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 Table of Contents  
Year : 2022  |  Volume : 5  |  Issue : 3  |  Page : 138-145

The effect of resilience indicators on the job stress level among nurses: A predictor study

1 Department of Occupational Health Engineering, Faculty of Health, Shoushtar University of Medical Sciences, Shushtar, Iran
2 Department of Occupational Health Engineering, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
3 Occupational Health Engineering, Student Research Committee, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

Date of Submission05-Jan-2022
Date of Decision23-Jun-2022
Date of Acceptance14-Jul-2022
Date of Web Publication9-Aug-2022

Correspondence Address:
Davood Afshari
Department of Occupational Health, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/shb.shb_4_22

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Introduction: Resilience is one of the competencies that enable nurses to adapt to stressful risk factors at work and demonstrate a healthy and stable psychological performance. The present study aimed to investigate the predictive role of resilience on job stress among Iranian nurses. Methods: The current cross-sectional study was conducted in Ahvaz, Iran, with participation of 200 nurses in May 2019. Participants were recruited via stratified random sampling. The resilience indicators and job stress data were collected by the Connor–Davidson Resilience Scale and OSIPOW Job Stress Questionnaire. Results: The results showed a significant negative correlation between resilience and job stress (r = −0.824, P < 0.05). Similarly, a significant linear regression existed between job stress and resilience (β = −0.824, P < 0.05) in such a way that resilience predicted 67.9% of the job stress variance in the participants (R2 = 0.679). In addition, it was revealed that the multi-aspect model could significantly predict job stress based on linear resilience indicators (P < 0.05). Conclusion: The results indicated that resilience indicators have a significant relationship with job stress, and this relationship can be used to predict changes in job stress based on resilience. Therefore, it is strongly recommended that resilience improvement programs should be developed and implemented for nurses.

Keywords: Hospital, job stress, mental health, nurses, physical health, resilience

How to cite this article:
Rashnuodi P, Nourollahi-Darabad M, Afshari D, Shirali GA, Amiri A, Rotkhali E, Shabgard Z. The effect of resilience indicators on the job stress level among nurses: A predictor study. Asian J Soc Health Behav 2022;5:138-45

How to cite this URL:
Rashnuodi P, Nourollahi-Darabad M, Afshari D, Shirali GA, Amiri A, Rotkhali E, Shabgard Z. The effect of resilience indicators on the job stress level among nurses: A predictor study. Asian J Soc Health Behav [serial online] 2022 [cited 2023 Dec 3];5:138-45. Available from: http://www.healthandbehavior.com/text.asp?2022/5/3/138/353637

  Introduction Top

In modern societies, job stress is one of the main risk factors for occupational health among health-care personnel.[1] One definition of stress argues that it occurs when there is no balance between job requirements and one's capabilities.[2] Job stress is one of the main problems in social life and a new threat to the health of workforces in the world. According to the International Labor Organization, job stress is a well-known risk factor for workers' health.[3] Health and Safety Executive predicted the loss of 5.13 million workdays and ≤4 billion per year between 2007 and 2009 due to the damages caused by job stress.[4],[5] The results of an epidemiological study have shown that 75% of medical problems and issues are directly related to stress; therefore, stress can be blamed for significant costs incurred to the health-care system, low performance, and unacceptable efficiency.[6] In 1992, the UN declared job stress to be the disease of the 20th century.[7] The WHO predicted that mental diseases, including stress, will be the second most debilitating cause by 2020.[8]

Based on the pieces of research conducted in recent decades, mental factors and job stress in the work environment are not limited to a specific job despite the presence of other harmful factors. Stress risk factors can be found in almost every job to varying extents.[9] In this regard, nursing is a specialized and complicated profession that entails emergency management and, thereby, is considered one of the highly stressful and challenging jobs.[1],[7] In this regard, the results of the systematic review study have shown that the overall prevalence of job stress among nurses working in Iran is high (60%).[10]

Job stress in nursing brings about concerns about mental health, mental diseases, employees' performance disorder, and possible adverse effects on the attitudes and behavior of nurses.[11],[12] Among the risk factors of stress at work for nurses, one may refer to conflict with patients, interpersonal relationships with physicians and colleagues, receipt of poor support, high job demand, leadership and management style, lack of reward, rotating schedule, struggling with emotional needs of patients, overtime work, facing death, and no guarantee for successful treatment.[13],[14] According to the related studies conducted in this field, more stressors such as complicated diseases, decreased control, ambiguous jobs, understaffed wards, advanced technology, and competition among hospitals have been added to the list.[15] The repercussions of job stress for nurses and other experts in the health-care sector include mental disorders, poor mental health, alcohol and narcotic abuse, absenteeism, delay to attend the job, job depression, accidents at work, musculoskeletal disorders, decrease in one's ability to provide quality care, lack of concentration, inattention, memory disorders, and adverse effects on patients' safety.[15],[16] Given these scientific reasons, stress may create complicated conditions or unwanted events for nurses.[2]

