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The Myth of Average:  Todd Rose at TEDxSonomaCounty

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Office of the California Surgeon General

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Understanding ACEs with Dr. Nadine Burke Harris

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The devastating, underdiagnosed toll of toxic stress on children

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Introduction

Childhood is an important period for the development of socioemotional and cognitive skills given the high degree of brain plasticity that facilitates learning and adaptation to the environment [ 1, 2]. However, early life adversity (ELA) during periods of heightened plasticity may alter developmental trajectories via complex neurobiological and stress-mediated mechanisms that, in turn, increase the risk of socioemotional and behavioral difficulties in children and youth [ 3]. ELA encompasses a wide range of experiences such as psychosocial and material neglect, exposure to intimate partner violence, and physical, sexual, and emotional abuse. Some of these experiences involve the presence of threatening inputs (e.g., abuse), while others reflect the absence of expectable inputs (e.g., neglect). Although the neurodevelopmental consequences of different dimensions of ELA may be at least partially distinct, each of these share a defining feature in that they generally entail a deviation from the expectable environment that requires considerable adaptation by the average child [ 4]. While this adaptation may foster survival under conditions of stress and adversity, it may be undesirable in more typical developmental circumstances and give rise to a multitude of poor outcomes, including health-risk behaviors that are associated with considerable early morbidity and mortality [ 5].

ELA is strongly correlated with higher rates of almost all commonly occurring mental health problems, including mood, anxiety, and substance use disorders [ 6, 7, 8, 9]. The association between ELA and mental health difficulties is especially concerning given that more than half of all children and youth will experience at least one form of ELA by adulthood [ 10, 11], and that ELA accounts for the onset of roughly half of all mental health problems in childhood [ 6, 10]. Psychiatric difficulties associated with ELA are also more severe, persistent, and treatment-resistant than difficulties and disorders not associated with ELA [ 7]. Thus, ELA is a critical target of public health inititives designed to reduce population disparities in mental health among children and youth [ 12].

Recently, there has been somewhat of a paradigm shift towards dimensional models of ELA that aim to better characterize the mechanisms linking particular experiences of adversity to specific developmental outcomes [ 13, 14, 15, 16, 17]. One such model is the Dimensional Model of Adversity and Psychopathology (DMAP) [ 16, 17], which posits that discrete forms of ELA exist along two broad dimensions: threat and deprivation. In this model, threat is operationalized as harm or the threat of harm, while deprivation is operationalized as the absence of expected environmental input or complexity. Another dimensional model that is informed by evolutionary life history theory is that of Ellis et al. which conceptualizes ELA along the dimensions of harshness and unpredictability [ 13]. In this Life History (LH) model, harshness is defined as suffering and mortality due to extrinsic forces (i.e., family life/community violence) which are out of the individual's control, while unpredictability is defined as random fluctuations in exposure to harshness. Recent work has integrated the DMAP and LH models to outline three primary dimensions along which specific types of ELA may fall: threat/harshness, neglect/deprivation, and unpredictability [ 18]. The current review draws on this framework to provide an up-to-date synthesis of the literature focused on evaluating the partially distinct cognitive, socioemotional, and mental health correlates of ELA along each of these three dimensions, while also detailing how alterations in cognitive and socioemotional function serve as a developmental pathway linking ELA to psychopathology in childhood and adolescence. This is important at the current juncture within the literature as it accompanies an ongoing discussion regarding the utility of both DMAP and LH models which may serve as a basis for future ELA research (see McLaughlin et al. for arguments supporting an integrated dimensional approach, and Smith and Pollak and Pollak and Smith for arguments generally opposing such approaches) [ 18, 19, 20].

Threat/harm

Threat/harm and psychopathology

Threat/harm and underlying mechanisms

The central tenets of the DMAP suggest that early exposure to threat is primarily associated with alterations in socioemotional development that promote the rapid identification of threat cues in the environment, which in turn serves as a distinct pathway to the expression of psychopathology [ 4]. A seminal study pointing to differences in social information processing among individuals exposed to threat was conducted by Pollak et al. who examined different patterns of emotion recognition by maltreatment subtype [ 27]. Children exposed to threat showed a more liberal threshold for the detection of anger that was not present in control participants or those who experienced deprivation (i.e., neglect). Following this study, research investigating socioemotional differences among children exposed to ELA has tended to focus on specific maltreatment subtypes in isolation, rather than comparing similarities and differences between types of ELA. However, in studies investigating how threat exposure impacts socioemotional development, accumulating evidence supports the idea that children exposed to threat identify angry facial stimuli with less sensory information and with greater accuracy compared to healthy controls [ 28, 29, 30, 31, 32, 33]. Pollak reported that children exposed to physical abuse were more accurate in identifying angry facial expressions, but not other emotions, compared to non-maltreated children [ 32]. This appears to be a dose-response relation, with greater exposure to abuse corresponding to quicker recognition of angry facial cues [ 33]. These results suggest that children exposed to threat have a perceptual bias towards the recognition of threatening stimuli in their environment, a conclusion further supported by studies demonstrating that children exposed to threat display an automatic attention bias towards threatening stimuli [ 34, 35]. However, it should be noted that there is heterogeneity around the directionality of this effect, with some studies reporting an attention bias away from threat cues associated with severity of exposure to threat in childhood [ 36]. Age may be an important moderator of these associations. For example, Weissman et al. showed that, as the severity of maltreatment increased, greater attention bias towards threat cues in children switched to a bias away from threat cues in older adolescents, thus underscoring the importance of developmental stage in examining links between threat exposure and attentional processes [ 37].

Although the ability to rapidly detect threat serves an adaptive function in dangerous environments, over time it may increase the risk of mental health difficulties. Previous studies have demonstrated associations between attentional bias to threatening cues and anxiety [ 38], depression [ 39], PTSD [ 40], and externalizing problems [ 41]. These attentional biases may relate to difficulties deploying effective strategies for regulating emotions, such as rumination and expressive suppression instead of adaptive skills like cognitive reappraisal [ 42]. Overreliance on unhealthy emotion regulation processes may increase transdiagnostic risk for psychopathology [ 43, 44]. Indeed, alterations in emotion regulation have been identified as an important mediator between childhood abuse and depression [ 45], self-harm [ 46], and PTSD [ 47]. Moreover, a recent study by Weissman et al. demonstrated that engagement in less optimal emotion regulation strategies, particularly expressive suppression and rumination, mediated the association between abuse exposure and longitudinal increases in general psychopathology (i.e., the "p" factor) [ 37].

Threat/harm and neurobiology

Functionally, threat has also been shown to be associated with frontoamygdala circuitry. Studies have consistently found greater amygdala activity in youth who live in environments characterized by threat [ 61, 62, 63, 64], although findings have been significantly more variable for vmPFC function [ 65]. Moreover, increased amygdala reactivity to negative stimuli may underlie risk of depression, anxiety, externalizing problems, and general psychopathology [ 66]. In contrast, a recent study conducted by Hein et al. reported decreased amygdala habituation (i.e., sustained activation) in a sample of 15-17 year olds exposed to threat when viewing angry facial stimuli, yet this was accompanied by low starting levels of amygdala activation, suggesting an overall blunting of amygdala activation [ 67]. This finding stands in contrast to the core hypotheses of the DMAP and requires replication in future longitudinal studies that track age-related changes in amygdala activation and habituation over time. In addition, threat exposure has been associated with differences in salience network activation. Studies measuring salience network activation have primarily reported increased anterior insula activation in response to threatening stimuli [ 61, 62, 68], while some studies report reduced dorsal anterior cingulate cortex (dACC) activation in response to threat cues [ 69]. It is worth noting here that these differences may be attributable to age-related changes in frontoamygdala communication. For example, recent work suggest that, among typically-developing youth, childhood may be characterized by information flow from amygdala to dACC to vmPFC (i.e., bottom-up processing), while adolescence may be characterized by information flow from vmPFC to dACC to amygdala (i.e., top-down processing) [ 70]. Further work should consider such developmental changes when interpretating the effects of ELA on neurodevelopment.

In terms of brain electrical activity (e.g., assessed using EEG), increased N2 and P3b activation has been observed in individuals exposed to threat as compared to controls when viewing angry faces, thus demonstrating a heightened vigilance for the rapid detection of threatening stimuli [ 31]. Further, this increased attention to threatening stimuli at the neural level mediated relationships between exposure to physical abuse and symptoms of anxiety [ 31].

