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Chapter 13 Dissociative Disorders

Steven Jay Lynn, Joanna M. Berg, Scott O. Lilienfeld, Harald Merckelbach, Timo Giesbrecht, Dalena Van-Heugten-Van Der Kloet, Michelle Accardi-Ravid, Colleen Mundo, and Craig P. Polizzi

The most recent edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association [APA], 2013) defines dissociative disorders as conditions marked by a disruption of and/or discontinuity in the normal integration of consciousness, memory, identity, emotion, perception, body representation, motor control, and behavior” (p. 291). The presentation of dissociative disorders is often dramatic, perplexing, and highly variable, both within and across individuals. The hallmarks of dissociation are profound and often unpredictable shifts in consciousness, the sense of self, and perceptions of the environment.

DSM-5 asserts that the dissociative disorders share a common feature: They are frequently manifested in the wake of trauma and are influenced by their proximity to trauma (p. 291). Later in the chapter, we contrast the post-traumatic theory that is firmly embedded in the DSM-5 account of dissociation with a competing theory that does not conceptualize trauma as a necessary precursor to dissociation. In the course of our discussion, we will present a case study that illustrates the treatment of a patient with dissociative identity disorder (DID) and highlight controversies that have dogged the field of dissociation since the time of Janet's seminal writings on the topic (Janet, 1889/1973).

The DSM-5 (APA, 2013) identifies three major dissociative disorders that we discuss in turn—dissociative amnesia, depersonalization/derealization, and DID. We then present an overview of dissociation in general, followed by a more detailed discussion of diagnostic considerations, prevalence, assessment, and etiology specific to each of the dissociative disorders.

1. Dissociative amnesia is marked by an inability to recall important autobiographical information, usually of a traumatic or stressful nature inconsistent with ordinary forgetting. This condition most often “consists of localized or selective amnesia for a specific event or events, or generalized amnesia for identity and life history” (APA, 2013, p. 298).

2. Depersonalization/derealization disorder (DDD), formerly known as depersonalization disorder, is diagnosed on the basis of symptoms of persistent depersonalization, derealization, or both. Depersonalization symptoms include experiences of unreality; feelings of detachment or being an outside observer of one's thoughts, feelings, sensations, or actions; an unreal or absent sense of self; physical and emotional numbing; and time distortion. In contrast, derealization experiences involve feelings of unreality or detachment with respect to one's surroundings that include the experience of individuals or objects as unreal, dreamlike, foggy, visually distorted, or lifeless.

3. Dissociative identity disorder (DID; formerly called multiple personality disorder) is marked by a disruption of identity characterized by two or more distinct personality states and recurrent gaps in the recall of everyday events, personal information, and/or traumatic events that are inconsistent with ordinary forgetting (APA, 2013, p. 292).

DSM-5 also includes a fourth category of other specified dissociative disorder, for patients who do not meet full criteria for any dissociative disorder. The essential features here are chronic and recurrent clusters of mixed dissociative symptoms, identity disturbance due to prolonged and intense coercive persuasion, acute dissociative reactions to stressors, and dissociative trance. Additionally, DSM-5 includes a fifth category of unspecified dissociative disorder in which criteria are not met for a specific dissociative disorder and there is insufficient information to make a more specific diagnosis. Finally, DSM-5 currently describes a dissociative subtype of post-traumatic stress disorder (PTSD) in which persistent or recurring feelings of depersonalization and/or derealization are manifested in reaction to trauma-related stimuli. DSM-5 requires that the symptoms of all dissociative disorders must cause significant distress, impairment of functioning in major aspects of daily life, or both, and must not be attributable to the effects of a substance or another medical condition.

Some epidemiological studies among psychiatric inpatients and outpatients have reported prevalence rates of dissociative disorders exceeding 10% (Ross, Anderson, Fleischer, & Norton, 1991; Sar, Tutkun, Alyanak, Bakim, & Barai, 2000; Tutkun, Sar, Yargiç, Özpulat, Yank, & Kiziltan, 1998), and a study among community women in Turkey even reported a prevalence rate of 18.3% for lifetime diagnoses of a dissociative disorder (Sar, Akyüz, & Dogan, 2007). In contrast, many authors would take issue with these high prevalence rates in both clinical and nonclinical samples. Indeed, as our discussion will reveal, estimates of the prevalence of dissociative disorders vary widely and are surrounded by considerable controversy.

Although many authors regard symptoms of depersonalization/derealization and dissociative amnesia as core features of dissociation, the concept of dissociation is semantically open and lacks a precise and generally accepted definition (Giesbrecht, Lynn, Lilienfeld, & Merckelbach, 2008). This definitional ambiguity is related, in no small measure, to the substantial diversity of experiences that fall under the rubric of “dissociation.” Dissociative symptoms range in their manifestation from common cognitive failures (e.g., lapses in attention), to nonpathological absorption and daydreaming, to more pathological manifestations of dissociation, as represented by the dissociative disorders (Holmes et al., 2005).

This variability raises the possibility that some of these symptoms are milder manifestations of the same etiology or have different etiologies and biological substrates, raising questions about whether dissociation is a unitary conceptual domain (Hacking, 1995; Holmes et al., 2005; Jureidini, 2003). Indeed, van der Hart, Nijenhuis, Steele, and Brown (2004, 2006) have distinguished ostensibly trauma-related or pathological dissociation, which they term structural dissociation of the personality, from nonpathological dissociative experiences (e.g., altered sense of time, absorption). Structural dissociation, in turn, can be subdivided into levels that encompass primary dissociation, which is thought to involve one purportedly apparently normal part of the personality (ANP) and one emotional part of the personality (EP), secondary structural dissociation, supposedly associated with a single ANP and further division of the EP, and tertiary dissociation, ostensibly limited to DID and characterized by several ANPs and EPs. Nevertheless, as our review will demonstrate, researchers' attempts to discriminate pathological from nonpathological dissociative experiences psychometrically have been subject to criticism and have been less than uniformly successful (Giesbrecht et al., 2008; Modestin & Erni, 2004; Waller, Putnam, & Carlson, 1996; Waller & Ross, 1997).

Other researchers (Allen, 2001; Cardeña, 1994; Holmes et al., 2005) have proposed two distinct forms of dissociation: detachment and compartmentalization. Detachment consists of depersonalization and derealization, which we describe in some detail later, and related phenomena, like out-of-body experiences. Psychopathological conditions, which reflect symptoms of detachment, include depersonalization disorder and feelings of detachment that occur during flashbacks in PTSD. Compartmentalization, in contrast, ostensibly encompasses dissociative amnesia, marked by extensive forgetting of autobiographical material, and somatoform dissociation, such as sensory loss and “unexplained” neurological symptoms (Nijenhuis, Spinhoven, Van Dyck, Van der Hart, & Vanderlinden, 1998). The core feature of compartmentalization is a deficit in deliberate control of processes or actions that would normally be amenable to control, as is evident in DID or somatization disorder. Although clinicians may find it helpful to subdivide dissociative symptoms into two different symptom clusters (Bernstein-Carlson & Putnam, 1993), attempts to differentiate such clusters on a psychometric basis have not been consistently successful (see, for an example, Ruiz et al., 2008).

Dissociation is often presumed to reflect a splitting of consciousness, although it must be distinguished from the superficially similar but much debated concept of Freudian repression. Specifically, dissociation can be described as a “horizontal” split; that is, consciousness is split into two or more parts that operate in parallel. In contrast, repression is more akin to a “vertical” split, in which consciousness is arranged in levels, and traumatic or otherwise undesirable memories are ostensibly pushed downwards and rendered more or less inaccessible.

Although the existence of dissociation as a clinical symptom is not much in dispute, dissociative disorders are among the most controversial psychiatric diagnoses. Disagreement generally centers on the etiology of these disorders, with advocates often arguing for largely trauma-based origins (e.g., Dalenberg et al., 2012; 2014; Gleaves, 1996). In this light, dissociative symptoms are regarded as manifestations of a coping mechanism that serves to mitigate the impact of highly aversive or traumatic events (Gershuny & Thayer, 1999; Nijenhuis, van der Hart, & Steel, 2010). In contrast, skeptics often emphasize the role of social influences, including cultural expectancies and inadvertent therapist cueing of symptoms (e.g., Lilienfeld et al., 1999; Lynn et al., 2015; McHugh, 2008). As we will learn later in the chapter, the controversies stemming from etiology and classification of dissociative disorders extend to their assessment and treatment. We will focus our discussion on chronic dissociative symptoms, rather than dissociation at the time of a highly aversive event (i.e., peritraumatic dissociation). Also, we will not elaborate on the dissociative subtype of PTSD described in DSM-5 (see, for a critical analysis, Dutra & Wolf, 2017). However, we will present a number of “state” measures of dissociation because researchers not infrequently consider temporary changes in dissociation in the context of research on more chronic presentations of dissociation.

Dissociative Amnesia

The diagnosis of dissociative amnesia requires that the memory loss is extensive and not attributable to substance use or to a neurological or other medical condition such as age-related cognitive loss, complex partial seizures, or closed-head brain injury and that the symptoms are not better explained by DID, PTSD, acute stress disorder, somatic symptom disorder, or major or mild neurocognitive disorder (APA, 2013, p. 298). This disorder, formerly referred to as psychogenic amnesia, often presents as retrospective amnesia for some period or series of periods in a person's life, frequently involving a traumatic experience.

DSM-5 lists several subtypes of dissociative amnesia. In localized amnesia, the individual cannot recall any information from a specific period of time, such as total forgetting of a holiday week. Selective amnesia involves the loss of memories for some, but not all, events from a specific period of time. In generalized amnesia, individuals cannot recall anything about their entire lives, and in continuous amnesia, individuals forget each new event as it occurs. Finally, systematized amnesia consists of the “loss of memory for specific categories of information” (e.g., sexual abuse, a particular person). These last three types of dissociative amnesia—generalized, continuous, and systematized—are much less common than the others, and may be manifestations of more complex dissociative disorders, such as DID rather than dissociative amnesia alone.

Lynn et al. (2014a) argued that the central diagnostic criterion for dissociative amnesia is vague and subjective in stipulating that one or more episodes of inability to recall important information must be “…inconsistent with ordinary forgetting” (APA, 2013, p. 298). The reliability of judgments of what constitutes “ordinary forgetfulness” is questionable, and what is “ordinary” hinges on a variety of factors, including the situational context and presence of comorbid conditions. A similar point was raised by Read and Lindsay (2000), who demonstrated that when people are encouraged to remember more about a selected target event, they report their forgetting to be more extensive, compared with individuals who are asked to simply reminisce about a target event.

Epidemiology

Because rates of reporting vary so widely, it is difficult to obtain reliable epidemiological information regarding dissociative amnesia. Questions concerning the validity of dissociative amnesia as a diagnostic entity are fueled by markedly different prevalence rates in the general population across cultures: 0.2% in China, 0.9% and 7.3% in Turkey, and 3.0% in Canada (Dell, 2009). These varying prevalence estimates could reflect genuine cultural differences, but they could just as plausibly reflect different interviewer criteria for evaluating amnesia.

The DSM-5 states that dissociative amnesia can present in any age group, although it is more difficult to diagnose in younger children due to their difficulty in answering questions about periods of forgetting and possible confusion with a number of other disorders and conditions, including inattention, anxiety, oppositional behavior, and learning disorders. There may be just one episode of amnesia, or there may be multiple episodes, with each episode lasting anywhere from minutes to decades. Other sources (e.g., Coons, 1998) suggest that most cases occur in individuals in their 30s or 40s, and that 75% of cases last between 24 hours and 5 days. The prevalence of dissociative amnesia is approximately equal between genders. Still others argue that the scientific evidence for the existence of dissociative amnesia is unconvincing, and that barring brain injury or substance abuse or dependence, individuals who have experienced trauma do not forget those events (e.g., McNally, 2003; Pope, Hudson, Bodkin, & Oliva, 1998).

Certain cases of purported traumatic amnesia are in fact attributable to organic or other nondissociative causes. For example, when critiquing a “convincing demonstration of dissociative amnesia” (Brown, Scheflin, & Hammond, 1997), McNally (2004) discussed a study (Dollinger, 1985) of two children who witnessed a playmate struck and killed by lightning, and who were later diagnosed with dissociative amnesia. Yet as McNally noted, this diagnosis was clearly mistaken, because the children had also been struck by lightning and knocked unconscious.

Amusingly, and perhaps tellingly, Pope, Poliakoff, Parker, Boynes, and Hudson (2007) offered a reward of $1,000 to “the first individual who could find a case of dissociative amnesia for a traumatic event in any fictional or nonfictional work before 1800” (p. 225) on the basis that, whereas the vast majority of psychological symptoms can be found in literature or records dating back centuries, dissociative amnesia appears only in more modern literature beginning in the late 1800s. Over 100 individuals came forward with examples, but none met the diagnostic criteria for the disorder (although the prize later went to someone who discovered a case of dissociative amnesia in a 1786 opera, Nina, by the French composer Nicholas Dalayrac). Although Pope and colleagues' challenge does not “prove” anything regarding the validity of the disorder, its relative scarcity, and apparently recent (perhaps after the late 18th century) development, raise troubling questions about its existence as a natural category or entity.

A special form of dissociative amnesia is crime-related amnesia. Many perpetrators of violent crimes claim to experience great difficulty remembering the essential details of the crime they committed (Moskowitz, 2004). Memory loss for crime has been reported in 25–40% of homicide cases and severe sex offenses. Nevertheless, skeptics believe that genuine dissociative amnesia in these cases is rare. They have pointed out that trauma victims (e.g., concentration camp survivors) almost never report dissociative amnesia (Merckelbach, Dekkers, Wessel, & Roefs, 2003). For example, Rivard, Dietz, Matell, and Widawski (2002) examined a large sample of police officers involved in critical shooting incidents and found no reports of amnesia.

Also, recent laboratory research shows that when participants encode information while in a “survival mode,” this manipulation yields superior memory effects (Nairne & Pandeirada, 2008). This finding is difficult to reconcile with the idea of dissociative amnesia while committing a crime. Thus, it is likely that feigning underlies most claims of crime-related amnesia (Van Oorsouw & Merckelbach, 2010), and the recent literature provides detailed case studies illustrating this point (Marcopolus, Hedjar, & Arredondo, 2016).

Dissociative Fugue

Dissociative fugue (previously called psychogenic fugue) is arguably the most controversial dissociative phenomenon after DID. In DSM-IV-TR, dissociative fugue (i.e., short-lived reversible amnesia for personal identity, involving unplanned travel or wandering) was listed as a separate diagnosis. In DSM-5, dissociative fugue—defined therein as apparently purposeful travel or bewildered wandering associated with amnesia for identity or other important autobiographical information—is no longer diagnosed as a disorder in its own right, but is instead coded as a condition that can accompany dissociative amnesia. In a fugue (“fugue” has the same etymology as the word “fugitive”) episode, amnesia for identity may be so extreme that a person physically escapes his or her present surroundings and adopts an entirely new identity. If and when this identity develops, it is often characterized by higher levels of extraversion than the individual displayed pre-fugue, and he or she usually presents as well integrated and nondisordered.

