Cargando…
Knowledge, Attitudes and Intentions to Prescribe Antibiotics: A Structural Equation Modeling Study of Primary Care Institutions in Hubei, China
The aim of this paper is to measure the knowledge and attitudes of primary care physicians toward antibiotic prescriptions and their impacts on antibiotic prescribing. A questionnaire survey was conducted on 625 physicians from 67 primary care facilities in Hubei, China. Structural equation modellin...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651188/ https://www.ncbi.nlm.nih.gov/pubmed/31284381 http://dx.doi.org/10.3390/ijerph16132385 |
_version_ | 1783438287779659776 |
---|---|
author | Liu, Chenxi Liu, Chaojie Wang, Dan Zhang, Xinping |
author_facet | Liu, Chenxi Liu, Chaojie Wang, Dan Zhang, Xinping |
author_sort | Liu, Chenxi |
collection | PubMed |
description | The aim of this paper is to measure the knowledge and attitudes of primary care physicians toward antibiotic prescriptions and their impacts on antibiotic prescribing. A questionnaire survey was conducted on 625 physicians from 67 primary care facilities in Hubei, China. Structural equation modelling (SEM) was applied to test the theoretical framework derived from the Knowledge, Attitudes, and Practices (KAP) theory. Physicians’ knowledge, five sub-types of attitudes, and three sub-types of behavioral intentions towards antibiotic use were measured. Physicians had limited knowledge about antibiotic prescriptions (average 54.55% correct answers to 11 questions). Although they were generally concerned about antibiotic resistance (mean = 1.28, SD = 0.43), and were reluctant to be submissive to pressures from consumer demands for antibiotics (mean = 1.29, SD = 0.65) and the requirements of defensive practice (mean = 1.11, SD = 0.63), there was a lack of motivation to change prescribing practices (mean = −0.29, SD = 0.70) and strong agreement that other stakeholders should take the responsibility (mean = −1.15, SD = 0.45). The SEM results showed that poor knowledge, unawareness of antibiotic resistance, and limited motivation to change contributed to physicians’ high antibiotics prescriptions (p < 0.001). To curb antibiotic over-prescriptions, improving knowledge itself is not enough. The lack of motivation of physicians to change needs to be addressed through a systematic approach. |
format | Online Article Text |
id | pubmed-6651188 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66511882019-08-07 Knowledge, Attitudes and Intentions to Prescribe Antibiotics: A Structural Equation Modeling Study of Primary Care Institutions in Hubei, China Liu, Chenxi Liu, Chaojie Wang, Dan Zhang, Xinping Int J Environ Res Public Health Article The aim of this paper is to measure the knowledge and attitudes of primary care physicians toward antibiotic prescriptions and their impacts on antibiotic prescribing. A questionnaire survey was conducted on 625 physicians from 67 primary care facilities in Hubei, China. Structural equation modelling (SEM) was applied to test the theoretical framework derived from the Knowledge, Attitudes, and Practices (KAP) theory. Physicians’ knowledge, five sub-types of attitudes, and three sub-types of behavioral intentions towards antibiotic use were measured. Physicians had limited knowledge about antibiotic prescriptions (average 54.55% correct answers to 11 questions). Although they were generally concerned about antibiotic resistance (mean = 1.28, SD = 0.43), and were reluctant to be submissive to pressures from consumer demands for antibiotics (mean = 1.29, SD = 0.65) and the requirements of defensive practice (mean = 1.11, SD = 0.63), there was a lack of motivation to change prescribing practices (mean = −0.29, SD = 0.70) and strong agreement that other stakeholders should take the responsibility (mean = −1.15, SD = 0.45). The SEM results showed that poor knowledge, unawareness of antibiotic resistance, and limited motivation to change contributed to physicians’ high antibiotics prescriptions (p < 0.001). To curb antibiotic over-prescriptions, improving knowledge itself is not enough. The lack of motivation of physicians to change needs to be addressed through a systematic approach. MDPI 2019-07-05 2019-07 /pmc/articles/PMC6651188/ /pubmed/31284381 http://dx.doi.org/10.3390/ijerph16132385 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Chenxi Liu, Chaojie Wang, Dan Zhang, Xinping Knowledge, Attitudes and Intentions to Prescribe Antibiotics: A Structural Equation Modeling Study of Primary Care Institutions in Hubei, China |
title | Knowledge, Attitudes and Intentions to Prescribe Antibiotics: A Structural Equation Modeling Study of Primary Care Institutions in Hubei, China |
title_full | Knowledge, Attitudes and Intentions to Prescribe Antibiotics: A Structural Equation Modeling Study of Primary Care Institutions in Hubei, China |
title_fullStr | Knowledge, Attitudes and Intentions to Prescribe Antibiotics: A Structural Equation Modeling Study of Primary Care Institutions in Hubei, China |
title_full_unstemmed | Knowledge, Attitudes and Intentions to Prescribe Antibiotics: A Structural Equation Modeling Study of Primary Care Institutions in Hubei, China |
title_short | Knowledge, Attitudes and Intentions to Prescribe Antibiotics: A Structural Equation Modeling Study of Primary Care Institutions in Hubei, China |
title_sort | knowledge, attitudes and intentions to prescribe antibiotics: a structural equation modeling study of primary care institutions in hubei, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651188/ https://www.ncbi.nlm.nih.gov/pubmed/31284381 http://dx.doi.org/10.3390/ijerph16132385 |
work_keys_str_mv | AT liuchenxi knowledgeattitudesandintentionstoprescribeantibioticsastructuralequationmodelingstudyofprimarycareinstitutionsinhubeichina AT liuchaojie knowledgeattitudesandintentionstoprescribeantibioticsastructuralequationmodelingstudyofprimarycareinstitutionsinhubeichina AT wangdan knowledgeattitudesandintentionstoprescribeantibioticsastructuralequationmodelingstudyofprimarycareinstitutionsinhubeichina AT zhangxinping knowledgeattitudesandintentionstoprescribeantibioticsastructuralequationmodelingstudyofprimarycareinstitutionsinhubeichina |