Professional School Counseling Journal Cbt and Problem Solving

One: Effective Cognitive Behavioral Therapy in Schools

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DOI:

10.1891/9780826183132.0001

Abstract

INTRODUCTION

At its essence, counseling is the art of facilitating a trusted and guided conversation that fosters healthy thoughts and behaviors as well as inspires personal insight. Much like the supportive conversations that evolve around social interactions with family and friends, first understanding an individual's needs while establishing rapport is the foundation for counseling. In its most sophisticated form, counseling is the applied science of astutely recognizing thought patterns and then matching evidence-based strategies to needs in order to optimize positive change. Within the plethora of research studies on counseling techniques, cognitive behavioral therapy (CBT) is highly regarded as a first-line treatment for many mental health and personal stressor needs (Silverman et al., 2008). This text focuses on the provision of effective CBT from the initial techniques of rapport building and microskills, facilitating counseling session discussions, to the components that are most efficacious for specific mental health needs. Understanding these precision targeted components allows counselors to streamline intervention, conserving valuable time and resources, so clients are well served and institutions can effectively meet the needs of individuals.

OVERVIEW OF MENTAL HEALTH NEEDS OF CHILDREN IN THE UNITED STATES

The provision of school-based mental health support services has been a long-standing priority for best practice service delivery models in school counseling, school psychology, and school social work associations (American School Counselor Association, 2014; National Association of School Psychologists, 2010; School Social Work Association of America, 2013a). In fact, multiple educational reform efforts have called for further enhancing the integration of mental health services into schools (Atkins, Hoagwood, Kutash, & Seidman, 2010; Schelar, Lofink Love, Taylor, Schlitt, & Even, 2016).

As noted in the Individuals with Disabilities Education Improvement Act (IDEIA, 2004, Part 300 A, Section 300.34 [c][2]), highly qualified school professionals with appropriate training, such as guidance counselors, psychologists, school psychologists, and social workers, are ideally positioned to be the first-line providers of counseling services to children and youth. With training in mental health issues and counseling techniques, these related-service school personnel have valuable expertise to contribute in serving children with mental health needs (American School Counselor Association, 2015; Center for Mental Health in Schools at UCLA, 2014; Joyce-Beaulieu & Rossen, 2014; National Association of School Psychologists, 2010; School Social Work Association of America, 2013b).

In their graduate training, psychologists, school psychologists, counselors, and social workers all receive knowledge of and experience in delivering counseling services to youth and thus are well positioned to provide these services. However, studies also indicate that regardless of their initial training, practitioners also benefit from ongoing training in best practices methods, such as CBT. This continued training serves to help practitioners maintain and enhance skills as well as remain diligent in bridging the gap between practice and emerging research (Beidas & Kendall, 2010). In surveys of therapists and school psychologists, school-based practitioners cite insufficient training and knowledge as barriers to providing these mental health supports (Beidas & Kendall, 2010; Castillo, Arroyo-Plaza, Tan, Sabnis, & Mattison, 2017; Suldo, Friedrich, & Michalowski, 2010). As an example, in a nationally representative sample survey, Hanchon and Fernald (2013) discovered over 90% of school psychology practitioners indicated that they had knowledge and training in counseling techniques but nearly 40% indicated that they felt less than sufficiently prepared in providing individual counseling services in schools, whereas over 40% indicated they felt less than sufficiently prepared to provide group counseling. Other studies note general practitioner criticism of formal treatment manuals and difficulty navigating counseling services within the institutional context of schools (Beidas & Kendall, 2010). In response to these needs, this book endeavors to provide school-based practitioners, whether they are new to the field or seasoned veterans, easily accessible tools to utilize when providing effective CBT for students and offers numerous examples of practical school-based applications. This chapter provides an overview of the use of CBT within schools and the multitiered systems of support (MTSS) model, whereas Chapter 2, Cognitive Theoretical Foundations, and Chapter 3, Cognitive Behavioral Therapy Essential Components, discuss CBT theoretical foundations and essential components. The second section of the text (i.e., Chapter 4, Emotional and Behavioral Regulation Strategies, through Chapter 6, Applied Cognitive Behavioral Therapy Session Activities) offers specific counseling techniques, utilizing a number of session activities and worksheet resources (found in the Appendix). Lastly, Chapter 7, Case Studies, provides case studies that integrate CBT intervention as applied within a school setting. These case studies give a "real-world" context for many of the techniques described in the book.

The delivery of school-based counseling is important in that it removes many of the barriers to services, such as missed appointments due to transportation challenges, the hardship of lost employment time for parents, and the financial strain on families to pay for private mental health treatment. Moreover, integrating counseling as a key component of school intervention service delivery can be highly beneficial for students because youth are available multiple days per week to receive these services. Counseling plans can be coupled with classroom behavior strategies to foster generalization of skills, and a plethora of opportunities exist for teachers to reinforce concepts within their classrooms throughout the day. Additionally, school-based service delivery offers many opportunities to observe and monitor newly learned strategies in an authentic setting, which can help ensure that lasting behavioral changes are achieved. Research suggests that providing school-based mental health services also can reduce disparities in the utilization of mental health services among minority youth (Cummings, Ponce, & Mays, 2010) given that school systems provide equal access to services regardless of the financial resources of families.

A report from the U.S. surgeon general estimates that 20% of school-age children experience mental health problems in any given year. Of those students who will experience significant mental health needs, nearly 10% to 15% will suffer significant impairment in their ability to learn, be successful at school, make and keep friends, and maintain positive relationships with their caregivers (Merikangas et al., 2010; U.S. Department of Health & Human Services [USDHHS], 2000). Another indicator of student adjustment risk is school dropout. Unfortunately, within the general population, only about 82% (i.e., 4 out of every 5) of students in the United States successfully graduate from high school with a regular diploma within 4 years of entering ninth grade. This results in thousands of students dropping out of school each day in the United States (McFarland, Stark, & Cui, 2018). Regular diploma graduation rates vary significantly by state with the District of Columbia lowest at 61% and Iowa highest at 91%. Thirty-five states maintain averages at 80% or higher. Differential graduation rates also exist across gender, income, recency of immigration, race/ethnicity, and disability status. Males and students with low-income circumstances are overrepresented as dropouts across all race/ethnicities, and low-income students have a higher dropout rate than middle- or high-income students (9.4%, 5.4%, and 2.6%, respectively). Among those students with low income, students who also experience homelessness are especially vulnerable for both dropout and mental health distress (Sulkowski & Michael, 2014). Hispanic students born outside the United States have a 21% dropout rate (3.9% for non-Hispanic students) with first-generation students' dropout rates decreasing to 7.1% for Hispanic and 2.2% for non-Hispanic students (McFarland et al., 2018).

In 2013–2014, the regular diploma graduation rate within 4 years of entering ninth grade was 87% for White students, 76% for Hispanic students, and 73% for Black students (McFarland et al., 2018). For students of Hispanic heritage, the dropout rates also differed significantly by subgroups, as those of Cuban, Spaniard, Costa Rican, Panamanian, Colombian, Peruvian, and Venezuelan descent have lower than national mean dropout rates. In contrast, dropout rates for students from Guatemalan and Honduran descent are quite high: 28.7% and 19.5%, respectively (McFarland et al., 2018). Likewise, students of Asian descent generally have lower than mean dropout rates with the exception of Nepalese and Burmese descent: 19.6% and 27.5%, respectively. When data include high school completed by alternative means (e.g., general education diploma [GED]), graduation rates increase for most groups (i.e., White 94%, Black 92%, Hispanic 87%, Asian 99%, Pacific Islander 94%, American Indian/Alaska Native 79%, two or more races 97%; male 92% and female 93%). These data are lower for students with disabilities even when including alternative graduation status (with disability 84%, without disability 93%). For students receiving services for emotional disturbance (ED) under IDEIA, the dropout rate (i.e., no less than 35% from 2005 to 2015) is higher than in any other disability category, including those with intellectual disabilities (U.S. Department of Education [USDOE],Office of Special Education and Rehabilitative Services, & Office of Special Education Programs, 2018). Across the data, individuals with disabilities, especially ED, males, low income, native-born, American Indian/Alaska Native, and some subgroups within broad race/ethnicity groups appear to be most vulnerable. Therefore, they are likely to need and benefit from social–emotional and counseling supports. Given the unique life circumstances of these individuals, cultural considerations also are warranted in delivering services. Chapter 3, Cognitive Behavioral Therapy Essential Components, to Chapter 5, Exposure and Response Prevention and Cognitive Behavioral Therapy, offer additional information of cultural awareness and competencies for delivering counseling.

