Identifying and Supporting Students with Affective Disorders in Schools

Academic Anxieties and Emotional Information Processing

Authored by: Jerrell C. Cassady , Christopher L. Thomas

Handbook of Educational Psychology and Students with Special Needs

Print publication date:  February  2020
Online publication date:  February  2020

Print ISBN: 9781138295421
eBook ISBN: 9781315100654
Adobe ISBN:




The success of learners who encounter negative affective states within educational settings is tied to researchers’ and practitioners’ ability to detect at-risk students and guide them to appropriate academic supports. This chapter begins with a discussion of how restricted attention to aspects of anxiety and problematic diagnostic criteria for emotional disturbance have interfered with educators’ ability to support at-risk students. For instance, learners with academic anxieties (e.g., test anxiety) are not eligible to receive academic supports unless a broader form of anxiety is assessed and documented. In this chapter, we discuss methods of assessing academic anxiety and emotional disabilities that fall within and outside existing diagnostic frameworks and advocate for increased attention to supporting learners who struggle to function at an optimal level, but do not meet formal diagnostic criteria. This chapter also discusses causes of emotional challenges in school settings to enable more effective interventions. Since the 1980s, interventions have struggled to derive positive outcomes among “high anxiety” learners. Our work, however, has suggested that these null effects are in part an artifact of a mismatch between “sources” of test anxiety and the focus of intervention efforts. Effectively differentiating among subtypes of test-anxious students can overcome the traditional problem of assuming that all test-anxious learners are alike and allow educators to tailor intervention efforts to meet their needs more effectively. Finally, we provide an overview of the emotional information processing model (Cassady & Boseck, 2008), which identifies a recursive self-regulated framework for detecting and responding to affective signals within the individual and in the environmental context. Building from this framework, we offer real-world applications to help educators and special needs support teams identify areas of need and promote the development and internalization of skills and strategies conducive to long-term academic success.

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Identifying and Supporting Students with Affective Disorders in Schools

The overarching professional mission of school leaders, teachers, and support staff is to develop and maintain environments and learning events supportive of long-term academic success for students with differing levels of ability and unique challenges. Despite their best efforts, students’ abilities to thrive in standard educational settings are routinely disrupted by negative affective experiences triggered by stressors within or beyond the academic environment (Pekrun, 2006; Putwain, 2007; Thomas, Cassady, & Heller, 2017). Available data suggest that anywhere between 20 and 45% of students will experience debilitating anxiety, depression, or a similar emotional disorder at some point during their academic career – with incidence rates increasing along the developmental trajectory (Greenberg, Domitrovich, & Bumbarger, 1999; Kessler, Berglund, Demler, Jin, & Walters, 2005). To assist learners at risk for maladaptive affective responses, schools must make use of methods supporting the accurate and timely detection of such students who would benefit from targeted intervention, reasonable accommodations, or course modifications. In the sections that follow, we outline the current state of screening methods for students with emotional and behavioral disorders, discuss how current diagnostic frameworks often fail to meet the changing and diverse needs of learners, and articulate a model that can be used by school personnel to detect and support students who struggle to effectively navigate emotionally laden and potentially challenging academic settings.

Characteristics of Emotional Disturbance

The detection of students with emotional and behavioral disorders in the United States education system is guided by definitions and guidelines detailed in the U.S. Individuals with Disabilities Act (Individuals with Disabilities Education Act, 2004). According to the Individuals with Disabilities Education Act (2004), emotional disturbance is defined as:

a condition exhibiting one or more of the following characteristics over a long period of time and to a marked degree that adversely affects a child’s educational performance: (1) an inability to learn that cannot be explained by intellectual, sensory, or health factors, (2) an inability to build or maintain satisfactory interpersonal relationships with peers and teachers, (3) inappropriate types of behavior or feelings under normal circumstances, (4) a general pervasive mood of unhappiness or depression, and/or (5) a tendency to develop physical symptoms or fears associated with personal or school problems.

( Although the Individuals with Disabilities Education Act (2004) was developed to ensure students with emotional and behavioral disorders are not denied access to quality educational opportunities, educators and special needs support staff have expressed frustration over the definition of emotional disturbance, arguing the vague and subjective nature of the characteristics listed often interfere with the effective detection of at-risk students (Walker, Nishioka, Zeller, Severson, & Feil, 2000).

The ambiguity surrounding the defining characteristics of emotional disturbance is exacerbated upon consideration of cross-cultural comparisons of the practices that are used to identify students struggling with emotional and behavioral issues. For instance, in response to international calls to guarantee students’ rights to inclusive education services, many European countries have worked to refine the diagnostic criteria used to identify students with special education needs to ensure the allocation of the resources to students at considerable risk for academic difficulties (Banks & McCoy, 2011; Chakraborti-Ghosh, Mofield, & Orellana, 2010). Despite these reform efforts, most Western countries have failed to generate an agreed upon definition of emotional disturbance – also referred to as severe emotional disability (ED), emotional difficulties, or emotionally disturbed within commonly used classification schemes – and some countries have failed to recognize students with emotional disturbance as a unique subtype of students with special education needs (Chakraborti-Ghosh et al., 2010). Further complicating discussions of definitional guidelines is evidence suggesting that efforts to establish clear definitions of emotional and behavior disturbance within many non-Western countries are still in their infancy (Chakraborti-Ghosh, 2008; Chakraborti-Ghosh et al., 2010; Mazurek & Winzer, 1994).

