to explore and identify those managerial actions that can buffer in between job stress and its accompanying negative consequences. In this perspective, literature abounds with studies that have identified different forms of interventions likely to moderate job stress’ influences at the workplace. These interventions include employee characteristics such as age (Mauno et al., 2013), gender (Jayathilaka and Subasinghe, 2016), organizational rank (Kim et al., 2009) and organizational tenure (Jayathilaka and Subasinghe, 2016; Ciobot
a, 2013) as well as managerial actions and programs such as social support (Rathi and Barath, 2013), supervisory support (Karatepe, 2010), workplace initiatives (Wickramasinghe, 2010), managerial orientations (Sumrall and Sebastianelli, 1999) and organizational resources (Marwat et al., 2012).

The survey conducted by WHO on employee population of about 1,900 million people regarding worldwide risk of problems related to their work showed that there are 160 million employees experiencing illness. There are 8 percent of them who have occupational stress, which is the same as Thai employees who suffer stress and anxiety the most (32.24 percent) and were in working age of 26-30 years in 2014[1]. The occupational stress is a disadvantage resulting in the loss of working potential and in mental health illnesses[1]. The development of Thai society focuses on industrial society under globalization, which has become the turning point of society, with economic changes in Thailand including Thai immigrant employees[2] under AEC policies[3]. A survey disclosed that Thai immigrant employees still tended to work in the same regions, rather than in different regions[4, 5]. Some studies explained that migrants who were employees need to adapt themselves to new environment while leaving their aging parents to live alone in rural areas. When their aging parents have illnesses, it leads to anxiety to them[6]. Several studies found that poor working conditions, job insecurity, poor occupation, great distances, and inconvenient transportation were associated with occupational stress, anxiety, and depression[7-10]. For example, some paper in China concluded that time period, wages, family support, housing conditions, age, and job characteristics were related to mental health[11], and job demands (such as, carrying heavy loads, an awkward posture, and psychological demands), decision latitude, (such as, skill variety and job control) and support (such as, supervisory control and the safety climate) were all linked to both mental and physical health issues[12, 13-18], high job responsibility[19], or different occupational characteristics, such as job stress among Thai farm worker[20], poor wages associated with job stress and pressure[21] including great distance[17, 21]. In contradiction, some immigrant employees had conflicts between work and rearing their family (i.e. children, spouse, and/or aging parent). This became a psychosocial problem and led to poor mental health[22]. For example, male migrants who were separated from family always suffered from mental health, fear, anxiety, and depression [23]. These are also found among females who were working as maids[24]. That is to say, job conditions were important factor that contributed to mental health[17]. It is important and necessary to compare the causal relationships and job stress among employees between those who were supporting their aging parents to the other group who were not. As a result, operational definitions consisted of, first, working conditions, means questions about exploitation, job characteristics, working environment, and workloads, which have effected job stress; second, supporting aging parents who are older than 60 years old and live in their original province; third, wages represent the total incomes from both part-time and full-time jobs in Thai baht/month (1 baht ≈ $35); fourth, employees are rural-urban migrants who work in Bangkok (n ¼ 352 cases) and Nonthaburi provinces (n ¼ 248 cases), whose original provinces are neither of these provinces, fifth, job stress is pressure, occupational stress, burnout, job control, job-confliction-related to poor mental health and job potency, and finally, the distance traveled between their home town and the workplace in kilometers.

1. Introduction

The weakest link in a security system is most often the human factor (Schneier, 2004). It is widely accepted, and well documented, that cyber security breaches cannot be prevented through the implementation of solely technical solutions (Furnell et al., 2006, Parsons et al., 2014, Schultz, 2005). This has been supported by security and incident reports, international security standards, and peer reviewed literature. For example, IBM Global Technology Services (2015) determined that breaches were often unintentional and that over 95% were the result of human error. Standards Australia Limited (2015) released a code of practice outlining information security controls, which recommends an emphasis on human resource security, thereby recognising the liability of the human in information security. In recent years there has been an increased focus on better understanding the characteristics of employees and how they can affect an organisation’s information security (McCormac et al., 2017c, Shropshire et al., 2006). Research has shown that organisations may reduce the risk of a security breach by 45% to 70% through improvements to employee behaviour (Wombat Security Technologies and Aberdeen Group, 2015). In line with this, the current study examined the relationships between resilience, job stress and Information Security Awareness (ISA). Essentially, it is likely that employees who are more resilient may be better at coping with job stress, and may therefore have better ISA. Throughout the following sections we introduce the main constructs considered in this study, namely, resilience, job stress and ISA.

1.1. Resilience

There is no agreement in the literature regarding the definition of the term resilience. This is primarily because it has been studied in many disciplines, including psychology, sociology, anthropology, biology, medicine, education and management. Resilience has been described a trait, process, capacity or outcome (Kossek and Perrigino, 2016, Southwick et al., 2014). For the purposes of this study, we have adopted the definition provided by the American Psychological Association (2014), which states that resilience is “the process of adapting well in the face of adversity, trauma, tragedy, threats or even significant sources of stress” (p.2). This definition suggests that resilience, as a process, is strongly influenced by our interactions within our environments. Resilience involves thoughts, behaviours and actions. Therefore, resilience can be learnt and developed, and it can also change and evolve (American Psychological Association, 2014).

