扩展支柱集成过程(ePIP):一种数据集成方法，允许系统地综合来自三个不同来源的发现

IF 3.8 1区社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY

Journal of Mixed Methods Research Pub Date : 2022-10-22 DOI:10.1177/15586898221135409

Julia Gauly, Arun Ulahannan, A. Grove

{"title":"扩展支柱集成过程(ePIP):一种数据集成方法，允许系统地综合来自三个不同来源的发现","authors":"Julia Gauly, Arun Ulahannan, A. Grove","doi":"10.1177/15586898221135409","DOIUrl":null,"url":null,"abstract":"Mixed methods research requires data integration from multiple sources. Existing techniques are restricted to integrating a maximum of two data sources, do not provide step-by-step guidance or can be cumbersome where many data need to be integrated. We have solved these limitations through the development of the extended Pillar Integration Process (ePIP), a method which contributes to the field of mixed methods by being the first data integration method providing explicit steps on how to integrate data from three data sources. The ePIP provides greater transparency, validity and consistency compared to existing methods. We provide two worked examples from health sciences and automotive human factors, highlighting its value as a mixed methods integration tool.","PeriodicalId":47844,"journal":{"name":"Journal of Mixed Methods Research","volume":null,"pages":null},"PeriodicalIF":3.8000,"publicationDate":"2022-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The Extended Pillar Integration Process (ePIP): A Data Integration Method Allowing the Systematic Synthesis of Findings From Three Different Sources\",\"authors\":\"Julia Gauly, Arun Ulahannan, A. Grove\",\"doi\":\"10.1177/15586898221135409\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mixed methods research requires data integration from multiple sources. Existing techniques are restricted to integrating a maximum of two data sources, do not provide step-by-step guidance or can be cumbersome where many data need to be integrated. We have solved these limitations through the development of the extended Pillar Integration Process (ePIP), a method which contributes to the field of mixed methods by being the first data integration method providing explicit steps on how to integrate data from three data sources. The ePIP provides greater transparency, validity and consistency compared to existing methods. We provide two worked examples from health sciences and automotive human factors, highlighting its value as a mixed methods integration tool.\",\"PeriodicalId\":47844,\"journal\":{\"name\":\"Journal of Mixed Methods Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2022-10-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Mixed Methods Research\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1177/15586898221135409\",\"RegionNum\":1,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mixed Methods Research","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1177/15586898221135409","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}

引用次数: 1

摘要

混合方法研究需要来自多个来源的数据集成。现有技术仅限于集成最多两个数据源，不能提供循序渐进的指导，或者在需要集成许多数据时可能很麻烦。我们通过开发扩展的支柱集成过程（ePIP）解决了这些限制，该方法是第一种数据集成方法，为如何集成来自三个数据源的数据提供了明确的步骤，从而为混合方法领域做出了贡献。与现有方法相比，ePIP提供了更大的透明度、有效性和一致性。我们提供了健康科学和汽车人为因素的两个工作示例，强调了其作为混合方法集成工具的价值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

The Extended Pillar Integration Process (ePIP): A Data Integration Method Allowing the Systematic Synthesis of Findings From Three Different Sources

Mixed methods research requires data integration from multiple sources. Existing techniques are restricted to integrating a maximum of two data sources, do not provide step-by-step guidance or can be cumbersome where many data need to be integrated. We have solved these limitations through the development of the extended Pillar Integration Process (ePIP), a method which contributes to the field of mixed methods by being the first data integration method providing explicit steps on how to integrate data from three data sources. The ePIP provides greater transparency, validity and consistency compared to existing methods. We provide two worked examples from health sciences and automotive human factors, highlighting its value as a mixed methods integration tool.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Journal of Mixed Methods Research SOCIAL SCIENCES, INTERDISCIPLINARY-

CiteScore

10.40

自引率

28.20%

发文量

期刊介绍： The Journal of Mixed Methods Research serves as a premiere outlet for ground-breaking and seminal work in the field of mixed methods research. Of primary importance will be building an international and multidisciplinary community of mixed methods researchers. The journal''s scope includes exploring a global terminology and nomenclature for mixed methods research, delineating where mixed methods research may be used most effectively, creating the paradigmatic and philosophical foundations for mixed methods research, illuminating design and procedure issues, and determining the logistics of conducting mixed methods research. JMMR invites articles from a wide variety of international perspectives, including academics and practitioners from psychology, sociology, education, evaluation, health sciences, geography, communication, management, family studies, marketing, social work, and other related disciplines across the social, behavioral, and human sciences.