Abstract
Objective
Disseminating behavioral health (BH) research to legislators (i.e., elected policy makers) is widely acknowledged as a priority, but little is known about how research evidence is used and sought by this audience. The primary aim of this exploratory study was to identify the research dissemination preferences and research seeking practices of legislators who prioritize BH issues and describe the role research plays in determining their policy priorities. The secondary aim was to assess if these legislators differ from legislators who do not prioritize BH issues.
Methods
A telephone-based survey was conducted with 862 US state legislators (response rate 50%). A validated survey instrument was used to assess legislators’ priorities and the factors that determine them, research dissemination preferences, and research seeking practices. Bivariate analyses were conducted to characterize the study population and compare legislators who prioritized BH issues to legislators who did not.
Results
Legislators who prioritized BH issues were significantly more likely to identify research evidence as a factor that determined policy priorities than legislators who did not prioritize these issues (odds ratio=1.91, 95% CI=1.25–2.90, p=.002). Legislators who prioritized BH issues also attributed more importance to 10-of-12 features of disseminated research (e.g., research being unbiased [p=.014], research telling a story [p=.033]) and engaged in 8-of-11 research seeking and utilization practices (e.g., attending research presentations [p=.012]) more often.
Conclusions
Legislators who prioritize BH issues actively seek, have distinct preferences for, and are particularly influenced by research evidence. Testing legislator-focused BH research dissemination strategies is an area for future research.
The purpose of mental health and substance misuse (hereafter referred to as behavioral health, BH) research is to improve population well-being. Public policy can help achieve this aim by allocating resources for evidence-based interventions and enacting regulations that support the prevention, management, and treatment of BH disorders (1–3). For BH research to inform policy decisions, however, policy makers must be knowledgeable about it. Thus, disseminating BH research to policy makers has been resoundingly acknowledged as a priority in the United States (US) (4–6, 9–12).
Dissemination is defined as the use of tailored strategies and preferred communication channels to spread research evidence among target audiences (7–8). The importance of policy-focused dissemination is apparent in the Substance Abuse and Mental Health Services Administration’s action plan (9), the National Institute of Mental Health’s (NIMH) objective to “Strengthen the Public Health Impact of NIMH-Supported Research” (10), the National Institute on Drug Abuse’s mission to “Ensure the rapid and effective dissemination of research results to… inform policy” (11), and the National Institute on Alcohol Abuse and Alcoholism’s mission of “Translating and disseminating research findings to… policymakers” (12).
Dissemination does not occur spontaneously, however, and the ‘passive’ dissemination strategies typically used by researchers (e.g., peer-reviewed publications) are generally ineffective at reaching policy makers (13–16). Dissemination is most effective when tailored to specific audiences (17), and the field of policy dissemination research has emerged to address this need by generating knowledge about policy makers’ preferences for receiving research evidence (e.g., who delivers it, how it is presented) and the practices through which it is used (e.g., when and where they seek it) (18–20). Few policy dissemination studies have explored BH issues (42), however, and little empirical evidence exists to inform the design of policy-focused BH dissemination strategies.
A recent systematic review of interventions to increase the use of research in MH policy making highlights the knowledge gap (21). The review identified only nine studies and, as the authors noted, virtually none involved public policy makers (a policy maker was broadly defined as any decision maker—including program directors and community leaders). These results were consistent with previous reviews which identified few studies focused on how research evidence is used in BH policy making (22–23). Studies have explored uses of research in BH policy making in Canada (24–25), Australia (26–27), and Belgium (28), but offer limited guidance regarding how to disseminate BH research to US policy makers. Corrigan and Watson extrapolated findings from social psychological research to propose factors (e.g., political ideology) that might influence policy makers’ decisions about mental health services (29). The article, however, primarily drew from studies conducted with student populations, not actual policy makers. A qualitative study of federal policy makers found that research evidence was important in passing BH parity legislation, but did not explore issues related to research dissemination (30).
BH research dissemination has been inadequately investigated among US state policy makers. This knowledge gap warrants particular attention because most government authority to address BH issues exists at the state-level. State policy makers, for example, determine the types of BH services that are reimbursable through Medicaid—the largest payer of BH services in the US (31–32). Federal legislation has attempted to promote BH insurance parity (33), but state legislation is needed to supplement federal laws and ensure equal coverage (34–35).
Our study begins to address a critical gap in the field of BH services research by analyzing survey data collected from US state legislators (i.e., policy makers elected to the state House or Senate). The primary aim of this exploratory study was to identify the research dissemination preferences and research seeking practices of legislators who prioritized BH issues and describe the role research played in determining their policy priorities. The secondary aim was to assess if legislators who prioritized BH issues differed from legislators who did not prioritize the issues.
