5 Chapter 5: Child Development and Behaviour

Mathieu Beaudoin Banville; Madison Prudencio; Sophie Shears; and Conor Barker

Throughout their lives, children and youth encounter difficulties related to learning, social relationships, decision-making, and managing emotions, including feelings of anxiety, depression, worry, and isolation (Eklund et al., 2020). Eklund and colleagues recognize that educators, parents, students, and community members can benefit from school psychologists’ expertise in identifying, understanding, and resolving long-term, chronic, and short-term challenges youth face. Supporting students’ ability to learn and teachers’ ability to teach is within a school psychologist’s area of expertise.

School psychologists are uniquely qualified individuals who apply their knowledge in mental health, learning, and behaviour to help students succeed academically, socially, and emotionally (Forman et al., 2013). More specifically, school psychologists improve academic achievement, promote mental health, support diverse learners, create safe and positive school climates, strengthen family-school partnerships, and improve schoolwide assessments and student progress (Eklund et al., 2020). School psychologists use standardized cognitive and educational assessments, which provide crucial information for parents, researchers, and educators (Thompson et al., 2018). Thompson and colleagues (2018) stated that to determine appropriate educational placements, develop intervention plans and measure progress, it is essential to understand the unique developmental strengths and challenges of students and use standardized, objective and reliable tools to classify behaviour. The primary focus of school psychologists is their role in the assessment process. Still, this process does not look the same for every individual, especially those with behavioural disorders.

This chapter addresses common developmental and behavioural disorders in children and adolescents and how school psychologists provide accommodations to support students through various means, such as interventions and consultations. Interventions and management of problem behaviours are done through behavioural management in the classroom. Behavioural management interventions are used to alleviate environmental stressors and provide accurate and helpful accommodations for individual students. Behaviour management models and strategies discussed in this chapter are used to support students with developmental and behavioural disorders, such as attention-deficit/hyperactivity disorder (ADHD), disruptive behaviour disorder, autism spectrum disorder (ASD). Anxiety and mood disorders are also touched upon in this chapter. We provide definitions of developmental and behavioural disorders, as well as developmental pathways and neurological research. Additionally, this chapter offers a variety of assessment tools and effective treatments to allow students to partner in the process and provide evidence-based mental health interventions in the school setting (Wiener, 2020). The objective of these assessment tools is to provide a detailed description of individuals’ problems, strengths, and adaptive skills, as well as examine environmental factors that facilitate and impede learning and psychological adjustment. This, in turn, leads to, recommending appropriate interventions and enhancing overall understanding of individuals, parents, and teachers (Wiener, 2020).

Learning Objectives

  • Describe the prevalence and risk factors for developmental and behavioural disorders to ensure appropriate intervention strategies.
  • Describe a school psychologist’s role in behaviour management, assessment, and intervention.
  • Define common developmental and behavioural disorders.
  • Describe developmental pathways and neurological research associated with common developmental and behavioural disorders.
  • Identify how a school psychologist assesses developmental and behavioural challenges in children and adolescents.
  • Name effective interventions associated with common developmental and behavioural disorders.

 

Mental Health Disorders in School Settings

Developmental and Behavioural Disorders

Common developmental and behavioural disorders in children are attention-deficit/hyperactivity disorder (ADHD), disruptive behaviour disorder, autism spectrum disorder (ASD), anxiety disorders, and mood disorders. ADHD is characterized by deficits in attention, hyperactivity, or impulsivity, which are first observed during the developmental period and are present in two or more settings. ADHD must also significantly impact functioning in two or more contexts. Disruptive behaviour disorder is persistent negativity, irritability, opposition, and annoying behaviours. ASD is associated with deficits in social communication, difficulties processing sensory information, and a restricted range of activities and interests. Anxiety disorders are associated with worries, preoccupations, thought distortions, and physical symptoms. Mood disorders are associated with low mood, sadness, lack of engagement, and irritability.  

School psychologists provide accommodations to support students through various means, such as interventions and consultations. Interventions and management of problem behaviours are done through behavioural management in the classroom. Behavioural management interventions are used in classroom settings to alleviate environmental stressors and provide accommodations for the individual student. Behaviour management models and strategies are used to support students with learning or behavioural disorders, such as attention-deficit/hyperactivity disorder(ADHD), disruptive behaviour disorder, autism spectrum disorder (ASD), anxiety disorders, and mood disorders. 

Prevalence 

Mental health is essential to children’s overall wellbeing and health. Mental health includes mental, emotional, and behavioural wellbeing. It affects how children feel and act in any situation (Stein et al., 2021). Mental disorders have traditionally been defined in clinical work, such as the Diagnostic and Statistical Manual (DSM-5), as a syndrome characterized by clinically significant disturbance in an individual’s cognition, emotion regulation, or behaviour that reflects a dysfunction in the psychological, biological, or development processes underlying mental functioning (Stein et al., 2021). This can lead to severe changes in how children typically behave, learn, or handle their emotions, leading to distress and problems navigating day-to-day life. Doll (1996) stated that the most common mental disorders school psychologists diagnose are ADHD, anxiety disorders, and other behavioural disorders.

Seventy percent of mental health disorders are identified before age 18 (YMHC, 2019). An estimated 1.2 million children and youth in Canada are affected by mental illness, yet less than 20% receive appropriate treatment (YMHC, 2019). Without the proper support, children with mental illness, caregivers, and families experience great suffering. Access to programs and services, including health promotion, will ensure that these individuals receive preventative care, treatment, and the support necessary to recover and thrive (CMHA, 2021).  

Risk Factors 

A critical period in a child’s life occurs at the start of school when the environment changes and their cognitive and social capabilities develop. Children’s academic and social trajectories form during this period, making it an opportune time to evaluate academic competence, behavioural competence, and social competence (Nelson et al., 2019). Huffman and colleagues (year) acknowledged that these three areas of competency are marked by success or failure. Children can experience success in later school years and develop increased independence and social confidence with less reliance on social services; on the other hand, children can be labelled delayed learners and placed on different learning tracks, which can decrease the likelihood of positive social exchange and peer support. This may lead to later behavioural, emotional, academic, and social developmental issues (Lanza et al., 2010). For instance, children who repeat a grade are at greater risk of developing several specific disorders, such as ADHD, obsessive-compulsive disorder (OCD), anxiety disorders, and major depressive disorder (MDD) (Huffman et al., 2000).  

Many risk factors can impact children’s development. Different risk factors can affect children’s learning outcomes, as suggested by Huffman and colleagues. Firstly, there is a risk factor that may be a fixed marker, that is, one that cannot change, like traits such as sex and ethnicity. Secondly, there is a risk factor that may be a variable marker, that is, one that can be demonstrated to change but, when changed, does not alter the probability of the outcome, such as income level or peer group. Finally, a risk factor may be a causal risk factor, one that can be changed and, when modified, does alter the risk of the outcome, such as a negative attitude or age.  

Some risk factors that affect children include prenatal risk factors (i.e., maternal medical issues), natal risk factors (i.e., premature or unusual delivery), postnatal risk factors (i.e., medical problems prolonging hospital stay), externalizing behaviour patterns during early childhood (i.e., overactive, impulsive, stubborn, temper outbursts, or aggression), internalizing behaviour patterns during early childhood (i.e., shy, socially withdrawn, cautious, or difficulty sleeping), childhood maladjustment (i.e., physically abusive to others, psychiatric hospitalization, or runaway), childhood maltreatment (i.e., sexually or physically abused), antisocial and psychiatric family history (i.e., domestic violence, mental illness, substance abuse, or convicted of a crime). Belonging to a disadvantaged minority group is also a risk factor for low academic achievement and family structure (i.e., one parent, low socioeconomic status, or no previous education) (Nelson et al., 2007).

Success or difficulties in academic settings are unlikely the result of just one factor. Behavioural issues are common in children with severe learning disorders. Understanding the factors associated with the increased risk of these difficulties is important for school psychologists to develop appropriate intervention strategies (Chadwick et al., 2000).  

Future Directions of Research 

While we know a great deal about common childhood developmental and behavioural disorders, and assessment and intervention processes, there is much that remains to be uncovered empirically. Topics for additional research include cross-ethnic and cross-sex studies on assessment tools, specifically when assessing anxiety in children and using the Spence Children’s Anxiety Scale (SCAS). Examining how assessment measures function across ethnic populations is essential because there is evidence of response bias among ethnic groups, putting test validity into question (Holly et al., 2015).

The lack of valid standardized assessments for children with learning disorders means that assessment results cannot always be translated into comprehensive treatment and intervention plans. Specific characteristics apply to each behavioural and learning disorder that interferes with the standardized assessment process, which can lead to invalid results. Thus, bettering the assessment process means future administration of these tests reduces the number of children who receive “untestable” results.

Another major concern for implementing prevention and early intervention plans in schools is the workload for counsellors, school social workers, teachers, and school psychologists. Time management is an issue for school psychologiststhere is often not enough time to decrease a child’s anxiety symptoms before they return to the classroom. Therefore, conducting some interventions (i.e., extensive exposure therapy sessions) at school is not feasible (Mychailyszyn et al., 2011). 

Classroom and Behaviour Management

The role of school psychologists in managing students with disruptive or problem behaviours has typically been limited to testing and diagnosis, with students often handled on a case-by-case basis (Hunter, 2003). School psychologists report they prefer reduced assessment activities and increased roles in other service deliveries, such as consultation, research, and intervention (Watkins et al., 2001). Interventions are implemented through classroom management, which seeks to establish a calm environment for students to partake in meaningful learning and positively contribute to students social and moral development (Hart, 2010).

Behavioural management interventions, models, and strategies are mainly used to support students with learning or behavioural disorders, such as attention- deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), disruptive behaviour disorder (DBD) (e.g., oppositional defiant disorder, conduct disorder), anxiety, and mood disorders. To achieve success with behaviour management, school psychologists use diagnostic practices, interventions, theories, and models, and collaborate with community members. 

Understanding Behaviour  

Before school psychologists can make a diagnosis and support students, they must have an in-depth understanding of behaviour and how behavioural disorders affect individuals. Recently, child health professionals, including school psychologists, have failed in their attempts to agree on a cross-cultural definition of behavioural disorders (Gaoni et al., 1998), which may contribute to the diversity of methods used for studying behaviour (Uher, 2016). In everyday life, behaviour is pervasive and intrinsic, with researchers seeming to rely more on an intuitive understanding of behaviour instead of scientific definitions (Uher, 2016).  

The term behaviour disorder is used to describe individuals who violate current social norms and act in ways that society deems antisocial (Gaoni et al., 1998). Individuals with behavioural disorders also display repetitive and persistent maladaptive patterns (Gaoni et al., 1998), such as disruptive behaviour in the classroom. Behaviour is believed to be not the property of a stimulus but rather something that emerges from interactions between the stimulus and the mind of an individual (Vandenbosch & Higgins, 1996). 

Environment heavily influences behaviour; thus, the effectiveness of interventions can be increased by drawing on behavioural theories that incorporate social, cultural, and economic influences (Davis et al., 2015). From this, one can see how behaviour is learned (often stemming from one’s environment). Therefore, behaviour can be unlearned or managed through behavioural interventions. To understand what motivates specific behaviours, it is important to understand the factors that control problem behaviours. The functional control of problem behaviours has been conceptualized through available analysis as involving attention (obtain/access), escape (avoidance), sensory reinforcement (self-regulation), and tangible factors (power/control) (Carr, 1994), with each influencing some motivating factor of behaviour.  

There are many models implemented by school psychologists to help identify problem behaviours and understand behaviour through the lens of the individual. The functional behavioural analysis model, also known as antecedent-behaviour-consequence (ABC), combines descriptive and experimental data to understand behaviour as a function of one’s environment (McMahon et al., 2020). This model analyzes the immediate antecedent (i.e., what occurred before the behaviour, environmental factors) and consequence (i.e., what happened after the conduct occurred, environment and external responses) of a particular behaviour (McMahon et al., 2020). Functional behavioural analysis is used to help teachers develop intervention plans for behaviours, such as classroom aggression and disruption. It involves meticulous observation and documentation of events as they occur (McMahon et al., 2020). This is particularly important since one of school psychologists’ main roles is identification of problem behaviours and diagnosis of behavioural disorders to implement effective interventions. 

Referral & Diagnostic Practices 

Students may access school-based services as part of a multitiered system of supports; however, these services have limitations, such as lack of time, inability to address severe problems, and inadequate numbers of related service centers (Villarreal, 2018). Therefore, it is required that schools are prepared to make referrals to community-based mental health providers to help identify and manage problem behaviours. A referral is appropriate when a school-based professional is unable to identify and fully meet a student’s needs, or when it is necessary to involve other service providers, such as school psychologist (Villarreal, 2018). Referrals are a necessary practice for schools in implementing universal mental health screening (Villarreal, 2018), such as diagnostic screenings conducted by school psychologists. A school psychology referral may range from academic problems, such as reading, writing or math, or behavioural problems, such as aggression or repetitive disruption (Bramlett et al., 2002). 

