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

Lauren S. Wakschlag, Megan Y. Roberts, Rachel M. Flynn, Justin D. Smith, Sheila Krogh-Jespersen, Aaron J. Kaat, Larry Gray, John Walkup, Bradley S. Marino, Elizabeth S. Norton & Matthew M. Davis

To cite this article: Lauren S. Wakschlag, Megan Y. Roberts, Rachel M. Flynn, Justin D. Smith, Sheila Krogh-Jespersen, Aaron J. Kaat, Larry Gray, John Walkup, Bradley S. Marino, Elizabeth S. Norton & Matthew M. Davis (2019) Future Directions for Early Childhood Prevention of Mental Disorders: A Road Map to Mental Health, Earlier, Journal of Clinical Child & Adolescent Psychology, 48:3, 539-554, DOI: 10.1080/15374416.2018.1561296

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Journal of Clinical Child & Adolescent Psychology, 48(3), 539–554, 2019 Copyright © Society of Clinical Child & Adolescent Psychology

ISSN: 1537-4416 print/1537-4424 online



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

Lauren S. Wakschlag

Department of Medical Social Sciences, Feinberg School of Medicine & Institute for Innovations in Developmental Sciences, Northwestern University

Megan Y. Roberts

Department of Communication Sciences and Disorders, School of Communication & Institute for Innovations in Developmental Sciences, Northwestern University

Rachel M. Flynn

Department of Medical Social Sciences, Feinberg School of Medicine & Institute for Innovations in Developmental Sciences, Northwestern University

Justin D. Smith

Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine & Institute for Innovations in Developmental Sciences, Northwestern University

Sheila Krogh-Jespersen and Aaron J. Kaat

Department of Medical Social Sciences, Feinberg School of Medicine & Institute for Innovations in Developmental Sciences, Northwestern University

Larry Gray

Department of Pediatrics, Feinberg School of Medicine & Institute for Innovations in Developmental Sciences, Northwestern University and Ann & Robert H. Lurie Children’s Hospital of Chicago

John Walkup

Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine & Institute for Innovations in Developmental Sciences, Northwestern University

Bradley S. Marino

Department of Pediatrics, Feinberg School of Medicine & Institute for Innovations in Developmental Sciences, Northwestern University and Ann & Robert H. Lurie Children’s Hospital of Chicago

Correspondence should be addressed to Lauren S. Wakschlag, Northwestern University, Department of Medical Social Sciences, 633 N. St. Clair, 19th Floor, Chicago, IL, 60611. E-mail:

Color versions of one or more of the figures in the article can be found online at .


Elizabeth S. Norton

Department of Communication Sciences and Disorders, School of Communication & Institute for Innovations in Developmental Sciences, Northwestern University

Matthew M. Davis

Department of Pediatrics, Feinberg School of Medicine & Institute for Innovations in Developmental Sciences, Northwestern University and Ann & Robert H. Lurie Children’s Hospital of Chicago

Mental disorders are the predominant chronic diseases of youth, with substantial life span 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 road map 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 self-regulation in early childhood within large-scale health care delivery systems. The Earlier Pillar rests on a “science of when to worry” that (a) optimizes clinical assessment methods for characterizing probabilistic clinical risk beginning in infancy via deliberate incorporation of neurodevelopmental heterogeneity, and (b) universal primary- care-based screening targeting patterns of dysregulated irritability as a robust transdiagnostic marker of vulnerability to life span mental health problems. The core of the Healthier Pillar is provision of low-intensity selective intervention promoting self-regulation for young children with developmentally atypical patterns of irritability within an implementation science framework in pediatric primary care to ensure highest population impact and sustainability. These Mental Health, Earlier strategies hold much promise for transforming clinical outlooks and ensuring young children’s mental health and well-being in a manner that reverberates throughout the life span.

Mental disorders are the predominant chronic diseases of youth (7%–29% of the population), accounting for greater life span morbidity and mortality than physical diseases (Insel, 2009; Merikangas et al., 2010; Pennap et al., 2018). Mental health and disorder are neurodeve- lopmental in nature, with the seeds of vulnerability and resilience planted in early life (Mittal & Wakschlag,2017; Pine & Fox, 2015). Thus, the unfolding clinical sequence of mental disorder flows from vulnerability to prodromal symptoms to frank disorder with clinically recognizable symptoms.