Lastly, mental health issues among youth are a global problem that extends well beyond the boundaries of the United States. In this regard, a study by the World Health Organization indicates that mental health problems account for nearly half of all disabilities internationally among individuals between the ages of 10 and 24 (Gore et al., 2011). Of those in need of mental health services worldwide, less than half receive services (Patton et al., 2012), illustrating the significant need. The provision of high-quality and targeted counseling interventions can assist students experiencing these difficulties to stay in school and to complete their education. Collectively, these findings highlight a critical need to provide mental health interventions to at-risk students before their problems become pervasive or chronic.

Schools and school-based mental health professionals can have a significant impact on addressing the unmet emotional, behavioral, and adjustment needs of youth. Research indicates that the majority of youth (i.e., 70%–80%) who do receive mental health services access these services through their local school districts (Bains & Diallo, 2016; Dowdy et al., 2015). Based on these data, the American Academy of Pediatrics (n.d.) has advocated for the provision of more school-based mental health services, noting the benefits of better access to assessment/evaluation or intervention compliance. As part of their initiatives, they endorsed the Mental Health in Schools Act of 2015 (H.R. 1211), which calls for increased funding and health student programs in schools to promote student well-being. Additionally, through the surgeon general's national agenda, mental health services are considered a national priority for all children, including intervention research and behavioral support delivered within the school. In particular, students from underrepresented groups, those living in poverty, and those with disabilities may demonstrate vulnerabilities that warrant considerations for early school-based intervention services (Bains & Diallo, 2016; Dowdy et al., 2015).

Counseling in schools can come in many forms, and it can be tailored to support a wide variety of developmental concerns. In elementary school, first-tier counseling services often include addressing systems-wide issues related to bullying prevention, character values, stress reduction, prosocial life skills, and consulting on educational issues. Second-tier counseling services often provide small-group and individual counseling. Examples may include friendship groups for new or shy students, self-esteem building, teaching self-regulation in regard to classroom rules or expectations, peer mediation, conflict resolution, grief counseling, organization skills, understanding body changes as puberty approaches, addressing abuse or family crisis, and advising on personal hygiene or appropriate social boundaries. Addressing all of these needs generally involves explicitly teaching skills to the child through counseling strategies or collaborating with the family to improve the student's response to temporary life stressors. In middle and high school, first-tier systems-wide counseling services may include life skills training, bullying prevention, and substance use prevention, as well as consultation as a member of leadership teams on educational issues. Second-tier, short-term, or individualized counseling interventions for older students often address increasing interpersonal communication skills, goal setting, social skills, and career planning. All of these counseling functions noted are vital in schools. However, for students with the most pervasive and severe mental health disorders, the services noted previously may not be adequate, as these students require more extensive and formalized therapeutic approaches, such as CBT, to address social and emotional dysfunction.

DSM-5 CHILD AND ADOLESCENT DIAGNOSES AND AGE OF ONSET

A brief overview of the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association [APA], 2013) diagnoses that are common to school-age children is provided in this section, as students with these symptoms are most likely to require more intensive or therapeutic counseling interventions. However, it is important to note that the CBT techniques expressed throughout this book also can be applied to a wide range of adjustment, behavioral, and social–emotional needs for youth even if a formal diagnosis is not indicated. A wealth of research over the past few decades indicates that very specific components of CBT are well suited and effective for treating many specific disorders and thinking distortions; however, the same CBT components are not equally effective for each type of diagnosis. For example, exposure and response prevention (E/RP, see Chapter 5, Exposure and Response Prevention and Cognitive Behavioral Therapy), a type of therapy that falls under the CBT umbrella and involves facing one's fears while abstaining from engaging in anxiety-reductive compulsions, has been found to be a first-line treatment for obsessive-compulsive disorder (OCD) in children (Jordan, Reid, Mariaskin, Augusto, & Sulkowski, 2012). In contrast, the same CBT method of E/RP could be contraindicated for a child with conduct disorder. Being aware of specific symptoms of these disorders can assist in planning CBT sessions to focus on the correct targeted skills and avoiding wasted time and counterproductive methods (Soutullo, Palma, & Joyce, 2014; Sulkowski, Joyce, & Storch, 2011).

Research suggests that over one-half of all lifetime mental health diagnoses first manifest during childhood/adolescence, and up to three-fourths of all syndromes emerge before age 24 (Kessler et al., 2005). The early emergence of a wide range of mental health issues is illustrated in Figure 1.1, which provides a review of the DSM-5 (APA, 2013). Therefore, it is important for school-based counselors to consult the DSM-5 when they are seeking to better understand the students they work with who have mental health diagnoses. The DSM-5 also can offer insight for conceptualization of intervention plans, alert practitioners to common co-occurring symptoms, and offer insights on gender, race/ethnicity, socioeconomic status (SES), and cultural considerations (Joyce-Beaulieu & Sulkowski, 2016).

Elementary behavior specialists, social workers, counselors, and school psychologists are likely to receive the initial teacher referrals for disorders. Depending on the developmental course of specific syndromes, the age of onset varies and thus may be initiated at different points in a child's educational experience. Therefore, practitioners who are in elementary schools may encounter significantly different child needs from those who are primarily serving students in secondary education settings (see Table 1.1). With appropriate intervention, some emotional stressors and diagnoses seem to resolve within a prescribed time frame (e.g., reactive attachment disorder, typical school adjustment), whereas others are more episodic based on stressors and temporal factors (e.g., adjustment disorders, major depressive disorder) that can recur along with negative life events throughout a student's educational years. Symptoms of other mental health disorders are chronic in nature (e.g., attention deficit hyperactivity disorder [ADHD], autism spectrum disorder, and schizophrenia). They may require more sustained school and even community services throughout the youth's educational experience. The following list denotes disorders that are most likely to occur first during specific grades and are more likely to be treated initially by counselors in those school levels.

Figure 1.1

Common DSM-5 psychiatric disorders with prevalence rate and typical age of initial diagnosis.

Note: Data in this table are based on DSM-5 prevalence, development, and course information related to childhood through early adulthood, unless data were available only for adults. Neurocognitive and substance use disorders are excluded. Light shading indicates pre-K to 12th grade; dark shading denotes college age.

ADHD, attention deficit hyperactivity disorder; DSM-5, Diagnostic and Statistical Manual of Mental Disorders, 5th edition; F, female; M, male; ?, unknown based on DSM-5.

• Preschool or elementary school: ADHD, autism spectrum disorder, reactive attachment disorder, selective mutism, separation anxiety, specific phobia, and Tourette's disorder

• Middle and high school: excoriation (skin-picking) disorder, social anxiety disorder, and trichotillomania (compulsive hair-pulling disorder)

• Postsecondary/college: antisocial personality disorder, avoidant personality disorder, bipolar type I disorder, borderline personality disorder, histrionic personality disorder, narcissistic personality disorder, obsessive-compulsive personality disorder, and paranoid personality disorder

Other disorders are more variable in their onset range, as noted in Table 1.1, with onset ages that span from childhood to adolescence or preadulthood. These disorders include the following: adjustment disorder, anorexia nervosa, bulimia nervosa, conduct disorder, disruptive mood dysregulation disorder, generalized anxiety disorder, hoarding disorder, major depressive disorder, OCD, oppositional defiant disorder (ODD), panic disorder, persistent depressive mood disorder, posttraumatic stress disorder (PTSD), schizoid personality disorder, schizophrenia, schizotypal personality disorder, and somatic symptom disorder. As the onset of these disorders spans across different academic years, practitioners serving children of all ages will likely need counseling skills to help students who are affected by these disorders.

Specific mental health supports and transition services are often needed to help students with disorders that present during adolescence and young adulthood. School-based mental health service providers may be involved with formal efforts to prepare students with mental health needs for successful entrance into postsecondary education settings and related opportunities through their participation in federally mandated transition planning efforts (Joyce & Grapin, 2012; Joyce-Beaulieu & Grapin, 2014; Sulkowski & Joyce, 2012).

Beginning at age 16, written transition supports are legally mandated and written into the individualized education plans of students with disabilities (USDOE, 2011). Depending on the student, these supports may include counseling interventions that build self-efficacy, mental health wellness, and/or self-advocacy for continuing mental health supports in college or in workplace transitions. Services for students with disabilities also extend to direct service provision in postsecondary education mental health centers and college disability centers for traditional college enrollment. Now more than ever, the lines are blurred between high school and college, as 82% of high schools offer dual enrollment, according to the National Center of Education Statistics (NCES) report (Marken, Gray, & Lewis, 2013). The number of students in adolescence receiving instruction in college settings for at least part of the day is on the rise (National Research Center for Career and Technical Education, 2010; USDOE, 2011). Students utilizing dual enrolment are typically in ninth grade or higher (although some states, such as Arizona, have no age limit). Therefore, counseling for high-school students may occur within the postsecondary institution in which they are dual enrolled.