Despite all these challenges, one way that enables nurses to self-adapt to their work environment with a healthy psychological performance is to improve their resilience to physical and mental risk factors. Resilient nurses learn to overcome their problems and find better approaches to fight stress in demanding work environments.[17] Resilient individuals seek methods to improve their capabilities and create flexible processes at all levels of organizational tensions.[18],[19] In fact, this concept has been referred to as a multidimensional feature that helps a person successfully tackle the challenges ahead and enhances protection against stressful situations.[20]

A surge in the interest in identifying the effect of resilience on health-care employees has come into play over the past decades. Based on the results of the studies, resilience is necessary for success in the nursing profession, and nurses should be able to overcome negative experiences in their work environment by promoting resilience.[20],[21] The results have shown that resilience is vital in health outcomes such as physical and mental health and job performance.[17],[22] It has been frequently recommended that resilience should get improved in nursing programs.[23] Some studies have indicated that the indices of resilience can affect job stress.[17],[23],[24] The mental health of nurses in improving the quality of health services is of great significance; moreover, job stress is one of the essential factors affecting the mental health of these people. Therefore, resilience as a coping strategy can help people, especially nurses, to control stress in their work environment. However, despite the importance of resilience and its relationship with the stress and health of nurses, this field of science has received little attention, especially in Iran. Consequently, the present study aimed to investigate the predictive role of resilience on job stress among Iranian nurses.

  Methods Top

Study design and participants

This cross-sectional study was conducted among nurses of Ahvaz educational hospitals for 1 month in May 2019. Ahvaz is the capital of Khuzestan, located in Southwest Iran. Ahvaz is the seventh most populous city in Iran, where there are 21 hospitals, 8 of which are university and educational. The inclusion criteria were at least 1 year of experience and having no chronic physical or mental illness by self-report.

Sample size estimation

The sample size was calculated by considering the 95% confidence interval and 80% test power. According to previous studies and considering the correlation r = 0.24 for resilience and job stress variables in Equation 1, the minimum required samples was 135 people. This study was completed by considering 200 samples as a statistical population in the educational hospitals of Ahvaz. Including five incomplete questionnaires, the number of samples in this study was 195 people.

Sampling procedure

Stratified random sampling was used to select the samples. In this way, first, the statistical population of nurses in Ahvaz teaching hospitals was determined. The total number of nurses in teaching hospitals was 3107. Next, the coefficient of each hospital was determined considering the population of nurses in each hospital to the total number of nurses in Ahvaz educational hospitals. The statistical population of nurses in each hospital was determined by multiplying the coefficient of each hospital in the statistical population (200 people). Simple random sampling was performed in each hospital.


Demographic questionnaire

The participants provided detailed information on a range of demographic items, including their age, height, weight, gender, exercise, education level, smoking, job status, marital status, ward, work schedule, and work experience.


The Persian version of Connor–Davidson Resilience Scale (CD-RISC) was employed to examine the resilience indices. This scale has been used and standardized in several studies. The validity and reliability of the Persian version of this questionnaire were assessed in a study by Mohammadian and Khodabakhsh Koulaie who reported that Cronbach's alpha coefficient equals 0.89 and 0.87, respectively.[25],[26] The questionnaire items are scored on a five-point Likert scale (completely wrong = 0, rarely = 1, sometimes = 2, mostly right = 3, and always right = 4). The total score of the whole scale ranges from 0 to 100, and the higher score represents the availability of higher resilience.

Job stress

The Persian version of OSIPOW Job Stress Tool was employed to assess job stress. It measures stress risk factors, such as workload, role incompetence, role dyad, limits of the role, responsibility, and work environment. A large number of studies have used and standardized this tool. For example, the reliability and validity of the Persian version of this scale were checked by Sharifian et al., and its Cronbach's alpha coefficient was obtained equal to 0.83.[27] The statements have been designed based on a five-point Likert scale (1 = never, 2 = sometimes, 3 = mostly, 4 = usually, and 5 = regularly). The total score of this tool ranges from 60 to 300, where the higher score is tantamount to higher stress in the respondent. In addition, total stress is categorized in four categories (i.e., 60–110 = low stress, 120–179 = low-moderate stress, 180–239 = moderate-severe stress, and 240–300 = severe stress).

Ethical consideration

The study protocol was approved by the Ahvaz Jondishapur University of Medical Sciences Ethical Review Committee under decree code of IR.AJUMS.REC.1398.029. Participation in the study was on a voluntary basis, and informed consent was obtained from all participants before their participation.

