KWDI Korean Women’s Development Institute

Job stress in modern times has been reported to be associated with many diseases such as musculoskeletal disorder, hypertension, coronary heart disease, mental stress and burnout. In Korea, diseases resulting from job stress have been rapidly increasing since the women have actively participated in the labor market.

Women working in the service sector come from lower social class compared to those employed in other sectors. This could leave women in the service sector vulnerable to job stress because social determinants of health may negatively affect health condition. 

The purpose of this study is to investigate the causes, the level of job stress and socio-psychological well-being of working women in the service sector of Korea. For the purpose of comparison, we have examined men working at the service sector as well. Lastly, we also have searched for the best job stress management policy by reviewing the cases of England, United States, and Japan.   

Specifically, we have examined the level of job stress and socio-psychological well-being dependent upon various social determinants such as socio-demographics, health behaviors, job related characteristics, role conflict between workplace and home, emotional labor and sexual harassment.

Using a survey method, we have collected data from women (n=900) and men (n=400) working in the service sector at offices located in 6 major provinces of Korea. In order to correctly estimate the level of job stress, we have capitalized job stress-related survey items compiled by Korean Society of Occupational Stress (KSOS).  The survey items for job stress were proven to be significantly correlated to the stress level in Korea because they were based on not only well-known theory such as Karasek model but also the Korean culture associated with causes of job stress.  Job stress questionnaire in the survey covered 8 areas such as physical environment, job demand, job autonomy, unstable employment, relationship conflict, organizational system, insufficient reward and organizational culture.  We have also used Short Form of Psychological Well-being Index (SF-PWI) to estimate socio-psychological well-being of working women and men in the service sector. SF-PWI also proved significant correlation between mental and physical conditions and job stress.

For analytical methods, descriptive and multivariate analysis were used. All statistical models employed in this study were separated by gender. For descriptive analysis, job stress as well as socio-psychological well-being was analyzed using sociodemographics, health behaviors, job related characteristics, role conflict between workplace and home, emotional labor and sexual harassment. One-way ANOVA analysis was used for the bivariate analysis and multiple hierarchical regression analysis was used for the multivariate analysis.    

The result of this study showed that job stress score among workers employed in the service sector (47.06) was higher than that of professional (44.48) and office workers (45.62), although the score was similar to that of blue collar workers. Job stress of women showed decreasing tendency for those who are married (ß=-2.28, p<0.05) and have longer period of work on duty (ß=-1.99, p<0.05). However, job stress showed increasing tendency for those who experience sexual harassment (ß=5.13, p<0.001) and feel pressure of work at home (ß=3.12, p<0.01). For men service workers, job stress showed decreasing trend for those who have higher educational attainment (ß=-2.22, p<0.01) and increasingtendency for those who are closer to type A (ß=4.07, p<0.001) and are irregular and temporary workers (ß=2.34, p<0.01). Finally, job stress showed increasing trend for those who are getting old regardless of the gender (women, ß=2.01, p<0.05 men, ß=3.50, p<0.001).

Socio-psychological well-being of women and men service workers were influenced by different job stressors. Psychological well-being of women service workers were negatively affected (ß=5.23, p<0.001) when they do not receive enough monetary or psychological reward for their work. Socio-psychological well-being of men service workers were negatively affected (ß=2.66, p<0.001) when organizational system did not meet their needs well. Lastly, employment (women, ß=5.04, p<0.001 men, ß=3.50, p<0.001), centralized organizational culture and collective organizational culture (women, ß=4.43, p<0.001 men, ß=3.26, p<0.01) negatively influenced socio-psychological health for both women and men service workers.

Policy-related implication of the study is that gendered management of job stress is imperative in obtaining better results of job stress intervention. Also, gender based analysis, evaluation and management of job stress should be carried out to enhance gender equality. Most importantly, an effective policy of preventing and managing job stress should be implemented to respond to service workers' needs by actively reshaping the work environment.     