TABLE 1.1

Behavior Modification Strategies

Technique	Description and Goals	Key Points for Implementation
Shaping	Shaping is utilized to encourage an individual to exhibit a target behavior by reinforcing successive approximations of that behavior over time. It is best applied when there is a large gap between a student's current behaviors and the desired behaviors.	Identify target or desired behavior goal. Identify a behavior in the individual's present repertoire as a starting point for reinforcement. Select an appropriate reinforcer. Create a sequence of successive approximations of the behavior. Reward successive approximations of the behavior until the child arrives at the target behavior. For example, if targeting completing math worksheets, start by rewarding completion of one item, then two items, and so on, to completion.
Fading	Fading is used to encourage an individual to demonstrate a target behavior across multiple settings. This is accomplished by gradually changing one setting, in which the behavior already occurs, to a second setting. Note: This technique calls for changes in settings rather than changes in behaviors.	Identify the setting in which the behavior is already occurring. Identify a setting in which the behavior should occur (i.e., target environment). Create a sequence of successive approximations of the target environment. Use a token economy to reward the display of appropriate behaviors in the target setting as the child progresses through this sequence. For example, if a child learns to control anxiety in counseling sessions but cries when in class, gradually increase the number of persons in counseling activities, until she or he is more comfortable with others, and then move to a classroom full of students.
Chaining	Chaining is used to encourage the student to exhibit a series of related behaviors (i.e., to strengthen a sequence of new responses that ultimately elicit the target behavior). Chaining can also be used to weaken maladaptive behavior patterns.	Identify response patterns in the old behavior chain, starting back far enough to include responses that prompt the undesired behavior. Write a new behavior chain that prompts the target behavior. Model the new behavior chain, and have the child follow the new sequence. Reinforce the child for successfully implementing the new chain. For example, if a student is chronically late from lunch, teach a new response (e.g., clean lunch tray up earlier, quicker route back to class), model and remind her or him; if she or he forgets, walk back to cafeteria and rehearse.
Contingency contracting	Contingency contracting is used to increase the occurrence of a low-frequency behavior. In this technique, permission to engage in high-frequency behaviors is made contingent on the performance of a low-frequency behavior.	Establish a contract to determine the terms of contingency between the low- and high-frequency behaviors. Reward the child frequently with smaller amounts of the preferred or high-frequency activity and only after he or she has executed the low-frequency behavior (i.e., do not provide noncontingent reinforcement). For example, give 10 minutes of preferred computer time for 1 hour of work completion.
Token reinforcement	The purpose of token reinforcement is to increase the occurrence of desirable behaviors and/or to decrease the occurrence of problematic behaviors by systematically reinforcing the goal behavior.	Identify and define problematic behaviors as well as appropriate replacement behaviors. Identify tokens, feasible reinforcers, and a schedule of reinforcement. Provide reinforcers when desired behavior occurs. Implement a response cost when inappropriate behaviors are exhibited. For example, a child earns tokens toward a reinforcer for work completed; not turning in assignments could result in token reduction.
Replacement behavior training	Replacement behavior training is used to teach new behaviors and skills that can be used in place of problematic behaviors.	Identify and define the problematic behavior. Identify and teach the individual replacement behaviors. This may require modeling and opportunities for student practice. Implement schedule of reinforcement for replacement behaviors. For example, each time a student prone to impulsive anger says "excuse me" or uses an "I" statement, offer points toward earning a reinforcer.
Interdependent group-oriented contingency management	This technique is a group management system that reinforces the behaviors of a group as a whole. The goal of this strategy is to increase appropriate behaviors while simultaneously decreasing classroom disruptions; groups also may persuade individuals to cooperate.	Divide the class into groups or teams. Model appropriate behaviors and instruct students to role-play behavior. Identify a group reinforcer (e.g., points, reward). Post a visual representation of points earned or lost. Reinforce the winning team at predetermined intervals. For example, groups caught displaying good social skills earn points (e.g., helping others, quiet group projects, saying "thank you").
Precorrection and prompting	This technique is designed to encourage the display of appropriate or desirable behaviors, especially when it is likely that the individual will need reminders to do so.	Identify the context in which problem behaviors typically occur and clarify behavioral expectations for that setting. Define/model expected behaviors, have student role-play behavior. Provide reinforcement for appropriate behaviors. Provide cuing and prompting as needed for appropriate behaviors. For example, prompting a withdrawn student to join a group or cuing the student on introductory comments (e.g., "Say hello to Juan").
Differential reinforcement of alternative or incompatible behavior	The purpose of this technique is to weaken maladaptive behaviors by simultaneously strengthening an incompatible or competing response.	Identify and define the problematic behavior. Identify a competing behavior (i.e., one that will be incompatible with the problem behavior). Reinforce occurrences of the competing behavior while ignoring or redirecting the student when the problematic behavior occurs. For example, when targeting classroom running, reward in-seat behavior or walking behaviors.
Self-monitoring	Self-monitoring is used to increase the individual's awareness of his or her behaviors and to encourage him or her to self-regulate while working toward a goal.	Identify target behavior to be monitored. Set intervention goals as well as time frame for goal. Provide child with a cuing graphic, list, or behavior chart. Define and describe steps for self-monitoring the behavior and model them for the student. For example, a shy student might mark his or her own behavior chart each time he or she initiates a conversation with someone; try to increase total interactions each day or weekly.
Self-reinforcement	This technique is used to encourage students to reinforce their own appropriate behaviors with either tangible or intangible rewards.	Identify an appropriate reinforcer. Determine contingencies for earning the reinforcer. Describe and model steps for earning and accessing the reinforcer. For example, student can self-initiate a 2-minute Internet surfing break after 30 minutes of work completion in the library.

Source: Alberto, P. A., & Troutman, A. C. (2012). Applied behavior analysis for teachers (9th ed.). New York, NY: Pearson; Kaplan, J. S., & Carter, J. (1995). Beyond behavior modification: A cognitive-behavioral approach to behavior management in the school (3rd ed.). Austin, TX: Pro-Ed.

COUNSELING WITHIN MTSS IN SCHOOLS

Although a wide range of mental health high-quality services are available through community agencies and private practitioners, a review of the status of national mental healthcare for youth indicates that those services are most often accessed in a fragmented and noncomprehensive manner. This has often resulted in low service effectiveness, especially for more chronic or severe mental health problems (USDHHS, 2000). Response to intervention (RtI) and MTSS are models of school-based service delivery that have evolved over the past few decades to provide schools with the infrastructure to offer a continuum of multifaceted counseling and behavioral supports to students who display a range of academic, behavioral, and mental health needs (Cook et al., 2015; Sulkowski & Michael, 2014; Sulkowski, Wingfield, Jones, & Coulter, 2011). When mental health services are well integrated into a systematic model, academic outcomes improve, behavioral referrals decrease (Hussey & Guo, 2003), and there are reduced disparities for students who receive services (Cummings et al., 2010).

The overarching RtI/MTSS frameworks incorporate a multitiered approach to service delivery to help students at varied levels of need (Elliott & Morrison, 2008; Kurns & Tilly, 2008). At the first tier of service delivery (tier I), general emotional and behavioral health as well as preventive universal or school-wide services are delivered. Examples may include prosocial social–emotional learning curricula embedded within the classroom instruction and positive behavioral intervention and supports (PBIS) framework for structuring school environments for all students. Tier I services meet the needs of approximately 80% to 85% of students. At the second tier (tier II), interventions are provided for students who display needs that cannot be adequately addressed by tier I services alone and are at risk for academic failure or other negative outcomes. Tier II services are predicted to serve 5% to 15% of the population, and these services are designed as short-term, low-intensity interventions that may be structured around a protocol or prescribed curricula. They often are provided once or twice a week for 6- to 12-week periods and can be delivered in group settings. Tier II interventions tend to address more common student needs and may include elements of CBT as needed (e.g., relaxation training, identifying negative emotional states, understanding cognitive triad), although other methods may be employed as well. Examples of tier II counseling interventions might include friendship groups, social skills training groups, self-esteem building exercises, problem-solving skills, test anxiety, or conflict resolution strategies. Within a typical school setting, there is generally a continued and revolving need for tier II counseling groups, especially around key student transitions (e.g., adapting to a new school, bereavement or loss, coping with teen relationship stressors). When students respond well to the intervention, a problem-solving team may decide to discontinue. If it is determined that a more intensive intervention is needed, students are provided more individualized, longer-term, and often more frequent intervention. This third tier (tier III) often supports 1% to 5% of the student population. Examples might include a semester or more of CBT therapy sessions, meeting two or more times per week, to address depression or a sequence of anger management/self-regulation interventions.

