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Prenatal Exposure And Child brain and mental Health (PEACH) study: protocol for a cohort study of children and youth with prenatal alcohol exposure
  1. Catherine A Lebel1,2,3,
  2. W. Ben Gibbard2,4,
  3. Christina Tortorelli5,
  4. Jacqueline Pei6,
  5. Christian Beaulieu7,
  6. Mercedes Bagshawe1,2,3,
  7. Carly A McMorris2,8
  1. 1Department of Radiology, University of Calgary, Calgary, Alberta, Canada
  2. 2Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
  3. 3Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
  4. 4Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
  5. 5Social Work, Mount Royal University, Calgary, Alberta, Canada
  6. 6Faculty of Education, University of Alberta, Edmonton, Alberta, Canada
  7. 7Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
  8. 8Werklund School of Education, University of Calgary, Calgary, Alberta, Canada
  1. Correspondence to Dr Catherine A Lebel; clebel{at}


Introduction Fetal alcohol spectrum disorder (FASD), which is caused by prenatal alcohol exposure (PAE), affects an estimated 4% of North Americans, and is the most common preventable cause of intellectual disability. Mental health problems, including anxiety and depression, are experienced by nearly all individuals with FASD. However, there is very limited knowledge about effective mental health treatments for individuals with FASD; effective treatments are hindered in part due to a lack of understanding of the basic neurobiology underlying internalising disorders in youth with FASD.

Methods and analysis The Prenatal Exposure And Child brain and mental Health (PEACH) study includes children aged 7–18 years. We will use longitudinal neuroimaging (anatomical T1-weighted, diffusion and passive viewing function MRI) and mental health assessments (Behaviour Assessment Scale for Children, Multi-dimensional Anxiety Scale for Children, Children’s Depression Inventory (CDI-2), Kiddie Scale of Affective Disorders) to: (1) characterise brain development trajectories in youth with FASD, (2) determine whether brain alterations mediate increased anxiety and depression in youth with FASD and (3) identify baseline brain features that predict changes of anxiety and depression symptoms over the next 2 years. All of this will be done while considering sex and adverse postnatal experiences, which can significantly impact mental health and brain outcomes. This project will forge new understanding of FASD and mental health from a neurobiological perspective, highlighting key time periods (ie, sensitive windows) and brain regions (ie, that may be susceptible to neurostimulation), while identifying factors that predict individual trajectories of anxiety and depression symptoms.

Ethics and dissemination This study was approved by the University of Calgary Conjoint Health Research Ethics Board and the University of Alberta Health Research Ethics Board. Study results will be disseminated in peer-reviewed journals, at relevant conferences and in conjunction with our knowledge mobilisation partners.

  • mental health
  • child & adolescent psychiatry
  • magnetic resonance imaging
  • depression & mood disorders

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Strengths and limitations of this study

  • We use longitudinal neuroimaging to assess brain structure and brain growth.

  • Alcohol-exposed participants will have confirmed prenatal alcohol exposure, though specific measures of timing, frequency and dose of prenatal alcohol exposure may be difficult to obtain.

  • We use multiple mental health assessments to measure symptoms of depression and anxiety, and include a comprehensive neurocognitive battery.

  • This study uses a longitudinal, prospective design and will follow children over 2 years.

  • We incorporate comprehensive assessment and analysis of both prenatal and postnatal adverse exposures.


Fetal alcohol spectrum disorder (FASD) is a neurodevelopmental disorder caused by prenatal alcohol exposure (PAE). It is characterised by life-long cognitive, behavioural and neurological deficits.1 The prevalence of FASD in North America is estimated to be 4%,2 3 with lifetime costs over $C 1 million per individual.3–5 Beyond the primary cognitive and behavioural deficits, over 90% of individuals with FASD experience co-occurring mental health problems,6–8 compared with 20% in the general population.9 Depression and anxiety are among the most common, affecting 45%–50% and 20%–40% of individuals with FASD, respectively.10–12 Developing early and appropriate interventions to minimise mental health problems and maximise adaptive outcomes in FASD is critical for improving quality of life and reducing the societal burden of FASD. Concerns have been raised that existing mental health treatments for individuals with FASD may be less effective than for the general population,13 14 perhaps hindered by a lack of understanding of their neurobiological basis.

