Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 + 1462 word(s) 1462 2022-01-27 06:52:23 |
2 Format Change Meta information modification 1462 2022-01-27 10:22:17 | |
3 Format Change Meta information modification 1462 2022-01-27 10:23:38 |

Video Upload Options

Do you have a full video?

Confirm

Are you sure to Delete?
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Lam, L. Work-Related Burnout among Corporate Employees. Encyclopedia. Available online: https://encyclopedia.pub/entry/18887 (accessed on 29 March 2024).
Lam L. Work-Related Burnout among Corporate Employees. Encyclopedia. Available at: https://encyclopedia.pub/entry/18887. Accessed March 29, 2024.
Lam, Lawrence. "Work-Related Burnout among Corporate Employees" Encyclopedia, https://encyclopedia.pub/entry/18887 (accessed March 29, 2024).
Lam, L. (2022, January 27). Work-Related Burnout among Corporate Employees. In Encyclopedia. https://encyclopedia.pub/entry/18887
Lam, Lawrence. "Work-Related Burnout among Corporate Employees." Encyclopedia. Web. 27 January, 2022.
Work-Related Burnout among Corporate Employees
Edit

Work is an essential part of our daily life. It has been estimated that on average, full-time workers in OECD countries spend about 37% of their time working in a normal day.  Burnout is classified as an occupational phenomenon, not as a medical condition, in the 11th version of the International Classification of Diseases (ICD-11). It is defined as: ”a syndrome conceptualized as resulting from chronic workplace stress that has not been successfully managed”.

burnout work environment risk factors protective factors COVID-19

1. Introduction

In the past two years, due to the global crisis of the COVID-19 pandemic, the work life of the working population in many countries has been changed drastically. For some, the pandemic has caused the cessation of work because of the closure of businesses and redundancy, or as a result of restructuring and downsizing. Some workers may experience a change in their status, position, or a total departure from the industry in which they have been working for many years. The changes in the macro- and micro-work environments may pose new challenges to workers and affect modes of operation in many different industries. As a result, different influencing factors of work-related burnout may arise under this unusual circumstance. As part of a government-funded intervention program for enhancing mental health and wellbeing in the workplace, data on personal and environmental variables were collected at the baseline, post-intervention, and 3-month follow-up [1]. The current study aims to report both environmental and personal factors that are associated with work-related burnout in a population of corporate employees who managed to retain their jobs amidst the global crisis.

