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Journal of Public Health Research logoLink to Journal of Public Health Research
. 2021 Aug 12;11(1):2365. doi: 10.4081/jphr.2021.2365

Exploring the effort-reward structure of university work focusing on perceived overall stress, self-reported health, and musculoskeletal disorders

Bence Verpeléti 1,, Edina Horváth 1, Gordana Dobi-Ágoston 1, Gergely Ágoston 2, Kitti Bérces 2, Regina Molnár 1, Veronika Mátó 3, Albert Varga 2, Edit Paulik 1
PMCID: PMC8874843  PMID: 34461691

Abstract

Background: The effort-reward imbalance (ERI) model by Siegrist encouraged numerous scientific investigations that reported particular ties between psychosocial risks and poor self-reported health (SRH), while psychosocial work-related stress has also been linked to musculoskeletal disorders (MSDs). The aim of this study was to examine the health status and the perceived levels of occupational stress of university employees and to analyse the findings according to the employees’ effort and reward structure of work, perceived overall stress, SRH and the presence of MSDs.

Design and methods: 398 employees – including healthcare professionals, academic personnel and workers with administrative or other jobs – employed at the University of Szeged, Faculty of Medicine were investigated with a self-administered questionnaire including the Effort-Reward Imbalance Questionnaire (ERIQ) and Perceived Stress Scale 4 (PSS-4).

Results: More than half of the investigated subjects (54.8%) reported some forms of MSDs. Low self-reported health (P<0.001) and presence of MSDs (P=0.015) were significantly associated with the level of perceived stress and effort-reward imbalance (ERI), moreover increased level of perceived stress was independently associated with the likelihood of MSDs (AOR=1.13) and low self-reported health (AOR=1.30). ERI well predicted low self-reported health (AOR=2.05) as well. Increased level of perceived stress positively correlated with high workrelated effort (r=0.247, P<0.001) and over-commitment (r=0.387, P<0.001) while with work-related reward (r=−0.181, P=0.011) perceived stress showed a negative connection.

Conclusion: Our results suggest that addressing the burden of effort-reward imbalance and MSDs would likely lessen employees’ perceived level of overall stress and affect their self-reported overall state of health.

Significance for public health.

In a university hospital setting, numerous areas of academic and healthcare work are strongly interlaced. For that reason, healthcare workers, academics, and employees with various other job roles all share the work-related psychosocial and health risks that originate from the same organizational setting. As workrelated stress, poor self-reported health, and musculoskeletal disorders (MSDs) are all closely linked to effort-reward imbalance (ERI), exploring the effort and reward structure of university work could provide valuable insight in the possible role of the ERI model to guide interventions in this particular setting. Our results suggest that addressing university employees’ ERI, their burden of MSD, or possibly both, would likely affect employees’ perceived level of overall stress and self-reported overall state of health.

Key words: Academic personnel, Effort-reward imbalance, Musculoskeletal complaints, Healthcare worker, Perceived stress

Introduction

Health is not only central to human well-being, it is also an essential social capital:1 in healthy populations people live longer, the onsets of disabilities are delayed2 and both absenteeism and economic cost of treatment is lower among healthy employees.3 Therefore, addressing the social determinants of health is crucial in supporting a healthy, productive society.1

As one of the social and economic determinants of health, healthcare professionals are key to improve the quality of health services. However, they generally suffer from high levels of work-related stress that likely hinders their motivation.4 Occupational stress is also a significant predictor of burnout; and higher burnout levels are in turn associated with diminished job performance and more absences5 – particularly due to mental health issues, that are among the leading causes of absenteeism and early retirement everywhere in Europe.6 Also there are substantial scientific evidence linking psychosocial work-related stress to cardiovascular diseases, affective disorders and musculoskeletal disorders (MSDs).7

This group of painful disorders of muscles, tendons, joints and nerves (i.e. MSDs) are the most prevalent health problem associated with work in Europe.8,9 MSDs concern workers in all occupations8 and generally several risk factors of MSDs are present.9 Roughly three out of five workers in the EU-28 report MSD complaints. 8 Among them, healthcare workers have one of the highest self-reported MSD prevalence due to patient handling tasks,9 while academic employees’ prolonged sitting position – especially with frequent computer use – is a major contributor in MSD development as well.10