Despite ambiguity with the operational definition provided by the U.S. Individuals with Disabilities Education Act (2004) and classification schemes used by educators within other Western and non-Western countries, researchers and practitioners have come to a general consensus that manifestations of emotional disturbance can be parsed into two qualitatively distinct categories: internalizing and externalizing (Merrell & Walker, 2004). Students with externalizing forms of emotional disturbance routinely engage in overt behavioral patterns that disrupt the classroom environment and interfere with effective instruction (i.e., aggression, noncompliance, and delinquent behaviors; Stouthamer-Loeber & Loeber, 2002; Walker, Ramsey, & Gresham, 2004), whereas students with internalizing forms of emotional disturbance typically exhibit inwardly focused cognitions and behaviors that contribute to academic deficits (i.e., major depressive disorder, generalized anxiety, obsessive compulsive tendencies, somatic complaints, eating disorders; Gresham & Kern, 2004; Morris, Shah, & Morris, 2002). Hue (Chapter 10, this volume) provides additional discussion of internalizing and externalizing behaviors. Given the clear impact that externalizing disorders have on learning environments and the relative ease of observation for external behaviors, there has historically been greater attention to this form of emotional disturbance. However, there is a growing and pressing level of research being devoted to internalizing disorders, prompted largely by the rising rates of identification of anxiety, depression, and related emotional disorders. The internalizing domain is where the bulk of our focus lies, but it is imperative to recognize that externalizing disorders frequently co-occur or point to more covert internalized emotional difficulties and should not be overlooked during the identification and intervention efforts (Bubier & Drabick, 2009; Martín, Granero, Domènech, & Ezpeleta, 2017).

The association between emotional disturbance and maladaptive outcomes is well established within literature focusing on the contribution of non-cognitive factors to academic success. Across their academic lives, students with emotional disturbance often struggle to master fundamental skills that are required for success (i.e., reading comprehension, written expression, mathematical reasoning; Reid, Gonzalez, Nordness, Trout, & Epstein, 210, 004; Wagner & Cameto, 2004; Wagner & Davis, 2006), receive lower grade point averages (Newman et al., 2011), fail courses at higher rates (Newman et al., 2011), and are more likely to withdraw from school prior to completion (Kaufman, Alt, & Chapman, 2004). Unfortunately, the experience of maladaptive outcomes among this population of learners is not confined to the school years and persists into adulthood. Results of large-scale, longitudinal examinations investigating students’ transitions to adulthood indicate learners with emotional disturbance experience more negative employment outcomes (i.e., unemployment, underemployment, and job instability; Bullis & Cheney, 1999; Carter & Wehby, 2003; Wood & Cronin, 1999), attend college at a lower rate (Wagner & Cameto, 2004), are more likely to come into contact with the criminal justice system (U.S. Department of Health and Human Services, 1999), and engage with the community at lower rates than their non-emotionally disturbed peers (Armstrong, Dedrick, & Greenbaum, 2003).

Factors Interfering with the Identification of Students with Emotional Disturbance

Given the sizable population of students at risk for persistent maladaptive outcomes associated with emotional disturbances, it is critical that educators can identify at-risk learners early enough to secure formal and informal support services (e.g., academic, social, emotional). However, research repeatedly demonstrates school personnel struggle to effectively identify and support students with emotional disturbances, as illustrated by the extremely small percentage of K–12 students (< 5%) who are currently receiving special education services (McFarland et al., 2017).

Low Diagnostic Training

One likely source leading to the discrepancy between the number of children served and the number likely in need of service rests with traditional identification procedures in schools. The first step to developing an individualized educational support plan for students with emotional disorders typically relies on teacher referral to experts in special education, school psychology, or school counseling. The widespread use of teacher referral places educators in the role of gatekeepers to specialized academic diagnostic and intervention services. Unfortunately, the evidence clearly demonstrates that teachers generally have not received sufficient training to recognize and support students with internalizing emotional disorders (Hoagwood, Burns, Kiser, Ringeisen, & Schoenwald, 2001). Although teacher reports and referrals provide useful information about student behavior (e.g., frequency of behavior, location of problematic behaviors, potential environmental antecedents), experts recognize that teachers have difficulty identifying students who: (a) meet the diagnostic criteria for serious externalizing and internalizing disorders, (b) are not exhibiting current academic or behavioral problems but exhibit more covert indicators or cues that diagnosticians may identify as precursors to maladaptive outcomes, and (c) are experiencing mild or moderate impairments (Beare & Lynch, 1986). As such, we agree that teachers should be a critical part of the data collection process for identifying learners with emotional disturbances, but more systematic reviews of indicators are recommended to ensure more success in identifying students with need.

Imbalanced Identification of Internalized and Externalized Disorders

Although it is clear that educators (and parents) have difficulty effectively identifying students who should be referred for assessment, the barrier is more pronounced when considering learners at risk for internalized disorders (Achenbach, McConaughy, & Howell, 1987; Bradshaw, Buckley, & Ialongo, 2008; Glaser, Calhoun, Bradshaw, Bates, & Socherman, 2001). Explanations for the lower likelihood of referral for internalized disorders generally center on the accessibility of the indicators of the disorders (i.e., externalized aggression is easier to identify than internalized depression). This inability to identify internal disorders can be attributed to both the covert nature of the symptoms and the potential that students may mask or hide their emotional difficulties for fear of stigmatization (Amstadter, 2008; Mennin, Heimberg, Turk, & Fresco, 2002). Moreover, in a daily context, internalizing behaviors pose less immediate threat to classroom management and effective instruction (Lane, 2007). Externalized behavior disturbances also have been reliably and durably tied to academic performance, attracting the attention of educators, interventionists, and administrators alike (Nelson, Benner, Lane, & Smith, 2004). Finally, some experts hypothesize that schools place less emphasize on internalizing disorders simply because they are not equipped to serve those needs (Cheney, Flower, & Templeton, 2008; Kern, Hilt-Panahon, & Mukherjee, 2013).

Current versus Projective Identification

Finally, in-depth reviews of emotional and behavioral screening practices confirm that educators are most likely to refer students who are currently experiencing significant academic, behavioral, or emotional difficulties – and are unable to reliably identify students most likely to experience difficulties in the future (Bruhn, Woods-Groves, & Huddle, 2014; Donovan & Cross, 2002). Although this is not surprising, the ability to identify individuals with initial indicators of emotional distress would aid a more proactive approach to supporting learners before problems become exacerbated and problematic (Atkinson & Hornby, 2002).