Students requiring tier III services often have a multifaceted support plan that also may include other behavioral interventions in addition to counseling (e.g., mentoring, daily behavior report cards, positive reinforcement plans to increase generalization of new behaviors taught in counseling sessions). For students with needs that require sustained intervention, special education eligibility may be considered with a classification of ED. Once identified, individuals receiving ED services may continue to require a structured counseling regimen for multiple years as well as supplemental mental health supports (e.g., behavior modification, outside counseling or family therapy coupled with school counseling, and sometimes psychopharmacology). A quick review of behavioral modification strategies that school personnel can utilize to supplement counseling or enhance multifaceted interventions is noted in Table 1.1.

Progress Monitoring

A key factor in well-implemented RtI/MTSS intervention models is the mandate for data-based decision-making and the utilization of progress-monitoring measures to track student outcomes. Progress monitoring offers a number of benefits, including feedback to the counselors on how well interventions are working, information to decide when goals are met and therefore when counseling can be ended, as well as guidance on when students may require more intense services or multifaceted intervention plans. This section reviews several easy methods for collecting progress-monitoring data on the effectiveness of counseling interventions: naturally occurring school performance data, observational data, knowledge/skills testing, daily behavioral report cards, behavior rating scales, subjective units of distress (SUDs) data, and the DSM-5 cross-cutting symptomology measures.

Best practices associated with psychoeducational assessment involve employing a multifaceted approach that includes gathering information across multiple settings, at multiple times, and from multiple sources, using multiple data collection methods (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 2014; Saklofske, Joyce, Sulkowski, & Climie, 2013). Although originally written for comprehensive test design, these principles also are valuable for conducting brief intervention outcome-related measurements, such as pre- and postintervention assessments. By acquiring data across multiple settings, personnel can ensure that the student is applying the new skills throughout the day and generalizing to other contexts outside the counseling sessions. These data provide strong evidence that a student has adopted the new strategies and the counseling has had positive impact. A benefit of gathering information multiple times is to establish that new knowledge or improved emotional mood is stable. For example, measuring a child's feelings of sadness across several sessions and establishing a period of time that their mood improves and stabilizes can indicate effectiveness and perhaps a good rationale for closing the intervention, whereas a couple of session of not feeling sad does not provide enough information to determine whether intervention should be withdrawn. Additionally, if the first measures are made prior to the counseling, the data will provide information on the student's baseline level of functioning in a particular domain (e.g., anxiety, social skills) that can be compared to later levels of functioning that are assessed during or after counseling to provide stronger evidence of improvement. By collecting information on a student's level of functioning across multiple sources (e.g., teacher, parent, self-report), possible rater biases can be controlled. For example, a parent's overly optimistic perceptions of his or her child may not be supported by data provided by another caregiver or by adults at school.

Of course, to rule out or control for rater biases, high-quality rating measures are needed. These include validity scales that alert practitioners to inconsistent or overly negative/positive rating patterns. Through measuring multiple variables, practitioners also can ensure that complex sets of skills are thoroughly assessed before recommendations to change or discontinue services are made. An example of this might include measuring an adolescent's knowledge of new relaxation techniques and problem-solving strategies as well as obtaining his or her self-rated feelings of anger.

Additionally, interviewing the student directly can provide qualitative information on state-of-mood, attitudes, and perceptions, which will be important to informing therapy sessions. For students who are reticent to share their thoughts verbally, therapists may find sentence completion exercises or if/then questionnaires helpful (see Appendix Exhibits 1.1–1.3 for examples). These data coupled with observations of her or his use of the relaxation techniques in a natural setting (e.g., in class when frustrated, during competitive physical education activities) and decreasing discipline referrals for angry outbursts would offer a well-rounded set of data for intervention decision-making that would be consistent with an RtI model of assessment and service delivery.

Traditionally, intervention effectiveness decisions have relied on anecdotal evidence (e.g., teacher report of improvement), which subsequently left unanswered questions about whether reported changes were stable, enduring, adequately learned, and generalizable to other settings, thus transportable to other contexts or applicable in similar situations that the student may encounter. Fortunately, there are many quick and easy progress-monitoring methods available that offer greater validity and reliability than anecdotal reports. The following sections offer a brief review of counseling progress-monitoring methods with the understanding that the practitioner's choice of specific methods (or combinations of measures) will depend on the complexity of the presenting problems displayed by the student and the targeted goals of CBT.

Naturally Occurring School Data

A number of readily available sources of behavioral data can be easily accessed by school-based mental health practitioners. These sources do not require extra data collection effort or time for counselors and thus are highly efficient. Often, these data are directly related to the counseling referral concerns and the preferred outcomes that are desired after intervention. As an example, for students with externalizing or acting-out behavioral problems, important and relevant school data to track include office discipline referrals (ODRs), in-school suspensions (ISSs), and incidents of out-of-school suspensions (OSSs). For youth with the aforementioned problems and a significant discipline history, counseling strategies often aim to foster self-regulation, anger management, or conflict resolution skills, which, if successfully learned and applied, likely will result in reductions in ODR, ISS, and OSS incidents. Similarly, for students who are disengaged academically, do not participate in class, have low work completion, and have difficulty meeting deadlines for projects, monitoring work completion and grades related to assignments can provide a direct measure of whether counseling to address academic motivation is being effective.

For students with social anxiety who may avoid performance assignments (e.g., oral presentation, group projects) and also may exhibit high rates of absenteeism, attendance data, number of days tardy, and completion of key assignments requiring public evaluation are easily accessible data sources that can help with measuring the efficacy of intervention. As another example, for anxious students with high numbers of unjustified nurse visits and unnecessary requests to go home for somatic complaints (e.g., headaches, stomach pains), their nurse visit data can be tracked across the counseling intervention sessions to show improvements. Nurse visits are logged daily and thus are easy-to-access and naturally occurring data within school systems.

Figure 1.2 provides an example of using naturally occurring school data for progress monitoring during the course of counseling intervention. To assess therapeutic progress, ODR, ISS, and school absences were reviewed, as these data were tracked by schools as part of their general operating procedures and readily available for review. Weeks 1 to 3 are baseline data, and weeks 4 to 12 represent data during counseling. The counseling sessions aimed to address impulse control difficulties in a student that resulted in numerous altercations with classmate, disciplinary referrals, and subsequent school avoidant problems.

Figure 1.2

Naturally occurring school data progress-monitoring sample.

ISS, in-school suspension; ODR, office discipline referral.

To help this student, cognitive restructuring was provided to challenge two cognitive distortions: jumping to negative conclusions and mind reading. In addition, anger management skills were taught that aimed to increase the student's emotional regulation skills, and the use of "I" statements was taught to help the student communicate his needs better in a nonconfrontational manner. Lastly, the student was taught conflict resolution skills (i.e., generating nonaggressive yet effective solutions for addressing interpersonal conflicts). Counseling for this student was individualized and delivered two times a week (30 minutes per session) for 9 weeks, totaling 18 sessions. Additionally, avoidance issues related to school attendance were addressed. Data indicate the student's ODR and ISS incidents steadily diminished to zero incidents and stabilized there for several weeks, so counseling appears to have had a positive effect, at least on part of the goals for better self-regulation. However, absences were only modestly improved during the intervention time frame; thus, additional interventions to address attendance were warranted.

Observational Data

School-based mental health professionals are highly familiar with observational data, as these data are often requested by teachers who are trying to better understand puzzling or maladaptive student behaviors, physicians who are diagnosing ADHD or monitoring medication effects, as well as parents who have concerns regarding the interpersonal actions of their children. Observational data also can be utilized to measure counseling outcomes. Examples might include pre- and postintervention data for on-task behaviors when the goals of counseling are addressing self-regulation, attention, frustration tolerance, withdrawal, or work completion. Several factors can increase the utility of observational data: assuring that baseline functioning is documented for comparison to intervention measures, collecting samples across classes and times of day, and establishing peer comparisons.

Figure 1.3

Observational data progress-monitoring sample; frequency of maladaptive behaviors during math quizzes.

An example of observational data is noted in Figure 1.3 for an anxious student with a history of maladaptive test behaviors that included significant nail biting, loud finger tapping, and episodes of staring off. These behaviors were interfering with her test performance specifically in math, a class she struggled in academically as she was preoccupied with worry and not finishing quizzes in the allotted time. Therefore, a goal of counseling was to challenge her cognitive distortions associated with catastrophizing: "I'll never pass math," "I can't get answers right on math tests," and "I'll never graduate or go to college without math." Further, a second goal was to teach her more appropriate replacement strategies that she could employ when she was anxious (e.g., four-square breathing relaxation technique, positive self-affirmations). Observations were taken each Friday using time sampling method for 20 minutes with 30-second intervals during the weekly math quiz. The first 2 weeks' baseline data were collected. Weeks 3 to 8 counseling intervention was implemented twice weekly with 20-minute sessions (total of 12 counseling sessions). Results of this case study indicate that the student improved because she displayed fewer maladaptive behaviors related to her test anxiety. Additionally, teacher data on number of test items completed also indicated improvement. By the 9th week, she was completing all quiz items. Although, not all items were always correct, the interference from math test anxiety behaviors was important to her success. The discrete math skill components continued to be addressed in tier II math intervention. A technique for measuring how well she is applying replacement strategies taught in counseling (e.g., breathing technique) could also be acquired through observing her use of the new strategies during quizzes.