MRI can be used to investigate neurological abnormalities in FASD. The most common MRI finding in individuals with FASD is widespread reductions in brain volume, which have been observed with anatomical MRI from neonates to adults.15–17 Diffusion tensor imaging assesses microstructure of structural white matter connections via fractional anisotropy (FA) and mean diffusivity (MD), measures sensitive to myelination and axonal density.18 Numerous studies have shown lower FA and/or higher MD in children, adolescents and young adults with FASD.19–22 Recent studies suggest that brain diffusion alterations are also present in infants and young children, though in the opposite direction (ie, higher FA and lower diffusivity).23 24 Resting state functional MRI (rs-fMRI) measures patterns of spontaneous brain connectivity by correlating functional signals across regions (‘functional connectivity’)25; findings suggest atypical functional connectivity in children and youth with FASD.26–29 Regional brain volume reductions, weaker white matter connectivity (lower FA/higher MD, and atypical functional connectivity have been reported throughout the brain, but alterations are most prominent in subcortical structures17 30 and prefrontal areas.20 29–31 Most studies to date have been cross-sectional, and thus the trajectories of brain maturation remain unclear. The few longitudinal MRI studies that do exist in FASD show that children with FASD have faster changes of cortical thickness,32 volume33 and white matter connectivity34 than unexposed controls; these faster changes possibly reflect a ‘catch-up’ in brain maturation. It is not known how key functional networks change with age in FASD. Longitudinal research is critical for revealing the developmental trajectories of brain connectivity in FASD.

Previous studies have related cognitive abilities and clinical features (eg, dysmorphology) to brain structure in FASD29 33 35–38; however few studies have examined relationships between brain measures and mental health.39 In individuals without FASD, internalising symptoms are most commonly associated with brain alterations in the anterior cingulate cortex (ACC), medial prefrontal cortex (mPFC), dorsolateral prefrontal cortex (dlPFC), amygdala and hippocampus, as well as connections between these structures.40–42 Resting state functional connectivity is higher in the ACC and mPFC in adolescents with depression,42 43 while weaker structural connectivity (lower FA and/or higher MD) in frontal white matter (eg, cingulum, uncinate) is associated with depression and anxiety in youth.44–49 Areas identified by neuroimaging (eg, prefrontal cortex, cingulate) can be used as brain targets for neurostimulation to treat adults with depression and anxiety,50–52 highlighting the importance of understanding the neurological correlates of internalising symptoms. Given the overlap between structures identified as atypical in children and youth with FASD, and brain areas associated with anxiety and depression, brain alterations induced by PAE may underlie, at least in part, the increased the risk of internalising disorders.

Little is known about the trajectories of mental health symptoms in youth with FASD, though difficulties tend to persist or worsen with age.53 54 However, FASD is a heterogenous disorder, with heterogeneous outcomes,55 so it is critical to consider differences at the individual level. In adolescents without FASD, functional connectivity between the amygdala and mPFC predicts the severity of future internalising symptoms.56 Brain volumes in the hippocampus57 and ACC58 also predict treatment response in adults with depression (but without FASD). However, it is unclear which baseline features predict future mental health outcomes in youth with FASD, though this could inform treatment decisions. Thus, longitudinal research is needed to understand associations between brain alterations and trajectories of depressive and anxiety symptoms in individuals with FASD, to help predict individual outcomes.

