Aligning Dissemination and Implementation Science With Health Policies to Improve Children’s Mental Health

Abstract

The prevalence of mental health problems among children (ages 0-21) in the U.S. remains unacceptably high, and post-COVID-19, is expected to increase dramatically. Decades of psychological knowledge about effective treatments should inform the delivery of better services. Dissemination and implementation (D&I) science has been heralded as a solution to the persistent problem of poor quality services and has, to some extent, improved our understanding of the contexts of delivery systems that implement effective practices. However, there are few studies demonstrating clear, population-level impacts of psychological interventions on children. Momentum is growing among communities, cities, states, and some federal agencies to build “health in all policies” to address broad familial, social, and economic factors known to affect children’s healthy development and mental health. These health policy initiatives offer a rare opportunity to repurpose D&I science, shifting it from a primary focus on evidence-based practice implementation, to a focus on policy development and implementation to support child and family health and well-being. This shift is critical as states develop policy responses to address the health and mental health impacts of the COVID-19 pandemic on already-vulnerable families. We provide a typology for building research on D&I and children’s mental health policy.

Editor’s note.

This article is part of a special issue, “Expanding the Impact of Psychology Through Implementation Science,” published in the November 2020 issue of American Psychologist. Shannon Wiltsey Stirman and Rinad S. Beidas served as editors of the special issue, with Anne E. Kazak as advisory editor.

Introduction

Health policies directly affect population health and typically drive changes in the payment and delivery of services in health systems, including mental health care. Federal health policies and their resulting programs, such as Medicaid’s Early and Periodic Screening, Diagnostic, and Treatment (EPSDT) program, the Title IV-E Federal Foster Care Program, and the Title V Maternal and Child Health Services Block Grant Program, direct the coverage of health and mental health services for children and families, particularly those from vulnerable populations (i.e., impoverished families, at-risk young children, and children in foster care). In the past decade, a trend towards implementing the “health in all policies” (HiAP) framework has opened the door for more sustained public health impact from the psychological knowledge base that is ready to be deployed. HiAP target determinants that extend beyond traditional notions of health, including housing, employment and tax credits, and are coming to be recognized as important drivers of population mental health (Purtle et al., 2020; Dopp & Lantz 2019).

While health policies typically include laws, rules, codes, judicial decisions, or broad-reaching and publicly-funded initiatives at local, state, or national levels (Bogenschneider & Gross, 2004), the HiAP framework also promotes collaboration across non-health sectors (e.g. housing, public safety, education, and transportation) to create the conditions for healthy development by improving the social, economic, and physical environments where families live (Centers for Disease Control and Prevention, 2020). A decade ago, The World Health Organization (2010) acknowledged HiAP as a driver of population health, and it is being utilized by many cities and states to guide policymaking, particularly in large urban areas (Gase et al., 2013; Hearne et al. 2015). It is also a foundation for the National Prevention Strategy and Healthy People 2020 to improve population health and address inequities in care in the U.S.

Over the last three decades, psychological science has substantially advanced knowledge about the risks that delay or derail children’s development, as well as about effective prevention programs and treatments that reduce the burden of mental disorders, particularly among youth and families who live in areas of concentrated disadvantage (Biglan et al., 2020). Despite this amassed psychological knowledge, along with population-based evidence that 75% of adult mental disorders begin before age 24 (Kessler & Wang, 2008), the prevalence of two major mental health disorders in children has increased since the mid-1990’s (i.e. anxiety and depression; Bitsko et al., 2018), and there have been increases in rates of youth suicide (ages 10-24)(Curtin & Heron, 2019), psychiatric hospitalizations (McDermott et al., 2017) and risky behaviors (Kann et al., 2018). Serious public policy attention has not yet been paid to the population-level implementation of early intervention and treatment services to help children thrive. There are undoubtedly many reasons for this, but one may be scientific inattention to public health policy drivers (Dopp & Lantz, 2019). In fact, the chasm between scientific findings and public policy has been called the ‘valley of death” (Meslin et al., 2013).

The science of dissemination and implementation (D&I) has filled an important gap in the chasm between knowledge acquisition and knowledge translation, with a major focus on improving understanding of the process of installing effective psychological treatments, preventive programs and practices (i.e., evidence-based practices or EBPs), and scaling up their spread. However, critiques of implementing EBPs (Chorpita, 2019; Atkins et al., 2016; Kazdin, 2019) call into question the virtue of continuing to focus primarily on promoting EBP’s as products—decontextualized from the venues of their delivery. Chorpita (2019) points out that the dynamic and changing knowledge base about effective interventions requires new ways of managing knowledge itself, and suggests shifting attention to the knowledge delivery problem (Chorpita & Daleiden, 2014), including using knowledge management tools (e.g., outcome monitoring and measurement feedback systems embedded in the delivery of the service or available online) to enable continuous learning. Atkins et al. (2016) point to the need for an ecological approach to enhance delivery of services, rather than the promotion of programs. Kazdin (2019) in a prescient, pre-COVID-19 paper, pointed to the lackluster impact of the dominant intervention delivery model—face-to-face treatment, with a trained mental health professional, provided in a clinical setting, which constrains both the scale and reach of psychosocial interventions—and called for novel methods (e.g. social media, socially-assistive robots, and social networks) to deliver services.