Finally, a recent systematic review reported that alterations to the structure and function of the frontoamygdala circuit and salience network were consistently observed in children exposed to threat, but not necessarily those exposed to deprivation [ 65]. This adds further support for the differential neurocognitive consequences of threat compared to deprivation. An important next step for the field is to examine whether these neurocognitive differences mediate associations between unique dimensions of ELA and different forms of psychopathology. This requires longitudinal designs in which different dimensions of ELA are captured, different cognitive and neural phenotypes are measured, and multiple domains of psychopathology are jointly assessed. Especially important is the need for well-powered studies that can detect meaningful associations by avoiding false positive findings and failures of replication. An example of such a study is the Adolescent Brain Cognitive Development study [ 71], which will be an invaluable resource to the field in the years ahead.

Deprivation

Deprivation and psychopathology findings

One domain of mental health that is strongly linked to early deprivation is ADHD. Multiple studies show that preschool-aged children reared in institutions have significantly higher rates of ADHD than never-institutionalized children [ 77, 78]. While the rates of many common psychiatric difficulties in children removed from institutions begin to approximate rates of never-institutionalized children by adolescence [ 72, 74], rates of ADHD generally persist through adolescence and young adulthood [ 72, 73, 75, 79, 80]. Some evidence suggests that those reared in institutions exhibit a distinct inattentive subtype of ADHD [ 80]. This may point to specific neurodevelopmental mechanisms impacted by early life deprivation (expounded below).

The link between deprivation and psychiatric difficulties is not limited to severe forms such as institutionalization. Indeed, other forms of deprivation, including poverty and low socioeconomic status (SES), are also associated with increased rates of psychopathology [ 81, 82]. Furthermore, previous reviews and meta-analyses have shown that different types of maltreatment (abuse and neglect) are associated with greater risk for multiple mental health problems [ 83, 84, 85]. While there is some variability in the extent of risk conferred by specific types of ELA, experiences of both threat (e.g., abuse) and deprivation (e.g., neglect) show significant positive associations, with largely similar effect sizes [ 83, 84, 85, 86, 87]. Thus, each of these dimensions is generally considered a non-specific risk factor for mental health problems. In contrast, there is evidence that deprivation is associated with partially distinct mechanisms that underlie psychopathology compared to threat. We explicate these mechanisms below.

Deprivation and underlying mechanisms

The DMAP suggests that early deprivation is primarily associated with alterations in cognitive functioning that are not observed as consistently among those exposed to threat [ 4]. In support of this hypothesis, exposure to deprivation has been consistently linked to a range of cognitive and academic difficulties [ 88, 89, 90, 91, 92, 93]. It has also been shown that early intervention can offset these cognitive difficulties through early removal from institutions and placement in high-quality family care settings [ 88, 89, 94, 95]. Early work by Tizard and Rees demonstrated that improving the quality of institutional care to focus on providing enriched social and cognitive stimulation can mitigate cognitive impairments associated with institutionalization [ 96]. Indeed, a core mechanism underpinning the cognitive difficulties associated with early deprivation is in the lack of socioemotional and cognitive input that characterize both institutional care and family-based neglect, the most common form of maltreatment in the United States [ 97]. Thus, the difference between institutional deprivation and common forms of neglect is likely a matter of degree rather than a qualitative difference.

In addition to impairments in general intellectual and academic abilities, deprivation has also been associated with reduced language skills [ 90, 91, 98, 99]. In studies of typically-developing children, reduced language input from caregivers at 18 months is associated with lower pre-academic skills at age 4.5 years through a host of cognitive skills at age 3, including reduced language ability, inhibitory control, and ToM [ 100]. Interestingly, when controlling for maternal linguistic input (i.e., stimulation), maternal responsiveness (e.g., warmth and sensitivity) was not strongly associated with these cognitive abilities. Recent meta-analytic work has shown a moderate inverse association between experiences of both threat and deprivation with language abilities, but no moderating effect of ELA type [ 101]. In contrast, recent longitudinal work has reported that while both threat and deprivation in childhood are associated with increased risk of internalizing and externalizing problems in adolescence, only deprivation operates through language ability [ 102, 103]. Evidence from preschool children similarly shows that lower SES (a proxy for deprivation) is associated with reduced language ability at age 3, and that lower language ability is correlated with higher general psychopathology at age 4.5 years [ 104]. Given the importance of language abilities for self-regulation, effective problem-solving, and emotional expression and awareness, this may serve as a key mechanism connecting early deprivation to broad-spectrum psychopathology over the course of childhood and adolescence.

It has been suggested that deficits in associative learning may serve as a common mechanism linking deprivation to multiple domains of cognitive functioning [ 113]. The framework for this model is derived from the notion that associative learning promotes the formation of new synaptic connections, yet in the absence of contingent responsiveness (e.g., from caregivers) or a general lack of available rewards in the environment (e.g., provision of food, physical proximity, and affection), synaptic connections will either not form (i.e., reduced proliferation) or will be prematurely eliminated (i.e., accelerated pruning). Support for this model comes from studies looking at alterations in stimulus-response relationships, with consistent findings that children reared in institutions perform significantly worse than never-institutionalized children on associative learning tasks [ 114, 115, 116]. In turn, reduced associative learning mediates the relation between early deprivation and depression symptoms in early adolescence [ 114]. Strikingly, studies also show that children removed from institutional settings at early stages of development perform as well as children who were never institutionalized on associative learning tasks [ 114, 115], suggesting that recovery is possible when contingent responsiveness is restored. It is important to note, however, that deficits in associative learning have also been linked to early threat exposure [ 117, 118]. However, to our knowledge no study has examined the association between threat and deprivation with associative learning while controlling for the effect of the other dimension of ELA, which is required to determine specificity of these associations. This is an important direction of future work.

Deprivation and neurobiology

Evidence from developmental cognitive neuroscience demonstrates clear associations between early deprivation and brain structure and function in regions involved in EF. Structurally, deprivation is correlated with reduced gray matter in the prefrontal, parietal, and temporal regions, as well as reductions in total gray matter and white matter volume [ 119, 120, 121]. A recent systematic review by McLaughlin et al. [ 65] highlighted that deprivation is associated with fairly reliable reductions in volume or thickness of frontoparietal network regions, including the dorsolateral PFC (dlPFC) and superior parietal cortex. Altered structure in these areas is, in turn, linked with increased risk for multiple types of psychopathology [ 122, 123]. Some evidence for alterations in structural connectivity also exist, with reduced fractional anisotropy (FA; measuring white matter microstructural organization) in the superior longitudinal fasciculus and inferior fronto-occipital fasciculus in relation to deprivation [ 124, 125]. This is in contrast to threat exposure, where increased FA has been observed in relation to traumatic events [ 126].

Furthermore, altered neural function of frontoparietal regions and other regions important for EF have been observed in youth exposed to deprivation. For example, on a cognitive task involving neutral stimuli, children exposed to deprivation recruited the inferior frontal cortex and dACC more strongly than control subjects [ 127]. Additionally, in a recent study by Silveria et al. functional connectivity of the dACC to other regions within the cingulo-opercular network were found to mediate the association between deprivation and externalizing symptoms [ 128]. Furthermore, on cognitive control tasks involving emotional cues, children exposed to deprivation show reduced recruitment in the dlPFC [ 129]. This is in contrast to children exposed to threat, who have been shown to demonstrate increased recruitment of the PFC during cognitive control of emotion [ 61, 65]. Again, this suggests differences in how cognitive control is deployed to regulate emotionally-salient cues based on the dimension of ELA.