Individuals with PAE/FASD frequently have adverse postnatal experiences (~43% have abuse or neglect).59–61 Such early adversity is commonly operationalised as adverse childhood experiences (ACEs),62 which provides a cumulative risk score accounting for abuse, neglect and other household dysfunction in childhood. In the general population, ACEs are associated with heightened risk of anxiety and depression63 and alterations to frontal and limbic brain structure and function.64–72 Animal studies show that PAE and postnatal adversity interact to increase depression risk.73 However, few human studies of FASD have incorporated any measure of postnatal risk. Two recent human studies show differential associations between socio-economic status and brain volumes in children with and without PAE,74 75 and one showed that postnatal adversity (neglect, abuse, etc) moderates the association between PAE and brain connectivity.22 All of this evidence underscores the need for FASD studies to consider postnatal adversity. ACEs treats all adverse experiences similarly, although different types of adversity may have different effects on individuals.76 We recently developed a risk characterisation framework that accounts for the duration, frequency, timing and type of risks, which we believe is more appropriate for children with PAE who may experience a wide range of adversities.60

Understanding brain development in individuals with FASD, its relation to internalising symptoms and predictors of positive outcomes is critical for targeting treatments at the right time (eg, age-appropriate therapy),77 for the right brain regions (eg, for neurostimulation)50 and for the right person (eg, considering individual circumstances).78 In this study, we will recruit 125 youth with heavy PAE or FASD and 125 control youth (7–18 years) and acquire longitudinal MRI and mental health assessments to study trajectories of brain and mental health with the following aims:

  1. Characterise developmental trajectories of brain connectivity in youth with FASD. Hypothesis 1: Structural and functional connectivity to the prefrontal cortex, hippocampus and amygdala will show faster increases in FASD compared with unexposed controls.

  2. Determine whether brain structure and function mediate the relationship between FASD and internalising symptoms. Hypothesis 2: Brain connectivity between the amygdala, hippocampus and prefrontal cortex (specifically, lower FA, higher MD, and stronger functional connectivity) will mediate the association between FASD and symptoms of anxiety and depression.

  3. Identify baseline factors that predict changes of internalising symptoms over time in youth with FASD. Hypothesis 3: Weaker structural connectivity, stronger functional connectivity and smaller brain volumes at baseline will predict worsening anxiety and depressive symptoms over the subsequent 2 years.

Methods and analysis


We will recruit 125 children and youth with heavy PAE or FASD and 125 unexposed controls aged 7–18 years. This age range was chosen because: (1) FASD diagnosis typically occurs at or after age ~6–7 years in Alberta,79 (2) 7–18 years includes the most common ages of onset for anxiety disorders,80 (3) depression and anxiety symptoms are common in youth with PAE of this age range8 and (4) children this age are more likely to tolerate MRI scanning than younger children.81 Repeat assessments and MRI scanning will occur 2 years after baseline, which allows for measurable brain development within individuals,82 as well as meaningful changes in mental health symptoms. Approximately equal numbers of men and women will be recruited to be able to appropriately examine sex effects, and approximately half in Edmonton and half in Calgary. Informed written consent will be obtained from parents/guardians, as well as written assent from children/youth.

FASD/PAE group

Participants will be recruited through diagnostic clinics throughout Alberta (including the Pediatric FASD Clinic at the Glenrose Hospital in Edmonton and the Cumulative Risk Diagnostic Clinic at the Alberta Children’s Hospital in Calgary), Alberta Children’s Services, parent/caregiver support groups for FASD, community groups (eg, Calgary and Edmonton Fetal Alcohol Networks), as well as online advertisements and word of mouth.