While these approaches are auspicious and likely to improve the spread and reach of interventions, making these and other D&I EBP focused changes, absent attention to an overlooked yet powerful driver of public health impact—the implementation of public health policies—could be a missed opportunity (Purtle et al., 2020). In 2016, Joyner, Panetta, and Ioannidis wrote a viewpoint in the Journal of the American Medical Association provocatively titled, “What Happens When Underperforming Big Ideas in Research Become Entrenched?” (Joyner et al., 2016). They argued that the public health benefits from large NIH investments in “big ideas”— including gene therapy, regenerative medicine, stem cells, and electronic health records—had largely failed to materialize. The rhetorical promises and occasional hype surrounding D&I science and evidence-based practices, in the absence of compelling evidence of public health impact, is dangerously reminiscent of underperforming “big ideas.”

We suggest that to create the conditions for maximum impact of the psychological knowledge base on practice, D&I science methods could be productively repurposed to focus on health and mental health policies, including HiAP, where the “intervention” itself is the policy. This differs from instances where an evidence-based treatment (EBT) or EBP is rolled out with consideration of the policy context (e.g., Glisson et al., 2010; Chaffin et al., 2012; Grimes et al., 2011). Although findings from these types of studies can have implications for policy, we are arguing for a complementary— but different paradigm—that applies D&I methods to health policies themselves that target child-related health or mental health outcomes (e.g., infant mortality, school readiness, social-emotional development, social isolation).

Numerous naturalistic health and mental health policy experiments are already underway in communities and states across the country, and they reflect a complex and nuanced appreciation of the neurodevelopmental, familial, social, and community contexts in which children develop (Smith et al., 2018; Gratale et al., 2020; National Academies of Sciences and Engineering, 2019). The current health policy environment, particularly now, given the COVID-19 pandemic and the strain on the health care system, provides a critical opportunity to study the implementation of policies into health systems. It also is well positioned for facilitating the integration of novel, digitalized, and technological advances and knowledge management tools. Health policies may, in fact, be the strongest avenue for incentivizing these innovations (Fagan et al., 2019; Weaver & DeRosier, 2019). Health policies, particularly as applied to children’s health and mental health, have been neglected areas for examination by D&I science. Since the issuance of the first D&I program announcement in 2003, National Institutes of Health (NIH) D&I investments in children’s mental health policy research—where the opportunity to effect broad population-level change exists— are inconsequential. Between 2007-2014, only 2 unique grants, or less than 1% of all NIH D&I science projects were focused on children’s mental health policy (Purtle et al., 2016), although more recent attention (2015-2018) has been given to work at the intersection of children’s mental health, policy, and D&I [(i.e., RO1MH072961, sustainment of an evidence-based child neglect intervention in a large statewide public service system; and R21MH111806, methods to improve the uptake of federal parity legislation in state mental health systems (NIH RePORTER, 2020)].

In this paper, we briefly describe trends in children’s mental health, illustrating the persistence of these problems and the disparities inherent in them. We describe the growth in the psychological knowledge base on EBPs, efforts to scale several EBPs in the U.S. and internationally, and describe some of the limitations of this psychological knowledge base, including the de-contextualization of EBPs from community, social, and policy environments. We describe how the current focus of D&I science on EBPs has underperformed when it comes to children’s health and mental health, and suggest that taking a D&I lens to examine health policies offers a greater likelihood of improving children’s health and well-being. We then present a typology for examining the interface of D&I methods and children’s health policy, and describe two natural policy experiments underway (in New York and Ohio) designed to promote children’s healthy development by targeting changes in social and community supports. We conclude with ideas about ways to align psychological science and D&I science and to focus attention on questions relating to health policies and their effect on children’s mental health and wellbeing, more critical than ever in a post-COVID-19 era.

A. Background: Trends and Disparities in Children’s Mental Health Disorders

The Centers for Disease Control and Prevention now estimates the overall prevalence of children’s psychological disorders at 17.4% (Cree et al., 2018). Among children aged 3–17 years, 7.1% have current anxiety problems, 7.4% have a current behavioral/ conduct problem, and 3.2% have current depression (Ghandour et al. 2019). Prevalence rates for two common childhood mental health disorders have increased (e.g. anxiety and depression; Bitsko et al., 2018; Mojtabai et al., 2016) since the groundbreaking, population-based Great Smoky Mountain Study conducted two decades ago (Costello et al., 1996). Importantly, many children also often have considerable comorbidities; 40% of children with mental health disorders have at least one comorbid mental health condition (Olfson, 2018; NASEM, 2019), and rates of comorbidity for mood and disruptive behavior disorders are higher for children with substance use disorders— nearly double that of children without them (Kandel et al., 1999).

