The relationships among research, decision-making, and policy development are often complex due to the multifaceted processes that involve varying institutions, people, and information. For both scientific and health research fields these issues are common. Specifically, knowledge and evidence utilization are not static concepts; rather they occur within dynamic settings encompassing a spectrum of types of information use where adaptive incorporation of new evidence is often required (Baghbanian, Hughes, Kebriaaei, & Khavarpour, 2012; Giebels, van Buuren, & Edelenbos, 2015; Nutley, Walter, & Davies, 2007). Furthermore, effective utilization of evidence and knowledge is not intrinsic to the processes. A variety of factors influence the degree and manner by which evidence and knowledge are utilized (Liverani et al., 2013; McCaughey & Burning, 2010; Nursey-Bray et al., 2014). Within the current Canadian context these factors may be having an effect on knowledge utilization within the Government of Canada, potentially causing concern.
The Use of Research
Using research to make policy decisions is not a linear process. Research results may change information about a topic and may require decision makers to request additional research. In health and science fields, policy decisions may need to be made within short timelines with incomplete information or degrees of uncertainty about subjects.
Nutley, Walter and Davies (2007) describe how information can be utilized in different ways by different actors depending on the type of knowledge, the decision being made, and the role of the recipient. The authors introduce a spectrum of research use that varies between conceptual and instrumental. Instrumental uses of research are rarer and entail direct application in practice and policy (Nutley et al., 2007). Conceptual uses of research add to a decision maker’s pool of knowledge or understanding on a subject (Nutley et al., 2007). Conceptual uses of research are more common than instrumental uses; however, it is often difficult for policy makers to identify particular pieces of research that influenced their policy decisions.
How Informed Decision-Making is Hindered
The incorporation of evidence and knowledge into the policy process can be affected by many factors. Factors that hinder the utilization of evidence and knowledge can occur both internally and externally in decision-making processes.
McCaughey & Bruning (2010) discuss how current healthcare systems strive to apply Evidence-Based Decision-Making (EBDM), but failure often occurs due to the effect of an individual’s cognitive information processing. The cognitive information processing of an individual is defined as the “internally generated mechanisms by which relevant decision-making information is processed” (McCaughey & Burning, 2010, p. 2-3). From this perspective, the authors postulate a decision-making framework that uses a series of cognitive factors to outline how subjectivity and internal biases affect decision-making processes (McCaughey & Burning, 2010). Principally, these factors act as a barrier to EBDM because they can distort information and provide a false sense of informed decision-making (McCaughey & Burning, 2010). In particular, three cognitive processes are identified as a major source of influence: utility maximization assessment, mood and personal characteristics, and stereotyping (McCaughey & Burning, 2010). The ubiquity of these factors ultimately requires decision makers to plan for their mitigation.
Nursey-Bray et al. (2014) discuss the policy process further by assessing the utilization of knowledge in coastal policy formulation. Through historical analysis and discussion the authors examine how to facilitate suitable coastal management policy better by exploring the transmission of science into policy activities. Principally, the authors discuss a gap between how science is developed and how it is incorporated into policy (Nursey-Bray et al., 2014). The authors describe this gap as “a knowledge governance gap, caused by structural, functional, cultural and political disjunctures between knowledge and governance, which constrain enablers from implementing knowledge” (Nursey-Bray et al., 2014, p. 109). For coastal policy, the principal cause of this gap is the separation of knowledge into two distinct components, namely, local knowledge and scientific knowledge. While scientific knowledge is important to inform decision-making, local knowledge can provide insight for successful implementation (Nursey-Bray et al., 2014). Thus, the integration of local and scientific knowledge is crucial for the successful implementation of policy (Nursey-Bray et al., 2014). The arbitrary separation of knowledge paradigms acts as a hindrance to the policy process; effective policy often requires a diversity of knowledge types.
Using a systematic approach, Liverani et al. (2013) conducted a literature review that pertained to the application of evidence for decision-making within health policy contexts. In general, the authors had difficulty finding literature that dealt with these issues directly. The authors propose that a greater concentration of power, political centralisation, institutional mechanisms, government staff turnover, and external organizational influence negatively correlate with evidence usage (Liverani et al., 2013). In contrast, increased pressure from wider policy agendas, alignment with wider political agendas, and increased democratization positively correlate with increased evidence use (Liverani et al., 2013). Ultimately, the complex interplay of these factors can result in a net effect that is either detrimental or beneficial to policy and decision-making processes. As a result, practitioners need to be aware of the context to effectively utilize evidence and knowledge in policy making.
In order to address the influences that hinder evidence and knowledge utilization, acknowledgement that external and internal factors can hinder use is needed (McCaughey & Burning, 2010; Nursey-Bray et al., 2014). Furthermore, participants in research and policy processes must initiate greater communication and collaboration. Specifically, knowledge sharing and knowledge brokering initiatives can mitigate hindering factors (Liverani et al., 2013; McCaughey & Burning, 2010; Nursey-Bray et al., 2014).