Periods of fugue vary considerably across individuals, both in duration and in distance traveled. In some cases, the travel can be a brief and relatively short trip, whereas, in more extreme cases, it can involve traveling thousands of miles and even crossing national borders. While in the dissociative fugue state, individuals often appear to be devoid of psychopathology; if they attract attention at all, it is usually because of amnesia or confusion about personal identity. Again, it is doubtful that fugues constitute a fixed and cross-cultural diagnostic category. Hacking (1995) provides a detailed historical and critical analysis of fugue showing that they first appeared in the 19th century and since that time fluctuated in apparent prevalence and acceptance by the psychiatric community.

Diagnostic Considerations

Although DSM-5 notes that dissociative fugue, with travel, is not uncommon in DID, dissociative fugue may manifest with other symptoms, including depression, anxiety, dysphoria, grief, shame, guilt, stress, and aggressive or suicidal impulses (APA, 2013). Reportedly, the condition often develops as a result of traumatic or stressful events, which has led to controversy and ambiguity regarding the relation between dissociative fugue and PTSD. Precipitants associated with the development of dissociative fugue include war or natural disasters, as well as the avoidance of various stressors, such as marital discord or financial or legal problems (Coons, 1998). Such avoidance suggests that clinicians must be certain to rule out malingering and factitious disorders before diagnosing dissociative fugue. Staniliou and Markowitsch (2014) discuss basic memory mechanisms that might be involved in fugue states.

Certain culture-bound syndromes exhibit similar symptoms to dissociative fugue. These include amok, present in Western Pacific cultures (which has given rise to the colloquialism “running amok”), pibloktok, which is present in native cultures of the Arctic, and Navajo “frenzy” witchcraft, all of which are marked by “a sudden onset of a high level of activity, a trancelike state, potentially dangerous behavior in the form of running or fleeing, and ensuing exhaustion, sleep, and amnesia” for the duration of the episode (APA, 2000, p. 524; Simons & Hughes, 1985).

Epidemiology

DSM-IV-TR places the population prevalence estimate of dissociative fugue at 0.02%, with the majority of cases occurring in adults (APA, 2000, p. 524). Ross (2009b) observed that in the approximately 3,000 individuals he treated in his trauma program over a 12-year period, he encountered fewer than 10 individuals with pure dissociative amnesia or pure dissociative fugue, although he noted that symptoms of amnesia and fugue were common in the patients he admitted.

Depersonalization/Derealization Disorder

Depersonalization/derealization disorder (DDD) is one of the most common dissociative disorders and perhaps the least controversial. In DDD, reality testing remains intact (APA, 2013, p. 302): Individuals are aware that the sensations are not real and that they are not experiencing a break from reality akin to psychosis. In a departure from DSM-IV, in which depersonalization and derealization were diagnosed separately, DSM-5 created a new diagnostic category of DDD. This “lumping” of formerly separate conditions is supported by findings (Simeon, 2009a) that individuals with derealization symptoms do not differ significantly from those with depersonalization accompanied by derealization in salient respects (e.g., illness characteristics, comorbidity, demographics).

Greatly contributing to our knowledge about depersonalization symptoms has been the development of well-validated screening instruments, notably the Cambridge Depersonalization Scale (CDS; Sierra & Berrios, 2000; Sierra, Baker, Medford, & David, 2005). Depersonalization episodes are not uncommonly triggered by intense stress and are often associated with high levels of interpersonal impairment (Simeon et al., 1997).

Episodes of depersonalization or derealization are also frequently associated with panic attacks, unfamiliar environments, perceived threatening social interactions, the ingestion of hallucinogens, depression, and PTSD (Simeon, Knutelska, Nelson, & Guralnik, 2003). Individuals with DDD are also more likely than healthy individuals to report a history of emotional abuse. In contrast, general dissociation scores are better predicted by a history of combined emotional and sexual abuse (Simeon, Guralnik, Schmeidler, Sirof, & Knutelska, 2001).

Diagnostic Considerations

Nearly 50% of adults have experienced at least one episode of depersonalization in their lifetimes, usually in adolescence, although a single episode is not sufficient to meet criteria for the disorder (Aderibigbe, Bloch, & Walker, 2001). Because depersonalization and derealization are common, DDD should be diagnosed only if these symptoms are persistent or recurrent and are severe enough to cause distress or impairment in functioning, or both. The distress associated with DDD may be extreme, with sufferers reporting they feel robotic, unreal, and “unalive.” They may fear becoming psychotic, losing control, and suffering permanent brain damage (Simeon, 2009a). Individuals with DDD may perceive an alteration in the size or shape of objects around them. Other people may appear mechanical or unfamiliar, and affected individuals may experience a disturbance in their sense of time (Simeon & Abugel, 2006).

Although symptoms of depersonalization often occur in the presence of psychotic symptoms (e.g., Gonzalez-Torres et al., 2010; Goren et al., 2012; Vogel, Braungardt, Grabe, Schneider, & Klauer, 2013), a diagnosis of DDD requires that the symptoms do not occur exclusively in the course of another mental disorder, nor can they be attributable to substance abuse or dependence or to a general medical condition. Furthermore, DDD should not be diagnosed solely in the context of meditative or trance practices.

Symptoms of other disorders, such as anxiety disorders, major depression, somatoform disorders, substance use disorders, and certain personality disorders (especially avoidant, borderline, and obsessive-compulsive), may also be present in the context of DDD (Belli, Ural, Vardar, Yesilyrt, & Oncu, 2012; Lynn et al., 2014b; Simeon et al., 1997). Depersonalization and derealization symptoms are also commonly part of the symptom picture of acute stress disorder (ASD; APA, 2013), which is often a precursor to PTSD.

Epidemiology

DSM-5 estimates the lifetime prevalence of DDD in the United States at 2%, with a range of 0.8– 2.8% (see also Ross, 1991), suggesting that DDD might be as common as or more common than schizophrenia and bipolar disorder. DDD is diagnosed almost equally in women and men (Simeon et al., 2003). It frequently presents for treatment in adolescence or adulthood, even as late as the 40s, though its onset may be earlier. Estimates of the age of onset of DDD range from 16.1 (Simeon et al., 1997) to 22 years (Baker et al., 2003).

The onset and course of DDD vary widely across individuals. Some people experience a sudden onset and others a more gradual onset; some experience a chronic form of the disorder, whereas others experience it episodically. In about two-thirds of people with DDD, the course is chronic, and symptoms of depersonalization are present most of the time, if not continually. Episodes of depersonalization may last from hours to weeks or months, and in more extreme cases, years or decades (Simeon, 2009a).

Dissociative Identity Disorder

According to DSM-5, “the defining feature of DID is the presence of two or more distinct personality states or experiences of possession” (APA, 2013, p. 292). Thus, the requirement that people diagnosed with DID must experience distinct identities that recurrently take control over one's behavior is no longer present. Importantly, in DSM-5 “distinct personality states” replaces the term identities. The diagnostic language in DSM-5 represents a marked departure from DSM-II (APA, 1968), which used the term multiple personalities, and from DSM-IV (APA, 1994), which labeled the condition DID to underscore alterations in identity, rather than fixed and/or complete “personalities.”

These shifts in diagnostic criteria may prove to be problematic and result in changes in the prevalence rates of DID. For example, what constitutes a personality state or an experience of possession may be open to greater interpretation compared with previous iterations of DSM. Moreover, in DSM-5, signs and symptoms of personality alteration may be not merely “observed by others,” but also “reported by the individual” (APA, 2013; p. 292), further expanding opportunities for the diagnosis of DID. In cases in which alternate personality states are not witnessed, in DSM-5 it is still possible to diagnose the disorder when there are “sudden alterations or discontinuities in sense of self or agency…and recurrent dissociative amnesias” (APA, 2013; p. 293), creating even more latitude and subjectivity in the diagnosis of DID. Moreover, amnesia is no longer restricted to traumatic events and may now be diagnosed in relation to everyday events, which may also increase the base rates of diagnosed DID. Although DSM-5 no longer defines DID in terms of “distinct identities that recurrently take control of the individual's behavior” (DSM-IV, p. 519), in the remainder of the chapter, we will not refrain from using the terms personalities and identities, insofar as these terms (a) continue to be widely used in the extant literature and (b) encompass “personality states.”

Diagnostic Considerations

To meet diagnostic criteria for DID, an individual's symptoms cannot be attributable to substance use or to a medical condition, and the “disturbance is not a normal part of a broadly accepted cultural or religious practice” (APA, 2013; p. 292). When the disorder is assessed in children, the symptoms must not be confused with imaginary play. To recognize cultural variants of dissociative phenomena, DSM-5 refers to a “possession form” of DID, which is “typically manifest as behaviors that appear as if a ‘spirit,’ supernatural being, or outside person has taken control, such that the individual begins speaking or acting in a distinctly different manner” (APA, 2013, p. 293). Because such manifestations are not uncommon in different cultures (see, for a discussion of trance/possession phenomena, Cardeña, van Duijl, Weiner, & Terhune, 2009), to warrant a diagnosis of DID, the identities must be present recurrently, be unwanted or involuntary, engender significant distress or impairment, and not be a part of accepted cultural/religious practices. Some authors have questioned clinicians' ability to discriminate between pathological and nonpathological forms of possession (see, for a discussion, Delmonte, Lucchetti, Moreira-Almeida, & Farias, 2016).

In nonpossession forms of DID, there is typically considerable variation in the presentation of symptoms. Nevertheless, the primary identity or personality state in an individual with DID often carries the individual's given name and tends to be “passive, dependent, guilty, and depressed.” Other personalities, often called “alters,” may be assertive or even aggressive and hostile, and these more dominant identities usually possess more complete memories regarding the individual's actions and history. Within one individual, there can often be anywhere between two and 100 or more personalities, with approximately 50% of individuals reporting 10 or fewer distinct identities, although extreme cases of many as 4,500 alters have been reported (Acocella, 1999). Reported identities are usually just “regular” people, but more extreme and bizarre cases exist. There have been reports of identities claiming to be Mr. Spock from Star Trek, the rock star Madonna, the bride of Satan, and even a lobster.

Researchers have documented substantial comorbidity of DID with other disorders. For example, Ellason, Ross, and Fuchs (1996) reported that DID patients met criteria for an average of eight Axis I disorders and 4.5 Axis II disorders. One-half to two-thirds of patients with DID meet diagnostic criteria for borderline personality disorder (BPD; Coons, Bowman, & Milstein, 1988; Horevitz & Braun, 1984). Conversely, Sar, Akyuz, Kugu, Ozturk, and Ertem-Vehid (2006) found that 72.5% of patients screened for BPD had a dissociative disorder. In one study, researchers (Kemp, Gilbertson, & Torem, 1988) reported no significant differences between BPD and DID patients on measures of personality traits, cognitive and adaptive functioning, and clinician ratings, suggesting noteworthy commonalities between the two conditions. Histories of sexual and physical abuse are also commonly reported in both patient groups, and BPD patients score well above general population norms on measures of dissociation (Lauer, Black, & Keen, 1993). High levels of dissociation among BPD patients exacerbate cognitive performance deficits (Krause-Utz et al., 2017; Winter et al., 2015). Although Lauer et al. (1993) suggested that DID is an epiphenomenon of the combination of BPD with high suggestibility, Brand et al. (2016) argued that DID and BPD are distinct disorders.

Individuals with DID often experience additional symptoms, including self-mutilation; suicidal or aggressive behavior; as well as major depression, substance abuse, and sexual, eating, and sleep disorders (Fullerton et al., 2000; North, Ryall, Ricci, & Wetzel, 1993; Ross, 1997). Accordingly, some clinicians have argued that the DID diagnosis really is a severity marker identifying extreme variants of a host of other disorders (for an extensive discussion see North et al., 1993).

Many DID patients meet the criteria for schizoaffective disorder (Lauer et al., 1993), and as many as half have received a previous diagnosis of schizophrenia (Ross & Norton, 1988). Indeed, auditory and visual hallucinations are common in both DID and schizophrenia. However, patients with DID commonly report that hallucinated voices originate inside their heads, whereas patients with schizophrenia tend to perceive the origin of voices outside their heads and possess less insight into the nature of their symptoms (Coons, 1998; Kluft, 1993).

Chiu et al. (2016a) reported that among acute psychiatric patients, symptoms of psychosis and dissociation were associated with an altered sense of individuality. DID patients have been reported to endorse more positive symptoms (e.g., delusions, hallucinations, and suspiciousness) and Schneiderian first-rank symptoms, which include themes of passivity, than do schizophrenic patients (Ellason & Ross, 1995; Steinberg, Rounsaville, & Cichetti, 1990). Ellason and Ross (1995) argued that the presence of positive symptoms can be used to formulate an accurate differential diagnosis between the two disorders, although further research regarding this possibility is necessary (for further diagnostic considerations see Steinberg & Siegel, 2008).

Post-traumatic stress disorder is one of the most commonly comorbid conditions with DID (Loewenstein, 1991). Moreover, PTSD patients are more likely to present with symptoms of dissociation (e.g., numbing, amnesia, flashback phenomena) than are patients with major depression, schizophrenia, and schizoaffective disorder (Bremner, Steinberg, Southwick, Johnson, & Charney, 1993).

DSM-5 lists a number of differential conditions that clinicians should consider before diagnosing a patient with DID. Two of these are malingering and factitious disorder in which individuals intentionally fabricate symptoms. For those who want to fabricate illness, the odd, unusual, and highly subjective experiences that are inherent to dissociative symptoms are ideal because they signal so clearly to other people that one suffers from a disease (Kuperman, 2006). Recent studies have drawn attention to the overlap between dissociative symptoms and feigning tendencies (Merckelbach, Boskovic, Pesy, Dalsklev, & Lynn, 2017) and, given this state of affairs, clinicians are well advised to look into the possibility of feigning with so-called symptom validity tests (see later) when psychometrically evaluating the nature and intensity of dissociative symptoms.

Epidemiology

Dissociative identity disorder may be episodic or continuous, and in some cases may remit after the late 40s (APA, 2000). There are documented cases of DID extending decades, and the concept of fragmented or multiple personalities is an ancient one. That said, the number of cases has increased exponentially in the past few decades. Prior to 1970, there were approximately 80 reported cases, but by 1986 that number had ballooned to approximately 6,000. As of 1998, there were approximately 40,000 cases (Lilienfeld & Lynn, 2015).

Population prevalence estimates vary widely, from extremely rare (e.g., Piper, 1997; Rifkin, Ghisalbert, Dimatou, Jin, & Sethi, 1998) to rates approximating that of schizophrenia (1–2%; Coons, 1998; Ross, 1997). Estimates of DID in inpatient settings range from 1% to 9.6% (Rifkin et al., 1998; Ross, Duffy, & Ellason, 2002). In addition to the dramatic increase in DID's prevalence over the past few decades, there has been an increase in the number of “alters” reported, from only two or three separate identities to an average of approximately 16 (interestingly, the exact number reported by the movie Sybil; see later) by 1990.

Dissociative identity disorder is between three and nine times more common in women than men, and women also tend to have more identities (an average of 15, as compared with the male average of eight; APA, 2000). Nevertheless, this imbalanced sex ratio may be an artifact of selection and referral biases (Lynn, Fassler, Knox, & Lilienfeld, 2009). In particular, a larger proportion of males with DID may end up in prisons (or other forensic settings) than in clinical settings (Putnam & Loewenstein, 2000).

