Difference between revisions of "Policy and Real World Evidence"
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The field epidemiologist aims to provide, as reliable as possible, real-world evidence (RWE) to support policy decisions. | The field epidemiologist aims to provide, as reliable as possible, real-world evidence (RWE) to support policy decisions. | ||
− | The policy and decision-making processes in health are usually complex. During crises specifically, | + | The policy and decision-making processes in health are usually complex and rely on many factors besides RWE. Policies usually aim to reflect societal values and need to be aligned with related policies, in order to build a coherent and consistent frame of reference for public decision making. Evidence alone cannot guide a policy. For example, vaccine effectiveness (VE) is an epidemiological indicator that can be quantified and substantiated with real word data and expressed with confidence intervals. However, VE alone does not inform policymakers sufficiently WHOM to vaccinate (Bosman, 2019). That choice depends on many other factors than epidemiological evidence alone. |
+ | |||
+ | ==Facilitators and Barriers for using research evidence in policy== | ||
+ | In a systematic review on Health policy-makers' perceptions of their use of evidence, facilitators and barriers were identified (Invaer, 2002). | ||
+ | |||
+ | The most commonly mentioned '''facilitators''' of the use of research evidence in policy-making were: | ||
+ | * Personal contact between researchers and policy- makers (13/24). | ||
+ | * Timeliness and relevance of the research (13/24). | ||
+ | * Research that included a summary with clear recommendations (11/24). | ||
+ | * Good quality research (6/24). | ||
+ | * Research that con rmed current policy or endorsed self-interest (6/24). | ||
+ | * Community pressure or client demand for research (4/24). | ||
+ | * Research that included effectiveness data (3/24). | ||
+ | |||
+ | The most commonly mentioned barriers to the use of research evidence in policy-making were (not surprisingly related to the facilitators): | ||
+ | * Absence of personal contact between researchers and policy-makers (11/24). | ||
+ | * Lack of timeliness or relevance of research (9/24). | ||
+ | * Mutual mistrust, including perceived political naivety of scientists and scientic naivety of policy-makers (8/24). | ||
+ | * Power and budget struggles (7/24). | ||
+ | * Poor quality of research (6/24). | ||
+ | * Political instability or high turnover of policy-making staff (5/24). | ||
+ | |||
+ | |||
+ | ==Pressures on policy during crises== | ||
+ | During crises specifically, the complex policy process can be subject to various overt and covert pressures, leading governments to pursue policies that disregard real-world evidence or even rely on false evidence. Such a phenomenon can be observed in many different contexts, not just during crises like the COVID-19 pandemic. It can be due to a variety of reasons, including cognitive biases, political interests, and lack of quality information. | ||
Possible explanations if this phenomenon: | Possible explanations if this phenomenon: | ||
# '''[[Cognitive bias|Cognitive biases]]''': Decision-makers, like all humans, are influenced by various cognitive biases. They may overemphasize evidence that supports their existing beliefs and disregard evidence that contradicts them, a phenomenon known as confirmation bias (Nickerson, 1998). Similarly, they may be affected by availability bias, where they give undue weight to immediate and memorable examples over statistically significant evidence (Tversky & Kahneman, 1973). | # '''[[Cognitive bias|Cognitive biases]]''': Decision-makers, like all humans, are influenced by various cognitive biases. They may overemphasize evidence that supports their existing beliefs and disregard evidence that contradicts them, a phenomenon known as confirmation bias (Nickerson, 1998). Similarly, they may be affected by availability bias, where they give undue weight to immediate and memorable examples over statistically significant evidence (Tversky & Kahneman, 1973). | ||
− | |||
# '''[[Political Interests and Populism]]''': Governments sometimes prioritize political interests over evidence-based policy. They might disregard evidence if it contradicts their political agenda or the preferences of their supporters (Cairney, 2016). Populist movements can exacerbate this tendency by appealing to emotions and popular beliefs over expert evidence (Mudde, 2004). | # '''[[Political Interests and Populism]]''': Governments sometimes prioritize political interests over evidence-based policy. They might disregard evidence if it contradicts their political agenda or the preferences of their supporters (Cairney, 2016). Populist movements can exacerbate this tendency by appealing to emotions and popular beliefs over expert evidence (Mudde, 2004). | ||
− | |||
# '''[[Misinformation and False Evidence]]''': The spread of misinformation and fake news can also lead governments to rely on false evidence, especially if they lack the resources to properly vet information (Lewandowsky et al., 2012). This problem has been particularly pronounced during the COVID-19 pandemic, due to the rapid spread of misinformation on social media (Pennycook et al., 2020). | # '''[[Misinformation and False Evidence]]''': The spread of misinformation and fake news can also lead governments to rely on false evidence, especially if they lack the resources to properly vet information (Lewandowsky et al., 2012). This problem has been particularly pronounced during the COVID-19 pandemic, due to the rapid spread of misinformation on social media (Pennycook et al., 2020). | ||
− | |||