Knowledge/Skills Testing

Often through the CBT process, a number of new skills are taught. These skills might include being able to identify and describe one's feelings, employing self-calming and relaxation techniques (e.g., diaphragmatic breathing, progressive muscle relaxation), challenging negative self-talk or cognitive distortions, interacting more effectively with peers, or becoming more assertive in getting one's needs met in a prosocial manner. The student's awareness of these skills can provide a good comparison of pre- and posttest knowledge. For example, this might occur by having the counselor inquire during the first session as to how many (and what) self-calming techniques a student knows or how many (and what) feeling words he or she can recall and pair with facial expressions (e.g., sad, mad, angry). When measuring this knowledge, it is important to have the child recall without providing her or him with cues that can give away answers or simply stating his or her opinion of how many new strategies he or she has acquired. Having the child demonstrate the skill also is a strong measure of knowledge acquisition.

Figure 1.4 illustrates pre- and posttest progress-monitoring data for a small-group application of CBT addressing social skills. In general, the goal of the CBT sessions was to provide support for four third-grade students from different classrooms who had similar needs. Teacher referrals indicated that the students were socially withdrawn and awkward in interacting with others, and they had been observed to voice maladaptive and self-deprecating statements when they were encouraged to contribute to group projects. These negative statements sometimes also caused others to avoid playing or working with them. Examples of statements were as follows: "Nobody ever likes me" (overgeneralizing), "They won't like my drawing on the group poster" (fortune-telling), and "I'm just stupid" (labeling). Counseling sessions addressed several of the cognitive distortions displayed by the students by teaching the students to identify and employ more adaptive positive self-affirmations as replacement thoughts and also building prosocial skills in interacting with others (e.g., joining a group, reciprocity in sharing ideas).

Figure 1.4

Knowledge acquisition progress-monitoring sample.

One 20-minute group counseling session was provided per week for 6 weeks. Over the 6 weeks, each student had to create five positive replacement thoughts he or she could use in difficult situations and memorize the affirmations. These were acquired one per week, and they were given practice scenarios in sessions to build fluency. The affirmations they came up with and began to apply to replace their cognitive distortions included "Some people like me," "The group poster might be hard but I can try my best," "I am good at ____, so maybe I'll be good at this too," and "Sometimes I may feel stupid but everyone does. I actually do good at school sometimes." As one can see, all of the replacement self-affirmations are more adaptive, objective, and rational than the cognitive distortions were. Additionally, these statements are not overly Pollyannaish or unreasonably or illogically optimistic. One of the goals in CBT is to be realistic and adaptive but not to be dismissive of real stressors students may encounter. Instead, the positive replacement statements provide relief by reducing students' use of negative thoughts as opposed to artificially inflating their use of positive ones.

In the example provided in Figure 1.4, Tamika, Brittany, and Aarav memorized and demonstrated fluency in applying five different positive replacement affirmations when presented a variety of social scenarios, by the 6th week. Although their progress was different, they each reached the goal. Verification by the teachers that the children also were heard using healthier responses in the classroom and were improving both the number and quality of interactions with others also supported invention effectiveness. Adding classroom observations would also strengthen confirmation that the skills were being applied. As noted in the graph, Nathan made little progress and stagnated at week 4. Thus, a rationale could be made for continuing and individualizing intervention for him.

Daily Behavioral Report Cards

Daily behavioral report cards are often utilized as a behavioral modification strategy, and they involve identifying observable and objectively defined target behaviors that are positively phrased that the child strives to achieve each day. Examples might include "Sally will raise her hand before asking questions" or "Juan turns in his homework at the beginning of each class." The child may be asked to have each teacher throughout the day note whether the behavioral goal is achieved. Usually, this strategy requires a parent review and/or signature at the end of the day, and it is tied to a specific reward if a certain number of points are earned. Often, rewards can be delivered at both home and school to ensure the generalizability of the plan across settings as well as the presentation of desired behaviors. Rewards may be tangible objects or preferred activities. Rewards should be coupled with praise and recognition for demonstrating positive or desired behaviors. The goals are set to be obtainable 75% or more of the time, and the criterion for reward is moved up as the child reaches his or her behavioral goals. When used as counseling outcome data, the results from daily behavioral report cards may be confounded with the behavioral management/incentive effects, as goal lines are often moved up over time. In other words, changes to behavior plans and related contingencies may make it challenging to generalize from these plans across different time points. However, it is not uncommon for students with high needs to require multifaceted interventions, and coupling more than one method of support with the counseling effort is often a necessary strategy.

Figure 1.5

Daily behavioral report card progress-monitoring sample.

An example of a daily behavioral report card is given in Figure 1.5. The child's referral concern was task avoidance due to the student's perfectionistic tendencies, resulting in immediately giving up or throwing away a paper if he felt he made a mistake. Counseling targeted challenging an all-or-nothing (e.g., "I can't turn it in if it is not just right") thinking cognitive distortion, and it involved conducting behavioral exposures (i.e., managing distress associated with submitting less than perfect papers). Counseling also was coupled with a behavior plan that rewarded completion of class assignments. As reflected in the daily behavior report card data, the goal was graduated over time. It was first set at completing four tasks per day (e.g., worksheets, assignments, art activity) and then moved up one point each week after the 2nd week of the plan. The teacher also initially provided prompting, cueing, and positive praise for attempts at work, even if the answer was incorrect during the 1st week of intervention. Counseling was provided twice weekly for 4 weeks, and results showed notable improvement by the 3rd week.

Subjective Units of Distress

SUDs measurement is simply based on self-reported feelings (e.g., anxiousness, fear, and anger) that individuals experience in the moment when asked. The method can be utilized for a number of counseling purposes but is often applied during behavioral exposures to assess the degree of anxiety that an individual is experiencing when facing a feared situation or stimulus. A more detailed explanation for the procedure of using SUDs is provided in the section on the exposure/response prevention therapy technique in Chapter 5, Exposure and Response Prevention and Cognitive Behavioral Therapy; however, a basic review of this process is worth mentioning in this chapter. The student and the therapist can work together to help create the SUDs scale, and it can have a wide or small range of points (e.g., 1–100, 1–10). For younger children, it may be helpful to use a smaller number of points and to provide descriptors on the scale adjacent to the numbers that the student chooses to make it personally more meaningful (e.g., "10 = freaking out," "4 = a little scared," 1 = "easy"). However, for assessing and interpreting progress-monitoring data, it will be important to report the scale number rather than the qualitative descriptors. Additionally, using pictorial representations may assist younger students in conceptualizing the scale (e.g., thermometers, rulers, rising stars). Pictorial themes may be especially appealing if they reflect the child's personal interests (e.g., sports, animals, rockets blasting off). Two samples of pictorial feelings scales for younger students are provided in the Appendix (see Exhibits 1.4 and 1.5).

Figure 1.6

Subjective units of distress (

SUDs

) data progress-monitoring sample; exposures to crowded situations at school.

SUDs data can be collected at each session, across the duration of intervention at select points (e.g., every 3 weeks), or multiple times within a session (particularly when E/RP is occurring). Figure 1.6 provides an example of SUDs progress-monitoring data on an anxiety scale with a range of 1 to 100 (100 = extremely high anxiety, 0 = absolute calm). This example reflects self-reported SUDs scale measurement every 5 minutes across five exposure counseling sessions. In this example, an adolescent student was afraid of crowds or being in dense groups of people (e.g., in crowded hallways). This fear resulted in her avoiding the cafeteria, missing required auditorium meetings, and avoiding participating in large-group activities (e.g., band practice).