Participants in the PAE group must have a diagnosis of FASD or confirmed heavy PAE at levels consistent with Canadian FASD diagnostic guidelines (≥7 drinks/week or ≥2 binge episodes at some point during pregnancy).1 Alcohol exposure will be confirmed via biological mother’s self-report, reliable observations by close family or friends, clinical observation, and/or medical, legal or child services records. Additional prenatal exposures (eg, tobacco, cannabis, illicit drugs) and adverse experiences (eg, lack of prenatal care, maternal mental health problems) will be documented where information is available.60 Participants with genetic disorders associated with significant intellectual or developmental impairments, diagnosed with a neurological disorder (eg, epilepsy, cerebral palsy), or with contraindications to MRI (ie, metal implants, dental devices, claustrophobia) will be excluded. Participants will not be excluded for common comorbid developmental disorders such as attention deficit hyperactivity disorder (ADHD) or learning disabilities.

Control group

Controls must have confirmed absence or minimal PAE (≤5 drinks total in pregnancy, with no binge episodes) via biological maternal report, no diagnosis of genetic or neurological disorders and no contraindications to MRI scanning. Controls will be recruited through online advertisements, parent groups in Edmonton and Calgary and word of mouth. Controls must not have significant intellectual or developmental impairments, but will not be excluded for neurodevelopmental disorders such as ADHD or learning disabilities.

MRI scanning

MRI scanning at baseline and 2-year follow-up will take place at the Alberta Children’s Hospital (Calgary) on a research-dedicated General Electric 3T MR750w system, or at the Peter S Allen MRI Centre (Edmonton) on a research-dedicated Siemens 3T Prisma. The imaging protocol is detailed in table 1.

Table 1

MRI protocol. Parameters are given for GE MR750w before Siemens Prisma; if only one set of parameters is given, they were the same for both scanners

Image analysis

T1-weighted images will be processed using FreeSurfer’s83 longitudinal processing stream.84 Each subject’s parcellation will be manually checked and receive minor corrections if necessary. Brain volumes of the left and right hippocampus, amygdala and prefrontal cortical areas (dACC, dlPFC, mPFC) will be extracted.

Diffusion data will be quality checked, brain extracted and corrected for eddy currents and head motion. FA and MD maps will be generated for each subject. Tractography (FA >0.2, angle <30) will be used to reconstruct white matter fibres connecting frontal and limbic regions (uncinate fasciculus, cingulum, fornix). FA and MD will be assessed within each white matter fibre bundle as primary variables of interest. The dual b-value scan also allows for more advanced diffusion models and analysis,85 86 which will be examined in follow-up analyses after primary aims are complete.

Assessment of rs-fMRI data will use AFNI and FSL tools.87 88 Each individual’s fMRI data will be registered to their anatomical (T1-weighted) scan, then to a paediatric brain template for 5–18 year olds.88 89 Volumes with high framewise displacement (>0.25 mm) will be identified and regressed out. Scans with <5 min of low-motion data will be eliminated. For each prefrontal region (dlPFC, mPFC, dACC) and the hippocampus and amygdala, averaged time courses will be generated. Correlations between time courses in each pair of regions will be analysed to measure functional connectivity.

Mental health assessments

Mental health assessments will occur at baseline, a subset of tests will be administered online at 1-year follow-up, and the full set will be administered again at 2-year follow-up (see table 2). Symptoms of depression and anxiety will be measured using both self-reports and caregiver-reports on the Behaviour Assessment System for Children (BASC-3),90 Child Depression Inventory-2 (CDI-2)91 92 and the Multidimensional Anxiety Scale for Children (MASC-2).93 The MASC-2 is a self-report assessment of anxiety symptoms in children and adolescents (8–19 years of age); MASC-2 will not be used for the youngest children aged 7 years. The CDI-2 is a brief questionnaire that measures cognitive, affective and behavioural signs of depression in children and adolescent ages 7–17 years. We will use the Beck Depression Inventory94 to assess depression symptoms in youth/young adults ≥18 years, and the PROMIS Anxiety Short Form95 to assess anxiety symptoms in young adults aged 20 years. The BASC-3 provides a validated assessment of a range of mental health symptoms, including anxiety and depression, while the CDI-2 and MASC-2 provide more specific measures of depression and anxiety symptoms, respectively, that are consistent with diagnostic criteria. The BASC-3 caregiver report and self-report (only children ≥12) will be used to assess behaviour.