Referrals are a vital part of mental health practice in schools (Villarreal, 2018). Current models emphasize service provision that collaborates between communities, families, and schools, in which school psychologists are in a key position to address children’s mental health problems (Ohan et al., 2015). Schools can refer children to community agencies for services or invite agencies to provide services within the school setting (Herman et al., 2004). Mental health consultants (e.g., social worker, school psychologists) are occasionally asked to complete observations in the school environment to attempt to identify antecedents and purposes of behaviour to help inform meaningful interventions (Miranda et al., 2022).

Mental health consultants also speak with parents to see if they observe behavioural concerns at home (Miranda et al., 2022). Assessing an individual in all environments provides a more in-depth conceptualization of the problem behaviours expressed, and what type of external factors may be influences them. Research finds parents of individuals with problem behaviours have more positive attitudes toward general practitioners (GP) compared to mental health professionals (Ohan et al., 2015), such as school psychologists. This is important to note as initial identification of problem behaviours is done by an individual’s community (e.g., parents, teachers, caregivers), then they are referred by general practitioners and then to a school psychologist for diagnosis. 

Assessing children’s mental health requires a range of current and past data about their functioning in a variety of systems (e.g., school, home) from multiple informants (e.g., patient, parent, teacher) (Sattler et al., 2019). Common behavioural assessment methods are structured behavioural interviews, behaviour checklists, rating scales, and systematic observations (Shapiro & Heick, 2004). School psychology assessment practices primarily consist of measures of intelligence, standardized individual academic achievement, perceptual-motor performance, and projective techniques, regardless of the reason for referral (Shapiro & Heick, 2004). According to research, the top-ranked measures used by school psychologists for assessment in behaviour, social, emotional domains include interviewing, behavioural observations, and informant reports (e.g., CBCL, Conners, Abbreviated Conners Teacher Rating Scale) (Shapiro & Heick, 2004). Additionally, it was reported that experienced school psychology practitioners add methods consistent with behavioural assessment principles (i.e., projective and personality assessments) to their assessment toolkit (Shapiro & Heick, 2004). This practice may aid in the identification of individuals who require support, as well as the implementation of effective behaviour management interventions. 

Behaviour Management & Intervention 

For behaviour management, referral, and diagnostics to be successful, school psychologists must have an in-depth understanding of widely used models for behavioural interventions, such as Response to Intervention (RTI). RTI is different from more traditional prevention methods as it can extend problem solving within educational settings and communities (Kratochwill et al., 2007). Professionals implement multitiered models of prevention and intervention services, programs, and practices related to RTI (Kratochwill et al., 2007) to help support individuals manage their problem behaviours.

Used as a model for improving student outcomes, RTI is based on frequent and intense student performance monitoring (Prasse et al., 2012), as seen in class assessments and intervention follow-ups done by the community (i.e., parents, teachers, psychologists). Best practice and use of RTI suggest implementing a continuum of effective behavioural support, including primary-level prevention and intervention procedures, secondary-level targeted or supplemental procedures (e.g., small-group instruction, focused classroom management programs), and tertiary-level intensive interventions for students who need support (e.g., individualized instruction, functional assessment-based intervention) (Hawken, 2006; Kratochwill et al., 2007). The primary purpose of RTI interventions is to assist students in adapting to the general education classroom (Ardoin et al., 2005). One of RTI’s main uses is also an essential component for changing, modifying, or intensifying interventions (Gresham, 2004).  

Within the three tiers of intervention, the first tier focuses on core instruction directed at all students (e.g., core curriculum), with students’ responses to core education determining the need for increased intervention (Prasse et al., 2012). Data collected in tier one can be used to identify students with dual discrepancies who need further support; however, it is important to note that tier one instruction works for most students (Ardoin et al., 2005). Dual discrepancy refers to if a student’s rate of growth and level of performance are more than 1 standard deviation below the mean level and slope of their classmates. If this is the case, students are moved up to the next tier (Ardoin et al., 2005).

In tier two, students who do not respond to class-wide interventions (i.e., tier one) are exposed to small-group supplemental instruction (e.g., altered course curriculum) (Ardoin et al., 2005). Students who do not respond to the second tier are provided with intensive individualized intervention and instruction in tier three, with the help from outside supports and resources (e.g., outside referral, clinical psychologist) (Ardoin et al., 2005).  

Behavioural interventions have many broad theoretical categories (e.g., applied behavioural analysis, social learning theory, cognitive behaviour therapy) (Gresham, 2004). Each behavioural intervention model assumes a different cause and maintenance of problem behaviours. Some problem behaviours require interventions using one model, while others need more intensive intervention, utilizing multiple models simultaneously (Gresham, 2004). Applied behavioural analysis descends from functional behavioural analysis (i.e., ABCs of behaviour) developed by Skinner in 1953. Most school-based interventions rely on applied behavioural analysis to determine the function a specific problem behaviour serves in that specific environment or situation (Gresham, 2004).

The social learning theory model determines which environmental events are attended to, retained, and subsequently performed. It utilizes concepts of vicarious learning and roles of cognitive mediational processes. Additionally, it describes an individual’s behaviour in terms of the change it has on an environment and vice-versa (Gresham, 2004).

Cognitive behavioural therapy (CBT) assumes an individual’s behaviour is mediated by their cognitions in response to environmental events (Gresham, 2004). The goal of CBT is to change maladaptive cognitions and emotions, which in turn helps modify behaviour. Interventions based on these models are superior to other psychotherapy methods (e.g., humanistic methods or psychodynamic) (Gresham, 2004), with evidence pointing towards effective interventions that include multitiered methods and models (i.e., combination of models and interventions). Based on training and experience, school psychologists design, implement, and evaluate behavioural intervention services in schools (Gresham, 2004). 

Community Supports 

            Engaging the community is critical for intervention success. Teachers must be able to seek assistance from administrators, school districts, specialists (e.g., psychologists, consultants, counsellors), and colleagues, as well as work with families to provide continuous care and support (Barker & Lugt, 2022). Community engagement is defined as involving communities in the decisions making, planning, design, governance, and delivery of services in interventions (O’Mara-Eves et al., 2015). Engagement activities can take many forms, such as information-sharing, consultation, joint decision-making, joint action, as well as supporting community interests. Advocated as a practical strategy, community engagement can be used to reduce health inequalities (e.g., housing, education, income) and alleviate stressors on education systems (e.g., time constraints, lack of resources) (O’Mara-Eves et al., 2015). Inclusive philosophy suggests all students should be supported in the classroom, but stressors on education systems result in students being referred to alternative settings for behaviour management and intervention (Barker & Lugt, 2022). 

            Alternative settings are used for students with the most challenging educational and behavioural needs, as well as those who require intensive interventions that extend beyond the public school environment (Simonsen et al., 2011). Settings can include public and private alternative schools, special day or residential treatment facilities, and hospitals or clinical schools. Although alternative settings may be multidisciplinary (i.e., public health, mental health, family, correctional facilities), alternative settings should primarily be based on education (Simonsen et al., 2011). An emphasis on education is important as the goal of alternative placement settings is to meet students educational needs and improve behaviour so that they can return to a less restrictive and normalized educational setting (Simonsen et al., 2011; Sugai & Homer, 2006). 

Attention-Deficit/Hyperactivity Disorder

Definition 

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders (Ayano et al., 2020). From 2003 to 2007, the prevalence of ADHD in American youth aged four to seventeen increased from 7.8% to 9.5% (Danielson et al., 2018). The worldwide prevalence is 5.29% (Polanczyk et al., 2007) In Canada, the prevalence is estimated to be around 8.6% (Espinet et al., 2022). The high prevalence of ADHD is associated with high societal costs, estimated to be between $38 to $72 billion. The financial burden of ADHD is observed through children utilizing more services, as well family members requiring outpatient support and mental-disorder-specific care (Dieleman et al., 2016; Doshi et al., 2012).  

ADHD is characterized by symptoms of inattention, impulsivity, delay-aversion, deficits in working memory, and reward sensitivity. It may also be accompanied by hyperactivity symptoms (Danielson et al., 2018). Children with ADHD have difficulty suppressing inappropriate actions and controlling behavioural inhibition, suggesting difficulty in top-down processing. These difficulties can also be explained by the triple pathway theory, which describes how difficulty in executive function (cold cognition), reward processing (hot cognition) and timing/temporal deficits are homogenous among children with ADHD (Buitelaar et al., 2019; Sonuga-Barke et al., 2010).  

Developmental Pathways & Neurological Research 

Because of the nature of ADHD symptoms, children may have trouble at school. For example, it is not uncommon for children with ADHD to fail academic assessments. This is partly due to difficulty listening and paying attention to teachers. Impulsivity may also lead to students beginning a project before being fully aware of the task’s requirements, which contributes to poor academic achievement due to a failure to meet expectations. Academic underachievement can result in academic anxiety and reduced employability as an adult. Individuals with ADHD may find it challenging to keep their job and experience increased poverty as a result. Moreover, people with ADHD are more likely to abuse illicit substances and be diagnosed with substance abuse disorder. Their impulsive nature may expose them to more risks, which can lead to injuries and frequent hospitalization (Danielson et al., 2018). 

Dopamine is a neurotransmitter involved in attention, cognition, executive function, and reward processing. Children with ADHD have reduced dopamine synaptic markers in the reward pathway of the brain (Volkow et al., 2009). Functional magnetic resonance imaging (i.e., fMRI) studies of children with ADHD show decreased activity in the frontal, parietal, and medial regions (Buitelaar et al., 2019). Activation in the frontal and tempo-parietal nodes is associated with severity of ADHD, while the inferior frontal nodes are correlated with the stop signal. These neural activations offer evidence to explain response inhibition and ADHD severity (Buitelaar et al., 2019). Furthermore, ADHD patients often have a reduction in gray matter localized to the right lentiform nucleus and extending to the caudate nucleus while having slightly increased gray matter volume in the left posterior cingulate cortex (Nakao et al., 2011).  

How is ADHD Assessed?  

According to the DSM-5, symptoms must be present in children for at least six months in two social settings (e.g., home, school, stores) and must impair academic, social, or occupational functioning. The onset of the symptoms should occur before the age of 12 (Austerman, 2015). ADHD has two dimensions for diagnosis: inattention and hyperactivity. Children must show at least six symptoms of either inattention or hyperactivity

Inattention symptoms refer to behaviours such as frequently losing or misplacing items, which can lead to difficulty completing tasks. Children may become sidetracked by external or frivolous stimuli. This can be observed through difficulty finishing assignments and trouble maintaining attention during specific tasks. Failure to listen when spoken to directly and lack of following instructions are also common. They have difficulty organizing belongings and often avoid or procrastinate tasks that require sustained mental effort.

Hyperactivity symptoms include movements such as fidgeting or tapping the hands or feet. Children may leave their seats when they are expected to remain seated. They may run and climb in inappropriate situations. They are often unable to partake in leisure activities quietly. They may talk excessively and present impulsive behaviour, such as yelling out answers before questions have been completed. It can be difficult for them to wait their turn; thus, they may intrude on or interrupt others (American Psychiatric Association, 2013). 

The DSM offers a good starting point for diagnosis, but it alone is not comprehensive. An ADHD diagnosis should be made with “developmental context” in mind. This means that symptoms must be inappropriate in relation to the child’s developmental age. For example, a 7-year-old should not be expected to maintain the same level of attention a 13-year-old. The younger child may not be able to stay as quiet and focused as the older child for a long period of time (Danielson et al., 2018).  

There is a battery of reliable tests that can be used to assess ADHD in children. Tests like go/no go are supported by evidence (Kuntsi et al., 2005). Parent and teacher rating scales like the Vanderbilt ADHD Diagnostic Scale or the ConnersThird Edition show high correlations with ADHD. Self-report questionnaires such as the Diagnostic Interview for Children and Adolescents are also evidence-based diagnostic tools. To assess ADHD, a combination of interviews, in addition to an objective scale administered by a professional, provides the best overview of a child’s situation (Austerman, 2015). 

Effective Interventions 

Behavioural therapy is recommended by the American Psychological Association as a first-line treatment for ADHD (Danielson et al., 2018). Children who undergo interventions (e.g., the Incredible Years) show symptom improvement up to one year after treatment (Jones et al., 2008; Webster-Stratton et al., 2013). In schools, teachers can use neurofeedback training; empirical studies show it reduces inattention and hyperactivity-impulsivity symptoms at the 6-month follow-up mark. Because of the potential stress having a child with ADHD can cause (Theule et al., 2011), familial therapy is also recommended. Interventions such as Parent-Child Therapy can help parents manage behavioural issues and promote consistent parenting strategies.  

The Triple P Positive Parenting Program is a parental intervention that increases parent confidence and improves child attachment. It also decreases dysfunctional parenting practices such as laxness, overactivity, and verbosity (i.e., the reliance on lengthy verbal responses or the use of ineffective language) (Austerman, 2015; Treacy et al., 2005).

