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Mixed methods in public health research in Taiwan – Using visual diagrams to communicate complex design procedures

Bibliographic Data

ID15218302
AuthorsSu‐i Hou (0000-0002-4519-0974, University of Central Florida, corresponding author), Michael D Fetters (0000-0001-8521-5681, Japanese Family Health Program, University of Michigan Mixed Methods Research and Scholarship Program, Family Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA)
Year2018
Volume40
Issue5
Pages515-526
Publication date2018-11-28
Open AccessNo
TypeARTICLE
VenueHealth Care For Women International (JOURNAL)
Journal identifiersISSN: 0739-9332 • E-ISSN: 1096-4665
PublisherTaylor & Francis (PUBLISHER • GB)
DOI10.1080/07399332.2018.1516769
PMID30484750
OpenAlexW2903253999
LanguageEN
Citations received2
References cited22

Scholars introduce modern mixed methods research (MMR) and its application in public health research in Taiwan. Specifically, they showcase a multi-phased Taiwan cervical cancer screening mixed methods study using visual diagrams to communicate complex design procedures. While some previous researchers have incorporated quantitative and qualitative data in research, here we hope to provide significant clarity to guide those new to the MMR field. We have structured the article in the following way. First, we provide a brief overview of MMR. Second, we illustrate the compelling need for MMR from a public health perspective using cancer screenings as an example. Third, we introduce the Taiwan cervical cancer screening program as an exemplar of MMR application and the utility of visual diagrams. Study methodology can be applied to international researchers and scholars from interdisciplinary fields beyond public health

Cancer · Cervical cancer · CLARITY · Data science · Field (mathematics · Management science · Mathematics education · Multimethodology · Pathology · Perspective (graphical · Public health · Qualitative research · Social science · Sociology · Clinical practice guidelines implementation · Computer Science · Engineering · Medicine · Psychology · Artificial Intelligence

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Citations per year0.67
Citation span2023 - 2024 (2)
Highly citedNo

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