Prevention offers a compelling opportunity to reduce the public health burden of mental disorder by mitigating risks and promoting mental health before disorders are present (Casey, Oliveri, & Insel, 2014; Uddin & Karlsgodt, 2018). For the common, preventable mental disorders of childhood, this points to prevention in early childhood. Neurodevelopmental risk factors are evident as early as infancy, and common clinical syndromes are identifiable by preschool age (Dougherty et al., 2015). Promotion of early childhood mental health, particularly reductions in dysregulation, may have a profound impact on overall health, disease, and human capital across the

life span. Our framework centers on irritability, a robust indicator of dysregulation and transdiagnostic mental health risk marker identifiable as early as the 1st year of life. For example, preventing early childhood dysre- gulation results in life span improvements in health, and costs savings of 13% per year in service utilization (Knudsen, Heckman, Cameron, & Shonkoff, 2006).

Considering these disparate bodies of work together underscores the tremendous promise for ameliorating the significant population attributable risk for common, preven- table emotional and behavioral disorders of childhood (e.g., depression, disruptive behavior) emanating from early dys- regulation during the period of greatest neurodevelopmen- tal plasticity. Regrettably, this science base has not translated into concomitant investments in comprehensive, population-level early-life prevention of mental disorders and its impact on health care cost containment (Boat, 2015; Shonkoff, 2003). The key objective of this article is to set an agenda for closing this science-to-application gap and driving transformative change.

We propose a Mental Health, Earlier road map as a central future direction for mental health prevention by harnessing transdisciplinary strengths from developmental,

clinical, population, and implementation science to catalyze a long overdue paradigm shift in the mental health field.

Pillar I: Earlier calls for identification of mental health risk as soon as possible in early childhood using reliable clinical risk thresholds, which capture those children at increased risk for mental health problems in childhood and beyond. This rests on a “science of when to worry,” grounded in an inte- grative and theoretically- and empirically-derived develop- mental specification framework (Wakschlag et al., 2018; Wakschlag, Tolan, & Leventhal, 2010). Earlier requires a shift from a categorically based diagnostic process to one that is transdiagnostic, dimensional, probabilistic, and grounded in normal-versus-abnormal differentiation of neurodevelopment.

Pillar II: Healthier draws on the foundation of the Earlierpillar to drive a shift from the current reactive, treatment- focused, clinic-based approach to a preemptive and population- based early-life mental health selective prevention program. To actualize this, we propose to capitalize on the centrality and effectiveness of pediatric primary care medical homes (PCMH) to enact a population-based strategy for mental health promo- tion, drawing on advances in health information technology, prevention science, and implementation science (Medical Home Initiatives Advisory Committee, 2002). These strategic priorities will drive actualization of the pivot needed to achieveMental Health, Earlier. We provide the empirical evidence undergirding this approach and specify the critical steps toward realization.


Ironically, one of the most significant obstacles to scalable clinical and population health applications in early life has been human development itself. The complexities of develop- ment continue to be viewed, scientifically and clinically, as a major barrier to early mental health prevention. These “chal- lenging” developmental features include the rapid pace of developmental changes and skill acquisition (measured in weeks and months, not years), and extensive normative varia- tion (including transient self-correcting perturbations). These challenges are further amplified by the nondevelopmental nat- ure of current nosologic systems. Traditional mental health syndromes are conceptualized as downward extensions of adult or adolescent phenomenology. Further, there is substantial overlap of normative misbehavior and many clinical symptoms (Wakschlag, Leventhal, & Thomas, 2007). The predominant response to such challenges is clinical approaches that erase developmental “noise” and favor entrenched “they’ll grow out of it” myths (Dirks, De Los Reyes, Briggs-Gowan, Cella, & Wakschlag, 2012; Luby, 2012).