Dissociative identity disorder is the most controversial dissociative disorder, and easily among the most controversial disorders in DSM-5. Skeptics of the disorder (Paris, 2012; Piper & Merskey, 2004) argue that its proliferation is in part a function of media exposure. In 1976, the movie Sybil was released, documenting the real-life story of a woman who had supposedly experienced severe child abuse and later developed 16 personalities (but see the “Etiological Considerations” section for evidence calling into question significant details of the Sybil case). In addition to the number of cases increasing after the release of this movie, the number of individuals reporting child abuse as a cause of DID also rose drastically (Lilienfeld & Lynn, 2015; Spanos, 1996). In contrast, proponents of the disorder respond that clinicians are now simply better equipped to identify the disorder (Gleaves, May, & Cardeña, 2001) and continue to maintain that dissociative disorders are massively underdiagnosed (Brand et al., 2016). We elaborate on this etiological debate later in the chapter.

Psychological Assessment

A variety of assessment instruments are available to evaluate dissociation and dissociative disorders. In this section, we review commonly used structured interview and self-report measures.

Structured Interview Measures

The Structured Clinical Interview for DSM-IV (SCID-D; Steinberg, 1985) and its revision (SCID-D-R; Steinberg, 1994) are semistructured interviews that systematically assess five core symptoms of dissociation: amnesia, depersonalization, derealization, identity confusion, and identity alteration. The SCID-D incorporates the DSM-IV criteria for dissociative disorders. The full 250-item administration may take 2–3 hours for psychiatric patients with dissociative symptoms; however, nondissociative psychiatric patients may complete the interview in 30–90 minutes, and nonpsychiatric participants in 30 minutes. The severity of each of the five core symptoms is scored in terms of distress, dysfunctionality, frequency, duration, and course. The revised scale was administered in National Institute of Mental Health field trials that encompassed 350 interviews of dissociative and nondissociative adults. Reports from the field trials (N = 141 mixed psychiatric patients) revealed that the interexaminer and temporal reliability of the SCID-D-R ranges from adequate to excellent (weighted kappa = 0.77–0.86) for both the presence and extent of dissociative symptoms over three time periods. For type of dissociative disorder, inter-examiner agreement ranged from 0.72 to 0.86, and test–retest reliability for the overall presence of a dissociative disorder was good (0.88 over 7-day period). The SCID-D-R possesses good convergent validity and is capable of distinguishing DID patients from patients with anxiety disorders, substance abuse, personality disorders, eating disorders, and psychotic disorders (Cardeña, 2008). The SCID-D-R may be helpful in discriminating DID from feigning. It also appears to distinguish DID from schizophrenia (Wellburn et al., 2003). Nevertheless, Kihlstrom (2005, p. 3) countered that “even with relatively strict criteria in place, it can be difficult to discriminate between dissociative disorders and bipolar disorder, borderline personality disorder, and even schizophrenia.”

The Dissociative Disorders Interview Schedule (DDIS; Ross et al., 1989) is a structured interview used to assist in the diagnosis of dissociative disorders, as well as conditions that often co-occur with it, including somatization disorder, major depressive disorder, and borderline personality disorder. The interview has been used for clinical and research purposes and consists of 16 sections with a total of 131 questions. The interview is highly structured to minimize interviewer confirmation bias and sequenced so that indirect questions about secondary features of DID precede increasingly specific questions.

In the original validation study, 80 psychiatric patients from specialized research clinics were interviewed. Patients diagnosed with DID (n = 20) were compared with patients with panic disorder (n = 20), eating disorder (n = 20), and schizophrenia (n = 20). For DID, the DDIS yielded a sensitivity of 90% and a specificity of 100% [see also Ross et al. (1992) who demonstrated high agreement (94.1%) of DDIS classification using the DDIS with independent clinical evaluation]. The authors reported that interrater reliability was adequate (r = 0.68; Ross et al., 1989). The DDIS has demonstrated good convergent validity, as indexed by high correlations of DID diagnosis scores with the Dissociative Experiences Scale (DES; r = 0.67–0.78; Cardeña, 2008). Nevertheless, the authors (Ross et al., 1989) cautioned that depersonalization disorder cannot be reliably diagnosed using the DDIS (interrater reliability = 0.56).

The Clinician Administered Dissociation State Scale (CADSS; Bremner et al., 1998) was developed to assess dissociative states. The clinician verbally administers 19 “subject-rated” items on a Likert-type scale ranging from 0 (not at all) to 4 (extremely). Three subscales subsume the subject-rated items: amnesia, depersonalization, and derealization. The clinician also observes the participant's behavior during the interview and rates eight behaviors presumed to indicate the presence of a dissociative state on the same Likert-type scale as the subject-rated items.

In the original study, the CADSS was administered to patients with combat-related PTSD and a comorbid dissociative disorder (PTSD/dissociative) (n = 68). These patients were compared with patients with schizophrenia (n = 22), mood disorders (n = 15), healthy comparison individuals (n = 8), and combat veterans without PTSD (n = 11). The CADSS discriminated between patients with PTSD and comorbid dissociative disorders (86% of cases) and patients with the comparison conditions. Furthermore, the CADSS detected changes in dissociative symptoms before and after patients with PTSD participated in a traumatic memories group. These patients showed a significant increase in symptoms compared with baseline, suggesting that the CADSS may be sensitive enough to capture changes in repeated measures designs. Interrater reliability was excellent for the total scale (intraclass correlation coefficient, ICC = 0.92) and for the subject-rated portion (ICC = 0.99), but was markedly lower for the observer ratings (ICC = 0.34). The internal consistency of the CADSS was good to excellent for the total scale (α = 0.94), subjective portion (α = 0.94), observer ratings (α = 0.90), and the individual subscales (α = 0.74–.90). Recently, Condon and Lynn (2014) reported that the CADSS correlated at r = 0.63 with the revised DES (DES-II) and reported the internal consistency of the CADSS to be α = 0.80 in a sample of undergraduates.

Self-Report Measures

The DES (Bernstein & Putnam, 1986) and the DES-II (Bernstein-Carlson & Putnam, 1993) are brief self-report measures of dissociation that can be used in both research and clinical settings to assess individuals within normal and psychiatric populations. Participants rate 28 items pertaining to dissociation in terms of the frequency at which they are experienced, from 0% to 100%. In the original sample, the test–retest reliability among 192 participants was 0.84 over a period of 4–8 weeks, and split half reliability coefficients ranged from 0.71 to 0.96, indicating good internal consistency. In addition, DES scores differentiated participants with a dissociative disorder (e.g., DID) from those without a dissociative disorder (e.g., nonsymptomatic adults, late adolescent college students, people with alcohol problems, and people with phobias) A cutoff of 30 correctly identified 74% of patients with DID and 80% of subjects without DID in a multicenter study (Carlson et al., 1991b).

The DES is the most frequently used self-report measure of dissociation (Brand, Armstrong, & Loewenstein, 2006). Nevertheless, researchers have questioned whether the scale is unidimensional, as would be expected of a factorially pure measure of dissociation. Carlson et al. (1991a) reported a three-factor solution—amnesia, absorption (related to openness to experience), and depersonalization (also see Ross, Ellason, & Anderson, 1995; Sanders & Green, 1994)—and others (Ray & Faith, 1994) have identified four factors. In contrast, Waller (1995) reanalyzed Carlson et al.'s (1991a) data and concluded that their three-factor solution could reflect the skewed distribution of the items, and thus might be a statistical artifact reflecting the presence of difficulty factors (that is, factors induced by similar levels of skewness across the items; see also Holmes et al., 2005; Wright & Loftus, 1999).

Waller, Putnam, and Carlson (1996) responded to criticisms that the DES contains a substantial number of nonpathological items that tap absorption (e.g., “Some people find that when they are watching television or a movie they become so absorbed in the story that they are unaware of other events happening around them”) by developing the DES-Taxon (DES-T) scale. This eight-item scale contains items from the original DES that measure pathological dissociation, including derealization, depersonalization, psychogenic amnesia, and identity alteration. Waller and Ross (1997) estimated that the general population base rate of pathological dissociation is 3.3%. Of course, being classified as a taxon member (i.e., distinct type or latent class) cannot be equated with DID (Modestin & Erni, 2004), as the prevalence of DID in the general population is almost certainly much lower than 3%. Although the resulting scale was stricter in the criteria for establishing evidence of pathologic dissociation, the data supporting its validity are mixed. Simeon et al. (1998) found that the DES-T sum score is superior to the standard DES at distinguishing patients with depersonalization disorders (DDD) from comparison subjects. Nevertheless, later studies revealed that the DES-T: (a) classified only 64% of patients with DDD as having a dissociative disorder (Simeon et al., 2003), (b) produced high false-positive rates (Giesbrecht, Merckelbach, & Geraerts, 2007b; Modestin & Erni, 2004), and (c) lacked temporal stability for taxon membership probability (Watson, 2003). Nevertheless, many studies have documented significant differences between people who score high versus low on both the DES and the DES-T with respect to a variety of measures of memory and cognition (Giesbrecht et al., 2008).

The Adolescent Dissociative Experiences Scale (A-DES; Armstrong, Putnam, Carlson, Libero, & Smith, 1997) is a 30-item self-report measure designed exclusively for use with adolescent populations. The scale is intended to serve as a screening tool for dissociative disorders among adolescents and traces the developmental trajectories of normal and pathological dissociation over time. The A-DES items are rated on an 11-point Likert-type scale, and they comprise the following subscales: dissociative amnesia, absorption and imaginative involvement, passive influence, and depersonalization and derealization. The A-DES was normed using a group of healthy adolescents in junior-high and high school populations (Smith & Carlson, 1996) and a group of adolescent clinical patients (Armstrong et al., 1997). The authors reported excellent internal consistency for the total score (α = 0.93) and subscales (α = 0.72–85). Nevertheless, there are questions concerning the A-DES's convergent validity. In a sample of 331 nonreferred youths, Muris, Merckelbach, and Peeters (2003) reported that A-DES scores are significantly related not only to PTSD symptoms and fantasy proneness, but also to other anxiety symptoms.

The Multidimensional Inventory of Dissociation (MID 5.0; Dell, 2006) is a self-report measure created to assess the symptom domain of DID and the phenomenological domain of dissociation. The MID 5.0 contains 168 dissociation items and 50 validity items rated on a 0–10 Likert-type scale. The validity items measure response sets (e.g., careless, inattentive responding, which is a feature that other self-report instruments measuring dissociativity (e.g., the DES) lack. The MID shows promising convergent validity with other psychiatric diagnoses (e.g., it distinguishes among individuals with DID, dissociative disorder not otherwise specified, mixed psychiatric, and nonclinical adults; Dell, 2002) and self-report measures (e.g., correlations with the DES = 0.90; Dell, 2006), as well as structural validity (e.g., factor analyses isolated a single overarching factor of pathological dissociation; see Dell, 2006). Nevertheless, these findings have yet to be replicated by independent research groups, and Kruger and Fletcher (2017) have described one first attempt with encouraging results. The authors reported good-to-excellent internal consistency of the 23 dissociation scales (α = 0.84–0.96) and temporal stability (4- to 8-week test–retest interval; r = 0.82–0.97) in a large clinical sample. These latter results were replicated in Israel and Germany (see Dell, 2006).

The Somatoform Dissociation Questionnaire (SDQ-20; Nijenhuis, Spinhoven, Van Dyck, Van der Hart, & Vanderlinden, 1996) is a self-report measure designed to evaluate the presence of somatoform responses associated with dissociative states that cannot be medically explained. Participants rate items on a five-point Likert-type scale. Twenty of the 75 original items discriminated outpatients with dissociative disorders from nondissociative psychiatric outpatients and comprised the final scale. The authors reported excellent internal consistency (α = 0.95) and higher scores among patients with DID compared with patients with dissociative disorder not otherwise specified. The authors also reduced the SDQ-20 to a five-item screen for dissociative disorders (SDQ-5; Nijenhuis, Spinhoven, Van Dyck, Van der Hart, & Vanderlinden, 1997). For dissociative disorders among psychiatric patients, the SDQ-5 exhibited a sensitivity of 94% and a specificity of 98% (Nijenhuis et al., 1998). A study in which DES, MID, and SDQ-20 were compared with SCID-D outcomes in psychiatric outpatients found that these self-report instruments have comparable diagnostic accuracy and are equivalently suitable as screening tools for dissociative disorders (Mueller-Pfeiffer et al., 2013).

The Dissociation Questionnaire (DIS-Q; Vanderlinden, Van Dyck, Vandereycken, & Vertommen, 1991) was developed to account for sociocultural differences in European populations as well as to assess a broad spectrum of dissociative experiences. The authors generated items from existing dissociation questionnaires and clinical experience. Participants rate items on a 1–5 Likert-type scale; the final 63-item scale was normed on 374 participants from the general population in Belgium and the Netherlands. Four factors constitute the DIS-Q (i.e., identity confusion, loss of control, amnesia, and absorption). Internal consistency of the subscales (α = 0.67–0.94) and the overall scale (α = 0.96) was adequate to excellent, as was test–retest reliability over a period of 3–4 weeks. The authors report successful discrimination of patients with dissociative disorders and nondissociative disorders with the exception of PTSD. Within the dissociative disorders, the DIS-Q successfully discriminated DID from dissociative disorder–not otherwise specified.

The State Scale of Dissociation (SSD; Kruger & Mace, 2002) is a self-report inventory designed to detect changes in dissociative states, rather than traits. The SSD was developed using existing scales, the DSM-IV and the ICD-10, along with the aid of clinical experts. The 56-item scale is scored on a Likert-type scale from 0 to 9 and broken down into seven subscales: derealization, depersonalization, identity confusion, identity alteration, conversion, amnesia, and hypermnesia (remembering things too well). In the original study, the SSD was administered to 130 patients with major depression (n = 19), schizophrenia (n = 18), alcohol withdrawal (n = 20), dissociative disorders (n = 10), and healthy controls (n = 63). A score of > 3.9 nearly doubled the certainty of a diagnosis of a dissociative disorder, although an important limitation is the small sample of dissociative patients. The internal consistency of the SSD was good to excellent for the total scale (α = 0.97), and correlation between the SSD and the DES among people with a dissociative disorder was r = 0.81, and in healthy controls, r = 0.57. Following a brief grounding activity (53 minutes, during which participants completed a number of other scales), the SSD scores among all participants decreased significantly on retest, suggesting that the SSD is sensitive to short-term changes in dissociative states across diagnostic groups.

The Cambridge Depersonalization Scale (CDS; Sierra & Berrios, 2000) consists of 29 items that ask respondents to rate recent depersonalization symptoms on a five-point frequency scale (anchors: 0 = never; 4 = all the time) and a six-point duration scale (anchors: 1 = few seconds; 6 = more than a week). The scale differentiates patients with DDD from other patient groups (e.g., patients with epilepsy, anxiety disorders) and from healthy controls (Sierra & Berrios, 2000). Sierra and Berrios (2000, 2001) reported sound internal consistency for the CDS (e.g., α = 0.89). An exploratory factor analysis identified four factors that accounted for 73.3% of the variance: anomalous body experience, emotional numbing, anomalous subjective recall, and alienation from surroundings (Sierra et al., 2005).

