Studies on the association between job satisfaction and depression have often been reported. However, no study has examined how job satisfaction impacts depression while considering satisfaction with other aspects of life. In this study, we evaluated the effect of job satisfaction on depression after adjusting for satisfaction with other domains of life.
We used data from the 16th wave of the Korean Welfare Panel Study. A total of 3568 current employees without depression who completed a survey were included. Depression was measured using the abbreviated version of the CES-D scale. Various types of satisfaction, including job satisfaction, were measured using single-item questions and a 5-point Likert scale. The association between job satisfaction and depression after considering satisfaction with other life domains was analyzed using a multiple logistic regression model.
Crude models showed a significant association between job satisfaction and depression in males (odds ratio [OR]: 7.90; 95% confidence interval [CI]: 4.11–15.23) and females (OR: 7.12; 95% CI: 4.40–11.50). When adjusted for sociodemographic factors, health-related factors, and work-related factors, the association remained significant in males (OR: 6.20; 95% CI: 3.10–12.41) and females (OR: 6.28; 95% confidence interval (CI): 3.79–10.40). However, when satisfaction with other life domains was included, the association remained significant only in females (OR: 3.55; 95% CI: 1.93–6.50).
This study shows an association between job satisfaction and depression in Korean employees. However, when satisfaction with other life domains was considered, this association remained significant only in women. Regular screening of job satisfaction should be considered as a means of preventing and managing depression among female employees.
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Research on job training and job satisfaction has been conducted from various perspectives. Job training is thought to be associated with job satisfaction, which is known as an important factor for depression among workers. We hypothesized that job training duration could influence depression through potential mediators (job satisfaction, motivation to work, and work engagement).
This study encompassed participants from the sixth Korean Working Conditions Survey (KWCS), conducted between 2020 and 2021. To show the relationships between demographic or occupational characteristics and risk of depression, a χ2 test was conducted. The association between job training duration, potential mediators, and risk of depression was analyzed by constructing multiple logistic regression models. The mediating effects of potential mediators on job training duration and risk of depression was evaluated with flexible mediation analysis with weighting-based methods.
The final study population consisted of 25,294 participants. Longer job training duration significantly decreased risk of depression after adjusting for confounders. In the group that received the longest job training duration (≥ 10 days), compared with the group without job training, the odds ratio (OR) for high risk of depression was 0.46 (95% confidence interval [CI], 0.39–0.54). Each three potential mediators showed statistically significant indirect effects and direct effect. Although indirect effects were not strong compared to direct effect, motivation to work had the strongest mediating effect in this study, with an OR of 0.94 (95% CI, 0.92–0.95).
Job training duration was found to have a statistically significant negative association on the risk of depression, and three mediators partially mediating this effect. Although the mechanism was unknown, our findings suggest that job training has a positive influence on workers' mental health. Furthermore, by suggesting the possibility of other pathways existing between job training and depression, we provide directions for future research.
The purpose of this study is to assess the validity and reliability of general job satisfaction (JS) in the Korean Labor and Income Panel Study (KLIPS).
We used the data from the 17th wave (2014) of the nationwide KLIPS, which selected a representative panel sample of Korean households and individuals aged 15 or older residing in urban areas. We included in this study 7679 employed subjects (4529 males and 3150 females). The general JS instrument consisted of five items rated on a scale from 1 (strongly disagree) to 5 (strongly agree). The general JS reliability was assessed using the corrected item-total correlation and Cronbach’s alpha coefficient. The validity of general JS was assessed using confirmatory factor analysis (CFA) and Pearson’s correlation.
The corrected item-total correlations ranged from 0.736 to 0.837. Therefore, no items were removed. Cronbach’s alpha for general JS was 0.925, indicating excellent internal consistency. The CFA of the general JS model showed a good fit. Pearson’s correlation coefficients for convergent validity showed moderate or strong correlations.
The results obtained in our study confirm the validity and reliability of general JS.
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The purposes of this study are 1) to measure the prevalence of smoking according to weekly work hours by using data from the Korean Labor and Income Panel Study (KLIPS), and 2) to explain the cause of high smoking prevalence among those with short or long work hours by relative explanatory fraction.
Data from a total of 2,044 male subjects who responded to the questionnaire in the 10th year (2007) and 11th year (2008) of the Korean Labor and Income Panel Study were used for analysis. Current smoking, smoking cessation, continuous smoking, start of smoking, weekly work hours, occupational characteristics, sociodemographic and work-related factors, and health behavior-related variables were analyzed. Log-binomial regression analysis was used to study the relationship between weekly work hours and smoking behaviors in terms of the prevalence ratio.
The 2008 age-adjusted smoking prevalence was 64.9% in the short work hours group, 54.7% in the reference work hours group, and 60.6% in the long work hours group. The smoking prevalence of the short work hours group was 1.39 times higher than that of the reference work hours group (95% confidence interval of 1.17-1.65), and this was explained by demographic variables and occupational characteristics. The smoking prevalence of the long work hours group was 1.11 times higher than that of the reference work hours group when the age was standardized (95% confidence interval of 1.03-1.19). This was explained by demographic variables. No independent effects of short or long work hours were found when the variables were adjusted.
Any intervention program to decrease the smoking prevalence in the short work hours group must take into account employment type, job satisfaction, and work-related factors.
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