Central to the Earlier pillar is the notion of embracing,rather than erasing, developmental variation to achieve ear- lier, accurate identification of mental health risk. Figure 1provides a heuristic illustration of typical and atypical pat- terns of irritability across early childhood in relation to probabilistic risk of mental health or disorder. Its fundamen- tal premise is that achievement of self-regulatory compe- tence vs. enduring dysregulation in early childhood is a key set-point for resilience or vulnerability to mental health problems across the life span. This is because dynamic biologic, social, and ecological influences profoundly shape these patterns well beyond early childhood. Thus, Earlier is not a deterministic framework. Rather, as Shonkoff and colleagues have posited in their landmark work, self-(dys) regulation in early childhood sets a “sturdy” or “fragile”foundation for ensuing learning, experience, and relation- ships (Phillips & Shonkoff, 2000). Although not all irritable young children develop mental health problems, enduring patterns of early irritability exponentially increase the risk that they will. Nor does Earlier imply that the improved developmental precision of a science of when to worry will identify all individuals who will have mental health pro- blems by the time they are 5 years old. Rather, it leverages a strong science base to identify the substantial group of children who have or at are high risk for impairing mental health problems due to difficulty managing emotions and behavior with concomitant impact on health and environ- mental experience in order to alter mental health trajectories at the population level.

Embracing Development Within and Across Individuals and Time

The Mental Health, Earlier road map proposes that future research must rest on a developmental specification approach, pinpointing features that enhance normal/abnormal distinctions (Wakschlag et al., 2018). Developmental specification encom- passes rigorous accounting for aspects of individual differences and developmental patterning that differentiate normative var- iation from atypical manifestations. For example, many fea- tures of the brain reach essentially adultlike levels very early in childhood, e.g., folding patterns (gyrification), and cortical thickness, which reaches 97% of adult levels by around age 2 (Grayson & Fair, 2017; Lyall et al., 2015). While challenging to account for this rapid pace, the crux of this science of when to worry is built by empirically defining atypicality as deviation from age-graded normative patterns at both brain and beha- vioral levels (Wakschlag et al., 2018). To date, developmental specification has largely been applied to young children’s dis- ruptive behavior and is more mature for behavioral rather than brain-based markers, but this framework is equally relevant for other common emotional and behavioral syndromes (Dougherty et al., 2015).




Probabilistic Outlook for Mental Health and Disorder


Developmentally abnormal range of irritability

Developmentally normal range of irritability

Early Childhood

Optimal Mental Health

Childhood & Beyond

FIGURE 1 Earlier pillar: Harnessing developmental variation in irritability patterns to forecast life span clinical risk. Note. Trajectories shaped by dynamic biologic, social, and ecological influences.

Distinguishing Normative (Mis)Behavior From Clinical Markers

Actualizing developmentally-generated clinical thresholds requires a reorientation from traditional symptom-based mod- els (present/absent) to more fine-grained distinction of fea- tures of behavior that mark atypicality across a spectrum within the developmental context of early childhood (Kaat et al., 2018; Wakschlag et al., 2007). These key features of behavior that are most informative for the normal:abnormal distinction in early childhood are (a) quality, (b) developmen- tally expectable and matched to context, (c) dimensional and narrow-band, and (d) regularity of occurrence.


Quality of behavior reflects the extent to which it is modu- lated and responsive to environmental intervention and distin- guishes typical from atypical manifestations (Wakschlag et al.,2008). For example, high and persistent irritability (i.e., tendency to respond to frustration with intense, easily elicited, and dysre- gulated anger and/or chronic negative mood) is perhaps the best developmental and transdiagnostic indicator of a host of psy- chopathologies (Biedzio & Wakschlag, in press; Vidal-Ribas, Brotman, Valdivieso, Leibenluft, & Stringaris, 2016). Yet one of the foremost expressions of irritability in children is temper tantrums, which occur regularly in the vast majority of young children and are a core feature of several Diagnostic and Statistical Manual of Mental Disorders (DSM) disorders

(Wakschlag et al., 2012). Dysregulated tantrum features include destructiveness, resistance to efforts to help calm, and duration lasting more than 5 min (Belden, Thompson, & Luby, 2008; Wakschlag et al., 2012). Although tantrums are endemic to early childhood, dysregulated tantrums occur regularly in fewer than 10% of preschoolers, making them excellent, easily detectable risk markers. This pattern has been demonstrated and replicated in two independent samples of more than 3,000 sociodemogra- phically diverse preschoolers (Wakschlag et al., 2018).