Unpredictability

The third and final dimension of ELA we cover in this review is unpredictability, which is believed to differ in its developmental consequences compared to harshness/threat [ 13]. According to Life History (LH) theory, in harsh environments there is less access to necessary resources and a correspondingly greater risk of external injury, illness, or death. In contrast, unpredictability refers to stochastic fluctuations in harshness over space and time (i.e., residential transitions, how often caregivers change jobs, and changes in cohabitation) [ 134]. An outgrowth of the LH model is the Adaptive Calibration Model (ACM), which postulates that individual differences in physiological stress responsiveness and related behaviors are a consequence of adaptation to the conditions of the environment [ 135]. This means that stress response systems of an organism mediate alternate LH strategies as a function of exposure to threatening or unpredictable environments. The ACM is primarily focused on stress-mediated behaviors that relate to growth and reproduction, including exploration, learning, parenting, risk-taking, impulsivity-aggression, and cooperation [ 136]. Another recent model that has emerged from LH theory which more explicitly focuses on cognitive functions associated with adversity is the Hidden Talents Approach [ 137]. This approach is unique in highlighting cognitive advantages conferred by adversity that permit adaptation to threatening and/or unpredictable environments. The Hidden Talents Approach, like the DMAP, acknowledges that specific experiences and exposures may have distinct associations with certain cognitive abilities because they pose different developmental challenges [ 138]. This model grants its own strengths and limitations, including issues related to measurement and how to differentiate between dimensions of ELA [ 138]. Notably, the challenge of disaggregating dimensions of ELA is not specific to the Hidden Talents Approach, as adversities indeed co-occur and can make it difficult to model ELA dimensionally [ 20]. However, this problem is not so difficult that it cannot be overcome with adequate sampling and statistical techniques [ 18]. A related conceptual difficulty is disambiguating unpredictability from deprivation. Both unpredictability and deprivation relate to socioeconomic disadvantage, which is often used as a proxy for both dimensions in the extant literature. Yet another question that requires further inquiry is how the dimension of unpredictability differs from, or includes, related constructs such as household, school, or neighborhood chaos or instability. These issues are reviewed in detail elsewhere [ 138, 139]. For the purpose of the current review, we include chaos and instability within the general construct of unpredictability.

Unpredictability and psychopathology findings

Although LH theory and the Hidden Talents Approach posit individual strengths that may arise from ELA, other studies have noted that unpredictable environments are associated with increased risk for mental health problems in children and youth [ 140, 141]. For example, externalizing behaviors at age 16 have been found to mediate the link between early unpredictability and externalizing and criminal behaviors in young adulthood [ 142]. Moreover, in a sample of college students, childhood unpredictability with respect to meals, money, discipline, and nurturance was associated with more symptoms of depression and anxiety [ 143]. In a sample of adolescents, unpredictability (measured as parental inconsistency) was shown to correlate with general psychological disorder symptoms [ 144]. Studies of school-age children have similarly shown that the effects of low SES on socioemotional problems is mediated by heightened levels of chaos, operationalized as noise, crowding, foot traffic, confusion at home, and disrupted routines and rituals [ 145]. In other studies of young children, household chaos has been associated with more conduct problems even after controlling for socioeconomic factors [ 146]. Moreover, when dimensions of both household instability (e.g., number of moves, changes in caregiver) and household disorganization (e.g., cleanliness, neighborhood noise) are measured in early childhood, disorganization, but not instability, has been associated with child conduct problems and callous-unemotional traits in first-graders [ 147]. Also interesting in the latter study is that both disorganization and instability were associated with higher callous-unemotional traits through increased parental harshness. As with studies drawing on the DMAP dimensions of threat and deprivation, these findings underscore the non-specificity of unpredictability with respect to psychopathology, instead suggesting that unpredictability may be a transdiagnostic risk for both internalizing and externalizing problems.

Unpredictability and underlying mechanisms

As noted above, unpredictability is a dimension of ELA that is particularly difficult to measure, with many heterogeneous approaches [ 139]. Despite this caveat, there is some evidence linking environmental unpredictability to cognitive mediators of psychopathology. Perhaps the strongest evidence for cognitive alterations associated with exposure to household chaos comes from a recent meta-analysis which showed that disorganization and instability in the home have small but significant associations with EF [ 148]. The effects were stronger for informant-completed reports than direct assessment of EF, and for instability compared to disorganization dimensions of chaos. These results dovetail with the recent meta-analysis reported above in which both dimensions of threat and deprivation were associated with reductions in certain EF domains, despite stronger associations for deprivation [ 112].

Notwithstanding the evidence linking dimensions of threat, deprivation, and unpredictability to both heightened psychopathology and reduced EF, LH models propose that early exposure to harsh and unpredictable environments involves developmental tradeoffs that promote traits synonymous with a "fast lifestyle" which may be beneficial in meeting the challenges of stressful and unpredictable environments [ 13, 137, 149]. One such adaptation is an enhanced ability to flexibly switch between tasks or mental sets and for tracking novel environmental information, especially under conditions of stress or uncertainty. Indeed, there is some evidence of enhanced cognitive flexibility (or shifting of attention) [ 150, 151] and updating working memory [ 152] among those exposed to early unpredictability. Most of these studies have been conducted with adults who retrospectively report on childhood unpredictability, yet some evidence has recently linked unpredictability-measured by the number of paternal transitions-to improved effortful control in preschool children [ 153]. Likewise, caregiving instability defined as the number of caregiver switches has recently been associated with lower response inhibition and attentional control, but enhanced cognitive flexibility in school-aged children [ 154]. It is suggested that these developmental enhancements may reflect a process of adaption to meet the challenges associated with unpredictable early environments. Although these observations seem relatively specific to experiences of unpredictability, recent evidence has also linked early deprivation to enhanced working memory [ 155]. Determining the conditions under which decrements versus enhancements in specific aspects of EF emerge, and the implications of this for mental health, remains an important area for future work in this field.

Unpredictability and neurobiology

Furthermore, high levels of unpredictability are associated with brain functional alterations in regions subserving cognitive control. For instance, household chaos has been shown to moderate the association between parental behavioral control and activation of the insular cortex-a region involved in salience processing and often considered part of a wider network of cognitive control, including flexibility [ 159]-in a sample of adolescents [ 160]. Household chaos has also been shown to moderate the association between parental control and a global factor indexing neural activation during cognitive control in several regions, including the insula and regions comprising the frontoparietal network (e.g., inferior and middle frontal gyrus) in a cohort of adolescents [ 161]. Specifically, only in low chaos homes was higher parental control associated with better neural cognitive control among adolescents. However, household chaos was not directly related to neural cognitive control. This suggests that the ability of parents to serve as effective regulators of adolescent's cognitive control may be undermined in high chaos environments. In turn, poor neural cognitive control was associated with compromised social competence only in high chaos households. These results highlight the fact that different dimensions of ELA may not only directly impact cognitive control and its underlying neural mechanisms, but may shape the way in which the environment scaffolds these skills, including how responsive children and youth are to social organizers of cognition and emotion, ultimately increasing the risk of psychopathology and other functional outcomes.

Evidence directly supporting dimensional models of ELA

It is important to note that very few studies have studied the unique effects of threat/harshness, deprivation, and unpredictability simultaneously in relation to mental health, cognition, and/or their neurobiological underpinnings. As such, this section is dedicated to outlining findings from studies that have taken an integrated dimensional approach. One such study measured exposure to violence (threat), cognitive stimulation (deprivation), and unstable aspects of the physical environment such as cleanliness and safety (unpredictability) [ 162]. Assessments of associative memory, cued attention, and memory-guided attention were conducted. The results showed that violence exposure was specifically associated with poor associative memory after controlling for cognitive stimulation and the physical environment. In contrast, cognitive stimulation and the physical environment were associated with cued attention, but not independently of other environmental factors. Finally, the physical environment was associated with memory-guided attention after adjusting for violence and stimulation. While not neatly mapping onto hypotheses derived from DMAP or LH models, these results suggest differential associations between different dimensions of ELA and specific cognitive abilities. An important next step in this work is to determine whether these cognitive alterations mediate psychopathology risk in children and youth following exposure to specific dimensions of ELA.

To our knowledge, only one study has simultaneously measured the neurobiological effects of threat, deprivation, and unpredictability over time [ 163]. In this recent three-wave longitudinal study of 9-19-year-old participants, higher family-level deprivation was broadly associated with lower initial resting-state connectivity and less connectivity increases over time both within networks (salience network and default mode network) and between networks (default mode-to-frontoparietal, default mode-to-salience, and frontoparietal-to-salience networks). Neighborhood deprivation was not associated with any specific connectivity differences. Adolescents exposed to unpredictability had lower initial levels of salience network connectivity and had less of a connectivity increase over time between both salience and default mode networks, as well as between salience and frontoparietal networks. Adolescents exposed to threat demonstrated slower decreases over time within frontoparietal networks and between default node and salience networks. The authors concluded that, while family-level deprivation may diffusely impact neural connectivity across multiple networks, both threat and unpredictability may have more focal connectivity correlates. These results demonstrate that different dimensions of ELA may be associated with different underlying neurobiological mechanisms. However, it should be noted that there is some variability within recent longitudinal studies examining connectivity differences across dimensions of adversity. For example, one study reported that salience network resting-state functional connectivity tended to increase for both individuals exposed to threat and deprivation in a longitudinal sample of adolescents aged 16-19 years, and these increases mediated associations between different dimensions of ELA and depressive symptoms at age 19 years [ 164]. Another longitudinal study of adolescents aged 15-17 years reported reduced resting-state functional connectivity density within the salience network, and between default mode and salience networks, among those exposed to threat, but not social deprivation [ 165]. It is possible that these study differences in connectivity are attributable to age-related changes in connectivity, the timing of adversity exposure, or other sampling/measurement factors that make clear conclusions difficult to draw. Additional studies that catalog connectivity differences from childhood to through adolescence will be required to better understand these findings.