The complex relationship between psychosocial factors and MSDs is also well established.7,11,12 The effort-reward imbalance (ERI) model by Siegrist13 – which theorizes that high efforts spent and low rewards received is likely to elicit negative emotions and sustained stress14 – encouraged numerous scientific investigations, that reported particular ties between psychosocial risks and cardiovascular diseases7 as well as a significant association between effort-reward imbalance and poor self-reported health.15

Aside from having legal responsibilities to ensure a safe and healthy workplace, it is in the healthcare providers’ best interest to create a health-promoting, ergonomic work environment for employee well-being, increased productivity and efficient management. 6,16

Aims of present study

The aims of this study are to examine the health status and the perceived levels of occupational stress of university employees in dependence of their socio-demographic characteristics, in addition to analyse the findings in relation to the employees’ effort and reward structure of work focusing on perceived overall stress, selfreported health and the presence of MSDs.

Design and methods

Study design, population, and data collection

Data were collected during routine occupational health checkups for healthcare professionals, academic personnel, and employees with administrative, other (e.g. cleaners) or multiple job roles (e.g. both practicing and teaching physicians). Subjects were all employed by the University of Szeged, Faculty of Medicine, working at its various medical, academic or administrative sites. The survey was scheduled from November 2017 through the end of June 2019; the study included 398 respondents.

Data were collected by a self-administered questionnaire. Questions concerned participants’ socio-demographic data (age, gender, marital status, levels of education, type of job) and health status (self-reported level of health, MSDs and presence of any other chronic diseases). Regarding MSDs questions concerned joint stiffness and recurring pain in neck, back (upper, lower), upper extremity (hand, elbow, shoulder) or lower extremity (foot, knee, hip) for an unspecified extensive period of time.

Overall perceived stress level for each subject was determined using the Hungarian validated four-item version of the Perceived Stress Scale (PSS-4).17,18 Participants were asked how often they felt or thought a certain way during the last four weeks on a fivepoint scale. After scoring the negatively-worded items and reverse scoring the positively-worded items the PSS assesses the participant’s subjective global stress where higher scores indicating higher perceived stress.19

The effort and reward structure of work was measured by the short (15 items) Hungarian version of the Effort-Reward Imbalance Questionnaire (ERI-Q) psychometrically validated by Salavecz et al.20 The effort-reward imbalance (ERI) model was originally developed to identify conditions of failed reciprocity with a particular focus on work, and to predict reduced well-being,21,22 increased illness susceptibility13 and diminished job satisfaction.23 The model is also widely regarded as a well-justified measure of work-related stress, convenient for comparative socio-epidemiologic research.24 As part of ERI-Q, subscales measuring work-related effort, reward and over-commitment was included.20 ERI-Q uses Likert-scales to indicate whether ERI and over-commitment are present. Higher scores in effort and over-commitment refer to more demanding aspects of the work environment while higher scores in reward postulate higher extrinsic work-related reward.24 In essence the more dominantly work-related effort is perceived over reward, the higher the ERI value is for that participant.

The effort–reward ratio (i.e. ERI) was calculated as: ER= (e / r) × c where ‘e’ is the summed score of the effort scale, ‘r’ is the summed score of the reward scale, and ‘c’ defines a correction factor for different numbers of items. As the short version of the Hungarian validated questionnaire contains three items in the effort subscale and six items in the reward subscale the correction factor was 0.5.20

Statistical analysis

IBM SPSS Statistics 24.0 was used for the data analysis.

Descriptive statistics for the participants’ characteristics were determined, and Cronbach’s α value was calculated for each psychometric scale to check for reliability.

As sample distributions violate the assumption of normality, one-way ANOVA on ranks (Kruskal-Wallis H test) was used with pairwise comparisons (Mann-Whitney U test) for post-hoc analysis to determine any statistically significant differences between the medians of PSS-4 value and effort-reward ratio among groups formed according to sociodemographic and health related characteristics. Separate analyses for effort, reward, and overcommitment subscales were also included. Detailed comparisons among median PSS-4 values were also made based on ERI-Q items individually using one-way ANOVA on ranks.

Univariable and multivariable logistic regressions were used to assess the effect of PSS-4 and ERI on the presence of MSD and poor or average self-reported health. The multivariable model was adjusted for possible sociodemographic (gender, age, education, marital status) and occupational (job role) confounding factors. Odds ratios (OR) were calculated with 95% confidence intervals (95% CI).

To determine the independent contribution of ERI and each subscale of ERI-Q to perceived stress covariate-adjusted Spearman’s rank correlation analysis was performed with the use of probability-scale residuals.25

During the analyses missing values were excluded. Statistical significance was set at P<0.05 (two-tailed).