Developmentally Expectable and Matched to Context

Although traditional nosologic systems are typically con- text-agnostic (Dirks et al., 2012), the extent to which behavior is developmentally expectable and matched to context is clinically differentiating for young children (Buss, 2011; Wakschlag et al., 2007). For example, dysregulated fear exhibited in nonthreatening versus threatening contexts pre- dicts which preschoolers will develop anxiety symptoms (Buss, 2011). Further, preschoolers who do not display con- textually matched regulation of behavior are at heightened risk of clinical problems (Petitclerc et al., 2015).

Dimensional, Narrow-Band Approaches

Dimensional, narrow-band approaches are a cornerstone of characterizing developmental variation. These assume that clinical patterns cannot be defined by a single extreme

Mental Health Problems

threshold but rather are expressed along a continuum ran- ging from normative variation to increasing probabilistic risk. Continuous approaches have long been a mainstay within the developmental psychopathology approach (Achenbach, 1997). However, these have typically relied on counts of problem behaviors rather than characterization along an ordered spectrum from normative to problematic in a developmentally informed manner. We developed the Multidimensional Assessment Profile for Disruptive Behavior (MAP-DB) dimensional approach to assess the normal-to-abnormal spectrum of preschool behavior via parent report, with atypical behaviors defined as deviation from normative variation within a developmental period (Nichols et al., 2014; Wakschlag et al., 2014). Severity of each item is weighted psychometrically using item response theory. The MAP-DB scale has psychometrically characterized dimensional spectra for irritability (“Temper Loss”), noncompliance, aggression, callous behavior (“Low Concern for Others”), and punishment insensitivity. These spectra differentiate those behaviors that occur in the majority of young children and are severe by virtue of frequent occurrence from those that rarely occur and mark dysregulation at lower frequencies.

A burgeoning body of work demonstrates the meth- odologic, clinical, and mechanistic utility of this dimen- sional approach (Briggs-Gowan et al., 2014; Grabell et al., 2017; Kaat et al., 2018). For example, we have shown that the fear processing deficits widely estab- lished as a mechanism of callousness and psychopathy are evident and specific as early as preschool age (White et al., 2016). Using the MAP-DB Temper Loss scale, we have also demonstrated that probabilistic risk for clinical disorder occurs at levels of irritability fall- ing within the normal range on traditional checklist ratings (Wakschlag et al., 2015). This same irritability spectrum differentiates variations in recruitment of pre- frontal resources during frustration for impaired versus nonimpaired irritable children (Grabell et al., 2017). Dimensional approaches are particularly well suited for capturing the rapid developmental change of early childhood because they capture a fuller spectrum of behavioral variation, not merely behaviors at the extremes.

Regularity of Occurrence

Regularity of occurrence has also proven clinically informative in young children. Traditional symptom thresholds have been defined via subjective frequency (e.g., “often loses temper”). These have also been “one size fits all,” treating all behaviors identically without regard to developmental stage. As a result, clinicians assessing young children have long been vexed by the question, “How often is too often?” Such reliance on subjective judgement about commonly occurring

behaviors creates a high risk of overidentification. The MAP-DB was designed to address this issue via an objective frequency scale (from never in past month tomany times per day) to psychometrically derive frequency thresholds demarcating abnormality in a manner sensitive to the extensive developmental variation of this period. Data from two large community samples of diverse pre- schoolers indicate that misbehavior is common (i.e., most young children do it) but not predominant (Wakschlag et al., 2018). Clinical risk varies based on the type of behavior although both high-frequency normative misbe- haviors and pathognomonic indicators of dysregulation are key to sensitive and specific early identification (Wiggins et al., 2018). For example, normative misbeha- viors become abnormal only if they occur very frequently (e.g., daily tantrums). In contrast, dysregulated tantrums (e.g., destructive) are pathognomonic, occur much less commonly, and are abnormal at lower frequencies. Rigorous psychometric analysis is necessary to specify thresholds of atypicality across early childhood (Biedzio & Wakschlag, in press). The absence of developmentally tuned thresholds impedes identification at the earliest phase of the clinical sequence.

