Organisations are accommodating four different social generations in the working environment. This poses a challenge for Human Resources departments to manage these diverse age cohorts in the workforce, as they are likely to have different needs, values and variables affecting their wellness.
The objective of the present study was to assess whether various age groups differ with regard to their sense of coherence and burnout, and whether age significantly moderates the relationship between sense of coherence and burnout.
Although the literature review suggests that age groups may differ with regard to their sense of coherence and burnout, the findings seem to be somewhat inconclusive in this regard. There also seems to be a paucity of research examining the interaction effect between sense of coherence, burnout and age.
A cross-sectional quantitative survey approach was used. A nonprobability convenience sample of adults (
The results showed that employees between the ages of 51 and 60 years of age experienced higher levels of comprehensibility and lower levels of reduced professional efficacy than their younger counterparts. The relationship between sense of coherence and exhaustion was also stronger for employees between 51 and 60 years old than for younger age categories.
The results of the study can be useful when planning human resource interventions to enhance the well-being of employees from different age groups.
The results of the study add new insights to the well-being literature by showing that employees’ age is important to consider when addressing their sense of coherence and burnout levels.
Life expectancy and the average age of the population are increasing (Johnson, Holdsworth, Hoel & Zapf, 2013). This demographic change has an impact on the age structures of the working population (Boehm & Kunze,
Mauno, Ruokalainen and Kinnunen (2013) investigated the moderating effect of age between various job stressors and well-being indicators. They found that younger employees seemed to be better equipped to handle job insecurity in comparison to their older counterparts. Older employees were better able to cope with work–family imbalance and high workload. Haley, Mostert and Els (
Studying the effects of age in the workplace is not a new phenomenon. Ageism and the influence of generations at work are well-researched domains (Hansen & Leuty,
Antonovsky (
Antonovsky (
Antonovsky (
Subsequent international studies on SOC stability over 30 years reveal mixed results, with some concurring the ‘age hypothesis’ (Feldt et al.,
Looking purely at the differences between age groups, Feldt
The incidence of burnout had increased over the past 30 years with dire consequences for organisations’ performance and employees’ health (Abdool Karrim Ismail, Coetzee, Du Toit, Rudolph & Joubert,
a persistent, negative work-related state of mind in normal individuals that is primarily characterised by exhaustion, which is accompanied by distress, a sense of reduced effectiveness, decreased motivation and the development of dysfunctional attitudes and behaviours at work. (p. 36)
More recently, burnout was described as a multidimensional construct that is evident in employees’ ‘experiences of physical and psychological exhaustion, depersonalisation, frustration and reduced sense of personal accomplishment’ (Abdool Karrim Ismail et al.,
South African research conducted by Smit (
Nevertheless, research findings with regard to the relationship between age and burnout have not been consistent. Brewer and Shapard (
South African studies are also in alignment with these international findings and indicated burnout to be more prominent for younger employees (Haley et al.,
The results with regard to the relationship between burnout and age therefore seem inconclusive, but since the theory of burnout suggests that burnout might be more of a threat for younger employees, the researchers formulated the second hypothesis to be tested as follows:
Research indicates overwhelming support for the mitigating impact of sense of coherence on burnout (Johnston et al.,
In investigating age as a moderator, Johnson et al. (
Zaniboni et al. (
You, Huang, Wang and Bao (
No research could be found that investigated age as a moderator in the relationship between sense of coherence and burnout.
The purpose of this study is therefore to determine the relationship between age, sense of coherence and burnout and to investigate the moderating effect of age in the relationship between sense of coherence and burnout. The third hypothesis to be tested in this study is as follows:
A cross-sectional survey design is used to achieve the objectives of this descriptive study. A cross-sectional design is an economical design that allows one to examine different criterion groups at a single point in time (Spector,
An availability sample (
Characteristics of participants in the sample.
Item | Category | Percentage | Frequency |
Gender | Male | 79.3 | 195 |
Female | 20.7 | 51 | |
Age | 18–30 | 35 | 86 |
31–40 | 26 | 64 | |
41–50 | 18.3 | 45 | |
51–60 | 18.7 | 46 | |
Marital status | Single | 19.5 | 48 |
Married | 67.9 | 167 | |
Divorced | 5.7 | 14 | |
Life partner | 2.4 | 6 | |
Widowed | 0.8 | 2 | |
Qualification | Grade 11 and lower | 0.8 | 2 |
Grade 11 and lower with trade certificate | 1.6 | 4 | |
Grade 12 | 7.3 | 18 | |
Grade 12 with trade certificate | 18.7 | 46 | |
Diploma | 14.6 | 36 | |
Graduate | 37 | 91 | |
Honours degree | 15 | 37 |
A biographical questionnaire was administered to obtain personal information about the participants such as their age, gender, marital status, qualification and job level.
