库姆医院“官僚恐惧症”的构成因素分析(用质性研究方法)

Hossein Azari, H. Roodsaz, Behrouz Rezaei Manesh, Mir Ali Seyed Naghavi
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引用次数: 0

摘要

背景与目的:医疗保健各个领域的研究都试图通过提供更有利的服务来获得公民的信任。尽管这种观点是普遍的,但“办公室恐惧症”作为行为领域的一种新态度,对这些研究提出了质疑。目前的研究旨在确定在伊朗库姆公立医院转诊的人的官僚恐惧症的组成部分。方法:采用主题分析法进行定性研究。研究人群包括在库姆省公立医院转诊的所有人。其中,190人被选中并接受了采访。访谈记录分三个阶段进行分析:描述性编码、解释性编码和主题识别。结果:通过分析,形成了131个描述码、50个解释码和10个主题。结果表明,直接经历、个性、角色/榜样、官僚政治体制、社会资本、官僚失灵、公共部门内在特征、金钱主义、道德价值观和社会正义是官僚恐惧症的组成部分。结论:官僚恐惧症患者有悲观的看法。对公立医院提供的服务感到满意并不一定导致对这些中心的信任。有些人经常接触到关于公立医院的负面意见;因此,他们对公立医院的态度是消极的和有偏见的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identify Components of Bureauphobia Attitude in Qom Hospitals (With Qualitative Research Approach)
Background and Objectives: Studies in various fields of healthcare seeks to gain the trust of citizens by providing more favorable services. Despite the generality of this view, Bureauphobia as a new attitude in the field of behavior, questioned these studies. The current study aims to identify the components of bureauphobia in in people referred to public hospitals in Qom, Iran. Methods: This is a qualitative study using thematic analysis. The study population consists of all people referred to public Hospitals in Qom province. Of these, 190 were selected and interviewed. The interview transcribes were analyzed in three stages: descriptive coding, interpretive coding, and identifying main themes. Results: The analysis led to the formation of 131 descriptive codes, 50 interpretive codes and 10 main themes. The results showed that direct experiences, personality, role/ example, the political system governing public bureaucracy, social capital, malfunction of the bureaucracy, intrinsic features of the public sector, moneyism, moral values, and social justice were the components of bureauphobia. Conclusion: People with bureauphobia have a pessimistic view. Satisfaction with the services provided by public hospitals does not necessarily lead to trust in these centers. Some people are constantly exposed to negative opinions about public hospitals; hence, their attitudes towards public hospitals are negative and biased.
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