2. Current Research on Work-Related Burnout

A total of 456 participants were recruited to the trial from six corporations of different natures of business including real estate, insurance, property management, and other industries. Baseline data collected prior to the randomisation of participants in the intervention and control groups of the CRCT were complete without any refusals to respond to the survey. The descriptive statistics on the demographic, health, and work-related variables, and the outcome variables, namely work-related burnout were summarised in Table 1. As shown, the average age of participants was 38.3 years (s.e. = 2.4) with slightly more females than males (54.6% vs. 45.4%), with the majority attaining an education level of a university degree or above (n = 370), and less than half were married (48%). For work-related variables, all participants worked full-time except three, with an average duration in the industry of 8.3 years (s.e. = 1.1) and about one-third (n = 143) could work flexible hours. The majority of participants were non-smokers (95.6%), light or non-drinkers (92.2%), and more than two-thirds exercised regularly (n = 342), with only a small proportion (8.2%) requiring three or more days of sick leaves in the past three months. In terms of the work environment measures by the Woo’s Work Environmental Scale, the mean standardised scores of nearly all domains were close to 50 with 48.2 (s.e. = 2.8) for work involvement, 51.3 (s.e. = 1.6) for co-worker cohesion, 54.3 (s.e. = 4.7) and 50.1 (s.e. = 2.1) for supervisor support and work pressure, respectively. Workplace management control was the only domain that scored the highest with an average standardised score of 60.5 (s.e. = 5.0). However, slightly more than half (52.7%) of participants indicated that they had contemplated resigning from their company in the past three months. Regarding the outcome measures of this study, namely work-related burnout, the average scores of the three domains including emotional exhaustion, depersonalisation, and professional accomplishment were 21.6 (s.e. = 0.4), 6.9 (s.e. = 0.4), and 27.8 (s.e. = 1.1), respectively. These represented about 60% of participants rated at a moderate (29.2%) to a high level (31.5%) on emotional exhaustion, about 45% on depersonalisation (moderate/high: 29.9%/15.4%), and only 32% on professional accomplishment (moderate/high: 20.9%/11.0%) following the classification provided by the scale authors.
Table 1. Descriptive statistics on participants’ demographic and other variables (N = 456).
Participants’ Characteristics Frequency (%) or Mean (s.e.) a
Demographics  
Age (years) 38.3 (2.4)
Sex  
Male 224 (45.4%)
Female 232 (54.6%)
Education level  
University or above 370 (64.5%)
Secondary and post-secondary 86 (35.5%)
Marital status  
Married 177 (48.0%)
Others 279 (52.0%)
Working duration (years) 8.3 (1.1)
Full time  
Yes 453 (97.4%)
No 3 (2.6%)
Flexible hours  
Yes 143 (36.3%)
No 313 (63.7%)
Health-related variables  
Regular exercise  
Yes 342 (80.6%)
No 106 (19.4%)
Smoker  
Yes 16 (4.4%)
No 436 (95.6%)
Drinker  
Moderate/heavy drinker 32 (7.8%)
Light drinker 411 (92.2%)
Sick days in the past 3 months  
Less than 3 days 419 (91.8%)
3 days or more 29 (8.2%)
Work environment-related variables  
Intended to resign  
Yes 244 (52.7%)
No 212 (47.3%)
Standardised score of work involvement 48.2 (2.8)
Standardised score of co-worker cohesion 51.3 (1.6)
Standardised score of supervisor support 54.3 (4.7)
Standardised score of work pressure 50.1 (2.1)
Standardised score of management control 60.5 (5.0)
Outcome variables  
Burnout—Emotional exhaustion 21.6 (0.4)
Burnout—Depersonalisation 6.9 (0.4)
Burnout—Professional accomplishment 27.8 (1.1)
a Adjusted for the clustering effect.
The bivariate relationships between the three domains of work-related burnout and participants’ demographics, health and work-related variables, and the work environment variables were investigated with the results summarised in Table 2. As shown, with only adjustment for the clustering effect, a different set of variables were associated with each of the three domains. For example, age, education level, and working duration were related to emotional exhaustion but not the other two domains. On the other hand, intention to resign and supervisor’s support was associated with all three. (Table 2) These variables, with others that satisfied the pre-set selection criteria, were included in further analyses.
Table 2. Correlation or mean difference (s.e.) and unadjusted associations between demographic, health-related, work environment-related variables, and burnout.
Participants’ Characteristics Results on the Association a
Demographics Emotional Exhaustion Depersonalisation Professional Accomplishment
Age r = −0.25 * r = −0.21 r = 0.18
Sex µdiff = −0.91 (1.30) µdiff = 0.44 (0.96) µdiff = 1.31 (1.47)
Education level µdiff = 3.58 (1.03) * µdiff = −0.91 (1.30) µdiff = 0.56 (0.58)
Marital status µdiff = 1.80 (1.18) µdiff = 0.02 (1.18) µdiff = −0.44 (0.81)
Working duration µdiff = −0.18 (0.05) * µdiff = −0.08 (0.06) µdiff = 0.22 (0.11)
Full time µdiff = 4.99 (0.43) ** µdiff = 3.11 (0.46) ** µdiff = 6.01 (1.16) **
Flexible hours µdiff = 1.75 (1.00) µdiff = −0.31 (0.59) µdiff = 1.86 (1.92)
