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Titre : | A clinical care competency inventory for nurses in Traditional Chinese Medicine: Development and psychometric evaluation (2020) |
Auteurs : | Miao-Ju Chang ; Suh-Ing Hsieh ; Tzu-Hsin Huang ; Li-Ling Hsu |
Type de document : | Article |
Dans : | Nurse Education in Practice (Vol. 49, November 2020) |
Article en page(s) : | 102881 |
Note générale : | https://doi.org/10.1016/j.nepr.2020.102881 |
Langues: | Anglais |
Descripteurs : |
HE Vinci Compétence ; Infirmières et infirmiers ; Medecine traditionnelle chinoise |
Mots-clés: | Inventaire de compétences |
Résumé : | The aims of this study were to develop a clinical care competence inventory for Traditional Chinese Medicine nurses and to test its psychometric properties. A cross-sectional survey was conducted in hospitals around Taiwan using a newly developed scale called Clinical Care Competency Inventory for Traditional Chinese Medicine Nurses. A total of 322 participants took the survey, and response rate was 95.7%. An exploratory factory analysis was used to analyze items and confirm the construct validity. Principal Component Analysis is an exploratory factor analysis used to identify the underlying dimension of the constructs of a particular scale. Six factors were determined from this study: evidence-based nursing capability, routine medical auxiliary behavior in acupuncture and moxibustion, medical auxiliary behavior in Traditional Chinese Medicine orthopedics, basic Traditional Chinese Medicine related knowledge and skills, diagnostic questioning and Traditional Chinese Medicine assessment in special conditions, and patient education about Traditional Chinese Medicine nursing which together explained 63.45% of the variance. The findings of this study can assist in the planning of in-service education for Traditional Chinese Medicine nurses. The nurse competence indicators are useful in planning nursing training and letting patients and their families know what to reasonably expect from nurses in relation to traditional Chinese medicine. |
Disponible en ligne : | Oui |
En ligne : | https://login.ezproxy.vinci.be/login?url=https://www.sciencedirect.com/science/article/pii/S1471595318301215#! |