In addition to the high and increasing prevalence of mental health disorders in children, glaring disparities exist in access to services. Ethnic/racial minorities have lower treatment rates than non-Hispanic whites for several classes of disorders; Hispanic children are less likely to receive treatment for mood and anxiety disorders; non-Hispanic Blacks were less likely to receive treatment for mood disorders; and other/multiracial ethnic youth were less likely to receive treatment for anxiety and ADHD (Merikangas et al., 2011). Many practical and perceptual barriers also contribute to disparities in the receipt of services. These include practical barriers of time, location, and cost of attendance (Haine-Schalgel & Walsh, 2015); stigma and perceived usefulness of treatment (Alegria et al., 2010; Reardon et al., 2017; Owens et al., 2002); difficulties engaging families in care, particularly for the most vulnerable and high-risk families (Bornheimer et al., 2018; McKay et al., 2004); and lack of perceived need (Green et al. 2020). Recently, a multidisciplinary international colloquium convened to explicitly examine how to leverage D&I science to reduce decades-long disparities in mental health care access and treatment for children and families (Stadnick et al., 2020). Stadnick and colleagues report that potential solutions to solving these inequities involve two policy-driven solutions: an appropriate and trained workforce and insurance reimbursement.

B. Underperforming: The Problem of Decontextualization

From 1990 to approximately 2010, federal investments in services and intervention research, largely by the National Institute of Mental Health (NIMH), focused on developing and field-testing therapeutic interventions to address many childhood mental health disorders, including those that targeted anxiety, depression, attention deficit hyperactivity disorder, as well as parenting programs (August et al., 2002; Dodge & Conduct Problems Research Prevention Group, 2007; Hawkins et al., 2009; Jensen et al., 2007; Lewinsohn et al., 1999). As a result of these investments, the portfolio of evidence-based therapies and practices expanded exponentially, such that there are literally hundreds of trials of psychosocial treatments, preventive practices, and services for children. Most of these approaches became programs that are now cataloged in large practice registries. These include the Evidence-Based Practices Resource Center, Blueprints, Title IV-E Prevention Services Clearinghouse, the California Evidence Based Clearinghouse for Child Welfare, and the sophisticated Managing and Adapting Practice (MAP) clinical decision support tool (Chorpita & Daleiden, 2009). Many of these EBPs have also been analyzed for their costs and benefits by the Washington State Institute for Public Policy (WSIPP), and this information is available freely on their website (WSIPP, 2019).

Studies that examine the implementation of EBP’s for children have shown modest impact, at best. Efforts to implement wraparound and coordinated care services to improve child mental health outcomes have shown limited impact (Bruns et al., 2015), due to poor fidelity, organizational culture and climate, and worker morale, or no impact at all in less complex populations (Wu et al., 2018). Recent work implementing evidence-based therapies in outpatient clinics in an urban environment found that after five years of intensive consultation of trained therapists, there was only a 3% increase in the use of these practices in routine care, and effect sizes for improvements were smaller than effect sizes observed in efficacy and effectiveness studies (Beidas et al., 2019; Rudd et al., 2019). Attempts to implement a measurement feedback system (i.e., the Contextualized Feedback System™ or CFS) into routine outpatient clinics failed, largely due to differences in acceptance of consultation, clinical supervision procedures, and technical support in the use of the CFS™ (Gleacher et al., 2016). Finally, EBP implementation in non-clinic settings showed that implementation of Interpersonal Psychotherapy—Adolescent Skills Training in schools showed only modest results in comparison to school-based group counseling (Young et al., 2016). These EBP implementation studies have apparently met with inner and outer context challenges. Furthermore, this is a problem that is not unique to the United States (Stadnick et al., 2020).

There have been a few efforts to scale EBP management systems, prevention programs, and even policies that have met with some success. One promising effort is in Los Angeles (L.A.), where the L.A. County Department of Mental Health implemented, countywide, the Managing and Adapting Practice (MAP) clinical decision support system (www.practicewise.com), which includes a searchable online database of evidence-based practices, practice and process guides to organize service delivery, and an outcome tracking or ‘dashboard’ tool. MAP provides clinicians with guidance on an array of EBP’s that can be matched to the diverse needs of children in the county (Chorpita & Daleiden, 2009). MAP-treated children had positive outcomes for four different primary problems (effect sizes ranging from .59 to .80). Further, the findings suggested that scaling up a system-wide (county) initiative like MAP could improve children’s outcomes when attention was paid to contextual factors, such as adequate investment, community collaborative partnerships, intensive training, and supervisory support (Southam-Gerow et al., 2014).

Several prevention programs have also been scaled. One of these is the Communities that Care (CTC) prevention program, which is aimed at reducing problem behaviors and promoting healthy youth development by targeting children’s risk and protective factors (Hawkins et al., 2014). A large, 7-state randomized trial of CTC had shown a positive impact on youth outcomes (Hawkins et al., 2009), and a retrospective examination of the implementation of CTC statewide in Pennsylvania found a small effect in the reduction of youth problem behavior (Chilenski et al., 2019). CTC is an example of a parallel process of implementing community-based supports and EBPs while simultaneously involving community leaders and then evaluating their perspectives (Brown et al., 2014). It is not the same type of study we are describing in our proposed policy typology (see Table 1), which targets the policies and/or policymaking processes directly. However, it is an important approach for learning about policy processes as implementation is evaluated, and using that knowledge to inform broader policymaking.

Table 1.