The SPSS (version 22.0) program was used for the statistical analysis. Descriptive statistics, alpha coefficients, correlation and ANOVA were calculated to determine the relationship between age, sense of coherence and burnout. Hierarchical multiple regression with the enter method was then used to determine the moderating effects of age on the relationship between sense of coherence and burnout. The data met the standard assumptions with regard to multicollinearity, homoscedasticity and normality of residuals. Predictor, moderator, and outcome variables were z-standardised (Cohen, Cohen, West & Aiken,
The variables were entered in the following order: Step 1 contained sense of coherence as predictor; Step 2 contained sense of coherence and age as predictors; Step 3 contained sense of coherence, age and the interacting terms of the age categories multiplied by SOC as predictors.
Analyses were conducted for the three separate burnout dimensions. Cohen’ s (
Ethical clearance was obtained from Unisa to collect the data. The necessary permission was then obtained from the organisation’s senior management as well as Human Resources department to administer the instruments in the organisation. An electronic link to a web-based survey document was distributed via email, as well as an information sheet and an informed consent document. The consent form provided a brief introduction to the intent and background of the survey. Employees were reassured of the anonymity of the questionnaires, as well as the voluntary nature of the research. Participants were informed that the research results of the entire group may be shared with the management of the organisation, but that no individuals would be identified. The survey duration (approximately 30 minutes) and the survey procedure were discussed and the necessary permission documents were included.
Firstly, descriptive statistics, alpha coefficients and correlation were conducted to determine the relationship between sense of coherence and burnout. The results are displayed in
From
Descriptive statistics, alpha coefficients and Pearson correlations of the measuring instruments.
Scale | Mean | Standard deviation | α | 1 | 2 | 3 | 4 | 5 | 6 |
Comprehensibility | 47.48 | 10.51 | 0.81 | - | - | - | - | - | - |
Manageability | 50.33 | 8.79 | 0.78 | 0.64++ | - | - | - | - | - |
Meaningfulness | 43.33 | 7.45 | 0.79 | 0.44+ | 0.68++ | - | - | - | - |
Sense of coherence | 141.19 | 22.77 | 0.90 | 0.85++ | 0.90++ | 0.79++ | - | - | - |
Exhaustion | 10.60 | 6.89 | 0.91 | -0.32+ | -0.45+ | -0.51++ | -0.48+ | - | - |
Cynicism | 9.56 | 6.65 | 0.79 | -0.40+ | -0.56++ | -0.62++ | -0.60++ | 0.56++ | - |
Professional efficacy | 29.62 | 5.11 | 0.76 | 0.36+ | 0.33+ | 0.45+ | 0.44+ | -0.25 | -0.40+ |
All correlations were significant at the 0.01 level.
+, Correlation is practically significant
Next, an ANOVA was conducted to determine the degree to which sense of coherence and burnout differed with regard to the various age categories. The results are presented in
Analysis of variance between age categories, sense of coherence and burnout.
Category | Source of variation | Sum of squares | Mean square | Significance | ||
---|---|---|---|---|---|---|
Comprehensibility | Between groups | 1247.759 | 3 | 415.920 | 4.037 | 0.01 |
Within groups | 24314.891 | 236 | 103.029 | - | - | |
Total | 25562.650 | 239 | - | - | - | |
Manageability | Between groups | 226.156 | 3 | 75.385 | 0.986 | 0.40 |
Within groups | 18051.694 | 236 | 76.490 | - | - | |
Total | 18277.850 | 239 | - | - | - | |
Meaningfulness | Between groups | 272.790 | 3 | 90.930 | 1.636 | 0.18 |
Within groups | 13173.741 | 237 | 55.585 | - | - | |
Total | 13446.531 | 240 | - | - | - | |
Sense of coherence total | Between groups | 3271.724 | 3 | 1090.575 | 2.179 | 0.09 |
Within groups | 118112.609 | 236 | 500.477 | - | - | |
Total | 121384.333 | 239 | - | - | - | |
Exhaustion | Between groups | 235.023 | 3 | 78.341 | 1.671 | 0.17 |
Within groups | 11018.475 | 235 | 46.887 | - | - | |
Total | 11253.498 | 238 | - | - | - | |
Reduced professional efficacy | Between groups | 210.195 | 3 | 70.065 | 2.724 | 0.05 |
Within groups | 6070.738 | 236 | 25.723 | - | - | |
Total | 6280.933 | 239 | - | - | - | |
Cynicism | Between groups | 346.949 | 3 | 115.650 | 2.712 | 0.05 |
Within groups | 10108.362 | 237 | 42.651 | - | - | |
Total | 10455.311 | 240 | - | - | - |
From
Next, the main and interaction effects of sense of coherence and age on exhaustion, cynicism and professional efficacy were tested. In order to eliminate the possibility of multicollinearity, only the sense of coherence total score was included in the regression model. The results are displayed in
Moderated multiple regression with exhaustion as the dependent variable.