Prior to engaging in the counseling intervention, the student and the school psychologist worked together to come up with a hierarchy of feared situations, and the student agreed to confront these situations. Therapy was first structured to have the student confront her anxious thoughts associated with being in crowded places through engaging in imaginal exposures. Then, a series of graduated in vivo (i.e., in real life) exposures (e.g., sitting in back of cafeteria during lunch, joining a band practice, attending the all-school meeting in the auditorium) were attempted, with the counselor accompanying and monitoring the student's self-reported stress level. According to the student's subjective report, her initial level of anxiety was a 90/100 SUDs during the first exposure trial. However, this decreased throughout the 30-minute exposure. In subsequent trials, her anxiety started to drop lower than the previous trial start point. Additionally, the pattern of data within each session indicated that the student's SUDs quickly dropped within about 5 to 10 minutes after exposure, which is relatively common for many youth experiencing anxiety problems. During trials 4 and 5, the student reported below-50 initial distress via her SUDs ratings. Overall, these data indicate the student was responding favorably to E/RP and benefiting from treatment as evidenced by reductions in overall distress at the outset of each exposure session as well as reductions in distress following each exposure.

Behavioral Rating Scales

Rating scales come in a wide variety of formats and degrees of complexity, and they may or may not have norm-referenced scores. Four basic types of behavior rating scales have obvious utility for progress monitoring associated with implementing CBT in the schools:

• Omnibus measures sample psychopathology across a number of internalizing and externalizing domains and allows comparison to a nationally representative sample of children. The Behavior Assessment System for Children, Third Edition (BASC-3) is one example of an omnibus measure that has multiple mental health scales (e.g., anxiety, depression, withdrawal, somatization, social skills, aggression, attention; Reynolds & Kamphaus, 2015). Although not necessarily intended to be used as a repeated measure of progress over a short period of time (e.g., instructions often ask for ratings of behavior over the past several weeks), this type of measure offers clinical norms and can be useful for measuring progress over time for students who fall in the clinical range. A limitation of omnibus measures is often their length, as many have over 100 items.

• A second generation of rating scales also has emerged to provide quick options for tier I screening in RtI/MTSS models. These measures typically contain 10 to 30 items and offer a single T-score that can be compared to national norms for identifying emotionally at-risk students. The BASC-3 Behavioral and Emotional Screening System (BASC-3 BESS) and the Conners 3 Global Index (Conners 3 GI) are examples of rating screener measures (Kamphaus & Reynolds, 2015; Conners, 2008). These instruments can be used repeatedly to track progress; however, one limitation of these measures is that they only give one global score rather than tracking progress on specific symptoms.

• Third-generation rating scales have added progress-monitoring forms that are short/quick measures addressing targeted areas of intervention need. They are norm referenced and designed for repeated measures over short periods of time. Many also offer scoring and tracking software programs that create intervention progress-monitoring graphs. Examples include the BASC-3 Flex Monitor forms. The instrument also offers the option of selecting items from a pool of 600 questions to customize the ratings (Reynolds & Kamphaus, 2016). Additional examples include the Conners 3 ADHD Index (Conners 3 AI), the Children's Depression Inventory–Second Edition, Short Form (CDI-2), and the Social Skills Improvement System (SSIS), as well as short versions of the Anger Regulation and Expression Scales (ARES-S; Conners, 2008; DiGiuseppe & Tafrate, 2011; Gresham & Elliot, 2008; Kovacs, 2004).

  Figure 1.7

  Test anxiety Likert scale progress-monitoring sample.

  

• Self-made Likert scales can be created by the counselor to specifically target questions for the student, and they can be highly individualized. Decisions made based on these scales must be made with caution, as they lack norm-referenced comparison information. Figure 1.7 provides an example of a therapist-created Likert survey with specific questions based on targeted counseling goals and teacher-reported referral needs.

DSM-5 Cross-Cutting Symptomology Measures

For the first time, the DSM-5 manual offered a series of freely accessible measures of psychiatric symptoms that also can be used as progress-monitoring measures. The measures can be downloaded and reproduced without charge by clinicians for use with their patients from the APA's DSM-5 website (www.psychiatry.org/practice/dsm/dsm5/online-assessment-measures). Forms include ages 6 through adult and offer self-ratings, parent ratings, and some clinician ratings. The following categories are available:

• Level 1 cross-cutting symptom measure includes adult symptom self-report (i.e., ages 18 and older), parent/guardian measures for ages 6 to 17, and child self-report measures (i.e., ages 11–17) with 25 items across 12 domains: depression, anger, irritability, mania, anxiety, somatic symptoms, inattention, suicidal ideation/attempt, psychosis, sleep disturbance, repetitive thoughts and behaviors, and substance use.

• Level 2 cross-cutting symptom measures include several brief adult (i.e., age 18 and older), parent report (i.e., ages 6–17), and child self-report (i.e., ages 11–17) symptom domain-specific measures (e.g., depression, anger, mania, anxiety).

• Disorder-specific severity measures offer symptom severity ratings for several syndromes (e.g., depression, separation anxiety disorder, social anxiety) that may be particularly important to diagnosis criteria where severity specifiers are indicated. Adult, child, and clinician-rated forms are available.

• Disability measures are based on the World Health Organization Disability Assessment Schedule 2.0 (Üstün, Kostanjsek, Chatterji, & Rehm, 2010). They include 36 items and assess disability impact across six domains: understanding/communicating, getting around, self-care, getting along with others, daily life activities, and integration/participation in society.

• Personality inventories are provided for adult (i.e., age 18 and older), child (i.e., ages 11–17), and parent report (i.e., ages 6–17). Five personality domains are included (i.e., negative affect, detachment, antagonism, disinhibition, and psychoticism).

• Additionally, the DSM-5 site offers early development and home background interview forms as well as cultural formulation interviews that may be helpful during the case conceptualization stage of planning for CBT sessions. An example of DSM-5 rating data (i.e., level 2 cross-cutting measure for somatic symptoms and severity measure for separation anxiety disorder) is included in the sample report in Chapter 7, Case Studies.

CBT EFFICACY IN SCHOOL-BASED APPLICATIONS

There are many different theoretical orientations for counseling; however, CBT is one of the most effective approaches as noted by the American Psychological Association's Task Force on Promotion and Dissemination of Psychological Procedures (Silverman et al., 2008). CBT has a long history of empirical support among clinical service providers for helping students with a wide range of needs, including ADHD, austism spectrum disorder, anxiety, bullying, OCD, depression, PTSD, panic attacks, and phobias (Abdulkader, 2017; Albano & Kendall, 2002; Bella-Awusah, Ani, Ajuwon, & Omigbodun, 2016; Kendall, 2006; Luxford, Hadwin, & Kovshoff, 2017; Rones & Hoagwood, 2000; Salloum, Sulkowski, Sirrine, & Storch, 2009). In fact, some researchers have found that CBT has more enduring results than medication for moderate and mild needs, and coupling CBT with medication can extend positive effects over medication alone for anxiety and depression (Carpenter et al., 2018; Cuijpers et al., 2014).

CBT also has been successfully adapted to provision of services within school settings for a wide range of disorders, including depression, anxiety, ODD, PTSD, and OCD (Creed, Reisweber, & Beck, 2012; Masia-Warner, Fisher, Shrout, Rathor, & Klein, 2007; Ruocco, Gordon, & McLean, 2016). Research indicates that the efficacy of CBT extends across a range of school settings serving diverse student populations (Mychailyszyn, Méndez, & Kendall, 2010; Neil & Christensen, 2009). Studies support both individual and small-group counseling delivery; however, results may vary by specific counseling needs (Eiraldi et al., 2016; Zaboski et al., 2019). For example, Ginsburg, Becker, Kingery, and Nichols (2008) found CBT services delivered in school-based mental health clinics were highly efficacious for high-risk populations of inner-city schools.

In addition to direct positive mental health outcomes, CBT intervention also has been shown to improve school academic performance. In a nonmanualized CBT intervention study that delivered 14 weeks of counseling to high school students, attendance was improved, discipline referral rates were lowered, and one half of the participants had higher grade point averages following services (Michael et al., 2013). A national review of school-based counseling literature found that positive impact was also documented for improving general social competency, reading and math scores, and personal engagement and commitment to school success (Foster et al., 2005).

CONTRAINDICATIONS FOR COUNSELING THERAPY

The application of CBT is dependent on a student's ability to understand causal connections among thoughts–feelings–behaviors, insightful self-awareness, and a motivation to participate in a meaningful way. Therefore, cognitive ability and maturity are essential considerations in selecting CBT as a counseling method. For students with significant intellectual disabilities, CBT may not be the most effective intervention methods. A second consideration is the child's developmental stage. Early Piagetian developmental theory noted that preoperational children (i.e., ages 2–7 years old) tend to function primarily from an egocentric view. Thus, it is unlikely that they will have great insight into their own thinking patterns or insight into others' perspectives during social interactions. Concrete operational age children (i.e., ages 7–11) can reason better than younger children, especially if concepts are demonstrated or put into concrete examples. Thus, CBT counseling that incorporates concrete activities and examples is likely to be somewhat effective. In comparison, children in the formal operational stage (i.e., ages 12 and older) can reason deeply, even about abstract concepts; therefore, the CBT framework is a good match for their metacognitive skills. In fact, research by Durlak, Fuhrman, and Lampman (1991) found CBT outcomes consistent with early Piagetian developmental theory in that children in the formal operations stage (ages 11 and older) have twice the positive effects utilizing CBT as children ages 2 to 10.