Typology of D&I Research on Children’s Mental Health Policy

Type of Policy D&I Study	Objectives	Example
Policy Dissemination Research
Formative Studies of Policymakers	Characterize policymakers’ awareness about, attitudes towards, support for, and preferences for receiving information about children’s mental health policy issues	Stewart et al. (2018) used survey data to state mental health agency officials’ attitudes towards policies that incentivize the use of evidence-based treatments
	Identify discrete and meaningful sub-groups among policymakers that vary in terms of their attributes related to children’s mental health policy issues	Purtle et al. (2018b) used survey data and latent class analysis to identify three different types of legislator that vary in terms of their thinking about mental health issues
	Understand how contextual factors influence policymakers’ support for, and decisions about, children’s mental health policy issues	Hyde et al. (2016) used interview methods to understand factors influencing uses of research evidence in state policy decision-making related to mental health services for youth being served by child welfare agencies
Dissemination Effectiveness Studies of Policymakers	Test dissemination strategies to determine which are most effective at changing policymakers’ awareness about, attitudes towards, support for evidence-based children’s mental health policies	Crowley et al. (2018) conducted a pilot trial of a prevention science evidence provision service for U.S. Congresspersons and their staff
Policy Implementation Research
Policy Process Implementation Studies	Describe the process through which a policy has been implemented	Purtle et al. (2018b) used survey data to assess inter-agency strategies used by state mental health agencies to support implementation of federal mental health parity laws
	Identify policy implementers’ perceptions of barriers and facilitators to policy implementation, acceptability/feasibility of implementation strategies, or fidelity	Regan et al. (2017) conducted interviews to understanding barriers and facilitators to implementation of the California Mental Health Services Act on child serving mental health agencies in Los Angeles County
Policy Impact Implementation Studies	Test or contrast policy implementation strategies to determine which are most effective at improving implementation outcomes	Bruns et al (2019) studied the association between modifiable and unmodifiable inner and outer context factors on the implementation of evidence-based practices in state mental health systems

There have also been several international efforts that have examined the impact of scaling child mental health policies. Timimi (2015) reports on the National Health Service efforts in the United Kingdom (UK) to deploy a countrywide program for improving children’s access to psychological therapies for depression and anxiety disorders, and measurement of its impact has been described by Hall et al. (2014). While this work is noteworthy, the health care system in the UK is substantively different from that in the U.S. so extrapolation of the impact may not be accurate.

Despite these positive developments, the public health potential of knowledge about effective interventions and their implementation for children is not having measurable impact at a population level. The prevalence rates for two of the most common mental health disorders in children are increasing (i.e., anxiety and depression; Bitsko et al., 2018), suicide rates are increasing (Curtin & Heron, 2019), and rates of service use have changed only slightly across all disorders; only about half of children get needed treatment (Whitney & Peterson, 2019), and non-white children are at particular risk for non-treatment (Merikangas et al., 2011). Why is the public health potential of knowledge about effective interventions and their implementation not having measurable impact at a population level for children in the United States?

One reason for limited impact may be that many of these services have been developed in the absence of attention to the contexts in which those services were delivered (Atkins et al., 2006; Atkins et al., 2016; Bickman, 2013; Hoagwood et al., 2014; Ringeisen et al., 2002; Schoenwald et al., 2010; Weisz et al., 2013). This has made their implementation difficult, and at times, impossible (Hoagwood & Olin, 2002; Chambers et al., 2013). The challenges in scaling up EBPs have been well documented, including most recently in a National Academies of Sciences, Engineering and Medicine (NASEM) report, Mental, Emotional and Behavioral Development in Children and Youth (2019). Necessary supports include active engagement of stakeholders, a well-trained workforce, ongoing monitoring using feasible and interoperative data systems, cross-system collaborations, financing models that are adequate, and active policy leadership, among other issues. While each of these separately, or in combination, can be examined as D&I barriers, these same factors constitute core components of several major health policy initiatives that are targeting broad social and economic factors. Therefore, alignment of D&I science goals with these policy rollouts could be an efficient way to accelerate the public health impact of both D&I and psychological science.

C. Unexamined: D&I Research on Children’s Mental Health Policy

The interface between D&I science and policymaking, particularly in children’s mental health, has been largely ignored. One reason might be that policymaking is seen as residing within a political world, where science has no place, power politics preside, and policymaking is insusceptible to dispassionate intervention. However, recent work suggests that the factors which shape evidence-informed mental health policymaking can, in fact, be identified (Purtle et al., 2018). Secondly, policymaking in children’s mental health is seen as largely atheoretical and, therefore, not capable of being studied with scientifically-informed hypotheses. However, the field of policy studies has produced empirically-informed, testable theories of policymaking processes that can be applied to implementation science (Nilsen et al. 2013; Sabatier 2019). Finally, academic researchers are typically not rewarded (i.e., by promotion and tenure standards) for policy-relevant work done in local, state, or federal systems (Meisel et al., 2019).

Theoretical Foundations.

The term “evidence-based” has a different meaning in the policy context than in clinical use (Baicker & Chandra, 2017; Cairney & Oliver, 2017). While evidence-based practice entails the implementation of empirically proven treatments in the clinical context, it more broadly refers to the use of research evidence in the policy context. For example, the Congressionally-mandated Commission on Evidence-Based Policymaking (2017) defines evidence-based policymaking as "the application of evidence to inform decisions in government."