Apart from those that have already been mentioned, there are other self-report measures of dissociative symptoms (e.g., the Multi-scale Dissociation Inventory; MDI; Briere, Weathers, & Runtz, 2005). What is currently missing is a thorough analysis of how these various instrument relate to one another and what aspects of dissociation they are particularly sensitive to. Also, with the exception of the MID, none of these instruments contain validity scales, i.e., items with which inattentive responding or symptom exaggeration can be detected. These response sets may artificially increase dissociative symptom reports. To detect and exclude such artefacts, diagnostic assessment procedures in this domain should include symptom validity tests geared to identify over-reporting (see, for examples, Merckelbach et al., 2017).

Assessment is often an ongoing process in psychotherapy, and much information can be gleaned in the absence of standardized tests of dissociative experiences and symptoms. In this regard, a number of caveats are in order. Less formal assessment procedures that even subtly suggest a history of abuse or validate the manifestation of alters with separate histories (e.g., personality “system mapping” to establish contact with nonforthcoming alters, providing names to alters, prompting or suggesting the emergence or appearance of alters) should be avoided. A concern is that therapists who repeatedly ask leading questions such as “Is it possible that there is another part of you with whom I haven't yet spoken?” may elicit via suggestion imagined-believed-in alter personalities that ostensibly account for their clients' otherwise enigmatic behaviors (e.g., self-mutilation, and rapid and intense mood shifts). The point here is that clinicians are positioned to shape the illness beliefs of their patients in such way that misinformation about symptoms may set into motion symptom escalation (see also Merckelbach et al., 2011). Repeated questioning about historical events is not helpful, as it can lead patients to mistakenly believe that they have significant gaps (e.g., amnesia) in their autobiographical memories of childhood (Belli, Winkielman, Read, Schwartz, & Lynn, 1998; Read & Lindsay, 2000). Assessors should also eschew the use of hypnosis to recover allegedly dissociated or repressed memories given that hypnosis does not enhance the overall accuracy of memories and is associated with a heightened risk for confabulation (Lynn, Knox, Fassler, Lilienfeld, & Loftus, 2004).

Case Example

Case Identification and Presenting Complaints

The patient, a 47-year old Caucasian female, first presented with dissociative symptoms to a health professional during a routine pelvic examination (see Colletti, Lynn, & Laurence, 2010 for a more complete description). During the exam, she exhibited dramatic changes in her demeanor. In quick succession, her emotions vacillated unpredictably, from calm and composed, to scared and vulnerable, to angry and aggressive. The physician referred her for psychotherapy, insofar as her histrionic presentation was at sharp variance with what he observed during prior office visits.

History

When the patient reinstated treatment with a psychotherapist, she insisted that her problems were the product of stress at work related to serious medical concerns (e.g., lupus, peripheral neuralgia, among others) that interfered with her job performance. Nevertheless, the therapist, a graduate student at a psychological clinic, noted that her mood and behavior fluctuated dramatically both within and between sessions, with episodes of anger and anxiety flaring up frequently and unpredictably within sessions. Over the next 2 years, the patient recounted a history of sexual assault 7 years prior to treatment, the death of a sibling, intense and sometimes unstable interpersonal relationships, and sexual abuse in childhood. Emotional outbursts during sessions escalated; seemingly innocuous statements by the therapist could trigger memories of highly aversive events. The patient began to experience more frequent crises in and out of sessions as well as emotional lability, often alternating between speaking in a childlike voice and that of an angry adult, only to later apologize and express deep regret. Her memory for what transpired when she appeared to be enacting different “identities” was spotty and at times devoid of meaningful content.

After 2 years of treatment, the graduate student transferred the case to his supervisor, who witnessed increased irritability, vitriolic anger, and flashback-like experiences in sessions that were followed by amnesia, depersonalization, derealization, and problems in focusing attention. The patient reported feeling “spaced out” in session, and reported that she often was aware of “missing time” at home, and experienced difficulties recalling anything beyond the gist of the previous session. At the start of treatment with her second therapist, she met the criteria for borderline personality disorder, and DID was considered a rule-out diagnosis. She reported hearing “voices in my head” and experienced herself as “splitting off” into an angry “adult protector” or defender of others and childlike aspects of herself that required protection. One major diathesis for her dissociative symptoms appeared to be a history of fantasy versus reality-based coping originating in childhood. She became aware of this style of coping when her sister died when the patient was 5 years old, and she experienced guilt for not somehow preventing her death. She stated that she began, from that time forward, to think of herself as split into angry and protective “parts.” As therapy progressed, she reported more frequent episodes of depersonalization and disturbing episodes of amnesia, as well as disorientation at times of high stress. She also reported more incidents of abuse during childhood, and her therapist felt her presentation now met criteria for DID.

At this time, Steven Jay Lynn, one of the authors of this chapter, was invited to serve as a consultant and co-therapist. The therapists conveyed the consistent message that although at times she felt as if she housed distinct personalities, she truly embodied only one personality. The therapists implemented a multifaceted treatment that included: (a) elements of affect management and problem-solving to contend with anger; (b) cognitive-behavioral therapy (CBT techniques including activity scheduling for depressed mood, progressive muscle and hypnosis-based relaxation, and rational disputation of maladaptive thoughts); (c) mindfulness-based techniques for detaching from negative and self-deprecating cognitions and moods; and (d) affect containment methods derived from dialectical behavior therapy. After 4 years of treatment, the patient exhibited no signs of “personality split” and only occasional episodes of depersonalization, with improved functioning and mood stabilization.

Assessment

The patient met all the diagnostic criteria for DID, including her enacting distinct “identities” during sessions and reports of such alterations outside of sessions. She also reported amnesia associated with dissociative episodes, and she was troubled by her failure to recall key interpersonal interactions that others remembered well. The patient was not assessed at the outset of treatment, although when SJL came onboard, she was evaluated with the DES and scored in the clinical range (i.e., 39) and met diagnostic criteria for DID based on the SCID-D (Steinberg, 1994).

Etiological Considerations

Behavioral Genetics

Limited research is available on the behavioral genetics of dissociative disorders. The evidence indicates that DID co-aggregates within biological families (APA, 1994), although data on intact family members are indeterminate with regard to genetic versus shared environmental causation. Using twin registry data, Jang, Paris, Zweig, Frank, and Livesley (1998) reported that 48% of the variability in DES-T scores is attributable to genes, and that the other 52% of the variance can be attributed to nonshared environments. When the researchers considered nonpathological dissociation scores, excluding taxon items, genetic influences accounted for 55% of the variance, whereas nonshared environmental influences accounted for 45% of the variance. Similarly, a study of children and adolescents found a substantial genetic (59% genes, 41% nonshared environments) contribution to dissociation scores (Becker-Blease et al., 2004). In contrast, a study based on 280 identical twins and 148 fraternal twins (Waller & Ross, 1997) found no evidence of genetic influences. Approximately 45% of the variance on a measure of pathological dissociation (DES-T) was attributable to shared environmental influences, with the remaining variance due to nonshared environmental influences. A Polish study of 83 monozygotic and 65 dizygotic twins estimated the heritability of dissociativity at 62% and concluded that the propensity to dissociate is highly heritable (Domozych & Dragen, 2017). Researchers have begun to explore how traumatic experiences may interact with genetic vulnerabilities to produce dissociative symptoms; variations in the FK506 binding protein 5 gene, which is involved in the regulation of the body's stress system, are an intriguing target for this type of gene × environment research (Yaylaci, Cicchetti, Rogosch, Bulut, & Hertzel, 2017). Adoption studies would help to clarify the extent to which the familial clustering of dissociative disorders is due to genes, shared environment, or both.

Biology

Drugs, notably low doses of the anesthetic ketamine, often produce dream-like states and dissociative symptoms, suggesting that dissociative experiences need not necessarily arise in the aftermath of trauma. Krystal et al. (1994) found that ketamine produces alterations in the perception of time (i.e., slowing) and alterations in the vividness, form, and context of sensory experiences, all possibly attributable to diminished N-methyl-D-aspartate (NMDA)-related neurotransmission (Simeon, 2004). Interestingly, cannabinoids, including marijuana, which induce dissociative experiences, may similarly affect NMDA receptors (Simeon et al., 2003). The fact that hallucinogens (e.g., LSD), which frequently elicit depersonalization reactions in healthy participants, are agonists of serotonin 5-HT2A and 5-HT2C receptors, implies that serotonin also may mediate dissociation (Simeon, 2004). Research that establishes links between drugs that produce dissociative symptoms in conjunction with changes in specific neurotransmitter systems hold the potential to shed light on the neurobiological basis of these dissociative symptoms (Giesbrecht et al., 2008). For example, a recent study showed that MDMA, cannabis, and cocaine all induce acute dissociative symptoms (Van Heugten-van der Kloet et al., 2015). The pharmacological study of dissociation is important because it may shed light on the paradoxical phenomenon that detoxified opiate users exhibit higher dissociation scores than do patients who are on a methadone maintenance regimen (Somer, Altus, & Ginzburg, 2010). One possible explanation for this pattern is the chemical dissociation hypothesis, that is, the notion that substance abuse patients achieve dissociative-like states through chemicals (e.g., alcohol, opiates), and in the absence of chemicals, they feel compelled to produce the dissociative symptoms themselves (see, for a recent discussion, Wegen, van Kijke, Aalbers, & Zedlitz, in press). This line of reasoning is consistent with pilot data suggesting that the opioid-blocking drug naloxone is effective in reducing depersonalization experiences (Nuller, Morozova, Kushnir, & Hamper, 2001; but see Somer, Amos-Williams, & Stein, 2013).

Studies examining daytime EEG activity in highly dissociative individuals have generally found evidence that dissociative experiences are related to parameters signaling reduced attentional control (e.g., attenuated P300, Kirino, 2006; decreased theta activity; Krüger, Bartel, & Fletcher, 2013). Sleep EEG recordings obtained in insomnia patients found suggestive evidence that dissociative psychopathology is related to extended REM sleep (van der Kloet et al., 2013). It is tempting to relate lack of attentional control and extended REM to structural sleep disturbances, as suggested later in our discussion.

Simeon et al. (2000) used positron emission tomography (PET) and magnetic resonance imaging (MRI) of the brain to compare eight participants with DDD with 24 healthy participants. The researchers found that depersonalization is associated with functional abnormalities in sequential hierarchical areas—secondary and cross-modal—of the sensory cortex (visual, auditory, and somatosensory), as well as areas responsible for integrated body schemas. Specifically, DDD patients showed lower metabolic activity in right Brodmann areas 21 and 22 of the superior and middle temporal gyri, and higher metabolism in parietal Brodmann areas 7B and 39 and left occipital Brodmann area 19. The researchers contended that these findings are compatible with the phenomenological conceptualization of depersonalization as a dissociation of perceptions, as well as with the subjective symptoms of DDD.

In a fascinating study, Sang, Jáuregui-Renaud, Green, Bronstein, and Gresty (2006) showed that disorienting vestibular stimulation produced by caloric irrigation of the ear labyrinths engendered depersonalization in healthy participants and symptoms (e.g., feeling spaced out, body feels strange/not in control of self) similar to those experienced by patients with vestibular disease. The researchers suggested that depersonalization/derealization experiences may “occur because distorted vestibular signals mismatch with sensory input to create an incoherent frame of spatial reference which makes the patient feel that he or she is detached or separated from the world” (p. 760).

In a later study, the researchers (Jáuregui-Renaud, Sang, Gresty, Green, & Bronstein, 2008b) found that patients with peripheral vestibular disease reported a higher prevalence of depersonalization/derealization symptoms and greater errors on a body rotation test of updating spatial orientation compared with healthy comparison participants. The investigators claimed that their findings support their theory that DDD symptoms sometimes reflect a mismatch between disordered vestibular input and other sensory signals of orientation. This claim was supported in a study in which patients with vestibular disease, and patients with retinal disease reported more symptoms of depersonalization than did patients with hearing loss and healthy participants (Jáuregui-Renaud, Ramos-Toledo, Aguilar-Bolaños, Montaño-Velazquez, & Pliego-Maldonado, 2008a). Depersonalization and derealization experiences may well be the product of mismatches or lack of integration between multisensory inputs (e.g., vestibular, visual, proprioceptive) which produces dysfunctional neural representations that, in turn, generate an altered sense of self and reality (Aspell & Blanke, 2009).

Out-of-body experiences (OBEs), which are intimately related to depersonalization, are increasingly being studied in the laboratory (e.g., Ehrsson, 2007; Lenggenhager, Tadi, Metzinger, & Blanke, 2007) and are coming to be understood in terms of the scrambling of the senses (e.g., touch and vision) when people's usual experience of their physical body becomes disrupted. In addition, scientists are identifying the brain location of OBEs by stimulating the vestibular cortex, the superior temporal gyrus, and the place where the brain's right temporal and parietal lobes join (Blanke, Ortigue, Landis, & Seeck, 2002; Blanke & Thut, 2007; Cheyne & Girard, 2009; De Ridder, Van Laere, Dupont, Menovsky, & Van de Heyning, 2007; Persinger, 2001).

Ehrrson (2007) provided participants with goggles that permitted them to view a video display of themselves relayed by a camera placed behind them. This setup created the illusion that their bodies, viewed from the rear, were standing in front of them. Ehrrson touched participants with a rod on the chest while he used cameras to make it appear that the visual image was being touched at the same time. Participants reported the eerie sensation that their video double was also being touched. In short, they reported that they could experience the touch in a location outside their physical bodies (see also Aspell, Lenggenhager, & Blanke, 2009; Lenggenhager et al., 2007). When visual sensory impressions combine with physical sensations, they can deceive people into believing that their physical selves are separate from their bodies (Cheyne & Girard, 2009; Terhune, 2009), suggesting a physiological genesis of at least some depersonalization experiences. Relatedly, disruptions in somatosensory signals may explain why some people experience OBEs during sleep paralysis (Nelson, Mattingly, Lee, & Schmitt, 2006) and during general anesthesia when they retain partial awareness (Bunning & Blanke, 2005). Nevertheless, researchers have little understanding of how stressors and other precipitants of depersonalization and derealization create and maintain the symptoms of dissociative disorders.

Researchers have devoted considerable attention to describing physiological differences among alters in DID and have reported inter-identity differences in heart rates, voice pitch, eyeglass prescriptions, handedness, handwriting, allergies, or pain tolerance (see Lilienfeld & Lynn, 2015). Nevertheless, it is unclear whether such differences validate the existence of alters, as many of these differences may merely reflect differences in mood or differences stemming from the unconscious role-playing of different identities, or both. Also, some authors have pointed out that one may obtain similar intraindividual differences when healthy actors are instructed to role-play alters (Boysen & Van Bergen, 2014; Merckelbach, Devilly & Rassin, 2002a). Moreover, Allen and Movius (2000) suggested that some of these apparent differences might reflect type I errors, given the large number of psychophysiological variables analyzed in many of these studies.