The Use of Universal Screening to Support the Identification of Students with Emotional Disturbance

Given the obvious limitations of these traditional “wait to fail” approaches, advocates have called for the adoption of universal screening methods to support the detection of emotional disorders and disturbances alongside cognitive deficiencies. Universal emotional and behavioral screening is a proactive approach that tests all students within particular educational settings (e.g., classrooms, schools, school systems) throughout critical time points (Bruhn et al., 2014; Glover & Albers, 2007). Those data are analyzed to identify the students who may need intensive and structured support or more limited supportive efforts to thrive academically (Marquez, Yeaton, & Vincent, 2014). A variety of benefits associated with the use of universal screening practices have been articulated in the literature, including greater precision in identifying need, timely response to provide support for those at risk, and the ability to more effectively observe changes over time within students.

Foremost in this list of benefits is that validated assessment measures enhance the likelihood of identifying students at risk for emotional disturbance who would benefit from additional academic, social, or emotional support. Related to this, universal screening improves the timeliness of identification. The importance of early identification cannot be overstated given the plethora of empirical evidence suggesting a large percentage of students with emotional disturbance are often identified too late for supports to meaningfully impact student outcomes (Walker et al., 2004). Finally, the collection of data at multiple points during the academic year allows educators to observe both progressive and rapid changes in level of risk that may prove critical in detecting student needs (Lane, Menzies, Oakes, & Kalberg, 2012).

The development and adoption of universal screening methodologies are generally most effective when incorporated into a “multitiered” program of academic support emphasizing the integration of identification and support strategies to assist struggling learners. Multitiered intervention frameworks are consistent with the logic of the response-to-intervention approach (Brown-Chidsey & Steege, 2010; Walker et al., 1996) which strives to support learners by implementing a continuum of evidence-based academic and behavioral interventions matched to the severity of the presenting behavior. The lowest tier of support (Tier 1) involves exposing all students in an educational setting to programming promoting core social and emotional competencies to prevent the development of problematic internalizing and externalizing behaviors (i.e., conflict resolution skills, classroom behavioral expectations, anger management strategies; Horner, Sugai, & Anderson, 2010; Seeley, Severson, & Fixsen, 2010; Walker et al., 1996). Students who demonstrate persisting deficits in functioning following exposure to Tier 1 programming are referred to receive additional support (Fletcher & Vaughn, 2009; Walker & Severson, 1992). The Tier 2 interventions are more intensive and tailored to meet the needs of clusters of at-risk students demonstrating behaviors that interfere with effective instruction and learning (e.g., social skills lessons, identification and management of emotional states; Horner et al., 2010; Walker et al., 1996). Finally, students who exhibit multiple risk factors for ED as well as learners who are not responsive to Tier 1 and 2 supports are exposed to Tier 3 interventions, which are highly structured, individualized interventions designed to reduce the intensity and frequency of severe externalizing and internalizing behaviors (Sugai & Horner, 2009). Because of their individualized nature and intensity, Tier 3 programs require coordination among a team of individuals (i.e., educators, administrators, school psychologists, counselors, behavioral specialists) to develop and implement them effectively (Horner et al., 2010; Seeley et al., 2010).

Benefits of Universal Screening Methods

Universal screening and multitiered frameworks represent a relatively new approach in the field of behavioral and emotional disabilities screening (Brown-Chidsey & Steege, 2010), but their impact on student outcomes is promising. Studies of implementations of school-wide screening practices that emphasize both preventative practices and targeted support after identification through screening practices have shown significant improvements in academic performance (i.e., improved vocabulary, course grades, standardized test scores), classroom behavior, and mental health outcomes (i.e., improved emotional perception, emotional management, reductions in internalizing behavior; Hoagwood et al., 2007; Vidair, Sauro, Blocher, Scudellari, & Hoagwood, 2014).

Unfortunately, schools in the United States and many other Westernized countries have been slow to incorporate universal screening and multitier support into their emotional and behavioral screening procedures (Bruhn et al., 2014; Volpe et al., 2018). For instance, one recent nationwide investigation of the prevalence of emotional and behavioral screening methods used in K–12 educational settings in the United States indicated the majority of surveyed school systems (87%) do not use universal screening and multitier frameworks to identify at-risk students (Bruhn et al., 2014). Common barriers to implementation cited by educational professionals include limited access to screening materials, budgetary concerns, and mere lack of awareness (Bruhn et al., 2014). Although these barriers were identified by educators in the United States, available evidence suggests educators interested in adopting multitiered support systems in European countries also cite limited access to screening tools as the primary barrier preventing the adoption of universal screening practices (Grosche, & Volpe, 2013; Volpe et al., 2018).

We see promise and advocate for broader use of universal screening and multitier intervention supports based on the value of early identification and intervention in promoting academic and emotional thriving for more students, as well as the financial benefits schools experience when adopting proactive rather than reactive policies. However, until universal screening becomes commonplace, schools must rely upon “frontline” educators to initially identify students with needs. One strategy to support this is to provide teachers and other school professionals with parsimonious and functional approaches to recognizing the signs demonstrated by students struggling to manage emotional stressors in educational settings.