ADHD can also be managed with pharmacotherapy, using psychostimulant drugs. Children with ADHD are usually prescribed amphetamine or a derivative like Ritalin or Concerta (Johnson et al., 2021). The use of psychostimulants alone is often enough to reduce the impairment caused by ADHD symptomsThese drugs block dopamine transporters, which increases dopamine levels in parts of the basal ganglia (e.g., the striatum) (Austerman, 2015). Johnson et al. (2021) found that youth treated with psychostimulants significantly improved on measures of verbal memory, processing speed, and working memory on the WISC.

Disruptive Behaviour Disorder

Definition 

Disruptive behaviour disorder (DBD) includes a constellation of disorders marked by maladaptive behaviors that exert a disruptive influence on the dynamics and functioning of the social milieu.. Behaviours are on a spectrum and include frequent non-compliance and temper tantrums (Wright et al., 2013), which can sometimes harm others (Loeber & Burke, 2011). A child with oppositional defiant disorder (ODD) shows emotional dysregulation (e.g., they have a hard time controlling their temper) (Steiner & Remsing, 2007), emotional overreaction, and affective liability (Burke et al., 2005; Cavanagh et al., 2014). The lifetime prevalence of ODD is estimated to be 10.2% (Nock et al., 2007).  

Conduct disorder (CD) is characterized by repetitive aggressive behaviours toward peers, parents, teachers, and caregivers accompanied by frequent rule breaking. More specifically, youth with CD show a pattern of disrespect for the basic rights of others and disregard for age-appropriate rules and social norms (Euler et al., 2015; Greenfield et al., 2017; Loeber et al., 2000). CD is associated to peer rejection, school suspension, expulsion, and criminal behaviour.

Because of the risk to others, CD is an important mental health problem (Frick, 2016). Little is known about the societal cost of DBD (Christenson et al., 2016). However, the estimated public cost of CD over a a 7-year period was $70,000 (Foster et al., 2005). Furthermore, costs related to psychotherapy for victims of crime, often perpetrated by individuals with CD, was estimated to be more than $5.8 billion a year (Cohen & Miller, 1998). 

Developmental Pathways & Neurological Research 

The recurring nature of negative behavioural patterns can impair children on social and academic levels (Hamilton et al., 2008). Youth with DBD have fewer positive peer interactions, are less popular with peers, (Evans et al., 2016) and are more frequently reported as being annoying to peers (Lahey et al., 2004). Children may also have impaired relationships with parents and teachers. Social impairments can lead to academic difficulties; for example, these students may have a hard time completing assignments in the classroom and at home (Burke et al., 2010; Lahey et al., 2004).  

Oppositional behaviour may emerge two to three years prior to preschool (Steiner & Remsing, 2007). The stability of the diagnosis is approximately 67%, yet most children outgrow ODD after roughly three years (Loeber et al., 2000; Steiner & Remsing, 2007). Despite this, approximately 20% of ODD cases are linked to antisocial personality disorder in adulthood. These individuals are also more prone to substance use in adulthood (Grizenko & Pawliuk, 1994). For instance, there is an association between ODD and alcohol addiction (Ghosh et al., 2014), as well as drug abuse and addiction later in life (Nock et al., 2007). 

Developmental pathway refers to the process of identifying individuals who are at risk for developing more problem behaviours compared to those who develop fewer behaviours. It provides a rubric of an escalation model. Since violence emerges in middle to late adolescence, early identification is key to helping break the cycle (Loeber & Burke, 2011).

Researchers used factor analysis to identified three main pathways related to ODD. The first is the Authority Conflict Pathway, which begins prior to the age of 12 where stubborn behaviour often targeted at teachers or parents is observed. This behaviour can evolve into authority defiance, disobedience, and authority avoidance. The second is the Covert Pathway, which usually begins with minor behind-the-scenes behaviours such as shoplifting and frequent lying. This behaviour can evolve into property damage, moderate delinquency (e.g., fraud) and serious delinquency (e.g., auto theft or burglary). The Overt Pathway begins with minor aggression including bullying which can evolve into physical fighting (or gang fighting) and more serious violent crimes (e.g., rapes or attacks) (Vassallo et al., 2002). A child with a conduct disorder diagnosis will likely experience more severe internalizing and externalizing problems over time (Evans et al., 2016).  

Internalizing problems are associated with mood disorders, including depression and anxiety (Mikolajewski et al., 2017). Depression is positively correlated with severity of ODD symptoms (Loeber & Burke, 2011). ODD is also a strong predictor of depression symptoms in early adulthood (Copeland et al., 2009). Neurological research suggests abnormality in decision-making is mediated by the dorsomedial and prefrontal cortex, as well as in the reward-processing region of the ventral caudate. These two parts appear to be overactivated; precisely, dysfunction in the medial prefrontal cortex (mPC) principally in the ventral and medial mPC affects the control network (Alegria et al., 2016). 

How are Disruptive Behaviour Disorders Assessed?

Even though diagnosis often occurs in late preschool or early school-age children, diagnoses are not age-restricted (Steiner & Remsing, 2007). ODD is characterized by recurrent patterns of disruptive, hostile, defiant, disobedient, or argumentative behaviours targeted toward peers and authority figures that persist for more than 6 months (Gomez et al., 2022; Loeber et al., 2000; Loeber & Burke, 2011; Munkvold et al., 2011; Riley et al., 2016). 

An important aspect of diagnosing DBD is biological sex. Diagnostic criteria do not accurately identify CD and ODD in preadolescent girls (Steiner & Remsing, 2007). Female teenagers typically do not use physical aggression, but rather use indirect verbal violence and relational aggression. For instance, females may use character defamation, alienation, and ostracism directed at “friends” (Björkqvist et al., 1992; Crick & Grotpeter, 1995). These types of behaviours are not represented among CD symptoms and can make it difficult to clinically diagnose teenage girls (Loeber et al., 2000.) Different methods can be used to identify developmental pathways. For example, the age of onset for different behaviours, the prediction of onset by the presence of other behaviours, and the prediction of change in behaviour by the change in another behaviour.

The onset of ODD is often preceded by the onset of conduct disorders (Nock et al., 2007). The severity of ODD symptoms is a significant predictor of CD symptoms the following year, which suggests a homotypic continuity (Loeber & Burke, 2011). Therefore, to assess disruptive behaviour, it is imperative to view the child’s history, looking for symptom increases to notice any increases in severity that could suggest an evolution of ODD into CD.

Self-report of symptoms, official delinquency records, and parental reports are notorious for underreporting the age of onset and obfuscating the developmental sequence that leads to delinquency (Loeber & Burke, 2011). Externalizing disorders are generally predictive of conduct problems. For instance, callousness (i.e., cruel and insensitive disregard for others) and delinquency is associated with being headstrong. Therefore, children who purposely engage in conflict with authority figures, violate rules, and blame their peers are more at risk to begin fighting, bullying, lying, stealing, and cheating (Whelan et al., 2013).  

Effective Interventions 

While most children outgrow DBD, effective interventions help those who do not (Loeber et al., 2000). For instance, ODD can be comorbid with other disorders and if left untreated, it is often a predictor of CD later (Loeber et al., 2000); therefore, early intervention is key for success. Treatment of ODD should be a non-pharmacologic approach because medication tends not to get to the root cause of the disorder. Although medications is useful to treat comorbid disorders (e.g., ADHD or anxiety disorders), this is not the case with the case with DBD. Improvement is mostly seen during the treatment period and does not persist beyond the use of medications. Another problem is that most samples used in pharmacological research were male subjects, which reduces the generalization of medication efficacity (Hood et al., 2015). Therefore, research has shown that behavioural therapies are the most effective intervention for DBD 

Research suggests that the quality of the relationship between parent and child is influenced by one other. In other words, the parents react to the child reacting, and the child reacts to the parent reacting, hence the snowball effect (Chen et al., 2021). Parent Management training is a group therapy based on the work of Gerald Patterson. He viewed ODD as a pattern of learned behaviour fostered by reciprocal negative interactions between the child and the parent, which relies on operant conditioning (Hood et al., 2015). Therefore, family therapy includes parents and helps them manage their stress and increase their confidence level. To stay consistent in their response to consequences or reinforcement by ignoring negative attention-seeking and rewarding positive behaviours. The goal for the clinician is to improve family cohesion and break the cycle of reactivity (Brestan-Knight & Eyberg, 1998). Typically, psychotherapies that include both parent and child are found to be the most effective (Webster-Stratton, 2001). Ultimately, in terms of successful interventions, caregivers should reinforce positive responses by the children and ignore or explicitly discourage negative behaviour to disrupt the cycle of argumentativeness and attention-seeking (Hood et al., 2015). 

Autism Spectrum Disorder (ASD)

Definition 

Autism spectrum disorder, also known as ASD, is characterized in the DSM-5 as a neurodevelopmental disorder. In 1991, ASD became a distinct category for special education eligibility within amendments to the Individuals with Disabilities Education Act (IDEA).  With these revisions and inclusions of autism in IDEA, school-based identification was found to be quintupled (Sullivan, 2013). Earlier versions of the DSM, such as the DSM-III-R and DSM-IV, included subtypes such as autistic disorder, Asperger’s disorder, Rett’s disorder, childhood disintegrative disorder, and pervasive developmental disorder not otherwise specified (PDD-NOS) (Wiggins et al., 2019). The DSM-5 no longer includes these subtypes, instead replacing all previous diagnoses with a single diagnosis of autism spectrum disorder (5th ed.; DSM-5; American Psychiatric Association, 2013).  

ASD consists of five criteria for diagnosis, with Criterion A and Criterion B being its essential features. Compared to previous iterations, the DSM-5 states that individuals must meet all three social criteria and only two behavioural criteria to be diagnosed with ASD. Social criterion (Criterion A) features deficits in reciprocal social communication and nonverbal communicative behaviours for social interaction (i.e., developing, managing, and understanding relationships). Criterion B (a behavioural criterion) features deficits in repetitive patterns of behaviour, interest, or activities (5th ed.; DSM-5; American Psychiatric Association, 2013).

There are also three additional criteria for diagnosing ASD: Criterion C, Criterion D, and Criterion E (5th ed.; DSM-5; American Psychiatric Association, 2013), which are a collective triad of symptoms. In Criterion C, symptoms must be present in the early developmental period but may also not fully manifest until social demands exceed limited capacities or individuals learn how to mask it later in life (5th ed.; DSM-5; American Psychiatric Association, 2013). If symptoms cause clinical and significant impairment or debilitation in social, occupational, or other important areas of current functioning, they fall in Criterion D (5th ed.; DSM-5; American Psychiatric Association, 2013). Criterion E consists of ruling out the possibility of an intellectual disability or any other disorders that may explain an individual’s symptoms. (5th ed.; DSM-5; American Psychiatric Association, 2013). However, it is important to note that ASD and intellectual disabilities often co-occur. If social communication is below the typical development level of an individual for their age, a comorbid diagnosis of ASD and intellectual disability should be considered (5th ed.; DSM-5; American Psychiatric Association, 2013). 

Developmental Pathways & Neurological Research 

The study of inherited factors involving the etiology of disorders using methods from medical and clinical epidemiology is known as genetic epidemiology (Szatmari et al., 1998). Autism spectrum disorder has been established by genetic epidemiologists as highly heritable, affecting approximately 1 in 100 children and adolescents (Charman et al., 2011). Genetic epidemiology looks to answer four specific questions (i.e., Is a disorder inherited? What phenotype was inherited? How is it inherited/transmitted? What is the nature of the genetic mutation influencing the development of a disorder?) (Szatmari et al., 1998). Several diverse genetic factors have been identified and explored in relation to the development of ASD, which may contribute to ASD being a high-risk disorder. (Buxbaum & Hof, 2011).  

Evidence suggests that ASD includes a range of considerable phenotypic heterogeneity, in terms of presentation at certain ages and across development, which likely differ in underlying etiology (Charman et al., 2011). These phenotypic regions, including the frontal and temporal neocortex, the caudate, and the cerebellum, contribute to both social and non-social deficits in ASD (Charman et al., 2011; Takumi et al., 2020). For example, recent studies involving structure of white and grey matter, as well as functional imaging of cortical networks, have demonstrated a degree of underconnectivity in certain networks. This research found that adolescents with ASD have weaker connectivity between the posterior hub, also known as the default network (primarily the medial prefrontal cortex, posterior cingulate cortex, and angular gyrus), and the superior frontal cortex compared to a control group (Buxbaum & Hof, 2011). This indicates that the default mode network is partially responsible for task initiation and de-initiation, often becoming active when individuals are at rest or relaxed. When an individual goes to initiate a task, this default mode network decreases in activity (Mars et al., 2012), which signifies that individuals with ASD may suffer from trouble with things such as task initiation, self-motivation, and relaxation.

