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| ID | Type | Description | Link |
|---|---|---|---|
| R01DA056627 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Institute on Drug Abuse (NIDA) | NIH |
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If science is to inform effective substance misuse prevention policy and ultimately improve public health, the field needs an effective strategy for directly supporting policymakers' use of research evidence, yet our field lacks an evidence-based model designed for this purpose. Accordingly, a state-level randomized controlled trial (N = 30 states) of a formal, theory-based approach for appropriately supporting policymakers' use of scientific evidence--known as the Research-to-Policy Collaboration (RPC) Model is proposed. This work has the potential to reduce population-level substance misuse by improving the use of scientific information in policymaking, thus increasing the availability of evidence-based prevention programs and policies.
If science is to inform policy and ultimately improve public health, the field needs an effective strategy for directly supporting policymakers' use of research evidence. However, the field lacks an evidence-based model designed for supporting state policymakers' use of prevention research in crafting legislation. Instead, the field continues to largely rely on ad hoc strategies for translating prevention research (e.g., opportunistic outreach and responding to policymakers' requests if or when they are made). Accordingly, an experimental study of a formal, theory-based approach for supporting policymakers' use of scientific evidence that does not involve lobbying-the Research-to-Policy Collaboration (RPC) Model is proposed. The RPC fosters productive engagement between the policy and research communities by implementing systematic capacity building and outreach strategies. Previous experimental work on the RPC demonstrated the ability of this model to increase engagement between researchers and policymakers, increase policymakers' value for research evidence, and improve their use of scientific evidence in their policymaking.1 The study proposes a state-level randomized controlled trial of the RPC (N = 30 state legislatures) that will evaluate the model's ability to improve engagement between state policymakers' and the prevention science community, build policymakers' awareness and value of substance misuse prevention research, and subsequently their use of research evidence throughout the policymaking process. To accomplish this, the study will test three specific research aims. Aim 1 will assess historical and current use of research evidence in state legislation pertaining to substance misuse prevention. This will involve qualitative coding of bills introduced by state legislatures over the last five years. Aim 2 will compare the frequency and quality of engagement with prevention researchers between the intervention and control conditions. Additionally, the study will assess how the RPC model influences policymakers' value and awareness of substance misuse prevention over time using a validated survey across three time points. Aim 3 will evaluate the effectiveness of the RPC on legislators' actual use of research in legislation by observing and quantifying changes in legislator behavior related to research use. Improving the use of scientific information in policymaking can reduce population-level substance misuse by increasing the availability of evidence-based prevention programs and policies.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Intervention Group | Experimental | Legislative offices who receive the full Research-to-Policy Model intervention. |
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| Control Group | Active Comparator | Legislative Offices who do not receive the full RPC Model intervention. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Intervention: RPC Group | Behavioral | The RPC model entails seven interrelated steps including a capacity building and collaboration phase. Throughout the implementation, researchers are provided direct access to intermediary support from our trained RPC fellows who facilitate RPC activity at each step coordinated by an implementation supervisor. Importantly, this model does not involve any lobbying. Consistent with NIH guidelines for grantees, the RPC instead aims to "highlight and translate public health evidence…; conduct coalition building…; provide leadership and training, and foster safe and healthful environments". Specifically, implementation of the RPC model explicitly does not attempt to influence legislative actions, but instead facilitates honest brokerage in which researchers discuss evidence without indicating opinion or stance on how legislators should change specific policies, programs, or regulations. |
| Measure | Description | Time Frame |
|---|---|---|
| RPC impact on introduction of evidence-informed bills | Assessment of use of research evidence in bills introduced during the intervention period. It is anticipated that legislators will introduce over 5,000 bills relating to substance use are. These bills will be coded for presence of evidence markers using a validated, deductive codebook to identify how legislators use research evidence in legislative language. A subset of these bills (N = 150) will be reviewed by trained coders to identify the form (i.e. direct or indirect) and the goal of evidence use (i.e., sharing the cause of the problem, status of the problem, solving the problem, generating new knowledge, or accountability). Observed use of research evidence in bills will be quantified and analyzed in a series of multi-level models to test change across three time points. | Baseline, post intervention, and 6-months post intervention |