Theoretical framework
Our decision to focus on legislators who prioritized BH issues was motivated by Kingdon’s multiple streams theory of the policy making process (36–37). The theory is founded on the premise that countless issues are constantly competing for policy makers’ attention and that three “streams” determine if and how issues are addressed: 1) a problem stream, consisting of issues that need to be addressed; 2) a policy stream, consisting of solutions to these issues; and 3) a political stream, consisting of public opinion and the broader sociopolitical environment. When these three streams converge around an issue, a “policy window” opens and “policy entrepreneurs” (i.e., people who advocate for a specific issue) can advance their proposals to address it.
Accordingly, our study focused on legislators who perceived BH issues as priorities because these legislators are most likely to act as policy entrepreneurs and advance policies to address BH issues when a policy window opens (38). By producing an understanding how this important sub-group of legislators uses research evidence, the study can inform how BH research might be most effectively communicated to them via targeted dissemination strategies. By assessing whether this sub-group of legislators differs from legislators who do not prioritize BH issues, the study can signal whether tailored dissemination strategies are needed or if uniform strategies are sufficient.
Methods
Design, Participants, and Recruitment
We conducted a cross-sectional survey of US state legislators. We partnered with the National Conference of State Legislatures to obtain a complete list of US state legislators (7,525) and generated a random sample of 2,000 legislators who were recruited to participate in a telephone-based survey between January-October 2012. Up to ten attempts were made to contact each legislator, 1,719 were successfully contacted, and 862 completed the survey (response rate 50%). This is considered a good response rate for a legislator population (39). The survey was administered by an independent research firm. Institutional Review Board approval was obtained.
Measures
We measured legislators’ use of research evidence with an instrument that has been validated with state legislators (16, 40–41). Details about the sources of instrument items and reliability coefficients are described elsewhere (16).
Legislators’ prioritization of BH issues
Whether or not legislators perceived BH issues as policy priorities (yes/no) served as the dependent variable. Two items were used to determine this. First, legislators were prompted with the open-ended question: “describe one or two policy priorities that are most important to you” (Q1). Legislators were then asked to select “the top three most important health issues for policy action in your state” (Q2) and presented with a list of 19 issues: “mental health,” “prescription drug abuse,” “access to healthcare,” “aging,” “cancer,” “diabetes,” “diet/nutrition,” “heart disease,” “HIV/AIDS,” “infectious diseases,” “injury prevention,” “Medicare/Medicaid,” “obesity,” “physical activity,” “quality of healthcare,” “the environment,” “tobacco use/cessation,” “universal coverage,” “violence prevention” in addition to an open-ended “other” option. At least one “other” health issue was named by 77% of respondents.
Open-ended responses from Q1 and Q2 were searched for the terms “mental,” “behavioral,” and “psych” to screen for mental health issue prioritization and “substance,” “drug,” and “alcohol” to screen for substance misuse issue prioritization. Each response was coded as “mental health,” “substance misuse,” “both,” or “neither.” A legislator was categorized as perceiving BH issues as priorities if they identified a mental health issue, a substance misuse issue, or both in open-ended responses to Q1 or Q2 or selected “mental health” or “prescription drug abuse” in response to Q2.
Factors that determine legislators’ health policy priorities
As follow-up to Q2, legislators were asked to select “which two factors most help you determine which health issues you work on” and presented with a list of seven options.
Legislators’ research dissemination preferences
Legislators were presented with 12 statements about features of disseminated research and instructed to “rate the level of priority that you attribute to each” on a scale of 1–5 (1=low-priority, 5=high priority). To assess how perceptions of disseminated research varied according to the source, legislators were also presented with a list of eight sources of disseminated research (e.g., universities, the media) and instructed to “rate the reliability” on a scale of 1–5 (1=very unreliable, 5=very reliable).
Legislators’ research seeking and utilization practices
Legislators were presented with 11 statements about research seeking and utilization practices. Seven statements focused on where legislators go when seeking research evidence and four focused on what they do with it. For each statement, legislators were promoted with the statement “when making policy, how often do you…” and rated each on a scale on a scale of 1–5 (1=never, 5=always).
Legislators’ individual characteristics
We collected information on legislators’ gender, educational attainment, parental status, self-rated health status, number of years served in the state legislature, chamber, and political party membership. We also asked legislators whether they identified as liberal, moderate, or conservative on social issues and fiscal issues.
Analysis
Univariate descriptive statistics were produced to characterize the study population, stratified by whether or not the legislator prioritized BH issues. For dichotomous independent variables, Pearson χ2 and Fisher exact tests were used to identify associations with BH issue prioritization. Unadjusted odds ratios (ORs) with 95% confidence intervals (CIs) were produced to quantify the magnitude of these associations. For continuous and ordinal independent variables, we conducted two-tailed independent sample t-tests and Mann-Whitney U tests to compare means between legislators who did and did not prioritize BH issues. Responses of “don’t know” and “refuse to answer” were coded as missing and excluded from analyses. Missing data did not exceed 3% for any variable.