# '''[[Scientific Uncertainty]]''': Especially in a rapidly evolving situation like the COVID-19 pandemic, scientific evidence is often uncertain and can change over time. This can make it difficult for governments to determine what the "real" evidence is, and can lead to flip-flopping on policy as new evidence emerges (Sarewitz, 2004). | # '''[[Scientific Uncertainty]]''': Especially in a rapidly evolving situation like the COVID-19 pandemic, scientific evidence is often uncertain and can change over time. This can make it difficult for governments to determine what the "real" evidence is, and can lead to flip-flopping on policy as new evidence emerges (Sarewitz, 2004). | ||
− | |||
# '''Short-term focus''': Governments can sometimes be influenced by short-term interests, such as upcoming elections, rather than longer-term outcomes. This can lead them to implement policies that have immediate, visible benefits, rather than those that are most supported by evidence (Jacobs, 2011). | # '''Short-term focus''': Governments can sometimes be influenced by short-term interests, such as upcoming elections, rather than longer-term outcomes. This can lead them to implement policies that have immediate, visible benefits, rather than those that are most supported by evidence (Jacobs, 2011). | ||
− | |||
# '''Influence of [[Lobbying]]''': Policy decisions can also be heavily influenced by lobbying from various interest groups. If these groups are promoting policies that are not based on solid evidence, this can lead to a disconnect between policy and evidence (Grossmann, 2012). | # '''Influence of [[Lobbying]]''': Policy decisions can also be heavily influenced by lobbying from various interest groups. If these groups are promoting policies that are not based on solid evidence, this can lead to a disconnect between policy and evidence (Grossmann, 2012). | ||
− | |||
# '''Lack of expertise and resources''': Governments may not always have sufficient access to expertise or resources to fully evaluate the evidence. This is particularly likely in less developed countries, but can also be a problem in developed countries where government capacity has been eroded (Peters et al., 2019). | # '''Lack of expertise and resources''': Governments may not always have sufficient access to expertise or resources to fully evaluate the evidence. This is particularly likely in less developed countries, but can also be a problem in developed countries where government capacity has been eroded (Peters et al., 2019). | ||
=References= | =References= | ||
− | + | * This article was written by ChatGPT4.0 on June 2, 2023 and revised by Arnold Bosman | |
+ | * Innvaer, Simon, et al. "Health policy-makers' perceptions of their use of evidence: a systematic review." Journal of health services research & policy 7.4 (2002): 239-244. | ||
* Cairney, P. (2016). The Politics of Evidence-Based Policy Making. Palgrave Macmillan. | * Cairney, P. (2016). The Politics of Evidence-Based Policy Making. Palgrave Macmillan. | ||
* Grossmann, M. (2012). Interest group influence on US policy change: An assessment based on policy history. Interest Groups & Advocacy, 1(2), 171-192. | * Grossmann, M. (2012). Interest group influence on US policy change: An assessment based on policy history. Interest Groups & Advocacy, 1(2), 171-192. | ||
+ | * Bosman, A (2019). Video masterclass on attitudes and values in the context of core competencies in public health. https://vimeo.com/404643912 | ||
* Jacobs, L. R. (2011). Governing for the long term: Democracy and the politics of investment. Cambridge University Press. | * Jacobs, L. R. (2011). Governing for the long term: Democracy and the politics of investment. Cambridge University Press. | ||
* Lewandowsky, S., Ecker, U. K. H., & Cook, J. (2017). Beyond Misinformation: Understanding and Coping with the “Post-Truth” Era. Journal of Applied Research in Memory and Cognition, 6(4), 353–369. | * Lewandowsky, S., Ecker, U. K. H., & Cook, J. (2017). Beyond Misinformation: Understanding and Coping with the “Post-Truth” Era. Journal of Applied Research in Memory and Cognition, 6(4), 353–369. |
Latest revision as of 11:32, 3 June 2023
The field epidemiologist aims to provide, as reliable as possible, real-world evidence (RWE) to support policy decisions.
The policy and decision-making processes in health are usually complex and rely on many factors besides RWE. Policies usually aim to reflect societal values and need to be aligned with related policies, in order to build a coherent and consistent frame of reference for public decision making. Evidence alone cannot guide a policy. For example, vaccine effectiveness (VE) is an epidemiological indicator that can be quantified and substantiated with real word data and expressed with confidence intervals. However, VE alone does not inform policymakers sufficiently WHOM to vaccinate (Bosman, 2019). That choice depends on many other factors than epidemiological evidence alone.
Facilitators and Barriers for using research evidence in policy
In a systematic review on Health policy-makers' perceptions of their use of evidence, facilitators and barriers were identified (Invaer, 2002).
The most commonly mentioned facilitators of the use of research evidence in policy-making were:
- Personal contact between researchers and policy- makers (13/24).