The work of social scientists in the 1960s and 1970s, particularly that of Weiss (1979), contributed to a typology of four broad types of research use in policymaking. Instrumental research use involves the use of research evidence to solve a problem or directly inform a decision. Conceptual research use broadly affects how policymakers think about the causes and consequences of a problem and solutions to address it. Tactical research use entails using research evidence as political ammunition to support a pre-determined policy position or political agenda. Finally, imposed research use relates to policymakers using research evidence because they are required to do so by statute or administrative code. For example, a 2017 Pew-MacArthur analysis found that 22 states had mandates that required policymakers to use research evidence in the area of behavioral health and 16 had such mandates in the area of child welfare (Pew-MacArthur Results First Initiative, 2017).

While this typology has been widely used to study the use of research evidence in health policymaking (Yanovitzky & Weber, 2019), its application to mental health in general, and children’s mental health in particular, is very limited. Only two studies, both qualitative, have explored variations in research use in children’s mental health policymaking—one focused on policymakers overseeing state foster care systems (Hyde et al., 2016)—and one was conducted in Canada (Waddell et al., 2005). A 2015 systematic review of interventions to promote evidence-based mental health policymaking did not identify any studies focused on children in U.S. contexts (Williamson et al., 2015).

D. Expanding D&I Research in Children’s Mental Health Policy: A Proposed Typology

Redirecting some D&I research investments towards health policy requires a different but complementary framework from the current D&I model that typically targets EBP implementation, to reflect new domains, purposes, and outcomes. Table 1 describes our new typology consisting of four broad categories of policy studies, subsumed under the two primary domains of dissemination research and implementation research. In the domain of policy dissemination research, formative studies of policymakers can shed light on factors affecting decision making, including how policymakers think about children’s mental health issues, what they want from children’s mental health evidence that is disseminated to them, and how contextual factors might influence decision-making processes. The utility of these formative studies is their ability to provide an empirical foundation to inform the design of dissemination strategies, as well as the tailoring of dissemination strategies for different policymaker audiences and contexts. For example, Purtle and colleagues conducted a series of studies that characterized state legislators’ and mental health agency officials’ opinions about specific issues related to mental health (e.g., adverse childhood experiences, mental health insurance parity laws), preferences for receiving mental health evidence, and identified discrete audience segments of legislators in terms of their opinions and behaviors related to mental health policy issues (Purtle et al., 2020).

Formative studies can also document policymaking processes. For example, Waddell et al. (2005) explored how research evidence was used in making policy decisions about children’s mental health in Canada and Hyde et al. (2016) explored variations in how research evidence was used in policymaking related to services for children in child welfare agencies in the U.S. (Hyde et al., 2016). Also in the dissemination domain are experimental studies that provide head-to-head comparisons of the effects of different policymaker-focused dissemination strategies. This area of research is under-developed in D&I in general, and especially in children’s mental health. One relevant example comes from Crowley et al. (2018) who conducted a pilot trial of a “research-to-policy collaboration” model aimed at translating prevention research to increase evidence-based policymaking by U.S. Congresspersons and their staff.

In the domain of policy implementation research, very little research related to children’s mental health has been conducted. However, some policy process implementation studies exist. For example, studies have assessed community service providers’ experiences with implementation of the California Mental Health Services Act in Los Angeles County (Regan et al., 2017; Starks et al., 2017). Policy implementation studies can also generate data that can assess how factors related to policy implementation might mediate or moderate policy effects on children’s mental health service use or other relevant outcomes (i.e., the impact of the policy on population-based health or educational outcomes for children) (Tremper et al., 2010). For example, Bruns et al (2019) studied associations between modifiable and unmodifiable inner and outer context factors and state EBP implementation, finding that policy supports (e.g. interagency collaboration, investment in research centers) were more predictive of states that promoted use of EBPs.

Policy process implementation studies may additionally examine policy implementers’ perceptions of the acceptability and feasibility of various implementation strategies, including fidelity of implementation that could be used to enhance implementation as a whole. Implementation process studies can also shed light on how the design of a children’s mental health policy might need to be modified or tailored for a specific context. Experiments that test the effects of implementation strategies on policy implementation or policy outcomes are needed overall in the field of D&I, but are especially lacking in children’s mental health.

A review of the examples in Table 1 also suggests that applying psychological theories to D&I policy studies could expand the knowledge gained from these studies. For example, Stewart et al. (2018) used a Diffusion of Innovation Theory approach when examining the use of financial incentives by state mental health personnel to promote the use of EBPs. Although the data derived from this survey was useful, it might have had more impact if data had been collected based on the Unified Theory of Behavior Change (Fishbein, 1980; Jaccard et al., 1999; 2002). This well-respected social and health psychology theory could have identified what might motivate policymakers to champion the use of more effective financial incentives.

Crowley et al. (2018) concluded that context, trust, and partnerships were important for shaping the use of research findings from prevention science in the U.S. Congress. Thus, focusing on context, as suggested by ecological theory (Bronfenbrenner, 1977) and previously identified as key for large-scale EBP implementation efforts (Atkins et al., 2016; Chorpita et al., 2002; Regan et al., 2017), could be useful when approaching policymakers about the use of EBPs. Similarly, partnerships and trust when transmitting scientific evidence to policymakers argues for careful attention to team building, an important health care topic heavily investigated by industrial/organizational psychologists (Ferdandez & Grand, 2015). The importance of trust, reciprocity and team building was clearly shown in a report by Palinkas et al., (2015) when examining three effective models of research-practice-policy partnerships.