Hierarchical Multiple Regression of Selected Variables on Job Stress for Women

Variables	Model 1		Model 2		Model 3		Model 4
	B	T	B	T	B	T	B	T
Age	0.03	0.52	0.02	0.38	0.05	1.02	0.11	2.01*
Education	-0.08	-0.09	0.52	-2.04*	-0.08	-1.92	-0.07	-1.69
Married	0.10	2.20*	0.10	2.19*	0.12	2.66**	-0.16	-2.28*
Income	-0.06	-1.62	-0.06	-1.52	-0.04	-0.95	-0.03	-0.80
Type A	0.08	2.30*	0.08	2.25*	0.07	2.10*	0.07	1.95
Smoking			0.00	0.12	0.00	0.03	-0.00	-0.11
Drinking			0.02	0.51	0.01	0.41	0.01	0.17
Exercise			-0.07	-2.10*	-0.07	-2.07*	-0.07	-2.04*
Number of employees					0.02	0.48	0.02	0.52
Temporary position					0.06	1.61	0.04	1.28
Non-shift worker					-0.06	-1.74	-0.06	-1.65
Period of work					-0.08	-1.87	-0.08	-1.99*
Sexual harassment					0.18	5.24***	0.17	5.13***
Emotional labor					0.01	0.21	-0.01	-0.16
Pressure of work at home							0.18	3.12**
Pressure of childcare							0.15	2.59
Pressure of caretaking the sick and the old							-0.05	-1.41
Constant	44.60		45.99		43.85		42.94
F	5.85		4.26		5.20		6.17
R2	0.03		0.04		0.08		0.11
*P<0.05, **P<0.01, ***P<0.001

Hierarchical Multiple Regression of Selected variables

Variables	model 1		model 2		model 3		model 4		mdoel 5
	B	T	B	T	B	T	B	T	B	T
Age	-0.08	-1.59	-0.05	-0.98	-0.03	-0.49	-0.04	-0.93	-0.08	-1.64
Education	-0.07	-1.65	-0.03	-0.72	-0.03	-0.62	-0.01	-0.16	0.00	-0.12
Married	-0.06	-1.26	-0.05	-1.15	-0.04	-0.94	-0.09	-2.20*	0.04	0.55
Income	-0.10	-2.63**	-0.11	-2.86**	-0.09	-2.22*	-0.04	-1.06	-0.04	-1.14
Type A	0.20	5.74***	0.19	5.68***	0.19	5.37***	0.18	5.39***	0.18	5.31***
Smoking			0.02	0.46	0.01	0.27	-0.01	-0.22	0.00	-0.10
Drinking			0.02	0.71	0.02	0.62	0.03	0.87	0.03	1.04
Exercise			0.16	4.67***	0.15	4.62***	0.18	5.99***	0.18	5.93***
Number of Employees					0.03	0.82	0.02	0.56	0.02	0.54
Temporary position					0.06	1.75	0.05	1.54	0.05	1.75
Non-shift worker					0.02	0.45	0.04	1.23	0.03	1.12
Period of work					-0.06	-1.39	-0.02	-0.65	-0.03	-0.70
Sexual harassment					0.11	3.18**	0.03	1.06	0.03	1.09
Emotional labor					0.04	1.27	0.03	0.94	0.04	1.13
Physical  environment							0.02	0.71	0.03	1.01
Job demand							-0.01	-0.37	-0.01	-0.21
Job autonomy							0.00	0.03	0.00	0.12
Relationship conflict							0.06	1.77	0.07	1.96
Unstable  employment							0.17	5.07***	0.17	5.04***
Organizational system							0.04	0.97	0.04	1.02
Insufficient  reward							0.22	5.09***	0.22	5.23***
Organizational culture							0.16	4.64***	0.15	4.43***
Pressure of work at  home									0.00	0.09
Pressure of childcare									-0.15	-2.77**
Pressure of caretaking the sick and the old									0.04	1.25
Constant	19.65		15.42		10.70		-5.36		-5.62
F	11.44		10.13		7.11		14.05		12.86
R2	0.06		0.09		0.11		0.27		0.28
*P<0.05, **P<0.01, ***P<0.001

On Socio-Psychological Distress for Women

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