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Impact of Sense of Coherence on Work Ability: A Cross-sectional Study Among Croatian Nurses

Abstract Introduction Aimed at preparing the basis for planning evidence-based public health measures for preservation/ improvement of nurses’ work ability (WA), the objective was to assess the relationship between WA and sense of coherence (SOC). Methods A cross-sectional study was conducted in 2018 among 713 nurses in Croatia. The association between poor WA index (PWAI) and SOC score (SOCS), adjusted for possible confounders, was determined by binary logistic regression analysis. Results The results of univariate logistic regression analysis showed a statistically significant negative association between SOCS and PWAI (OR=0.977, 95% CI 0.968 – 0.986, p<0.001). The results of multivariate logistic analysis showed an even stronger statistically significant negative association between SOCS and PWAI (OR=0.966, 95% CI 0.954 – 0.977, p<0.001) when adjusted for confounders. Conclusions The present study suggested SOC as an important health promoting resource of nurses which might offer protection regarding work-related stress. Weak SOC could be an important explanatory factor of poor WA. Accordingly, improving SOC by implementing health promotion measures in nurses’ workplace could be an important way to increase the WA among nurses.


INTRODUCTION
Work ability (WA) is an evidence-based concept defined as a balance between worker's personal resources and work-related factors (1). In order to obtain more knowledge about an individual's WA, the Finnish Institute of Occupational Health constructed an instrument, the Work Ability Index Questionnaire (WAIQ) (2,3), as a tool for investigating how long individuals are actually able to work (1). The measure obtained by the WAIQ is the Work Ability Index (WAI). WAIQ was recommended to be used as a diagnostic instrument for the development of measures for health support (4).
Sense of coherence (SOC) is a coping resource that helps individuals to identify and use their external and internal resources (Generalized Resistance Resources -GRR) for problem solving and managing stressful life events (5,6). Additionally, SOC was supposed to allow the individual experience of a stressful event to be perceived as meaningful, manageable and comprehensible by mobilizing GRRs, which arise from cultural, social and environmental conditions of living and early childhood rearing, and socialization experiences (6). Literature has shown that strong SOC has a positive effect on health and quality of life (7). It is also suggested that SOC is a health resource positively associated with well-being in a work environment (6,8); furthermore, it moderates the effects of unfavourable working conditions on health outcomes (6).
Considering that the nursing profession is mentally and physically demanding and stressful (9,10), it is necessary for nurses to maintain good mental and physical health in order to adequately perform their job. Unfortunately, a recent study revealed that they had poorer health compared to the general population (11). According to Prochnow et al., exposure to stress can have negative consequences on nurses' WA and health (12). Consequently, it is essential to recognize the importance of ensuring a positive and healthy working environment to avoid such consequences (13).
In the context of nurses' WA, SOC could be seen as a resource for adequate coping with workplace stressors (6). The literature demonstrates that a strong SOC protects nurses from stress (14) and contributes to nurses' healthy functioning at work (8). The literature has also shown that healthcare workers, including nurses, with strong SOC more often seek strategies for coping with stress (15). According to Masanotti et al., nurses' individual and work-related factors, such as age, gender, marital status, educational level, years of work experience, type of employment, shift work, work department, job satisfaction and work engagement, are an integral part of the GRRs and participate in the modelling of the nurses' SOC (16). All this is closely related to health promotion, more precisely to the workplace health promotion concept for nurses (17). Health promotion measures in nursing environments are more effective if they are evidence-based (18).
In Croatia, a study by Golubic et al. carried out about a decade ago showed that occupational stress was present also among Croatian nurses (19). The organization of work and financial issues, lower educational level and older age are the factors significantly associated with low WA (19). According to our knowledge and available literature, the relationship between WA and SOC in the population of nurses has not yet been explored either among Croatian nurses or elsewhere in the world. Consequently, aimed at preparing the basis for planning evidence-based health promotion measures for the preservation/improvement of nurses' WA, the objective of this study was to assess this relationship among Croatian nurses.

