Designing high-quality implementation research: development, application, feasibility and preliminary evaluation of the implementation science research development (ImpRes) tool and guide

Background:  Designing implementation research can be a complex and daunting task, especially for applied health researchers who have not received specialist training in implementation science. We developed the Implementation Science Research Development (ImpRes) tool and supplementary guide to address this challenge and provide researchers with a systematic approach to designing implementation research. Methods:  A multi-method and multi-stage approach was employed. An international, multidisciplinary expert panel engaged in an iterative brainstorming and consensus-building process to generate core domains of the ImpRes tool, representing core implementation science principles and concepts that researchers should consider when designing implementation research. Simultaneously, an iterative process of reviewing the literature and expert input informed the development and content of the tool. Once consensus had been reached, specialist expert input was sought on involving and engaging patients/service users; and economic evaluation. ImpRes was then applied to 15 implementation and improvement science projects across the National Institute of Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London, a research organisation in London, UK. Researchers who applied the ImpRes tool completed an 11-item questionnaire evaluating its structure, content and usefulness. Results:  Consensus was reached on ten implementation science domains to be considered when designing implementation research. These include implementation theories, frameworks and models, determinants of implementation, implementation strategies, implementation outcomes and unintended consequences. Researchers who used the ImpRes tool found it useful for identifying project areas where implementation science is lacking (median 5/5, IQR 4–5) and for improving the quality of implementation research (median 4/5, IQR 4–5) and agreed that it contained the key components that should be considered when designing implementation research (median 4/5, IQR 4–4). Qualitative feedback from researchers who applied the ImpRes tool indicated that a supplementary guide was needed to facilitate use of the tool. Conclusions:  We have developed a feasible and acceptable tool, and supplementary guide, to facilitate consideration and incorporation of core principles and concepts of implementation science in applied health implementation research. Future research is needed to establish whether application of the tool and guide has an effect on the quality of implementation research

A large community outbreak of waterborne giardiasis- delayed detection in a non-endemic urban area

BACKGROUND: Giardia is not endemic in Norway, and more than 90% of reported cases acquire the infection abroad. In late October 2004, an increase in laboratory confirmed cases of giardiasis was reported in the city of Bergen. An investigation was started to determine the source and extent of the outbreak in order to implement control measures. METHODS: Cases were identified through the laboratory conducting giardia diagnostics in the area. All laboratory-confirmed cases were mapped based on address of residence, and attack rates and relative risks were calculated for each water supply zone. A case control study was conducted among people living in the central area of Bergen using age- and sex matched controls randomly selected from the population register. RESULTS: The outbreak investigation showed that the outbreak started in late August and peaked in early October. A total of 1300 laboratory-confirmed cases were reported. Data from the Norwegian Prescription Database gave an estimate of 2500 cases treated for giardiasis probably linked to the outbreak. There was a predominance of women aged 20–29 years, with few children or elderly. The risk of infection for persons receiving water from the water supply serving Bergen city centre was significantly higher than for those receiving water from other supplies. Leaking sewage pipes combined with insufficient water treatment was the likely cause of the outbreak. CONCLUSION: Late detection contributed to the large public health impact of this outbreak. Passive surveillance of laboratory-confirmed cases is not sufficient for timely detection of outbreaks with non-endemic infections

Observational measure of implementation progress in community based settings: The Stages of implementation completion (SIC)

