Background: The relationship between employees' intent to stay/leave a position and the actual turnover of employees merits further investigation. Most previous studies of this relationship have utilized cross-sectional designs to examine nurse turnover from a fixed point in time. Research using a longitudinal design could increase the ability to predict who will leave, and to identify factors that cause turnover behavior.
Objectives: To investigate whether the same mechanisms and factors that affect employee's turnover intentions can be applied to actual turnover in a longitudinal way in an effort to expose causal relationships.
Design: After a review of existing literature, we collected baseline data on turnover determinants as well as two intervening variables: job satisfaction and intent to stay. Three years later, hospital personnel records were used to identify the actual turnover of nurses who responded in the first wave.
Settings: With its 600 beds and metropolitan site, the target hospital located in Taichung, Taiwan is representative of Taiwan's general hospitals.
Methods: The 412 registered staff nurses (managers excluded) at work in this hospital were reached by a mail questionnaire in the first wave. Three years later, the turnover data collected in wave two had divided the wave one's 308 respondents (74.8%) into 132 leavers (42.9%, coded as "1") and 176 stayers (57.1%, coded as "0"). The data were then processed by descriptive statistics, exploratory factor analysis, multiple regression, and logistic regression.
Results: As in previous studies of this type, distributive justice, workload, resource inadequacy, supervisory support, kinship support, and job satisfaction were again proven to be highly associated with intent to stay/leave. Nevertheless, with the exception of workload, these indicators worked poorly when predicting the actual turnover.
Conclusions: The study confirms earlier findings on the relationships among turnover determinants, job satisfaction, and intent to stay, and suggests a more comprehensive selection of turnover factors must be taken into account when attempting to explain variations in actual turnover.