Stress at work is associated with significant economic and human costs, as it leads to an increase in increasing absenteeism, decrease in job satisfaction, and deterioration in the health of workers (Leka and Jain, 2010). Occupational stress is a known health risk for a range of psychological, behavioral, and medical disorders and diseases (Quick and Henderson, 2016). There is a tendency to neglect the physical environmental factors despite the fact that such factors can influence the worker not only physically, but also psycho-socially (Levi, 1984). Contemporary research on stress in the work environment typically focuses on psychosocial factors that affect job performance, strain and employee health, and does not address the issues of work-related stress and the physical work environment in which the work is performed (Vischer, 2007). Research suggests that the characteristics of the physical environment of the workplace do have a marked and measureable impact upon a worker’s well-being and behavior (Hassard and Cox, 2017). Apart from the working environment, mental stress is also most heavily concentrated among workers with lower income, lower education, fewer skills, and less prestigious jobs than their peers (NIOSH, 1988). Certain population sub-groups are at higher risk of mental disorders because of their greater exposure and vulnerability to unfavorable social, economic, and environmental circumstances (WHO, 2014). Quarry workers constitute such a vulnerable group that suffers from a poor socio-economic condition (Mathur, 2015) and is constantly exposed to potentially dangerous environments (Pule, 2011). Quarry workers in India face many different kinds of abuse to their socio-economic status, and physical health, apart from the risk of exploitation by third persons like doctors and mine contractors (Ahmad, 2015), which may adversely affect their mental health. However, despite the miners being prone to such vulnerability, there is very limited research information on mental health issues concerning miners (McLean, 2011), and in fact, no such research is available at all in India. The state of Rajasthan is producing about 90 percent of the sandstone in India (IBM, 2015), with over 2.5 million mine workers engaged in this task (Dutt, 2005). A majority of these mines are in the unorganized sector (NIMH, 2011). All the people who work in mines have a high potential of exposure to various physical, chemical, mechanical, biological and psychosocial risks (Pule, 2011). Irrespective of whether mining is done over the ground or below the sub-surface, extreme physical work conditions, stemming from, for example, temperature and humidity, lead to stress (Szabo et al., 1983). However, mining, if undertaken in the organized sector, ensures safe and healthy working conditions (Sishodiya and Guha, 2013). On the other hand, working conditions in stone quarries, which are largely of an unorganized nature, are poor due to non-compliance with health and safety standards (NIMH, 2011). Thus, mining in India represents a highly exploitative situation, with all kinds of violations of the law and breach of human rights (Dutt, 2005).

Job stress is usually defined as an adverse relationship of person and work environment in which work tasks exceed an individual’s knowledge, skills, or ability, inhibiting one’s behavior to cope and triggering a lot of psychological and physical issues (Lazarus and Folkman, 1984). Due to the nature of their jobs, the individuals working in healthcare professions are exposed to chronically high levels of stress, making them particularly susceptible to job stress-related mental health problems (McVicar, 2003; Chou et al., 2014). Many studies have shown that the long-term stressful work conditions lead to depressive symptoms (Ahola and Hakanen, 2007). Moreover, the researchers have used stress paradigms as the model of depression for a long time (Willner, 1997). Depression is a common mental disorder among healthcare workers with complex origins that is linked with considerable morbidity and mortality (Kiecolt-Glaser and Glaser, 2002; Cheung and Yip 2015; Wurm et al., 2016). For example, a study of 3474 nurses showed that 38% of nurses had depressive symptoms, and they reported tension in nurse–patient relationships and work load as the main reasons for those symptoms (Gong et al., 2014). A series of consequences may be caused by depression, including sleep problems, physical illness, and even impaired cognitive performance (Asarnow et al., 2013; Clarke et al., 2009; Rock et al., 2014). Further, depression not only endangers the health and well-being of occupational staff themselves, but also is associated with lower job performance and work productivity (Lerner and Henke, 2008). The projection for depression has become the second most common cause of disability by 2020 (Moussavi et al., 2007). Therefore, it is necessary to understand the relevant risk factors and susceptibility of depression. Although many risk factors for depression have been identified, the underlying mechanisms for depression are still unknown. Both environmental factors, such as stressful life events (SLEs), and genetic predisposition play an important role in the etiology of depression (Levinson, 2006), highlighting the importance of gene–environment interactions. Brain derived neurotrophic factor (BDNF), an important member of the neurotrophin family, is a protein with a broad range of activities in the central nervous system, such as the regulation of synaptic function, synaptic plasticity and the promotion of neuronal survival (Hyman et al., 1991;Kowianski et al., 2017), suggesting its implication for synaptogenesis and neurogenesis, especially for hippocampal neurogenesis (Kowianski et al., 2017). Many studies have shown that BDNF plays a central role in the neuropathology of depression by modulating the neuroplastic response (Brunoni et al., 2008; Jiang et al., 2013). The neurotrophin hypothesis of depression, one of leading hypotheses to explain the etiology and clinical course of this disorder, proposes that depression results from stress-induced reduction of BDNF expression levels while increases in BDNF levels could cause an antidepressant effect (Martinowich et al., 2007; Molendijk et al., 2014). Decreased brain levels of BDNF could contribute to cell loss and neuronal atrophy in the hippocampus and prefrontal cortex in depressed subjects (Duman and Monteggia, 2006). A meta-analyses study found reduced serum BDNF levels in major depression patients, indicating peripheral BDNF alteration in depression (Bocchio-Chiavetto et al., 2010).