Educational Psychology Perspectives on Emotional Disturbances

A variety of theoretical perspectives are relevant when examining the impact of emotional disturbances on optimal student functioning in schools (e.g., Pekrun & Loderer, Chapter 18, and Wigfield & Ponnock, Chapter 17, this volume). From a broad perspective, our work on explaining and intervening with students who present with internalized emotional difficulties is predominantly informed by social-cognitive and cognitive perspectives. This is not to minimize the clear utility of behavioral and cognitive-behavioral strategies to support learners with both internalized and externalized emotional difficulties. That literature is well established, and we recognize the utility of effective behavior management supports. However, we believe incorporating the social-cognitive and cognitive perspectives provides added value in helping educators recognize relevant factors that can support learners’ representations of academic settings and events to promote optimal functioning. Collectively, our views are explained by a model referred to as the emotional information processing framework (EIP; Cassady & Boseck, 2008). The EIP attempts to support the understanding of learners’ abilities to successfully navigate challenging events by recognizing the influences of (a) individuals’ perceptions of internal and external cues and (b) self-regulated learning and emotion regulation strategies (e.g., Crick & Dodge, 1994; Lazarus & Folkman, 1984, 1987; Pekrun, 2006; Schunk & Zimmerman, 2003). In short, the EIP model (see Figure 3.1) recognizes an iterative process for encoding and interpreting internal and external cues, developing and evaluating goals to respond to the perceived situation, and implementing solutions to meet these goals (relying on personal experiences to determine the most viable solutions for the task at hand; see Cassady & Boseck, 2008).

Emotional Information Processing Model

Figure 3.1   Emotional Information Processing Model

Perceptions of Threat and Self-Efficacy

One of the core suppositions of the EIP is built on the work demonstrating significant variation in the interpretation of both internal and external cues among individuals. From a basic social-cognitive or constructivist framework, the EIP recognizes that each unique situation provides us with a set of environmental stimuli that are interpreted through the lens of our own histories. Crick and Dodge (1994) demonstrated that, in social situations, the selection of external cues to attend to and the interpretation of those cues were dramatically different among individuals with varied levels of social skills. Their social information processing model was instrumental in demonstrating that the progressive failures of children with high levels of aggression could be traced back through an information processing pathway that relied on their attention to environmental and personal factors, and this commonly led to these children presuming a hostile situation in contexts that non-aggressive children interpreted quite differently. Zentall, Cassady, and Javorsky (2001) used this framework while working with children with high levels of inattention and hyperactivity, demonstrating that their attentional biases in reviewing social contexts reliably led to less effective social problem-solving. In that study, refocusing the child to attend to more contextual cues mitigated the negative social outcomes for those children with hyperactivity, suggesting that reframing the situational interpretation may serve to support learners with difficulty in social or educational settings (Zentall et al., 2001).

In addition to environmental and contextual cues, the EIP model recognizes the critical role of learners’ internal representation of their ability. Building from Lazarus and Folkman’s (1984) coping model and Bandura’s (2005) representation for the utility of self-efficacy in learning situations, the EIP suggests that it is the comparative analysis of the perceived event, stressor, or challenge and the learner’s interpretation of their own abilities to successfully manage the task at hand that determine the interpretation of the event as a manageable challenge, stressor, or even threat to self. To illustrate, consistent with the classic representation of stress and performance (i.e., Yerkes & Dodson, 1908), we agree that limited levels of environmental stress can have a positive or motivating influence (Alpert & Haber, 1960; Couch, Garber, & Turner, 1983; Glass & Singer, 1972; Keeley, Zayac, & Correia, 2008; Raffety, Smith, & Ptacek, 1997). In line with that, low levels of academic stress may have a facilitative influence by initiating learners’ behaviors toward addressing the task. However, when learners perceive stressors to exceed their level of ability or competence, the event or context is interpreted as a threat to academic success, social standing, or the self (Lazarus & Folkman, 1984, 1987). When the individual perceives an environmental stressor to be threatening rather than challenging, anxiety arises and can exert a debilitating influence on the situation (i.e., maladaptive anxiety), impeding learning efficiency and performance or sparking neurotic thoughts and behaviors (Keeley et al., 2008).

Self-Regulation and Emotion Regulation

Once the academic task or situation in question has been mentally represented by an individual, the set of processes referred to in the EIP are consistent with social-cognitive orientations toward self-regulated learning (SRL). (See Perry, Mazabel, & Yee, Chapter 13, this volume, for additional discussion of SRL to support learners with special needs in classrooms.) Dominant representations of SRL recognize the roles of planning, self-monitoring, self-regulation, and control processes in determining the success of learners in meeting quality achievement goals (e.g., Schunk & Zimmerman, 2003). Pintrich (2004) recognized that, in addition to regulating cognition, more complete representations of effective SRL functioning recognize that effective learners demonstrate the ability to regulate not only their cognitive processes, but also affect (or emotions), behavior, and the context within which they are operating. Gross’s (1998, 2015) process model for emotion regulation provides a strong analogue to the EIP model, proposing that attention, cognitive change, and response modulation are key features in identifying how people may either change their emotional set or modify the severity of an emotional response. Gross’s (2015) distinction between emotion regulation and coping draws a compelling line between the general management of emotional cues (i.e., emotion regulation) and response to stressors (i.e., coping). The EIP makes no explicit distinction between these two affective regulation strategies; however, Gross’s representation for this distinction is a useful method for clarifying distinctions in the utility of emotion-focused and adaptive coping. That is, research on coping has frequently struggled to reconcile the overall utility of emotion-focused coping in academic settings (e.g., Thomas et al., 2017) but recognizes that, in specific cases, where the goal is to moderate or mitigate the influence of emotional influences on a situation, the adoption of emotion-focused coping may have an adaptive (or proactive function). In step with Gross, the EIP recognizes that the utility of a coping (or emotion regulation) strategy is predominately reliant on the goal that has been established. If the goal is to reduce emotional reactivity, manage emotional intensity, or separate from overwhelming emotional response, then emotion regulation is an effective coping strategy (cf. Gross, 2015). However, in cases where the primary goal is to advance understanding of content or improve performance on a task, emotion regulation strategies alone may not have the adaptive utility of other coping strategies.

