Methodological implications
PCD
Several alternative models and frameworks could have been considered for our analysis. In the following, we examine some possible alternatives: The Behavior Change Wheel by Susan Michie and colleagues [Our second example is the Grol and Wensing Implementation of Change Model [The Consolidated Framework for Implementation Research (CFIR) [Besides this wide range of contextual factors, the CFIR also takes individual factors into account, namely Capability, Opportunity, and Motivation (which we also found in the PCD and the behaviour change wheel). In general, we consider the CFIR to be a very suitable framework for implementation research.However, for our analyses, we chose to work with the primary care-associated PCD in order to more precisely focus on the implementation factors specific to the setting and to acknowledge the substantial potential of incorporating complexity-based models into primary care research, as emphasized in existing literature [We aim to answer this call by bringing together a complexity theory-based model (PCD) with a non-linear method (QCA). The case-based perspective and configurational understanding of QCA enabled us to identify two equifinal configurations of conditions, highlighting the fundamental notion of the PCD that primary care practices are dynamic and complex settings, where change, such as implementation efforts, does not follow a linear path [By identifying complex causal patterns with QCA, we demonstrated that the PCD effectively explains changes in a primary care setting. Our findings support the basic assumption of the PCD that practices are adaptive learning systems that evolve through an interaction of internal and external factors [Furthermore, by combining QCA and PCD we believe we have been able to address some existing research gaps such as the mechanisms underpinning the interplay of organizational factors and the relevance of organizational readiness to change and organizational resilience in particular.QCA is capable of identifying equifinal patterns in a dataset and attributing context-sensitive causality, going beyond the single-cause attribution that statistical methods would typically provide [It is worth noting that for researchers looking to delve deeper into qualitative methodologies beyond QCA, there exists a range of methodological alternatives, including Realist Evaluation [