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Repeated calls have been made for the increased use of theory in designing and evaluating improvement and implementation interventions.1–4 The benefits are argued to include identifying contextual influences on quality improvement (QI), supporting the generalisability of findings and anticipating how future phenomena might unfold.2 5 Most importantly, the ability of theories to provide robust explanations is invaluable for understanding how, why and in what circumstances interventions work (or do not work),6 thus addressing crucial questions relating, for example, to variation in improvement outcomes.4 7
Although the use of theory in improvement and implementation research appears to be increasing over time,8 the emphasis largely remains on adopting a theoretically informed approach, that is, applying theory to design an intervention or to systematise and explain evaluation findings. Despite the recognised need to ‘test’ theories by scrutinising their assumptions in the light of empirical findings,9 improvement researchers are often inclined to treat existing theoretical knowledge as received wisdom which is rarely critiqued and hardly ever moved forward. This often results in a one-way relationship, whereby theory shapes data collection and analysis, but little effort is made to explain what the resulting empirical findings mean for theory.
Part of the problem is that theories may be reduced to lists of ‘contextual factors’ rather than providing explanations that would uncover causal relationships between them.10 This is in contrast to other social science fields, such as organisation and management studies, where theories are seen as ‘examined sets of concepts’ aiming to reveal previously hidden mechanisms underpinning the development of social phenomena.11 Rather than producing exhaustive lists of variables, the aim here is to focus on a relatively limited number of key concepts but explore …
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