In addition to attention to context, understanding the drivers of behavior change, and the development of partnerships, message framing might be critical to t dissemination effectiveness studies focused on policymakers. Social psychology research has shown the power of appropriately-framed messages for influencing attitudes and behaviors (Tversky and Kahneman, 1986). In addition to “loss” versus “gain” frames, more recent work suggests that Regulatory Focus Theory (better outcomes versus maintaining the current state) is also important for influencing attitudes (Higgens, 1997; Mannetti et al., 2013). Message framing can be a powerful tool both when approaching policymakers and when implementing EBPs, even those focused on highly stigmatized individuals/topics (Bandara et al., 2020).

E. Applying a D&I Policy Typology to Health in All Policy Experiments Promoting Children’s Health and Wellness

This new proposed typology (Table 1) outlining four broad categories of policy D&I studies can provide a framework within which to assess the impact of the many health policies intended to support children’s mental, emotional, and behavioral health. The recently released NASEM report on Children and Youth (2019) cites the significance of health policies as “public health tools to protect populations against risks, and prevent disease or harm.” Health policies targeting children’s development are focused on building capacities of families, neighborhoods, and communities to create the conditions for children to thrive (NASEM, 2019; National Research Council and Institute of Medicine, 2000). Examples of policies that bolster parent capacity for responsive care include direct access to community-provided early childhood prevention services and parenting programs (e.g., Triple P Parenting Program, Early Head Start), or policies that target conditions affecting neighborhood contexts (e.g. access to affordable housing). Medicaid eligibility expansions under the ACA, for example, provided improved access to mental health care, lowered health care costs, and improved parental mental health (Morrow et al., 2016). The Earned Income Tax Credit and the Child Tax Credit reduced poverty for working families, and lifted an estimated 9.4 million people out of poverty in 2013—including 5 million children (Marr et al., 2015). These are but a few examples of health policies that affect children’s development by affecting their family or neighborhood contexts.

A series of state and local experiments designed to optimize children’s healthy development are happening across the country. These experiments are being spurred by redeployment of funding (from federal, foundation, and local sources), and are being shaped not by university-based researchers, but by neighborhoods, advocacy coalitions, and some state and local systems taking collective action. One example is the ‘Culture of Health’ initiative, funded by the Robert Wood Johnson Foundation and the RAND Corporation, which provides an “action framework for change” that communities can implement to improve the health and well-being of its citizens and address inequities in health. The focus is on community-driven change and cross-systems collaborations to target health, social, economic, physical, and environmental factors that impact individual and population-level health. Another example is The Center for Medicare and Medicaid Innovation’s (CMMI) Integrated Care for Kids (InCK) pilot grants. These are a local service delivery and state payment model pilots aimed at improving child health, reducing avoidable inpatient stays and out-of-home placements, and developing sustainable Alternative Payment Models (APMs). State Medicaid agencies and local partnership councils (which are a required partner) must collaborate to develop a plan that provides early identification and treatment of children with health-related needs across settings, care coordination and case management across physical and behavioral health, and child-and family-centered care. Eight cooperative agreements to seven states were funded in late 2019, and the seven-year projects launched in early 2020.

There are many more examples, but to further exemplify the potential of repurposing D&I methods towards examining the impact of children’s policy initiatives, we profile two efforts: New York State’s (NYS) value-based payment reform effort, and The Healthy Families, Healthy Neighborhoods Initiative in Columbus, Ohio.

New York State (NYS) Medicaid Redesign.

In 2015, the NYS Department of Health (NYS DOH) launched a redesign of its Medicaid program, committing to shift at least 80 percent of Medicaid managed care payments to value-based payments (VBP) by the year 2020. The initial focus of this VBP initiative was only on the adult population; however, in 2016, the United Children’s Hospital Fund, the Commonwealth Fund, and the Schuyler Center for Analysis and Advocacy convened with NYS DOH to develop a pediatric VBP model that included a stakeholder engagement framework (detailed for other states in a recent report, Achieving Payment Reform for Children through Medicaid and Stakeholder Collaboration;Brundage & Shearer, 2019a; Brundage & Shearer, 2019b) and was guided by an advisory group, which included stakeholders, experts, and providers from pediatrics, children’s behavioral health, managed care, child welfare, and children’s advocacy, representing a wide range of interests. The collaborating stakeholders created a quality measure set to guide the development of this VBP model (NYS Department of Health, 2019). This effort marked a sharp shift away from a longstanding focus on volume—to a focus on value; the value proposition for children’s health services posits that promoting optimal child health across the life course will lead to lower long-term health care utilization, and thus costs, by preventing chronic conditions in adulthood, and that savings and better outcomes within non-health sectors (education, child welfare, justice) will occur by improving healthy child development. This value proposition stands in stark contrast to adult health care, where value comes from reducing costs over a one- to-two-year timeframe, while maintaining or improving quality through better disease management.