There has also been compelling data showing ASD has profound etiological heterogeneity, which can include diagnoses of as many as one hundred or more chromosomal abnormalities and known genetic disorders (Buxbaum & Hof, 2011). It is important to note that research into the biology of ASD, its development, and how it relates to clinical and cognitive domains is still ongoing. As such, diagnoses of ASD are not based on the genetic influences, etiologies, or phenotypes. Instead, diagnoses are based on expert observation and assessment of behaviour and cognition by clinical and medical professionals (Geschwind, 2011), which in turn has helped to further aid research of the biological implications in ASD.  

How is Autism Spectrum Disorder Assessed?

Publications detailing evaluations (i.e., assessments) of children with autism spectrum disorder in educational settings (e.g., schools) are lacking in recent years compared to clinical settings (McClain et al., 2018). In a survey given to school psychologists, researchers found about 25% of that population reported using best practice evaluations and assessments for students with ASD in schools (McClain et al., 2018). Interestingly, the same researchers documented gaps between current practice and best practice implications for assessing and diagnosing students with ASD. Authors highlighted the importance of being conscious of the direct impact school psychology journals have on practitioners and trainers, and the influence those publications have on skills and service quality (McClain et al., 2018). In a review of school psychology journals from 2002-2012, the above researchers found that only thirty-eight publications focused on ASD specifically. Many of these publications focused less on practices related to school-based assessments, instead reviewing etiology and intervention effectiveness (McClain et al., 2018). The proposed explanation researchers gave for the gaps in the literature and best practice was due to a lack of ASD-focused assessment publications in school psychology journals, as well as a lack of emphasis on school-based assessment practices (McClain et al., 2018).  

            Although there is still much exploration on best practices for evaluation and assessment, there are many effective ways to identify and assess students with ASD. Considered to be one of the first steps in best practice assessment is interviews from several sources (e.g., caregivers, parents, and teachers) to assess core symptoms (Christopher & Lord, 2022). In addition to assessing symptomatology, interviews gather key medical, family, and psychosocial history, focusing on developmental milestones and learning ability.

The Autism Diagnostic Interview-Revised (ADI-R) is the gold-standard comprehensive autism interview, which includes a lengthy interview and extensive training (Christopher & Lord, 2022). The ADI-R has been found to consistently demonstrate high diagnostic accuracy with symptoms found in the DSM-5 and has been specifically recommended for use in schools by the National Research Council in 2001 (Aiello et al., 2017; Christopher & Lord, 2022).

In addition to the ADI-R, one of the most widespread and well researched assessment tools is the Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) (Christopher & Lord, 2022). Due to its powerful psychometric properties, the ADOS-2 has seen a rise in use for assessment purposes in clinical and educational settings (i.e., instead of its intended or original purpose of research) (Chojnicka & Pisula, 2017; Christopher & Lord, 2022).

The ADOS-2 is semi-structured play-based assessment, which includes five modules, each testing an individual at different ages and levels of developmental. Researchers are currently suggesting that due to its high interrater and test-retest reliability, as well as high standardization and validity measures, the ADOS-2 is one of the gold standards of best practice for structured observations (Chojnicka & Pisula, 2017). 

The heterogeneous nature of ASD makes accurate diagnosis challenging for new and experienced professionals (Christopher & Lord, 2022). Diagnostic and assessment practices for ASD normally rely on screening instruments, rather than the recommended comprehensive diagnostics measures (Aiello et al., 2017). Practitioners are ultimately encouraged to use individualized multi-informant approaches. Researchers propose the reason for this is due to the discrepancy seen in academic profiles related to ASD, as well as the argument that no measure perfectly encapsulates any one skill (Harry et al., 2022). Using best practices (i.e., the gold standard) to assess and diagnose in schools provides information on appropriate interventions and educational placements for individuals with ASD on their own and in the community.

Effective Interventions          

Intervention for individuals with ASD in academic settings often requires interdisciplinary care coordination. The concept of care coordination assumes a central role within the National Association of School Psychologists Model for Comprehensive and Integrated School Psychological Services (i.e., NASP Practice Model) (Shahidullah et al., 2020). Care coordination should be done between primary care clinicians, community-based providers, and school personnel (e.g., school psychologists). Unfortunately, school psychologists have difficulty collaborating care with outside supports and providers, specifically due to eligibility criteria for medical versus educational diagnosis, lack of specified roles, and restrictive infrastructure surrounding shared information (Shahidullah et al., 2020). It is important that outside supports (e.g., primary care practitioners, teachers) work as a team with school psychologists to provide the recommended care coordination needed.

Care coordination should also involve communication with other health professionals (e.g., doctors) who can attend to co-occurring difficulties (Moss & Howlin, 2009). School psychologists must use evidence-based practices (EBPs) and coordinate of EBPs with relevant community members when assessing, diagnosing, and implementing interventions for individuals with ASD (Shahidullah et al., 2020). Originally targeted to primary care clinicians, school psychologists may find the EBP program beneficial, particularly those in rural areas or those with limited access to ASD-specific training (Shahidullah et al., 2020). School psychologists should continue to develop and pursue further training and education on care coordination and EBPs to provide the best support possible for those with ASD.   

Anxiety

Definition 

Anxiety has been traditionally defined in the Diagnostic and Statistical Manual (DSM-5) as excessive worry and apprehensive expectations, occurring more days than not for at least six months and occurring during several events or activities, such as work or school (Glasofer & Gans, 2022). Anxiety symptoms make individuals less able to regulate responses to negative feelins, as they have abnormalities in the way their brain unconsciously controls emotions (Brandt, 2010). Anxiety symptoms include feeling nervous, restless, or tense, feeling a sense of impending danger, panic, or doom, increased heart rate, rapid breathing, sweating, trembling, feeling weak or tired, and having trouble concentrating and thinking about anything other than the present worry (Wheaton et al., 2012). 

Developmental Pathways & Neurological Research 

Symptoms of mood and anxiety disorders are caused by an imbalance of activity in the emotional centers of the brain. Three brain regions in the frontal cortical regions work together to ensure the regulation of impulses, emotions, and behaviours via inhibitory top-down processing of emotional structures (Martin et al., 2013).  Martin and colleagues broke down this process by first explaining the role of the prefrontal cortex which is responsible for executive functioning such as planning, decision making, predicting consequences for potential behaviours, and understanding and moderating social behaviour. Afterwards, the orbitofrontal cortex codes information, controls impulses and regulates mood while the ventromedial prefrontal cortex is involved in reward processing and the emotional response (Gauthier & Nuss, 2015). Research by Gauthier et Nuss (2015) went on to explain that when the neurotransmitters providing communication between these regions are disrupted by increased activity in emotion-processing brain regions, individuals who have an anxiety disorder exhibit stress sensitivity in relation to mood and the anxiety disorder. In other words, when the three frontal cortical regions sense threat whether its imaginative or real, it floods the body with hormones, specifically stress hormones, cortisol and adrenaline which causes anxiety symptoms such as feeling nervous, restless, or tense. Also, having a sense of impending danger, panic, or doom. As well as having an increased heart rate, breathing rapidly, sweating, trembling, feeling weak or tired and having trouble concentrating or thinking about anything other than the present worry (Wheaton et al., 2012). 

How is Anxiety Assessed?

Assessing anxiety in youth requires a multi-method, multi-informant approach, drawing information from interviews, youth self-reports, parent and teacher reports, and behavioural observations (Hajiamini et al., 2012). A comprehensive anxiety assessment includes a structured diagnostic interview conducted separately with the child and primary caregiver, a standardized parallel self-report questionnaire completed by the child and parents, and information from teachers collected through interviews or standardized questionnaires (Lyneham et al., 2008).

There are certain questionnaires, such as the Child Behaviour Checklist – Teacher Report Form (CBCL-TRF), the Strengths and Difficulties Questionnaire – Teacher Version (SDQ), and the Behaviour Assessment System – Teacher Rating Scales for Children (BASC-TRSC) that have subscales assessing symptoms of anxiety and depression symptoms generally, but these broad scales fail to differentiate between types of negative emotions and specific anxiety disorder symptoms. Therefore, research by Lyneham and colleagues (2018) acknowledged that the Spence Children’s Anxiety Scale (SCAS) and the School Anxiety Scale-Teacher Report (SAS-TR) are two gold-standard assessment tools most widely used to assess anxiety-focused symptomology and disorders. 

The Spence Children’s Anxiety Scale (SCAS) is a promising instrument for school-based universal screenings (Holly et al., 2015). The Spence Children’s Anxiety Scale (SCAS) is a child self-report measure developed to closely align with DSM diagnoses, such as generalized anxiety disorder, separation anxiety disorder, and social phobia. Scores on the Spence Children’s Anxiety Scale (SCAS) differentiate children with anxiety from those with other disorders and comorbidities (Holly et al., 2015). In schools, the Spence Children’s Anxiety Scale (SCAS) is especially useful because childhood anxiety is tied to poor attendance, poor testing performance, academic failure, and difficulties in relationships (May et al., 2015). Research by May and colleagues (2015) demonstrated that the Spence Children’s Anxiety Scale (SCAS) can help address school mandates for the identification of services for students with social and emotional difficulties.  

The School Anxiety Scale-Teacher Report (SAS-TR) is another scale used to assess anxiety in children at school. This scale was designed to assess children aged five to twelve, targeting behaviours and feelings distinctive to anxiety (Hajiamini et al., 2012). The School Anxiety Scale-Teacher Report (SAS-TR) contains two subscales: social anxiety and generalized anxiety. Social anxiety is described as a fear of humiliation or embarrassment in social situations, which can lead to distress or avoidance of the situation completely (Bögels et al., 2010). Generalized anxiety disorder refers to excessive anxiety and worry, accompanied by symptoms of motor tension and vigilance (Andrews et al., 2010).  

Effective Interventions 

School-based programs can reduce and alleviate many common barriers to treatment in the community, such as time, location, stigmatization, transportation, and cost (Neil & Christensen, 2009). Research conducted by Neil & Christensen (2009) discovered that three types of programs for prevention and early intervention tend to be offered in schools. First, universal programs are presented to all students regardless of symptoms and are often designed to build resiliency or enhance general mental health. Second, selective programs target youth with particular risk factors, such as being a child of an anxious parent or having divorced parents. Lastly, specific programs are delivered to students with early or mild anxiety symptoms. 

Cognitive Behavioural Therapy (CBT) is proven to be an effective treatment for anxiety disorders in youth (Kendall et al., 1997; Mychailyszyn et al., 2011; Silverman et al., 2008). The Coping Cat program is a 16-session manualized Cognitive Behavioural Therapy (CBT) program for anxious youth. Over 60% of youth treated with the Coping Cat no longer presented with baseline principal anxiety disorders post-treatment and gains were maintained at one-year follow-up (Kendall, 1994). Research by Mychailyszyn and colleagues (2011) established that the Coping Cat blends cognitive and behavioural strategies to help youth cope with anxiety. The goal is not to “cure” anxiety but teach youth adaptive ways to manage their anxiety symptoms. Treatment is guided by a manual used by guidance counselors, school social workers, teachers, and school psychologists, alongside a child workbook. The therapist manual is a coaching tool to guide youth to develop skills to manage anxiety while assuring the child that it is normal to experience anxiety.

Everyone experiences anxiety, but some individuals experience it too often or too intensely. CBT programs, such as Coping Cat, help manage symptoms (Mychailyszyn et al., 2011). The early identification and treatment of anxiety disorders in youth is critically important for improving current functioning and protecting long-term health (Bandelow et al., 2017). 

Mood Disorders

Definition 

A mood is an emotional state that subtly affects experience, behaviour, and cognition. Moods can be subtle because they are not necessarily linked to obvious causes or associated with certain events. Moods are usually experienced with low to medium intensity, can last for hours to days, and are characterized by the predominance of certain subjective feelings (Wilhelm & Schoebi, 2007). Mood disorders are estimated to affect 3.7% of schoolage children (Merikangas et al., 2010), with a worldwide prevalence of around 7% (Mokdad et al., 2016). Another study estimated a range between 6% and 8% for major depression (Collins et al., 2004).  

On the unipolar spectrum, there is major depressive disorder (MDD) and dysthymia . These two disorders are characterized by generalized lower mood associated with internalizing behaviour. Bipolar disorder affects both polarities of children’s moods. For instance, the child will oscillate between the symptoms of MDD, and a phase of highly elevated mood called mania (Lack & Green, 2009). In 2013, the DSM-5 added a new disorder called disruptive mood dysregulation disorder (DMDD). It was added because of the over-diagnosis of bipolar disorder in children (Rao, 2014), although this addition was received with controversy (Rao, 2014). 

Between 14% and 24% of the population is diagnosed with some type of mood disorder by the age of 18 (Fox et al., 2008). Mood disorders are a leading contributor of disease in children across the globe (Mokdad et al., 2016), though the presence of bipolar disorder in children can be controversial (Duffy et al., 2020, 2020; Van Meter et al., 2017); hence, research on the subject is less garnished than for teenage and adult populations 

Developmental Pathways & Neurological Research 

Children with mood disorders are at higher risk for suicidal behaviour and difficulties in academic performance (Kann et al., 2018; Van Meter et al., 2017). Academic failure can be linked to higher rates of school absence due to depression (Finning et al., 2019). Mood disorders in children are also associated with physical health problems and risk-taking behaviour. Later in life, they are associated with adult mental illness and substance abuse.