The EIP recognizes these critical skills in planning, monitoring, and regulating cognitions, emotions, and behavior during the goal articulation, response selection, and enactment phases (see Figure 3.1; Cassady & Boseck, 2008). Key aspects of SRL theory articulated in the EIP include recognizing that effective goals are proximal, specific, and measurable (Schunk & Zimmerman, 2003); SRL strategies can be taught, modeled, and practiced (Bandura, 2005; Martynowicz & Cassady, 2018); accurately identifying, monitoring, and managing emotional influences on the context are inherently entwined with cognitive and behavioral operations (Gross, 2015; Pintrich, 2004); and, as the repository of effective strategies at a learner’s disposal increases, their potential for successfully overcoming challenges also improves (Bjork, Dunlosky, & Kornell, 2013).

The primary value of effective SRL and emotion regulation strategies employed by learners is the long-term benefit of a recursive process of continued skill acquisition in establishing quality goals, employing effective strategies, and reflecting on those successes over time (e.g., Dunlosky, Rawson, Marsh, Nathan, & Willingham, 2013; Kitsantas & Zimmerman, 2009). As such, learners who employ effective self-regulation processes simultaneously experience gains in learning strategy use, self-efficacy, and achievement motivation outcomes (Bjork et al., 2013; Schunk & Zimmerman, 2003). As the level of success increases (either qualitatively or quantitatively), learners become more likely to view future events as manageable (or less threatening), as their appraisal of their ability to meet the cognitive or emotional demands of the contextual challenge increases, promoting a sense of agency that influences each phase of the EIP (Bandura, 2005; Cassady & Boseck, 2008; Folkman, Lazarus, Dunkel-Schetter, DeLongis, & Gruen, 1986).

Emotional Information Processing Framework and Affective Disorders in Schools

Building on the brief overview of theory, this section is intended to provide a bridge between theory and practice, with an attempt to illustrate how educators may gain insight into identifying and subsequently supporting individuals with affective disorders (i.e., emotional disturbances) in academic contexts. The wide range of specific emotional and affective disruptions learners encounter in schools precludes a full detailing of all conditions. Given our own experience, we use academic anxieties to illustrate what we see as the functional potential of the EIP. However, the model is intended to function effectively in explaining a wide array of negative and positive emotional representations and behavioral outcomes that follow from those experiences.

Anxiety in Schools

Within the educational domain, many representations of anxiety have been articulated, ranging from clinical diagnoses of generalized anxiety disorder, social anxiety disorder, and specific phobias – including “school phobia” (American Psychiatric Association, 2013) – to experiences of anxiety that are not clinically identified, but maintain influence on learners’ experiences. Our use of the term “academic anxieties” is an attempt to generalize the findings from research exploring anxieties learners cope with in academic settings (e.g., test anxiety, reading anxiety, math anxiety; Cassady, Pierson, & Starling, 2019). These various forms of anxiety in schools often share many features regarding manifestation and potential interventions, with the primary variation among these domains of anxiety resting with the specific stressor(s) underlying the anxiety (cf. Cassady, 2010a). To clarify our position, we represent academic anxiety as a response to perceived environmental stressors by the learner. These representations of stressors are formed in a constructive and individually specific process, whereby environmental stimuli (e.g., challenges, stressors, expectations) interact with personal factors (e.g., perceived ability, prior experiences), leading to a final appraisal of the level of threat imposed by the stressor and, eventually, the interpretation of personal ability to meet that challenge (see Bandura, 2005; Cassady & Boseck, 2008; Lazarus, 1993; Lazarus & Folkman, 1984, 1987). Our research also supports the notion of a “nested” representation of academic anxieties, demonstrating that academic anxieties serve as more specific or hierarchically subordinate forms of anxiety compared with generalized anxiety disorders (i.e., individuals with high levels of anxiety have a higher likelihood of experiencing these more contextually focused forms of anxiety; Cassady et al., 2019).

Because most learners who experience anxiety in an academic setting will not rise to a level of clinical diagnosis requiring formalized support, there is growing attention to help educators identify the rates of incidence of these academic anxieties, as well as illustrating the range of negative outcomes that are associated (Putwain, 2007; Putwain & Daly, 2014; von der Embse & Hasson, 2012; von der Embse, Mata, Segool, & Scott, 2014). Estimations of the prevalence of test anxiety in schools suggest that 40–60% of students encounter some degree of test anxiety, and roughly 10–15% may encounter severe levels (Ergene, 2003; Putwain & Daly, 2014; von der Embse, Kilgus, Segool, & Putwain, 2013). This approach to detecting academic anxieties has broader utility, as research clearly demonstrates comorbidity of anxiety and other emotional conditions such as depression (Anderson & Hope, 2008; Cassady et al., 2019). Students identified with both anxiety and depression are of particular concern, because they experience lower overall psychological health, are more resistant to treatment efforts, and are linked to higher rates of suicide attempts (Garber & Weersing, 2010; Rhebergen et al., 2011).

Variations in Emotional Difficulties in Schools

A primary misconception we observe in our work with current and future educators is the belief there is uniformity in the experiences students with special needs or disabilities encounter. That is, many novice educators in particular suggest that characteristics of emotional disturbances will be universally demonstrated by all students experiencing that disorder. Obviously, this is an error of overgeneralization that is not limited to educating learners with emotional difficulties, but it is imperative to start all identification and intervention efforts with a reaffirmation that wide variability underlies individual experience. In the case of test anxiety, for instance, there is a long history of research demonstrating that there are at least two primary factors of test anxiety (i.e., cognitive/worry and affective/emotional; Cassady & Johnson, 2002; Liebert & Morris, 1967; Zeidner, 1998), with recent research suggesting a third factor emphasizing the role of socially focused concerns (i.e., fear of letting down important social others) in the experience of test anxiety (Friedman & Bendas-Jacob, 1997; Kavanagh, Harvey, & Mesagno, 2017; Lowe et al., 2008).