| Measure | Description | Time Frame |
|---|---|---|
| RPC impact on legislators' perceived use of prevention research | Legislators' perceived use of research evidence will be assessed with the Reported Use of Research Evidence Scale (minimum value = 1, maximum value =5, higher scores indicate increased use of research evidence), which assesses use of research across various stages of the policy process (e.g., agenda setting, policy evaluation) and the three types of research use (i.e., instrumental, conceptual, and symbolic). Research will be defined for participants as information gleaned from scientific studies, academic investigations, or program evaluations assessing the effectiveness of an intervention. Surveys from state legislators will be analyzed longitudinally by modeling change across the two time points-including multi-level repeated measures and growth curve models (MLM). |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Daniel M Crowley, Ph.D | Contact | 866-905-1872 | dmc397@psu.edu | |
| Jennifer T Scott, Ph.D | Contact | 864-431-2411 | jxs1622@psu.edu |
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| Facility | Status | City | State | ZIP | Country | Contacts |
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| Penn State University | Recruiting | University Park | Pennsylvania | 16802 | United States |
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Sampled states' legislatures will be randomly assigned to either a comprehensive intervention or a control group that receives minimal intervention.
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| Active Comparator: Control Group | Behavioral | Control group participants will receive "light touch" research support, similar to previous work (e.g., an RPC associate will send publicly available research materials in response to research requests). This light touch control condition will increase responsiveness of state officials to survey follow up requests. |
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| Baseline, post intervention, and 6 months post-intervention |
| RPC impact on legislators' engagement with prevention researchers | The investigators will use validated quantitative survey instrument to investigate how the RPC model influences the frequency of policymakers' different types of interactions with researchers (5-pt. Likert scale; ɑ = .89). A series of multi-level models will be employed to account for the nested structure of the study design. In addition to main effects models at each time point, this includes a three-level design that nests legislators within their state legislature across 3 time points (baseline, post intervention, and 6 months following the intervention. Survey data will be modeled in terms of absolute difference and change from baseline to post-test to assess trial main effects. Survey data from state legislators will also be analyzed longitudinally across the three time points-including multi-level repeated measures and growth curve models (MLM) using MPlus. | Baseline, post collaboration, and 6 months post-intervention |
| RPC impact on state legislators' value of substance misuse prevention science | The investigators will use a validated quantitative survey instrument to assess how the RPC model influences legislators' perceived value of research use in their work and in policymaking more generally. It will be measured with an adapted version of the Seeking, Engaging with, and Evaluating Research (SEER) protocol. Policymakers will be asked to rate how strongly they agree with four statements assessing whether they feel they know general information pertaining to prevention programming. A series of multi-level models will be employed to account for the nested structure of the study design. In addition to main effects models at each time point, this includes a three-level design that nests legislators within their state legislature across 3 time points (baseline, post intervention, and 6 months following intervention). Survey data will be modeled in terms of absolute difference and change from baseline to post-test to assess trial main effects. | Baseline, post intervention, and 6 months post intervention |
| RPC effectiveness on legislators' awareness of substance misuse prevention science | The investigators will use a validated quantitative survey instrument to investigate how the RPC model influences legislators' awareness of substance misuse prevention science. Policymakers will be asked to rate how strongly they agree with four statements assessing whether they feel they know general information pertaining to prevention programming. A series of multi-level models will be used to account for the nested structure of the study design. In addition to main effects models at each time point, this includes a three-level design that nests legislators within their state legislature across 3 time points (baseline, post intervention, and 6 months following intervention). Survey data will be modeled in terms of absolute difference and change from baseline to post-test to assess trial main effects. | Baseline, post intervention, and 6 months post-intervention |
| ID | Term |
|---|---|
| D019966 | Substance-Related Disorders |
| ID | Term |
|---|---|
| D064419 | Chemically-Induced Disorders |
| D001523 | Mental Disorders |
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