이산시간 사건사분석을 적용한 사회복지 종사자의 이직 요인

초록

The purpose of this study was to identify factors influencing the actual turnover hazard of social welfare workers using discrete-time event history analysis and to provide practical and policy implications for reducing turnover in the social welfare workforce. STATA 18/SE was employed for the analysis, and the following methodological procedures were conducted. First, frequency analysis was performed to examine the demographic characteristics of the panel sample. Second, descriptive statistics and correlation analyses were conducted to investigate the characteristics and relationships among the major variables. Third, the Kaplan-Meier nonparametric method was applied to estimate the survival rate of social welfare workers. Finally, discrete-time event history analysis was employed to identify factors affecting turnover hazards. The findings revealed that no statistically significant predictors were identified in Model 1, which included only demographic variables. In Model 2, self-rated health status significantly increased the turnover hazard. In Model 3, which incorporated occupational factors, gender (male=1) and regular employment status (Permanent employee =1) were found to significantly affect turnover hazards. In the final model, which additionally included household-level factors, job satisfaction, self-rated health status, and regular employment status were identified as significant predictors of turnover hazards among social welfare workers. Based on these findings, practical and policy implications for reducing turnover among social welfare workers are discussed. The limitations of the study and suggestions for future research are also presented.

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