Development Matters

A fundamental principle of Mental Health, Earlier is that earlier identification requires a move away from static assess- ments that treat development as random noise (e.g., the DSMexclusion of children under six for its key irritability related syndrome, Disruptive Mood Dysregulation Disorder). We recognize the challenge of doing so as methods for detecting within-person change often require a very large change to be greater than measurement error, or require multiple assessment occasions (de Vet et al., 2006; Lin et al., 2016). Natural devel- opmental processes compound this problem, as change is inher- ent. Further, any developmentally varying threshold for diagnostic status or intervention effect requires a difference in the change over time distinguishable from expectable variation. Nonetheless, state-of-the-art science enables such differentia- tion once development is deliberately taken into account.

We posit that accounting for developmental change over time (both within and across individuals) will substantially improve reliability of risk estimation. A repeated measures approach is critical to ensuring sufficiently stable patterns for probablistic risk estimates. When optimized, this type of longitudinal approach will provide empirical parameters (e.g., how many time points, at what ages, probability estimates that a child will develop impairing problems). Multiple repeated assessments allow for evaluation of two types of stability and change over time: (a) average level of behavior (i.e., an intercept) and/or (b) individual trajectory (i.e., slope), which may have differential predictive utility (Wakschlag et al., 2015).



Although interindividual differences are fairly stable, even in very young children, as they reflect relative tenden- cies, intraindividual instability is developmentally norma- tive (Bornstein, 2014). This is particularly true for problem behaviors; changes in expression and frequency of occur- rence manifest over relatively short time frames. For exam- ple, the majority of 17-month-olds who frequently exhibit problem behavior no longer do so 1 year later (change in the intercept), and vice versa (Baillargeon et al., 2007). Using MAP-DB dimensional characterization, we have also shown that about 33% of preschool children vary substantially in their irritability profiles over time, moving across typical and atypical levels (Wakschlag et al., 2015). Accounting for such intrapersonal longitudinal variation improves clinical prediction (Wakschlag et al., 2015; Whalen et al., 2016). For example, less than 30% of beha- viorally inhibited toddlers remain so across early child- hood, with stability over time increasing probabilistic risk of anxiety disorder (Henderson, Pine, & Fox, 2015). Requisite frequency of repeated assessment should be somewhat regular (e.g., during well-child visits), with interim assessments conditioned on occurrence of life events (e.g., birth of a sibling) and milestone acquisition (e.g., capacity to say “no”) that may cause transient devel- opment perturbations (Biedzio & Wakschlag, in press).

Transdiagnostic Risk Identification

The Mental Health, Earlier road map posits the need for transdiagnostic approaches at the earliest identifiable vul- nerability phase of the pediatric clinical sequence. Of note, such vulnerability begins well before birth; mental health prevention that begins during or prior to the prenatal period is a key future direction (Tremblay & Japel, 2003; Wakschlag et al., 2018). Broadly writ, this transdiagnostic approach aims to prevent early markers of dysregulation (i.e., vulnerabilities) from worsening to the point of persis- tent and pervasive patterns that impede adaptive function- ing (i.e., syndromes). This is consistent with National Academy of Medicine (NAM) recommendations for pre- vention: emphasizing risk reduction and delay of onset, which is associated with increased future severity and pub- lic health burden (Brown & Beardslee, 2016). NAM’s approach has reduced population attributable risk for phy- sical disease, but uptake has been slower for mental dis- orders (Brown & Beardslee, 2016).