Tsai, Condie, Wu, and Chang (1999) used MRI with a 47-year-old female with DID in an attempt to corroborate a history of childhood abuse. The authors drew upon previous investigations that had reported a reduction in hippocampal volume following combat trauma (e.g., Bremner, Randall, Scott, & Bronen, 1995) and early abuse (Bremner, Randall, Vermetten, & Staib, 1997; Stein, Koverola, Hanna, & Torchia, 1997) to hypothesize that DID patients—given their presumed history of early abuse—would similarly exhibit decreased hippocampal volume. As predicted, they found significant bilateral reductions in hippocampal volume in their patient with DID. Nevertheless, this finding must be interpreted cautiously for two major reasons (Lilienfeld & Lynn, 2015). First, because it is based on only one patient, its generalizability to other individuals with DID is unclear. Second, decreased hippocampal volume is not specific to PTSD or to other conditions secondary to trauma, and has also been reported in schizophrenia (Nelson, Saykin, Flashman, & Riordan, 1988) and depression (Bremner et al., 2000). Consequently, decreased hippocampal volume may be a nonspecific marker of long-term stress (Sapolsky, 2000) that is present in many psychiatric conditions.

More recent neuroimaging studies have focused on brain activation patterns during the different identity states of people with DID. For example, in one study, researchers (Reinders et al., 2014) confronted DID patients (n = 11) and matched DID-simulating healthy comparison subjects (n = 16) with autobiographic script-driven imagery while brain activation was monitored using PET. According to the authors, their results are in line with the idea that DID involves alternations between a hypoaroused identity state with overmodulation of emotional regulation that activates the prefrontal cortex, cingulate, posterior association areas, and parahippocampal gyri, and a hyperaroused identity state with undermodulated emotion regulation that activates the amygdala and insula as well as the dorsal striatum.

Learning, Modeling and Life Events

Some cases of (mis)diagnosed dissociative disorders are probably the product of malingering. Estimates suggest that malingering or other forms of feigning (e.g., the faking seen in factitious disorders) account for 2–10% of diagnoses of inpatient dissociative disorders (Friedl & Draijer, 2000). There is widespread agreement that DID can be successfully malingered. For example, Kenneth Bianchi, one of the two Hillside Strangler murderers, is widely believed to have faked DID to escape criminal responsibility (Orne, Dinges, & Orne, 1984). In one survey, experienced neuropsychologists estimated the prevalence of feigned dissociative symptoms in cases involved in litigation to be about 10% (Mittenberg, Patton, Canyock, & Condit, 2002). Nevertheless, cases of malingered DID are believed to be quite rare outside of forensic settings, and the substantial majority of individuals with this condition do not appear to be intentionally fabricating their symptoms. Malingerers strive for advantages (e.g., financial, legal), but dissociative disorders are known to be associated with functional impairments that are so severe that they qualify as serious and often debilitating mental illnesses (Mueller-Pfeiffer et al., 2012).

The Post-Traumatic versus the Sociocognitive Models of Dissociation

There is little dispute that some individuals meet the diagnostic criteria for DID, display unpredictable and sometimes bizarre shifts in mood and behavior, and are convinced that they house compartmentalized “personalities” engendered by severe early physical abuse, sexual abuse, or both. Nevertheless, over the past 25 years, controversy has swirled around the question of whether the symptoms of DID are naturally occurring responses to early trauma (Dalenberg et al., 2012; Gleaves, 1996), as the post-traumatic model (PTM) of dissociation holds, or are largely socially constructed and culturally influenced, as the sociocognitive model (SCM)—called by some the fantasy model (Dalenberg et al., 2012)—of dissociation holds (Spanos, 1994). One commentator (Paris, 2012) has gone so far as to claim that DID is a fad that is now declining in interest in the psychiatric community, whereas others have vigorously challenged this assertion (Brand, Loewenstein, & Spiegel, 2013b; Martinez-Taboas, Dorahy, Sar, Middleton, & Krüger, 2013).

Proponents of the PTM (Gleaves, 1996; Gleaves et al., 2001; Ross, 1997) argue that DID is a post-traumatic condition that arises primarily from a history of severe physical and/or sexual abuse in childhood. Advocates of the PTM contend that such abuse is a crucial contributor to DID: The child compartmentalizes the abuse so that he or she feels as though it is happening to someone else (Ross, 1997). Moreover, alters or ego states supposedly arise as a means of coping with the intense emotional pain of the trauma (see Lilienfeld & Lynn [2015], for an explanation and critique). PTM theories variously emphasize the effects of childhood abuse and early traumatic experiences on producing (a) patterns of disorganized interpersonal attachment (Liotti, 1999, 2009) that engender dissociation; (b) structural dissociation (i.e., the development of different “parts” of the personality to handle different functions in “defense” and everyday life; Steele, van der Hart, Nijenhuis, 2009); (c) disturbances in the self-system that integrates “identity-mind-body-world-time” into a coherent whole—in this view, alters are conceptualized as “younger self-systems (ego-states) that are ‘trapped’ in a past trauma” (Beere, 2009, p. 283); (d) developmental deficits that degrade self-regulation and promote fragmentation of the self (Carlson, Yates, & Sroufe, 2009); and (e) a dissociative information processing style related to feelings of being betrayed by a trusted caregiver (Barlow & Freyd, 2009; Freyd, 1996).

These diverse theories are ostensibly supported by very high rates—sometimes exceeding 90%—of reported histories of severe child abuse among patients diagnosed with DID and other severe dissociative disorders (Dalenberg et al., 2012; Gleaves, 1996). Nevertheless, critics of the PTM (see Giesbrecht et al., 2008, 2010; Lilienfeld et al., 1999; Lynn et al., 2014b; Merckelbach & Muris, 2001; Spanos, 1994, 1996) have questioned the notion that DID is invariably linked to child abuse or maltreatment for the following six reasons:

1. Many studies that purport to confirm this association lack objective corroboration of child abuse (e.g., Coons, Bowman, & Milstein, 1988). For example, Sanders and Giolas (1991) found a correlation of r = 0.44 between the DES and scores on a child-abuse questionnaire. Yet when a psychiatrist (unaware of the dissociative status of participants) provided more objective ratings of trauma based on hospital records, the authors found a nonsignificant negative correlation between ratings of traumatic experiences and dissociation (r = −0.21).

2. Correlations between dissociation and highly aversive events are highly variable, ranging between r = −0.013 (not significant) to r = 0.44 (P < 0.001) in nonclinical samples, and from r = 0.14 (not significant) to r = 0.63 in clinical samples (see Dalenberg et al., 2012; Patihis & Lynn, 2017). Additionally, 40% of the correlations have been below 0.30 (Dalenberg et al., 2012). Consistent substantive moderators of these marked correlational differences have yet to be identified (although see no. 6 for a potential methodological moderator). Briere et al. (2005) found in their heterogeneous sample of N > 1300 participants that the percentage of unique dissociation variance accounted for by trauma exposure was only 4.4%, with an effect size (d) of approximately 0.41. The authors concluded that “trauma exposure may be only a relatively small aspect in the genesis of dissociative responses” (Briere et al., 2005, p. 229).

3. The overwhelming majority of studies investigating the link between self-reported trauma and dissociation are based on cross-sectional designs that do not permit causal inferences (Merckelbach & Muris, 2001) and that are subject to retrospective biases. Prospective studies that circumvent the pitfalls of retrospective reporting often fail to substantiate a consistent link between childhood abuse and dissociation in adulthood (Dutra, Bureau, Holmes, Lyubchik, & Lyons-Ruth, 2009; Noll, Trickett, & Putnam, 2003; Ogawa, Sroufe, Weinfield, Carlson, & Egeland, 1997; but see Bremner, 2010; Dalenberg et al., 2012).

4. Researchers rarely control for potentially comorbid psychopathological syndromes and symptoms known to be related to dissociative disorders (e.g., anxiety/obsessive-compulsive, eating, personality disorders, impulsivity, schizotypal traits; see Giesbrecht et al., 2008; Lynn et al., 2014b; Soffer-Dudek, 2014).

5. The reported high levels of child abuse among DID patients may be attributable to selection and referral biases common in psychiatric samples. For example, patients who are abused are more likely than other patients to enter treatment (Pope & Hudson, 1995).

6. Correlations between abuse and psychopathology tend to decrease substantially or disappear when (a) participants' perception of family pathology is controlled statistically (Nash, Hulsey, Sexton, Harralson, & Lambert, 1993) and (b) measures of trauma and dissociation are administered in separate test contexts, suggesting that the trauma-dissociation link may be, in part, an artifact of the way trauma and dissociation are measured (Lemons & Lynn, 2016). Based on these six points of contention, Lilienfeld and Lynn (2015) noted that the available evidence provides little or no warrant for concluding that abuse is a necessary causal antecedent of DID (see also Lynn et al., 2014b), although it may be one nonspecific influence among many others in the causal matrix. In contrast to the PTM, proponents of the SCM (Spanos, 1994, 1996; see also Aldridge-Morris, 1989; Lilienfeld et al., 1999; 2014; Lynn & Pintar, 1997; McHugh, 1993; Merskey, 1992; Sarbin, 1995) contend that DID results from inadvertent therapist cueing (e.g., suggestive questioning regarding the existence of possible alters, hypnosis, sodium amytal), a tendency to fantasize and suggestibility (see a more extended discussion below in the context of cognitive mechanisms), media influences (e.g., television and film portrayals of DID, such as Sybil), and broader sociocultural expectations regarding the presumed clinical features of DID.

Advocates of the SCM cite the following findings (Lilienfeld et al., 1999; Lilienfeld & Lynn, 2015) as consistent with the SCM or as challenges to the PTM:

1. The number of patients with DID, along with the number of alters per DID individual, have increased dramatically over the past few decades (Elzinga, van Dyck, & Spinhoven, 1998; North et al., 1993), although the number of alters at the time of initial diagnosis appears to have remained constant (Ross, Norton, & Wozney et al., 1989).

2. The massive increase in reported cases of DID followed closely upon the release of the best-selling book Sybil (Schreiber, 1973) in the mid-1970s, which told the story of a young woman with 16 personalities who reported a history of severe child abuse at the hands of her mother. As noted earlier, in 1976, this book was turned into a widely viewed television film starring Sally Fields. Interestingly, however, a well-known psychiatrist who was involved closely with the Sybil case later contended that Sybil's presentation of DID was largely or entirely the product of therapeutic suggestion. Herbert Spiegel, who served as a backup therapist for Sybil, maintained that Sybil's primary therapist, Cornelia Wilbur, frequently encouraged her to develop and display different personalities in therapy. According to Rieber (2006), who possessed tapes of conversations between Sybil and Cornelia Wilbur, Spiegel referred to Sybil as a “brilliant hysteric,” with multiple identities fabricated to please the all too credulous Wilbur. Spiegel further maintained that Cornelia Wilbur and Flora Schreiber, who authored the best-selling book about Sybil, insisted that Sybil be described in the book as a “multiple” to make the book more appealing (Acocella, 1999). Rieber concluded “the three women—Wilbur, Schreiber, and Sybil—are responsible for shaping the modern myth of multiple personality disorder” (Rieber, 2006, p. 109). In short, increases in the diagnosis of DID and the number of alters per DID patient coincide with dramatically increased therapist and public awareness of the major features of DID (Fahy, 1988).

3. Mainstream treatment techniques for DID often reinforce patients' displays of multiplicity (e.g., asking questions like, “Is there another part of you with whom I have not spoken?”), reify alters as distinct personalities (e.g., therapists calling different alters by different names, mapping their “personality systems”), and encourage patients to establish contact and dialogue with presumed latent alters (Spanos, 1994, 1996). A case in point is the N = 1 within-subject study by Kohlenberg (1973), who showed that the behavioral displays of alter personalities can depend on reinforcement contingencies: The patient's alters soon “disappeared” after hospital staff stopped attending to them.

4. Many or most DID patients show few or no clear-cut signs of this condition (e.g., alters) prior to psychotherapy (Kluft, 1984)

5. The number of alters per DID individual tends to increase substantially over the course of DID-oriented psychotherapy (Piper, 1997), and there are indications that this type of therapy might exacerbate symptoms (Fetkewicz, Sharma, & Merskey, 2000).

6. Therapists who use hypnosis tend to have more DID patients in their caseloads than do psychotherapists who do not use hypnosis (Powell & Gee, 1999).

7. The majority of diagnoses of DID derive from a relatively small number of psychotherapists, many of whom are specialists in DID (Mai, 1995), and from a relatively small number of people in treatment (Boysen, 2011; Boysen & Van Bergen, 2013; but see Brand, Loewenstein, & Spiegel, 2013b; Brand et al., 2016 for a rebuttal).

8. Laboratory studies suggest that nonclinical participants who are provided with appropriate cues and prompts can reproduce many of the overt features of DID (Spanos, Weekes, & Bertrand, 1985; Stafford & Lynn, 2002).

9. Until 20 years ago, diagnoses of DID were limited largely to North America, where the condition has received widespread media publicity (Spanos, 1996), although DID is now being diagnosed with considerable frequency in some countries (e.g., the Netherlands) in which it has become more widely publicized since the 1990s. Manifestations of DID symptoms also vary across cultures. For example, in India, the transition period during which the individual shifts between alter personalities is typically preceded by sleep, a presentation that reflects common media portrayals of DID in India (North et al., 1993). There are indications that both research interest in DID and media coverage of the condition are waning, and so it will be interesting to see whether this change heralds a drop in prevalence rates (Pope, Barry, Bodkin & Hudson, 2006).

10. Laboratory research summarized in the following discussion challenges the assertion that consciousness can be separated into multiple streams by amnesic barriers to form independently functioning alter personalities (Huntjens, Verschuere, & McNally, 2012; Kong, Allen, & Glisky, 2008; Lynn et al., 2004).

These 10 sources of evidence do not imply that DID can typically be created in vacuo by iatrogenic (therapist-induced) or sociocultural influences. SCM theorists acknowledge that iatrogenic and sociocultural influences typically operate on a backdrop of pre-existing psychopathology, and exert their impact primarily on individuals who are seeking a causal explanation for their instability, identity problems, and impulsive and seemingly inexplicable behaviors. Indeed, the SCM is entirely consistent with findings, reviewed earlier, that many or most patients with DID meet criteria for borderline personality disorder, a condition marked by extremely labile behaviors. Still, many of the tenets of the SCM have been vigorously challenged by advocates of the trauma-dissociation perspective (e.g., Brand et al., 2016; Dalenberg et al., 2012, 2014; Gleaves, 1996), ensuring that theoretical tensions are unlikely to abate in the foreseeable future.

Cognitive Mechanisms of Dissociation

Despite subjective reports of profound cognitive disturbances like amnesia, feelings of unreality, and identity alterations, researchers have found evidence for only relatively subtle and specific cognitive deficits in highly dissociative individuals. Such individuals usually fall within the normative range on tests of intellectual ability and standard neuropsychological tests (Giesbrecht et al. 2008; Schurle, Ray, Bruce, Arnett, & Carlson, 2007). Indeed, whereas most studies, with few exceptions (but see Prohl, Resch, Parzer, & Brunner, 2001), fail to report any link between dissociation and working memory capacity, some report that dissociative individuals exhibit superior verbal working memory capacity or verbal memory performance (Giesbrecht et al., 2008; McKinnon et al., 2016).

