Realizing Population-Level Improvements for All Children’s Cognitive, Affective, and Behavioral Health

Brown, C. Hendricks; Beardslee, William R.

doi:10.1016/j.amepre.2016.07.017

Cited by 6 publications

(11 citation statements)

References 27 publications

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“…Broadly writ, this transdiagnostic approach aims to prevent early markers of dysregulation (i.e., vulnerabilities) from worsening to the point of persistent and pervasive patterns that impede adaptive functioning (i.e., syndromes). This is consistent with National Academy of Medicine (NAM) recommendations for prevention: emphasizing risk reduction and delay of onset, which is associated with increased future severity and public health burden (Brown & Beardslee, 2016). NAM's approach has reduced population attributable risk for physical disease, but uptake has been slower for mental disorders (Brown & Beardslee, 2016).…”

Section: Transdiagnostic Risk Identificationsupporting

confidence: 73%

Future Directions for Early Childhood Prevention of Mental Disorders: A Road Map to Mental Health, Earlier

Wakschlag

Roberts²,

Flynn

et al. 2019

Journal of Clinical Child & Adolescent Psychology

101

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Mental disorders are the predominant chronic diseases of youth, with substantial lifespan morbidity and mortality. A wealth of evidence demonstrates that the neurodevelopmental roots of common mental health problems are present in early childhood. Unfortunately, this has not been translated to systematic strategies for improving population level mental health at this most malleable neurodevelopmental period. We lay out a translational Mental Health, Earlier roadmap as a key future direction for prevention of mental disorder. This paradigm shift aims to reduce population attributable risk of mental disorder emanating from early life, by preventing, attenuating or delaying onset/course of chronic psychopathology via the promotion of selfregulation in early childhood within large scale healthcare delivery systems. The Earlier Pillar

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Section: Transdiagnostic Risk Identificationsupporting

confidence: 73%

Future Directions for Early Childhood Prevention of Mental Disorders: A Road Map to Mental Health, Earlier

Wakschlag

Roberts²,

Flynn

et al. 2019

Journal of Clinical Child & Adolescent Psychology

101

View full text Add to dashboard Cite

show abstract

“…If testing of this new scale-out requires the full empirical evaluation that would be required for establishing an EBI, this would be exceptionally costly, time consuming, and would delay implementation, especially to populations underrepresented in scientific trials or in settings where its delivery could reasonably produce benefit. Indeed, if we can legitimately borrow strength from previous studies and a modest amount of empirical evidence, this could accelerate and expand benefit to populations that have experienced health disparities that might never be included in a rigorous randomized effectiveness trial [ 6 ].…”

Section: Defining a New Concept For Implementation—“scaling-out”mentioning

confidence: 99%

“…Next is the degree of uptake by the target population (e.g., the reach into the target community and the degree of exposure to, or usage of the clinical/preventive intervention). Following this in sequence are the proximal behavioral outcomes (e.g., changes in parent-child communication, medication adherence, and selection of evidence-based prevention programs that match community needs) and the ultimate health outcomes (e.g., reduced HIV infections for PrEP or parenting skills, children’s cognitive, affective, or behavioral health for parenting programs) [ 6 ]. The Greek letters in this figure indicate the strength of relationships between the steps in this mediational sequence, and the Roman letters represent mean levels achieved for each of these.…”

Section: Evaluation Options For Scaling-outmentioning

confidence: 99%

“Scaling-out” evidence-based interventions to new populations or new health care delivery systems