<p>Abstract</p> <p>Background</p> <p>An increasingly large body of research is focused on designing and testing strategies to improve knowledge about how to embed evidence-based programs (EBP) into community settings. Development of strategies for overcoming barriers and increasing the effectiveness and pace of implementation is a high priority. Yet, there are few research tools that measure the implementation process itself. The Stages of Implementation Completion (SIC) is an observation-based measure that is used to track the time to achievement of key implementation milestones in an EBP being implemented in 51 counties in 53 sites (two counties have two sites) in two states in the United States.</p> <p>Methods</p> <p>The SIC was developed in the context of a randomized trial comparing the effectiveness of two implementation strategies: community development teams (experimental condition) and individualized implementation (control condition). Fifty-one counties were randomized to experimental or control conditions for implementation of multidimensional treatment foster care (MTFC), an alternative to group/residential care placement for children and adolescents. Progress through eight implementation stages was tracked by noting dates of completion of specific activities in each stage. Activities were tailored to the strategies for implementing the specific EBP.</p> <p>Results</p> <p>Preliminary data showed that several counties ceased progress during pre-implementation and that there was a high degree of variability among sites in the duration scores per stage and on the proportion of activities that were completed in each stage. Progress through activities and stages for three example counties is shown.</p> <p>Conclusions</p> <p>By assessing the attainment time of each stage and the proportion of activities completed, the SIC measure can be used to track and compare the effectiveness of various implementation strategies. Data from the SIC will provide sites with relevant information on the time and resources needed to implement MTFC during various phases of implementation. With some modifications, the SIC could be appropriate for use in evaluating implementation strategies in head-to-head randomized implementation trials and as a monitoring tool for rolling out other EBPs.</p

Neural networks and dynamical systems

AbstractModels for the identification and control of nonlinear dynamical systems using neural networks were introduced by Narendra and Parthasarathy in 1990, and methods for the adjustment of model parameters were also suggested. Simulation results of simple nonlinear systems were presented to demonstrate the feasibility of the schemes proposed. The concepts introduced at that time are investigated in this paper in greater detail. In particular, a number of questions that arise when the methods are applied to more complex systems are addressed. These include nonlinear systems of higher order as well as multivariable systems. The effect of using simpler models for both identification and control are discussed, and a new controller structure containing a linear part in addition to a multilayer neural network is introduced

Combined use of the Consolidated Framework for Implementation Research (CFIR) and the Theoretical Domains Framework (TDF): A systematic review

Background: Over 60 implementation frameworks exist. Using multiple frameworks may help researchers to address multiple study purposes, levels, and degrees of theoretical heritage and operationalizability; however, using multiple frameworks may result in unnecessary complexity and redundancy if doing so does not address study needs. The Consolidated Framework for Implementation Research (CFIR) and the Theoretical Domains Framework (TDF) are both well-operationalized, multi-level implementation determinant frameworks derived from theory. As such, the rationale for using the frameworks in combination (i.e., CFIR + TDF) is unclear. The objective of this systematic review was to elucidate the rationale for using CFIR + TDF by (1) describing studies that have used CFIR + TDF, (2) how they used CFIR + TDF, and (2) their stated rationale for using CFIR + TDF. Methods: We undertook a systematic review to identify studies that mentioned both the CFIR and the TDF, were written in English, were peer-reviewed, and reported either a protocol or results of an empirical study in MEDLINE/PubMed, PsycInfo, Web of Science, or Google Scholar. We then abstracted data into a matrix and analyzed it qualitatively, identifying salient themes. Findings: We identified five protocols and seven completed studies that used CFIR + TDF. CFIR + TDF was applied to studies in several countries, to a range of healthcare interventions, and at multiple intervention phases; used many designs, methods, and units of analysis; and assessed a variety of outcomes. Three studies indicated that using CFIR + TDF addressed multiple study purposes. Six studies indicated that using CFIR + TDF addressed multiple conceptual levels. Four studies did not explicitly state their rationale for using CFIR + TDF. Conclusions: Differences in the purposes that authors of the CFIR (e.g., comprehensive set of implementation determinants) and the TDF (e.g., intervention development) propose help to justify the use of CFIR + TDF. Given that the CFIR and the TDF are both multi-level frameworks, the rationale that using CFIR + TDF is needed to address multiple conceptual levels may reflect potentially misleading conventional wisdom. On the other hand, using CFIR + TDF may more fully define the multi-level nature of implementation. To avoid concerns about unnecessary complexity and redundancy, scholars who use CFIR + TDF and combinations of other frameworks should specify how the frameworks contribute to their study. Trial registration: PROSPERO CRD4201502761