Model | Variable | Unstandardised coefficients | Standardised coefficients | Adjusted |
|||||
B | SE | Beta | |||||||
1 | Constant | 31.12 | 2.49 | - | 12.51 | 0.00 | 0.48 | 0.23 | 0.22 |
Sense of coherence | -0.15 | 0.02 | -0.48 | -8.33 | 0.00* | - | - | - | |
2 | Constant | 30.29 | 2.50 | - | 12.11 | 0.00 | 0.50 | 0.25 | 0.23 |
Sense of coherence | -0.15 | 0.02 | -0.48 | -8.29 | 0.00* | - | - | - | |
Age 31–40 | 2.30 | 1.00 | 0.15 | 2.31 | 0.02* | - | - | - | |
Age 41–50 | 0.74 | 1.18 | 0.04 | 0.66 | 0.51 | - | - | - | |
Age 51–60 | 0.71 | 1.11 | 0.04 | 0.64 | 0.52 | - | - | - | |
3 | Constant | 29.85 | 2.46 | - | 12.16 | 0.00 | 0.54 | 0.29 | 0.27 |
Sense of coherence | -0.14 | 0.02 | -0.47 | -8.23 | 0.00* | - | - | - | |
Age 31–40 | 2.191 | 0.98 | 0.14 | 2.23 | 0.03* | - | - | - | |
Age 41–50 | 0.25 | 1.10 | 0.01 | 0.23 | 0.82 | - | - | - | |
Age 51–60 | 1.09 | 1.10 | 0.06 | 1.00 | 0.32 | - | - | - | |
Sense of coherence x age 31–40 | -0.65 | 0.47 | -0.09 | -1.39 | 0.17 | - | - | - | |
Sense of coherence x age 41–50 | 0.78 | 0.46 | 0.11 | 1.71 | 0.09 | - | - | - | |
Sense of coherence x age 51–60 | -0.89 | 0.43 | -0.14 | -2.08 | 0.04* | - | - | - |
*, All correlations were significant at the 0.01 level.
It is clear from
Interaction between sense of coherence and age with exhaustion as dependent variable.
Moderated multiple regression with cynicism as the dependent variable.
Model | Variable | Unstandardised coefficients | Standardised coefficients | Adjusted |
|||||
B | SE | Beta | |||||||
1 | Constant | 34.34 | 2.17 | - | 15.85 | 0.00 | 0.60 | 0.36 | 0.36 |
Sense of coherence | -0.18 | 0.02 | -0.60 | -11.56 | 0.00* | - | - | - | |
2 | Constant | 33.40 | 2.18 | - | 15.34 | 0.00 | 0.62 | 0.38 | 0.37 |
Sense of coherence | -0.17 | 0.02 | -0.60 | -11.41 | 0.00* | - | - | - | |
Age 31–40 | 2.23 | 0.87 | 0.15 | 2.58 | 0.01* | - | - | - | |
Age 41–50 | 0.40 | 0.98 | 0.02 | 0.41 | 0.68 | - | - | - | |
Age 51–60 | 0.38 | 0.97 | 0.02 | 0.39 | 0.70 | - | - | - | |
3 | Constant | 33.40 | 2.20 | - | 15.21 | 0.00 | 0.62 | 0.38 | 0.36 |
Sense of coherence | -0.17 | 0.02 | -0.60 | -11.28 | 0.00* | - | - | - | |
Age 31–40 | 2.17 | 0.88 | 0.15 | 2.48 | 0.01* | - | - | - | |
Age 41–50 | 0.37 | 0.99 | 0.02 | 0.37 | 0.71 | - | - | - | |
Age 51–60 | 0.33 | 0.99 | 0.02 | 0.33 | 0.74 | - | - | - | |
Sense of coherence x age 31–40 | -0.27 | 0.42 | -0.04 | -0.65 | 0.52 | - | - | - | |
Sense of coherence x age 41–50 | -0.07 | 0.41 | -0.01 | -0.19 | 0.85 | - | - | - | |
Sense of coherence x age 51–60 | -0.05 | 0.39 | -0.01 | -0.14 | 0.89 | - | - | - |
*, All correlations were significant at the 0.01 level.
From the ANOVA analyses, it follows that the regression model significantly predicted cynicism at every step (Step 1:
It is clear from
Moderated multiple regression with professional efficacy as the dependent variable.