Table 2

Questionnaires and assessments

To determine whether an individual meets diagnostic criteria for anxiety or depression, youth ≥12 years of age and all caregivers will complete a diagnostic assessment of internalising mental health disorders with a trained and reliable clinician using the mood and affective disorders subscales of Kiddie Schedule for Affective Disorders and Schizophrenia – Lifetime Version (K-SADS-PL).96 The K-SADS-PL is a semi-structured diagnostic interview and gold standard for assessing a variety of mental health disorders in youth based on Diagnostic and Statistical Manual of Mental Disorders (DSM-5) diagnostic criteria.97 The Diagnostic Interview for Anxiety and Mood, and OCD and Related Neuropsychiatric Disorders (DIAMOND)98 will be used for participants over 18 years.

We also examine the frequency, chronicity and location of pain of children and youth in the past 30 days.99 100 The Adaptive Behaviour Assessment System is a comprehensive parent report measure of the adaptive or daily functioning skills of children and youth across the lifespan.101 The Sensory Profile measures a child’s sensory processing patterns in various contexts (home, school and community settings).102

Cognitive assessments

IQ will be assessed using the Wechsler Abbreviated Scale of Intelligence – Second Edition103 2-subtest form at baseline to obtain an estimate of Full Scale IQ. The Rey-Osterrieth Complex Figure Test104 examines visuospatial ability and visuospatial memory in individuals between 6–89 years of age. The Wisconsin Card Sorting Test105 is an executive functioning measure used to determine cognitive flexibility and set shifting in individuals 6.5–89 years of age. The California Verbal Learning Test (CVLT-C) measures learning and long-term recall and recognition of verbal information in 5–16.11 year olds.106 The CVLT-3 will be used for youth ≥17 years. The NEPSY-II is a neuropsychological assessment tool for children aged 3–16 years of age that assesses functioning in six domains107; we will use the subscales of inhibition (measuring inhibition) and word generation (verbal productivity). The Wechsler Individual Achievement Test measures academic abilities in children and adolescents aged 4–50.11 years.108

Early adversity

Adverse postnatal exposures are assessed using questions adapted from the National Crittenton Foundation ACEs survey,62 109 a validated survey deemed acceptable by families and caregiving agencies.110 For children in foster or adoptive care, adverse experiences will be ascertained through child services records and interviews with biological and/or adoptive parents. With this information and information about prenatal exposures (see above), we will apply our own characterisation tool, which accounts for the timing, amount, and type of adverse exposure(s) experienced both prenatally and postnatally.60

Other variables

Caregivers will complete a comprehensive demographic survey that includes information about other individuals in the house, household income, parent education and ethnicity. Caregivers will be asked if youth have other diagnoses or are taking medications. Depending on the age and abilities of the youth, they and/or their caregiver will be asked to complete a short questionnaire about puberty. Youth will be asked to self-report their sex and gender. Sex will be included as a covariate in all analyses, and sex-by-age or sex-by-anxiety/depression interaction terms will be included where appropriate. Gender and its interaction terms will be used as additional covariates if numbers permit.

Statistical analysis

Statistical analysis will occur in SPSS (IBM), R ( and Matlab. Aim 1 will begin with a cross-sectional analysis using a regression model including age, sex, group and age-by-group interaction terms, run separately for each brain measure. Once longitudinal data is available, linear mixed effects models in R (using lme4 and lmerTest)111 112 will be used to determine developmental patterns of structural and functional connectivity for the FASD and control groups. Subject will be modelled as a random factor, with sex, age, group and age-by-group included in the model. For both cross-sectional and longitudinal analyses, postnatal adversity and IQ will be included as covariates. Mixed effects models will be run separately on volumes of each region, structural connectivity (FA) for each white matter tract, and functional connectivity (correlation) for connections between each pair of regions in the prefrontal–amygdala–hippocampus network (shown in figure 1). False discovery rate will be used to correct for multiple comparisons.

