Capacity and training demand of the emergency staff from centers for disease control and prevention at county and municipal levels in Zhejiang Province
10.19485/j.cnki.issn2096-5087.2018.03.003
- VernacularTitle:浙江省市县疾病预防控制中心卫生应急人员能力及培训需求研究
- Author:
Zhen WANG
1
;
Na LI
;
Ren-Jie ZHANG
;
Xue-Hai ZHANG
;
Xiao-Hua QI
;
Bi-Yao LIU
Author Information
1. 浙江大学公共卫生学院
- Keywords:
Center for Disease Control and Prevention;
Emergency staff;
Training demand
- From:
Journal of Preventive Medicine
2018;30(3):226-231
- CountryChina
- Language:Chinese
-
Abstract:
Objective To study the emergency staff's knowledge, skills and their training demand in centers for disease control and prevention (CDC) at county and municipal levels in Zhejiang Province. Methods Using multistage cluster sampling, 518 emergency staff from 34 CDCs in Zhejiang Province were involved in this study. A questionnaire survey was conducted among the emergency staff to evaluate their emergency knowledge and training demand. The differences between the staff from CDCs at county and municipal levels were evaluated. Results The average score of the emergency staff was 2.93 about all emergency knowledge. Some items' scores were lower, such as nuclear radiation control, first aid, risk management, ethics, laws and emergency system. The score of the survey items were similar at county and municipal level except education degree, positional title, and proportion of staff in emergency training, score of epidemiology, risk management and first aid. The highest degree of training demand was professional knowledge related to emergency response. The emergency staff inclined to the training mode (≥4) about short-term training, field guidance, drill and exercise and case study. Conclusion We should improve the health emergency training according to the demand and target of fostering inter-disciplinary talents for fieldwork. We should strengthen training of basic theories, basic knowledge and basic skills, to cover the shortage. The short-term training and practical training should be the main training model.