Traditional diagnostically oriented approaches (e.g., theDSM) have been widely validated for common mood and dis- ruptive syndromes in preschoolers. Indeed, of the approxi- mately 20% of children with mental health problems, a majority of these problems have roots in early childhood (Dougherty et al., 2015; Pennap et al., 2018). Most children exhibiting mental health problems by preschool age have had

enduring problems with dysregulation, suggesting that negative cascades impacting child and family functioning are already entrenched (Tremblay & Japel, 2003). However, there has been reluctance to apply a clinical lens at younger ages. This impeded validation of preschool psychopathology syndromes for dec- ades, and now constrains a shift to earlier emphasis on mental health risk detection in infancy (Task Force on Research Diagnostic Criteria, 2003; Wakschlag et al., 2007). This is most unfortunate, given evidence that dysregulation as early as the 1st year of life (e.g., excessive irritability) is linked to increased risk of disruptive behavior and biomarkers for psy- chopathology risk (Hemmi, Wolke, & Schneider, 2011; Hyde, O’Callaghan, Bor, Williams, & Najman, 2012). It is also at odds with neurodevelopmental understandings of the dynamic unfolding of psychopathological patterns, which are morefluid and less discrete than the bounds of current nosologies and emerge far earlier than traditional symptom-based approaches can detect (McGorry & Nelson, 2016).

There are cogent arguments for adopting the Mental Health, Earlier risk-oriented, transdiagnostic approach. First, in very young children, mental health risk is best captured by well-defined, cross-cutting problems in self- regulation rather than narrowly defined syndromes. Second, it is not feasible to do large-scale screening targeting risk factors for multiple distinct syndromes. Early dysregula- tion, in contrast, is a salient target that is a prominent parental concern (Brown, Raglin Bignall, & Ammerman,2018). Targeting shared elements implicated in common pediatric problems—rather than discrete mechanisms spe- cific to a particular syndrome—will have highest popula- tion-level impact (Smith, Montaño, Dishion, Shaw, & Wilson, 2015; Walkup, Mathews, & Green, 2017).

Irritability as Candidate Marker

Mental Health, Earlier posits that irritability (e.g., dysregu- lated tantrums) is the optimal early life transdiagnostic marker for large-scale screening of risk for common emotional and behavioral syndromes. Deficits in self-regulation forecast men- tal health risk. Self-regulation is a multifaceted construct including executive function, effortful and self-control, and emotional and behavioral regulation, which is not feasibly reducible to a brief pediatric screening assessment (Murray, Rosanbalm, Christopoulous, & Hamouidi, 2015; Raver, 2013). In contract, irritability is one of the most prominent and easily observable aspects of self-regulatory problems that compose mental health risk (Heckman, Pinto, & Savelyev, 2013; Moffitt, Poulton, & Caspi, 2013). It has robust transdiagnostic predic- tive utility for common disruptive and mood problems (e.g., oppositional defiant disorder, attention deficit/hyperactivity dis- order, depression, and anxiety) across the life span (Vidal-Ribas et al., 2016). Finally, its salient features (e.g., outbursts, moodi- ness) encompass normative misbehaviors of early childhood

that are easily identified with well-developed measurement methods, particularly its discrete behavioral expression (i.e., tantrums; Wakschlag et al., 2012).

As just highlighted, applying modern measurement science methods with the MAP-DB, we have demonstrated that irrit- ability can be reliably measured along a normal-to-abnormal spectrum as early as 12 months of age, using survey methods in a manner that is informative for clinical and mechanistic iden- tification (Wakschlag et al., 2018). Thus, we posit irritability as a reliable risk marker of vulnerability to mental health pro- blems, beginning by 12 months of age. This is younger than the age targeted by standard early childhood prevention and inter- vention programs (typically at preschool age, with age 2 years as the lower bound; Comer, Chow, Chan, Cooper, & Wilson,2013; Perrin, Sheldrick, McMenamy, Henson, & Carter, 2014).

Of note, we expect that even this lower developmental bound (age 12 months) also likely reflects a methodologic artifact, which is already dissipating as clinically informed neurodevelopmental frameworks are increasingly applied to the 1st year of life (Bosl, Tager-Flusberg, & Nelson, 2018; Hay, 2017; Miller, Iosif, Young, Hill, & Ozonoff, 2016). One informative line of research along these lines has been a focus on excessive crying and “fussy” behaviors in early infancy (Rao, Brenner, Schisterman, Vik, & Mills, 2004). For example, excessive and persistent infant crying predicts dysregulatory problems including externalizing problems through age 28 (Bilgin et al., 2018; DeSantis, Coster, Bigsby, & Lester, 2004; Wolke, Rizzo, & Woods, 2002). This work suggests that extend- ing the rigor of the developmental specification framework to infancy (a period when normative variation in crying is at its peak) may be fruitful for identification of clinically salient irritability markers to the 1st year of life.