Study design, research method and population
A cross-sectional study (survey type: health interview survey) was conducted. Data were collected in 2018 at the University Hospital Centre (UHC) in Croatia, a large health institution similar to other institutions around the world, which employs a large number of nurses. A total population of 1,465 nurses of different profiles (nurses with secondary school education, bachelors of nursing, masters of nursing) employed in different departments of the UHC were considered for inclusion in the study. The only exclusion criterion was absence from the work-place at the time of the survey. Due to sick leave, annual leave and study leave 165 nurses were excluded and consequently 1,300 were invited to participate in the study.

Data collection procedures
The principal investigator held a meeting with the head nurses of each clinic at the UHC and presented to them the aim and objectives of the research and the research protocol. The paper-and-pencil self-administered study questionnaire was distributed to the nurses in all hospital departments personally by the first author. Anonymity was assured by using special identification codes unique to each participant. Written informed consent was obtained from each participant, gathered separately from completed questionnaires.

Measurement instruments
The two main instruments used in this study were WAIQ and the 'orientation to life questionnaire', also called the SOC scale.

Variables in the study
The observed outcome (a central phenomenon in the study that is intended to be explained to the greatest extent possible) was based on the WAI obtained by the administration of the WAIQ (2, 3). The WAI is a summary measure obtained by summing up the scores of individual responses to all items of WAIQ ranging from 7-49 points. A higher WAI suggests a better WA. The WAI could be analysed as a numeric value or categorized into four categories: 7-27 points indicating a poor WAI, 28-36 points a moderate WAI, 37-43 points a good WAI, and 44-49 points indicating an excellent WAI (2,3). For the purposes of our study, based on previous studies (10,22), the WAI was dichotomized into two groups: poor (<37 points) and good WAI (≥37 points). The poor WAI (PWAI) was considered the observed outcome and was included in the analysis as a dependent variable.
The explanatory factor (a phenomenon by which the occurrence of the observed outcome is intended to be explained) was the SOC score (SOCS), a summary measure obtained by summing up the scores of individual responses to all items of SOC-29, ranging from 29 to 203 points. A higher SOCS suggests a stronger SOC (5, 6).
As potential confounders (control variables) (phenomena that could potentially distort the assessment of the association between the observed outcome and explanatory factor), four groups of phenomena were considered. The first group consisted of socio-demographic characteristics: gender (female, male), age (≤40 years, >40 years), marital status (married, other), educational level (secondary school, bachelor of nursing, master of nursing), ongoing education (yes, no). The second group consisted of health behaviour: number of cigarettes per day (0, 1-5, >5), and physical activity (maximum 2 days per week, about 3 days per week, every day or almost every day). The third group consisted of work-related factors: work length (<1 year, 1-20 years, >20 years), work department (departments with special demands: polyclinic, oncology/haematology, psychiatric and paediatric units; other), time getting to work (≤30 minutes, >30 minutes), transportation mode (by car only, on foot only; other). The last group consisted of self-reported health conditions: injury from accidents, musculoskeletal diseases, cardiovascular diseases, respiratory diseases, mental disorders, neurological and sensory diseases, digestive diseases, genitourinary diseases, skin diseases, tumours, endocrine and metabolic diseases, blood diseases and birth defects (all of them yes, no).

Statistical analysis
In both the univariate and multivariate analyses of association between SOC and poor WAI, binary logistic regression was used. In the univariate analysis the direct method was used in which all independent variables in a block are entered in a single step. In multivariate analysis the stepwise method was used, more precisely the forward selection method using a likelihood criterion, in which independent variables enter the model step by step according to the criterion. The dummy variables were created for categorical explanatory/confounding factors with more than two categories (the simple method was applied). P-values <0.05 were considered statistically significant. Data analysis was performed using IBM SPSS Statistics for Windows (Version 21.0. SPSS Inc. Chicago. IL. USA).

