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运用COM-b模型探究影响兽医抗菌药物处方行为的因素:孟加拉国一项定性研究的结果

An application of COM-b model to explore factors influencing veterinarians' antimicrobial prescription behaviors: Findings from a qualitative study in Bangladesh.

作者信息

Shano Shahanaj, Kalam Md Abul, Afrose Sharmin, Rahman Md Sahidur, Akter Samira, Uddin Md Nasir, Jalal Faruk Ahmed, Dutta Pronesh, Ahmed Mithila, Kamal Khnd Md Mostafa, Hassan Mohammad Mahmudul, Nadimpalli Maya L

机构信息

Institute of Epidemiology Disease Control and Research (IEDCR), Mohakhali, Dhaka, Bangladesh.

Global Health and Development Program, Laney Graduate School, Emory University, Atlanta, Georgia, United States of America.

出版信息

PLoS One. 2024 Dec 16;19(12):e0315246. doi: 10.1371/journal.pone.0315246. eCollection 2024.

Abstract

The integration of behavioral theories in designing antimicrobial stewardship (AMS) interventions aimed at optimizing the antimicrobial prescription in veterinary practice is highly recommended. However, little is known about the factors that influence veterinarians' antimicrobial behavior for food-producing animals in lower- and middle-income settings like Bangladesh. There is a large body of research on the factors that influence veterinarian behavior of prescribing antimicrobials, however, there is a need for more studies that use comprehensive behavior change models to develop and evaluate interventions. Applying the Capability, Opportunity, and Motivation for Behavior (COM-B) model, this qualitative study attempted to address this gap by conducting 32 one-on-one semi-structured interviews with registered veterinarians in Bangladesh. In alignment with COM-B constructs and the theoretical domain framework (TDF), thematic analysis (both inductive and deductive inferences) was performed to analyze the data and identify underlying factors that influence veterinarians' antimicrobial prescription behavior. We found that under "Capability," factors such as knowledge of antimicrobial resistance (AMR); ability to handle complex disease conditions; ability to identify the appropriate antimicrobial type, routes of administration, and potential side effects influence prescription behavior by veterinarians. Under "Opportunity," veterinarians' prescription behavior was influenced by lack of laboratory testing facilities, poor farm biosecurity, farm management and location, farming conditions, impacts of climate change, the clinical history of animals and social influence from different actors including senior figures, peers, farmers, and other informal stakeholders. Under "Motivation," national laws and guidelines serve as catalysts in reducing antimicrobial prescriptions. However, perceived consequences such as fear of treatment failure, losing clients, farmers' reliance on informal service providers, and economic losses demotivate veterinarians from reducing the prescription of antimicrobials. Additionally, veterinarians feel that reducing the burden of AMR is a shared responsibility since many informal stakeholders are involved in the administration and purchase of these medicines. Based on our results, this study recommends incorporating the factors we identified into existing or novel AMS interventions. The behavior change wheel can be used as the guiding principle while designing AMS interventions to increase capability, opportunity and motivation to reduce antimicrobial over-prescription.

摘要

强烈建议将行为理论整合到旨在优化兽医实践中抗菌药物处方的抗菌药物管理(AMS)干预措施设计中。然而,对于孟加拉国等中低收入环境下影响兽医对食用动物抗菌药物使用行为的因素,人们知之甚少。关于影响兽医抗菌药物处方行为的因素已有大量研究,但仍需要更多使用综合行为改变模型来开发和评估干预措施的研究。本定性研究应用行为的能力、机会和动机(COM-B)模型,通过对孟加拉国注册兽医进行32次一对一的半结构化访谈,试图填补这一空白。根据COM-B结构和理论领域框架(TDF),进行了主题分析(包括归纳和演绎推理)以分析数据,并确定影响兽医抗菌药物处方行为的潜在因素。我们发现,在“能力”方面,诸如对抗菌药物耐药性(AMR)的了解;处理复杂疾病状况的能力;识别合适的抗菌药物类型、给药途径和潜在副作用等因素会影响兽医的处方行为。在“机会”方面,兽医的处方行为受到缺乏实验室检测设施、农场生物安全措施差、农场管理和位置、养殖条件、气候变化影响、动物临床病史以及包括上级、同行、农民和其他非正式利益相关者在内的不同行为者的社会影响。在“动机”方面,国家法律和指南是减少抗菌药物处方的催化剂。然而,诸如担心治疗失败、失去客户、农民对非正式服务提供者的依赖以及经济损失等可感知后果,会使兽医减少抗菌药物处方的积极性受挫。此外,兽医认为减轻AMR负担是一项共同责任,因为许多非正式利益相关者参与了这些药物的管理和采购。基于我们的研究结果,本研究建议将我们确定的因素纳入现有或新的AMS干预措施中。在设计AMS干预措施以提高减少抗菌药物过度处方的能力、机会和动机时,行为改变轮可作为指导原则。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32b8/11649135/dab29b93f8a0/pone.0315246.g001.jpg

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