Explaining oscillations and variability in the p53-Mdm2 system

<p>Abstract</p> <p>Background</p> <p>In individual living cells p53 has been found to be expressed in a series of discrete pulses after DNA damage. Its negative regulator Mdm2 also demonstrates oscillatory behaviour. Attempts have been made recently to explain this behaviour by mathematical models but these have not addressed explicit molecular mechanisms. We describe two stochastic mechanistic models of the p53/Mdm2 circuit and show that sustained oscillations result directly from the key biological features, without assuming complicated mathematical functions or requiring more than one feedback loop. Each model examines a different mechanism for providing a negative feedback loop which results in p53 activation after DNA damage. The first model (ARF model) looks at the mechanism of p14^ARFwhich sequesters Mdm2 and leads to stabilisation of p53. The second model (ATM model) examines the mechanism of ATM activation which leads to phosphorylation of both p53 and Mdm2 and increased degradation of Mdm2, which again results in p53 stabilisation. The models can readily be modified as further information becomes available, and linked to other models of cellular ageing.</p> <p>Results</p> <p>The ARF model is robust to changes in its parameters and predicts undamped oscillations after DNA damage so long as the signal persists. It also predicts that if there is a gradual accumulation of DNA damage, such as may occur in ageing, oscillations break out once a threshold level of damage is acquired. The ATM model requires an additional step for p53 synthesis for sustained oscillations to develop. The ATM model shows much more variability in the oscillatory behaviour and this variability is observed over a wide range of parameter values. This may account for the large variability seen in the experimental data which so far has examined ARF negative cells.</p> <p>Conclusion</p> <p>The models predict more regular oscillations if ARF is present and suggest the need for further experiments in ARF positive cells to test these predictions. Our work illustrates the importance of systems biology approaches to understanding the complex role of p53 in both ageing and cancer.</p

Qualitative study on the implementation of professional pharmacy services in Australian community pharmacies using framework analysis

Abbreviations: BCT, Behavioural change techniques taxonomy; BCW, Behavioural change wheel; CFIR, Consolidated framework for implementation research; EPOC, Cochrane effective practice and organisation of care; FISpH, Framework for the implementation of services in pharmacy; GIF, Generic implementation framework; KPI, Key performance indicator; TDF, Theoretical domains frameworkBackground: Multiple studies have explored the implementation process and influences, however it appears there is no study investigating these influences across the stages of implementation. Community pharmacy is attempting to implement professional services (pharmaceutical care and other health services). The use of implementation theory may assist the achievement of widespread provision, support and integration. The objective was to investigate professional service implementation in community pharmacy to contextualise and advance the concepts of a generic implementation framework previously published. Methods: Purposeful sampling was used to investigate implementation across a range of levels of implementation in community pharmacies in Australia. Twenty-five semi-structured interviews were conducted and analysed using a framework methodology. Data was charted using implementation stages as overarching themes and each stage was thematically analysed, to investigate the implementation process, the influences and their relationships. Secondary analyses were performed of the factors (barriers and facilitators) using an adapted version of the Consolidated Framework for Implementation Research (CFIR), and implementation strategies and interventions, using the Expert Recommendations for Implementing Change (ERIC) discrete implementation strategy compilation. Results: Six stages emerged, labelled as development or discovery, exploration, preparation, testing, operation and sustainability. Within the stages, a range of implementation activities/steps and five overarching influences (pharmacys' direction and impetus, internal communication, staffing, community fit and support) were identified. The stages and activities were not applied strictly in a linear fashion. There was a trend towards the greater the number of activities considered, the greater the apparent integration into the pharmacy organization. Implementation factors varied over the implementation stages, and additional factors were added to the CFIR list and definitions modified/contextualised for pharmacy. Implementation strategies employed by pharmacies varied widely. Evaluations were lacking. Conclusions: The process of implementation and five overarching influences of professional services implementation in community pharmacy have been outlined. Framework analysis revealed, outside of the five overarching influences, factors influencing implementation varied across the implementation stages. It is proposed at each stage, for each domain, the factors, strategies and evaluations should be considered. The Framework for the Implementation of Services in Pharmacy incorporates the contextualisation of implementation science for pharmacy.The study was funded as part of a University of Technology Sydney (UTS) Research Excellence Scholarship (RES), comprising of an Australian Postgraduate Award (APA) Scholarship funded by the Australian Government, plus a Top-up funded by the University of Technology Sydney, received from the primary author (JCM)