Model | Variable | Unstandardised coefficients | Standardised coefficients | Adjusted |
|||||
B | SE | Beta | |||||||
1 | Constant | 15.67 | 1.90 | - | 8.27 | 0.00 | 0.43 | 0.19 | 0.19 |
Sense of coherence | 0.10 | 0.01 | 0.43 | 7.41 | 0.00* | - | - | - | |
2 | Constant | 15.75 | 1.92 | - | 8.21 | 0.00 | 0.45 | 0.20 | 0.19 |
Sense of coherence | 0.09 | 0.01 | 0.42 | 7.01 | 0.00* | - | - | - | |
Age 31–40 | 0.21 | 0.77 | 0.02 | 0.27 | 0.79 | - | - | - | |
Age 41–50 | 0.89 | 0.86 | 0.07 | 1.03 | 0.30 | - | - | - | |
Age 51–60 | 1.50 | 0.85 | 0.12 | 1.75 | 0.08 | - | - | - | |
3 | Constant | 15.48 | 1.91 | - | 8.13 | 0.00 | 0.48 | 0.23 | 0.20 |
Sense of coherence | 0.10 | 0.01 | 0.42 | 7.19 | 0.00 | - | - | - | |
Age 31–40 | 0.33 | 0.76 | 0.03 | 0.44 | 0.66 | - | - | - | |
Age 41–50 | 0.93 | 0.86 | 0.07 | 1.08 | 0.28 | - | - | - | |
Age 51–60 | 1.81 | 0.86 | 0.14 | 2.12 | 0.04* | - | - | - | |
Sense of coherence x age31–40 | 0.59 | 0.36 | 0.11 | 1.65 | 0.10 | - | - | - | |
Sense of coherence x age 41–50 | -0.04 | 0.36 | -0.01 | -0.11 | 0.92 | - | - | - | |
Sense of coherence x age 51–60 | -0.44 | 0.33 | -0.09 | -1.32 | 0.19 | - | - | - |
*, All correlations were significant at the 0.01 level.
From the ANOVA analyses, it follows that the regression model significantly predicted professional efficacy at every step (Step 1:
It is clear from
The purpose of this study was to determine the relationship between age, sense of coherence and burnout and to determine if age moderated the relationship between sense of coherence and burnout.
Hypothesis 1 states that older age categories would have higher SOC levels. The current study’s findings partially support Hypothesis 1. Results revealed that employees in the 51–60-year-old age category experienced higher levels of comprehensibility than employees in the 18–30 year old age category. This seems to be in line with the findings of Feldt et al. (
Hypothesis 2 states that older age categories would have lower levels of burnout. Looking only at the results of the ANOVA, it seems that the findings of this study did not support Hypothesis 2 and appeared to be in alignment with the findings of Bezuidenhout and Cilliers (
Hypothesis 3 states that age moderates the relationship between SOC and burnout. The findings of the current study partially support Hypothesis 3 as only one indirect effect was found. The 51- to 60-year-old age category moderated the relationship between SOC and exhaustion. The interaction showed an enhancing effect. It seems that having a high level of SOC were more beneficial to prevent exhaustion for employees older than 51 years of age when compared to younger employees with the same level of SOC. These results seem to be in alignment with that of Johnson et al. (
A practical contribution of this study is an increased understanding of the implications of an age-diverse group of employees when developing and implementing well-being interventions in an organisation. The results of this study seems to confirm that employees that are 51 years and older experience higher levels of well-being and lower levels of burnout than their younger colleagues (Haley et al.,
The first limitation of the study is that it made use of a cross-sectional design when the data were collected. A longitudinal study could indicate causal relationships regarding age, burnout and SOC. The nonprobability sample size is also quite small and this limits the generalisability of the results. Larger, random samples in other industries could be included in future studies to see if the difference in SOC and burnout could be generalised to other populations as well. Participants were not asked to indicate their job tenure in the study. Because of the relationship between age and work experience, this could have been an important variable to consider in this study and future research could investigate this aspect in more detail.
In conclusion, it seems that employees that are 51 years and older experienced higher levels of comprehensibility, lower levels of reduced professional efficacy and lower levels of exhaustion, especially when coupled with a high SOC. On the other hand, it seems that employees between 31 and 40 years old might be more susceptible to exhaustion and cynicism.
The authors declare that they have no financial or personal relationships which may have inappropriately influenced them in writing this article.
S.v.d.W. (University of South Africa) conceptualised the research problem of the current study, conducted the statistical analysis and literature review and wrote up the research article. C.H. (SASOL) and A.V. (SASOL) collected the data.