Figure 1

Key grey matter regions (A) and white matter connections (B) related to anxiety and/or depression symptoms. Volume of the regions in A, functional connectivity between pairs of regions in A and structural connectivity (diffusion metrics) of tracts in B will be measured. dACC, dorsal anterior cingulate cortex; dlPFC, dorsolateral prefrontal cortex; mPFC, medial prefrontal cortex.

For Aim 2, mediation will be carried out by testing the first pathway from the main predictor (PAE) to each brain measure (volume, structural or functional connectivity), controlling for age and sex of participants, and then testing the second pathway from each brain measure to each mental health measures (anxiety or depression symptoms), with age, sex and postnatal adversity as covariates. The overall mediation effect will be tested using percentile-based bootstrap CIs, computed from 5000 simulations.113 Caregiver-report T-scores from the CDI-2 and MASC-2 will be used as primary measures of depression and anxiety symptoms, respectively. BASC-3 T-scores on the anxiety and depression subscales of internalising symptoms will be used as secondary information. Self-report scores will be used for supplementary analysis, as they sometimes provide different information.114 115

For Aim 3, change in anxiety and depression symptoms will be calculated by subtracting the T-scores at Time 2 from the T-score at Time 1. Primary variables will be caregiver-reported CDI-2 and MASC-2 scores for depression and anxiety, respectively. Brain measures, postnatal adversity, sex, IQ, age and group will then be entered into a multiple regression model to determine which baseline factors predict anxiety and depression trajectories over time. Change in BASC-3 T-scores on the anxiety and depression subscales over the 2 years, as well as self-report scores on CDI-2 and MASC-2 will be used in a supplementary analysis. Initially, change in anxiety and depression outcomes will be used as a continuous measure. If enough youth meet criteria for a diagnosis of a depression or anxiety disorder (as measured by the K-SADS), a group analysis (those whose symptoms changed in severity to meet criteria for a diagnosis vs those whose did not) will also be conducted.

Power calculations

We collected preliminary data, including MRI, mental health assessments and postnatal adversity on 17 children with FASD and 19 controls without PAE aged 7–15 years. Control subjects (part of a different study)85 86 had follow-up scans and assessments ~2 years later. This preliminary data showed age-by-group interactions in structural and functional connectivity with effect sizes of 0.067–0.192 (partial eta2). To detect effects this size for Aim 1 with power ≥0.8 using an analysis of variance (ANOVA) with main effects and interactions, we require 112 individuals in total (calculated in G*Power). Preliminary data shows small-medium effects for both FASD-brain and brain-anxiety pathways in the mediation. According to simulations,116 these effects require a sample size of ≥162 total individuals to detect mediation using percentile bootstrap with power ≥0.8 (Aim 2). Linear regression of relationships between brain measures and changes in anxiety and depression in controls showed effects of r=0.4–0.6. To detect these effects (Aim 3), we require at least 130 participants in total (G*Power). Thus, we aim to have ≥162 individuals in total (81 per group) at time 1 (Aims 1 and 2), and ≥130 (65 per group) with longitudinal data (Aims 1 and 3).

Patient and public involvement

CT (co-investigator on the project) was an Associate Director of Alberta Children’s Services and was involved in study design. She has since moved on to a role as Assistant Professor at Mount Royal University and remains involved with the project. We continue to involve staff from Children’s Services in the design and execution of the study, and will involve them in interpretation and dissemination of findings. We also have active relationships with organisations serving individuals with FASD and their families, including the Calgary and Edmonton Fetal Alcohol Networks and CanFASD (co-investigator JP is Senior Research Lead/Intervention Lead at CanFASD). These organisations have provided study feedback and support and will assist with interpretation and dissemination of findings.