Finally, we would like to highlight a recent large-scale longitudinal study by McGinnis et al. (2022) which draws attention to interpersonal loss (e.g., death of a parent) as another potentially distinct dimension of ELA alongside the existing dimensions of threat, deprivation, and unpredictability [ 166]. Consistent with the core hypotheses of the DMAP, McGinnis et al. found that only material deprivation was associated with the proximal outcome of lower IQ in early adulthood despite being associated with a host of later psychiatric and functional outcomes, lending support to alterations in cognitive function as a putative mechanism linking deprivation to broad psychological well-being. Moreover, although no proximal outcomes associated with emotional functioning were evaluated within this study, threat was the only dimension of ELA that was significantly correlated with both adult depressive and anxiety as distal psychiatric outcomes, lending some support to alterations in emotional functioning following threat exposure. Moreover, unpredictability was associated with number of sexual partners at age 16 and downstream conduct and criminality outcomes in adulthood, consistent with LH theory. Uniquely, interpersonal loss was not associated with any psychiatric outcome or cognitive function in adulthood, but was associated with both sexual partners at age 16 years and age at first childbirth, as well as economic and conduct problems as functional outcomes in adulthood. Interestingly, after controlling for the dimensions of adversity noted above, a composite measure of "other adversities"-which included exposure to illness, disaster, and accidents-was associated with only one-of-four psychiatric outcomes (cannabis use), as well as distal health, economic, and conduct problems, but was unrelated to any proximal mechanism proposed by either DMAP or LH theory. The fact that each of the four dimensions of ELA assessed (threat, deprivation, unpredictability, and loss) was associated with multiple psychiatric and functional outcomes but partially distinct proximal mechanisms lends support to dimensional models of ELA. Indeed, future longitudinal work that examines other potential dimensions of adversity in addition to those noted above will improve our understanding of the shared and distinct consequences of ELA and their associated mechanisms.

Conclusion and future directions

Emerging evidence supports the use of dimensional models in mapping the cognitive, socioemotional, and mental health consequences of ELA, with partially distinct neurodevelopmental mechanisms operating for different dimensions of ELA. Specifically, while the dimensions of threat/harshness, deprivation, and unpredictability appear to confer increased risk for multiple mental health difficulties along the internalizing and externalizing spectra, they do not necessarily do so via the same neurocognitive and socioemotional pathways. However, this is not to say that the mechanisms connecting ELA to psychopathology are completely distinct. Indeed, while some meta-analyses show significant associations for one dimension of ELA but not the other (e.g., associations of threat but not deprivation with markers of biological aging [ 167]), others show this distinction only in degree (e.g., both threat and deprivation are associated with EF, with stronger associations for deprivation [ 112]). There are also some aspects of functioning or physiology that are common across dimensions of ELA, such as stress system responsiveness [ 18].

With an eye to the future, the field will likely begin to focus on the ways in which multiple transdiagnostic mechanisms work in tandem to heighten the overall risk of psychopathology. In the case of co-occurring adversities across different dimensions of ELA, it will be important to examine how the cognitive and socioemotional difficulties inherent to threatening, depriving, and unpredictable experiences interact with one another to shape mental health outcomes. Indeed, in the cumulative risk literature it is well-established that as risks accrue, so too does the risk of psychopathology [ 168]. While frequently attributed to processes such as increased allostatic load [ 169], it may also be that exposure to multiple adversities up- or downregulates several neurodevelopmental processes that potentiate one another to exacerbate psychopathology risk. To this end, a recent study investigating white matter connectivity differences among adolescents who experienced adversity in childhood reported that, although there were no specific differences been individuals who experienced threat compared to social deprivation, there was a significant interaction between exposure to violence and social deprivation such that violence exposure only predicted white matter differences when social deprivation was high, but not when social deprivation was at mean or low levels [ 170]. This study illustrates that multiple co-occurring adversities or singular exposures can be studied through a dimensional lens to more comprehensively understand how dimensions of ELA are associated with the neurobiological mechanisms underlying psychopathology in childhood and adolescence.

Moreover, in the case of complex exposures (e.g., poverty, homelessness, etc.), multiple or singular mechanisms may account for the increased psychiatric risk, depending on the specific exposures of a given child in those settings. For some children and adolescents, this may mean experiencing predominantly threat (e.g., sexual abuse/exploitation), and for others it may mean deprivation (e.g., isolation) or unpredictability (e.g., inconsistent access to shelters or food). However, the fact that complex exposures may involve multiple ELA dimensions does not mean we should expect that each of these dimensions is the same with respect to their developmental consequences; and indeed, each person is likely to be differentially impacted based on their unique clustering of adversities within a given exposure. This is why dimensional models advocate for a more nuanced assessment of what specifically is occurring within a given exposure that signals the presence of threat, deprivation, or unpredictability. In contrast, cumulative adverse childhood experience (ACE) models-which simply sum adversities together-assume each ACE operates on the same mechanism and is weighted equally [ 18]. While such approaches may be useful in public health initiatives to screen for broad risk (though see Finkelhor for cautions to this approach, and Baldwin et al. for evidence of poor accuracy in predicting individual risk from ACE scores), cumulative ACE models are less helpful in ascertaining the mechanisms by which adversity confers increased mental health risk [ 171, 172]. This highlights a need for improved measures that can help to chronicle various ELA types and their underlying dimensions to better understand the mechanisms involved in the sequelae of adversity [ 173]. Applied widely, use of such measures will help to control for methodological differences that may explain heterogeneity in the pattern of results across studies, thus aiding replicability and generalizability within the field of adversity science.

We believe that an integrated framework is required in order to better understand the shared and distinct outcomes and mechanisms associated with ELA along the dimensions of threat/harm, deprivation, and unpredictability [ 18], as well as lesser-studied dimensions (e.g., loss). This includes theoretical models that can be explicitly tested and which draw on multiple perspectives in psychology, neuroscience, cognitive science, psychophysiology, and evolutionary theory, as well as the development of new tools for better assessing and distinguishing between dimensions of ELA in diverse populations. Programs of research that assess multiple types of ELA and which simultaneously chart functioning in numerous neurocognitive and socioemotional domains should be prioritized to further determine the validity and utility of dimensional models, with concerted efforts to create cohesion in the measures and methods used to allow for joining of datasets and to facilitate future meta-analytic work. It may be too early to determine how dimensional models can inform clinical initiatives that tailor interventions to the unique needs of individuals, but such an approach is consistent with parallel initiatives in psychiatry and neuroscience which aim to better characterize the mechanisms underpinning risk of psychopathology. This includes the recently developed Hierarchical Taxonomy of Psychopathology (HiTOP) as a dimensional classification system for mental health problems, and the Research Domain Criteria (RDoC) as a research framework for identifying transdiagnostic biobehavioral systems implicated in psychopathology [ 174]. Despite the potential of these complementary approaches to inform the development of a dimensional psychiatric nosology, neither of them explicitly includes ELA as a target of assessment or measurement. However, dimensional models of ELA clearly square with both the dimensional and mechanistic focus of HiTOP [ 175] and RDoC [ 176]. We believe that further integration of dimensional models of ELA-one of the most robust risk factors for psychopathology-into these models will advance efforts to improve how we study, assess, diagnosis, and ultimately treat mental health problems in children and youth.

References

1. McLaughlin P Katie A, Sheridan M, Humphreys KL, Belsky J, Ellis BJ. The value of dimensional models of early experience: thinking clearly about concepts and categories. 2020. https://doi.org/10.31234/osf.io/29fmt.

