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Systems Thinking, Knowledge and Action: Towards Better Models and Methods
Abstract and Figures
The way we think about how research, policy and practice inform and interact with each other shapes our efforts to improve health and social outcomes. In this paper we describe linear, relationship and systems models with regard to how they approach bridging evidence and policy/practice, or turning knowledge into action. We contribute to the knowledge to action (KTA) systems thinking discussion by highlighting four interconnected aspects of this model we believe merit exploration: evidence and knowledge, leadership, networks and communications. We conclude with the challenge of developing measurement methods for systems research to better understand the KTA process.
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... Proponents of knowledge mobilisation emphasise the importance of long-term collaborations between researchers and research users, the influence of users upon research questions and a reciprocally enhanced understanding of research by end-users and end-users by researchers, in turn [13,22]. Best and Holmes [23] conceptualise different perspectives on getting knowledge into action as (1) linear models, (2) relationship models and (3) systems models. This paper uses their 'three-generations' perspective to provide theoretical insight into the process of trying to mobilise knowledge from healthcare research (to which they refer as 'knowledge to action'). ...
... Evaluation of the potential use of each product was based upon objective measurements (website hits) and stakeholder opinion of current and future utilisation [33]. By using Best and Holmes's [23] systems thinking model of knowledge mobilisation, a theoretically informed approach to the analysis was taken [34]. ...
... The comparative case study approach enabled the in-depth study of complex contemporaneous phenomena [36,37] and the development of broader generalisations [38][39][40]. This approach has been advocated for the study of dissemination and implementation research [31,41] more broadly and knowledge mobilisation more specifically [23,42]. ...
Background
Getting knowledge from healthcare research into practice (knowledge mobilisation) remains a global challenge. One way in which researchers may attempt to do this is to develop products (such as toolkits, actionable tools, dashboards, guidance, audit tools, protocols and clinical decision aids) in addition to journal papers. Despite their increasing ubiquity, the development of such products remains under-explored in the academic literature. This study aimed to further this understanding by exploring the development of products from healthcare research and how the process of their development might influence their potential application.
Methods
This study compared the data generated from a prospective, longitudinal, comparative case study of four research projects which aimed to develop products from healthcare research. Qualitative methods included thematic analysis of data generated from semi-structured interviews (38), meeting observations (83 h) and project documents (300+). Cases were studied for an average of 11.5 months (range 8–19 months).
Results
Case comparison resulted in the identification of three main themes with the potential to affect the use of products in practice. First, aspects of the product , including the perceived need for the specific product being identified, the clarity of product aim and clarity and range of end-users. Second, aspects of development , whereby different types of stakeholder engagement appear to influence potential product application, which either needs to be ‘meaningful’, or delivered through the implicit understanding of users’ needs by the developing team. The third, overarching theme, relates to the academic context in which products are developed, highlighting how the academic context perpetuates the development of products, which may not always be useful in practice.
Conclusions
This study showed that aspects of products from healthcare research (need/aim/end-user) and aspects of their development (stakeholder engagement/implicit understanding of end-users) influence their potential application. It explored the motivation for product development and identifies the influence of the current academic context on product development. It shows that there is a tension between ideal ‘systems approaches’ to knowledge mobilisation and ‘linear approaches’, which appear to be more pervasive in practice currently. The development of fewer, high-quality products which fulfil the needs of specified end-users might act to counter the current cynicism felt by many stakeholders in regard to products from healthcare research.
... In other public policy areas, similar issues have been found, and one explanation that informs the approach in this article relates to the argument of Best and Holmes (2010) in the health sector. They suggest that previous 'generations' of approaches to research use have only partially understood how research evidence can inform practice. ...
... Here we further interrogate the literature on research use, building on our introduction in section 1 of Best and Holmes' (2010) 'three generations' of system approaches. Researchers have recognised a series of limitations of traditional, linear research-use approaches, centred on evidence that 'passive' dissemination of research alone is unlikely to impact significantly on practitioners' behaviours (Best & Holmes, 2010;Levin, 2013;Nutley et al., 2007). In terms of dissemination, communicating research is more likely to impact on decision-making if it is also combined with strategies that generate opportunities, motivation and skills for What are the actors and the roles they fulfil in the system under study? ...
... Turning next to the importance of relationships (Best and Holmes, 2010's second-generation approach), Best's influential work on 'knowledge to action' systems captures this principle well, in highlighting that activities and processes to encourage research use do not work in isolation, but sit within complex systems outside of research, with multiple actors and influences, each with their own priorities, motivations, processes, time-scales and world views (Best & Holmes, 2010). One of the features of such a systems model is that the degree of research engagement is a function of the effective integration with external organisations and the systems in which they operate. ...