Potential limitations

Research on children and youth with FASD is complex due to confounding prenatal and postnatal exposures, missing information and behavioural difficulties. If recruitment or retention are lower than anticipated, we will recruit participants outside Calgary and Edmonton (eg, through the other 10 FASD Networks across Alberta). The strict diagnostic criteria used here will ensure that all participants have a minimum level of PAE, though exact amounts may not be known. We will use all available sources to characterise other risks and diagnoses in our participants and will statistically control for these in our analyses.60 In some cases, information will be missing, which is a challenging but unavoidable aspect of doing research in this population.


FASD is a common disorder (~4% of Canadians) with a very high societal cost (>$17B annually). Most individuals with FASD experience co-occurring mental health issues throughout their lifespan, but effective treatments are hindered by a lack of understanding of the neurobiological basis for these problems. The use of quantitative MRI to understand the brain abnormalities and atypical development patterns underlying mental health problems in youth with FASD is critical to early identification and appropriate intervention strategies to improve outcomes. This study will reveal developmental patterns of brain connectivity, identify the underlying neurological correlates of anxiety and depression symptoms in youth with FASD and identify baseline brain features that can predict the worsening of anxiety and depression symptoms. This knowledge is crucial for advancing research and identifying prevention and early intervention strategies, which will have substantial benefits for children and youth with FASD, their families and the public health system and society. This innovative project will address significant gaps in the literature, inform prevention strategies and promote early detection and intervention of internalising issues in children and youth with FASD.

Ethics and dissemination

This study has been approved by the University of Calgary Conjoint Health Research Ethics Board (REB17-0663) and the University of Alberta Health Research Ethics Board (Pro00093230). Data collection takes 4–6 hours for youth, and 2–3 hours for caregivers (table 1) and occurs at the Alberta Children’s Hospital (Calgary) or University of Alberta Hospital (Edmonton). Caregivers complete some questionnaires ahead of the visit, and additional questionnaires and interviews during the visit. Children complete the MRI scan, mental health and neuropsychological assessments and questionnaires during the visit. Children ≥12 years complete the KSADS interview. Breaks are given and support is provided as necessary for children and youth. Snacks, parking and an honorarium ($150 at baseline visit, $50 at 1-year visit and $250 at 2-year visit) are provided for each family. The honorarium reflects the commitment of the families, as this study requires substantial time commitments from both the child and the caregiver. If an MRI reveals any incidental findings, it will be referred to the site’s medical director (a neuroradiologist) for review and follow-up. If the mental health assessments reveal any concerns, youth will be referred by a child clinical psychologist (CAM or JP) for appropriate follow-up through the child’s physician or other appropriate mental health services.

Communication of our findings to other researchers will occur via publications in peer-reviewed journals and presentations at relevant conferences (eg, Organization for Human Brain Mapping, Canadian Academy of Child & Adolescent Psychiatry). As we publish our research findings, we will produce lay summaries and infographics for distribution to stakeholders via our website, our Twitter accounts, Kids Brain Health Network’s website (, social media (including Kids Brain Health Network’s YouTube, Facebook and Twitter accounts), and email.

Knowledge translation to the wider community will include direct communication (via reports, presentations, meetings) with diagnostic clinics and Children’s Services. Results will be presented at policy and practice meetings (eg, International Conference on Child and Family Maltreatment, Canadian Association of Pediatric Health Centres, Canadian Pediatric Society, Alberta College of Social Workers).



  • Contributors CAL, BG, CT, JP, CB, MB and CAM contributed to conceptualisation of this study. CAL wrote the first draft of this manuscript; all authors (CAL, BG, CT, JP, CB, MB and CAM) edited the manuscript and approved the final version.

  • Funding This work is supported by the Canadian Institutes of Health Research (PJT-162217).

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

  • Provenance and peer review Not commissioned; peer reviewed for ethical and funding approval prior to submission.