Turnover intention and its associated factors among health extension workers in illubabora zone, south west Ethiopia

Abstract

Background: The efficiency and quality of a health service can be compromised by turnover intention. Employees who intend to leave their job may identify themselves in the form of withdrawal, being predisposed to lateness, absenteeism, and declining participation. This study aimed to determine the level of turnover intention and to identify factors associated with turnover intention among health extension workers in the Illubabora zone. Methods: A facility-based cross-sectional study with quantitative and qualitative methods of data collection was conducted on 125 randomly selected health posts. All health extension workers in the sampled health posts (n = 245) and 6 key informants were included from February 21 to April 20, 2020. Multiple linear regression models were used to indicate the association between dependent and independent variables. The data obtained from the in-depth interviews were coded, categorized then thematized manually, and supplemented with quantitative data. Results: The prevalence of turnover intention of health extension workers was 52%. The turnover intention was highest among service length >10 years (34.4%), level IV educational status (30.5%), married health extension workers (61.7%), and age category 26–30 years (40.6%). Statistically significant variables were motivation (β=−2.801; 95% CI −5.097, to −0.505), high workload (β=−3.35; 95% CI −6.038, to −0.661) and career structure (β= −3.452; 95% CI −6.267, to −0.638). Conclusion: Overall, the magnitude of health extension workers’ turnover intention of their current job was high. Among variables, high workload, lack of motivation, and limited career structure were a significant predictor of turnover intention. Therefore, an amendment of the career structure and overtime payment should be made to retain health extension workers. They should be encouraged to perform only health sector tasks. Providing transportation is another important mechanism to reduce the workload.