Models of research use in education tend to focus on specific elements of education systems or underplay the complexity of system change. Within other public policy areas, notably health, more work has been undertaken to integrate systems thinking when considering knowledge mobilisation and research use. In this paper, we survey public policy system change literature to develop a set of system dimensions. We use these to examine models relating to research use that are widely referenced in education. We then apply these dimensions to the work of the Education Endowment Foundation (EEF), the UK's What Works Centre for Education, which aims to support evidence-informed practice at all levels of the education system. We focus on its work to embed research-informed practices in regional school systems, through a case analysis of two ‘scale-up campaigns’ to mobilise evidence relating to the effective deployment of teaching assistants (educational support paraprofessionals). The findings highlight the value of using the system dimensions framework as a diagnostic tool to understand how to effect system change, highlighting the key role of brokerage and system leadership at different system levels; school-level capacity to implement change; and system relationships.
... The theoretical models that best fit implementation science in corrections are from multiple contexts, but have key features (Best & Holmes, 2010;Damschroder et al., 2009) outer setting is composed of economic, political, and social issues outside of the agency that influence the agency. As a result, implementation and buy-in to research needs to be conducted at every level of the system, because changing one level is not sufficient (Damschroder et al., 2009). ...
... Similar to both the KTA systems model and the Consolidated Framework, successful implementation in correctional agencies needs to be addressed at each of the following levels, since each level has their own interdependent subsystem with multiple agents: (a) the state and local level outside of the agency (e.g., political priorities, community values, state and local regulations), (b) the agency level (e.g., resources available for training, amount of staff, financial capabilities), (c) the management level (e.g., supervision skills, amount of collaboration and support towards those they supervise, leadership, individual characteristics, beliefs, perceptions, and attitudes), and (d) the staff level (e.g., fidelity of EBPs, competencies and motivation to use EBPs, caseload size, individual differences, conflict between dual-roles; Alexander, 2011). They view an agency as a living, breathing, and dynamic system with many interrelated and interdependent aspects; if one level changes, the whole system is affected (Best & Holmes, 2010;Joplin et al., 2004;Lane, Turner, & Flores, 2004). ...
The Risk-Need-Responsivity (RNR) model’s authentic content and iterative research documented in early writings has become ‘lost scrolls’ of the past. This chapter revitalizes foundational theoretical explanations from the lost scrolls and provides an abbreviated timeline of seminal studies in the 1970s and 1980s that led to the creation of RNR. The methodological rigor, theoretical support, and practical considerations that built each RNR principle are explored. Throughout the chapter, the pioneers’ words from the lost scrolls are resurrected through quotes from Andrews and colleagues to illustrate foundation concepts, such as “Statements to the effect that acquisition, maintenance, and modification of criminal and noncriminal behavior are governed by similar principles does not constitute a theory of criminal behavior. They are statements concerning a general theory of behavior” [emphasis added] (Andrews, 1980, p. 450). Further, the chapter explores how social learning theory is at the heart of why targeting criminogenic needs during interventions is effective at reducing recidivism. Lastly, the chapter discusses next steps in knowledge accumulation, such as the use of multidisciplinary implementation models. The chapter concludes by presenting lessons learned from the pioneers, such as noting the limitations of statistical significance and the importance of replication, transparent reporting, and building mutually beneficial partnerships.
... Tackling such barriers requires more than improved reporting and dissemination of research. Epidemiologists must find ways to address the real-world needs of policymakers and practitioners [13]; focusing less on supply and more on demand [14], tackling current policy questions and grappling with the complex systems and "wicked" problems that are central to policymaking [15,16]]. To this end, research-policy partnerships and other forms of cross-sector interaction are well established as the most productive means for advancing evidenceinformed policy [13,[17][18][19][20][21][22]. ...
Background
Use of epidemiological research in policy and practice is suboptimal, contributing to significant preventable morbidity and mortality. Barriers to the use of research evidence in policy include lack of research–policy engagement, lack of policy-relevant research, differences in policymaker and researcher practice norms, time constraints, difficulties in coordination, and divergent languages and reward systems.
Approach and outcomes
In order to increase policy-relevant research and research uptake, we developed the output-orientated policy engagement (OOPE) model, in Australia. It integrates a foundational approach to engagement with cycles of specific activity focused around selected research outputs. Foundational elements include measures to increase recognition and valuing of policymaker expertise, emphasis on policy uptake, policy awareness of the research group’s work, regular policy engagement and policy-relevant capacity-building. Specific activities include (i) identification of an “output”—usually at draft stage—and program of work which are likely to be of interest to policymakers; (ii) initial engagement focusing on sharing “preview” evidence from this output, with an invitation to provide input into this and to advise on the broader program of work; and (iii) if there is sufficient interest, formation of a researcher–policy-maker partnership to shape and release the output, as well as inform the program of work. This cycle is repeated as the relationship continues and is deepened. As well as supporting policy-informed evidence generation and research-aware policymakers, the output-orientated model has been found to be beneficial in fostering the following: a pragmatic starting place for researchers, in often large and complex policy environments; purposeful and specific engagement, encouraging shared expectations; non-transactional engagement around common evidence needs, whereby researchers are not meeting with policymakers with the expectation of receiving funding; built-in translation; time and resource efficiency; relationship-building; mutual learning; policy-invested researchers and research-invested policy-makers; and tangible policy impacts. A case study outlines how the output-orientated approach supported researcher–policymaker collaboration to generate new evidence regarding Aboriginal and Torres Strait Islander cardiovascular disease risk and to apply this to national guidelines.
