Q-方法在医疗保健研究中的范围审查|SCI晨读

2021

08/23

NursingResearch护理研究前沿

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在检索确定的 2,302 篇文章中，本综述纳入了 289 项研究。

SCI晨读：

Q-方法在医疗保健研究中的范围审查

摘要

背景

Q-方法是一种研究人类“主观性”复杂问题的方法。尽管这种方法是在 20 世纪初开发的，但直到最近才认识到 Q 方法在医疗保健中的价值。本综述的目的是对实证医疗文献进行范围审查，以检查 Q 方法在医疗保健中的使用程度，包括它是如何使用的以及用于什么目的。

方法

对三个电子数据库（Scopus、EBSCO-CINAHL Complete、Medline）进行了检索。没有应用日期限制。由五名研究者组成的团队进行了标题和摘要审阅，然后是全文审阅。纳入的文章是在医疗保健环境中使用 Q 方法（Q 排序和倒置因子分析）的同行评审的英文期刊文章。以下数据项被提取到专门设计的 Excel 电子表格中：研究细节（例如，场所、国家、年份）、使用 Q 方法的原因、医疗保健主题领域、参与者（类型和数量）、材料（例如，排名锚和 Q 集）、方法（例如，Q 集的开发、分析）、研究结果和研究意义。数据合成是描述性的，包括频率和计数

结果

在检索确定的 2,302 篇文章中，本综述纳入了 289 项研究。我们发现了在医疗保健中越来越多地使用 Q 方法的证据，特别是在过去 5 年中。然而，这项研究仍然很分散，分布在大量期刊和主题领域。在许多研究中，我们发现方法报告存在局限性，例如关于作者如何导出 Q-set、他们执行的分析类型以及解释的方差量的信息不足。

结论

尽管 Q 方法越来越多地用于医疗保健研究，但它似乎仍然相对新颖。该评论强调了该方法的使用方式、应用领域和该方法的潜在价值方面的共性。为了便于报告 Q 方法研究，我们提供了一份应包含在出版中的详细信息清单。

Abstract

Background

Q-methodology is an approach to studying complex issues of human ‘subjectivity’. Although this approach was developed in the early twentieth century, the value of Q-methodology in healthcare was not recognised until relatively recently. The aim of this review was to scope the empirical healthcare literature to examine the extent to which Q-methodology has been utilised in healthcare over time, including how it has been used and for what purposes.

Methods

A search of three electronic databases (Scopus, EBSCO-CINAHL Complete, Medline) was conducted. No date restriction was applied. A title and abstract review, followed by a full-text review, was conducted by a team of five reviewers. Included articles were English-language, peer-reviewed journal articles that used Q-methodology (both Q-sorting and inverted factor analysis) in healthcare settings. The following data items were extracted into a purpose-designed Excel spreadsheet: study details (e.g., setting, country, year), reasons for using Q-methodology, healthcare topic area, participants (type and number), materials (e.g., ranking anchors and Q-set), methods (e.g., development of the Q-set, analysis), study results, and study implications. Data synthesis was descriptive in nature and involved frequency counting, open coding and the organisation by data items.

Results

Of the 2,302 articles identified by the search, 289 studies were included in this review. We found evidence of increased use of Q-methodology in healthcare, particularly over the last 5 years. However, this research remains diffuse, spread across a large number of journals and topic areas. In a number of studies, we identified limitations in the reporting of methods, such as insufficient information on how authors derived their Q-set, what types of analyses they performed, and the amount of variance explained.

Conclusions

Although Q-methodology is increasingly being adopted in healthcare research, it still appears to be relatively novel. This review highlight commonalities in how the method has been used, areas of application, and the potential value of the approach. To facilitate reporting of Q-methodological studies, we present a checklist of details that should be included for publication.