The chronic nature of mood disorders is well documented in the literature. Between fifty to 80% of patients will experience multiple depressive episodes during their lifetime, averaging about five episodes. The first episode if often preceded by a series of subthreshold episodes. Subthreshold episodes are also associated with severe impairment and a higher risk of severe psychiatric disorders (Collins et al., 2004; Coyne et al., 1999). 

The current neural model of depression is described as a dysfunction in the medial prefrontal network and the limbic structures, explaining behaviours and cognitions associated with major depressive disorder. The medial prefrontal network consists of the rostral and ventral part of the frontal cortex to the genu, a small caudolateral orbital region at the rostral end of the insula, and areas along the medial edge of the orbital cortex. These areas are implicated in self-referential function and patterns of physiological activity. They are also believed to be involved in the self-absorption and obsessive rumination associated with major depression (Price & Drevets, 2010). 

Functional and structural brain imaging technology suggests that bipolar disorder stems from a dysfunction of the prefrontal cortical region. During a manic phase, the patient experiences hyperconnectivity in the frontal cortex and basal ganglia. The frontostriatal circuity could explain the cognitive dysfunctions observed in individuals with bipolar disorder (Clark & Sahakian, 2008). Another study found reduced activation of the dorsolateral prefrontal cortex and a failure to deactivate the ventromedial pre-frontal cortex (Pomarol-Clotet et al., 2015). Limiting generalizability is that most neurological studies on bipolar disorder were performed on adult populations. 

How are Mood Disorders Assessed?

The primary criteria of MDD are characterized by a loss of interest or pleasure lasting most of the day, nearly every day, for at least two weeks. Symptoms must cause significant impairment in functioning, social, or occupational settings. A child with MDD may have decreased appetite, disinterest in what they usually love, or diminished interest in daily activities. The child may feel worthless and depressed daily and have difficulty thinking or concentrating (Bardick & Bernes, 2005).  

Children with depression may also express suicidal ideation and attempt suicide. Children exhibit frequent crying, increased social withdrawal, and complain of somatic ailments, such as aching arms, headaches, or stomach aches. Feeling of worthlessness in depressed children can be differentiated from the non-depressed when the child is hesitant to try something different.

The presence of depressive symptoms every day for over at least a year may indicate dysthymia. Dysthymia can present similar to MDD, except with dysthymia children experience lesser intensity and fewer symptoms. However, symptoms remain every day for more than two months (Lack & Green, 2009). 

The presence of mood swings between manic and depressive episodes can be an indicator of bipolar disorder. Usually, children will not have acute onset of symptoms or definite episodes of irritability or elevated mood. Nor will they show grandiosity or euphoric mood; instead, they may express a higher rate of psychotic features, and more rapid cycling between polarities has been observed (American Psychiatric Association, 2013). Children may engage in risky behaviours, such as getting into fights. Additionally, youth in the manic phase tend to sleep very little for several days without feeling tired and increase engagement in activities. They may be very talkative and talk very quickly while frequently changing topics (Bardick & Bernes, 2005). These moods are often irritable and unrestrained for more than a week. (Lack & Green, 2009). 

The presence of irritability has sparked interest in recent years. Irritability was a cardinal symptom proposed for pre-pubertal mania criteria, although the DSM never defined the criteria. Chronic irritability is no longer considered an alternative form of bipolar disorder (Duffy et al., 2020). The DSM-5 characterizes DMDD as severe and chronic irritability inchildren under 12 years old and older than six years old (Wiggins et al., 2021). Two types of irritability are observed: tonic and phasic. Tonic irritability refers to a child who is constantly angry, grumpy, and bad-tempered. Phasic irritability refers to sudden surges of intense anger (Moore et al., 2019). Both types appear to be a core feature of DMDD (American Psychiatric Association, 2013). 

Diagnosis occurs through structured or semi-structured interviews with the parents and child. Other tools can be used, such as questionnaires based on DMS criteria (Patra & Kumar, 2022). Patient Health Questionaire-9, Beck Depression Inventory, Epidemiological Studies Diagnostic Interview, and Clinical Interview Schedule are examples of valid questionnaires used with children (Forman-Hoffman et al., 2016; Rocha et al., 2013). Results from these questionnaires are connected to the child’s biopsychosocial history to facilitate understanding of their strengths and struggles. Regarding the differential diagnosis of bipolar disorder, which includes manic episodes, it was found that teachers did not add additional information to inform a diagnosis. A low score on the Child Behaviour Checklist in most settings means that bipolar disorder can be discarded as a diagnostic option (Youngstrom et al., 2005). 

Effective Interventions 

Because of the internalizing nature of MDD, it can be difficult for teachers or parents to identify at risk children. Around 80% of children do not receive services for emotional disorders (Collins et al., 2004; Finning et al., 2020; Ford et al., 2007). Children often only receive help once behaviour is observable, such as in the case of a suicide attempt. For this reason, screening youth for depression is vital.

Mood disorders are treated in various ways, including with medication, support programs, counselling, and psychoeducation (Patra & Kumar, 2022). Pharmacotherapy to treat depression among children can be controversial as the use of psychotropic medications tends to increase faster than the evidence to support such use (Deveaugh-Geiss et al., 2006).  

There is evidence that selective serotonin reuptake inhibitors (SSRIs) are effective for MDD with few side effects (e.g., fluoxetine). Notably, initial use of antidepressant drugs is associated with increased suicide risk, so professionals must be vigilant in monitoring side effects during the adaptive stage of the drug (Fritz & Rockney, 2004; Mullen, 2018). Mood stabilizers such as lithium (Kafantaris et al., 2003; Patel et al., 2006), divalproex sodium, and topiramate effectively treat bipolar disorder (Kowatch et al., 2000).

The main approach of psychotherapy for mood disorders is to include family psychoeducation and skill building to add to the benefit of pharmacotherapy (Fristad & MacPherson, 2014). Psychotherapy (e.g., CBT) is empirically supported.. The goal is to intervene at the behavioural, affective, and cognitive levels of the child, focusing on the interaction of these three components in the maintenance of depression (Price & Drevets, 2010). Multifamily psychoeducation psychotherapy adjunctive with treatment-as-usual has been shown to decrease scores on mood disorders six months post-treatment. One of the main benefits is that it is brief psychotherapy, which increases the willingness of the family to accept treatment (Fristad et al., 2009). 

Review key terminology related to common behavioural and learning disorders in children and adolescents and the assessment process.

Summary

When supporting students in the classroom, school psychologist must consider children’s developmental and behavioural challenges as they directly direct impact their education and social lives. Youth with developmental and behavioural challenges encounter difficulties related to learning, social relationships, decision making, and managing emotions, such as feelings of anxiety, depression, worry, and isolation (Eklund et al., 2020). School psychologists are faced with the difficult task of assessing various students. Many individuals with intellectual or behavioural disabilities experience testing challenges, such as communication, attention, and self-regulation, which interferes with the validity of the standardized assessment process and leads these individuals to be labelled “untestable” (Thompson et al., 2018).

Research conducted by Thompson and colleagues (2018) stated that in order to determine appropriate educational placements, develop intervention plans and measure progress, it is essential to understand the unique developmental strengths and challenges of each individual involved and use standardized, objective, and reliable tools to classify behaviour. Understanding common developmental and behavioural disorders in children and adolescents and how school psychologists provide accommodations to individually support students through a variety of means, such as interventions and consultations, is vital.

To accurately describe students’ problems, strengths, and adaptive skills, school psychologists must examine the environmental factors that facilitate and impede learning and psychological adjustment. This in turn leads to recommending appropriate interventions, which enhances overall functioning and academic success for students (Wiener, 2020).

References

Aiello, R., Ruble, L., & Esler, A. (2017). National study of school psychologists’ use of evidence-based assessment in autism spectrum disorder. Journal of Applied School Psychology, 33(1), 67–88. https://doi.org/10.1080/15377903.2016.1236307 

Alegria, A. A., Radua, J., & Rubia, K. (2016). Meta-Analysis of fMRI studies of disruptive behaviour disorders. American Journal of Psychiatry, 173(11), 1119–1130. https://doi.org/10.1176/appi.ajp.2016.15081089 

Ardoin, S. P., Witt, J. C., Connell, J. E., & Koenig, J. L. (2005). Application of a three-tiered response to intervention model for instructional planning, decision making, and the identification of children in need of services. Journal of Psychoeducational Assessment, 23(4), 362–380. https://doi.org/10.1177/073428290502300405 

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (Fifth Edition). American Psychiatric Association. https://doi.org/10.1176/appi.books.9780890425596 

Andrews, G., Hobbs, M. J., Borkovec, T. D., Beesdo, K., Craske, M. G., Heimberg, R. G., Rapee, R. M., Ruscio, A. M., & Stanley, M. A. (2010). Generalized worry disorder: A review of DSM-IV generalized anxiety disorder and options for DSM-V. Depression and Anxiety, 27(2), 134–147. https://doi.org/10.1002/da.20658 

Austerman, J. (2015). ADHD and behavioural disorders: Assessment, management, and an update from DSM-5. Cleveland Clinic Journal of Medicine, 82(11 suppl 1), S2–S7. https://doi.org/10.3949/ccjm.82.s1.01 

Ayano, G., Yohannes, K., & Abraha, M. (2020). Epidemiology of attention-deficit/hyperactivity disorder (ADHD) in children and adolescents in Africa: A systematic review and meta-analysis. Annals of General Psychiatry, 19(1), 21. https://doi.org/10.1186/s12991-020-00271-w 

Bandelow, B., Michaelis, S., & Wedekind, D. (2017). Treatment of anxiety disorders. Dialogues in Clinical Neuroscience, 19(2), 93–107. https://doi.org/10.31887/dcns.2017.19.2/bbandelow 

Bardick, A. D., & Bernes, K. B. (2005). A closer examination of bipolar disorder in school-Age children. Professional School Counseling, 9(1), 2156759X0500900. https://doi.org/10.1177/2156759X0500900103 

Barker, C., & Lugt, J. de. (2022). A review of evidence based practices to support students with oppositional defiant disorder in classroom settings. International Journal of Special Education (IJSE), 37(1). https://doi.org/10.52291/ijse.2022.37.29 

Björkqvist, K., Lagerspetz, K., & Kaukiainen, A. (1992). Do girls manipulate and boys fight? Developmental trends in regard to direct and indirect aggression. Aggressive Behaviour – AGGRESS BEHAV, 18, 117–127. https://doi.org/10.1002/1098-2337(1992)18:2%3C117::AID-AB2480180205%3E3.0.CO;2-3 

Bögels, S. M., Alden, L., Beidel, D. C., Clark, L. A., Pine, D. S., Stein, M. B., & Voncken, M. (2010). Social anxiety disorder: Questions and answers for the DSM-V. Depression and Anxiety, 27(2), 168–189. https://doi.org/10.1002/da.20670 

Bramlett, R. K., Murphy, J. J., Johnson, J., Wallingsford, L., & Hall, J. D. (2002). Contemporary practices in school psychology: A national survey of roles and referral problems. Psychology in the Schools, 39(3), 327–335. https://doi.org/10.1002/pits.10022 

Brandt, M. (2010). People with anxiety disorder less able to regulate response to negative emotions, study shows. News Center. https://med.stanford.edu/news/all-news/2010/02/people-with-anxiety-disorder-less-able-to-regulate-response-to-negative-emotions-study-shows.htm 

Brestan-Knight, E., & Eyberg, S. (1998). Effective psychosocial treatments of conduct-disordered children and adolescents: 29 Years, 82 Studies, and 5,272 Kids. Journal of Clinical Child Psychology, 27, 180–189. https://doi.org/10.1207/s15374424jccp2702_5 

Buitelaar, J. K., Meer,  van der, Dennis, & Richards, J. S. (2019). Understanding the essentials of the ADHD neurobiology. In L. A. Rohde, J. K. Buitelaar, M. Gerlach, & S. V. Faraone (Eds)., The World Federation of ADHD Guide (pp. 17–41). Artmed. http://cpo-media.net/ADHD/2019/ebook/HTML/files/assets/common/downloads/publication.pdf#page=27 

Burke, J. D., Loeber, R., Lahey, B. B., & Rathouz, P. J. (2005). Developmental transitions among affective and behavioural disorders in adolescent boys. Journal of Child Psychology and Psychiatry, 46(11), 1200–1210. https://doi.org/10.1111/j.1469-7610.2005.00422.x 

Burke, J. D., Waldman, I., & Lahey, B. B. (2010). Predictive validity of childhood oppositional defiant disorder and conduct disorder: Implications for the DSM-V. Journal of Abnormal Psychology, 119(4), 739–751. https://doi.org/10.1037/a0019708 

Buxbaum, J. D., & Hof, P. R. (2011). The emerging neuroscience of autism spectrum disorders. Brain Research, 1380, 1–2. https://doi.org/10.1016/j.brainres.2011.02.030 

Canadian Mental Health Association (CMHA) (2021). Fast facts about mental health and mental illness. Canadian Mental Health Association (CMHA). https://cmha.ca/brochure/fast-facts-about-mental-illness 

Carr, E. G. (1994). Emerging themes in the functional analysis of problem behaviour. Journal of Applied Behaviour Analysis, 27(2), 393–399. https://doi.org/10.1901/jaba.1994.27-393 

Cavanagh, M., Quinn, D., Duncan, D., Graham, T., & Balbuena, L. (2014). Oppositional defiant disorder is better conceptualized as a disorder of emotional regulation. Journal of Attention Disorders, 21. https://doi.org/10.1177/1087054713520221 

Chadwick, O., Walker, N., Bernard, S., & Taylor, E. (2000). Factors affecting the risk of behaviour problems in children with severe intellectual disability. Journal of Intellectual Disability Research, 44(2), 108–123. https://doi.org/10.1046/j.1365-2788.2000.00255. 