RESULTS
Of the 862 legislators who completed the survey, 125 (14.5%) identified BH issues as priorities (Table 1). Of these, 60 (48%) identified mental health issues, 57 (46%) identified substance misuse issues, and eight (6%) identified both. There were no significant differences between legislators who identified mental health issues and legislators who identified substance misuse issues. Legislators who prioritized BH issues were not significantly different than those who did not prioritize BH issues for any individual characteristic.
Table 1.
Characteristics of state legislators, United States, 2012
| All legislators (N=862) | BH policy priority (n=125) | BH not policy priority (n=737) | ||||||
|---|---|---|---|---|---|---|---|---|
| Characteristic | N | % | N | % | N | % | χ2a | p |
| Gender | ||||||||
| Male | 629 | 73 | 98 | 78 | 531 | 74 | .92 | .337 |
| Female | 210 | 24 | 27 | 22 | 183 | 26 | .92 | .337 |
| Highest level of educational attainment | ||||||||
| High school graduate or less | 36 | 4 | 5 | 4 | 31 | 4 | .03 | .855 |
| Trade/vocational schoolb | 16 | 2 | 0 | - | 16 | 2 | - | .149 |
| Some college or college graduate | 405 | 47 | 54 | 43 | 351 | 49 | 1.61 | .203 |
| Postgraduate degree | 379 | 44 | 66 | 53 | 313 | 44 | 3.31 | .069 |
| Have children | ||||||||
| Yes | 755 | 88 | 114 | 92 | 641 | 90 | .559 | .455 |
| No | 106 | 12 | 11 | 9 | 95 | 13 | ||
| Self-rated health status | ||||||||
| Excellent/ very good | 529 | 61 | 84 | 67 | 445 | 63 | .97 | .324 |
| Good | 249 | 29 | 32 | 26 | 217 | 31 | 1.2 | .267 |
| Fair/poor | 58 | 7 | 9 | 7 | 49 | 7 | .02 | .900 |
| Number of years served in state legislature | ||||||||
| (mean ± SD)b | 9.3± 7.2 | - | 9.0± 7.9 | - | - | .516 | ||
| Chamber | ||||||||
| House | 648 | 75 | 94 | 75.2 | 554 | 77.6 | .35 | .556 |
| Senate | 191 | 22 | 31 | 24.8 | 160 | 22.4 | .35 | .556 |
| Political party affiliation | ||||||||
| Democrat | 379 | 44 | 58 | 46.4 | 321 | 45.1 | .07 | .795 |
| Republican | 443 | 51 | 66 | 52.8 | 377 | 53.0 | .01 | .963 |
| Otherb | 14 | 2 | 1 | 0.8 | 13 | 1.8 | - | .706 |
| Social issues | ||||||||
| Liberal | 235 | 27 | 36 | 30 | 199 | 29 | .06 | .815 |
| Moderate | 165 | 19 | 26 | 21 | 139 | 20 | .13 | .717 |
| Conservative | 418 | 48 | 59 | 48 | 359 | 51 | .37 | .541 |
| Fiscal issues | ||||||||
| Liberal | 86 | 10 | 10 | 8 | 76 | 11 | .81 | .369 |
| Moderate | 174 | 20 | 23 | 18 | 151 | 21 | .82 | .366 |
| Conservative | 568 | 66 | 92 | 74 | 476 | 67 | 2.34 | .126 |
df=1
Fisher’s exact tests used to compare differences in the proportion of policymakers with the characteristic who did and did not identify BH issues as policy priorities.
Factors that determine health policy priorities
Legislators who prioritized BH issues were significantly more likely than legislators who did not prioritize BH issues to select research evidence as one of the two factors that determined health policy priorities (32% versus 20%, OR=1.91, p=.002) (Table 2). Research evidence was the second most frequently identified factor by legislators who prioritized BH issues while it was fifth among legislators who did not prioritize BH issues. Constituents’ needs and opinions were the primary factors that determined health policy priorities by legislators who prioritized BH issues (66%) as well as those who did not (68%). Among all legislators, economic issues (18%) and interactions with lobbyists (8%) were the factors least frequently identified as determining health policy priorities.
Table 2.
Factors that determine the health policy priorities of state legislators, United States, 2012a
| BH issues policy priority (n=125) | BH issues not policy priority (n=737) | ||||||
|---|---|---|---|---|---|---|---|
| Factor | N | % | N | % | ORb | (95% CI) | p |
| Constituents’ needs and opinions | 82 | 66 | 474 | 68 | .93 | .62–1.40 | .728 |
| Research evidence | 40 | 32 | 140 | 20 | 1.91 | 1.25–2.90 | .002 |
| Legislation proposed by colleagues | 35 | 28 | 221 | 32 | .85 | .56–1.30 | .458 |
| Data impacting local area | 33 | 27 | 208 | 30 | .86 | .56–1.32 | .484 |
| Personal interest | 25 | 20 | 161 | 23 | .85 | .53–1.36 | .486 |
| Economic issues | 22 | 18 | 129 | 18 | .96 | .58–1.57 | .855 |
| Interaction with lobbyists | 10 | 8 | 52 | 7 | 1.09 | .54–2.21 | .805 |
Each respondent was limited to selecting two factors.
