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      Qualitative Research in Healthcare: Data Analysis

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          Abstract

          Qualitative research methodology has been applied with increasing frequency in various fields, including in healthcare research, where quantitative research methodology has traditionally dominated, with an empirically driven approach involving statistical analysis. Drawing upon artifacts and verbal data collected from in-depth interviews or participatory observations, qualitative research examines the comprehensive experiences of research participants who have experienced salient yet unappreciated phenomena. In this study, we review 6 representative qualitative research methodologies in terms of their characteristics and analysis methods: consensual qualitative research, phenomenological research, qualitative case study, grounded theory, photovoice, and content analysis. We mainly focus on specific aspects of data analysis and the description of results, while also providing a brief overview of each methodology’s philosophical background. Furthermore, since quantitative researchers have criticized qualitative research methodology for its perceived lack of validity, we examine various validation methods of qualitative research. This review article intends to assist researchers in employing an ideal qualitative research methodology and in reviewing and evaluating qualitative research with proper standards and criteria.

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          Three approaches to qualitative content analysis.

          Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: conventional, directed, or summative. All three approaches are used to interpret meaning from the content of text data and, hence, adhere to the naturalistic paradigm. The major differences among the approaches are coding schemes, origins of codes, and threats to trustworthiness. In conventional content analysis, coding categories are derived directly from the text data. With a directed approach, analysis starts with a theory or relevant research findings as guidance for initial codes. A summative content analysis involves counting and comparisons, usually of keywords or content, followed by the interpretation of the underlying context. The authors delineate analytic procedures specific to each approach and techniques addressing trustworthiness with hypothetical examples drawn from the area of end-of-life care.
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            The qualitative content analysis process.

            This paper is a description of inductive and deductive content analysis. Content analysis is a method that may be used with either qualitative or quantitative data and in an inductive or deductive way. Qualitative content analysis is commonly used in nursing studies but little has been published on the analysis process and many research books generally only provide a short description of this method. When using content analysis, the aim was to build a model to describe the phenomenon in a conceptual form. Both inductive and deductive analysis processes are represented as three main phases: preparation, organizing and reporting. The preparation phase is similar in both approaches. The concepts are derived from the data in inductive content analysis. Deductive content analysis is used when the structure of analysis is operationalized on the basis of previous knowledge. Inductive content analysis is used in cases where there are no previous studies dealing with the phenomenon or when it is fragmented. A deductive approach is useful if the general aim was to test a previous theory in a different situation or to compare categories at different time periods.
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              Naturalistic inquiry

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                Author and article information

                Journal
                J Prev Med Public Health
                J Prev Med Public Health
                Journal of Preventive Medicine and Public Health
                Korean Society for Preventive Medicine
                1975-8375
                2233-4521
                March 2023
                15 February 2023
                : 56
                : 2
                : 100-110
                Affiliations
                [1 ]Department of Preventive Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea
                [2 ]Ulsan Metropolitan City Public Health Policy’s Institute, Ulsan, Korea
                [3 ]Department of Preventive Medicine, University of Ulsan College of Medicine, Seoul, Korea
                Author notes
                Corresponding author: Minsu Ock, Department of Preventive Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, 877 Bangeojinsunhwando-ro, Dong-gu, Ulsan 44033, Korea, E-mail: ohohoms@ 123456naver.com
                [*]

                Im & Pyo contributed equally to this work as joint first authors.

                Author information
                https://orcid.org/0000-0002-5092-4397
                https://orcid.org/0000-0001-7644-8088
                https://orcid.org/0000-0001-9252-3738
                https://orcid.org/0000-0002-3212-2446
                https://orcid.org/0000-0001-9949-9224
                Article
                jpmph-22-471
                10.3961/jpmph.22.471
                10111102
                37055353
                b5071470-bdd3-4af1-90c4-846490db8ff9
                Copyright © 2023 The Korean Society for Preventive Medicine

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 15 November 2022
                : 31 January 2023
                Categories
                Review

                Public health
                qualitative research,methodology,validation
                Public health
                qualitative research, methodology, validation

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