When cognitive deficits in dissociative patients are identified, they tend to be quite specific. For example, Guralnik, Schmeidler, and Simeon (2000) found that DDD patients exhibited deficits in visual perception and visual-spatial reasoning for both two- and three-dimensional stimuli. Patients' visual and verbal short-term memory capacity was also compromised, for both abstract and meaningful information, especially under information overload conditions. DDD participants experienced difficulty with early stimulus-encoding tasks under conditions of heightened distraction, to which they responded with more omission errors. Accordingly, DDD appears to be characterized by vulnerability in early information processing at the level of perception and attention (for replications, see Guralnik, Giesbrecht, Knutelska, Sirroff, & Simeon, 2007; Quaedflieg et al., 2012).

Simeon, Hwu, and Knutelska (2007) found evidence for a relation between the dissociative symptoms of DDD patients, temporal disintegration (i.e., problems in memory regarding the chronology and dating of events), and total DES scores. They concluded that the dissociative dimension of absorption is a significant predictor of temporal disintegration.

The relative absence of a measurable general neuropsychological deficit in the dissociative disorders is noteworthy, as it differentiates them from most other severe psychiatric disorders, such as schizophrenia and bipolar disorder. These other conditions overlap with the dissociative disorders, but unlike them, are marked by a wide range of neuropsychological deficits (Heinrichs & Zakzanis, 1998). In addition, different dissociative disorders appear related to different cognitive deficiencies. DID is characterized mainly by performance fluctuations (e.g., increased scatter on the Wechsler Adult Intelligence Scale [Wechsler, 1981]; Rossini, Schwartz, & Braun, 1996; reduced P300 amplitudes, but only during acute dissociative episodes in DID patients; Kirino, 2006), whereas DDD is associated with disruptions in early stages of information processing (Guralnik et al., 2000). Nevertheless, few investigations have controlled for general distress and psychopathology, or for scores on openness to experience, which is moderately associated with both dissociative tendencies (Kihlstrom, Glisky, & Angiulo, 1994) and with crystallized intelligence (DeYoung, Peterson, & Higgins, 2005). Interestingly, as we have noted earlier, dissociative individuals sometimes exhibit a performance advantage relative to nondissociative individuals (e.g., Chiu, Yeh, Huang, Wu, & Chiu, 2009), such as the ability to shift attention (Chiu et al., 2016b).

Some of the literature on cognitive mechanisms of dissociation is arguably more consistent with the SCM than with the PTM. As already noted, proponents of the PTM typically argue that individuals who undergo horrific trauma in early life often dissociate or compartmentalize their personalities into discrete alters, segregated by amnesic barriers, as a means of coping with the intense emotional pain of the trauma. However, studies of amnesia among patients with DID have generally not reported findings commensurate with the existence of true amnesia among so-called alter personalities (Giesbrecht et al., 2010). For example, researchers have found little or no evidence for inter-identity amnesia using objective measures (e.g., behavioral tasks or event-related potentials) of memory (e.g., Allen & Movius, 2000; Huntjens et al., 2006, 2012; Huntjens, Peters, Woertman, van der Hart, & Postma, 2007; Kong et al., 2008).

If dissociative symptoms attenuate the impact of traumatic events, individuals with heightened levels of dissociation should exhibit slower or impaired processing of threat-related information. Nevertheless, patients with DID and other “high dissociators” display better memory for to-be-forgotten sexual words in directed forgetting tasks (Elzinga, de Beurs, Sergeant, Van Dyck, & Phaf, 2000; see also Cloitre, Cancienne, Brodsky, Dulit, & Perry, 1996), a finding strikingly discrepant with the presumed defensive function of dissociation. Research on nonclinical samples (e.g., Candel, Merckelbach, & Kuijpers, 2003) showing that dissociation is not associated with inferior memory performance has been replicated in patients with DDD (Montagne et al., 2007). Studies of cognitive inhibition in high dissociative clinical (Dorahy, Irwin, & Middleton, 2002; Dorahy, Middleton, & Irwin, 2005; Dorahy, McCusker, Loewenstein, Colbert, & Mulholland, 2006) and nonclinical (Giesbrecht, Merckelbach, & Smeets, 2006) samples typically find a breakdown in such inhibition, which stands in sharp contrast with the widespread idea that amnesia (i.e., extreme inhibitory effect on memory) is a core feature of dissociation (Anderson et al., 2004). Research also finds mixed support at best for the contention that highly dissociative individuals are superior to low dissociators in dividing their attention. In two samples, Devilly et al. (2007) failed to replicate DePrince and Freyd's (2001) findings of superior forgetting of trauma-related words in high- versus low-dissociator college students in a divided attention task (see also Giesbrecht & Merckelbach, 2009). Giesbrecht et al. (2010) contended that the findings we have reviewed challenge the widespread assumption that dissociation is related to avoidant information processing and suggested that apparent gaps in memory in inter-identity amnesia, or dissociative amnesia more generally, could reflect intentional failures to report (McNally, 2003; Pope et al., 2006).

Giesbrecht and colleagues (Giesbrecht et al., 2008, 2010) further argued that dissociation is marked by a propensity toward pseudomemories, possibly mediated by heightened levels of suggestibility, fantasy proneness, and cognitive failures. They noted that at least 10 studies from diverse laboratories have confirmed a link between dissociation and fantasy proneness (Giesbrecht, Merckelbach, Kater, & Sluis, 2007c), and that heightened levels of fantasy proneness are associated with both the tendency to over-report autobiographical memories (Merckelbach, Muris, Horselenberg, & Stougie, 2000a) and the false recall of aversive memory material (Giesbrecht, Geraerts, & Merckelbach, 2007a).These authors contended that the relation between dissociation and fantasy proneness may explain why individuals with high levels of dissociation are more prone than other individuals to develop false memories of emotional childhood events (e.g., a severe animal attack; Porter, Birt, Yuille, & Lehman, 2000), and further pointed to data revealing links between hypnotizability, dissociative symptoms (Frischholz, Lipman, Braun, & Sachs, 1992), and high scores on the Gudjonsson Suggestibility Scale (GSS; Gudjonsson, 1984; Merckelbach, Muris, Rassin, & Horselenberg, 2000b; Wofradt & Meyer, 1998). Similarly, some researchers have shown that dissociation increases the risk of commission (e.g., confabulations/false positives, problems discriminating perception from vivid imagery, errors in response to misleading questions) rather than omission memory errors; the latter type of error is presumably associated with dissociative amnesia (Giesbrecht et al., 2008; Holmes et al., 2005). Nevertheless, findings pertinent to the relation between trait dissociation and false memory susceptibility are often mixed and not invariably strong in magnitude (see Dalenberg et al., 2012; Lynn et al., 2014b).

Taken together with research demonstrating a consistent link between dissociation and cognitive failures (Merckelbach, Horselenberg, & Schmidt, 2002b; Merckelbach, Muris, & Rassin, 1999; Wright & Osborne, 2005) and the tendency to over-report eccentric or rare symptoms of any kind (Merckelbach, Boskovic, Pesy, Dalsklev, & Lynn, 2017), the aforementioned findings point to a heightened risk of inaccurate reporting, confabulation, and possibly pseudomemories, which raise questions regarding the accuracy of retrospective reports of traumatic experiences. In addition, these findings limit the inferences that we can draw from studies that rely exclusively on self-reports to establish a connection between trauma and dissociation (Merckelbach & Jelicic, 2004; Merckelbach et al., 2000a). Still, these findings do not exclude some role for trauma in the genesis of dissociation and dissociative disorders. Suggestibility, cognitive failures, and fantasy proneness might contribute to an overestimation of a genuine, although perhaps weak or modest, link between dissociation and trauma. Alternatively, early trauma might predispose individuals to develop high levels of fantasy proneness (Lynn, Rhue, & Green, 1988), absorption (Tellegen & Atkinson, 1974), or related traits. In turn, such traits may render individuals susceptible to the iatrogenic and cultural influences posited by the SCM, thereby increasing the likelihood that they will develop DID following exposure to these influences. This and even more sophisticated etiological models of DID have yet to be subjected to direct empirical tests. In the next section, we examine a theory that provides a possible basis of rapprochement between the PTM and the SCM.

Sleep, Memory, and Dissociation: Possibilities for Theoretical Integration

A theory originally formulated by Watson (2001) linking sleep, memory failure, and dissociation may provide a conceptual bridge between the PTM and the SCM. In a review of 19 studies, van der Kloet, Merckelbach, Giesbrecht, and Lynn (2012) concluded that the extant research provides strong support for a link between dissociative experiences and a labile sleep–wake cycle that is evident across a range of phenomena, including waking dreams, nightmares, and hypnagogic (occurring while falling asleep) and hypnopompic (occurring after falling sleep) hallucinations. Studies that offered evidence for a link between dissociative experiences and sleep disturbances relied on clinical and nonclinical samples, and, with only one exception, yielded correlations in the range of 0.30–0.55, suggesting that unusual sleep experiences and dissociation are discriminable yet related constructs. Moreover, researchers (Giesbrecht, Smeets, Leppink, Jelicic, & Merckelbach, 2007d) have shown that sleep loss induced in the laboratory intensifies dissociative symptoms (see also van Heugten-van der Kloet, Giesbrecht, & Merckelbach, 2015), suggesting a possible causal link between sleep experiences and dissociation.

These findings suggest an intriguing interpretation of the link between dissociative symptoms and deviant sleep phenomena (see also Watson, 2001). Individuals with a labile sleep–wake cycle—perhaps associated with a genetic propensity or perhaps a byproduct of intrusions of trauma-related memories—experience intrusions of sleep phenomena (e.g., dream-like experiences) into waking consciousness, which in turn foster fantasy proneness, depersonalization, derealization, and a tendency to hyperassociate in response to emotional stimuli (Lynn et al., 2015; van Heugten-van der Kloet, Merckelbach, & Lynn, 2013). Researchers (Lynn et al., 2015; Van Heugten-van der Kloet, Cosgrave, Merckelbach, Haines, Golodetz, & Lynn, 2015) have hypothesized that the tendency to hyperassociate is a key feature of the sleep–dissociaton link and may account for rapid shifts in mental set that render it difficult for dissociative individuals to maintain a coherent sense of self and to recall autobiographical memories (Chiu, Lin, Yeh, Hwu, 2011; Chiu et. al., 2016b). Not only do dream-like experiences infiltrate everyday consciousness, but Soffer-Dudek (2017) hypothesized that daytime experiences of arousal may penetrate sleep states and engender unusual nocturnal experiences (e.g., sleep paralysis) that disturb sleep and produce difficulties in maintaining focus in response to distracting stimuli in the daytime (Soffer-Dudek, 2014). Disruptions of the sleep–wake cycle thus degrade memory (Hairston & Knight, 2004) and attentional control (Williamson, Feyer, Mattick, Friswell, & Finlay-Brown, 2001), which may account for, or contribute to, the attention deficits and cognitive failures evidenced by highly dissociative individuals (Giesbrecht, Merckelbach, Geraerts, & Smeets, 2004) and dissociative patients (Dorahy et al., 2006; Guralnik et al., 2007).

Accordingly, the sleep–dissociation perspective may explain both (a) how highly aversive events disrupt the sleep cycle and increase vulnerability to dissociative symptoms, and (b) why dissociation, trauma, fantasy proneness, and cognitive failures overlap. Thus, the sleep–dissociation perspective is commensurate with the possibility that trauma mediated by sleep disturbances plays a pivotal role in the genesis of dissociation, and suggests that previously competing theoretical perspectives may be amenable to integration. The SCM holds that patients become convinced they possess separate indwelling identities as a byproduct of suggestive media, sociocultural, and psychotherapeutic influences. These patients' sensitivity to suggestive influences may arise from their propensity to fantasize, memory errors, increased salience of negative memories, and difficulties in distinguishing fantasy and reality brought about by disruptions in the sleep cycle.

Signs of Theoretical Convergence

Signs are emerging of a modicum of convergence or rapprochement between competing theoretical perspectives. On the one hand, adherents of the PTM (Dalenberg et al., 2012) acknowledge that (a) “DID is a disorder of self-understanding” (p. 568) and that “those with DID have the inaccurate idea that they are more than one person” (p. 568); (b) the potential effects of trauma on dissociation are difficult to completely parcel out from harms caused by a pathogenic family environment; (c) biological vulnerabilities, psychiatric history, social support, and prenatal factors probably contribute to the genesis of dissociation; and (d) fantasy proneness may lead to inaccurate trauma reports. On the other hand, proponents of the SCM (Lynn et al., 2014b) currently acknowledge that (a) trauma may play a nonspecific role in dissociation (e.g., by increasing stress levels); (b) laboratory support for the link between false memories and dissociation is mixed and not consistently impressive in magnitude; (c) traumatic events may produce the subjective sense of memory fragmentation, although objective indications of fragmentation are largely absent (Crespo & Fernández-Lansac, 2016); and (d) therapeutic approaches to treat dissociation may be helpful, although the mechanisms by which improvement occurs have yet to be delineated and isolated from nonspecific effects of psychotherapy in the context of randomized clinical trials. The fact that divergent perspectives concur that multiple causal antecedents, and not merely early trauma, need to be considered to provide a comprehensive account of dissociation and dissociative disorders is a welcome development.

Treatment

Depersonalization and Derealization

The available research evidence provides few guidelines for the treatment of dissociative disorders. Pharmacological treatments have proven to be of little help in improving symptoms of DDD or other dissociative disorders (Somer, Amos-Williams, & Stein, 2013). For example, only a small proportion of people with DDD exhibit a clinically meaningful or even partial response to selective serotonin reuptake inhibitors or benzodiazepines. Although stimulant medications may improve concentration in individuals with DDD, they have little effect on the core symptoms of depersonalization (Simeon, et al., 1997, 2003). Moreover, the symptoms of depersonalization are no more responsive to fluoxetine (Simeon, Guralnik, Schmeidler, & Knutelska, 2004) or lamotrigine (Sierra, Phillips, Krystal, & David, 2003) than they are to a placebo. According to Simeon (2009b), the well-documented lack of response to anxiolytics or mood stabilizers among DDD patients suggests that this condition cannot be reduced to a mood or anxiety spectrum disorder, “despite being often triggered by, or co-occurring with, the latter” (p. 439). Nevertheless, the fact that treatment response differs across disorders does not necessarily preclude commonalities in etiology.

The literature on psychotherapy with patients with DDD is similarly scant. An open study conducted by Hunter, Baker, Phillips, Sierra, and David (2005) examined the effects of CBT in DDD. The investigators taught patients to interpret their symptoms in a nonthreatening way. Although there were dramatic improvements in the patient sample, and follow-up results were on the whole promising, the results must be interpreted with caution given the absence of a randomized control group. More rigorous trials are needed to confirm the merits of CBT and other psychotherapeutic approaches in patients with DDD. Recent studies on the beneficial effects of behavioral interventions on DDD symptoms that accompany anxiety disorders (e.g., social anxiety) indicate that this is a promising area of research (e.g., Schweden et al., 2016; see also Cathey & Zettle, 2016).

