자연주의적 탐구조사(Naturalistic Inquiry)

Qualitative research is increasingly common in health services research (Shortell 1999; Sofaer 1999). Qualitative studies have been used, for example, to study culture change (Marshall et al. 2003; Craigie and Hobbs 2004), physician–patient relationships and primary care (Flocke, Miller, and Crabtree 2002; Gallagher et al. 2003; Sobo, Seid, and Reyes Gelhard 2006), diffusion of innovations and quality improvement strategies (Bradley et al. 2005; Crosson et al. 2005), novel interventions to improve care (Koops and Lindley 2002; Stapleton, Kirkham, and Thomas 2002; Dy et al. 2005), and managed care market trends (Scanlon et al. 2001; Devers et al. 2003). Despite substantial methodological papers and seminal texts (Glaser and Strauss 1967; Miles and Huberman 1994; Mays and Pope 1995; Strauss and Corbin 1998; Crabtree and Miller 1999; Devers 1999; Patton 1999; Devers and Frankel 2000; Giacomini and Cook 2000; Morse and Richards 2002) about designing qualitative projects and collecting qualitative data, less attention has been paid to the data analysis aspects of qualitative research. The purpose of this paper is to offer practical strategies for the analysis of qualitative data that may be generated from in-depth interviewing, focus groups, field observations, primary or secondary qualitative data (e.g., diaries, meeting minutes, annual reports), or a combination of these data collection approaches.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1475-6773.2006.00684.x

Qualitative data analysis for health services research: developing taxonomy, themes, and theory.

Triangulation refers to the use of multiple methods or data sources in qualitative research to develop a comprehensive understanding of phenomena (Patton, 1999). Triangulation also has been viewed as a qualitative research strategy to test validity through the convergence of information from different sources. Denzin (1978) and Patton (1999) identified four types of triangulation: (a) method triangulation, (b) investigator triangulation, (c) theory triangulation, and (d) data source triangulation. The current article will present the four types of triangulation followed by a discussion of the use of focus groups (FGs) and in-depth individual (IDI) interviews as an example of data source triangulation in qualitative inquiry.

The Use of Triangulation in Qualitative Research

List of Boxes.List of Field Perspectives.Foreword.Preface.Acknowledgments.Chapter 1: Invitation to Explore.Chapter 2: The Language and Logic of Qualitative Research.Chapter 3: Designing the Study.Chapter 4: Collecting Qualitative Data: The Science and the Art.Chapter 5: Logistics in the Field.Chapter 6: Qualitative Data Analysis.Chapter 7: Putting It into Words: Reporting Qualitative Research Results.Chapter 8: Disseminating Qualitative Research.Appendix 1: Samples of Behavioral Frameworks.Appendix 2: Examples of Oral Consent Forms.Appendix 3: Example of a Qualitative-Quantitative Research Design.Appendix 4: Procedural Guidelines for Managing Focus Group Discussions.Appendix 5: Sample Budget Categories for Planning Focus Group Discussions.Appendix 6: Topic Guides for Focus Group Discussions on Reproductive Health.Appendix 7: Sample Interviewer Training Program Agenda.Appendix 8: Common Errors in Moderating Focus Groups.Appendix 9: Critical Appraisal Skills Programme (CASP): Ten Questions to Help You Make Sense of Qualitative Research.Appendix 10: Where to Publish.Appendix 11: Sample Research Brief on the Female Condom.Appendix 12: Who Is an Author?Appendix 13: Sample Brochure to Share Qualitative Study Findings with Participating Communities.Appendix 14: Making Study Findings Accessible to Other Researchers.Suggested Readings and Selected Internet Resources.References.The Authors.The Contributors.Index.

Qualitative Methods in Public Health: A Field Guide for Applied Research

Case research has commanded respect in the information systems (IS) discipline for at least a decade Notwithstanding the relevance and potential value of case studies, this methodological approach was once considered to be one of the least systematic Toward the end of the 1980s, the issue of whether IS case research was rigorously conducted was first raised Researchers from our field (eg, Benbasat et al 1987; Lee 1989) and from other disciplines (eg, Eisenhardt 1989; Yin 1994) called for more rigor in case research and, through their recommendations, contributed to the advancement of the case study methodology Considering these contributions, the present study seeks to determine the extent to which the field of IS has advanced in its operational use of case study method Precisely, it investigates the level of methodological rigor in positivist IS case research conducted over the past decade To fulfill this objective, we identified and coded 183 case articles from seven major IS journals Evaluation attributes or criteria considered in the present review focus on three main areas, namely, design issues, data collection, and data analysis While the level of methodological rigor has experienced modest progress with respect to some specific attributes, the overall assessed rigor is somewhat equivocal and there are still significant areas for improvement One of the keys is to include better documentation particularly regarding issues related to the data collection and analysis processes

Rigor in information systems positivist case research: current practices, trends, and recommendations

Varying philosophical and theoretical orientations to qualitative inquiry remind us that issues of quality and credibility intersect with audience and intended research purposes. This overview examines ways of enhancing the quality and credibility of qualitative analysis by dealing with three distinct but related inquiry concerns: rigorous techniques and methods for gathering and analyzing qualitative data, including attention to validity, reliability, and triangulation; the credibility, competence, and perceived trustworthiness of the qualitative researcher; and the philosophical beliefs of evaluation users about such paradigm-based preferences as objectivity versus subjectivity, truth versus perspective, and generalizations versus extrapolations. Although this overview examines some general approaches to issues of credibility and data quality in qualitative analysis, it is important to acknowledge that particular philosophical underpinnings, specific paradigms, and special purposes for qualitative inquiry will typically include additional or substitute criteria for assuring and judging quality, validity, and credibility. Moreover, the context for these considerations has evolved. In early literature on evaluation methods the debate between qualitative and quantitative methodologists was often strident. In recent years the debate has softened. A consensus has gradually emerged that the important challenge is to match appropriately the methods to empirical questions and issues, and not to universally advocate any single methodological approach for all problems.

M Q Patton

Papers

Enhancing the quality and credibility of qualitative analysis.