Our focus on irritability as the key transdiagnostic risk marker for mental health problems dovetails with broader trends in developmental surveillance in pediatrics (Marks, Page Glascoe, & Macias, 2011). Many pediatric screening instruments for young children include irritability items as part of broader socioemotional assessment (Briggs-Gowan, Carter, Irwin, Wachtel, & Cicchetti, 2004; Chen, Filgueiras, Squires, & Landeira-Fernandez, 2016). Moreover, the adverse effects of irritability on mental health are compounded by downstream effects on other aspects of health and functioning, including associations to obesity, poorer dental health, decre- ments in school readiness, and exacerbation of chronic pediatric conditions, making irritability a high impact target (Marino, Cassedy, Drotar, & Wray, 2016; Sheldrick et al., 2013). It is also aligned with neuroscientific evidence. Dispositional versus clinically impairing irritability in young children can be distin- guished as an aberration of frustrative nonreward processes, expressed via differential recruitment of prefrontal resources during frustration (Grabell et al., 2017). These findings bolster irritability as an optimal candidate risk marker as corollary neurobiologic vulnerability markers can be identified, and potentially altered, earlier than previously thought.


Despite this burgeoning science base for developmentally- based sensitive and specific early identification, implementa- tion of these discoveries into health care delivery systems remains a major gap impeding public health impact (Shonkoff, 2016). Translation of this evidence base to selective prevention targeting transdiagnostic dysregulation to alter life span probabilistic clinical risk at the population level is the core of the Healthier Pillar (Figure 2). This has transformative power for significantly reducing the substantial population attributable risk for mental disorder that emanates from early life self-regulatory deficits (Murray et al., 2015; Schaefer et al.,2017). Again we note that this Healthier approach does not suggest that such broad-based selective prevention will effec- tively eliminate life course risk of mental health problems. Rather, as Figure 2 shows, Healthier aims to alter the set point of risk as early as possible in development for those children already exhibiting clinically worrisome dysregulation profiles. Improved self-regulation is theorized to have both direct and indirect effects on children’s functioning via their own strengthened capacities and its impact on environmental transactions. For some children and families, this may suffice. However, there is some evidence that the use of ongoing“checkup” booster sessions are important for sustained impact (Dishion et al., 2014). Further, those children whose dysregula- tion is embedded in a high-risk ecological context and/or co- occurring with other clinical conditions (e.g., autism spectrum disorder, inflammatory bowel disease) may well require a tiered approach.

Reorienting Prevention to the Earliest Phase of the Clinical Sequence

Key components of the Healthier pillar are (a) leveraging pediatric primary care as a platform for early life preven- tion with greatest reach, (b) generating dynamic develop- mentally based risk models that use health information technology and are optimized for integration into clinical care, and (c) providing a scalable road map from risk to population-level prevention.

By definition, identifying and intervening with mental health risk at the vulnerability stage must take this process beyond the mental health clinic, as optimally children are identified prior to frank clinical problems. PCMH provide a transformative opportunity to advance scalable early identifi- cation and prevention of mental health problems at the popula- tion level (Asarnow, Kolko, Miranda, & Kazak, 2017; Shonkoff, 2016). Important to note, embeddedness in routine primary care provides broad population-level access and is the earliest and most frequent point of contact with health profes- sionals given that the vast majority of young children are seen



Naturalistic course with traditional “watch and wait” Mental Health Problems

Optimized trajectories with selective prevention

Mental Health Problems

Optimal Mental Health

Birth Early Childhood Childhood & Beyond

FIGURE 2 Healthier pillar: Targeted prevention of early dysregulated irritability moves the dial for young children’s mental health.

