Preface to Models@run.time 2016

The complexity of adapting software during runtime has spawned interest in how models can be used to validate, monitor and adapt runtime behaviour. The use of models during runtime extends the use of modeling techniques beyond the design and implementation phases. The goal of this workshop is to look at issues related to developing appropriate modeldriven approaches to managing and monitoring the execution of systems and, also, to allow the system to reason about itself. We aim to continue the discussion of research ideas and proposals from researchers who work in relevant areas such as MDE, software architectures, reflection, and autonomic and self-adaptive systems, and provide a 'state-of-the-art' research assessment expressed in terms of challenges and achievements.

Clinical interventions, implementation interventions, and the potential greyness in between - a discussion paper

Background: There is increasing awareness that regardless of the proven value of clinical interventions, the use of effective strategies to implement such interventions into clinical practice is necessary to ensure that patients receive the benefits. However, there is often confusion between what is the clinical intervention and what is the implementation intervention. This may be caused by a lack of conceptual clarity between 'intervention' and 'implementation', yet at other times by ambiguity in application. We suggest that both the scientific and the clinical communities would benefit from greater clarity; therefore, in this paper, we address the concepts of intervention and implementation, primarily as in clinical interventions and implementation interventions, and explore the grey area in between. Discussion: To begin, we consider the similarities, differences and potential greyness between clinical interventions and implementation interventions through an overview of concepts. This is illustrated with reference to two examples of clinical interventions and implementation intervention studies, including the potential ambiguity in between. We then discuss strategies to explore the hybridity of clinical-implementation intervention studies, including the role of theories, frameworks, models, and reporting guidelines that can be applied to help clarify the clinical and implementation intervention, respectively. Conclusion: Semantics provide opportunities for improved precision in depicting what is 'intervention' and what is 'implementation' in health care research. Further, attention to study design, the use of theory, and adoption of reporting guidelines can assist in distinguishing between the clinical intervention and the implementation intervention. However, certain aspects may remain unclear in analyses of hybrid studies of clinical and implementation interventions. Recognizing this potential greyness can inform further discourse.