Results

Overall characteristics of the sample are summarized in Table 1.

Out of 398 university employees the majority were females. The median age of the participants was 38 years [interquartile range (IQR)=18.0] and university degree was the most common educational qualification. 45.6% of subjects were healthcare professionals (physicians, surgeons, nurses, midwives) and 13.2% were academics (professors of various ranks, lecturers, and/or researchers including PhD students). A sum of 82 employees (20.6%) involved in administrative and various other activities (cleaning and catering services, economic and management activities) were classified as other, while 10.3% of study subjects with multiple roles were defined as mixed.

More than half of the investigated subjects (54.8%) reported musculoskeletal disorders and around a third of the subjects suffered from any other form of chronic disease (excluding MSDs) lasting for at least six months. Thyroid disease (25 instances) and hypertension (23 instances) were the most commonly reported chronic conditions, followed by asthma (11 cases) and carbohydrate metabolism disorders (10 cases). Nearly a quarter of the participants expressed average and poor overall state of health.

Table 2 shows the overview and descriptive statistics of perceived stress, ERI, its corresponding subscales, and Cronbach’s alpha coefficients for the scales. All Cronbach’s alpha coefficients were over 0.7 indicating the reliability of the scales.

The relationships between medians of PSS-4, effort-reward ratio, or any of the aforementioned subscales to sample characteristics are presented in Table 3.

The results indicate that low self-reported overall health rating (P<0.001) and presence of any form of MSDs (P=0.015) were significantly associated with overall stress perception (PSS-4). Other chronic diseases, socio-demographic characteristics or the type of job were not connected with PSS-4 values.

Considering each of the effort, reward and over-commitment subscales, the type of job affected all three. Post-hoc tests revealed that subjects having more than one role (i.e. mixed job) reported statistically significantly greater work-related effort and over-commitment compared to any other job role.

Female employees reported significantly lower work-related reward (P<0.001), and university graduates presented significantly higher perceived effort (P=0.021) and over-commitment (P=0.006). Aside from job role and gender, married or otherwise committed employees reported higher work-related effort compared to singles with marginal significance.

MSDs were significantly associated with all three subscales: effort and over-commitment subscales showed positive, while reward showed negative association with MSD. Suffering from any other form of chronic disease presented significant associations with perceived rewards and over-commitment but not with work-related effort. Regarding the effort-reward ratio only having any form of MSDs (P=0.011) and a low self-reported health rating (P<0.001) had a positive significant association. Poor self-reported health was found to be significantly connected with higher perceived overall stress and all ERI-Q subscales as well.

Univariable (i.e. unadjusted) logistic regression analysis showed that increased level of perceived stress and ERI were positively associated with the likelihood of suffering from any form of MSD (OR=1.10 / OR=1.56) and low (i.e. average or poor) self-reported health rating (OR=1.24 / OR=1.90) (Table 4). After adjusting for potential confounding factors (gender, age, education, marital status and job role), the adjusted odds ratios showed that the independent association between predictors and the outcomes are even more likely to be present; every one unit of increase of ERI doubles the likelihood for low self-reported health rating and with increasing levels of perceived stress the likelihood of MSD and low self-reported health grows 13% and 30% respectively with each increasing unit of measure. However, the independent association between MSD and ERI showed only marginal significance (P=0.056).

According to the results of the itemized analysis of variance on ranks among PSS-4 values, subjects indicating constant time pressure (P<0.001), many interruptions (P=0.002) and those who described their work increasingly more demanding (P<0.001) reported significantly higher perceived overall stress. Similarly, those with high values regarding all six items measuring overcommitment scored significantly higher PSS-4 values (P<0.001). Accordingly, employees reporting adequate job promotion prospects (P=0.004/P=0.008) and better employment security (P=0.003) showed significantly lower perceived stress. Likewise, receiving the well-deserved respect and prestige (P=0.058), and not expecting or experiencing undesirable change in work situations (P=0.044) yielded lower perceived stress scores with marginal significance. Inadequate payment proved to be less determinative (P=0.192) of perceived stress.

As effort-reward imbalance and all three subscales of ERI-Q showed monotonic relationship with PSS-4 values, covariateadjusted Spearman rank-order correlation coefficient has been calculated to determine the strength and direction of each mentioned association. After adjustments for gender, age, education, marital status and job role, both work-related effort (r=0.247, P<0.001) and over-commitment (r=0.387, P<0.001) positively associated with the level of perceived stress, while work-related reward showed a negative connection (r=−0.181, P=0.011). Positive association of overall perceived stress with the effort– reward ratio was also observable (r=0.227, P<0.001). Among the possible confounders job role was the most influential (i.e. over 10% coefficient difference).

