Nantiya Chookaew. Factors influencing "Brain drain" among professional nurses from public to private sector in Bangkok Metropolitan area. Master's Degree(Health Development). Chulalongkorn University. Center of Academic Resources. : Chulalongkorn University, 2537.
Factors influencing "Brain drain" among professional nurses from public to private sector in Bangkok Metropolitan area
Abstract:
The objective of this study was to determine the factors influencing "Brain Drain" among professional nurses from public to private sector in Bangkok Metropolitan Area. The study based on case-control study (Unmatched case-control) was conducted in 10 hospitals and 10 private hospitals from November 22, 1993 to January 21, 1994. Data was collected by a self-administered questionnaire. The case group was nurses in the private hospital who have received a bachelor degree in nursing from 1988 to 1992, worked in the public sector for at least 6 months and shifted from public to private sector for not more than 2 years. The control group was nurses in the public hospital who have received a bachelor degree in nursing from 1988 to 1992 and have been working in the public sector for at least 6 months. the total of 151 cases and 150 controls were collected during this period. The result of these studies found that 5 factors have a significant association with Brain Drain at p < 0.05, these were analysed by univariate analysis : spouse's occupation, convenience of travelling of work, compensation, working condition, and supervision. Spouse's occupation, convenience of travelling to work, compensation, and working condition were found to be a significant negative association. So the only one factor was supervision which is the main factor associated with Brain Drain Nurses who are dissatisfied with supervision are at risk to Brain Drain 2.63 times more than nurses having satisfaction with supervision. Factors which are not a significant association with Brain Drain were : marital status, number of dependents, family income, salary, fringe benefit, work itself, interpersonal relations, advancement opportunity, policy and administration. Analysis the predictive factors of Brain Drain by multiple logistic regression could not be done for this study due to a significant negative association. 4. Factors which have a significant negative association may be artificial association from random bias or recall bias. The result of this study recommend to hospital administration should established supervision and management training schemes. To create a good leadership style and type of management who are sensitive to the needs of all nursing and associated staff and patients