The embedded researcher model in Australian healthcare settings: comparison by degree of "embeddedness"

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Coates, Dominiek
Mickan, Sharon
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The embedded researcher model is a health-academic partnership where researchers are core members of a healthcare organization, with an aim to support evidence translation. The purpose of this study was to describe the characteristics and experiences of embedded researchers in Australian healthcare settings, and investigate how the model is experienced differently based on the level of "embeddedness." This exploratory study utilized a purpose-designed online survey. Responses were described using Word and Excel and analyzed using SPSS. To investigate how the model was experienced based on the level of "embeddedness," we tested for differences in responses between respondents with primary academic vs healthcare affiliations. A total of 104 embedded researchers from nursing and midwifery, allied health and medicine completed the survey, with equal numbers reporting a primary academic vs primary healthcare affiliation. Most indicated that research is a strategic objective of the healthcare organization (85.9%) yet almost a third (31%) reported that research outputs were not measured. While 60% agreed that clinical practice informed by research was valued, only 28% reported having adequate resources. Of those with a formal dual affiliation over a quarter reported conflict between expectations of the healthcare and academic organizations. Respondents with a primary academic affiliation were older, more qualified, had more research experience, had been in the role longer, and had more positive perceptions of the research culture of healthcare organizations. This study provides a starting point for healthcare organizations and academic institutions to partner in the further development and implementation of this model.

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Translational Research
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Clinical sciences
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Coates, D; Mickan, S, The embedded researcher model in Australian healthcare settings: comparison by degree of "embeddedness"., Translational Research, 2019