Table 1.

Respondent characteristics (n=398).

Characteristic Number %
Gender
   Female 315 79.1
   Male 83 20.9
Age
   18-35 174 43.7
   36-55 194 48.8
   56-65 30 7.5
Marital status
   Single 90 22.6
   Married or common-low relationship 259 65.1
   Divorced or widowed 49 12.3
Education
   Primary or secondary school 84 21.1
   University 314 78.9
Type of job
   Healthcare professional 181 45.6
   Academic personnel 53 13.2
   Other 82 20.6
   Mixed (i.e. multiple job roles) 41 10.3
   Missing 41 10.3
Musculoskeletal disorder
   Yes 218 54.8
   No 175 43.9
   Missing 5 1.3
Chronic disease
   Yes 119 29.9
   No 277 69.6
   Missing 2 0.5
Self-reported health
   Very poor 0 0.0
   Poor 3 0.8
   Average 90 22.6
   Good 234 58.7
   Very good 68 17.1
   Missing 3 0.8

Table 2.

Overview of PSS-4 scale, effort, reward, over-commitment subscales of ERI-Q and effort–reward imbalance based on ERI-Q.

Scales Scores Questionnaire attributes
Mean (SD) Number of items Total range of scores Cronbach’s alpha
PSS-4 scale 4.68 (2.65) 4 0-16 0.78
Effort subscale of ERI-Q 8.13 (3.35) 3 3-15 0.80
Reward subscale of ERI-Q 21.83 (5.02) 6 6-30 0.74
Over-commitment subscale of ERI-Q 13.94 (3.48) 6 6-24 0.81
ERI based on ERI-Q responses 0.84 (0.57)

SD, standard deviation; PSS-4, perceived stress scale four items; ERI-Q, effort-reward imbalance questionnaire.

Discussion

In this study the perceived stress level and the effort-reward structure of work among healthcare employees, academics and others with differing job roles were investigated. We found that low self-reported health and presence of MSD were in significant positive association with the level of perceived stress and ERI. High work-related effort and over-commitment positively correlated with increased level of perceived overall stress.

Epstein et al. found that, among at-risk physicians, the prevalence estimates for work-related musculoskeletal pain of the neck, shoulder, back, and upper extremity were 65%, 52%, 59% and 39% respectively.26 In the university environment, prevalence of MSDs was reported to be lower but still 59%, 53%, 47% and 30% of the total staff may experience discomfort in the same anatomical regions.10,27 Our findings are consistent with these reports with 54.8% of the subjects reporting some form of MSD.

Table 3.

Relationship of personal characteristics to perceived stress, effort, reward, over-commitment subscales and effort-reward imbalance (Kruskal-Wallis H test & Mann-Whitney U test for post-hoc pairwise comparisons).*