Dissociative Identity Disorder

Individuals with DID typically are in treatment for an average of 6–7 years before being diagnosed with this condition (Gleaves, 1996). Advocates of the PTM see this finding as evidence that individuals with DID are underdiagnosed, whereas advocates of the SCM see it as evidence that patients who are later diagnosed with DID typically enter treatment with few or no symptoms of the disorder. The treatment outcome literature for DID is sparse. According to Brand, Classen, McNary, and Zaveri (2009a), only eight studies have examined treatment outcomes for DID and other dissociative disorders. Brand's research team (Brand et al., 2009b) reported a naturalistic study of DID and DD-NOS treatment by community clinicians and recently reported promising 30-month treatment and follow-up findings (Brand et al., 2013c). Nevertheless, there are no randomized controlled trials on DID. Furthermore, studies do not permit an evaluation of the extent to which symptom reduction in dissociative patients is due to regression to the mean, the passage of time, placebo effects, or other artifacts that are unrelated to the treatment (see Lilienfeld, Ritschel, Lynn, Cautin, & Latzman, 2014). Other methodological problems include variability in treatments offered to patients (e.g., Choe & Kluft, 1995), lack of controls for nonspecific effects (e.g., Ellason & Ross, 1997), dropout rates as high as 68% (Gantt & Tinnin, 2007), and the failure to evaluate purported mediators of treatment gains and consistently document clinically meaningful changes following treatment (Maxwell, Merckelbach, Lilienfeld, & Lynn, 2018). As a consequence, one cannot draw confident conclusions regarding treatment efficacy from the extant literature.

Importantly, some literature suggests that patients treated with commonly used DID interventions that involve identifying alters, addressing “parts,” and recovering memories deteriorate significantly over the course of treatment (see Brand, Loewenstein, & Spiegel, 2014; Brand et al., 2016 for a contrary perspective). In one study, the majority of patients developed “florid posttraumatic stress disorder during treatment” (Dell & Eisenhower, 1990, p. 361). Moreover, after treatment commences, patients have reported increased suicide attempts (Fetkewicz et al., 2000), hallucinations, severe dysphoria, and chronic crises (Piper & Merskey, 2004). Nevertheless, Brand and Loewenstein (2014; see also Brand, Loewenstein, & Spiegel, 2014) contended that their analysis of treatment outcomes indicates that DID treatment, including interacting with “dissociated self-states,” improves clinical outcomes, particularly when treatment guidelines are followed, and that depriving DID patients of treatment may cause “iatrogenic harm.” Studies that compare negative sequelae across DID and conventional therapies are a clear priority.

Assuming that future studies establish that certain sleep deviations serve as causal antecedents of dissociative symptoms, it will be imperative to examine the effects of treatment interventions focused on sleep normalization in dissociative patients (Hamner, Broderick, & Labbate, 2001; Merckelbach & Giesbrecht, 2006). Previous studies that have explored the effectiveness of sleep medication in PTSD (Van Liempt, Vermetten, Geuze, & Westenberg, 2006), DID (Loewenstein, Hornstein, & Farber, 1988), and sleep hygiene protocols to reduce dissociative symptoms in a mixed inpatient group (van der Kloet, Giesbrecht, Lynn, Merckelbach, & de Zutter, 2012) and in a college sample (van der Kloet, Giesbrecht, Merckelbach, & Soontiens, 2015) have yielded promising results.

Dissociative symptoms and sleep disturbances overlap with alexithymia (“no words for feelings”), an impairment in the ability to accurately evaluate internal states and experiences (Bauermann, Parker, & Tayler, 2008; Merckelbach et al., 2017). Such impairment may contribute to a highly labile symptom presentation, as a lack of accurate evaluation of internal states may exacerbate both difficulties regulating emotions (Brady, Bujarski, Feldner, & Pyne, 2017) and the tendency of dissociative individuals to switch from one attentional set to another (Chiu et al., 2009). Because alexithymia may be reduced by interventions that encourage recognition and verbalization of feelings, which may also be promising in treating dissociative symptoms (Korzekwa, Dell, & Pain, 2009; Ogrodniczuk, Sochting, Piper, & Joyce, 2012), addressing alexityhmia may play a more prominent role in treating dissociation in the future (Maxwell et al., 2018).

Conclusion

Dissociative disorders and conditions, especially DID and dissociative fugue, are among the most controversial in all of descriptive psychopathology, and for good reason. Although dissociation is unquestionably a genuine subjective experience, serious questions remain concerning the assessment, etiology, and treatment of most dissociative disorders. Etiological issues are a particular sticking point, and appear no closer to resolution with the publication of DSM-5. Although some authors (e.g., Dalenberg et al., 2012; Gleaves, 1996) maintain that DID and perhaps other dissociative disorders stem primarily from early child abuse and maltreatment, others (e.g., Spanos, 1994) maintain that these conditions are largely socially and culturally influenced products that are aided and abetted by therapist prompting and cueing of symptoms—a view that is supported by multiple sources of circumstantial evidence (Lilienfeld et al., 1999). It remains to be seen whether new and promising models, such as those linking sleep deprivation to dissociative symptoms (van der Kloet et al., 2012), may provide common ground between these competing theories of the genesis of dissociative disorders. Scant controversy exists surrounding the idea that people diagnosed with dissociative disorders experience genuine psychological distress. Yet clinicians who work with dissociative patients should bear in mind the powerful historical lesson imparted by the literature on DID: In their well-meaning efforts to unearth psychopathology, assessors and therapists may inadvertently end up creating it (Lilienfeld et al., 1999).

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Chapter 14 Feeding and Eating Disorders

Cynthia M. Bulik, Lauren Breithaupt, Zeynep Yilmaz, Rachel W. Gow, Sara E. Trace, Susan C. Kleiman, and Suzanne E. Mazzeo

Description of the Disorders

Eating disorders represent a category of partially overlapping syndromes, all of which have some clinical features marked by eating dysregulation. We will focus our discussion on anorexia nervosa (AN), bulimia nervosa (BN), and binge-eating disorder (BED), which represent the primary eating disorders listed in DSM-5. Feeding disorders, such as pica, rumination disorder, and avoidant/restrictive food intake disorder—all more common in, but not exclusive to, children—will not be covered in this chapter. Eating disorders are serious mental illnesses that are influenced by both genetic and environmental factors. The syndromes are partially overlapping, as considerable diagnostic flux occurs over time, with individuals migrating from one clinical presentation to another, and because several diagnostic features are shared across disorders. Nonetheless, pure forms of each of the presentations also exist.

Clinical Picture

Anorexia nervosa, the most visible eating disorder, is a serious psychiatric illness characterized by an inability to maintain a normal healthy body weight or, in individuals who are still growing, failure to make expected increases in weight (and often height) and bone density. Despite increasing weight loss and frank emaciation, individuals with AN strive for additional weight loss, see themselves as fat even when they are severely underweight, and often engage in unhealthy weight-loss behaviors (e.g., purging, dieting, excessive exercise, and fasting).

Anorexia nervosa is characterized by low weight; however, the definition of "low weight" is somewhat complicated. DSM-5 highlights restriction of energy intake relative to requirements, leading to a significantly low body weight, and embeds that in the context of the individual's age, sex, developmental trajectory, and physical health. Even when at low weight, people with AN experience an intense fear of gaining weight or of becoming fat, or they engage in persistent behavior that interferes with weight gain. The behavior and cognitions of individuals with AN vigorously defend low body weight. Other aspects of the diagnostic criteria include a three-part criterion, of which only one component is necessary: disturbance in the way in which one's body weight or shape is experienced, undue influence of body weight or shape on self-evaluation, or persistent lack of recognition of the seriousness of the current low body weight.

In the past, amenorrhea of 3 months' or longer duration was a diagnostic criterion for AN. Wisely, this has been eliminated, as there are no meaningful differences between individuals with AN who do and do not menstruate (Gendall et al., 2006; Watson & Andersen, 2003). Although not diagnostic, cessation of menstruation can be a useful indicator of severity, and resumption of menses is a factor in determining recovery. AN presents either as the restricting subtype, in which low weight is achieved and maintained through energy restriction and increased physical activity only, or as the binge-eating/purging subtype, in which the individual has been regularly engaging in binge-eating or purging behavior (i.e., self-induced vomiting or the misuse of laxatives, diuretics, or enemas) over the past 3 months.

Bulimia nervosa is characterized by recurrent binge-eating episodes, defined as eating an unusually large amount of food in a short period of time (∼2 hours) while experiencing a sense of loss of control over the eating episode. In addition, bulimia includes recurrent inappropriate compensatory behaviors (e.g., self-induced vomiting, laxative, diuretic, or other medication misuse, fasting, or excessive exercise). In individuals with BN, self-evaluation is unduly influenced by body shape and weight. Binge eating and compensatory episodes occur on average once a week for at least 3 months. BN is only diagnosed if AN criteria are not met. Thus, to be diagnosed with BN, individuals should have a body mass index (BMI) greater than 18.5 kg/m2 in adults (i.e., the lower bound of normal weight according to the World Health Organization [WHO, 1992] and the Centers for Disease Control).

Bulimia nervosa onset most frequently occurs in adolescence or early adulthood, although it can occur at any point across the life span (American Psychiatric Association [APA], 2013). BN can also occur at any body weight (with the exception of the requirement to diagnose AN binge-eating/purging type if criteria for AN are met). BN tends to be over-represented in women; however, it has been argued that BN diagnostic criteria are gender-biased, leading to under-detection in men. Men who seek treatment for BN tend to manifest a greater reliance on nonpurging forms of compensatory behavior, such as excessive exercise (Anderson & Bulik, 2004; Lewinsohn, Seeley, Moerk, & Striegel-Moore, 2002). It is important to consider such gender differences in the clinical presentation of BN to revise prevalence estimates of this diagnosis (Anderson & Bulik, 2004).

In DSM-5, BED received recognition as a stand-alone disorder after years of being categorized as a disorder “worthy of further study.” Binge eating was first noted in a subset of obese individuals by Stunkard (1959). BED has had a slow and controversial evolution in the psychiatric nosology for eating disorders (Fairburn, Welch, & Hay, 1993; Spitzer et al., 1993; Walsh, 1992).

Binge-eating disorder is marked by recurrent binge eating (at least weekly for 3 months, as in BN) and a sense of lack of control over eating during the episode, but in the absence of regular compensatory behaviors. Unlike BN, the diagnostic criteria for BED include descriptions of the binge experience. To meet criteria, an individual must experience distress regarding the binge eating as well as at least three of the following: eating much more rapidly than normal, eating until feeling uncomfortably full, eating large amounts of food when not feeling physically hungry, eating alone because of feeling embarrassed by how much one is eating, or feeling disgusted with oneself, depressed, or very guilty afterward. It remains a curiosity as to why these descriptors remained in the BED criteria when they are not in the BN criteria; presumably, this was related to ensuring that individuals who simply overeat were not misdiagnosed as having BED. BED can occur at any body weight and is only diagnosed if neither AN nor BN criteria are met.

Other specified feeding or eating disorder (OSFED) is a new category in DSM-5, which replaces the historical eating disorder not otherwise specified (EDNOS). The reorganization in DSM-5 occurred in part because BED became a stand-alone diagnosis and in part because, historically, far too many individuals with eating disorders received a diagnosis of EDNOS, rendering it the most frequently diagnosed eating disorder. This alerted many researchers and clinicians to the fact that the diagnostic system was in need of revision so that a greater number of individuals could be captured under the hallmark categories of AN, BN, and BED. OSFED applies to presentations with symptoms characteristic of a feeding and eating disorder, but full diagnostic criteria are not met. Research suggests that these changes to the diagnostic schema yield fewer residual diagnoses. More specifically, applying DSM-5 diagnostic criteria, in comparison to DSM-IV criteria, increased diagnoses of AN by 3–7% (Brownley, Peat, La Via, & Bulik, 2015; Yilmaz, Hardaway, & Bulik, 2015; Yilmaz et al., 2014), BN by 0–4.5% (Mancuso et al., 2015; Vo, Accurso, Goldschmidt, & Le Grange, 2016), with ∼3–13% meeting BED criteria (Austin et al., 2011; Brandys et al., 2013; Grilo et al., 2012; Mancuso et al., 2015). In parallel, DSM 5 criteria reduced residual diagnoses (OSFED and UFED) by 8.6–28% (Mancuso et al., 2015; Thomas et al., 2015; Vo et al., 2016). Additional research is needed to clarify further whether DSM-5 criteria affect eating disorder treatment.

Other specified feeding or eating disorder includes a useful category of atypical AN, in which an individual meets all criteria for AN except that his/her weight falls within or above the normal weight range. This would capture, for example, an individual who was obese who precipitously lost a large amount of weight and exhibited all of the psychological features of AN, but, because of the weight at which the weight loss started, still fell within the normal weight range. Other presentations under OSFED include BN and BED of low frequency or limited duration, purging disorder (i.e., purging behavior in the absence of binge eating), and night eating syndrome, in which individuals report recurrent episodes of night eating, marked by eating after awakening from sleep or by excessive food consumption after the evening meal.

Based on previous research with EDNOS, it is not expected that individuals diagnosed with OSFED category have less serious symptomatology. The severity of pathology and psychosocial impairment is comparable among individuals with EDNOS, AN, and BN (Fairburn & Bohn, 2005; Keel, Gravener, Joiner, & Haedt, 2010). Clinical descriptions of EDNOS are consistent in stating that most cases have features similar to AN and BN (Crow, Agras, Halmi, Mitchell, & Kraemer, 2002; Waller, 1993; Walsh & Garner, 1997). Three studies (Fairburn & Cooper, 2007; Ricca et al., 2001; Turner & Bryant-Waugh, 2004) using the Eating Disorder Examination (EDE; Cooper & Fairburn, 1987) found that individuals with EDNOS presented with significant cognitive symptomatology related to eating, shape, and weight, suggesting that these syndromes are clinically significant. A recent study applying DSM-5 criteria found residual eating disorders (OSFED and UFED) are also clinically significant (Wu et al., 2016).

Diagnostic Considerations

With the publication of DSM-5 in 2013, investigation of the validity of the new classification system is an important research focus. Some advances of the DSM-5 system include attention to stages of illness. In the past, for example, if someone had met criteria for AN and then began to recover, she or he might have received a new diagnosis of EDNOS. In DSM-5, there is now the option to include the specifier of “in partial remission” if, after having met full criteria, weight has normalized but the psychological features remain, and “full remission” if, after having met full criteria, no criteria have been met for a sustained period of time. In addition, severity specifiers also exist, and are currently based on BMI, with mild AN being ≥17 kg/m2, moderate 16–16.99 kg/m2, severe 15–15.99 kg/m2, and extreme <15 kg/m2.

In addition to the core diagnostic features, individuals with AN often manifest a specific cluster of personality traits, including perfectionism, obsessionality, anxiety, harm avoidance, and low self-esteem (Cassin & von Ranson, 2005; Fassino, Amianto, Gramaglia, Facchini, & Abbate Daga, 2004; Klump et al., 2000). Furthermore, both these personality characteristics and anxiety disorders often precede AN onset (Bulik, Sullivan, Fear, & Joyce, 1997; Kaye, Bulik, Thornton, Barbarich, & Masters, 2004). Major depression and anxiety disorders frequently co-occur with AN (Bulik et al., 1997; Fernandez-Aranda et al., 2007; Godart, Flament, Perdereau, & Jeammet, 2002; Godart, Flament, Lecrubier, & Jeammet, 2000; Kaye et al., 2004), and longitudinal research suggests that depression often persists following recovery from AN (Sullivan, Bulik, Fear, & Pickering, 1998).

