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.

Challenges and experience of the Ethiopian rural health extension program: implications for reform and revitalization

“…Besides the time and energy, it poses greater dissatisfaction and misery in their life. This finding is consistent with a study conducted in Illubabora Zone; South West Ethiopia suggested that providing transportation is another important mechanism to reduce the workload [ 30 ]. Similar finding was observed in other studies in which 41% of HEWs’ was spent on travel in 2014 study [ 17 ] and a study in 2017, out of the total observed work time, HEWs spent 16% of their time through travel between work activities [ 25 ].…”

“…Furthermore, the magnitude of HEWs ' intention to leave their current position was high due to a heavy workload, a lack of enthusiasm, and a limited career structure, which were all significant predictors of turnover intention. [ 30 ]. Workload, large distances, and a lack of support were all highlighted as problems that could demotivate HEWs from providing outreach services.…”

“…Workload, large distances, and a lack of support were all highlighted as problems that could demotivate HEWs from providing outreach services. The HEWs were obliged to execute different sectors’ tasks other than those in the health sectors; as a result, there would be an elevated workload on the existing health extension worker [ 30 ].…”

Turnover intention among healthcare workers in Ethiopia: a systematic review and meta-analysis

“…Among the 29 included studies, 9 were from Amhara,16–24 8 were from Oromia,25–32 3 were from Addis Ababa,33–35 2 studies each from Tigray,36 37 Sidama,13 38 multiregional12 39 and Nationwide40 41 and one study was from Gambella 42. The study from Sidama region13 documented the highest prevalence (83.7%) of turnover intention among health professionals, while the lowest prevalence (39%) was documented from a study conducted by including the three regions of Afar, Gambela and Benishangul Gumz 12.…”

“…Twelve studies included a mixed variety of health professionals in general,13 17–19 25 27 28 30 32 34 35 42 while 10 other studies included nurse professionals only 20 22 23 26 31 33 36–38 40. Two studies included health extension workers16 29 and five studies each included physicians,39 health information technology professionals,24 anaesthetists,41 medical laboratory professionals21 and midwives,12 respectively. Table 1 summarises the characteristics of the included studies.…”