Personal PSS-4 Effort Reward Over-commitment ERI
characteristics M (range) P M (range) P M (range) P M (range) P M (range) P
Gender 0.859 0.540 0.001 0.280 0.081
   Female 4 (0-13) 9 (3-15) 22 (8-30) 14 (6-24) 0.80 (0.2-3.3)
   Male 5 (0-13) 8 (3-15) 24 (6-30) 14 (6-23) 0.69 (0.2-4.7)
Age (years) 0.379 0.595 0.334 0.809 0.388
   18-35 (a) 5 (0-13) 8 (3-15) 23 (9-30) 14 (6-23) 0.75 (0.2-3.3)
   36-55 (b) 4 (0-13) 8.5 (3-15) 22 (6-30) 14 (7-22) 0.79 (0.2-4.7)
   56-65 (c) 4 (0-9) 7 (3-15) 21 (13-28) 13 (7-24) 0.67 (0.2-2.2)
Marital status 0.952 0.044* 0.415 0.250 0.134
   Single (a) 4 (1-11) 8 (3-15) a-b 23 (10-30) 14 (7-23) 0.70 (0.2-2.7)
   Married or in relationship (b) 5 (0-13) 9 (3-15) 22 (8-30) 14 (6-24) 0.80 (0.2-3.3)
   Divorced or widowed (c) 4 (0-9) 7 (3-15) 22 (6-29) 14 (8-22) 0.67 (0.2-4.7)
Education 0.160 0.021 0.042 0.006 0.425
   Primary or secondary school 5 (0-10) 8 (3-15) 21 (6-30) 13 (6-24) 0.72 (0.2-4.7)
   University 4 (0-13) 9 (3-15) 23 (8-30) 14 (6-23) 0.76 (0.2-3.3)
Type of job 0.264 0.002* 0.017* 0.009* 0.141
   Healthcare professional (a) 4 (0-13) 8 (3-15) a-db-dc-d 22 (8-30) 14 (6-21) a-db-dc-d 0.78 (0.2-3.3)
   Academic personnel (b) 5 (1-11) 7 (3-13) 24.5 (10-30) 14 (6-19) 0.65 (0.2-2.2)
   Other (c) 5 (1-11) 7.5 (3-15) 22 (8-30) 13 (7-24) 0.72 (0.2-3.3)
   Mixed (d) 4 (0-13) 10 (3-15) 23.5 (11-30) 15 (9-23) 0.86 (0.2-2.7)
Musculoskeletal disorder 0.015 0.037 0.001 0.013 0.011
   Yes 5 (0-13) 9 (3-15) 21 (6-30) 14 (7-24) 0.82 (0.2-4.7)
   No 4 (0-13) 8 (3-15) 24 (9-30) 14 (6-21) 0.67 (0.2-3.3)
Chronic disease 0.722 0.854 0.005 0.045 0.277
   Yes 4.5 (0-11) 9 (3-15) 21 (8-30) 14 (7-24) 0.79 (0.2-3.3)
   No 4 (0-13) 8 (3-15) 23 (9-30) 14 (6-23) 0.74 (0.2-3.3)
Self-reported health 0.001* 0.044* 0.001* 0.043* 0.001*
   Poor (a) 7 (7-13) a-db-dc-db-c Non- 9 (6-14) b-d 12 (10-13) a-da-cb-cb-dc-d 15 (15-16) 1.80 (0.9-2.3) a-db-dc-d
   Average (b) 6 (0-12) 9 (3-15) 21 (6-29) 14.5 (7-23) 0.83 (0.2-4.7)
   Good (c) 4 (0-13) 9 (3-15) 22 (9-30) 14 (6-21) 0.76 (0.2-3.3)
   Very good (d) 3 (0-9) 6 (3-15) 25 (10-30) 13 (7-24) 0.49 (0.2-2.7)

M, median; range, minimum-maximum value; PSS-4, perceived stress scale four items; ERI, effort-reward imbalance; *pairs of personal characteristic groups (indicated with a, b, c or d) with statistically significant differences are listed under the p-values.

Table 4.

Univariable and multivariable logistic regressions predicting the likelihood of presence of musculoskeletal disorders and poor or average self-reported health rating based on PSS-4 and ERI values.

Outcome Predictor variable Univariable analysis Multivariable analysis
OR 95% CI P AOR 95% CI P
MSD present PSS-4 1.10 1.02-1.19 0.017 1.13 1.03-1.23 0.007
ERI 1.56 1.05-2.32 0.027 1.56 0.99-2.45 0.056
Poor or average SRH PSS-4 1.24 1.13-1.35 <0.001 1.30 1.17-1.45 0.001
ERI 1.90 1.28-2.84 0.002 2.05 1.27-3.31 0.003

OR, odds ratio; AOR, adjusted odds ratio; CI, confidence interval; MSD, musculoskeletal disorder; SRH, self-reported health; PSS-4, perceived stress scale four items; ERI, effort-reward imbalance.

Milutinović’s study reported significant differences in the perception of work-related stress among nurses, regarding psychological or somatic symptoms and certain diseases, indicating a close connection between work-related stress and psychosomatic health.28 These findings are similar to our results that suggest a close relationship between high perceived stress and suffering from MSD or poor overall health. Data from four major European studies showed that ERI, work-related effort, lack of reward and over-commitment are all significant risk factors for self-reported health.24 Our results are consistent with these findings as participants in our study with poor self-rated health can be characterized by high effort and low reward.15,24

Working indisposed or feeling unfit for any workplace situation could also explain a heightened level of perceived stress. However, in our study group neither prevalence of chronic diseases (excluding MSDs) exceeded the prevalence of chronic conditions among the general population reported in the European Health Interview Survey,29 nor did self-reported overall health proved worse compared to self-reported health status of the adult Hungarian population.30

