{"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":" ","pages":""},"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\":\" \",\"pages\":\"\"},\"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}
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.
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.