{"title":"Scientific models for qualitative research: a textual thematic analysis coding system - Part 1.","authors":"Frederik Alkier Gildberg, Rhonda Wilson","doi":"10.7748/nr.2023.e1893","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Models are central to the acquisition and organisation of scientific knowledge. However, there are few explanations of how to develop models in qualitative research, particularly in terms of thematic analysis.</p><p><strong>Aim: </strong>To describe a new technique for scientific qualitative modelling: the Empirical Testing Thematic Analysis (ETTA). Part 2 describes the ETTA model.</p><p><strong>Discussion: </strong>ETTA generates a semantic structure expressed through theme-code, content and functionality. It highlights the importance of authenticity markings and taxonomical and functional semantic analysis. Its primary advantage is the sequential need to account for taxonomic analysis, functionality factors, preconditioning items, cascade directories and modulation factors; this results in the production of a sound, systematic, scientific development of a model.</p><p><strong>Conclusion: </strong>ETTA is useful for nurse researchers undertaking qualitative research who want to construct models derived from their investigations.</p><p><strong>Implications for practice: </strong>This article provides a step-by-step approach for researchers undertaking research that culminates in the construction of a model derived from qualitative investigations.</p>","PeriodicalId":47412,"journal":{"name":"Nurse Researcher","volume":"31 3","pages":"36-42"},"PeriodicalIF":1.0000,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nurse Researcher","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7748/nr.2023.e1893","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/5/31 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"NURSING","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Models are central to the acquisition and organisation of scientific knowledge. However, there are few explanations of how to develop models in qualitative research, particularly in terms of thematic analysis.
Aim: To describe a new technique for scientific qualitative modelling: the Empirical Testing Thematic Analysis (ETTA). Part 2 describes the ETTA model.
Discussion: ETTA generates a semantic structure expressed through theme-code, content and functionality. It highlights the importance of authenticity markings and taxonomical and functional semantic analysis. Its primary advantage is the sequential need to account for taxonomic analysis, functionality factors, preconditioning items, cascade directories and modulation factors; this results in the production of a sound, systematic, scientific development of a model.
Conclusion: ETTA is useful for nurse researchers undertaking qualitative research who want to construct models derived from their investigations.
Implications for practice: This article provides a step-by-step approach for researchers undertaking research that culminates in the construction of a model derived from qualitative investigations.
期刊介绍:
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