Additional contraindications for the use of CBT include suicidality, abuse, and psychosis. Suicidal thoughts and ideation require mood stabilization, a safety plan, and sometimes psychopharmacological intervention first before the underlying core belief system of the individual can be addressed. In circumstances of abuse, protective measures for safety and reporting the incident are the first considerations. Often, abused children are quickly separated from caregivers or other significant persons in their lives, which can also introduce complex guilt and abandonment feelings. For these children and adolescents, a more specialized counseling approach, trauma-focused cognitive behavioral therapy (TFBT), may be more appropriate. TFBT combines components of traditional CBT with family therapy elements and behavioral modification (Child Welfare Information Gateway, 2018; Silverman et al., 2008). Youth who are receiving treatment for psychosis typically require a combined treatment plan that includes antipsychotic medications and social support systems and may include CBT. However, if the child or adolescent is having a psychotic episode or quickly cycling between episodes, he or she will not have the reasoning and insight required for effective CBT.

REFERENCES

1. Abdulkader, W. F. A. K.(2017). The effectiveness of a cognitive behavioral therapy program in reducing school bullying among a sample of adolescents with learning disabilities. International Journal of Educational Sciences , 18 (1–3), 16–28. doi:10.1080/09751122.2017.1346752

2. Albano, A. M., & Kendall, P. C. (2002). Cognitive behavioural therapy for children and adolescents with anxiety disorders: Clinical research advances. International Review of Psychiatry , 14 , 129–134. doi:10.1080/09540260220132644

3. Alberto, P. A., & Troutman, A. C. (2012). Applied behavior analysis for teachers (9th ed.). New York, NY: Pearson.

5. American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (2014). The standards for educational and psychological testing . Washington, DC: American Educational Research Association.

6. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.

9. Atkins, M. S., Hoagwood, K. E., Kutash, K., & Seidman, E. (2010). Toward the integration of education and mental health in schools. Administration and Policy in Mental Health and Mental Health Services Research , 37 (1–2), 40–47. doi:10.1007/s10488-010-0299-7

10. Bains, R. M., & Diallo, A. F. (2016). Mental health services in school-based health centers: Systematic review. The Journal of School Nursing , 32 (1), 8–19. doi:10.1177/1059840515590607

11. Beidas, R. S., & Kendall, P. C. (2010). Training therapists in evidence-based practice: A critical review of studies from a systems-contextual perspective. Clinical Psychology (New York) , 17 (1), 1–30. doi:10.1111/j.1468-2850.2009.01187.x

12. Bella-Awusah, T., Ani, C., Ajuwon, A., & Omigbodun, O. (2016). Effectiveness of brief school-based, group cognitive behavioural therapy for depressed adolescents in south west Nigeria. Child and Adolescent Mental Health , 21 (1), 44–50. doi:10.1111/camh.12104

13. Carpenter, J. K., Andrews, L. A., Witcraft, S. M., Powers, M. B., Smits, J. A. J., & Hofmann, S. G. (2018). Cognitive behavioral therapy for anxiety and related disorders: A meta-analysis of randomized placebo-controlled trials. Depression and Anxiety , 35 (6), 502–515. doi:10.1002/da.22728

14. Castillo, J. M., Arroyo-Plaza, J., Tan, S. Y., Sabnis, S., & Mattison, A. (2017). Facilitators of and barriers to model school psychological services. Psychology in the Schools , 54 (2), 152–168. doi:10.1002/pits.21991

15. Center for Mental Health in Schools at University of California, Los Angeles. (2014). Mental health in schools: New roles for school nurses . Retrieved from http://smhp.psych.ucla.edu/pdfdocs/nurses/unit1.pdf

16. Child Welfare Information Gateway. (2018). Trauma-focused cognitive behavioral therapy for children affected by sexual abuse or trauma. Retrieved from https://www.childwelfare.gov/pubPDFs/trauma.pdf

17. Conners, C. K. (2008). Conners 3rd edition™ (Conners 3®) . North Tonawanda, NY: Multi-Health Systems.

18. Cook, C. R., Frye, M., Slemrod, T., Lyon, A. R., Renshaw, T. L., & Zhang, Y. (2015). An integrated approach to universal prevention: Independent and combined effects of PBIS and SEL on youths' mental health. School Psychology Quarterly , 30 , 166–183. doi:10.1037/spq0000102

19. Creed, T. A., Reisweber, J., & Beck, A. T. (2012). Cognitive therapy for adolescents in school settings . New York, NY: Guilford Press.

20. Cuijpers, P., Sijbrandij, M., Koole, S. L., Anderson, G., Beekman, A. T., & Reynolds, C. F. (2014). Adding psychotherapy to antidepressant medication in depression and anxiety disorders: A meta-analysis. World Psychiatry , 13 (1), 56–67. doi:10.1002/wps.20089

21. Cummings, J., Ponce, N., & Mays, V. (2010). Comparing racial/ethnic differences in mental health service use among high-need adolescent populations across clinical and school-based settings. Journal of Adolescent Health , 46 , 603–606. doi:10.1016/j.jadohealth.2009.11.221

22. DiGiuseppe, R., & Tafrate, R. C. (2011). Anger Regulation and Expression Scale (ARES): Technical manual . North Tonawanda, NY: Multi-Health Systems.

23. Dowdy, E., Furlong, M., Raines, T. C., Bovery, B., Kauffman, B., Kamphaus, R. W., … Murdock, J. (2015). Enhancing school-based mental health services with a preventive and promotive approach to universal screening for complete mental health. Journal of Educational and Psychological Consultation , 25 (2–3), 178–197. doi:10.1080/10474412.2014.929951

24. Durlak, J., Fuhrman, T., & Lampman, C. (1991). Effectiveness of cognitive-behaviour therapy for maladaptive children: A meta-analysis. Psychological Bulletin , 110 , 204–214. doi:10.1037/0033-2909.110.2.204

25. Eiraldi, R., Power, T. J., Schwartz, B. S., Keiffer, J. N., McCurdy, B. L., Mathen, M., & Jawad, A. F. (2016). Examining effectiveness of group cognitive-behavioral therapy for externalizing and internalizing disorders in urban schools. Behavior Modification , 40 (4), 611–639. doi:10.1177/0145445516631093

27. Foster, S., Rollefson, M., Doksum, T., Noonan, D., Robinson, G., & Teich, J. (2005). School mental health services in the United States, 2002–2003 . Rockville, MD: Substance Abuse and Mental Health Services Administration.

28. Ginsburg, G. S., Becker, K. D., Kingery, J. N., & Nichols, T. (2008). Transporting CBT for childhood anxiety disorders into inner-city school-based mental health clinics. Cognitive and Behavioral Practice , 15 , 148–158. doi:10.1016/j.cbpra.2007.07.001

29. Gore, F. M., Bloem, P. J., Patton, G. C., Ferguson, J., Joseph, V., Coffey, C., … Mathers, C. D. (2011). Global burden of disease in young people aged 10–24 years: A systematic analysis. Lancet , 377 , 2093–2102. doi:10.1016/S0140-6736(11)60512-6

30. Gresham, F., & Elliott, S. N. (2008). Social Skills Improvement System (SSIS) rating scales . Bloomington, MN: Pearson Assessments.

31. Hanchon, T. A., & Fernald, L. N. (2013). The provision of counseling services among school psychologists: An exploration of training, current practices, and perceptions. Psychology in the Schools , 50 (7), 651–671. doi:10.1002/pits.21700

32. Hussey, D. L., & Guo, S. (2003). Measuring behavior change in young children receiving intensive school-based mental health services. Journal of Community Psychology , 31 , 629–639. doi:10.1002/jcop.10074

33. Individuals with Disabilities Education Improvement Act, 20 U.S.C. § 1400 et seq. (2004).

34. Jordan, C., Reid, A. M., Mariaskin, A., Augusto, B., & Sulkowski, M. L. (2012). First-line treatment for pediatric obsessive-compulsive disorder. Journal of Contemporary Psychotherapy , 42 , 243–248. doi:10.1007/s10879-012-9210-z

36. Joyce-Beaulieu, D., & Grapin, S. (2014). Support beyond high school for those with mental illness. Phi Delta Kappan , 96 (4), 29–33. doi:10.1177/0031721714561443

37. Joyce-Beaulieu, D., & Rossen, E. (2014). Preparation of school psychologists in the United States. International Journal of School and Educational Psychology , 2 , 166–171. doi:10.1080/21683603.2014.934643

38. Joyce-Beaulieu, D., & Sulkowski, M. (2016). The Diagnostic and Statistical Manual of Mental Disorders: Fifth Edition (DSM-5) model of impairment. In S. Goldstein & J. A. Naglieri (Eds.), Assessing impairment: From theory to practice (2nd ed., pp. 167–189). New York, NY: Springer.