Description of the study group
Out of 1,300 nurses 713 agreed to participate in the study (response rate 54.8%). The mean age of participants was 38.4 years (SD 12.5, range 19-65). Table 1 presents their characteristics. The lowest response rate to a single question was 99%.

Statistical properties of the main variables observed
The mean value of total WAI score was 40.6 points (SD 5.6, range

Results of univariate analysis of association between SOC-score and WAI
The data for univariate analysis of association were available for 685-691/713 participants (96.  Table 2.

Results of multivariate analysis of the association between SOC-score and WAI
Complete data for multivariate logistic regression analysis were available for 657/713 participants (92.1%  Table 3.

DISCUSSION
The results of our study revealed a statistically significant negative association between SOCS and PWAI, indicating that the lower the SOC is, the greater the odds of PWAI are. In other words, weak SOC could be a predictor of PWAI and improving SOC could significantly increase WA among nurses. Based on these results, we can propose SOC as an important and suitable intervention targeted outcome to consider in managing WA difficulties in clinical practice in nurses. Bearing in mind that stressful job demands are one of the major problems for nurses, identifying an independent modifiable coping resource is a great contribution.
The lack of similar studies makes it very difficult to compare our results. However, we can make some general comparisons. If we first want to make some comparisons in terms of the impact of SOC on WA, we can conclude that our results are consistent with the results of similar studies conducted on other population groups. To our knowledge, the relationship between SOC and WA was explored for example among unemployed people (23) and among Japanese workers employed in the information technology sector (24). Similar to our study, their findings indicated that low SOC was related to impaired WA (23,24). To this we can add that the results of our study showed something extremely important -SOC as an explanatory factor of WA from the univariate to the final multivariate model has not lost its power. On the contrary, the power increased even more. In parallel, all other factors that entered the final model lost a substantial portion of their power. This suggests that these factors interact with each other, while SOC remains an independent factor. We can also make some other comparisons. If we comment on the effect of age on WA, the final results of the present study showed that nurses older than 40 years have significantly higher odds for PWAI in comparison to the younger ones. This is consistent with the findings of other studies. Hatch et al. demonstrated, for example, that older age is a predictor of low WA among nurses from the southeast USA (25). Previous studies conducted among Croatian nurses also showed that WA decreases significantly with age (10,19). The reason could be found in a reduction of functional capacity of the individual due to the aging process and deficit in physical health (25). Contrary to our expectations, Rostamabadi et al. did not find an association between aging and WAI in their multivariate model among intensive care unit nurses (26). However, in their study, participants were aged only up to 39 years, while in our study a significant part was older than 40. Furthermore, it is important to explain why the authors of the present study considered it necessary for age to be dichotomized into two categories: ≤40 and >40 years. It was suggested that nurses over 40 years of age can experience visual and hearing impairments, weight gain, pain associated with musculoskeletal disorders and reduction in strength and flexibility (27) which can result in a reduced capacity to perform as well as younger nurses (27). Evidence showed that interventions targeting disease prevention and health maintenance from midlife and earlier may be effective ways to maintain nurses' WA with age (25). This should be a priority as the population of nurses is constantly aging (28).
To discuss the importance of self-assessed health conditions for WA, which proved to be important in our study, the most difficult thing was finding appropriate studies for comparison. Similar findings to our study regarding musculoskeletal diseases were reported among Brazilian nurses (29). The results of the systematic review and meta-analysis of Bernal et al. also showed that musculoskeletal diseases among nurses were the main causes of disability (30). As the high percentage of sick leave among healthcare workers can be largely attributed to musculoskeletal disorders, continuous workplace health-promoting measures to manage ergonomic risk factors in the aging nursing population would be of the utmost importance (31). SOC could also play an important role in these activities as it was shown that it influences nurses' healthy functioning at work (8).