2. Woolgar F, Garfield H, Dalgleish T, Meiser-Stedman R. Systematic review and meta-analysis: prevalence of posttraumatic stress disorder (PTSD) in trauma-exposed preschool-aged children. J Am Acad Child Adolesc Psychiatry 2021. https://www.sciencedirect.com/science/article/pii/S0890856721004238?casa_token=_3iUSL59XbUAAAAA:Aq3hdjDoW52RvyDSOXkBm9Ntcavv9USiHB5vRvMqfSXckN-haSrgftXg1-V4t83gYtQl2amZdZA.

3. Gee DG, Hanson C, Caglar LR, Fareri DS, Gabard-Durnam LJ, Mills-Finnerty C, et al. Experimental evidence for a child-to-adolescent switch in human amygdala-prefrontal cortex communication: a cross-sectional pilot study. Dev Sci. 2022:e13238. [Epub ahead of print].

4. Golm D, Sarkar S, Mackes NK, Fairchild G, Mehta MA, Rutter M, et al. The impact of childhood deprivation on adult neuropsychological functioning is associated with ADHD symptom persistence. Psychol Med. 2020;51:1-10.

Google Scholar

5. U.S. Department of Health & Human Services, Administration for Children and Families, Administration on Children, Youth and Families, Children's Bureau. Child maltreatment 2018. 2020. https://www.acf.hhs.gov/cb/research-data-technology/statistics-research/child-maltreatment.

6. Wismer Fries AB, Pollak SD. The role of learning in social development: Illustrations from neglected children. Dev Sci. 2017;20. https://doi.org/10.1111/desc.12431.

7. Ellis BJ, Abrams LS, Masten AS, Sternberg RJ, Tottenham N, Frankenhuis WE. Hidden talents in harsh environments. Dev Psychopathol. 2020;34:1-19.

Google Scholar

8. Fields A, Bloom PA, VanTieghem M, Harmon C, Choy T, Camacho NL, et al. Adaptation in the face of adversity: Decrements and enhancements in children's cognitive control behavior following early caregiving instability. Dev Sci. 2021. https://doi.org/10.1111/desc.13133.

9. McGinnis EW, Sheridan M, Copeland WE. Impact of dimensions of early adversity on adult health and functioning: a 2-decade, longitudinal study. Dev Psychopathol. 2022:1-12. [Epub ahead of print].

10. Berman I, McLaughlin KA, Tottenham N, Godfrey K, Seeman TE, Eric LB, et al. Measuring early life adversity across the lifespan. PsyArXiv. 2021. https://doi.org/10.31234/osf.io/y9xe8.

11. McLaughlin P Katie A, Gabard-Durnam LJ. Experience-driven plasticity and the emergence of psychopathology: a mechanistic framework integrating development and the environment into the research domain criteria (RDoC) model. 2021. https://doi.org/10.31234/osf.io/nue3d.

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Authors and Affiliations

Department of Applied Psychology and Human Development, University of Toronto, Toronto, ON, Canada

Mark Wade, Liam Wright & Katherine E. Finegold

Contributions

MW: Conceptualized the paper and its organization. Drafted the introduction and conclusion sections. Comprehensively reviewed all sections and provided critical edits and revisions on all drafts. LW: Drafted section on differences in cognition across dimensions of ELA and reviewed neurobiological literature relevant to threat exposure. Reviewed and edited other sections of the paper. KF: Drafted section on differences in psychopathology across dimensions of ELA and reviewed neurobiological literature relevant to deprivation exposure. Reviewed and edited other sections of the paper.

Corresponding author

Correspondence to Mark Wade.

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Wade, M., Wright, L. & Finegold, K.E. The effects of early life adversity on children's mental health and cognitive functioning. Transl Psychiatry 12, 244 (2022). https://doi.org/10.1038/s41398-022-02001-0
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# data[].attributes.attachment_link.title
The effects of early life adversity on children's mental health and cognitive functioning - Translational Psychiatry

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Emerging evidence suggests that partially distinct mechanisms may underlie the association between different dimensions of early life adversity (ELA) and psychopathology in children and adolescents. While there is minimal evidence that different types of ELA are associated with specific psychopathology outcomes, there are partially unique cognitive and socioemotional consequences of specific dimensions of ELA that increase transdiagnostic risk of mental health problems across the internalizing and externalizing spectra.

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Introduction

This Trauma-Informed and Healing-Centered pedagogies module is responsive to broad experiences of individual and community trauma in relation to academic settings, teaching, and learning. While the topics discussed herein vary in breadth and depth, the goal is to provide language, guidelines, frameworks, tools, and supportive resources to support faculty members and students as they navigate the complex layers of trauma and healing.

Honoring experiences that challenge individual and collective courage is critical, but alone not enough to establish a foundation of care that actively supports healing at the individual and community levels. With this in mind, we invite you to incorporate many of the suggested approaches presented in this module into your trauma-informed pedagogy toolkit.

This article covers:

Introduction

Teaching Tools

Supportive Resources

Types of Trauma Teaching Tools

To learn more about any of these types of trauma, engage with further research, and understand what you can do as an educator, visit our Types of Trauma teaching tools page!

Link to Teaching Tools Page

By adopting Trauma-Informed Pedagogies, we can seek to:

1. Equip ourselves as educators working to remove barriers for students' access to their education.

2. Mobilize our existing networks into a community of care.

3. Substantively support learners already in our educational sphere while creating inlets for those who are yet to participate.

Developing a trauma-informed learning environment benefits all students in your classroom.

A trauma response is our body's normal (reasonable) response to an abnormal situation.

Knowing how to offer concise, appropriate responses to difficult disclosures from students can go a long way toward supporting them.

The Center for Advocacy, Prevention, and Empowerment (CAPE) offers free and confidential services to all staff, faculty, and students at DU, including free consultations with faculty and staff to support them in responding to disclosures, or to talk through trauma-informed responses in and out of the classroom. Email cape@du.edu or call 303-871-3853 to request more information or get support.

Our students are incredibly resilient, and we don't need to know, or fix everything for them. And, in fact, we should not try to! Becoming familiar with the basic impacts of trauma equips us to identify behaviors stemming from stressors and lead with empathy in our responses and solutions.

Addressing & Combatting Compassion Fatigue

Types of Trauma Teaching Tools

"While teachers play many roles in students' lives, psychologist should not be one of them. This is for the benefit of students and teachers alike. For students, school needs to be a place of safety and predictability. Clear boundaries and roles help students establish a sense of safety in relationships. If we dig too deeply into explorations of trauma with students, at best we create a confusing dynamic. At worst, we can impede a student's healing journey by providing uninformed counsel or treatment." (Venet, 2019, p.3)

TIP: The Role of Assessment in Deep Insights and Learning - Dr. Valentina Iturbe-LaGrave

On Grief Pedagogy, a Kitchen Table Talk from Inclusive Teaching Practices at DU with Professor Erin K. Willer

Window of Tolerance

The Continuum of Stress

Grounding Techniques

# data[].attributes.attachment_link.description
This Trauma-Informed and Healing-Centered pedagogies module is responsive to broad experiences of individual and community trauma in relation to academic settings, teaching, and learning. While the topics discussed herein vary in breadth and depth, the goal is to provide language, guidelines, frameworks, tools, and supportive resources to support faculty members and students as they navigate the complex layers of trauma and healing.

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Abstract

Repeated overstimulation of the stress response system, caused by exposure to prolonged highly stressful experiences, is thought to affect brain structure, cognitive ability, and mental health. We tested the effects of highly stressful experiences during childhood and adulthood using data from the UK Biobank, a large-scale national health and biomedical study with over 500,000 participants. To do this, we defined four groups with high or low levels of childhood and/or adulthood stress. We then used T1-and diffusion-weighted MRI data to assess the macrostructure of grey matter and microstructure of white matter within limbic brain regions, commonly associated with the stress response. We also compared executive function and working memory between these groups. Our findings suggest that in females, higher levels of Childhood stress were associated with reduced connectivity within the posterior thalamic radiation and cingulum of the hippocampus. In males however, higher levels of Adulthood stress is associated with similar changes in brain microstructure in the posterior thalamic radiation and cingulum of the hippocampus. High stress in Childhood and Adulthood was associated with decreases in executive function and working memory in both males and females. Stress across the lifespan was also positively associated with the number of diagnosed mental health problems, with a stronger effect in females than in males. Finally, our findings also suggest that cognitive and mental health outcomes due to stress may be mediated by the sex specific stress related changes in brain microstructure. Together our findings demonstrate clear links between stress at distinct phases of the lifespan, changes in measures of brain microstructure, impairments in cognitive abilities and negative mental health outcomes.

