Development and Preliminary Validation of a Public Health Emergency Competency Model for Medical Staffs of National Health Emergency Teams in China
Overview
Affiliations
Background: In the present study, we attempted to develop and validate a participatory competency model for medical workers and then evaluate the current status of competency characteristics of Chinese medical workers.
Methods: The competency model was constructed in a multistage process, including literature review, expert consultation, critical incident and focus group interview. A pilot study was conducted to refine the initial model among 90 participators and the viability and reliability were evaluated by a questionnaire survey among 121 medical workers. Then, the current status of competency characteristics was measured based on the final version of competency model.
Results: In the pilot study, ten questionnaires were dropped for the poor quality and thus the eligible rate was 92% (138/150). KMO value was 0.785 and Bartlett test showed that the χ = 6464.546 (df = 903) and p value < 0.001. Then, 10 items with double loading and factor loading < 0.4 were deleted. Finally, 33 items were retained with the lowest factor loading value of 0.465. The validity and reliability of competency model were determined with Cronbach's α coefficient of 0.975 and ICC value of 0.933. Finally, a revised competency model with 5 dimensions and 31 items was obtained. The overall competencies of current medical workers were in a high level, except for emergency knowledge related competencies. Age was an independent factor affecting the competencies.
Conclusions: Our competency model was a reliable and validated tool for assessing the competences of medical staffs against public health emergencies, and the overall competencies of current medical workers in China were in a high level, except for emergency knowledge related competencies.
Common domains of nurses' competencies in public health emergencies: a scoping review.
Guo X, Bian L, Li Y, Li C, Lin Y BMC Nurs. 2023; 22(1):490.
PMID: 38124048 PMC: 10734140. DOI: 10.1186/s12912-023-01655-5.
Gao J, Tian M, Liu J, Chen J, Zhang L, Wang X BMC Health Serv Res. 2023; 23(1):1138.
PMID: 37872507 PMC: 10594754. DOI: 10.1186/s12913-023-10139-w.