The odds ratios reflect the association between the odds of a policymaker identifying BH issues as policy priorities and each factor that determined health policy priorities.
Research dissemination preferences
In addition to being more influenced by research when determining health policy priorities, legislators who prioritized BH issues were more discerning consumers of research evidence than legislators who did not prioritize BH issues. Legislators who prioritized BH issues reported a higher importance rating for 10-of-12 statements about features of disseminated research than legislators who did not (Table 3). Differences were statistically significant for four features: research being unbiased (p=.014), research being presented in a brief, concise way (p=.044), research being delivered by a person the legislator knows and respects (p=.033), and research telling a story about how a health issue affects constituents (p=.030). Research being unbiased was the factor with the highest rating among legislators who prioritized BH issues while it was tied for fourth among legislators who did not prioritize BH issues. The political feasibility of research received the lowest rating regardless of whether BH issues were identified as priorities.
Table 3.
Research dissemination preferences of state legislators, United States, 2012a
| BH issues policy priority (n=125) | BH issues not policy priority (n=737) | ||||||
|---|---|---|---|---|---|---|---|
| Preference | M | SD | M | SD | Test statistic | df | p |
| Features of disseminated researcha | |||||||
| Unbiased | 4.54 | .82 | 4.29 | 1.0 | U=40,095 | 826 | .014 |
| Understandably written | 4.47 | .82 | 4.45 | .80 | U=36,518 | 816 | .770 |
| Presented in a brief, concise way | 4.46 | .86 | 4.33 | .86 | U=43,517 | 834 | .044 |
| Available at the time decisions are being made | 4.43 | .83 | 4.42 | .82 | U=39,539 | 832 | .778 |
| Deals with a priority issue for legislative policy action | 4.39 | .79 | 4.29 | .81 | U=40,088 | 824 | .158 |
| Relevant to my constituents | 4.32 | .78 | 4.19 | .85 | U=40,095 | 826 | .150 |
| Provides data on the cost-effectiveness of a policy | 4.30 | .86 | 4.29 | .82 | U=43,251 | 828 | .817 |
| Delivered to me by someone I know or respect | 4.27 | .77 | 4.07 | .91 | U=38,976 | 830 | .033 |
| Tells a story of how a health issue affects my constituents | 4.20 | .83 | 4.00 | .92 | U=38,375 | 826 | .030 |
| Provides policy options | 4.15 | .84 | 4.07 | .92 | U=4,1461 | 826 | .409 |
| Supports my position | 3.31 | 1.2 | 3.46 | 1.1 | U=45,959 | 822 | .179 |
| Has politically feasible implications | 3.28 | 1.2 | 3.41 | 1.2 | U=43,929 | 810 | .295 |
| Sources of disseminated researchb | |||||||
| University | 3.97 | .823 | 3.87 | .86 | U=41,014 | 825 | .384 |
| Constituents | 3.52 | 1.0 | 3.45 | .91 | U=41,198 | 825 | .432 |
| Other legislators | 3.41 | .86 | 3.35 | .78 | U=40,369 | 824 | .251 |
| Government source | 3.36 | .82 | 3.24 | .92 | U=40,602 | 823 | .317 |
| Caucus leadership | 3.30 | 1.0 | 3.15 | .98 | U=38,914 | 818 | .109 |
| Industry | 3.15 | .92 | 3.13 | .89 | U=43,272 | 829 | .808 |
| Advocacy groups | 2.70 | .84 | 2.83 | .89 | U=46,035 | 833 | .155 |
| The media | 2.21 | .82 | 2.16 | .86 | U=42,335 | 829 | .603 |
Possible scores range from 1 to 5, with higher scores indicating higher priority.
Possible scores range from 1 to 5, with higher scores indicating higher perceived reliability.
Legislators who prioritized BH issues generally perceived research to be more reliable than legislators who did not prioritize BH issues, regardless of the dissemination source (Table 3). Legislators who prioritized BH issues reported a higher reliability rating than legislators who did not prioritize BH issues for seven-of-eight sources of disseminated research, although these differences were not significant. Universities were identified as the most reliable source and media the least reliable source by both legislators who did and did not prioritize BH issues.
Research seeking and utilization practices
Legislators who prioritized BH issues reported being more active seekers and users of research than legislators who did not prioritize BH issues. These legislators engaged in 8-of-11 research seeking and utilization practices more often than legislators who did not prioritize BH issues (Table 4). The difference was significant for the practice of attending seminars or presentations where research was discussed (p=.012). Among all legislators, asking internal legislative research bureaus for information was performed most often and reading or watching popular media stories was performed least often.
