Work Climate and Turnover Intention among Nurses in Tertiary Level Hospitals, Republic of The Gambia

Abstract

Background: High turnover rate among nurses is regarded as a big problem leading to a shortage which does not only affects the quality of patient care but also affects the cost of recruitment and training new staff. Actual turnover is predicted by turnover intention and employee intention mark the most immediate motivator of task performance and an individual's choice of behavior is influenced by their intentions. From the literature review, work climate is the highest predictor of turnover intention and there are challenging situations faced by nurses regarding their work climate and turnover intention levels in The Gambia. Objective: To examine work climate and turnover intention among nurses in the tertiary level hospitals and explore the relationship between work climate and turnover intention among nurses in tertiary level hospitals in the Republic of The Gambia. Methods: A descriptive correlation research design was used to examine the level of work climate and turnover intention and identify their relationship among nurses in the six tertiary hospital in the Republic of The Gambia. Sample size was 224 and participants were selected by simple random sampling from 11 departments with a response rate of 89.73%. Research instruments used in this study were the demographic data form, CRISO Psychological Climate Questionnaire and turnover intention scale. Reliability of the CRISO Psychological Climate Questionnaire was 0.92 and the turnover intention scale was 0.80. Data were analyzed using descriptive statistics and Pearson correlation analysis. Results: The level of overall work climate was favorable and the overall level of turnover intention at high level. There was a significant negative relationship between overall and each dimension of work climate and overall turnover intention. Conclusions: A recommendation is made to study other factors related to work climate and turnover intention, such as payment, gender, education level, and work department.