- Timeliness and relevance of the research (13/24).
- Research that included a summary with clear recommendations (11/24).
- Good quality research (6/24).
- Research that con rmed current policy or endorsed self-interest (6/24).
- Community pressure or client demand for research (4/24).
- Research that included effectiveness data (3/24).
The most commonly mentioned barriers to the use of research evidence in policy-making were (not surprisingly related to the facilitators):
- Absence of personal contact between researchers and policy-makers (11/24).
- Lack of timeliness or relevance of research (9/24).
- Mutual mistrust, including perceived political naivety of scientists and scientic naivety of policy-makers (8/24).
- Power and budget struggles (7/24).
- Poor quality of research (6/24).
- Political instability or high turnover of policy-making staff (5/24).
Pressures on policy during crises
During crises specifically, the complex policy process can be subject to various overt and covert pressures, leading governments to pursue policies that disregard real-world evidence or even rely on false evidence. Such a phenomenon can be observed in many different contexts, not just during crises like the COVID-19 pandemic. It can be due to a variety of reasons, including cognitive biases, political interests, and lack of quality information.
Possible explanations if this phenomenon:
- Cognitive biases: Decision-makers, like all humans, are influenced by various cognitive biases. They may overemphasize evidence that supports their existing beliefs and disregard evidence that contradicts them, a phenomenon known as confirmation bias (Nickerson, 1998). Similarly, they may be affected by availability bias, where they give undue weight to immediate and memorable examples over statistically significant evidence (Tversky & Kahneman, 1973).
- Political Interests and Populism: Governments sometimes prioritize political interests over evidence-based policy. They might disregard evidence if it contradicts their political agenda or the preferences of their supporters (Cairney, 2016). Populist movements can exacerbate this tendency by appealing to emotions and popular beliefs over expert evidence (Mudde, 2004).
- Misinformation and False Evidence: The spread of misinformation and fake news can also lead governments to rely on false evidence, especially if they lack the resources to properly vet information (Lewandowsky et al., 2012). This problem has been particularly pronounced during the COVID-19 pandemic, due to the rapid spread of misinformation on social media (Pennycook et al., 2020).
- Scientific Uncertainty: Especially in a rapidly evolving situation like the COVID-19 pandemic, scientific evidence is often uncertain and can change over time. This can make it difficult for governments to determine what the "real" evidence is, and can lead to flip-flopping on policy as new evidence emerges (Sarewitz, 2004).
- Short-term focus: Governments can sometimes be influenced by short-term interests, such as upcoming elections, rather than longer-term outcomes. This can lead them to implement policies that have immediate, visible benefits, rather than those that are most supported by evidence (Jacobs, 2011).
- Influence of Lobbying: Policy decisions can also be heavily influenced by lobbying from various interest groups. If these groups are promoting policies that are not based on solid evidence, this can lead to a disconnect between policy and evidence (Grossmann, 2012).
- Lack of expertise and resources: Governments may not always have sufficient access to expertise or resources to fully evaluate the evidence. This is particularly likely in less developed countries, but can also be a problem in developed countries where government capacity has been eroded (Peters et al., 2019).
References
- This article was written by ChatGPT4.0 on June 2, 2023 and revised by Arnold Bosman
- Innvaer, Simon, et al. "Health policy-makers' perceptions of their use of evidence: a systematic review." Journal of health services research & policy 7.4 (2002): 239-244.
- Cairney, P. (2016). The Politics of Evidence-Based Policy Making. Palgrave Macmillan.
- Grossmann, M. (2012). Interest group influence on US policy change: An assessment based on policy history. Interest Groups & Advocacy, 1(2), 171-192.
- Bosman, A (2019). Video masterclass on attitudes and values in the context of core competencies in public health. https://vimeo.com/404643912
- Jacobs, L. R. (2011). Governing for the long term: Democracy and the politics of investment. Cambridge University Press.
- Lewandowsky, S., Ecker, U. K. H., & Cook, J. (2017). Beyond Misinformation: Understanding and Coping with the “Post-Truth” Era. Journal of Applied Research in Memory and Cognition, 6(4), 353–369.
- Mudde, C. (2004). The populist zeitgeist. Government and opposition, 39(4), 541-563.
- Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220.
- Pennycook, G., McPhetres, J., Zhang, Y., Lu, J. G., & Rand, D. G. (2020). Fighting COVID-19 misinformation on social media: Experimental evidence for a scalable accuracy nudge intervention. Psychological Science, 31(7), 770-780.
- Peters, B. G., Jordan, A., & Tosun, J. (2019). Over-reaction and under-reaction in climate policy: an institutional analysis. Journal of Environmental Policy & Planning, 21(5), 585-598.
- Sarewitz, D. (2004). How science makes environmental controversies worse. Environmental Science & Policy, 7(5), 385-403.
- Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207–232.