Optimal Mental Health Childhood & Beyond

regularly through the first 5 years of life (Bloom, Jones, & Freeman, 2013). In addition, as PCMH emphasize preventive and continuity care, they provide a nonstigmatized medical home that parents trust (Leslie et al., 2016). Behavioral health issues are also among the most common presenting issue to pediatricians (Boat, 2015).

Developmentally Optimized Risk Assessment

We posit that providing clear decision-making parameters for “when to worry” about young children’s mental health requires a dynamic risk assessment process. This must harness advances in health information technology to enable efficient and accurate probabilistic risk estimation within the develop- mental context. A computer adaptive test (CAT) is one health information technology that could substantially improve screening efficiency and lay the groundwork for optimization of early identification at the population level (Veldkamp & van der Linden, 2002). CATs maximize precision by administering only those items necessary for clinical determination based on response patterns. CATs provide more efficient testing by max- imizing the precision of a score—in this case, probabilistic risk—while minimizing the number of items to reach that precision. There are many methods to accomplish this, but in the context of population health screening, the necessary precision is at the threshold of risk status. That is, it does not matter if a child is well below or well above the cutoff, as this classification will be accurate regardless. However, for children near the cutoff (tra- ditional area of uncertainty), a CAT can continue asking highly discriminative items to ensure appropriate precision above or below the threshold (McGlohen & Chang, 2008). CATs are of increasing interest in mental health assessment of youth (National Institute of Mental Health (2013–2018)). Although

not yet applied to assessment of irritability as a transdiagnostic risk marker in early childhood, recent psychometric work shows promise for this efficient screening approach. We recently demonstrated that parental report on only two MAP- DB irritability items (i.e., “easily frustrated” and “has destruc- tive tantrums”) has good predictive utility for irritability-relatedDSM disorders (Wiggins et al., 2018).

Recognizing the importance of brevity in screening, we also underscore that these CATs must be optimized to account for contextual factors external to the child that profoundly shape risk trajectories. For example, it is widely recognized that family stress and ecological adversity exacerbate neuro- developmental problems and impede intervention uptake but these have only recently been considered in pediatric care (Sheldrick & Perrin, 2009). Co-occurring developmental delays or conditions (e.g., language delays, autism) may also affect risk thresholds (Kaat & Lecavalier, 2013). Optimally, CAT algorithms will evolve to incorporate these developmen- tal and contextual factors as the basis for rapid decision making about the need for, and level of, mental health pre- vention services during young children’s pediatric checkups. CATs could also point to the need for more in-depth assess- ment prior to clinical determination for those children in the“gray area” (e.g., near the risk threshold for their age or due to the presence of other developmental and contextual factors that substantially increase risk; McGlohen & Chang, 2008). In the field of early childhood mental health, the developmental complexities of clinical assessment too often make the perfect the enemy of the good. There is urgent need to take the existing science base and tools, and partner with health ser- vices researchers and implementation scientists to generate robust methods for screening and prevention that can be implemented in real-world settings.

Birth Early Childhood



Probabilistic Outlook for Mental Health and Disorder

Probabilistic Outlook for Mental Health and Disorder

Joint consideration of behavioral indicators and biomar- kers in risk determination is a key aspect of multilevel optimization of risk assessment. Although its importance is widely recognized, actualization has been impeded by inade- quate operationalization for clinical application (Casey et al.,2014). There are hints from recent research with very young children that this avenue of investigation will be clinically fruitful. For example, inattentive/impulsive behaviors as early as 18 months combined with an atypical pattern of sustained visual attention from 3 to 24 months, predict attention deficit/hyperactivity disorder (Miller et al., 2016). Similarly, atypical brain growth trajectories across the first years of life differentiate infants at high familial risk who do or do not develop autism (Piven, Elison, & Zylka, 2017). Further, neural markers of clinical risk have now been iden- tified as early as 3–6 months of age, including brain struc- tural abnormalities (e.g., enlarged brain volume), functional and information processing atypicalities (e.g., face proces- sing), and nonlinear electroencephalogram (EEG) features (e.g., dynamical features of time series such as entropy andfluctuations; Bosl et al., 2018; Johnson, Gliga, Jones, & Charman, 2015).

Other observational studies highlight the interplay of biobehavioral