To generate value in the pediatric payment model, the approach must support high-quality pediatric primary care by incentivizing improvements in quality, encouraging less fragmentation in service delivery, and fostering the adoption of relatively low-cost health and development promotion services to improve outcomes over the life of a child. An important byproduct of this effort was the creation of the First 1,000 Days of Medicaid initiative, led by NYS’ Governor Cuomo in partnership with United Hospital Fund, Schuyler Center, and the Children’s Agenda, which advocates for a pediatric health care model that incorporates behavioral health, addresses social determinants of health, and promotes health equity among all children and families. In October 2019, the Preventive Pediatric Care Clinical Advisory Work Group released its final report, outlining this model of pediatric population health, one that will require “practice transformation to address social determinants of health related to poverty, racism and other environmental influences,” and integrates behavioral health care while continuing to address biomedical factors. The report also outlined the current NYS programs critical to achieving this advanced pediatric primary health care model, including statewide home-visiting programs, data systems development to facilitate cross-system referrals, and promoting early literacy (NYS DOH, 2019).

In addition to this statewide initiative, a New York City (NYC)-based initiative, led by the Office of Population Health, NYC Health + Hospitals, called the Integrated Model for Parents and Children Together, or 3-2-1…IMPACT!, is using a two-generation, integrated model of health care across three disciplines (i.e. pediatrics, behavioral health, and women’s health) to support the health and well-being of young children and their families. This initiative focuses on integrated, two-generation care for young children ages 0-3, and targets adverse childhood experiences (ACES), acknowledging ACES well-documented impact young children’s development (New York City Health + Hospitals, 2020; Burke-Harris 2001; Bethell et al., 2017).

There are many ways in which policy D&I research could generate knowledge to improve the rollouts and impacts of these models of multi-generational care. For example, formative policy dissemination research could assess knowledge about policy change among the directors and senior staff of Medicaid managed care organizations in New York State, before and after implementation of the value-based care model. This information could help to inform dissemination strategies that target knowledge deficits that are often detrimental to policy implementation. Implementation process studies could assess perceptions of policy implementation among stakeholders at different levels, ranging from directors of Medicaid managed care organizations, to billing and compliance specialists, to health care delivery systems leaders, to families and to front-line providers. Information generated by such studies could inform the selection and tailoring of implementation strategies that could be deployed and potentially tested in future research.

Columbus, Ohio Healthy Neighborhoods, Healthy Families.

The Healthy Neighborhoods, Healthy Families Initiative (HNHF) in Columbus, Ohio is an example of another stakeholder-driven, collaborative, community population health effort to create positive health outcomes. In 2008, Columbus’ South Side neighborhood, which falls primarily south of Nationwide Children’s Hospital, had high levels of poverty and other socioeconomic challenges, including high housing vacancy rates, high unemployment, and poor youth outcomes. Nationwide Children’s Hospital convened neighborhood stakeholders from faith-based organizations, community development organizations, youth-serving nonprofits, and local public schools. Together, they identified and collaboratively addressed their most critical community needs, including affordable housing, education, safe and accessible neighborhoods, and workforce development—not traditional health care needs that hospitals attend to—but factors that drive child and family outcomes and health care costs.

Since the HNHF initiative was launched in 2008, improvements have been documented in many areas: better housing stock, expanded employment opportunities via workforce initiatives in the community (e.g. Goodwill Industries, and at Children’s Hospital), expanded educational opportunities (e.g. kindergarten readiness programs, mentoring and tutoring programs), safer and more accessible neighborhoods, expanded health and wellness programs; and improved quality of care in early childcare settings. The housing vacancy rate was reduced from 25% to below the community average of 6%, sales of owner-occupied homes increased 50%, and home sale prices increased by 22%. In addition to this improved housing stock (which promotes stability in youth education and family employment), youth participating in youth development programs have shown progress in emotional health and academic performance; the local high school graduation rate rose from 64% in 2013, to 79% in 2017. And, though homicide rates climbed in the surrounding City of Columbus, no reported homicides occurred in the South Side neighborhood in 2017 (Kelleher et al., 2018). In short, this initiative has moved Nationwide Children’s Hospital from purely treating disease in the children seeking treatment in their hospital— to treating the “community” as a whole.

Policy process implementation studies of this kind of initiative could shed light on how and why the initiative worked, and the barriers to which implementation strategies could be applied. This kind of information is important for both replicability as well as sustainability. Prior to replication of the HNFF initiative in another jurisdiction, it could be valuable to use a formative policy dissemination research approach to characterize health care system leaders’ knowledge about the social determinants of mental health, and attitudes about the role of their health care system in fostering community changes that help children and families thrive. This information could inform strategies for targeting dissemination of findings to different stakeholder groups (i.e., federal, state, or local policymakers, advocacy organizations, health plans, families) to cultivate support for collective action and increase the chances of successful implementation.

In addition to these state and local efforts, new federal policies are also offering opportunities for communities to think more creatively about ways to improve child and family outcomes by focusing not only on the treatment of disorders, but on promoting healthy development and preventing risks that jeopardize children’s development. For example, in 2018, Congress passed the Family First Prevention Services Act (FFPSA), which changed how states can utilize their Title IV-E foster care funds. Title IV-E funds previously could be used only to cover costs of foster care maintenance, administrative expenses, and adoption and kinship guardianship assistance. Now, states have the option to use these funds to establish prevention programs for foster care youth, choosing from a menu of approved, evidence-based, trauma-informed prevention services. This is a major shift demonstrating federal attention to child health promotion and prevention.

