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Background: The concept of "mechanism" is central to realist approaches to research, yet research teams struggle to operationalize and apply the concept in empirical research. Our large, interdisciplinary research team has also experienced challenges in making the concept useful in our study of the implementation of models of integrated community-based primary health care (ICBPHC) in three international jurisdictions (Ontario and Quebec in Canada, and in New Zealand).Methods: In this paper we summarize definitions of mechanism found in realist methodological literature, and report an empirical example of a realist analysis of the implementation ICBPHC.Results: We use our empirical example to illustrate two points. First, the distinction between contexts and mechanisms might ultimately be arbitrary, with more distally located mechanisms becoming contexts as research teams focus their analytic attention more proximally to the outcome of interest. Second, the relationships between mechanisms, human reasoning, and human agency need to be considered in greater detail to inform realist-informed analysis; understanding these relationships is fundamental to understanding the ways in which mechanisms operate through individuals and groups to effect the outcomes of complex health interventions.Conclusions: We conclude our paper with reflections on human agency and outline the implications of our analysis for realist research and realist evaluation. [ABSTRACT FROM AUTHOR]

Background: Effectiveness of interventions in pragmatic trials may not translate directly into population impact, because of limited uptake by clinicians and/or the public. Uptake of an intervention is influenced by a number of factors.Methods: We propose a method for calculating population impact of clinical interventions that accounts for the intervention uptake. We suggest that population impact may be estimated by multiplying the two key components: (1) the effectiveness of the intervention in pragmatic trials (trial effect); and, (2) its uptake in clinical practice. We argue that participation rates in trials may be a valid proxy for uptake in clinical practice and, in combination with trial effectiveness estimates, be used to rank interventions by their likely population impact. We illustrate the method using the example of four interventions to decrease antibiotic prescription for acute respiratory infections in primary care: delayed prescribing, procalcitonin test, C-Reactive Protein, shared decision making.Results: In order to estimate uptake of interventions from trial data we need detailed reporting on the recruitment processes used for clinician participation in the trials. In the antibiotic prescribing example, between 75 and 91% of the population would still be prescribed or consume antibiotics because effective interventions were not taken up. Of the four interventions considered, we found that delayed prescribing would have the highest population impact and shared decision making the lowest.Conclusion: Estimates of uptake and population impact of an intervention may be possible from pragmatic RCTs, provided the recruitment processes for these trials are adequately reported (which currently few of them are). Further validation of this method using empirical data on intervention uptake in the real world would support use of this method to decide on public funding of interventions. [ABSTRACT FROM AUTHOR]