Mixed Methods and Simulation Studies

Mixed methods (combining qualitative and quantitative methods in a single study) is increasingly popular in health services research. The often piecemeal roll-out of policy and health services interventions makes some level of qualitative understanding vital for planning and understanding what exactly you are evaluating and the meaning of any results. This is particularly true for non-random quantitative evaluation where the researcher is not in charge of rolling out the intervention themselves, but can also be helpful for a randomised experiment.

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Mixed methods is an evolving methodological area, and there is little consensus on standardised reporting and evaluating quality of these studies. A number of texts are available to introduce the method and describe its importance in the context of health services research, however:

  • Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (Cresswell, 2009)

  • Mixed Methods Research: A discussion paper (Brennan, 2005)

  • Why, and how, mixed methods research is undertaken in health services research in England: a mixed methods study (O'Cathain et al, 2007)

  • Three techniques for integrating data in mixed methods studies (O'Cathain et al, 2010)

  • The Quality of Mixed Methods Studies in Health Services Research (O'Cathain et al, 2017)

When executed successfully, mixed methods research can accomplish a depth of reporting and understanding beyond many individual methodological approaches. This can help lead to high-impact publications. Examples of mixed methods research papers:

  • Primary care pedometer-based walking intervention: mixed-methods results from 3 year follow-up of PACE-UP cluster-randomised controlled trial (Wahlich et al, 2017)

  • Is a specialist breathlessness service more effective and cost-effective for patients with advanced cancer and their carers than standard care? Findings of a mixed-method randomised controlled trial (Farquhar et al, 2014)

  • An exploratory mixed methods study of the acceptability and effectiveness of mindfulness -based cognitive therapy for patients with active depression and anxiety in primary care (Finucane & Mercer, 2006)

Simulation studies can offer researchers insights beyond what can be directly observed, and in a safe and controlled environment. For example:

  • Using clinical simulation to study how to improve quality and safety in healthcare (Lame & Dixon-Woods, 2018)

  • Systems modelling and simulation in health service design, delivery and decision making (Pitt et al, 2015)