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A demonstration of mixed-methods research in the health sciences
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A demonstration of mixed-methods research in the health sciences
A demonstration of mixed-methods research in the health sciences
Journal Article

A demonstration of mixed-methods research in the health sciences

2016
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Overview
Background The growth of patient, community and population-centred nursing research is a rationale for the use of research methods that can examine complex healthcare issues, not only from a biophysical perspective, but also from cultural, psychosocial and political viewpoints. This need for multiple perspectives requires mixed-methods research. Philosophy and practicality are needed to plan, conduct, and make mixed-methods research more broadly accessible to the health sciences research community. The traditions and dichotomy between qualitative and quantitative research makes the application of mixed methods a challenge. Aim To propose an integrated model for a research project containing steps from start to finish, and to use the unique strengths brought by each approach to meet the health needs of patients and communities. Discussion Mixed-methods research is a practical approach to inquiry, that focuses on asking questions and how best to answer them to improve the health of individuals, communities and populations. An integrated model of research begins with the research question(s) and moves in a continuum. The lines dividing methods do not dissolve, but become permeable boundaries where two or more methods can be used to answer research questions more completely. Rigorous and expert methodologists work together to solve common problems. Conclusion Mixed-methods research enables discussion among researchers from varied traditions. There is a plethora of methodological approaches available. Combining expertise by communicating across disciplines and professions is one way to tackle large and complex healthcare issues. Implications for practice The model presented in this paper exemplifies the integration of multiple approaches in a unified focus on identified phenomena. The dynamic nature of the model signals a need to be open to the data generated and the methodological directions implied by findings.