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A framework for selecting data generation strategies in qualitative health research studies.
Jack, Susan M; Orr, Elizabeth; Campbell, Karen A; Whitmore, Carly; Cammer, Allison.
Afiliação
  • Jack SM; School of Nursing, McMaster University, Hamilton, Ontario, Canada.
  • Orr E; Department of Nursing, Brock University, St. Catharines, Ontario, Canada.
  • Campbell KA; School of Nursing, York University, Toronto, Ontario, Canada.
  • Whitmore C; Centre for Addiction and Mental Health, Toronto, Ontario, Canada.
  • Cammer A; College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
J Hum Nutr Diet ; 36(4): 1480-1495, 2023 08.
Article em En | MEDLINE | ID: mdl-36617529
ABSTRACT

BACKGROUND:

Qualitative health research has the potential to answer important applied health research questions to inform nutrition and dietetics practice, education and policy. Qualitative health research is a distinct subdiscipline of qualitative inquiry that purposefully draws upon the context of healthcare and emphasises health and wellness.

METHODS:

Qualitative health research is defined by two parameters (1) the focus of the study and (2) the methods used. When considering the methods to be used, decisions are required about the type of data to be generated (e.g., transcripts, images and notes) and the process involved in data generation (e.g., interviews, elicitation strategies and observations) to answer the research question(s). Drawing upon examples from nutrition and dietetics literature, this paper provides a framework to support decision-making for nutrition and dietetics researchers and clinician researchers designing conducting qualitative health research.

RESULTS:

The guiding questions of the framework include What types of data will be generated? Who is involved in data generation? Where will data generation occur? When will data generation occur? How will data be recorded and managed? and How will participants' and researchers' emotional safety be promoted?

CONCLUSION:

Questions about the types of data, those involved, where and when, as well as how safety can be maintained in data generation, not only support a more robust design and description of data generation methods but also keep the person at the centre of the research.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Dietética Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Revista: J Hum Nutr Diet Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Dietética Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Revista: J Hum Nutr Diet Ano de publicação: 2023 Tipo de documento: Article