The connection between MSDs and ERI is less clear. Our results presented that suffering from any form of MSDs corresponds with high work-related effort and over-commitment, and with low work-related reward; likewise, having some form of MSD was found to be associated with increased ERI. A systematic review by Koch et al. concludes that on the basis of 13 studies with positive, statistically significant association, a moderate level of evidence was inferred for the association between effort-reward imbalance and musculoskeletal pain.31 However, without additional longitudinal studies with standardised methods no reliable conclusion can be drawn of any association between the psychosocial factors using the ERI model and musculoskeletal complaints.31 Available research on connection of subscales of ERI model and gender is scarce. Satoh et al. proposed a link between ERI and emotional commitment to occupation,23 while Kong et al. highlighted ERI’s connection with empathy.32 As the reward subscale of ERI-Q focuses more on work-related extrinsic reward rather than intrinsic reward,24 perhaps a gender difference in occupational commitment, empathy or self-advocacy might explain our results which showed that female employees gain less reward. Future studies are needed in this question.

The fact that the level of education positively correlates with work-related effort, reward and over-commitment is well established since ERI-Q validation.20 However – similarly to our findings – the effort-reward ratio is not associated with the level of education.20

It is well known that role accumulation can offer employees a wide range of practical and psychological benefits such as increased salary and mobility, enhanced skills, status security and prestige esteem.33 In our study, subjects having more than one role reported greater work-related effort and over-commitment and presented greater reward suggesting a balance that was visible in the effort-reward ratio as well. Nonetheless, having multiple job roles has a clear potential for work overload and to impair the employee’s well-being.33

The fact that thyroid diseases were the first-mentioned of chronic conditions among university employees is somewhat peculiar. There is evidence that thyroid function, particularly TSH (thyroid-stimulating hormone) level correlates with perceived overall stress,34 however this association does not explain the high frequency of thyroid diseases in our findings, indicating a research gap for future studies to fill.

Implication for practice

It is extensively advised in corresponding literature that, in order to enhance employee performance, service providers should aim to improve working conditions,4,7,35 develop and maintain a healthy workforce,28,36 and focus on job satisfaction. 37,38,39 Healthy workplaces prevent occupational diseases and accidents, promote positive lifestyle behaviours, and facilitate organizational development.36 Addressing the high prevalence of musculoskeletal disorders (MSDs) possibly affects employees’ perceived level of overall health state and occupational stress. In addition to affecting productivity and retention, job satisfaction and ideal working conditions can also influence a healthcare network’s ability to achieve its patient-centered goals.39,40

Limitations of the study

The data were collected from university employees in the southern region of Hungary, therefore cannot be viewed as representative of Hungarian employees. No strategies to restrict admission into the group of subjects were employed. During statistical analysis regression modelling was employed to eliminate confounding effects, however multivariable analysis does not directly identify whether a factor is a true confounder. Therefore, it is not clear whether residual confounding remains in the model.41 Accordingly, further studies are needed in order to determine whether these findings can be generalized and to what extent. More limitations are that – in order to improve participation compliance – the abbreviated versions of PSS and ERI questionnaires were used, in addition to omitting a standardized questionnaire for estimating MSDs. Presence of MSDs and not specifically work-related MSDs were investigated, likewise the PSS-4 tool measures overall perceived stress, not occupational stress.42 Moreover, the responses given to any self-reported questionnaire are affected by recall bias. The subjects’ state of mind at the occupational health check-up, such as an overemphasis on health problems, could have influenced the results.

Conclusions

The perceived overall stress level and the effort-reward structure of work was investigated among healthcare employees, academics and others with differing job roles at the University of Szeged, Faculty of Medicine. Low self-reported health and the presence of musculoskeletal disorder were significantly associated with the level of perceived overall stress and effortreward imbalance. High work-related effort and over-commitment positively correlated with increased level of perceived overall stress, while greater work-related reward correlated with lower level of overall stress. Our results suggest that addressing university employees’ ERI, their burden of MSD or possibly both, would likely affect employees’ perceived level of overall stress and self-reported overall state of health.

Acknowledgments

We are deeply grateful to the participants of this study and those who co-operated with us in conducting the data collection.

Funding Statement

Funding: None.

