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1.  Process evaluation of appreciative inquiry to translate pain management evidence into pediatric nursing practice 
Background
Appreciative inquiry (AI) is an innovative knowledge translation (KT) intervention that is compatible with the Promoting Action on Research in Health Services (PARiHS) framework. This study explored the innovative use of AI as a theoretically based KT intervention applied to a clinical issue in an inpatient pediatric care setting. The implementation of AI was explored in terms of its acceptability, fidelity, and feasibility as a KT intervention in pain management.
Methods
A mixed-methods case study design was used. The case was a surgical unit in a pediatric academic-affiliated hospital. The sample consisted of nurses in leadership positions and staff nurses interested in the study. Data on the AI intervention implementation were collected by digitally recording the AI sessions, maintaining logs, and conducting individual semistructured interviews. Data were analysed using qualitative and quantitative content analyses and descriptive statistics. Findings were triangulated in the discussion.
Results
Three nurse leaders and nine staff members participated in the study. Participants were generally satisfied with the intervention, which consisted of four 3-hour, interactive AI sessions delivered over two weeks to promote change based on positive examples of pain management in the unit and staff implementation of an action plan. The AI sessions were delivered with high fidelity and 11 of 12 participants attended all four sessions, where they developed an action plan to enhance evidence-based pain assessment documentation. Participants labeled AI a 'refreshing approach to change' because it was positive, democratic, and built on existing practices. Several barriers affected their implementation of the action plan, including a context of change overload, logistics, busyness, and a lack of organised follow-up.
Conclusions
Results of this case study supported the acceptability, fidelity, and feasibility of AI as a KT intervention in pain management. The AI intervention requires minor refinements (e.g., incorporating continued follow-up meetings) to enhance its clinical utility and sustainability. The implementation process and effectiveness of the modified AI intervention require evaluation in a larger multisite study.
doi:10.1186/1748-5908-5-90
PMCID: PMC3000375  PMID: 21092118
2.  A realistic evaluation: the case of protocol-based care 
Background
'Protocol based care' was envisioned by policy makers as a mechanism for delivering on the service improvement agenda in England. Realistic evaluation is an increasingly popular approach, but few published examples exist, particularly in implementation research. To fill this gap, within this paper we describe the application of a realistic evaluation approach to the study of protocol-based care, whilst sharing findings of relevance about standardising care through the use of protocols, guidelines, and pathways.
Methods
Situated between positivism and relativism, realistic evaluation is concerned with the identification of underlying causal mechanisms, how they work, and under what conditions. Fundamentally it focuses attention on finding out what works, for whom, how, and in what circumstances.
Results
In this research, we were interested in understanding the relationships between the type and nature of particular approaches to protocol-based care (mechanisms), within different clinical settings (context), and what impacts this resulted in (outcomes). An evidence review using the principles of realist synthesis resulted in a number of propositions, i.e., context, mechanism, and outcome threads (CMOs). These propositions were then 'tested' through multiple case studies, using multiple methods including non-participant observation, interviews, and document analysis through an iterative analysis process. The initial propositions (conjectured CMOs) only partially corresponded to the findings that emerged during analysis. From the iterative analysis process of scrutinising mechanisms, context, and outcomes we were able to draw out some theoretically generalisable features about what works, for whom, how, and what circumstances in relation to the use of standardised care approaches (refined CMOs).
Conclusions
As one of the first studies to apply realistic evaluation in implementation research, it was a good fit, particularly given the growing emphasis on understanding how context influences evidence-based practice. The strengths and limitations of the approach are considered, including how to operationalise it and some of the challenges. This approach provided a useful interpretive framework with which to make sense of the multiple factors that were simultaneously at play and being observed through various data sources, and for developing explanatory theory about using standardised care approaches in practice.
doi:10.1186/1748-5908-5-38
PMCID: PMC2889857  PMID: 20504293

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