Using a systematic review to develop a taxonomy of uncertainties in health care to structure the design of future participatory research

Date & Time
Monday, September 4, 2023, 12:30 PM - 2:00 PM
Location Name
Pickwick
Session Type
Poster
Category
Qualitative synthesis methods
Authors
Eachempati P1, Nasser M1
1University of Plymouth, UK
Description

Background: Uncertainty pervades every aspect of the healthcare system. Identifying the different meanings and conceptual models of uncertainty proposed in healthcare with a systematic review will allow us to explore the patterns emerging from such models so that we can move further to identify how people interpret and respond to such uncertainties. Objective: The objective of this article is to showcase how we developed a holistic model of uncertainties that covers different levels of decision-making in healthcare based on findings from a systematic review and how it helped us shape our primary research. Methodology: A total of 4,143 articles were obtained and screened by two authors. Thirty-one studies were included in the review. Thematic synthesis was done by a clinician, a nonclinicaian and a methodology expert to compare the different approaches to the interpretation of data.
Results: Based on themes identified, we developed an overarching model of uncertainty. We illustrated the model at three distinct yet interdependent levels: the macro, meso and microlevel. We involved a few patients informally and sought their views on the developed model.
Conclusions: This systematic review was able to deconstruct the separate layers of uncertainty affecting health decisions and allowed us to acknowledge that uncertainty can change and evolve during interactions between different people. We used this framework to design an innovative participatory approach for our project which intends to explore how individuals of different ethnicities and uncertainty tolerance respond to uncertainties in oral health decisions. The approach can be extrapolated and adapted for other similar projects.