References

  • 1.American Medical Association. Healthy population equals healthy economy. 2020. Accessed August 31, 2020. Available from: https://www.ama-assn.org/practice-management/economics/healthy-population-equals-healthy-economy [Google Scholar]
  • 2.Mehta N, Myrskylä M. The population health benefits of a healthy lifestyle: life expectancy increased and onset of disability delayed. Health Aff (Millwood) 2017;36:1495-502. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Kaspin LC, Gorman KM, Miller RM. Systematic review of employer-sponsored wellness strategies and their economic and health-related outcomes. Popul Health Manag 2013;16:14-21. [DOI] [PubMed] [Google Scholar]
  • 4.Deng J, Guo Y, Ma T, et al. How job stress influences job performance among Chinese healthcare workers: a cross-sectional study. Environ Health Prev Med 2019;24:2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Parker PA, Kulik JA. Burnout, self- and supervisor-rated job performance, and absenteeism among nurses. J Behav Med 1995;18:581-99. [DOI] [PubMed] [Google Scholar]
  • 6.Baumann A, Muijen M, Gaebel W. Mental health and wellbeing at the workplace – protection and inclusion in challenging times. WHO Regional Office for Europe; 2010. [Google Scholar]
  • 7.Portuné R. Psychosocial risks in the workplace: An increasing challenge for German and international health protection. Arh Hig Rada Toksikol 2012;63:123-11. [DOI] [PubMed] [Google Scholar]
  • 8.de Kok J, Vroonhof P, Snijders J, et al. Work-related MSDs: prevalence, costs and demographics in the EU. European Agency for Safety and Health at Work (EU-OSHA); 2019. [Google Scholar]
  • 9.Schneider E, Irastorza X. European OSH in figures: Workrelated musculoskeletal disorders in the EU — Facts and figures. European Agency for Safety and Health at Work (EUOSHA); 2010. [Google Scholar]
  • 10.Tantawy S. Work-related musculoskeletal symptoms among employees with different tasks: Ahlia University case study. Biomed Res 2019;30. [Google Scholar]
  • 11.Bernal D, Campos-Serna J, Tobias A, et al. Work-related psychosocial risk factors and musculoskeletal disorders in hospital nurses and nursing aides: A systematic review and meta-analysis. Int J Nurs Stud 2015;52:635-48. [DOI] [PubMed] [Google Scholar]
  • 12.Ballester Arias AR, García AM. [Occupational exposure to psychosocial factors and presence of musculoskeletal disorders in nursing staff: A review of studies and metaanalysis].[ Article in Spanish]. Rev Esp Salud Publica 2017;91:e201704028. [PubMed] [Google Scholar]
  • 13.Siegrist J. Effort-reward imbalance at work and health. In: Perrewe PL, Ganster DC, editors. Historical and current perspectives on stress and health. Bingley: Emerald Group Publishing Ltd.; 2002. p. 261-91. [Google Scholar]
  • 14.Siegrist J. Effort-reward imbalance at work - theory, measurement and evidence. Department of Medical Sociology, University Düsseldorf, Germany; 2012. [Google Scholar]
  • 15.Niedhammer I, Tek M, Starke D, Siegrist J. Effort-reward imbalance model and self-reported health: cross-sectional and prospective findings from the GAZEL cohort. Soc Sci Med 2004;58:1531-41. [DOI] [PubMed] [Google Scholar]
  • 16.Jiménez P, Bregenzer A, Kallus K, et al. Enhancing resources at the workplace with health-promoting leadership. Int J Environ Res Public Health 2017;14:1264. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav 1983;24:385-96. [PubMed] [Google Scholar]
  • 18.Stauder A, Konkolÿ Thege B. Characteristics of the Hungarian version of the perceived stress scale (PSS). Mentálhigiéné és Pszichoszomatika 2006;7:203-16. [Google Scholar]
  • 19.Lavoie J, Douglas K. The perceived stress scale: Evaluating configural, metric and scalar invariance across mental health status and gender. J Psychopathol Behav Assess 2012;13:34-48. [Google Scholar]
  • 20.Salavecz G, Neculai K, Rózsa S, Kopp M. [Az Erőfeszítés- Jutalom Egyensúlytalanság Kérdőív magyar változatának megbízhatósága és érvényessége].[Article in Hungarian]. Mentálhigiéné és Pszichoszomatika 2006;7:231-46. [Google Scholar]
  • 21.de Jonge J, Bosma H, Peter R, Siegrist J. Job strain, effortreward imbalance and employee well-being: a large-scale cross-sectional study. Soc Sci Med 2000;50:1317-27. [DOI] [PubMed] [Google Scholar]