et al. 2017

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BackgroundImplementing treatments and interventions with demonstrated effectiveness is critical for improving patient health outcomes at a reduced cost. When an evidence-based intervention (EBI) is implemented with fidelity in a setting that is very similar to the setting wherein it was previously found to be effective, it is reasonable to anticipate similar benefits of that EBI. However, one goal of implementation science is to expand the use of EBIs as broadly as is feasible and appropriate in order to foster the greatest public health impact. When implementing an EBI in a novel setting, or targeting novel populations, one must consider whether there is sufficient justification that the EBI would have similar benefits to those found in earlier trials.DiscussionIn this paper, we introduce a new concept for implementation called “scaling-out” when EBIs are adapted either to new populations or new delivery systems, or both. Using existing external validity theories and multilevel mediation modeling, we provide a logical framework for determining what new empirical evidence is required for an intervention to retain its evidence-based standard in this new context. The motivating questions are whether scale-out can reasonably be expected to produce population-level effectiveness as found in previous studies, and what additional empirical evaluations would be necessary to test for this short of an entirely new effectiveness trial. We present evaluation options for assessing whether scaling-out results in the ultimate health outcome of interest.ConclusionIn scaling to health or service delivery systems or population/community contexts that are different from the setting where the EBI was originally tested, there are situations where a shorter timeframe of translation is possible. We argue that implementation of an EBI in a moderately different setting or with a different population can sometimes “borrow strength” from evidence of impact in a prior effectiveness trial. The collection of additional empirical data is deemed necessary by the nature and degree of adaptations to the EBI and the context. Our argument in this paper is conceptual, and we propose formal empirical tests of mediational equivalence in a follow-up paper.

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“…In the current paper, the MAPS IV Task Force took a public systems approach to scaling up EBIs because EBIs must be widely used to improve the health and well-being of the population and to reduce health disparities nationwide, and these goals are best achieved via public systems (Brown and Beardslee 2016). As shown in Table 1, public systems are charged and funded by the government to improve the behavioral health problems that EBIs target.…”

Section: The Promise Of Public Systems For Scaling Up Ebismentioning

confidence: 99%

Scaling up Evidence-Based Interventions in US Public Systems to Prevent Behavioral Health Problems: Challenges and Opportunities

et al. 2019

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A number of programs, policies, and practices have been tested using rigorous scientific methods and shown to prevent behavioral health problems (Catalano et al., Lancet 379:1653–1664, 2012; National Research Council and Institute of Medicine, 2009). Yet these evidence-based interventions (EBIs) are not widely used in public systems, and they have limited reach (Glasgow et al., American Journal of Public Health 102:1274–1281, 2012; National Research Council and Institute of Medicine 2009; Prinz and Sanders, Clinical Psychology Review 27:739–749, 2007). To address this challenge and improve public health and well-being at a population level, the Society for Prevention Research (SPR) formed the Mapping Advances in Prevention Science (MAPS) IV Translation Research Task Force, which considered ways to scale up EBIs in five public systems: behavioral health, child welfare, education, juvenile justice, and public health. After reviewing other efforts to scale up EBIs in public systems, a common set of factors were identified as affecting scale-up in all five systems. The most important factor was the degree to which these systems enacted public policies (i.e., statutes, regulations, and guidance) requiring or recommending EBIs and provided public funds for EBIs. Across systems, other facilitators of scale-up were creating EBIs that are ready for scale-up, public awareness of and support for EBIs, community engagement and capacity to implement EBIs, leadership support for EBIs, a skilled workforce capable of delivering EBIs, and data monitoring and evaluation capacity. It was concluded that the following actions are needed to significantly increase EBI scale-up in public systems: (1) provide more public policies and funding to support the creation, testing, and scaling up of EBIs; (2) develop and evaluate specific frameworks that address systems level barriers impeding EBI scale-up; and (3) promote public support for EBIs, community capacity to implement EBIs at scale, and partnerships between community stakeholders, policy makers, practitioners, and scientists within and across systems.

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Realizing Population-Level Improvements for All Children’s Cognitive, Affective, and Behavioral Health

Cited by 6 publications

References 27 publications

Future Directions for Early Childhood Prevention of Mental Disorders: A Road Map to Mental Health, Earlier

Future Directions for Early Childhood Prevention of Mental Disorders: A Road Map to Mental Health, Earlier

“Scaling-out” evidence-based interventions to new populations or new health care delivery systems

Scaling up Evidence-Based Interventions in US Public Systems to Prevent Behavioral Health Problems: Challenges and Opportunities

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