利用主题分析技术识别工作记忆成分的综合调查:一项定性研究

Nafiseh Tabatabaei, M. Nadi, I. Sajjadian
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引用次数: 0

摘要

背景:工作记忆通常被认为是短期记忆和长期记忆之间的中介。然而,WM也是一个数据处理器和操纵者,控制着我们相当一部分的认知能力。由于最近认识到进一步研究WM的重要性,本研究旨在利用定性主题分析来确定当前文献中存在的整个WM成分。方法:采用Stirling的定性归纳主题分析新方法,从2018年至今的文献中提取WM的全部成分。结果:我们的结果从1099个概念中产生了57个与WM相关的基本概念(主题),这些概念被整合到18个组织概念中,共同构成了WM的全球概念。通过专家确认和内容效度指数(CVI)计算(0.88)进行统计验证。Holsti系数为0.60,信度相对合适。结论:考虑到人们对中药成分研究的兴趣日益浓厚,开展旨在彻底澄清这些成分的综合研究是必要的。在此,我们运用主题分析的新技术,开发了一个全面的主题网络,旨在促进未来对WM的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Comprehensive Investigation to Identify Working Memory Components Utilizing Thematic Analysis Technique: A Qualitative Research
Background: Working memory (WM) is commonly known as a mediator between short-term and long-term memory. However, WM as well is a data processor and manipulator in charge of a considerable portion of our cognitive abilities. Due to the recently grasped significance of further investigations of WM, this study was conducted aiming to identify the entire WM components present in the current literature utilizing qualitative thematic analysis.Methods: Stirling’s novel method of qualitative inductive thematic analysis was applied to extract the entire components of WM from the current literature up to 2018.Results: Our results yielded 57 basic concepts (themes) related to WM out of 1099 concepts, which was integrated into 18 organizing concepts that altogether comprise the global notion of WM. Statistical validation was conducted through expert confirmation and content validity index (CVI) calculation (0.88). Moreover, the Holsti coefficient was 0.60 that indicates relatively appropriate reliability.Conclusion: Considering the growing interest in studying WM components, conducting an integrative research aiming to thoroughly clarify these components was required. Herein, through applying the novel technique of thematic analysis, we have developed a comprehensive theme network designed to facilitate future studies on WM.
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