Statistical analysis

Kolmogorov–Smirnov test was used to investigate the normality and distribution of variables. Nonparametric Kruskal–Wallis test and Mann–Whitney test were used to analyze data that did not follow the normal distribution. Moreover, the Pearson test was used to investigate the correlation between parametric variables and independent samples. Furthermore, t-test and one-way analysis of variance were used to investigate the differences between the mean of parametric variables that followed the normal distribution. All tests were carried out in SPSS version 25 (SPSS Inc., Chicago, IL, USA).

  Results Top

The results showed that the mean (± standard deviation [SD]) of age was 31.57 (6.89) years and one-half of the participants (50.8%) were younger than 30 years old. In addition, 84.1% (n = 164) of the sample group were women and 15.9% (n = 31) were men. In terms of education level, 94.4% of the participants had bachelors' degree. About one-half of the nurses (53.8%) had a temporary work contract, 40.5% had a permanent work contract, and 5.6% were trainees. The mean (SD) of work experience was 5.08 (4.43) so that 59% of the nurses had <5 years of work experience. In addition, the majority of the participants (82.6%) had a rotating schedule [Table 1]. The mean (SD) of the level of resilience and job stress in nurses was 60.85 (±4.97) and 185.59 (±21.64), respectively. These two indices based on demographics and the significance of difference between the groups are listed in [Table 1]. The results of statistical tests showed that there was no significant difference in resilience scores among different groups of the participants' demographic (P > 0.05). The results of job stress in terms of demographical variables showed a significant difference in terms of age groups and wards (P < 0.05). In addition, the mean score of job stress was not significantly different in terms of other demographical variables [Table 1].
Table 1: Demographic characteristics and Mean (± SD) of resilience and job stress

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To investigate the correlation of job stress with resilience and demographic variables in the study participants, the Pearson correlation test was run. The results of this analysis are shown in [Table 2]. Job stress had a statistically significant negative correlation with resilience (r = −0.82). This means that job stress is reduced with the increase of resilience. In addition, the correlation between the elements of resilience and job stress was statistically significant negative (P < 0.05). Based on the results, the strongest correlation was between positive acceptance of change (a resilience index) and responsibility (a job stress index) (r =−0.578). In addition, the least correlation was between the spiritual effects and incompetence (r = −0.198).
Table 2: Correlation between job stress and resilience and demographical variables

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[Table 3] lists resilience as a predictor variable that predicts changes in job stress in a significant linear regression model (P < 0.05). In addition, all the elements of resilience as the predicting elements of job stress were added to the model and the results showed that the multiple linear mode was significant (P < 0.05). Each one of the elements of resilience could predict variances in job stress of nurses (P < 0.05) [Table 3].
Table 3: Linear regression to explain job stress by considering resilience and its components

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  Discussion Top

The aims of this study were to determine the effect of resilience on job stress and present a predictive model of stress levels based on resilience indicators among nurses. The results of the present study revealed that the mean value of job stress was equal to 185.59 (±21.64). According to the categories of job stress, more than 50% of the participants suffered from moderate-severe stress. Therefore, job stress in the current research population lies in a warning state. This finding is consistent with the results of similar studies.[28],[29] These studies have reported that different factors, including overnight shifts, disruption of circadian rhythm, demanding nature of the job, communication with critically ill patients, carrying patients, changes in daily programs, and long work hours, are among the causes of job stress in nurses. These factors may lead to an increase in job stress in nurses.[28],[29],[30]

Concerning the relationship between job stress and the demographic variables, it was shown that there is a significant difference between nurses in different age groups and working in different wards in terms of job stress. The highest level of job stress was found among the nurses younger than 30 years old, and the lowest level of job stress was observed in the nurses placed in the 30-to-40-year-old age group. Similarly, the results of the study conducted by Hashemian et al. on the job stress of nurses in Iran have shown that the stress of older nurses was less than that of younger nurses, which could be due to the increased ability and skill of older nurses to manage occupational stress.[31] In this regard, the results of a meta-analysis study conducted by Isfahani et al. have demonstrated that job stress affects over a third of Iranian nurses. There was a significant negative correlation between job stress and age in such a way that every year of increase in nurses' age decreases the prevalence of job stress by 0.006%. The reason may be attributable to the increased work experience and job compatibility of nurses with higher ages. This finding is consistent with the findings of the current study.[32] Although the findings are consistent with those obtained by Kokoroko and Sanda,[28] they are inconsistent with the ones reported by Joseph et al.[29] One of the reasons for this inconsistency can be the different psychosocial and physical-cultural risk factors dominant in the two work environments.