Table 4.
Research seeking and utilization practices of state legislators, United States, 2012
| BH issues policy priority (N=125) | BH issues not policy priority (N=737) | ||||||
|---|---|---|---|---|---|---|---|
| Practice | M | SD | M | SD | Test statistic | df | p |
| Research seekinga | |||||||
| Ask internal legislative research bureaus for information | 4.23 | .94 | 4.06 | 1.0 | U=40,117 | 834 | 0.088 |
| Explore what other states are doing | 3.72 | 1.0 | 3.62 | .96 | U=41,383 | 836 | 0.182 |
| Read scientific research reports | 3.48 | 1.0 | 3.28 | 1.2 | U=40,513 | 835 | 0.099 |
| Ask an external legislative research organization for information | 3.30 | 1.1 | 3.36 | 1.1 | U=43,346 | 834 | 0.739 |
| Attend seminars or presentations where research is discussed | 3.05 | 1.1 | 2.78 | 1.1 | U=38,532 | 836 | 0.012 |
| Contact scientific researchers or experts for advice | 2.94 | 1.1 | 2.90 | 1.2 | U=43,142 | 832 | 0.715 |
| Read or watch popular media stories | 2.77 | 1.2 | 2.82 | 1.2 | U=45,820 | 833 | 0.470 |
| Research utilizationa | |||||||
| Use research to justify a decision | 4.16 | .95 | 4.11 | .91 | U=41,487 | 831 | 0.424 |
| Talk with colleagues about research on important issues | 4.15 | 1.0 | 4.15 | .92 | U=43,378 | 836 | 0.702 |
| Use research presented in committee testimony | 4.11 | .92 | 4.11 | .93 | U=44,240 | 832 | 0.946 |
| Take the results of a relevant scientific study into account when making a decision | 3.99 | .99 | 3.97 | .92 | U=42,507 | 832 | 0.514 |
Possible scores range from 1 to 5, with higher scores indicating greater frequency.
DISCUSSION
We found that legislators who prioritize BH issues actively seek and are influenced by research evidence; and more so than legislators who do not prioritize BH issues. These results suggest that the legislators who are most likely to act as BH policy entrepreneurs and best positioned to integrate BH research findings into policy designs are particularly receptive to research evidence and have distinct dissemination presences, although the magnitude of these differences are small. Future studies should examine, in greater detail, how BH research is used in state legislative processes and test the effects of legislator-focused BH research dissemination strategies. Our results offer guidance to structure the design of these strategies.
The finding that legislators who prioritized BH issues reported a significantly higher importance rating for the statement that research “tells a story of how a health issue affects my constituents” suggests that dissemination strategies which combine narrative with local BH data could be effective. Studies have found that narrative approaches to policy dissemination, in which stories about individuals affected by an issue are presented, are often more effective than exclusively data-focused approaches (43–45). This is consistent with research finding that people’s perceptions of mental illness improve when they know a person with a diagnosis (46) and Corrigan and Watson’s proposition that mental health policy advocacy is likely to be most effective when it involves personal stories about mental illness (29).
The finding that legislators who prioritized BH issues significantly preferred research delivered by a known and trusted individual suggests potential for initiatives that foster relationships between BH researchers and legislators. An initiative to enhance collaboration between mental health researchers and policy makers in Canada, for example, offers a model (47). BH researchers might also establish relationships with, and disseminate research findings directly to, legislative research bureau staff given that they were identified as legislators’ primary source for research evidence.
Our study can inform how BH researchers might utilize the media to infuse research evidence into policy making processes. Scholars have asserted that the media plays a major role in shaping BH policy (48–49). We found, however, that legislators rated the media as the least reliable and least utilized source for research. It is possible that BH research influences policy making indirectly via legislators’ constituents, who become knowledgeable about BH research through the media and advocate for legislators to act upon it. As described, constituent needs and opinions were identified as the most influential factors that determined health policy priorities and constituents were perceived as the second most reliable source of research.
We did not observe significant differences in political ideology between legislators who did and did not prioritize BH issues. This suggests bi-partisan support for BH policies, a situation that would increase the chances of BH policy proposals becoming law. Our study did not explore, however, legislators’ opinions about the types of policy approaches that should be used to address BH issues, the extent to which they were evidence-based, or varied by political ideology. As Corrigan and Watson describe, conservative and liberal legislators are likely to consider decisions to allocate resources for mental health services differently, with liberals being more inclined to support government funding of services (50).
Limitations
Limitations derive from the fact that we conducted a secondary analysis an existing dataset. Measures assessed legislators’ preferences and practices related to research evidence in general, not BH research in particular. This limits what can be inferred from the study. For example, we observed a strong association between research evidence being identified as a factor that determined health policy priorities and legislator prioritization of BH issues, but cannot infer whether BH research evidence contributed to legislators determining that BH issues were a priority.