Another key point related to classic misperceptions of test anxiety is that the condition is not a transient experience that arises and dissipates within an evaluative session. To the contrary, test anxiety has been identified as present in three phases of the “learning–testing cycle” (Cassady, 2004; Schwarzer & Jerusalem, 1992). This recursive cycle represents the test preparation, test performance, and test reflection phases. Review of each phase has demonstrated that learners with test anxiety show differing forms of anxious responses during the three phases. During the test preparation phase, common responses include procrastination, withdrawal, or selection of relatively ineffective study strategies when preparation for the test does begin (Cassady, 2004; Kalechstein, Hocevar, Zimmer, & Kalechstein, 1989; Zeidner & Matthews, 2005). During the performance phase, the traditional representations of distracting thoughts, physiological hyperarousal, and fear of negative consequences of the test are commonly reported, hampering performance (Zeidner, 1998). Finally, during test reflection, learners with test anxiety are more likely to adopt learned helplessness perspectives and attributional stances that perpetuate negative appraisals for future testing events (Cassady, 2004, 2010).

Such variations in learners’ experiences with test anxiety led to Zeidner and Matthews’ (2005) proposed classification of six types of test anxiety: (a) study or testing skills deficits; (b) anxiety blockage or retrieval failure; (c) failure-acceptance, where anxiety promotes learned helplessness and low motivation; (d) failure-avoidance, where the learner actively withdraws from or avoids perceived stressors; (e) self-handicapping, which involves self-imposed barriers to success that ultimately provide ego-preserving explanations for eventual performance failures; and (f) perfectionism, with a predominately “maladaptive” style that involves socially prescribed and overly high expectations for performance. We believe that the development of diagnostic protocols (including assessment instruments, behavioral data, and recommendations from educators) in schools will help schools more effectively identify (a) primary sources of the anxiety; (b) immediate cognitive, behavioral, or emotional responses to those stressors; and (c) the academic, emotional, and social impacts that follow. When these diverse elements are reviewed for each individual case, there is a greater potential to identify both the causes and solutions for more effectively managing emotional difficulties in the classroom (see von der Embse, Barterian, & Segool, 2013).

Assisting Students with Academic Anxiety and Related Emotional Difficulties

The utility of the EIP can only be realized when put into operation. This section is meant to articulate exemplar strategies educators can employ to identify, explain, and help remediate students’ emotional disturbances. Collectively, we reiterate that the optimal condition to support such an effort would rest within a universal screening and tiered intervention model, but believe that, in the absence of such a formalized structure, diagnostic observation and prescriptive intervention can still be realized. Whereas the full model of the EIP addresses five primary phases or steps, for simplicity we address two broad aspects of cognitive and emotional processing: (a) attention, perception, and interpretation of external and internal cues and (b) self-regulation and emotion regulation strategies that focus on setting effective goals and monitoring progress in meeting those goals. Below, we articulate both the model perspective on the importance of these two broad domains of EIP as well as provide exemplar strategies that may support optimal outcomes for learners.

Managing Learners’ Perceptions of Environmental and Internal Cues

As presented in the EIP (Figure 3.1; Cassady & Boseck, 2008), the interpretation of an emotional situation starts with the encoding of internal and external cues or stimuli. In a recursive – often self-fulfilling – nature, individuals with a history of emotional difficulty have a predisposition to orient attention toward those cues or stimuli that tend to validate their prior experiences (e.g., stereotype threat; Schmader & Beilock, 2012; Schmader & Johns, 2003). To more effectively identify sources of aversive emotional reactions, it is critical to identify the environmental and internal stimuli as interpreted by the learner. In this way, we liken the use of EIP to a functional behavior analysis, seeking to identify and address factors that may underlie and help to explain how learners operate in emotionally charged academic settings (Cassady & Boseck, 2008; Zentall et al., 2001). Although the cues learners attend to are critical in determining their emotion regulation, it is the interpretation of these cues – or the mental representation they form – that matters the most to professionals attempting to identify the sources and potential solutions of consistent emotional difficulties (Cassady & Boseck, 2008). As learners encode the cues, they reference their personal experiences with similar scenarios, building an appraisal of the situation that determines whether the situation poses a manageable challenge or a debilitating threat (Lazarus, 1993).

Zeidner and Matthews’ (2005) self-referent executive function model of emotional distress also asserts that it is this development of negative self-appraisals that activates anxiety and leads to continued ineffectual coping and performance owing to diminished cognitive and behavioral efficiency. In addition to self-reference judgments, learners with predispositions to anxiety may develop attributional biases that place the locus of projected failure on themselves, promoting views of helplessness or hopelessness. Investigations of effective cue encoding have demonstrated increases in emotional reactivity (e.g., anxiety) interfere with optimal allocation of attentional resources, limiting the ability to identify relevant features in academic or social contexts (Broadbent, 1971; Easterbrook, 1959). More recent conceptualizations of these limitations in processing efficiency for learners with anxiety have identified that anxiety impairs basic cognitive operations related to attentional control (Eysenck, Derakshan, Santos, & Calvo, 2007). In addition, overall processing efficiency drops, perhaps owing to the increase in cognitive load brought about by the learner engaging in both the task at hand and managing the distracting stimuli sparked by anxiety or related emotional responses (Chen & Chang, 2009).

In the case of academic anxieties, external stressors that may spark these negative self-appraisals and cognitive distractions include teachers’ comments about upcoming evaluations, perceived social pressures from peers and parents, public or private recriminations for failure to meet established standards, or the prototypical high-stakes assessments that permeate all dimensions of education in our current society (e.g., von der Embse & Witmer, 2014). Internal stressors include biological or physiological triggers (e.g., increased heart rate, shortness of breath) that are often interpreted as evidence of threat (Hembree, 1988), as well as emotional and cognitive ruminations that may orient toward self-deprecation (e.g., De Raedt & Koster, 2010; Sarason, 1986).