Data availability

The authors do not have permission to share data.

# data[].attributes.attachment_link.title
The effects of stress across the lifespan on the brain, cognition and mental health: A UK biobank study

# data[].attributes.attachment_link.description
Repeated overstimulation of the stress response system, caused by exposure to prolonged highly stressful experiences, is thought to affect brain structure, cognitive ability, and mental health. We tested the effects of highly stressful experiences during childhood and adulthood using data from the UK Biobank, a large-scale national health and biomedical study with over 500,000 participants.

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The Trauma-Informed Educational Practices Mission

What is trauma-informed education?

Why are trauma-informed practices needed in healthcare education?

What are the steps we need to take?

Build a trauma-informed lens: this is a journey, not a destination.

It is not enough to offer students remediation courses; what is required is a transformation in teaching and grading practices. This requires that we begin to accept that our practices are inequitable and work to change our practices, pedagogy, and policies.

Embed safety and trust in all our work: this requires that we build positive relationships with students to facilitate learning and mitigate stress and the impact of current or past trauma. Keep in mind as educators that fear of failure, anxiety, and self-doubt reduce cognitive and learning abilities.

Focus on culturally responsive practices: this requires that we are aware of and acknowledge historical and oppressive systems that have disproportionally affected racial, ethnic, and other systemically excluded groups. Our curriculum should be multicultural with positive cultural representations and provide evidence of the resilience of communities. Failing to honor and value students' background and experiences in the classroom is another form of violence and can lead to trauma or re-trauma.

Where can we start?

About

The development of this online platform was funded by the OHSU Racial Equity and Inclusion grant opportunity through the OHSU Center for Diversity and Inclusion in partnership with the OHSU Office of Educational Improvement and Innovation.

We aim to strengthen healthcare education by supporting faculty and staff with the desire to implement or evaluate trauma-informed educational practices. Please contact us if you would like more information about faculty and staff training or changes in your institution.

Rana Halabi Najjar, Ph.D., RN, CPNP

Associate Professor

OHSU School of Nursing - Monmouth

Pronouns: she, her, هي

Email Rana

Francis Alicia Rojina, M.P.H.

Student Inclusion & Success Coordinator

OHSU School of Nursing - Klamath Falls

Pronouns: she, her, ella

Email Francis

RIG/SIG

The purpose of our Research/Scholarship Interest Group is to develop a shared vision and support each other in implementing trauma-informed pedagogy in healthcare education. Individually, we are working on ways to expand our TI practices and pedagogical approaches. Collectively, we explore ways to support and share ideas on implementing TI in the educational environment. If you are interested in attending our educational sessions or our RIG/SIG, please contact us.

RIG/SIG Principle Investigator

Doria K. Thiele, PhD, CNM, IBCLC

Assistant Professor of Clinical Nursing

Pronouns: she/her

Email Doria

RIG/SIG Co-Investigator

Holly Villamagna, MD

Assistant Professor of Medicine

Division of Infectious Diseases, OHSU

Medical Director, Infection Prevention & Control, Hillsboro Medical Center

Medical Director, Occupational Health, Hillsboro Medical Center

RIG/SIG Co-Investigator

Rana Halabi Najjar, Ph.D., RN, CPNP

Associate Professor

OHSU School of Nursing - Monmouth

Pronouns: she, her, هي

Email Rana

Echo recording of presentation on 'Trauma Informed Pedagogy in Healthcare'

Framework

Equity-Centered Trauma-Informed Approach

The following diagram describes the Equity-Centered Trauma-Informed Approach to educational practice. The diagram illustrates the four phases of developing a trauma-informed lens which are centered in equity and justice. Remember, this is a journey, not a destination. The ongoing process of developing a trauma-informed lens should reflect in practice, pedagogy, and policy at OHSU to ensure safety, trust, peer support, collaboration, empowerment, and cultural responsiveness among the OHSU community. It takes all of these components to light the way towards becoming a trauma-informed space.

Resources

Articles

Blogs

Books

Equity-Centered Trauma-Informed Education

Training for Change: Transforming Systems to Be Trauma-Informed, Culturally Responsive, and Neuroscientifically Focused

by Dr. Alicia Moreland-Capuia

Podcasts

Resource Guides

Videos

Websites

Self-Care

Mindful Breaks & Practices

Grounding Exercises

For these grounding exercises, walk students through the exercises after you watch the videos. You can have students stand facing the walls in the room so they can't see each other. It helps them be uninhibited in their movements.

Tools

Standards of Practice for Trauma-Informed Care in Educational Settings

Trauma Informed Care Screening Tool

Upcoming events

2022-2023 Book Club: Discussing Equity-Centered Trauma-Informed Education

A joint collaborative activity between OHSU School of Nursing and the Betty Irene Moore School of Nursing. The book club discussions will focus on the book, Equity-Centered Trauma-Informed Education, by Alex Shervin Venet. Learn more about the author and book by visiting https://unconditionallearning.org.
Book Club Session Dates:

October 17th

November 14th

February 13th

March 20th (with special guest, author Alex Venet)

All sessions will be held via Zoom from 12:00 - 1:30 pm (PST). More information about registration to come in September 2022.

Blog (coming soon!)

This space is still in development. Check back later!

The Trauma-Informed Educational Practices Mission

What is trauma-informed education?

Why are trauma-informed practices needed in healthcare education?

What are the steps we need to take?

Build a trauma-informed lens: this is a journey, not a destination.

It is not enough to offer students remediation courses; what is required is a transformation in teaching and grading practices. This requires that we begin to accept that our practices are inequitable and work to change our practices, pedagogy, and policies.

Embed safety and trust in all our work: this requires that we build positive relationships with students to facilitate learning and mitigate stress and the impact of current or past trauma. Keep in mind as educators that fear of failure, anxiety, and self-doubt reduce cognitive and learning abilities.

Focus on culturally responsive practices: this requires that we are aware of and acknowledge historical and oppressive systems that have disproportionally affected racial, ethnic, and other systemically excluded groups. Our curriculum should be multicultural with positive cultural representations and provide evidence of the resilience of communities. Failing to honor and value students' background and experiences in the classroom is another form of violence and can lead to trauma or re-trauma.

Where can we start?

About

The development of this online platform was funded by the OHSU Racial Equity and Inclusion grant opportunity through the OHSU Center for Diversity and Inclusion in partnership with the OHSU Office of Educational Improvement and Innovation.

We aim to strengthen healthcare education by supporting faculty and staff with the desire to implement or evaluate trauma-informed educational practices. Please contact us if you would like more information about faculty and staff training or changes in your institution.

Rana Halabi Najjar, Ph.D., RN, CPNP

Associate Professor

OHSU School of Nursing - Monmouth

Pronouns: she, her, هي

Email Rana

Francis Alicia Rojina, M.P.H.

Student Inclusion & Success Coordinator

OHSU School of Nursing - Klamath Falls

Pronouns: she, her, ella

Email Francis

RIG/SIG

The purpose of our Research/Scholarship Interest Group is to develop a shared vision and support each other in implementing trauma-informed pedagogy in healthcare education. Individually, we are working on ways to expand our TI practices and pedagogical approaches. Collectively, we explore ways to support and share ideas on implementing TI in the educational environment. If you are interested in attending our educational sessions or our RIG/SIG, please contact us.

RIG/SIG Principle Investigator

Doria K. Thiele, PhD, CNM, IBCLC

Assistant Professor of Clinical Nursing

Pronouns: she/her

Email Doria

RIG/SIG Co-Investigator

Holly Villamagna, MD

Assistant Professor of Medicine

Division of Infectious Diseases, OHSU

Medical Director, Infection Prevention & Control, Hillsboro Medical Center

Medical Director, Occupational Health, Hillsboro Medical Center

RIG/SIG Co-Investigator

Rana Halabi Najjar, Ph.D., RN, CPNP

Associate Professor

OHSU School of Nursing - Monmouth

Pronouns: she, her, هي

Email Rana

Echo recording of presentation on 'Trauma Informed Pedagogy in Healthcare'

Framework

Equity-Centered Trauma-Informed Approach

The following diagram describes the Equity-Centered Trauma-Informed Approach to educational practice. The diagram illustrates the four phases of developing a trauma-informed lens which are centered in equity and justice. Remember, this is a journey, not a destination. The ongoing process of developing a trauma-informed lens should reflect in practice, pedagogy, and policy at OHSU to ensure safety, trust, peer support, collaboration, empowerment, and cultural responsiveness among the OHSU community. It takes all of these components to light the way towards becoming a trauma-informed space.