There are also limitations with our broad measure of BH issue prioritization. Legislators identified a range of specific BH issues (e.g., depression among elderly people, prescription drug abuse among adolescents) in open-ended responses, but we combined these issues into a single measure because we did not have statistical power to conduct sub-issue analyses. Although many BH issues are co-morbid and simultaneously addressed by a single law (e.g., state BH parity legislation), they affect distinct populations with specific needs. Future research should explore the particular types of research used by legislators when working on specific BH issues.
There are similar limitations with our measure of non-BH issue prioritization. Legislators in this group identified a various issues as policy priorities in response to Q1, some of which are not the subject of extensive research (e.g., unemployment, transportation). Consequently, compared legislators who prioritized BH issues, legislators who did not may have reported engaging in research seeking and utilization practices less frequently because they focus on issues for which research evidence is less relevant. This is unlikely to affect the implications of our study, however, because it simply signals that legislators who prioritize BH issues may engage in different research practices than legislators who do not prioritize these issues and that tailored dissemination strategies may be warranted. Our study was designed to assess whether use of research practices differed between legislators who did and did not prioritize BH issues, not to determine the reasons for the differences observed.
CONCLUSIONS
Compared to legislators who do not prioritize BH issues, legislators who prioritize BH issues more actively seek, have distinct preferences for, and are more influenced by research evidence. These results suggest potential for BH research findings to inform legislative decisions. Developing and testing policy-focused BH research dissemination strategies are areas for future research that can advance evidence-based policies which improve the well-being of people affected by BH issues.
Acknowledgments
This research was funded in part by the National Cancer Institute at the National Institutes of Health (grant number 1R01CA124404-01); the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK Grant Number 1P30DK092950); and Washington University Institute of Clinical and Translational Sciences grant UL1 TR000448 and KL2 TR000450 from the National Center for Advancing Translational Sciences.
Footnotes
Disclosures
None of the authors have any conflicts of interest to disclose.
Previous presentation
This research was presented at the 2015 AcademyHealth Annual Dissemination & Implementation Conference in Washington, DC on December 14, 2015.
Contributor Information
Jonathan Purtle, Email: jpp46@drexel.edu, Drexe Univerisity - Health Management & Policy, 3215 Market St., Philadelphia, Pennsylvania 19104.
Elizabeth A. Dodson, Washington University in St. Louis, Institute for Public Health
Ross C. Brownson, Washington University in St. Louis, Division of Public Health Sciences and Siteman Cancer Center
References
- 1.Mechanic D. Policy challenges in improving mental health services: Some lessons from the past. Psychiatric Services. 2003;54(9):1227–1232. doi: 10.1176/appi.ps.54.9.1227. [DOI] [PubMed] [Google Scholar]
- 2.Tanenbaum SJ. Evidence-based practice as mental health policy: Three controversies and a caveat. Health Affairs. 2005;24(1):163–173. doi: 10.1377/hlthaff.24.1.163. [DOI] [PubMed] [Google Scholar]
- 3.Lehman AF, Goldman H, Dixon LB, Churchill R. Evidence-based mental health treatments and services: Examples to inform public policy. Milbank Memorial Fund; 2004. Available at http://www.milbank.org/uploads/documents/2004lehman/2004lehman.html. [Google Scholar]
- 4.Hogan M. Using evidence to influence policy and improve practice. Psychiatric Services. 2015;66(8):769–769. doi: 10.1176/appi.ps.660803. [DOI] [PubMed] [Google Scholar]
- 5.Nelson G. Community psychology and transformative policy change in the neo-liberal era. American Journal of Community Psychology. 2013;52(3–4):211–223. doi: 10.1007/s10464-013-9591-5. [DOI] [PubMed] [Google Scholar]
- 6.Sarason SB. Community psychology and public policy: Missed opportunity. American Journal of Community Psychology. 1984;12(2):199–207. doi: 10.1007/BF00897043. [DOI] [PubMed] [Google Scholar]
- 7.Rabin BA, Brownson RC, Haire-Joshu D, Kreuter MW, Weaver NL. A glossary for dissemination and implementation research in health. Journal of Public Health Management and Practice. 2008;14(2):117–123. doi: 10.1097/01.PHH.0000311888.06252.bb. [DOI] [PubMed] [Google Scholar]
- 8.Glasgow RE, Vinson C, Chambers D, Khoury MJ, Kaplan RM, Hunter C. National Institutes of Health approaches to dissemination and implementation science: Current and future directions. American Journal of Public Health. 2012;102(7):1274–1281. doi: 10.2105/AJPH.2012.300755. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Substance Abuse and Mental Health Services Administration. Shaping and informing public policy to improve lives. 2011 Available at http://store.samhsa.gov/product/Shaping-and-Informing-Public-Policy-to-Improve-Lives/SMA11-PHYDE042611.