39. Kamphaus, R. W., & Reynolds, C. R. (2015). BASC-3 behavioral and emotional screening system (BASC-3 BESS) . Minneapolis, MN: Pearson Assessments.

40. Kaplan, J. S., & Carter, J. (1995). Beyond behavior modification: A cognitive-behavioral approach to behavior management in the school (3rd ed.). Austin, TX: Pro-Ed.

41. Kendall, P. C. (2006). Child and adolescent therapy: Cognitive-behavioral procedures (3rd ed.). New York, NY: Guilford Press.

42. Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry , 62 , 593–602. doi:10.1001/archpsyc.62.6.593

43. Kovacs, M. (2004). Children's depression inventory, second edition (CDI-2) . Toronto, ON, Canada: Multi-Health Systems.

45. Luxford, S., Hadwin, J. A., & Kovshoff, H. (2017). Evaluating the effectiveness of a school-based cognitive behavioural therapy intervention for anxiety in adolescents diagnosed with autism spectrum disorder. Journal of Autism and Developmental Disorders , 47 (12), 3896–3908. doi:10.1007/s10803-016-2857-7

46. Marken, S., Gray, L., & Lewis, L. (2013). Dual enrollment programs and courses for high school students at postsecondary institutions: 2010–11. First look [NCES 2013-002]. Washington, DC: National Center for Education Statistics.

47. Masia-Warner, C., Fisher, P. H., Shrout, P. E., Rathor, S., & Klein, R. G. (2007). Treating adolescents with social anxiety disorder in school: An attention control trial. Journal of Child Psychology and Psychiatry , 48 , 676–686. doi:10.1111/j.1469-7610.2007.01737.x

48. McFarland, J., Stark, P., & Cui, J. (2018). Trends in high school dropout and completion rates in the United States: 2014. Compendium report [NCES 2018-117]. Washington, DC: National Center for Education Statistics.

49. Merikangas, K. R., He, J. P., Burstein, M., Swanson, S. A., Avenevoli, S., Cui, L., … Swendsen, J. (2010). Lifetime prevalence of mental disorders in U.S. adolescents: Results from the National Comorbidity Survey Replication–Adolescent Supplement (NCS-A). Journal of the American Academy of Child & Adolescent Psychiatry , 49 , 980–989. doi:10.1016/j.jaac.2010.05.017

50. Michael, K. D., Albright, A., Jameson, J. P., Sale, R., Massey, C., Kirk, A., & Egan, T. (2013). Does cognitive behavioral therapy in the context of a rural school mental health program have an impact on academic outcomes?. Advances in School Mental Health Promotion , 6 , 247–262. doi:10.1080/1754730X.2013.832006

51. Mychailyszyn, M. P., Méndez, J. L., & Kendall, P. C. (2010). School functioning in youth with and without anxiety disorders: Comparisons by diagnosis and comorbidity. School Psychology Review , 39 , 106–121. doi:10.1002/pits.20548

52. National Association of School Psychologists. (2010). Model for comprehensive and integrated school psychological services . Bethesda, MD: Author.

53. National Research Center for Career and Technical Education. (2010). Programs of study: Year 2 joint technical report . Louisville, KY: Author.

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

55. Patton, G. C., Coffey, C., Cappa, C., Currie, D., Riley, L., Gore, F., … Ferguson, J. (2012). Health of the world's adolescents: A synthesis of internationally comparable data. Lancet , 379 (9826), 1665–1675. doi:10.1016/S0140-6736(12)60203-7

56. Reynolds, C. R., & Kamphaus, R. W. (2015). Behavior assessment system for children (3rd ed.). Bloomington, MN: Pearson Assessments.

57. Reynolds, C. R., & Kamphaus, R. W. (2016). BASC–3 flex monitor . Bloomington, MN: NCS Pearson.

58. Rones, M., & Hoagwood, K. (2000). School-based mental health services: A research review. Clinical Child and Family Psychology Review , 3 , 223–241. doi:10.1023/A:1026425104386

59. Ruocco, S., Gordon, J., & McLean, L. A. (2016). Effectiveness of a school-based early intervention CBT group programme for children with anxiety aged 5–7 years. Advances in School Mental Health Promotion , 9 (1), 29–49. doi:10.1080/1754730X.2015.1110495

60. Saklofske, D. H., Joyce, D. J., Sulkowski, M. L., & Climie, E. (2013). Models of personality assessment for children and adolescents. In C. R. Reynolds (Ed.), The Oxford handbook of child psychological assessment (pp. 348–365). New York, NY: Oxford University Press.

61. Salloum, A., Sulkowski, M. L., Sirrine, E., & Storch, E. A. (2009). Overcoming barriers to using empirically supported therapies to treat childhood anxiety disorders in social work practice. Child and Adolescent Social Work Journal , 26 , 259–273. doi:10.1007/s10560-009-0173-1

62. Schelar, E., Lofink Love, H., Taylor, K., Schlitt, J., & Even, M. (2016). Trends and opportunities for investment in student health and success: Findings from the 2013-2014 Census of School-Based Health Centers (SBHCs) . Washington, DC: School-Based Health Alliance.

64. School Social Work Association of America. (2013b). School social workers' role in addressing students' mental health needs and increasing academic achievement . Retrieved from https://www.sswaa.org/copy-of-about-school-social-work

65. Silverman, W. K., Ortiz, C. D., Viswesvaran, C., Burns, B. J., Kolko, D. J., Putnam, F. M., & Amaya-Jackson, L. (2008). Evidence-based psychosocial treatments for children and adolescents exposed to traumatic events. Journal of Clinical Child and Adolescent Psychology , 37 , 156–183. doi:10.1080/15374410701818293

66. Soutullo, O., Palma, L., & Joyce, D. (2014). DSM-5 depression symptoms and interventions: What school psychologists need to know. Florida Association of School Psychologists Newsletter , 40 , 34–47. Retrieved from http://www.fasp.org/PDF_Files/Newsletter/FASP_Winter_2014.pdf

67. Suldo, S. M., Friedrich, A., & Michalowski, J. (2010). Personal and systems-level factors that limit and facilitate school psychologists' involvement in school-based mental health services. Psychology in the Schools , 47 (4), 354–373. doi:10.1002/pits.20475

68. Sulkowski, M. L., & Joyce, D. (2012). School psychology goes to college: The emerging role of school psychology in college communities. Psychology in the Schools , 49 , 809–815. doi:10.1002/pits.21634

69. Sulkowski, M. L., Joyce, D. K., & Storch, E. A. (2011). Treating childhood anxiety in schools: Service delivery in a response-to-intervention paradigm. Journal of Child and Family Studies , 21 , 938–947. doi:10.1007/s10826-011-9553-1

70. Sulkowski, M. L., & Michael, K. (2014). Meeting the mental health needs of homeless students in schools: A multi-tiered system of support framework. Children and Youth Services Review , 44 , 145–151. doi:10.1016/j.childyouth.2014.06.014

71. Sulkowski, M. L., Wingfield, R. J., Jones, D., & Coulter, W. A. (2011). Response to intervention and interdisciplinary collaboration: Joining hands to support children and families. Journal of Applied School Psychology , 27 , 1–16. doi:10.1080/15377903.2011.565264

73. U.S. Department of Education, Office of Special Education and Rehabilitative Services, & Office of Special Education Programs. (2018). 39th annual report to Congress on the implementation of the Individuals with Disabilities Education Act, 2017 . Retrieved from https://www2.ed.gov/about/reports/annual/osep/2017/parts-b-c/39th-arc-for-idea.pdf

74. U.S. Department of Health & Human Services. (2000). Report of the Surgeon General's conference on children's mental health: A national action agenda . Washington, DC: Author. Retrieved from https://www.ncbi.nlm.nih.gov/books/NBK44233

75. Üstün, T. B., Kostanjsek, N., Chatterji, S., & Rehm, J. (2010). Measuring health and disability: Manual for WHO disability assessment schedule–WHODAS 2.0 . Geneva, Switzerland: World Health Organization.

76. Zaboski, B. A., Joyce-Beaulieu, D., Kranzler, J. H., McNamara, J. P., Gayle, C., & MacInnes, J. (2019). Group exposure and response prevention for college students with social anxiety: A randomized clinical trial. Journal of Clinical Psychology , 75 (9), 1489–1507. doi:10.1002/jclp.22792

Professional School Counseling Journal Cbt and Problem Solving

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