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Ensuring quality qualitative research reporting in community pharmacy: a systematic literature review

机译:确保社区药房的高质量定性研究报告:系统文献综述

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摘要

Objectives To evaluate the reporting quality for a sample of community pharmacy qualitative research articles based on the Standards for Reporting Qualitative Research (SRQR) guidelines, data interpretation and use of theory. Methods A systematic literature search was conducted using Ovid MEDLINE to identify qualitative research related to community pharmacy. Data were extracted and evaluated based on the SRQR standards, data interpretation level and use of theory. Adherence to standards was analysed using descriptive statistics. Key findings Eighty-one studies were retrieved through the database search (n = 81). Then, 31 studies met the inclusion criteria after screening abstracts and full texts. Twelve out of 21 SRQR were present in more than 80 of the studies. However, essential standards, such as research approach, reflexivity and trustworthiness techniques, were absent or partially present in 30 (97) studies, 30 (97) studies and 21 (68) studies, respectively. Data interpretation level was descriptive in 27 (87) studies and interpretive or partially interpretive in 4 (13) studies. Theory was absent in 19 (60) and implied, partially integrated or retrospectively applied in 12 (40) of the studies. Conclusion Trustworthiness and quality of qualitative inferences within community pharmacy research could be enhanced with increasing awareness about reporting; the approach and paradigm, reflexivity, trustworthiness techniques, data interpretation level and theoretical use.
机译:目的 根据定性研究报告标准 (SRQR) 指南、数据解释和理论使用,评估社区药房定性研究文章样本的报告质量。方法 采用Ovid MEDLINE软件进行系统文献检索,确定社区药学相关定性研究。根据SRQR标准、数据解释水平和理论运用对数据进行提取和评估。使用描述性统计分析了对标准的遵守情况。主要发现 通过数据库检索检索了81项研究(n=81)。然后,31项研究在筛选摘要和全文后符合纳入标准。21个SRQR中有12个存在于80%以上的研究中。然而,分别有30项(97%)研究、30项(97%)研究和21项(68%)研究缺乏或部分存在研究方法、反思性和可信度技术等基本标准。27项(87%)研究的数据解释水平是描述性的,4项(13%)研究的数据解释水平是解释性的或部分解释性的。19项(60%)研究缺乏理论,12项(40%)研究采用隐含、部分整合或回顾性应用。结论 随着报告意识的提高,社区药学研究中定性推论的可信度和质量可以得到提高;方法和范式、反身性、可信度技术、数据解释水平和理论应用。

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