Our study has some potential limitations. First, one can argue that this study involved participants from only one health institution. However, this institution is a typical large healthcare facility where a large number of nurses performing various tasks are employed. Consequently, this allows an in-depth study of health problems related to the nurses' workplace, which is a strength rather than a limitation. Second, one could argue the low response rate.  Table 3. Results of multivariate logistic regression analysis of the association between selected factors and PWAI in the study of impact of SOC on WA of Croatian nurses (n=657).
Legend: SOCS -sense of coherence score; CI -confidence interval; OR -odds ratio However, there is no agreed-upon standard for acceptable response rates (32). According to Babbie, cited by Draugalis et al., 50% is regarded as an acceptable response rate in social research postal surveys (32). Consequently, we assumed that the response rate achieved in our study still permits robust reliable conclusions to be drawn. Third, one could argue that the results are based only on nurses employed in a clinical setting. However, regardless of this, the results can also be roughly applied to some extent to nurses employed at the primary level of healthcare, considering the fact that it is possible to find to a certain extent an analogy between the work of nurses employed at the UHC (especially in the polyclinic departments) and primary healthcare nurses. Fourth, confounding factors may also be a subject of discussion. On the one hand, it could be pointed out that some are missing, e.g. minor children or relatives in care or a leading position. However, the selection was based on previous studies about SOC and WAI among nurses (16,19). Additionally, some confounding factors included seem to be too inclusive, e.g. mental disorders (covering very different disorders) or endocrine and metabolic disease. In these cases, we were limited by the WAI questionnaire, and such details were also beyond the scope of this study and may be the subject of more in-depth research in the future. In addition, for some confounders, one might argue that the categories were too broad to allow us to identify a risk area, e.g. work department, work length or number of cigarettes per day. In these cases, the aggregation of categories was indicated by the requirements of statistical methods. Next, one could argue how the missing values were dealt with. As the minimum response rate to an individual question was very high, making the possibility of bias due to missing values very small, data imputation methods were not applied. Finally, participants' motivation to respond is a limitation of the present study. It is unknown whether the nurses who participated in the study had the same level of SOC as the nurses who did not participate in the study. On the other hand, the study also has some important strengths. First, this study is the first to explore the association between SOC and WA in the nursing population. The results of this study might be especially useful for implementing health promotion in nurses' workplaces to preserve WA of this high-risk-for-stress population, as SOC could be seen as an important coping mechanism that nurse educators can integrate into nursing education. Second, the results of this study are applicable not only in Croatia but also in countries that were part of former Yugoslavia due to the similar transition process in departing from a common healthcare system. However, they are also applicable in general.
The findings of this study could serve as evidence for evidence-based planned public health measures for maintaining/enhancing good health among healthcare workers, especially nurses. Evidence about WA in the nursing profession demonstrated that WA is important for nurses in order to ensure good working conditions and to reduce work-related diseases and illness (33). As the evidence also demonstrated that the nursing profession is associated with stressful working conditions contributing to inadequate WA (34), monitoring SOC could be seen as a tool for the identification of nurses in need of support to cope better with stress, especially in those working environments where higher risk for burnout is expected, such as intensive care units (35). Moreover, as SOC could be considered an important factor of adjustment to difficulties among nurses with poor WAI, since people with strong SOC perceive a stressful situation as a challenge rather than as a threat (6), interventions for enhancing SOC could reduce the rates of poor WAI. An individual's SOC could be helpful in understanding the support needed in relation to health and WA and should be considered as an intervention outcome (36).
There is still much scope for further research in this area. First, it would make sense to extend the study to nurses employed in primary care. Additionally, it would make sense to extend the study to other healthcare profiles as well as to carry out an intervention study in which the intervention would be aimed at strengthening SOC in nurses who were found to have low SOC, and then reassess whether their WA has changed.

CONCLUSIONS
The present study proved an association between SOC and WA. SOC could be helpful in understanding the support needed in relation to health and WA, and should be considered as an intervention outcome. Improving SOC and consequently WA and implementing health promotion in nurses' workplaces could be an important way to increase WA.