Skip to main content

Table 1 Traditional versus new paradigm approaches to researching health services and systems

From: Studying complexity in health services research: desperately seeking an overdue paradigm shift

  Traditional approach New paradigm (complexity-informed) approach
Goal of research Establishing the truth, universal and enduring; finding solutions to well-defined problems Exploring tensions; generating insights and wisdom; exposing multiple perspectives; viewing complex systems as moving targets
Assumed model of causality Linear, cause-and-effect causality (perhaps incorporating mediators and moderators) Emergent causality: multiple interacting influences account for a particular outcome but none can be said to have a fixed ‘effect size’
Typical format of research question “What is the effect size of the intervention on the predefined outcome, and is it statistically significant?” “What combination of influences has generated this phenomenon? What does the intervention of interest contribute? What happens to the system and its actors if we intervene in a particular way? What are the unintended consequences elsewhere in the system?”
Mode of representation Attempt to represent research in one authoritative voice Attempt to illustrate the plurality of voices inherent in the research and phenomena under study
Good research is characterised by Methodological ‘rigour’, i.e. strict application of structured and standardised design, conventional approaches to generalisability and validity Strong theory, flexible methods, pragmatic adaptation to emerging circumstances, contribution to generative learning and theoretical transferability
Purpose of theorising Disjunctive: simplification and abstraction; breaking problems down into analysable parts Conjunctive: drawing parts of the problem together to produce a rich, nuanced picture of what is going on and why
Approach to data Research should continue until data collection is complete Data will never be complete or perfect; decisions often need to be made in situations of incomplete or contested data
Analytic focus Dualisms: A versus B; influence of X on Y Dualities: inter-relationships and dynamic tensions between A, B, C and other emergent aspects