Strategies to Reduce Environmental Stressors in Academic Settings

Helping learners with academic anxiety and related emotional difficulties adjust their attentional focus and initial interpretations of personal and environmental stressors encompasses the two pivotal steps in the EIP. To start, practitioners and support personnel can help by limiting the presence of threat indicators in academic settings (minimizing the number of triggering cues that may be encountered). This can be accomplished by minimizing threat appraisals when discussing upcoming evaluation events (Segool, Carlson, Goforth, von der Embse, & Barterian, 2013), managing the environment to be a more calm and secure space for learners (Hughes & Coplan, 2018), and advocating for a mastery-oriented classroom goal structure (limiting the competitive nature in academic settings; Meece, Anderman, & Anderman, 2006; Putwain, Woods, & Symes, 2010). In a more direct and transferable approach to training learners to manage their environment, educators can incorporate relaxation-based interventions such as mindfulness meditation, progressive relaxation, and breathing techniques that have repeatedly been identified as effective strategies in helping reduce the impact of situational stressors on performance (Hartman, Wasieleski, Whatley, 2016; Hembree, 1988; Holzel et al., 2011; von der Embse, 2018).

Strategies to Improve Mental Representations

In addition to limiting triggering cues in the environment, educators can support learners by helping them (a) reinterpret ambiguous cues that previously were viewed as threatening by priming competence cues (Lang & Lang, 2010; Van Yperen, 2007); (b) recognize positive cues that are initially overlooked (e.g., through active recall of the event; Zentall et al., 2001); or (c) recall prior successes, referencing peer models who have achieved similar tasks, and referencing academic or social support mechanisms that may support success in the given task (see Fletcher & Cassady, 2010). The general focus of these strategies is to adjust the perception of the stressors to be identified as less threatening or more manageable, which in turn leads to establishing mastery-oriented goals and selecting active coping strategies. As demonstrated in work by Serrano Pintado and Escolar Llamazares (2014), identification of strategies to mitigate the impact of stress on coping in academic settings and identification of the sources of anxiety are critical in selecting cognitive restructuring and skills development interventions, emotional management through relaxation techniques, or both.

Supporting Quality Goals and Coping Strategies

Once a mental representation for the academic event has been formed, situational goals based on personal interest and perceived control are established (Lazarus, 1993; Pekrun, 2006). Consistent with social-cognitive views of achievement motivation, we agree that learners develop goals in response to their interpretation of the academic and emotional setting, but those goals are also influenced by internal motivational impulses (e.g., mastery or performance goal tendencies; Shim & Ryan, 2005). When learners with emotional difficulties (e.g., academic anxieties) perceive high levels of threat in academic settings, it is common for them to select performance-avoidance goals that focus on relief from the perceived stressor rather than achievement-­oriented goals focused on completing the task at hand (e.g., Zeidner & Matthews, 2005). These goals lead to task avoidance or ego-defense behaviors such as procrastination, ­academic self-handicapping, or withdrawal from the academic settings (Thomas et al., 2017). The adoption of avoidance goals clearly does not support optimal performance – it merely relieves, temporarily, the emotional distress owing to separation from the stressor.

Once the goal is established, coping strategies or action plans for reaching the goal in the setting are reviewed and selected. Various classification models for these coping strategies have been proposed (e.g., problem-based vs. emotion-focused, adaptive vs. maladaptive, active vs. passive; Carver, Scheier, & Weintraub, 1989), but they tend to share a basic orientation toward recognizing that the functional utility of coping strategies rests in the ability of the chosen strategy to reduce the discrepancy between the individual’s appraisal of the current state and the goal state. Once again, prior experience of the learner is critical – when a learner has no repository of adaptive coping strategies to draw upon, or has a history of failure in similar settings, the probability of selecting and implementing a viable solution drops appreciably (Cassady & Boseck, 2008; Zentall et al., 2001).

Strategies to Promote Goal Setting and Strategy Selection

To support learners with emotional difficulties, educators can help students focus on mastery-focused or approach-oriented goals (Järvelä et al., 2015; Quoidbach, Mikolajczak, & Gross, 2015), paying attention to ensuring learners develop goals that are specific, proximal, and measurable (Schunk & Zimmerman, 2003). For instance, students with test anxiety are better served with a goal directed toward specific learning activities prior to an exam (e.g., attend tutoring sessions, read and take notes on each chapter) than goals focused on outcomes (e.g., “get an A”) or avoidance goals designed to escape the stressor (Thomas et al., 2017). Helping learners establish goals that directly combat the source of their emotional reactivity or academic difficulty in particular is an implicit aim of using this framework. This may include setting a goal to engage in relaxation activities before starting to study or take the exam, completing a programmed set of study activities prior to the exam, or engaging in expressive writing, exercise, or artistic expression as a means to release anxiety (e.g., Ramirez & Beilock, 2011; Serrano Pintado & Escolar Llamazares, 2014). However, it is also possible that promoting attention to emotion regulation goals may have positive utility as well (Gross, 2015). Differentiating between these approaches (approach-oriented adaptive coping strategies and emotion regulation efforts) largely rests in the established goal (see Figure 3.1). In a situation where the goal is to reduce negative affective experience, emotion regulation strategies (e.g., cognitive reframing, temporary disengagement) may be successful in meeting the goal. However, overall success in academic performance is more likely to be realized when emotion-focused goals are paired with mastery-oriented goals. This supports the potential that learners will adopt both emotion regulation strategies and SRL strategies that increase the likely outcome on academic tasks (Gross, 2015; Thomas et al., 2017).