  • 22.Yu S, Gu G, Zhou W, Wang S. Psychosocial work environment and well‐being: A cross‐sectional study at a thermal power plant in China. J Occup Health 2008;50:155-162. [DOI] [PubMed] [Google Scholar]
  • 23.Satoh M, Watanabe I, Asakura K. Occupational commitment and job satisfaction mediate effort-reward imbalance and the intention to continue nursing. Jpn J Nurs Sci 2017;14:49-60. [DOI] [PubMed] [Google Scholar]
  • 24.Siegrist J, Starke D, Chandola T, et al. The measurement of effort–reward imbalance at work: European comparisons. Soc Sci Med 2004;58:1483-99. [DOI] [PubMed] [Google Scholar]
  • 25.Liu Q, Li C, Wanga V, Shepherd BE. Covariate-adjusted Spearman's rank correlation with probability-scale residuals. Biometrics 2018;74:595-605. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Epstein S, Sparer E, Tran B, et al. Prevalence of work-related musculoskeletal disorders among surgeons and interventionalists. JAMA Surg 2018;153:e174947. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.James C, James D, Nie V, et al. Musculoskeletal discomfort and use of computers in the university environment. Appl Ergon 2018;69:128-35. [DOI] [PubMed] [Google Scholar]
  • 28.Milutinović D, Golubović B, Brkić N, Prokeš B. Professional stress and health among critical care nurses in Serbia. Arh Hig Rada Toksikol 2012;63:171-80. [DOI] [PubMed] [Google Scholar]
  • 29.Central Statistics Office. [A 2014-ben végrehajtott Európai Lakossági Egészségfelmérés eredményei. Összefoglaló adatok (Results of the European Population Health Survey conducted in 2014. Summary data)].[in Hungarian]. Central Statistics Office; 2018. Available from: https://www.ksh.hu/docs/hun/xftp/idoszaki/elef/elef2014_osszefoglalo.pdf [Google Scholar]
  • 30.Salavecz G, Chandola T, Pikhart H, et al. Work stress and health in Western European and post-communist countries: an East-West comparison study. J Epidemiol Community Health 2009;64:57-62. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Koch P, Schablon A, Latza U, Nienhaus A. Musculoskeletal pain and effort-reward imbalance- a systematic review. BMC Public Health 2014;14:37. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Kong L, Li W, Wang H, et al. The relationship between effortreward imbalance and empathy among clinical nurses: A crosssectional online survey. J Clin Nurs 2020;29:3363-72. [DOI] [PubMed] [Google Scholar]
  • 33.Kinman G. Effort-reward imbalance and overcommitment in UK academics: implications for mental health, satisfaction and retention. J High Educ Policy Manage 2016;38:504-18. [Google Scholar]
  • 34.Koner S, Chaudhuri A. A study of correlation of perceived stress and thyroid function among females in a rural population of reproductive age group. Med J Dr DY Patil Vidyapeeth 2020;13:30. [Google Scholar]
  • 35.Andersen LL, Fishwick D, Robinson E, et al. Job satisfaction is more than a fruit basket, health checks and free exercise: Cross-sectional study among 10,000 wage earners. Scand J Public Health 2017:45476-84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Whitehead D. Workplace health promotion: the role and responsibility of health care managers. J Nurs Manag 2006;14:59-68. [DOI] [PubMed] [Google Scholar]
  • 37.Gedif G, Sisay Y, Alebel A, Belay Y. Level of job satisfaction and associated factors among health care professionals working at University of Gondar Referral Hospital, Northwest Ethiopia: a cross-sectional study. BMC Res Notes 2018;11:824. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Saadat H, Kain Z. Wellness interventions for anesthesiologists. Curr Opin Anaesthesiol 2018;31:375-81. [DOI] [PubMed] [Google Scholar]
  • 39.Putra KR, Andayani T, Ningrum EH. Job satisfaction and caring behavior among nurses in a military hospital: A cross-sectional study. J Public Health Res 2021;10:2212. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Motley R, Mazzaccaro R, Burmeister D, et al. Using focus groups to identify characteristics of an ideal work environment for advanced practice clinicians. Healthcare 2016;4:151-4. [DOI] [PubMed] [Google Scholar]
  • 41.McNamee R. Regression modelling and other methods to control confounding. Occup Environ Med 2005;62:500-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Lee EH. Review of the psychometric evidence of the perceived stress scale. Asian Nurs Res (Korean Soc Nurs Sci) 2012; 6:121-7. [DOI] [PubMed] [Google Scholar]

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