In addition to passage of the FFPSA (and its implementation in states by October 2020), the Children’s Bureau within the Administration for Children, Youth, and Families, the U.S. Department of Health and Human Services, recently signaled their interest in pushing prevention to the forefront in child welfare, funding nine projects under the Community Collaborations to Strengthen and Preserve Families program. This shift in focus from intervention to promotion, through support for the broader ecological systems affecting families and children, may signal a critical tipping point. This is an example of a “health in all policies” initiative that moves the locus of intervention from the individual to the collective.

These kinds of initiatives—in states, hospital systems, health plans, and at the federal level—open a space within which D&I studies could thrive. Examples include studies (mixed method and qualitative) about policymakers’ decisional processes during rollouts of these initiatives and other stakeholders involved in the rollouts. Barriers and facilitators to the implementation of these policies could be studied. Obtaining feedback from policymakers on their attitudes, beliefs, or expectations related to the policy could provide knowledge relevant to dissemination of evidence to them. Identification of markers of successful implementation of the policy, and measurement of stages of implementation (akin to Saldana’s Stages of Implementation Change; Saldana 2014) could be developed. Because monitoring implementation of a policy requires attention to fidelity as well as stages of implementation (similar to installing EBPs), markers of fidelity to policy implementation and impact could be developed and used to assess whether high fidelity leads to greater impact. In addition, development of knowledge management systems to track policy implementation could also be important in assessing the quality and fidelity of policy rollouts. Finally, a range of implementation strategies could be developed and tested to assess the most efficient and effective ways policies can attain broad population-level impact.

The initiatives described above are only partial examples of the many state and local health system reconfigurations underway aimed at shifting the dominant model of mental health services from a “wait to fail” approach to a proactive, upstream, cross-system, and highly-contextualized process that acknowledges neurodevelopmental, social, economic, and community factors as all being critical to children’s healthy development. A new national infrastructure—a network and learning community called All Children Thrive (ACT)— provides a potential mechanism for states and localities to learn from each other in their efforts to transform care for children. ACT’s ambitious goal is to build a national movement for this transformed system of children’s health care by connecting communities across the country to share partnership models, experiences in developing these transformed systems, and importantly, data, needed to improve young children’s development (All Children Thrive, 2020).

F. Conclusion

Despite decades of studies documenting effective services to prevent and treat mental, emotional, and behavioral problems in children, the prevalence of depression and anxiety in youth has increased (Bitsko et al., 2018) as have rates of suicide, which climbed 56% between 2007 and 2017 for youth ages 10-24 (Curtin & Heron 2019), psychiatric hospitalizations (McDermott et al., 2017), and risky behaviors (Kann et al., 2018). The response to this from NIH and from the academic psychological research community has been to herald the idea of implementing, disseminating, and scaling evidence-based interventions to increase public health impact. Yet D&I studies in children’s mental health are still small in number, and those that exist have encountered numerous problems related to the challenges of putting new practices into poorly-understood and highly-complex community contexts. Even when services are implemented with fidelity, social, economic, and geographic factors within communities exert powerful influences on children’s development, and easily undermine the intended effects of new programs.

The public health impact of the psychological knowledge base about children’s mental health and services to address it has yet to be realized. To ignore broad policy-level contextual factors in the hope that an effective and generally discrete psychosocial program will be fully adopted and have meaningful impact is naive, and perhaps grandiose. The current paradigm of implementing psychosocial treatments or practices designed to address specific psychological conditions and developed for delivery in treatment settings will not solve the bigger problems thwarting children’s healthy development. Nor will it address the moral imperative to apply psychological findings to positively impact public health. Policies and their consequent funding streams are, as the Society for Prevention Research says, a “macro factor” likely to drive the scaling and sustainability of EBPs, and therefore likely to increase public health impact (Weaver and DeRosier 2019; Fagan et al., 2019).

Although there have been historical examples of broad implementation of such policies in the 1960’s (e.g., War on Poverty, Head Start), D&I scientific methods were not available then. The emergence at local, state, and federal levels of numerous stakeholder-led policy “experiments” that foreground attention to the contexts for children’s healthy development (i.e., employment, housing, health insurance coverage, tax credits, value-based purchasing) signals a turning point for the application of psychological knowledge to maximize public health impact. There is a rare opportunity now, in the post-COVID-19 era, to study health policy experiments with respect to their impact on children’s health and mental health, apply rigorous system science and mixed methods, and create tools and frameworks that can catalyze change in other communities. Many health experiments across the country reflect a “health in all policies” approach, and they open the door for creative thinking about how to attend to social determinants while promoting child and family health and mental health through broad-based, community-led efforts. Importantly, many of these health policy experiments are happening within communities of concentrated disadvantage (Biglan et al., 2020). In the post-COVID-19 era, a national, coordinated “Marshall Plan” for children and families may be needed to “build back better” an improved health and mental health system (Hoagwood & Kelleher, 2020). The alignment of D&I scientific methods with psychological science and with health policies focused on helping children and families thrive may be an idea whose time has come.

Public Health Significance:

The prevalence of mental health problems among children remains unacceptably high. Communities, cities, states, and some federal agencies are building “health in all policies” initiatives that address broad familial, social, and economic factors known to affect children’s healthy development. These initiatives offer a rare opportunity to repurpose D&I science and shift it from a primary focus on evidence-based practice implementation, to a focus on policy dissemination and implementation.

Biography