Charman, T., Jones, C. R. G., Pickles, A., Simonoff, E., Baird, G., & Happé, F. (2011). Defining the cognitive phenotype of autism. Brain Research, 1380, 10–21. https://doi.org/10.1016/j.brainres.2010.10.075 

Chen, H., He, T., Xu, M., Zhao, J., Li, L., & Lin, X. (2021). Children’s oppositional defiant disorder symptoms make parents difficult to be nice: Longitudinal association among parent emotion regulation, child emotion regulation and children’s oppositional defiant disorder symptoms in Chinese children with oppositional defiant disorder. Clinical Child Psychology and Psychiatry, 27, 135910452110558. https://doi.org/10.1177/13591045211055822 

Chojnicka, I., & Pisula, E. (2017). Adaptation and validation of the ADOS-2, Polish Version. Frontiers in Psychology, 8, 1916. https://doi.org/10.3389/fpsyg.2017.01916 

Christenson, J., Crane, D., Malloy, J., & Parker, S. (2016). The Cost of oppositional defiant disorder and disruptive behaviour: A review of the literature. Journal of Child and Family Studies, 25. https://doi.org/10.1007/s10826-016-0430-9 

Christopher, K., & Lord, C. (2022). Best practice assessments for autism spectrum disorders in schools. Psychology in the Schools, 59(7), 1454–1468. https://doi.org/10.1002/pits.22680 

Clark, L., & Sahakian, B. J. (2008). Cognitive neuroscience and brain imaging in bipolar disorder. Dialogues in Clinical Neuroscience, 10(2), 153–165. https://doi.org/10.31887/DCNS.2008.10.2/lclark 

Cohen, M., & Miller, T. (1998). The cost of mental health care for victims of crime. Journal of Interpersonal Violence – J INTERPERS VIOLENCE, 13, 93–110. https://doi.org/10.1177/088626098013001006 

Collins, K. A., Westra, H. A., Dozois, D. J. A., & Burns, D. D. (2004). Gaps in accessing treatment for anxiety and depression: Challenges for the delivery of care. Clinical Psychology Review, 24(5), 583–616. https://doi.org/10.1016/j.cpr.2004.06.001 

Copeland, W. E., Shanahan, L., Costello, E. J., & Angold, A. (2009). Childhood and adolescent psychiatric disorders as predictors of young adult disorders. Archives of General Psychiatry, 66(7), 764–772. https://doi.org/10.1001/archgenpsychiatry.2009.85 

Coyne, J. C., Pepper, C. M., & Flynn, H. (1999). Significance of prior episodes of depression in two patient populations. Journal of Consulting and Clinical Psychology, 67(1), 76–81. https://doi.org/10.1037/0022-006X.67.1.76 

Crick, N. R., & Grotpeter, J. K. (1995). Relational aggression, gender, and social-psychological Adjustment. Child Development, 66(3), 710. https://doi.org/10.2307/1131945 

Danielson, M. L., Bitsko, R. H., Ghandour, R. M., Holbrook, J. R., Kogan, M. D., & Blumberg, S. J. (2018). Prevalence of parent-reported ADHD diagnosis and associated treatment among U.S. children and adolescents, 2016. Journal of Clinical Child and Adolescent Psychology : The Official Journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53, 47(2), 199–212. https://doi.org/10.1080/15374416.2017.1417860 

Deveaugh-Geiss, J., March, J., Shapiro, M., Andreason, P. J., Emslie, G., Ford, L. M., Greenhill, L., Murphy, D., Prentice, E., Roberts, R., Silva, S., Swanson, J. M., Van Zwieten-Boot, B., Vitiello, B., Wagner, K. D., & Mangum, B. (2006). Child and adolescent psychopharmacology in the new millennium: A workshop for academia, industry, and government. Journal of the American Academy of Child & Adolescent Psychiatry, 45(3), 261–270. https://doi.org/10.1097/01.chi.0000194568.70912.ee 

Davis, R., Campbell, R., Hildon, Z., Hobbs, L., & Michie, S. (2015). Theories of behaviour and behaviour change across the social and behavioural sciences: A scoping review. Health Psychology Review, 9(3), 323–344. https://doi.org/10.1080/17437199.2014.941722 

Dieleman, J. L., Baral, R., Birger, M., Bui, A. L., Bulchis, A., Chapin, A., Hamavid, H., Horst, C., Johnson, E. K., Joseph, J., Lavado, R., Lomsadze, L., Reynolds, A., Squires, E., Campbell, M., DeCenso, B., Dicker, D., Flaxman, A. D., Gabert, R., … Murray, C. J. L. (2016). US Spending on personal health care and public health, 1996-2013. JAMA, 316(24), 2627–2646. https://doi.org/10.1001/jama.2016.16885 

Doll, B. (1996). Prevalence of psychiatric disorders in children and youth: An agenda for advocacy by school psychology. School Psychology Quarterly, 11(1), 20–46. https://doi.org/10.1037/h0088919 

Doshi, J. A., Hodgkins, P., Kahle, J., Sikirica, V., Cangelosi, M. J., Setyawan, J., Erder, M. H., & Neumann, P. J. (2012). Economic impact of childhood and adult attention-deficit/hyperactivity disorder in the United States. Journal of the American Academy of Child & Adolescent Psychiatry, 51(10), 990-1002.e2. https://doi.org/10.1016/j.jaac.2012.07.008 

Duffy, A., Carlson, G., Dubicka, B., & Hillegers, M. H. J. (2020). Pre-pubertal bipolar disorder: Origins and current status of the controversy. International Journal of Bipolar Disorders, 8(1), 18. https://doi.org/10.1186/s40345-020-00185-2 

Eklund, K., DeMarchena, S. L., Rossen, E., Izumi, J. T., Vaillancourt, K., & Rader Kelly, S. (2020). Examining the role of school psychologists as providers of mental and behavioural health services. Psychology in the Schools, 57(4), 489–501. https://doi.org/10.1002/pits.22323

Espinet, S. D., Graziosi, G., Toplak, M. E., Hesson, J., & Minhas, P. (2022). A Review of Canadian diagnosed ADHD prevalence and incidence estimates published in the past decade. Brain Sciences, 12(8), Article 8. https://doi.org/10.3390/brainsci12081051 

Euler, F., Jenkel, N., Stadler, C., Schmeck, K., Fegert, J. M., Kölch, M., & Schmid, M. (2015). Variants of girls and boys with conduct disorder: anxiety symptoms and callous-unemotional Traits. Journal of Abnormal Child Psychology, 43(4), 773–785. https://doi.org/10.1007/s10802-014-9946-x 

Evans, S. C., Pederson, C. A., Fite, P. J., Blossom, J. B., & Cooley, J. L. (2016). Teacher-reported irritable and defiant dimensions of oppositional defiant disorder: Social, behavioural, and academic correlates. School Mental Health, 8(2), 292–304. https://doi.org/10.1007/s12310-015-9163-y 

Finning, K., Ford, T., Moore, D. A., & Ukoumunne, O. C. (2020). Emotional disorder and absence from school: Findings from the 2004 British Child and Adolescent Mental Health Survey. European Child & Adolescent Psychiatry, 29(2), 187–198. https://doi.org/10.1007/s00787-019-01342-4 

Finning, K., Ukoumunne, O. C., Ford, T., Danielsson-Waters, E., Shaw, L., Romero De Jager, I., Stentiford, L., & Moore, D. A. (2019). The association between child and adolescent depression and poor attendance at school: A systematic review and meta-analysis. Journal of Affective Disorders, 245, 928–938. https://doi.org/10.1016/j.jad.2018.11.055 

Ford, T., Hamilton, H., Meltzer, H., & Goodman, R. (2007). Child mental health is everybody’s business: The prevalence of contact with public sector services by type of disorder among British school children in a three-year period. Child and Adolescent Mental Health, 12(1), 13–20. https://doi.org/10.1111/j.1475-3588.2006.00414.x 

Forman, S. G., Shapiro, E. S., Codding, R. S., Gonzales, J. E., Reddy, L. A., Rosenfield, S. A., Sanetti, L. M. H., & Stoiber, K. C. (2013). Implementation science and school psychology. School Psychology Quarterly, 28(2), 77. https://doi.org/10.1037/spq0000019

Forman-Hoffman, V., McClure, E., McKeeman, J., Wood, C. T., Middleton, J. C., Skinner, A. C., Perrin, E. M., & Viswanathan, M. (2016). Screening for major depressive disorder in children and adolescents: A systematic review for the U.S. preventive services task force. Annals of Internal Medicine, 164(5), 342–349. https://doi.org/10.7326/M15-2259 

Foster, E. M., Jones, D. E., & and The Conduct Problems Prevention Research Group. (2005). The high costs of aggression: Public expenditures resulting from conduct disorder. American Journal of Public Health, 95(10), 1767–1772. https://doi.org/10.2105/AJPH.2004.061424 

Fox, J. K., Halpern, L. F., & Forsyth, J. P. (2008). Mental health checkups for children and adolescents: A means to identify, prevent, and minimize suffering associated with anxiety and mood disorders. Clinical Psychology: Science and Practice, 15(3), 182–211. https://doi.org/10.1111/j.1468-2850.2008.00129.x 

Frick, P. J. (2016). Current research on conduct disorder in children and adolescents. South African Journal of Psychology, 46(2), 160–174. https://doi.org/10.1177/0081246316628455 

Fristad, M. A., & MacPherson, H. A. (2014). Evidence-based psychosocial treatments for child and adolescent bipolar spectrum disorders. Journal of Clinical Child & Adolescent Psychology, 43(3), 339–355. https://doi.org/10.1080/15374416.2013.822309 

Fristad, M. A., Verducci, J. S., Walters, K., & Young, M. E. (2009). Impact of multifamily psychoeducational psychotherapy in treating children aged 8 to 12 years with mood disorders. Archives of General Psychiatry, 66(9), 1013–1021. https://doi.org/10.1001/archgenpsychiatry.2009.112 

Fritz, G., & Rockney, R. (2004). Practice parameter for the assessment and treatment of children and adolescents with enuresis. Journal of the American Academy of Child & Adolescent Psychiatry, 43(12), 1540–1550. https://doi.org/10.1097/01.chi.0000142196.41215.cc 

Gaoni, L., Black, Q. C., & Baldwin, S. (1998). Defining adolescent behaviour disorder: An overview. Journal of Adolescence, 21(1), 1–13. https://doi.org/10.1006/jado.1997.0125 

Gauthier, I., & Nuss, P. (2015). Anxiety disorders and GABA neurotransmission: A disturbance of modulation. Neuropsychiatric Disease and Treatment, 165. https://doi.org/10.2147/ndt.s58841 

Geschwind, D. H. (2011). Genetics of autism spectrum disorders. Trends in Cognitive Sciences, 15(9), 409–416. https://doi.org/10.1016/j.tics.2011.07.003 

Ghosh, A., Malhotra, S., & Basu, D. (2014). Oppositional defiant disorder (ODD), the forerunner of alcohol dependence: A controlled study. Asian Journal of Psychiatry, 11, 8–12. https://doi.org/10.1016/j.ajp.2014.03.006 

Glasofer, D. R., & Gans, S. (2022). Generalized anxiety disorder: Symptoms and DSM-5 diagnosis. Verywell Mind. https://www.verywellmind.com/dsm-5-criteria-for-generalized-anxiety-disorder-1393147  

Gomez, R., Stavropoulos, V., Gomez, A., Brown, T., & Watson, S. (2022). Network analyses of Oppositional Defiant Disorder (ODD) symptoms in children. BMC Psychiatry, 22. https://doi.org/10.1186/s12888-022-03892-5 

Greenfield, B. L., Sittner, K. J., Forbes, M. K., Walls, M. L., & Whitbeck, L. B. (2017). Conduct disorder and alcohol use disorder trajectories, predictors, and outcomes for indigenous youth. Journal of the American Academy of Child & Adolescent Psychiatry, 56(2), 133-139.e1. https://doi.org/10.1016/j.jaac.2016.11.009 

Gresham, F. M. (2004). Current status and future Directions of school-based behavioural Interventions. School Psychology Review, 33(3), 326–343. https://doi.org/10.1080/02796015.2004.12086252 

Grizenko, N., & Pawliuk, N. (1994). Risk and protective factors for disruptive behaviour disorders in children. American Journal of Orthopsychiatry, 64(4), 534–544. https://doi.org/10.1037/h0079566 

Hajiamini, Z., Mohamadi, A., Ebadi, A., Fathi- Ashtiani, A., Tavousi, M., & Montazeri, A. (2012). The school anxiety scale-teacher report (SAS-TR): Translation and psychometric properties of the Iranian version. BMC Psychiatry, 12(1). https://doi.org/10.1186/1471-244x-12-82  

Hamilton, S. S., Armando, J., & Hospital, U.-M. (2008). Oppositional Defiant Disorder. 78(7), 6. 

