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Construction of an evaluation scale for post competence of family doctors based on knowledge-skill-management model / 中华全科医师杂志
Article en Zh | WPRIM | ID: wpr-994755
Biblioteca responsable: WPRO
ABSTRACT

Objective:

To construct an evaluation scale for post competence of family doctors based on knowledge-skill-management model.

Methods:

The evaluation dimensions and indicators for post competency of family doctors were preliminarily developed through literature review, internal group meeting and brainstorming, and in-depth interviews of experts. And 16 experts in the fields of general practice and health management were invited for 2 rounds of Delphi consultation from December 2020 to April 2021. A competency evaluation scale for family doctors based on the dimensions of knowledge, skills and management was finally constructed.

Results:

The age of the experts was (47.9±7.3) years with a working experience of (24.6±7.8) years. The Cronbach′s α of the questionnaires was 0.891 and the KMO was 0.844. The positive coefficients for 2 rounds of expert consultation were 100%; the familiarity level of experts was 0.86 and authority level was 0.89 in the first round consultation, and those were 0.84 and 0.90 in the second round consultation. After 2 rounds of consultation, the coordination coefficient of expert opinions in the knowledge and skill dimensions was>0.5, and that in the management dimension and overall evaluation system was>0.3. After discussion 2 indicators were deleted in the first round of consultation. The finally constructed family doctor post competency evaluation scale included 3 dimensions, 8 secondary indicators and 61 tertiary indicators.

Conclusion:

Through the Delphi consultation, we have successfully constructed an evaluation scale for post competence of family doctors based on the three dimensions of knowledge, skills and management.
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Texto completo: 1 Base de datos: WPRIM Idioma: Zh Revista: Chinese Journal of General Practitioners Año: 2023 Tipo del documento: Article
Texto completo: 1 Base de datos: WPRIM Idioma: Zh Revista: Chinese Journal of General Practitioners Año: 2023 Tipo del documento: Article