Health-related variables      
Regular exercise µdiff = 4.65 (1.30) * µdiff = 0.93 (1.64) µdiff = −2.62 (0.61) *
Smoker µdiff = 7.27 (2.97) µdiff = 7.69 (2.92) µdiff = −0.69 (0.95)
Drinker µdiff = 2.27 (3.00) µdiff = 0.66 (1.51) µdiff = 3.65 (1.04) *
Sick days in the past 3 months µdiff = 9.24 (6.20) µdiff = 3.63 (1.54) µdiff = −6.01 (1.97) *
Work environment-related variables      
Intended to resign µdiff = −5.65 (1.53) * µdiff = −3.08 (0.88) * µdiff = 3.82 (0.34) **
Work involvement r = −0.22 r = −0.25 * r = 0.16
Co-worker cohesion r = −0.26 * r = 0.25 * r = 0.08
supervisor support r = − 0.18 * r = −0.23 * r = 0.16 **
Work pressure r = 0.48 ** r = 0.37 * r = −0.05
Management control r = 0.13 r = 0.11 r = −0.13 *
a Adjusted for the clustering effect. * p < 0.05; ** p < 0.01.
Results of the final models of the Multinomial logistic regression analyses on factors associated with the three domains of work-related burnout were summarised in Table 3. As shown, a slightly different set of variables was associated with different levels of the three burnout domains. For emotional exhaustion, three variables were retained in the final model, but were only significantly related to the high level of this domain of burnout. This included age, co-worker cohesion, and work pressure, with the former two negatively, and work pressure positively, associated with emotional xxhaustion (OR = 1.09, 95%C.I. = 1.05–1.13). These results suggested that an increase in age and co-worker cohesion was related to a decrease in the emotional exhaustion of workers, and an increase in work pressure was associated with an increase in emotional exhaustion. For depersonalisation, four variables were identified as being related to different levels of this domain, At the moderate level of depersonalisation, age, co-worker cohesion, and work pressure were significant in the same direction as with emotional exhaustion, having odds ratios of 0.95 (95%C.I. = 0.92–0.99), 0.98 (95%C.I. = 0.97–0.99), and 1.03 (95%C.I. = 1.00–1.06), respectively. At the high level of depersonalisation, a slightly different set of variables was observed, with age and co-worker cohesion remaining, and work involvement replacing work pressure. All three variables were negatively associated with the high level of depersonalisation with odds ratios of 0.88 (95%C.I. = 0.82–0.95), 0.97 (95%C.I. = 0.95–0.98), and 0.98 (95%C.I. = 0.97–0.99), respectively. In terms of the professional sccomplishment domain, two variables were retained in the final model, namely drinking and resignation intention. These variables were both positively related to the moderate level of the domain only with odds ratios of 2.87 (95%C.I. = 1.17–7.36) and 1.66 (95%C.I. = 1.10–2.51), respectively.
Table 3. Results obtained from the final model of the multinomial logistic regression analyses.
Variables Retained in the Final Model OR (95%C.I.) a Significance
Outcome: Emotional exhaustion    
Moderate    
Age 0.96 (0.93–1.0) t = −2.34, p = 0.079
Co-worker cohesion 0.99 (0.96–1.02) t = −1.25, p = 0.278
Work pressure 1.01 (0.98–1.04) t = 1.17, p = 0.306
High    
Age 0.92 (0.88–0.96) t = −5.68, p = 0.005
Co-worker cohesion 0.98 (0.97–0.99) t = −5.78, p = 0.004
Work pressure 1.09 (1.05–1.13) t = 5.83, p = 0.004
Outcome: Depersonalisation    
Moderate    
Age 0.95 (0.92–0.99) t = −3.49, p = 0.025
Work involvement 0.99 (0.98–1.01) t = −0.40, p = 0.712
Co-worker cohesion 0.98 (0.97–0.99) t = −7.99, p = 0.001
Work pressure 1.03 (1.00–1.06) t = 3.05, p = 0.038
High    
Age 0.88 (0.82–0.95) t = −4.65, p = 0.010
Work involvement 0.97 (0.95–0.98) t = −6.40, p = 0.003
Co-worker cohesion 0.98 (0.97–0.99) t = −3.38, p = 0.028
Work pressure 1.06 (0.98–1.15) t = 2.14, p = 0.099
Outcome: Professional Accomplishment    
Moderate    
Drinker 2.87 (1.17–7.36) t = 3.10, p = 0.036
Intended to resign 1.66 (1.10–2.51) t = 3.41, p = 0.027
High    
Drinker 2.01 (0.43–9.45) t = 1.25, p = 0.278
Intended to resign 1.35 (0.53–3.42) t = 0.89, p = 0.424
a Adjusted for the clustering effect.

3. Summary

Burnout in this sample was prevalent with 60% of participants rated at a moderate to a high level on emotional exhaustion. Results from the multiple linear regression analyses suggested that different factors were related to different components of burnout. For example, age, work involvement, co-worker cohesion, and work pressure were associated with emotional exhaustion and depersonalisation while others were related to professional accomplishment. The overall results suggested that the work environment is of influential importance to the burnout of employees. However, although the study was conducted during the peak of the COVID-19 pandemic, the factors identified as relating to workplace burnout do not differ much from those identified in a crisis time. Implications of the results were discussed. 

References

  1. Lam, L.T.; Wong, P.; Lam, M.K.P. Protocol for a phase III wait-listed cluster randomised controlled trial of an intervention for mental wellbeing through enhancing mental health literacy and improving work friendliness in Hong Kong. BMC Trial 2019, 20, 672.
More
Information
Contributor MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
View Times: 468
Revisions: 3 times (View History)
Update Date: 27 Jan 2022
1000/1000