Resources

Articles

Blogs

Books

Equity-Centered Trauma-Informed Education

Training for Change: Transforming Systems to Be Trauma-Informed, Culturally Responsive, and Neuroscientifically Focused

by Dr. Alicia Moreland-Capuia

Podcasts

Resource Guides

Videos

Websites

Self-Care

Mindful Breaks & Practices

Grounding Exercises

For these grounding exercises, walk students through the exercises after you watch the videos. You can have students stand facing the walls in the room so they can't see each other. It helps them be uninhibited in their movements.

Tools

Standards of Practice for Trauma-Informed Care in Educational Settings

Trauma Informed Care Screening Tool

Upcoming events

2022-2023 Book Club: Discussing Equity-Centered Trauma-Informed Education

A joint collaborative activity between OHSU School of Nursing and the Betty Irene Moore School of Nursing. The book club discussions will focus on the book, Equity-Centered Trauma-Informed Education, by Alex Shervin Venet. Learn more about the author and book by visiting https://unconditionallearning.org.
Book Club Session Dates:

October 17th

November 14th

February 13th

March 20th (with special guest, author Alex Venet)

All sessions will be held via Zoom from 12:00 - 1:30 pm (PST). More information about registration to come in September 2022.

Blog (coming soon!)

This space is still in development. Check back later!

# data[].attributes.attachment_link.description
The Trauma-Informed Educational Practices Mission What is trauma-informed education? Why are trauma-informed practices needed in healthcare education? What are the steps we need to take? Build a trauma-informed lens: this is a journey, not a destination. It is not enough to offer students remediation courses; what is required is a transformation in teaching and grading practices.

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What Does Inclusive Teaching Mean to You?

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Dr. Gloria Ladson-Billings: You're Teaching, But Are They Learning?

If playback doesn't begin shortly, try restarting your device.

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2:26:48

59:06 / 2:26:48•Watch full video

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Dr. Gloria Ladson-Billings: You're Teaching, But Are They Learning?

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Culturally Responsive Teaching: 4 Misconceptions | Cult of Pedagogy

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In some cases, teachers think they’re practicing culturally responsive teaching, when in fact, they’re kind of not. Zaretta Hammond helps clear things up.

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Culturally Responsive Teaching & the Brain

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Just recently I lead a seminar for a group of instructional coaches and BTSA support providers and I asked them to define culturally responsive teaching. It's usually how I start my workshops. Actually, I got them into groups of 5 and asked each group to draw me a picture of the process (Robert Marzano would call that a non-linguistic representation).

I ask them to do it because it gets at the mental models they are carrying around inside their heads about what they think it is.

More often than not, every group emphasizes a different aspect of culturally responsive teaching that is a mix of truth and misconceptions. It's like the story of the king who asked six blind men to tell them what an elephant was like. One felt his tail and said it was like a rope. Another had hold of a big floppy ear and likened the elephant to a fan. And so it went.

Well, that's pretty much what it's like hearing folks talk about culturally responsive teaching. In reality it isn't a set of best practices, but a process.

The Ready for Rigor Framework

I find what teachers (and instructional coaches) need is a framework for organizing the process. The Ready for Rigor frame takes the key elements of cultural responsiveness and organizes them into four practice areas. Unlike the individual part of the elephant that is mistaken for the whole, each area of the frame is interdependent with the others. The social-emotional and cognitive aspects of teaching and learning show up in each area. At its core is the neuroscience that unifies the frame: the brain's reaction to living in a racialized world as well as how it programs itself using culture.

The Inner Circle: Crosscutting Practices

Then there is the inner circle with the four staple practices of every culturally responsive teacher.

Affirmation - noticing and naming the unique talents and gifts of each child, especially those culturally grounded ways of being and expressing oneself.

Validation - acknowledging to students through word or deed the impact of unearned disadvantage in a racialized society without guilt or excuses.

Instructional Conversation - talking with students regularly about their learning process in order to move them safely into their zone of proximal development.

"Wise" Feedback - providing students with wise feedback, what Claude Steele says is the anecdote to stereotype threat. It is corrective feedback that first affirms the student's capacity to meet the goal or standard, tells him honestly where he missed the mark, gives him actionable steps to improve his learning, and helps him monitor his progress.

It Not Mysterious or Magic

There's no magic to the Ready for Rigor frame and it's not the only culturally responsive frame out there. The real point is that you have to have some type of framework to make culturally responsiveness operational. The art of cultural responsiveness lies in weaving together these four practices areas into a process that calms the brain and sets the stage for neuroplasticity where the brain can grow itself.

Learn more about how to operationalize the framework in my new book, Culturally Responsive Teaching and the Brain: Promoting Authentic Engagement and Rigor Among Culturally and Linguistically Diverse Students (Corwin, 2014).

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Why We Need a Framework for Culturally Responsive Teaching - Culturally Responsive Teaching & the Brain

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Just recently I lead a seminar for a group of instructional coaches and BTSA support providers and I asked them to define culturally responsive teaching. It's usually how I start my workshops. Actually, I got them into groups of 5 and asked each group to draw me a picture of the process (Robert Marzano would call that a non-linguistic representation).

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The understanding of how one thinks and learns. It involves planning, monitoring, assessing and adapting one's efforts to learn, understand and perform. Metacognition practices increase one's level of awareness of his/her/their strengths and weaknesses.

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The following videos show University of Plymouth students and academics talking about their experiences of inclusive assessment and giving their advice on best practice. Listed below each video there are some questions to help you think further about making assessments inclusive in your role and with your students.

You could also download our guides which provide further information, advice and guidance on inclusive assessment.

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The following videos show University of Plymouth students and academics talking about their experiences of inclusive assessment and giving their advice on best practice. Listed below each video there are some questions to help you think further about making assessments inclusive in your role and with your students.

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The Power of Mindfulness: What You Practice Grows Stronger | Shauna Shapiro | TEDxWashingtonSquare

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Learning Outcomes

Learning outcomes are what you want your students to learn, either as a result of a specific lesson or on the grander, more general scale of the entire course. Learning outcomes target knowledge, skills, or attitudes for change. Bloom's taxonomy specifically targets these by seeking to increase knowledge (cognitive domain), develop skills (psychomotor domain), or develop emotional aptitude or balance (affective domain). Learning outcomes might be identified by someone outside the teacher, such as state-wide or departmental standards. The taxonomy provides a basis for developing sub-goals and assessment methodology to meet these goals. It is important to note that learning outcomes are goals, and are not the activities performed to achieve those goals. Outcomes can be categorized into broad, global outcomes that may take many years to achieve and provide direction for education, educational goals that guide curriculum development over the weeks or months it takes to complete a specific course, and instructional goals that narrowly focus on the daily activities, experiences, and exercises used in a specific lesson plan.

Objective Builder Tool

For applications specific to a course, the Center for Distributed Learning has developed an objective builder tool to help craft the language for measurable learning outcomes.

Applications of the Taxonomy

Taxonomies are developed to provide a framework for organizing a continuum along an underlying structure. For example, languages may be classified as Romantic, Germanic, etc. based on their underlying grammatical structure and origin. Bloom's taxonomy primarily provides instructors with a focus for developing their course learning outcomes. There are a number of reasons why a teacher would want to use Bloom's taxonomy. Initially, it can be used to increase one's understanding of the educational process. Teachers can see and understand complex cognitive development and how lower-level skills build into higher-order thinking (e.g., recalling facts and comprehending previous problems allows a student to apply their experience to similar problems). Using this understanding facilitates the prioritizing of material and can steer the organization of lessons to maximize class time. For example, lower-level skills (e.g., memorizing factual knowledge) can be developed before higher-level skills are introduced (e.g., analysis of relationships). Current educators frequently face a confusing array of standards and curriculum requirements. Bloom's taxonomy offers a guiding framework for breaking these criteria down into accessible chunks which can be used to direct day-to-day lesson plans and can be easily compared to their own goals for the class. Just as different levels require different instructional delivery methods, they also require different assessment methods. Bloom's taxonomy can be used as a checklist to ensure that all levels of a domain have been assessed and align assessment methods with the appropriate lessons and methodologies. In this way, the taxonomy also makes it easier for you to maintain consistency between assessment methods, content, and instructional materials and identify weak areas.