Conclusion
Output-orientated policy engagement provides a potentially useful pragmatic model to catalyse and support partnerships between researchers and policymakers, to increase the policy-relevance and application of epidemiological evidence.
... In the relational model, knowledge comes from multiple sources (research, theory, policy, practice), not just from the researcher. Its use and effectiveness depends on effective relationships and processes (Best, Holmes, 2010). ...
Globalization is shaping new societies, new kinds of communication, intensification of travels, pervasion of media, acceleration of information, at the same time as the news become outdated in few seconds. The rapidity of media exchanges is relentlessly dragging technology, like technology circularly increases the frequency and speed of news. The waves of information will change our attitude of thinking, even the brain mechanisms, forging a new social order. All this imposes new practices of teaching, in general, and in environmental, in particular, correlated to new procedures of teachers’ training. The new teachers should be instructed in technology, like they must instruct apprentices, to know the influence of the Web on identifying different appearances of society. There is a need of specialists, suitable for organizing the students, navigation into the ocean of information, at the same time, instructors must protect the youngest from the ultra-infiltration and dominance or pervasion of the Web. The educators’ job is progressively complicated, since education occurs yet more outside the school’s room in an amazing number of ways. The global world has open windows and open doors: everything (or almost) enters and everything goes out, creating opportunities, but also risks.
Im Wissenstransfer wird wissenschaftliches Wissen so aufbereitet, dass es in anderen gesellschaftlichen Zusammenhängen bedarfsabhängig nutzbar wird. Hierzu wird es in außerwissenschaftliche Handlungskontexte eingeordnet und dabei für eine konkrete Problemstellung adaptiert. Es findet also eine Übersetzung von bisher wissenschaftlich konfiguriertem Wissen in Praxisfelder statt. Häufig findet dies im Modus einer Koproduktion von Wissen statt, indem Wissenschaftler und Praktikerinnen gemeinsam und iterativ den Transfer und die diesem zugrundeliegende Forschung gestalten. Typische Formen sind Kooperationen mit externen Partnern in Projekten der angewandten Forschung/Innovation.
Despite the widespread effort to increase and improve the use of evidence in policy making and practice, practical efforts to enhance research-policy-practice engagement in the education sector often fall short of their ambition. Little is known about how such knowledge mobilisation initiatives can be characterised and how their impact can be understood and measured. This paper reviews theoretical and empirical literature on knowledge mobilisation focusing on the above research gaps. It conceptualises knowledge mobilisation actors and initiatives, discusses the shortcomings of the current literature, and proposes a set of frameworks that captures their objectives, functions and impact. It is hoped that these frameworks will support future empirical research efforts.
This chapter presents the results of the OECD Strengthening the Impact of Education Research policy survey with regard to the various mechanisms countries are using to facilitate research use. It presents a framework for classifying factors that influence research use, based on a review of literature. It then describes and contrasts mechanisms and barriers reported by the 37 survey-participating education systems. The chapter concludes by noting the importance of system-level coordination of the various mechanisms and research production.
This chapter provides an overview of some dominant models of knowledge mobilisation. First, it compares and contrasts these models using the three approaches of thinking described by Best and Holmes: Linear, relationship and systems. Second, the chapter highlights some additional, more recent models that focus on a specific aspect of research dynamics. The last section builds on these models and presents recommendations to capture the research dynamics at play within the complex interactions of education research, policy and practice. These recommendations may inform the development of a future model which could ultimately enhance student and professional learning.
This paper discusses the evaluation of networks of community-based, mostly publicly funded health, human service, and public welfare organizations. Consistent with pressures to perform effectively by a broad range of stakeholders, we argue that networks must be evaluated at three levels of analysis; community, network, and organization/participant levels. These three levels of analysis are closely related but each has its own set of effectiveness criteria that must be considered. We outline these criteria, discussing how effectiveness at one level of network analysis may or may not match effectiveness criteria at another level. We also discuss the importance of key stakeholders and how multiple constituents may be satisfied through the formation and maintenance of service delivery networks.
Systems thinking is attracting great interest in public health as a conceptual orientation to solving complex challenges around health care renewal in developed countries. Our approach is based on the tenet that effective systems thinking relies on the development of a trans-disciplinary knowledge base integrating traditional complex adaptive systems theory with community development, social ecology, social networks, and public health theory and practice (Best et al. 2003).