Harry, S. W., Bates-Brantley, K. E., Whitefield, B. L., & Dale, B. A. (2022). Supporting practitioners in school-based evaluations of autism spectrum disorders. Psychology in the Schools, n/a(n/a). https://doi.org/10.1002/pits.22684  

Hart, R. (2010). Classroom behaviour management: Educational psychologists’ views on effective practice. Emotional and Behavioural Difficulties, 15(4), 353–371. https://doi.org/10.1080/13632752.2010.523257 

Hawken, L. S. (2006). School psychologists as leaders in the implementation of a targeted intervention: The Behaviour Education Program. School Psychology Quarterly, 21(1), 91–111. https://doi.org/10.1521/scpq.2006.21.1.91 

Herman, K. C., Merrell, K. W., Reinke, W. M., & Tucker, C. M. (2004). The role of school psychology in preventing depression. Psychology in the Schools, 41(7), 763–775. https://doi.org/10.1002/pits.20016 

Holly, L. E., Little, M., Pina, A. A., & Caterino, L. C. (2015). Assessment of anxiety symptoms in school children: a cross-sex and ethnic examination. Journal of Abnormal Child Psychology, 43(2), 297–309. https://doi.org/10.1007/s10802-014-9907-4 

Hood, B. S., Elrod, M. G., & DeWine, D. B. (2015). Treatment of childhood oppositional defiant disorder. Current Treatment Options in Pediatrics, 1(2), 155–167. https://doi.org/10.1007/s40746-015-0015-7 

Huffman, L. C., Mehlinger, S. L., & Kerivan, A. S. (2000). Risk factors for academic and behavioural problems at the beginning of school. The Child Mental Health Foundations and Agencies Netword, 1-94. https://www.cecredit.com/articles/9580/riskfactorsacademic.pdf 

Hunter, L. (2003). School psychology: A public health framework: III. Managing disruptive behaviour in schools: the value of a public health and evidence-based perspective. Journal of School Psychology, 41(1), 39–59. https://doi.org/10.1016/S0022-4405(02)00143-7 

Johnson, M., Åsberg Johnels, J., Östlund, S., Cedergren, K., Omanovic, Z., Hjalmarsson, K., Jakobsson, K., Högstedt, J., & Billstedt, E. (2021). Long-term medication for ADHD and development of cognitive functions in children and adolescents. Journal of Psychiatric Research, 142, 204–209. https://doi.org/10.1016/j.jpsychires.2021.07.055 

Jones, K., Daley, D., Hutchings, J., Bywater, T., & Eames, C. (2008). Efficacy of the incredible years programme as an early intervention for children with conduct problems and ADHD: Long-term follow-up. Child: Care, Health and Development, 34(3), 380–390. https://doi.org/10.1111/j.1365-2214.2008.00817.x 

Kafantaris, V., Coletti, D. J., Dicker, R., Padula, G., & Kane, J. M. (2003). Lithium treatment of acute mania in adolescents: A large open trial. Journal of the American Academy of Child & Adolescent Psychiatry, 42(9), 1038–1045. https://doi.org/10.1097/01.CHI.0000070247.24125.24 

Kann, L., McManus, T., Harris, W. A., Shanklin, S. L., Flint, K. H., Queen, B., Lowry, R., Chyen, D., Whittle, L., Thornton, J., Lim, C., Bradford, D., Yamakawa, Y., Leon, M., Brener, N., & Ethier, K. A. (2018). Youth risk behaviour surveillance—United States, 2017. MMWR. Surveillance Summaries, 67(8), 1–114. https://doi.org/10.15585/mmwr.ss6708a1 

Kendall, P. C. (1994). Treating anxiety disorders in children: results of a randomized clinical trial. Journal of Consulting and Clinical Psychology, 62(1), 100–110. https://doi.org/10.1037/0022-006X.62.1.100 

Kendall, P. C., Flannery-Schroeder, E., Panichelli-Mindel, S. M., Southam-Gerow, M., Henin, A., & Warman, M. (1997). Therapy for youths with anxiety disorders: A second randomized clinical trial. Journal of Consulting and Clinical Psychology, 65(3), 366–380. https://doi.org/10.1037/0022-006X.65.3.366 

Kowatch, R., SUPPES, T., Carmody, T., Bucci, J., HUME, J., Kromelis, M., Emslie, G., WEINBERG, W., & Rush, A. (2000). Effect size of lithium, divalproex sodium, and carbamazepine in children and adolescents with bipolar disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 39, 713–720. https://doi.org/10.1097/00004583-200006000-00009 

Kratochwill, T. R., Volpiansky, P., Clements, M., & Ball, C. (2007). Professional development in implementing and sustaining multitier prevention models: Implications for response to intervention. School Psychology Review, 36(4), 618–631. https://doi.org/10.1080/02796015.2007.12087921 

Kuntsi, J., Andreou, P., Ma, J., Börger, N. A., & van der Meere, J. J. (2005). Testing assumptions for endophenotype studies in ADHD: Reliability and validity of tasks in a general population sample. BMC Psychiatry, 5(1), 40. https://doi.org/10.1186/1471-244X-5-40 

Lack, C. W., & Green, A. L. (2009). Mood Disorders in children and adolescents. Journal of Pediatric Nursing, 24(1), 13–25. https://doi.org/10.1016/j.pedn.2008.04.007 

Lahey, B. B., Applegate, B., Waldman, I. D., Loft, J. D., Hankin, B. L., & Rick, J. (2004). The structure of child and adolescent psychopathology: Generating new hypotheses. Journal of Abnormal Psychology, 113(3), 358–385. https://doi.org/10.1037/0021-843X.113.3.358 

Lanza, S. T., Rhoades, B. L., Nix, R. L., & Greenberg, M. T. (2010). Modeling the interplay of multilevel risk factors for future academic and behaviour problems: A person-centered approach. Development and Psychopathology, 22(2), 313–335. https://doi.org/10.1017/s0954579410000088 

Lyneham, H. J., Street, A. K., Abbott, M. J., & Rapee, R. M. (2008). Psychometric properties of the school anxiety scale—Teacher report (SAS-TR). Journal of Anxiety Disorders, 22(2), 292–300. https://doi.org/10.1016/j.janxdis.2007.02.001 

Loeber, R., & Burke, J. D. (2011). Developmental pathways in juvenile externalizing and internalizing problems: Developmental pathways in juvenile externalizing and internalizing problems. Journal of Research on Adolescence, 21(1), 34–46. https://doi.org/10.1111/j.1532-7795.2010.00713.x 

Loeber, R., Burke, J. D., Lahey, B. B., Winters, A., & Zera, M. (2000). Oppositional defiant and conduct disorder: A review of the past 10 years, part I. Journal of the American Academy of Child & Adolescent Psychiatry, 39(12), 1468–1484. https://doi.org/10.1097/00004583-200012000-00007 

Mars, R. B., Neubert, F.-X., Noonan, M. P., Sallet, J., Toni, I., & Rushworth, M. F. S. (2012). On the relationship between the “default mode network” and the “social brain.” Frontiers in Human Neuroscience, 6, 189. https://doi.org/10.3389/fnhum.2012.00189 

Martin, E. I., Ressler, K. J., Binder, E., & Nemeroff, C. B. (2013). The neurobiology of anxiety disorders: brain imaging, genetics, and psychoneuroendocrinology. Clinics in Laboratory Medicine, 30(4), 865–891. https://doi.org/10.1016/j.cll.2010.07.006 

May, T., Cornish, K., & Rinehart, N. J. (2015). Parent-child agreement using the Spence Children’s Anxiety Scale and a thermometer in children with autism spectrum disorder. Autism Research and Treatment, 2015, 1–9. https://doi.org/10.1155/2015/315495 

McClain, M. B., Otero, T. L., Haverkamp, C. R., & Molsberry, F. (2018). Autism spectrum disorder assessment and evaluation research in 10 school psychology journals from 2007 to 2017. Psychology in the Schools, 55(6), 661–679. https://doi.org/10.1002/pits.22133 

McMahon, S. D., Peist, E., Davis, J. O., Bare, K., Martinez, A., Reddy, L. A., Espelage, D. L., & Anderman, E. M. (2020). Physical aggression toward teachers: Antecedents, behaviours, and consequences. Aggressive Behaviour, 46(1), 116–126. https://doi.org/10.1002/ab.21870 

Merikangas, K. R., He, J.-P., Brody, D., Fisher, P. W., Bourdon, K., & Koretz, D. S. (2010). Prevalence and treatment of mental disorders among US children in the 2001–2004 NHANES. Pediatrics, 125(1), 75–81. https://doi.org/10.1542/peds.2008-2598 

Mikolajewski, A. J., Taylor, J., & Iacono, W. G. (2017). Oppositional Defiant Disorder dimensions: genetic influences and risk for later psychopathology. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 58(6), 702–710. https://doi.org/10.1111/jcpp.12683 

Miranda, A. H., Flood, S., McConnell, R., Blake, T., & Walker, K. (2022). Mutually beneficial: A head start-school psychology program partnership. Journal of Educational and Psychological Consultation, 32(3), 359–374. https://doi.org/10.1080/10474412.2022.2028158 

Mokdad, A. H., Forouzanfar, M. H., Daoud, F., Mokdad, A. A., El Bcheraoui, C., Moradi-Lakeh, M., Kyu, H. H., Barber, R. M., Wagner, J., Cercy, K., Kravitz, H., Coggeshall, M., Chew, A., O’Rourke, K. F., Steiner, C., Tuffaha, M., Charara, R., Al-Ghamdi, E. A., Adi, Y., … Murray, C. J. L. (2016). Global burden of diseases, injuries, and risk factors for young people’s health during 1990–2013: A systematic analysis for the Global Burden of Disease Study 2013. The Lancet, 387(10036), 2383–2401. https://doi.org/10.1016/S0140-6736(16)00648-6 

Moore, A. A., Lapato, D. M., Brotman, M. A., Leibenluft, E., Aggen, S. H., Hettema, J. M., York, T. P., Silberg, J. L., & Roberson-Nay, R. (2019). Heritability, stability, and prevalence of tonic and phasic irritability as indicators of Disruptive Mood Dysregulation Disorder. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 60(9), 1032–1041. https://doi.org/10.1111/jcpp.13062 

Moss, J., & Howlin, P. (2009). Autism spectrum disorders in genetic syndromes: Implications for diagnosis, intervention and understanding the wider autism spectrum disorder population. Journal of Intellectual Disability Research, 53(10), 852–873. https://doi.org/10.1111/j.1365-2788.2009.01197.x 

Mullen, S. (2018). Major depressive disorder in children and adolescents. The Mental Health Clinician, 8(6), 275–283. https://doi.org/10.9740/mhc.2018.11.275 

Munkvold, L. H., Lundervold, A. J., & Manger, T. (2011). Oppositional defiant disorder—gender differences in co-occurring symptoms of mental health problems in a general population of children. Journal of Abnormal Child Psychology, 39(4), 577–587. https://doi.org/10.1007/s10802-011-9486-6 

Mychailyszyn, M. P., Beidas, R. S., Benjamin, C. L., Edmunds, J. M., Podell, J. L., Cohen, J. S., & Kendall, P. C. (2011). Assessing and treating child anxiety in schools. Psychology in the Schools, 48(3), 223–232. https://doi.org/10.1002/pits.20548 

Nakao, T., Radua, J., Rubia, K., & Mataix-Cols, D. (2011). Gray matter volume abnormalities in ADHD: voxel-based meta-analysis exploring the effects of age and stimulant medication. American Journal of Psychiatry, 168(11), 1154–1163. https://doi.org/10.1176/appi.ajp.2011.11020281 