Update to Bloom's Taxonomy (2001)

Originally, Bloom's taxonomy was one-dimensional with an exclusive focus on the knowledge domain. The current updated version developed by Anderson and Krathwohl (2001) reorganizes, and highlights the interactions between, two dimensions: cognitive processes and knowledge content. Anderson and Krathwohl identify two reasons for updating the original handbook. They emphasize a refocusing of educational outcomes back to the original handbook, which was ahead of its time and can still offer assistance to modern educators and to incorporate new findings in psychology and education into the framework. In their revision, cognitive processes are presented as verbs and the knowledge content are presented as nouns. Along with exchanging the levels of Evaluation and Synthesis (which they rename to Creation), Anderson and Krathwohl redefine the knowledge dimension to include four types:

Factual Knowledge: Basic elements of a discipline that a student must know and be able to work with to solve problems including basic terminology and specific details and elements.

Conceptual Knowledge: Interrelationships between basic factual knowledge that demonstrate how elements work together, for example, classifications and categories, principles and generalizations, and theories, models, and structures.

Procedural Knowledge: How something is done including the methods of inquiry, skills, algorithms, techniques, and methods needed to investigate, apply, or analyze information.

Metacognitive Knowledge: Awareness and knowledge of one's own cognition including strategies for learning, contextual and conditional knowledge about cognitive tasks, and self-knowledge.

References:
Bloom, B. S. (1969). Taxonomy of educational objectives: The classification of educational goals : Handbook I, Cognitive domain. New York: McKay.
Anderson, L. W., Krathwohl, D. R., & Bloom, B. S. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom's taxonomy of educational objectives. New York: Longman.

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IntroductionBloom's taxonomy was developed to provide a common language for teachers to discuss and exchange learning and assessment methods. Specific learning outcomes can be derived from the taxonomy, though it is most commonly used to assess learning on a variety of cognitive levels. The table below defines each cognitive level...

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Disclaimer

The simplified model presented here is just one of many ways to categorize types of memory. There are other models too, and some of them use slightly different definitions for some of the terms used here.

This model highlights just a few of the key brain regions involved in different memory functions. Since no part of the brain exists in isolation, most types of memory include more areas than the ones listed here. The big idea to take away is that different areas of the brain have different functions.

If you wish to delve more deeply into the types of memory or the brain anatomy involved, we encourage you to explore the references linked at the bottom of the page.

When we learn, our brain takes in information about the world that causes us to change our behavior in some way.

For example, a young baby doesn't understand that fire can hurt them. But thanks to learning, if they touch a candle flame even one time, they will probably not do it again. The information that feeds into the brain-candle, flame, hot, pain-is physically recorded in the connections between cells. And those connections influence our future behavior-don't touch!

As the brain takes in any information and stores it, there are physical changes to the connections between brain cells. And those connections influence our behavior.

Neurons that fire together wire together

The brain is an enormous interconnected network of specialized cells called neurons and supporting cells called glia. To transmit information in the brain, neurons pass signals to one another. This passing of signals can cause physical changes to the connections between cells.

When we learn a skill (like riding a bike) or new information (like multiplication tables), we are building brain connections. The more we use those brain connections, the stronger they get. It's the reason "practice makes perfect."

In the activity above, you can read about how injuries to certain brain areas cause certain memory functions to stop working. But just as important are the connections between them. If two brain areas can no longer communicate, then learning and memory can break down.

Like trails through the wilderness, brain connections get stronger the more they're used

Learning is a process that relies on long-term memory systems in the brain. People who study learning typically divide it into 4 steps: attention, storage, consolidation, and retrieval. These steps dovetail with the Types of Memory described above, and they provide a slightly different framework for thinking about what happens when one or more of these steps go wrong.

Attention - Our sensory systems are constantly bombarded with information, yet most of it fades before we are even aware of it. Attention is like a filter that lets important information into the brain while keeping the irrelevant information out. Without attention, we would remember very little.

Encoding - As sensory information comes in, the brain processes it. Strings of sounds become words, flashes of light and color become images. The brain begins connecting this new information with what it already knows about the world. Some information that is encoded will fade, and some will stick around.

Storage - Long-term storage of information requires new brain connections. The brain has its own way of rehearsing experiences (there's evidence that this is what dreaming is all about), which helps strengthen brain connections. But we can also consciously repeat information or skills to help the brain form strong memories.

Retrieval - Retrieval is the process of accessing stored memories. We use it when we recall a fact or reimagine an experience. But we also use it when we take in new information. It's part of what helps us connect new information to old.

Even when memory systems function normally, memory is imperfect. To learn more about the fallibility of memory, visit The Seven Sins of Memory.

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The simplified model presented here is just one of many ways to categorize types of memory. There are other models too, and some of them use slightly different definitions for some of the terms used here. This model highlights just a few of the key brain regions involved in different memory functions.

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Think back to a really vivid memory. Got it? Now try to remember what you had for lunch three weeks ago. That second memory probably isn’t as strong— but why not? Why do we remember some things, and not others? And why do memories eventually fade? Catharine Young gives the basics on memory and memory loss. [Directed by Patrick Smith, narrated by Pen-Pen Chen].

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Elizabeth Cox: The surprising link between stress and memory

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You spend weeks studying for an important test. On the big day, you wait nervously as your teacher hands it out. You're working your way through, when you're asked to define "ataraxia." You know you've seen the word before, but your mind goes blank. What just happened?

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Teaching Strategies: Cognitive Load Theory

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At a glance

Culturally responsive teaching is a rich, intentional approach woven into every aspect of student learning.

It focuses on the assets students bring to the classroom rather than what students can't do.

It raises expectations and makes learning relevant for all students.

Culturally responsive teaching is a research-based approach to teaching. It connects students' cultures, languages, and life experiences with what they learn in school. These connections help students access rigorous curriculum and develop higher-level academic skills.

Our brains are wired to make connections. It's easier for our brains to learn and store information when we have a hook to hang it on. That hook is background knowledge. Students bring this knowledge to the classroom every day.

But for students of color, English language learners (ELLs), and other underserved student populations, those assets are often overlooked. When that happens, educators miss the chance to use them to support learning. (See recent work by Zaretta Hammond for the neuroscience behind this.)

Culturally responsive teaching values and reflects the assets of all students. By doing that, it raises academic expectations for all learners. It also sends the message that multiculturalism is an asset.

Dive deeper

The benefits of culturally responsive teaching

How culturally responsive teaching, UDL, and SEL work together

For educators: Culturally responsive teaching in the classroom

For educators: How to partner with families

Lydia Breiseth (director of Colorín Colorado), Shivohn García, PhD (senior director of the Impact team at Understood), and Shaquala Butler (Understood Teacher Fellow) contributed to this article.

About the author

About the author

Educators Team at Understood is made up of passionate writers, editors, educators, and subject matter experts who have worked in classrooms and with students who learn and think differently.

Reviewed by

Reviewed by

Karla Vigil, MAT is the chief executive officer and co-founder of the Equity Institute.

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Culturally responsive teaching helps create learning environments that validate and reflect the diversity, identities, and experiences of all students. Learn more.

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Creating a Culturally Responsive Classroom

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National Center on Universal Design for Learning

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Universal Design for Learning (UDL) is a way of thinking about teaching and learning that helps give all students an equal opportunity to succeed. This approach offers flexibility in the ways students access material, engage with it, and show what they know.

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CAST

CAST

2018

Abstract

What we know about the brain is central to the Universal Design for Learning Framework. Knowing key facts about the brain from a UDL perspective can help inform learning design to address learner variability. Find out more in this downloadable resource designed for educators.

Download & Learn More

Cite As

CAST (2018). UDL and the learning brain. Wakefield, MA: Author. Retrieved from http://www.cast.org/products-services/resources/2018/udl-learning-brain-neuroscience

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What we know about the brain is central to the Universal Design for Learning Framework. Knowing key facts about the brain from a UDL perspective can help inform learning design to address learner variability. Find out more in this downloadable resource designed for educators.

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Putting Neuroscience in the Classroom: How the Brain Changes As We Learn

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The more we know about how the developing brain changes as we learn, the better we can support young learners.

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How to practice effectively...for just about anything - Annie Bosler and Don Greene