In terms of wards, the highest and lowest levels of job stress were related to the general and emergency wards, respectively. This finding is consistent with that reported by Pflanz and Sonnek; they argued that the ward affects the stress level experienced by nurses such that the emergency ward was associated with the highest level of stress.[33] Despite the significant difference between different wards and age groups in job stress, the correlation between demographical variables and job stress was insignificant. Therefore, it can be concluded that aging does not necessarily decrease job stress among nurses. These findings align with the results of prior studies in this domain.[29] In fact, research has shown that nursing is a profession replete with numerous problems, including the conflict with patients, interpersonal relationships with physicians and colleagues, trivial support for nurses, highly demanding responsibility, the increased complication of patients' conditions, decreased control, ambiguous role, understaff wards, and complicated technologies. All these items intensify job stress.[13],[14],[15] Unlike these risk factors, resilience can be considered an efficient strategy to adapt to the situation and ensure a stable and healthy psychological performance.[18]

The results of the present study showed that resilience increased with increasing age, work experience, and education level, although this difference was not statistically significant. In fact, it can be pointed out that with increasing nurses' age, work experience, and education, their personal abilities and skills to cope with critical and stressful situations develop. The development of such skills helps with the creation of various coping strategies, which can facilitate their adaptation and provide them with the possibility to act effectively and more resiliently in such situations. In this line, Gillespie et al. carried out a study on the resilience of nurses and reported that resilience increased with the increase of age, experience, and education of nurses.[34] Furthermore, Campbell-Sills et al. also argued that the resilience score rises with an increase in the level of education.[35]

Another important result of this study was the significant negative correlation between resilience and job stress; in other words, the higher the resilience, the lower the job stress. In this regard, the lowest and highest levels of job stress belonged to the general and emergency wards, while the lowest and highest levels of resilience pertained to the emergency and general wards, respectively. Therefore, the higher the resilience of nurses at work, the lower the job stress they will experience. In the same way, Yilmaz examined the effectiveness of resilience as a strategy in dealing with challenges at work in nurses. They showed that resilience enables nurses to adapt to their work environment and demonstrate a healthy and stable psychological performance.[17] Similarly, Foureur et al. conducted a study on the effect of resilience on enhancing health and attachment and, at the same time, decreasing depression, anxiety, and stress in nurses and midwives. They concluded that health and attachment in the subjects experienced an increase along with a decline in their stress level.[36] In another study, the effects of resilience and stress control were assessed on psychosocial care in nurses by Lim et al. They reported that the increase in resilience was related to the decrease in stress.[37] These results are in line with recent studies that have proven the positive effect of resilience on job stress.[17],[23],[24]

Based on the results of the current study, the correlation between resilience and the elements of job stress was significant and negative in such a way that resilience had a relatively small correlation with incompetence and dyad role but a strong correlation with other elements of job stress. A significant negative correlation was also observed between the elements of resilience and the elements of job stress. In this vein, the minimum correlation was found between spiritual effects and control. In this line, the results of the study conducted by Rushton et al. also showed a negative correlation between resilience and stress so that higher levels of resilience were associated with increased hope and reduced stress.[38] Considering the reported findings, improving the aspects of resilience, such as control, is a reliable strategy to control job stress in the population.

In the present study, the results of regression analysis considered resilience as a predictor variable and reported that it was a significant predictor of job stress variations in a linear regression model, where resilience predicted 67.9% of changes in job stress (R2 = 0.679). Moreover, the results of the prediction model of job stress based on the elements of resilience showed that the multiple linear models were significant in such a way that the highest and lowest prediction powers pertained to the positive acceptance of change, and secure relationships (β = −0.092) and self-image of competence (β = −0.018). These findings further indicate that reducing job stress based on the elements of resilience has drawn a great deal of attention. Accordingly, resilience can be used as a strategy to control job stress.


One of the interfering factors in this study is the effect of stressful situations outside the workplace that had occurred at the same time the survey was being completed, which may affect the level of job stress in individuals. The second limitation in this study was that due to the location and time limitations, this study surveyed only end-point resilience among nurses of educational hospitals; therefore, to generalize the results in the nursing community, it is necessary to perform a longitudinal design study in a larger sample size in both educational and private hospitals.

  Conclusion Top

The results of the present study showed that the level of stress in nurses was moderate-severe. According to the study results, the relationship between resilience and job stress was significant and inverse. Furthermore, the findings of this study indicated that resilience and indicators of resilience can heavily predict changes in job stress. In addition, more attention should be paid to other variables that may influence stress, including age and wards. The information of this study can be used to implement the necessary interventions and design resilience training programs to strengthen the resilience level of nurses and as a result control and reduce stress.


The authors would like to thank all participants for their cooperation.

Financial support and sponsorship

The study was financially supported by the Research Committee, Ahvaz Jundishapur University of Medical Sciences, under research plan no. 98S5.

Conflicts of interest

There are no conflicts of interest.

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  [Table 1], [Table 2], [Table 3]


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