- 10.National Institute of Mental Health. Strategic plan. Available at http://www.nimh.nih.gov/about/strategic-planning-reports/NIMH_StrategicPlanforResearch_508Compliant_CORRECTED_FINAL_149979.pdf.
- 11.National Institute on Drug Abuse. Mission statement. Available at https://d14rmgtrwzf5a.cloudfront.net/sites/default/files/stratplan.pdf.
- 12.National Institute on Alcohol Abuse and Alcoholism. Mission statement. Available at http://www.niaaa.nih.gov/about-niaaa/our-work/mission-statement.
- 13.Brownson RC, Jacobs JA, Tabak RG, Hoehner CM, Stamatakis KA. Designing for dissemination among public health researchers: Findings from a national survey in the United States. American Journal of Public Health. 2013;103(9):1693–1699. doi: 10.2105/AJPH.2012.301165. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Bero LA, Grilli R, Grimshaw JM, Harvey E, Oxman AD, Thomson MA. Closing the gap between research and practice: an overview of systematic reviews of interventions to promote the implementation of research findings. BMJ. 1998;317(7156):465–468. doi: 10.1136/bmj.317.7156.465. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Brownson RC, Royer C, Ewing R, McBride TD. Researchers and policymakers: Travelers in parallel universes. American Journal of Preventive Medicine. 2006;30(2):164–172. doi: 10.1016/j.amepre.2005.10.004. [DOI] [PubMed] [Google Scholar]
- 16.Bogenschneider K, Corbett TJ. Evidence-based Policymaking: Insights from Policy-minded Researchers and Research-minded Policymakers. Routledge; 2011. [Google Scholar]
- 17.Lomas J. Diffusion, dissemination, and implementation: Who should do what? Annals of the New York Academy of Sciences. 1993;703(1):226–237. doi: 10.1111/j.1749-6632.1993.tb26351.x. [DOI] [PubMed] [Google Scholar]
- 18.Dodson E, Brownson RC, Weiss S. Policy Dissemination Research. In: Brownson RC, Colditz GA, Proctor EK, editors. Dissemination and Implementation Research in Health: Translating Science to Practice. Oxford University Press; 2012. [Google Scholar]
- 19.Glasgow RE, Chambers DA, Cynkin L. News from the NIH: Highlights in implementation science from the National Cancer Institute and the National Institute of Mental Health. Translational Behavioral Medicine. 2013;3(4):335–337. doi: 10.1007/s13142-013-0218-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Brownson RC, Seiler R, Eyler AA. Measuring the impact of public health policies. Preventing Chronic Disease. 2010;7(4) [PMC free article] [PubMed] [Google Scholar]
- 21.Williamson A, Makkar SR, McGrath C, Redman S. How can the use of evidence in mental health policy be increased? A systematic review. Psychiatric Services. 2015;66(8):783–797. doi: 10.1176/appi.ps.201400329. [DOI] [PubMed] [Google Scholar]
- 22.Oliver K, Innvar S, Lorenc T, Woodman J, Thomas J. A systematic review of barriers to and facilitators of the use of evidence by policymakers. BMC Health Services Research. 2014;14(1):2. doi: 10.1186/1472-6963-14-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Goldner EM, Jeffries V, Bilsker D, Jenkins E, Menear M, Petermann L. Knowledge translation in mental health: A scoping review. Healthcare Policy. 2011;7(2):83–98. [PMC free article] [PubMed] [Google Scholar]
- 24.Waddell C, Lavis JN, Abelson J, Lomas J, Shepherd CA, Bird-Gayson T, Offord DRD. Research use in children’s mental health policy in Canada: Maintaining vigilance amid ambiguity. Social Science & Medicine. 2005;61(8):1649–1657. doi: 10.1016/j.socscimed.2005.03.032. [DOI] [PubMed] [Google Scholar]
- 25.Waddell C, Shepherd CA, Lavis JN, Lomas JN, Abelson J, Bird-Gayson T. Balancing rigour and relevance: Researchers’ contributions to children’s mental health in Canada. Evidence and Policy. 2007;3(2):181–195. [Google Scholar]
- 26.Ritter A. The role of research evidence in drug policy development in Australia. Politička Misao. 2012;48(5):141–156. [Google Scholar]
- 27.Ritter A, Lancaster K. Measuring research influence on drug policy: A case example of two epidemiological monitoring systems. International Journal of Drug Policy. 2013;24(1):30–37. doi: 10.1016/j.drugpo.2012.02.005. [DOI] [PubMed] [Google Scholar]
- 28.Tieberghien J, Decorte T. Understanding the science–policy nexus in Belgium: An analysis of the drug policy debate (1996–2003) Drugs: Education, Prevention and Policy. 2013;20(3):241–248. [Google Scholar]
- 29.Corrigan PW, Watson AC. Factors that explain how policy makers distribute resources to mental health services. Psychiatric Services. 2014;54(4):501–507. doi: 10.1176/appi.ps.54.4.501. [DOI] [PubMed] [Google Scholar]