Strategies to Bolster Expectations of Success

Additional success for learners in establishing quality goals may be realized by promoting their judgments of efficacy and resilience (Schunk & Zimmerman, 2003). Interventions that demonstrate to learners they have the necessary competence to meet the challenge (e.g., illustrating prior successes) mitigate the influence of cognitive test anxiety on performance (Lang & Lang, 2010). Support for learners with emotional difficulties needs to also include bolstering their predictions for success in using the adaptive coping strategies, which can be achieved with efficacy-based motivational manipulations (i.e., providing peer testimonials identifying the utility of specific coping strategies; Martynowicz & Cassady, 2018). Initial failure-­accepting predictions, driven by past experience, lower self-efficacy, or general negative affect can lead to learned helplessness (Cassady, 2004; Zeidner & Matthews, 2005). However, when an intervention strategy is identified that the learner recognizes as likely effective, self-efficacy can be improved (Bandura, 2005), and greater levels of confidence in performance and persistence in task perseverance can be realized, leading to higher potential for success in the academic task (Schunk & Zimmerman, 2003).

Future Research

Our brief overview of several converging lines of research demonstrates the field of educational psychology is actively pursuing solutions to support learners with emotional disturbances on a variety of applied and theoretical fronts. From our perspective, the theoretical constructs have been sufficiently articulated and supported, and it is time for applied research studies to take a lead in the discipline. We see two primary areas of promising research that are centered on applications of the theories articulated in this chapter. First, recognition of the shared characteristics of subclinical forms of anxiety in educational contexts (e.g., academic anxieties such as math or test anxiety) is critical to support learners with negative affective responses to educational settings. Broadening the attention of educators to the variety of anxiety responses that commonly arise in educational settings may provide a more focused identification of learners who struggle to perform at optimal levels owing to the deleterious effects of anxiety. As more educators begin to recognize the common forms of evaluation-related anxiety learners experience in all phases of educational activity (not just “during tests”), the potential to support treatment in large groups, small groups, or individual counseling will be improved.

The second broad area of burgeoning research in the field of anxiety in school settings is focused on identifying the efficacy of specific interventions that will promote success for individuals experiencing distinct manifestations of academic anxiety (e.g., study skills limitations, cognitive distractions, emotional reactivity; Cassady, 2004; Zeidner & Matthews, 2005). As more precise identification of the component features of school-based anxieties (and related emotional difficulties) are identified (e.g., von der Embse, Kilgus, et al., 2013), provision of precision interventions is anticipated to be more effective, overcoming prior barriers in research demonstrating success for specific strategies of test anxiety (e.g., Hembree, 1988) because the interventions were not specifically focused on the primary areas of need.

In support of this next phase of work, in our own labs we are currently exploring the utility of real-time indicators of elevated anxiety (e.g., wearable heart rate monitors on smart watches) to help learners and educators identify periods of time when their anxiety is increased. Connected to this, using data from specific assessments to identify the sources of academic stress, we are working to provide prescriptive interventions that focus on emotional control strategies (e.g., relaxation techniques, improving views of self) and SRL strategies (e.g., study skills, cognitive monitoring) to overcome those uniquely identified challenges. We see great potential in connecting these lines of inquiry, ideally using integrated technology applications that help learners diagnose, plan, monitor, and engage in positive emotional and cognitive strategies to support their success.


As the incidence of affective disorders such as academic anxieties continues to rise, the field is in need of systemic research and practical solutions to support learners to reach their academic potential as well general subjective well-being. Overall, our review of this condition leads to the recommendations that schools will better serve their learners with the adoption of universal screening practices that will identify students in emotional distress, as well as those who are demonstrating precursors to distress. Taken in conjunction with a tiered support system to promote adaptive and positive emotional coping strategies, we believe considerable success can be achieved in breaking the negative cyclical trends observed in learners with maladaptive emotional responses to academic stressors. Even without these formal structures, educators can support students with predispositions toward negative emotional appraisals in academic settings by reviewing supportive strategies using a model such as the EIP. Starting with a clear understanding of the interpretation of the perceived threats in the academic setting, as well as learners’ beliefs in their ability to successfully meet the challenge, will help educators better understand the social-cognitive representation that has been formed by their learners. Helping students reframe threats as challenges that can be overcome, identifying support mechanisms to achieve that task, and establishing effective coping strategies and goals are all well-validated strategies that can support students with emotional disturbances and support optimal functioning.

The functional utility of examining these primary dimensions of emotional distress and reactivity rests in the ability to identify and modify primary perceived threats as well as guide the learners toward goal structures and academic behaviors that will scaffold their progressive success. That is, the pathways on which learners reach a given academic outcome vary dramatically, and, by extension, the methods for supporting the learners should also be strategically adopted and applied. For instance, one immediate impact of academic anxiety is inefficient cognitive processing (e.g., attention, organization, retrieval) during the test preparation and test performance phases (Cassady, 2004; Eysenck et al., 2007). This outcome of test anxiety is more commonly experienced by learners whose source of negative self-appraisal rests in deficient study skills or habits (e.g., Naveh-Benjamin, 1991) or limitations in attentional control, working memory, or SRL skills (e.g., Deffenbacher, 1980; Sarason, 1986). Successful interventions for this source and manifestation of test anxiety tend to orient toward training in SRL strategies or study skills interventions (Segool et al., 2013). However, these interventions would be less prescriptive for students whose source of anxiety is rooted in “emotional reactivity” and may have the necessary cognitive skills and study strategies to be successful. For these students, it is more promising to employ emotion regulation strategies that help them reduce the misattributions of threat through behavior or cognitive-behavioral therapies focused on de-escalating the anxiety symptoms (e.g., Serrano Pintado & Escolar Llamazares, 2014). The key to ensuring that more students achieve greater success in overcoming the deleterious effects of anxiety is to provide individually specific intervention strategies to first identify the primary contributing factors that spark the development of anxiety, then provide an intervention strategy that meets their needs directly. In so doing, researchers and educators are in a stronger position to enhance the academic journey of students who would otherwise experience a problematic passage through school – and beyond.


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