设计和验证在国家贫困地区保留医生和专家的模式:一种混合方法

Ahad Norouzzadeh
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引用次数: 0

摘要

卫生系统面临的主要挑战之一是贫困地区的人们获得卫生保健服务的机会有限。这是因为医生和专家不会在那里呆太久。这项研究还旨在设计一种模式,以便在该国贫困地区留住医生和专家。方法:本研究目的为探索性研究,类型为描述性研究。这是一项于2022年分定性和定量两个阶段进行的实地研究。在第一阶段,通过链式转诊法(滚雪球抽样)有目的抽样,从该国西北部贫困地区选出20名医生和专家。第二阶段随机抽取200名西北省份医学院校的医生。分析采用内容分析法,并采用Atlas-ti和Smart PLS。结果:根据调查结果,确定了以下内容为我国贫困地区留住医生和专科医生的组成部分和指标;就业(6个指标)、财政支持(3个指标)、社会(5个指标)、决策(4个指标)、动机(7个指标)、专业和职业发展(7个指标)、管理和系统因素(5个指标)、精神和心理因素(3个指标)。结论:在设计的模型中,“社会”成分的通径系数最高,为0.921,“管理与系统因素”成分的通径系数最低,为0.722。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Designing and Validating a Model for Retaining Doctors and Specialists in Deprived Areas of the Country: A Mixed Approach
Introduction: One of the major challenges of the health system is the limited access of people in deprived areas to healthcare services. This is because the doctors and specialists do not stay there for long. This research also aims to design a model for retaining doctors and specialists in deprived areas of the country. Methods: This research was exploratory in terms of purpose and descriptive in terms of type. It was a field study conducted in two qualitative and quantitative stages in 2022. In the first stage, 20 doctors and specialists from deprived areas in the northwest of the country were selected through purposive sampling using the chain-referral method (snowball sampling).  In the second stage, 200 doctors working in universities of medical sciences in northwestern provinces were randomly selected. For analysis, content analysis method and Atlas-ti and Smart PLS were used. Results:Based on the findings, the following contents were identified as the components and indicators of retaining doctors and specialists in deprived areas of the country; employment with 6 indicators, financial support with 3 indicators, social with 5 indicators, policy-making with 4 indicators, motivation with 7 indicators, professional and career improvement with 7 indicators, management and systematic factors with 5 indicators, and finally, mental and psychological factors with 3 indicators. Conclusion: The "social" component with a path coefficient of 0.921 had the highest coefficient, and "management and systematic factors" component with a value of 0.722 had the lowest coefficient in the designed model.
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