- 30.Barry CL, Huskamp HA, Goldman HH. A political history of federal mental health and addiction insurance parity. Milbank Quarterly. 2010;88(3):404–433. doi: 10.1111/j.1468-0009.2010.00605.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Cummings JR, Wen H, Ko M, Druss BG. Geography and the Medicaid mental health care infrastructure: Implications for health care reform. JAMA Psychiatry. 2013;70(10):1084–1090. doi: 10.1001/jamapsychiatry.2013.377. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Mark T, Levit K, Coffey R. National expenditures for mental health services and substance abuse treatment, 1993–2003. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2008. Publication No. SMA 07-4227. [Google Scholar]
- 33.Hernandez EM, Uggen C. Institutions, politics, and mental health parity. Society and Mental Health. 2012;2(3):154–171. doi: 10.1177/2156869312455436. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Burns ME. State Discretion over Medicaid Coverage for Mental Health and Addiction Services. Psychiatric Services. 2015;66(3):221–223. doi: 10.1176/appi.ps.201400440. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Wen H, Cummings JR, Hockenberry JM, Gaydos LM, Druss BG. State parity laws and access to treatment for substance use disorder in the United States: Implications for federal parity legislation. JAMA Psychiatry. 2013;70(12):1355–1362. doi: 10.1001/jamapsychiatry.2013.2169. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Kingdon JW. Agendas, Alternatives, and Public Policies. Little, Brown; 1984. [Google Scholar]
- 37.Sabatier PA, Weible C, editors. Theories of the Policy Process. Westview Press; 2014. [Google Scholar]
- 38.Mintrom M, Norman P. Policy entrepreneurship and policy change. Policy Studies Journal. 2009;37(4):649–667. [Google Scholar]
- 39.Brownson RC, Dodson EA, Stamatakis KA, Casey CM, Elliott MB, Luke DA, Kreuter MW. Communicating evidence-based information on cancer prevention to state-level policy makers. Journal of the National Cancer Institute. 2011;103(4):306–316. doi: 10.1093/jnci/djq529. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Bogenschneider K, Little OM, Johnson K. Policymakers’ use of social science research: Looking within and across policy actors. Journal of Marriage and Family. 2013;75(2):263–275. [Google Scholar]
- 41.Moreland-Russell S, Barbero C, Andersen S, Geary N, Dodson EA, Brownson RC. Hearing from all sides: How legislative testimony influences state level policy-makers in the United States. International Journal of Health Policy and Management. 2015;4(2):91–98. doi: 10.15171/ijhpm.2015.13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Purtle J, Peters R, Brownson R. A review of policy dissemination and implementation research funded by the National Institutes of Health 2007–2014. Implementation Science. 2016 Jan;4(1):1. doi: 10.1186/s13012-015-0367-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Stamatakis KA, McBride TD, Brownson RC. Communicating prevention messages to policy makers: the role of stories in promoting physical activity. Journal of Physical Activity & Health. 2010;7(1):S99. doi: 10.1123/jpah.7.s1.s99. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Baesler EJ, Burgoon JK. The temporal effects of story and statistical evidence on belief change. Communication Research. 1994;21(5):582–602. [Google Scholar]
- 45.Kreuter MW, Green MC, Cappella JN, Slater MD, Wise ME, Storey D, Woolley S. Narrative communication in cancer prevention and control: A framework to guide research and application. Annals of Behavioral Medicine. 2007;33(3):221–235. doi: 10.1007/BF02879904. [DOI] [PubMed] [Google Scholar]
- 46.Stuber JP, Rocha A, Christian A, Link BG. Conceptions of mental illness: Attitudes of mental health professionals and the general public. Psychiatric Services. 2014;65(4):490–497. doi: 10.1176/appi.ps.201300136. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Goering P, Butterill D, Jacobson N, Sturtevant D. Linkage and exchange at the organizational level: A model of collaboration between research and policy. Journal of Health Services Research & Policy. 2003;8(S2):14–19. doi: 10.1258/135581903322405126. [DOI] [PubMed] [Google Scholar]
- 48.Wahl OF. News media portrayal of mental illness implications for public policy. American Behavioral Scientist. 2003;46(12):1594–1600. [Google Scholar]
- 49.Hallam A. Media influences on mental health policy: long-term effects of the Clunis and Silcock cases. International Review of Psychiatry. 2002;14(1):26–33. [Google Scholar]
- 50.Corrigan PW, Watson AC, Warpinski AC, Gracia G. Stigmatizing attitudes about mental illness and allocation of resources to mental health services. Community Mental Health Journal. 2004;40(4):297–307. doi: 10.1023/b:comh.0000035226.19939.76. [DOI] [PubMed] [Google Scholar]