Adaptive Decision-making
An adaptive decision-making process allows policy and decision makers to hedge risk and add new information for particular decisions. This flexible process ensures that the policy adopted has the ability to adapt and remain useful.
Baghbanian et al. (2012) and Giebels et al. (2015) discuss the benefits of an adaptive decision-making technique employed in healthcare and environmental policy making settings. This practice encourages decision makers to allow for the incorporation of new or additional knowledge during the policy decision period. If a policy is rigid, i.e., it will not allow for the introduction of new or additional information, the policy may be inadequate because information about new discoveries is continually being produced (Baghbanian et al., 2012). Also, a rigid policy means that if the situation changes, the policy may no longer be appropriate; therefore, decision makers will be forced to design an entirely new policy.
The volume of knowledge used to determine a policy is discussed by Baghbanian et al. (2012). In a case of the health of an ecosystem, biologists were adamant that additional research was required, while decision makers felt that an appropriate body of information already existed with which to make a decision (Baghbanian et al., 2012). The authors also illustrated the difficulties in reaching a policy decision when information overload occurs. Incorporating all of the different forms of knowledge adds to the breadth of information but may make it difficult to reach a policy conclusion due a presence of competing interests (Baghbanian et al., 2012).
Limitations of the Studies
When evaluating the conclusions of the studies considered in this blog post, the research approaches used in the studies should be considered. The results presented by Giebels et al. (2015), McCaughey & Burning (2010), Liverani et al. (2013), and Nursey-Bray et al. (2014) address questions in the fields of coastal management policy and health policy, and may not be applicable in other policy fields. Furthermore, Giebels et al. (2015), and Liverani et al. (2013) conducted a series of case studies in a variety of political, economic, and social contexts. Case studies are often informative but the authors’ findings may not fully represent the contexts of their study environments.
Discussion
In recent years, the Canadian federal government has reduced the number of environmental scientists employed in government departments or agencies. The Polar Environment Atmospheric Research Laboratory and the Environmental Lakes Area Research Station are two notable programs cut by the government (Davison, 2012). The use of evidence in decision-making could be affected by this reduction in environmental scientists as less research is being conducted. Giebels et al. (2015) showed that policy decisions could be made without all of the available or desired information present. While this scenario may not seem like an ideal practice, is it still possible to make effective environmental policy decisions given the reduction in federal scientists?
If one draws on the results of the work of Liverani et al. (2013), one might conclude that political and institutional factors may be contributing to diminished utilization of evidence and knowledge within the Canadian federal government. Specifically, the increased concentration of power in the Prime Minister’s Office recently and the ubiquity of knowledge silos within federal departments may currently be a factor in the use of research evidence. Decreased knowledge utilization could subsequently result in future policies being less evidence-based than desirable, due to an institutional preference for re-implementing actions previously established internally or in other jurisdictions (Liverani et al., 2013).
References
Baghbanian, A., Hughes, I., Kebriaei, A., & Khavarpour, F. A. (2012). Adaptive decision-making: How Australian healthcare managers decide. Australian Health Review, 36, 49-56.
Davison, J. (2012). Scientists rally on Parliament Hill to mourn “death of evidence.” CBC. Retrieved from http://www.cbc.ca/news/technology/scientists-rally-on-parliament-hill-to-mourn-death-of-evidence-1.1237215
Giebels, D., van Buuren, A., & Edelenbos J. (2015). Using knowledge in a complex decision-making process – Evidence and principles from the Danish Houting project’s ecosystem based management approach. Environmental Science & Policy, 47, 53-67.
Liverani, M., Hawkins, B., & Parkhurst, J. O. (2013). Political and institutional influences on the use of evidence in public health policy. A systematic review. PLOS One, 8(10). e77404.
McCaughey, D., & Bruning, N. S. (2010). Rationality versus reality: The challenges of evidence-based decision making for health policy makers. Implementation Science, 5(1), 1- 13.
Nursey-Bray, M. J., Vince, J., Scott, M., Haward, M., O’Toole, K., Smith, T., Harvey, N., & Clarke, B. (2014). Science into policy? Discourse, coastal management, and knowledge. Environmental Science & Policy, 38, 107-119.
Nutley, S., Walter, I., & Davies, H. T. O. (2007). Chapter 2. What does it mean to “use” research evidence. In Using evidence. How can inform public service (pp. 33-59). Bristol: The Policy Press.
Authors: Amir Ahmadi Rashti and Adrian Koops
This blog post is part of a series of posts authored by students in the graduate course “The Role of Information in Public Policy and Decision Making,” offered at Dalhousie University.