Neil, A. L., & Christensen, H. (2009). Efficacy and effectiveness of school-based prevention and early intervention programs for anxiety. Clinical Psychology Review, 29(3), 208–215. https://doi.org/10.1016/j.cpr.2009.01.002 

Nelson, C. A., Zeanah, C. H., & Fox, N. A. (2019). How early experience shapes human development: The case of psychosocial deprivation. Neural Plasticity, 2019, 1–12. https://doi.org/10.1155/2019/1676285 

Nelson, J. R., Stage, S., Duppong-Hurley, K., Synhorst, L., & Epstein, M. H. (2007). Risk factors predictive of the problem behaviour of children at risk for emotional and behavioural disorders. Exceptional Children, 73(3), 367–379. https://doi.org/10.1177/001440290707300306 

Nock, M. K., Kazdin, A. E., Hiripi, E., & Kessler, R. C. (2007). Lifetime prevalence, correlates, and persistence of oppositional defiant disorder: Results from the National Comorbidity Survey Replication. Journal of Child Psychology and Psychiatry, 48(7), 703–713. https://doi.org/10.1111/j.1469-7610.2007.01733.x 

Ohan, J. L., Seward, R. J., Stallman, H. M., Bayliss, D. M., & Sanders, M. R. (2015). Parents’ barriers to using school psychology services for their child’s mental health problems. School Mental Health, 7(4), 287–297. https://doi.org/10.1007/s12310-015-9152-1 

O’Mara-Eves, A., Brunton, G., Oliver, S., Kavanagh, J., Jamal, F., & Thomas, J. (2015). The effectiveness of community engagement in public health interventions for disadvantaged groups: A meta-analysis. BMC Public Health, 15, 129. https://doi.org/10.1186/s12889-015-1352-y 

Patel, N. C., Delbello, M. P., Bryan, H. S., Adler, C. M., Kowatch, R. A., Stanford, K., & Strakowski, S. M. (2006). Open-label lithium for the treatment of adolescents with bipolar depression. Journal of the American Academy of Child & Adolescent Psychiatry, 45(3), 289–297. https://doi.org/10.1097/01.chi.0000194569.70912.a7 

Patra, K. P., & Kumar, R. (2022). Screening for depression and suicide in children. In StatPearls [Internet]. StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK576416/ 

Polanczyk, G., de Lima, M. S., Horta, B. L., Biederman, J., & Rohde, L. A. (2007). The worldwide prevalence of ADHD: A systematic review and metaregression analysis. American Journal of Psychiatry, 164(6), 942–948. https://doi.org/10.1176/ajp.2007.164.6.942 

Pomarol-Clotet, E., Alonso-Lana, S., Moro, N., Sarró, S., Bonnin, M. C., Goikolea, J. M., Fernández-Corcuera, P., Amann, B. L., Romaguera, A., Vieta, E., Blanch, J., McKenna, P. J., & Salvador, R. (2015). Brain functional changes across the different phases of bipolar disorder. British Journal of Psychiatry, 206(2), 136–144. https://doi.org/10.1192/bjp.bp.114.152033 

Prasse, D. P., Breunlin, R. J., Giroux, D., Hunt, J., Morrison, D., & Thier, K. (2012). Embedding multi-tiered system of supports/response to intervention into teacher preparation. Learning Disabilities — A Contemporary Journal, 10(2), 75–93. 

Price, J. L., & Drevets, W. C. (2010). Neurocircuitry of Mood Disorders. Neuropsychopharmacology, 35(1), 192–216. https://doi.org/10.1038/npp.2009.104 

Rao, U. (2014). DSM-5: Disruptive Mood Dysregulation Disorder. Asian Journal of Psychiatry, 0, 119–123. https://doi.org/10.1016/j.ajp.2014.03.002 

Riley, M., Ahmed, S., & Locke, A. (2016). Common Questions About Oppositional Defiant Disorder. 93(7), 6. 

Rocha, T. B. M., Zeni, C. P., Caetano, S. C., & Kieling, C. (2013). Mood disorders in childhood and adolescence. Revista Brasileira de Psiquiatria, 35(suppl 1), S22–S31. https://doi.org/10.1590/1516-4446-2013-S106 

Sattler, A. F., Leffler, J. M., Harrison, N. L., Bieber, E. D., Kosmach, J. J., Sim, L. A., & Whiteside, S. P. H. (2019). The quality of assessments for childhood psychopathology within a regional medical center. Psychological Services, 16(4), 596–604. https://doi.org/10.1037/ser0000241 

Shahidullah, J. D., McClain, M. B., Azad, G., Mezher, K. R., & McIntyre, L. L. (2020). Coordinating Autism care across schools and medical settings : considerations for school psychologists. Intervention in School and Clinic, 56(2), 107–114. https://doi.org/10.1177/1053451220914891 

Shapiro, E. S., & Heick, P. F. (2004). School psychologist assessment practices in the evaluation of students referred for social/behavioural/emotional problems. Psychology in the Schools, 41(5), 551–561. https://doi.org/10.1002/pits.10176 

Silverman, W. K., Pina, A. A., & Viswesvaran, C. (2008). Evidence-based psychosocial treatments for phobic and anxiety disorders in children and adolescents. Journal of Clinical Child & Adolescent Psychology, 37(1), 105–130. https://doi.org/10.1080/15374410701817907 

Simonsen, B., Jeffrey-Pearsall, J., Sugai, G., & Mccurdy, B. (2011). Alternative setting-wide positive behaviour support. Behavioural Disorders, 36(4), 213–224. https://doi.org/10.1177/019874291103600402 

Sonuga-Barke, E., Bitsakou, P., & Thompson, M. (2010). Beyond the dual pathway model: evidence for the dissociation of timing, inhibitory, and delay-related impairments in Attention-Deficit/Hyperactivity Disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 49(4), 345–355. https://doi.org/10.1016/j.jaac.2009.12.018 

Stein, D. J., Palk, A. C., & Kendler, K. S. (2021). What is a mental disorder? An exemplar-focused approach. Psychological Medicine, 51(6), 894–901. https://doi.org/10.1017/S0033291721001185 

Steiner, H., & Remsing, L. (2007). Practice parameter for the assessment and treatment of children and adolescents with oppositional defiant disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 46(1), 126–141. https://doi.org/10.1097/01.chi.0000246060.62706.af 

Sugai, G., & Homer, R. R. (2006). A promising approach for expanding and sustaining school-wide positive behaviour support. School Psychology Review, 35(2), 245–259. https://doi.org/10.1080/02796015.2006.12087989 

Sullivan, A. L. (2013). School-based autism identification: prevalence, racial disparities, and systemic correlates. School Psychology Review, 42(3), 298–316. https://doi.org/10.1080/02796015.2013.12087475 

Szatmari, P., Jones, M. B., Zwaigenbaum, L., & MacLean, J. E. (1998). Genetics of autism: Overview and new directions. Journal of Autism and Developmental Disorders, 28(5), 351–368. https://doi.org/10.1023/A:1026096203946 

Takumi, T., Tamada, K., Hatanaka, F., Nakai, N., & Bolton, P. F. (2020). Behavioural neuroscience of autism. Neuroscience & Biobehavioural Reviews, 110, 60–76. https://doi.org/10.1016/j.neubiorev.2019.04.012 

Theule, J., Wiener, J., Rogers, M. A., & Marton, I. (2011). Predicting parenting stress in families of children with ADHD: Parent and contextual factors. Journal of Child and Family Studies, 20(5), 640–647. https://doi.org/10.1007/s10826-010-9439-7 

Thompson, T., Coleman, J. M., Riley, K., Snider, L. A., Howard, L. J., Sansone, S. M., & Hessl, D. (2018). Standardized assessment accommodations for individuals with intellectual disability. Contemporary School Psychology, 22(4), 443–457. https://doi.org/10.1007/s40688-018-0171-4

Treacy, L., Tripp, G., & Baird, A. (2005). Parent stress management training for attention-deficit/hyperactivity disorder. Behaviour Therapy, 36(3), 223–233. https://doi.org/10.1016/S0005-7894(05)80071-1 

Uher, J. (2016). What is Behaviour? And (when) is language behaviour? A metatheoretical definition. Journal for the Theory of Social Behaviour, 46(4), 475–501. https://doi.org/10.1111/jtsb.12104 

Van Meter, A. R., Youngstrom, E. A., Birmaher, B., Fristad, M. A., Horwitz, S. M., Frazier, T. W., Arnold, L. E., & Findling, R. L. (2017). Longitudinal course and characteristics of cyclothymic disorder in youth. Journal of Affective Disorders, 215, 314–322. https://doi.org/10.1016/j.jad.2017.03.019 

Vandenbosch, B., & Higgins, C. (1996). Information acquisition and mental models: An investigation into the relationship between behaviour and learning. Information Systems Research, 7(2), 198–214. https://doi.org/10.1287/isre.7.2.198 

Vassallo, S., Smart, D., Sanson, A., & Dussuyer, I. (2002). Patterns and precursors of teenage antisocial behaviour.

Villarreal, V. (2018). Mental health referrals: A survey of practicing school psychologists. School Psychology Forum, 12(2), 66–77. 

Volkow, N. D., Wang, G.-J., Kollins, S. H., Wigal, T. L., Newcorn, J. H., Telang, F., Fowler, J. S., Zhu, W., Logan, J., Ma, Y., Pradhan, K., Wong, C., & Swanson, J. M. (2009). Evaluating dopamine reward pathway in ADHD: Clinical Implications. JAMA, 302(10), 1084. https://doi.org/10.1001/jama.2009.1308 

Watkins, M. W., Crosby, E. G., & Pearson, J. L. (2001). Role of the school psychologist: perceptions of school staff. School Psychology International, 22(1), 64–73. https://doi.org/10.1177/01430343010221005 

Webster-Stratton, C. (2001). The incredible years: parents, teachers, and children training series. Residential Treatment for Children & Youth, 18(3), 31–45. https://doi.org/10.1300/J007v18n03_04 

Webster-Stratton, C., Reid, M. J., & Beauchaine, T. P. (2013). One-year follow-up of combined parent and child intervention for young children with ADHD. Journal of Clinical Child and Adolescent Psychology: The Official Journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53, 42(2), 251–261. https://doi.org/10.1080/15374416.2012.723263 

Wheaton, M. G., Deacon, B. J., McGrath, P. B., Berman, N. C., & Abramowitz, J. S. (2012). Dimensions of anxiety sensitivity in the anxiety disorders: evaluation of the ASI-3. Journal of Anxiety Disorders, 26(3), 401–408. https://doi.org/10.1016/j.janxdis.2012.01.002 

Wiener, J. (2020). The role of school psychologists in supporting adolescents with ADHD. Canadian Journal of School Psychology, 35(4), 299–310. https://doi.org/10.1177/0829573520923536

Whelan, Y. M., Stringaris, A., Maughan, B., & Barker, E. D. (2013). Developmental continuity of oppositional defiant disorder subdimensions at ages 8, 10, and 13 years and their distinct psychiatric outcomes at age 16 years. Journal of the American Academy of Child & Adolescent Psychiatry, 52(9), 961–969. https://doi.org/10.1016/j.jaac.2013.06.013 

Wiggins, L. D., Rice, C. E., Barger, B., Soke, G. N., Lee, L.-C., Moody, E., Edmondson-Pretzel, R., & Levy, S. E. (2019). DSM-5 criteria for autism spectrum disorder maximizes diagnostic sensitivity and specificity in preschool children. Social Psychiatry and Psychiatric Epidemiology, 54(6), 693–701. https://doi.org/10.1007/s00127-019-01674-1 

Wiggins, J. L., Briggs-Gowan, M. J., Brotman, M. A., Leibenluft, E., & Wakschlag, L. S. (2021). Don’t miss the boat: towards a developmental nosology for disruptive mood dysregulation disorder in early childhood. Journal of the American Academy of Child and Adolescent Psychiatry, 60(3), 388–397. https://doi.org/10.1016/j.jaac.2020.04.015 

Wilhelm, P., & Schoebi, D. (2007). Assessing mood in daily life. European Journal of Psychological Assessment, 23(4), 258–267. https://doi.org/10.1027/1015-5759.23.4.258 

Wright, A. W., Parent, J., Forehand, R., Edwards, M. C., Conners-Burrow, N. A., & Long, N. (2013). The relation of parent and child gender to parental tolerance of child disruptive behaviours. Journal of Child and Family Studies, 22(6), 779–785. https://doi.org/10.1007/s10826-012-9632-y 

Youngstrom, E. A., Youngstrom, J. K., & Hamilton, J. (2005). Evidence-based assessment of pediatric bipolar disorder, part II: incorporating information from behaviour checklists. Journal of the American Academy of Child & Adolescent Psychiatry, 44(8), 823–828. https://doi.org/10.1097/01.chi.0000164589.10200.a4 

Youth Mental Health Canada (YMHC) (2019). Youth mental health reality: the difference we can make. Youth Mental Health Canada. https://ymhc.ngo/resources/ymh-stats/  

 

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