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      Burns pain management: The role of nurse–patient communication

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      Burns
      Elsevier BV

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          Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research.

          Purposeful sampling is widely used in qualitative research for the identification and selection of information-rich cases related to the phenomenon of interest. Although there are several different purposeful sampling strategies, criterion sampling appears to be used most commonly in implementation research. However, combining sampling strategies may be more appropriate to the aims of implementation research and more consistent with recent developments in quantitative methods. This paper reviews the principles and practice of purposeful sampling in implementation research, summarizes types and categories of purposeful sampling strategies and provides a set of recommendations for use of single strategy or multistage strategy designs, particularly for state implementation research.
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            Employing a Qualitative Description Approach in Health Care Research

            A qualitative description design is particularly relevant where information is required directly from those experiencing the phenomenon under investigation and where time and resources are limited. Nurses and midwives often have clinical questions suitable to a qualitative approach but little time to develop an exhaustive comprehension of qualitative methodological approaches. Qualitative description research is sometimes considered a less sophisticated approach for epistemological reasons. Another challenge when considering qualitative description design is differentiating qualitative description from other qualitative approaches. This article provides a systematic and robust journey through the philosophical, ontological, and epistemological perspectives, which evidences the purpose of qualitative description research. Methods and rigor issues underpinning qualitative description research are also appraised to provide the researcher with a systematic approach to conduct research utilizing this approach. The key attributes and value of qualitative description research in the health care professions will be highlighted with the aim of extending its usage.
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              Qualitative research in healthcare: an introduction to grounded theory using thematic analysis.

              In today's NHS, qualitative research is increasingly important as a method of assessing and improving quality of care. Grounded theory has developed as an analytical approach to qualitative data over the last 40 years. It is primarily an inductive process whereby theoretical insights are generated from data, in contrast to deductive research where theoretical hypotheses are tested via data collection. Grounded theory has been one of the main contributors to the acceptance of qualitative methods in a wide range of applied social sciences. The influence of grounded theory as an approach is, in part, based on its provision of an explicit framework for analysis and theory generation. Furthermore the stress upon grounding research in the reality of participants has also given it credence in healthcare research. As with all analytical approaches, grounded theory has drawbacks and limitations. It is important to have an understanding of these in order to assess the applicability of this approach to healthcare research. In this review we outline the principles of grounded theory, and focus on thematic analysis as the analytical approach used most frequently in grounded theory studies, with the aim of providing clinicians with the skills to critically review studies using this methodology.
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                Author and article information

                Contributors
                Journal
                Burns
                Burns
                Elsevier BV
                03054179
                September 2021
                September 2021
                : 47
                : 6
                : 1416-1423
                Article
                10.1016/j.burns.2020.11.011
                33277090
                bb60c06f-f1f7-441a-b58d-4499d5fb9c7f
                © 2021

                https://www.elsevier.com/tdm/userlicense/1.0/

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