Some personality features common among individuals with AN are also manifested by many women with BN, such as high harm avoidance, perfectionism, and low self-esteem. However, other personality features appear more specific to BN, including elevated novelty-seeking and impulsivity, low self-directedness, and low cooperativeness (Bulik, Sullivan, Joyce, & Carter, 1995; Fassino et al., 2004; Steiger et al., 2004). Further refinements of the components of impulsivity suggest that negative urgency, or the tendency to act rashly when distressed, is the facet of impulsivity most strongly associated with bulimia (Fischer, Smith, & Cyders, 2008).

Comorbid psychiatric disorders are very common among individuals with BN, occurring among nearly 80% of patients (Fichter & Quadflieg, 1997). These comorbidities include anxiety disorders, major depression, dysthymia, substance use, and personality disorders (Braun et al., 1994; Brewerton et al., 1995; Bulik et al., 2004; Perez, Joiner, & Lewinsohn, 2004).

Finally, BED also commonly co-occurs with numerous other psychiatric diagnoses, including mood, anxiety, and substance abuse disorders (Grucza, Przybeck, & Cloninger, 2007; Johnson, Spitzer, & Williams, 2001; Marcus, 1995; Striegel-Moore et al., 2001; Wilfley, Friedman, et al., 2000). Data from the National Comorbidity Survey Replication (Hudson, Hiripi, Pope Jr, & Kessler, 2007) indicate that BED is a chronic condition associated with significant impairment in daily functioning. Global data from the World Health Organization World Mental Health Surveys indicate that BED and BN are associated with significantly increased education in women. Early-onset BED predicted reduced odds of marriage in women and reduced odds of employment in men, while early-onset BN predicted increased odds of current work disability in both sexes. Both BED and BN were associated with significantly increased days of role impairment, although much of the role impairment was accounted for by the presence of comorbid disorders (Kessler et al., 2013).

Finally, those individuals with BED who are overweight or obese are at risk for medical complications (Hudson et al., 2007). Yet, the negative psychological impact of BED does not appear to be attributable to obesity. Obese individuals with BED report substantially poorer psychological functioning than do obese individuals without BED (Grucza et al., 2007), and normal-weight and overweight individuals with BED report equivalent psychological features of disordered eating and depression (Dingemans & van Furth, 2012).

Epidemiology

Most available epidemiologic data on eating disorders reflect DSM-IV diagnostic criteria; data based on the DSM-5 are slowly emerging. Thus, in this review, DSM-5 data are included where possible. Lifetime prevalence estimates of DSM-5 AN, BN, and BED by over age 20 are 0.8–1.7%, 0.08–2.6%, 2.3–3% in women (Brandys et al., 2012, 2013), and 0.1%, 0.1%, and 0.7% in men, respectively (Smink, Hoeken, Oldehinkel, & Hoek, 2014). The prevalence of subthreshold AN, defined as at least one criterion short of threshold, is greater and ranges from 0.37% to 1.3% (Hoek, 1991); DSM-5's atypical AN is 2.8% (Brandys et al., 2013). The gender ratio (women:men) for AN is approximately 9:1 (Association, 1994). Awareness of these disorders has increased; however, the data on changing incidence are conflicting. Some studies report increasing incidence of AN or increases in disordered eating behavior (such as strict dieting or fasting for weight or shape control) that are associated with AN (e.g., Eagles, Johnston, Hunter, Lobban, & Millar, 1995; Hay, Mond, Buttner, & Darby, 2008; Jones, Fox, Babigian, & Hutton, 1980; Lucas, Crowson, O'Fallon, & Melton, 1999; Møller-Madsen & Nystrup, 1992), whereas others describe stable prevalence (e.g., Currin, Schmidt, Treasure, & Jick, 2005; Hall & Hay, 1991; Hoek, 2006; Hoek et al., 1995; Pawluck & Gorey, 1998; Smink, van Hoeken, & Hoek, 2012). The peak age of onset for AN is between 15 and 19 years (Lucas, Beard, O'Fallon, & Kurland, 1988), However, reports suggest new-onset cases in mid-life and late life (Beck, Casper, & Andersen, 1996; Gagne et al., 2012; Inagaki et al., 2002; Mangweth-Matzek et al., 2006). A recent study of middle age women estimated lifetime eating disorder prevalence as 3.64% for AN, 2.15% for BN, and 1.96% for BED (Shea et al., 2012). Reports also suggest increasing presentations in children (Rosen, 2010).

The prevalence of BN in the United States is estimated to be 1.5% for women and 0.5% for men (Hudson et al., 2007). The prevalence of subthreshold behaviors is considerably higher, with 4.9% of women and 4% of men endorsing any binge eating. Similar to AN, reports suggest that more children and older adults are presenting with BN (Marcus, Bromberger, Wei, Brown, & Kravitz, 2007; Rosen, 2010).

The prevalence of BED among adults (>18 years) in the United States based on DSM-5 criteria has been estimated at 3.6% for women and 2.1% for men (Duncan et al., 2016; Hudson et al., 2007) while community surveys across 12 countries estimate the lifetime prevalence across both genders at 1.9% (Kessler et al., 2013). In a population-based study of female twins, 37% of obese women (BMI ≥ 30) reported binge eating (Bulik, Sullivan, & Kendler, 2002), 2.7% of the female population studied. Community studies of obese individuals have found a prevalence of BED of between 5% and 8% (Bruce & Agras, 1992; Bruce & Wilfley, 1996). The sex distribution in BED is more equal than in AN or BN (Duncan et al., 2016; Hudson et al., 2007), with few differences in prevalence across races or ethnic groups (Alegria et al., 2007; Marcus et al., 2007).

Psychological and Biological Assessment

Careful and accurate assessment of eating disorders, which are frequently complex and have multiple presentations, is critical for effective treatment and research. The general goal of psychological assessment is to elicit information that accurately describes symptomatology, accurately characterizes diagnostic profile, and indicates appropriate treatment recommendations (Peterson, 2005). Assessing individuals with eating disorders is often challenging secondary to denial of the illness and hidden signs and symptoms (Palmer, 2003; Schacter, 1999; Túry, Güleç, & Kohls, 2010; Vitousek, Daly, & Heiser, 1991). The use of active listening skills is important for developing rapport (Keel, 2001), and motivational interviewing techniques (Miller & Rollnick, 2002), which encourage rolling with resistance, avoiding arguments, and expressing empathy, are often helpful for conducting a successful assessment.

Clinical interviews in eating disorders are used to elicit the patient's perspective of the development of his or her difficulties and frequently include the reason for the assessment/primary complaint, history of present illness, medical complications, treatment history, and coexisting conditions (Peterson, 2005). A combination of structured interviews, self-report measures, and medical assessments might also be employed to obtain a more complete clinical picture. In the case of minors, corroborating information, such as reports from parents or school officials, is additionally informative (Lock, LeGrange, Agras, & Dare, 2001).

Structured Interviews

Structured interviews are essential for clarifying differential diagnostic issues and assessing psychiatric comorbidity. Structured interviews are advantageous in that they allow for active involvement of the interviewer, who can help to clarify concepts or answer questions that may arise during the assessment. Obvious drawbacks to structured interviews include greater financial cost and clinician burden (Grilo, 2005).

For untrained interviewers, the two dominant instruments for assessing Axis I pathology are the Diagnostic Interview Schedule (DIS; Robins, Helzer, Croughan, & Ratcliff, 1981) and the Composite International Diagnostic Interview (CIDI; Organization, 1992). However, these have not been updated for DSM-5 (Culbert, Racine, & Klump, 2015). The various versions of the Structured Clinical Interview for DSM-IV (SCID; First, Spitzer, Gibbon, & Williams, 1997) and DSM-5 (Frank, Shott, Riederer, & Pryor, 2016) have excellent validity and reliability (Grilo, 2005; Zanarini et al., 2000) and are recommended for assessing Axis I pathology in adults by trained interviewers.

To assess eating disorder symptomatology specifically, several clinician-based structured or semistructured interviews have been developed. The EDE (Cooper & Fairburn, 1987) is well established (Wilfley, Schwartz, Spurrell, & Fairburn, 2000) and widely used. It has been updated for DSM-5 (EDE-17.0;Frank, 2015) and includes 33 items that measure behavioral and psychological traits in AN and BN. With the exception of the diagnostic items, the EDE focuses on the 28 days preceding the assessment. Items are rated on a seven-point scale, with higher scores indicating greater pathology, and comprise the following scales: dietary restraint, eating concern, weight concern, and shape concern. The EDE has high interrater reliability (Cooper & Fairburn, 1987; Grilo, Masheb, Lozano-Blanco, & Barry, 2004; Rizvi, Peterson, Crow, & Agras, 2000), adequate internal consistency (Beumont, Kopec-Schrader, Talbot, & Touyz, 1993; Cooper, Cooper, & Fairburn, 1989), and good discriminative validity for distinguishing those with eating disorders from healthy individuals (Cooper et al., 1989; Wilson & Smith, 1989). The updated version (EDE-17.0; Frank, 2015) includes the same items as in previous versions; however, there are no skip logic rules, which helps to capture subthreshold features (Hardaway, Crowley, Bulik, & Kash, 2015). Other popular structured interviews for assessing disordered eating include the Interview for Diagnosis of Eating Disorders (IDED; Williamson, 1990) and the Structured Interview for Anorexic and Bulimic Disorders (SIAB-EX; Fichter, Herpertz, Quadflieg, & Herpertz-Dahlmann, 1998). However, these have not been updated for DSM-5 criteria. The Eating Disorders Assessment for DSM-5 (EDA-5; Fonville, Giampietro, Williams, Simmons, & Tchanturia, 2014) is a new semistructured interview developed to assess DSM-5 feeding and eating disorders (Fonville et al., 2014). For a full review of these and other structured interviews in eating disorders, see Grilo (2005).

The IDED-IV (Kutlesic, Williamson, Gleaves, Barbin, & Murphy-Eberenz, 1998) is another semistructured interview primarily used for differential diagnosis of DSM-IV AN, BN, and EDNOS. The IDED-IV differs from the EDE in that it does not focus on frequency and severity data, but rather on differential diagnosis. Four studies support the psychometric properties of this instrument (Kutlesic et al., 1998).

The current version of the SIAB-EX (Fichter et al., 1998) assesses specific criteria for AN and BN (including subtypes), consistent with both the DSM-IV and the ICD-10. There is also an algorithm that allows the data to be used to generate the BED research diagnosis and other eating disorder syndromes under the EDNOS category. The SIAB-EX has demonstrated good internal consistency, factor structure, interrater reliability, and convergent and discriminant construct validity (Fichter & Quadflieg, 2000, 2001). Overall, the EDE and the SIAB-EX have been shown to produce generally similar findings. However, areas of divergence do exist, many of which could be attributable to the differences in criteria and time frames for assessment (Fichter & Quadflieg, 2001).

The EDA-5 (Fonville et al., 2014) is a recently developed semistructured interview that assesses for all DSM-5 feeding and eating disorder diagnoses. Strengths of the EDA-5 include its brief administration time (approximately 15 minutes), web-based application, allowing for greater access and portability, and less intensive training required to administer as the application calculates BMI, enforces skip rules, and generates diagnoses (Sysko et al., 2015). However, the limitations of skip rules might inadvertently underestimate symptoms (Culbert et al., 2015). Initial validity and reliability for DSM-5 eating disorder diagnoses (AN, BN, and BED) were supported; however, additional psychometric data are needed (Sysko et al., 2015; Thomas & Roberto, 2015).

Self-Reports

Many self-report measures are available for assessing disordered eating in both research and clinical settings. Self-report assessments can be used for a variety of purposes, including identifying clinical features, quantifying symptoms, and verifying diagnoses. They are particularly useful for assessing change over time and are time- and cost-effective because they can be completed independently by the patient (Peterson & Mitchell, 2005). Two of the most widely used self-report questionnaires for assessing disordered eating include the Eating Disorder Inventory (EDI) and the Eating Disorder Examination–Questionnaire (EDE-Q).

The EDI (Garner, Olmsted, & Polivy, 1983, 1984), which assesses eating disorder symptoms and associated psychological traits, is useful for differentiating levels of eating disorder severity and for assessing treatment outcome (Williamson, Anderson, Jackman, & Jackson, 1995). This assessment is described by the authors as “investigator-based,” emphasizing that it is the investigator's job to make final judgments about what symptoms and behaviors are present (e.g., to determine what constitutes a binge). The EDI has 64 questions answered on a six-point scale and comprises the following eight subscales: drive for thinness, bulimia, body dissatisfaction, ineffectiveness, perfectionism, interpersonal distress, interoceptive awareness, and maturity fears. A revised version of the EDI, the EDI-2, was published in 1991 and includes 27 additional questions. The eight scales from the EDI were retained, and three additional scales—asceticism, impulse regulation, and social insecurity—were incorporated (Garner, 1991).

The third version of the scale, EDI-3 (Garner, 2004), retained the same items as the EDI-2 but has a slightly different factor structure (Garner, Olmsted, & Polivy, 2008). It contains 91 items rated on a 0–4 point scoring system. The three subscales assessing eating pathology added in the EDI-2 (drive for thinness, bulimia, and body dissatisfaction) remain largely unchanged, and the general psychology subscales include low self-esteem, personal alienation, interpersonal insecurity, interpersonal alienation, interoceptive deficits, emotional dysregulation, perfectionism, asceticism, and maturity fears. Scoring for the EDI-3 includes six composite scores – (1) eating disorder risk, (2) ineffectiveness, (3) interpersonal problems, (4) affective problems, (5) over-control, and (6) general psychological maladjustment – as well as infrequency and negative impression scores. The EDI-3 has yielded reliable and valid scores (Garner, 2004). The EDE-Q (Fairburn & Beglin, 1994), another widely used self-report measure of eating disorder symptoms, assesses severity of eating pathology and associated disturbances over the past 28 days. It is most often used in research, but it can be applied in clinical settings as well (Peterson & Mitchell, 2005). The EDE-Q was adapted from the structured interview EDE (Cooper & Fairburn, 1987), and, like the EDE, it consists of 33 items and four subscales (restraint, eating concern, shape concern, and weight concern). The subscales and total scores are based on averages from 0 to 6, with higher scores indicating greater pathology. The EDE-Q has been described as an accurate method for assessing binge eating (Wilson, Nonas, & Rosenblum, 1993) and shows acceptable reliability and validity (Fairburn & Cooper, 1993).

There are numerous other self-report assessments for eating disorders, including the Multiaxial Assessment of Eating Disorder Symptoms (MAEDS; Anderson, Williamson, Duchmann, Gleaves, & Barbin, 1999), the Stirling Eating Disorder Scales (SEDS; Williams et al., 1994), the Anorexia Nervosa Inventory for Self-Rating (ANIS; Fichter & Keeser, 1980), the Three Factor Eating Questionnaire (TFEQ; Stunkard & Messick, 1985), the Binge Eating Scale (BES; Gormally, Black, Daston, & Rardin, 1982), and the Questionnaire for Eating and Weight Patterns-Revised (QEWP-R; Yanovski, 1993). A full review of these and other self-report measures for assessing disordered eating can be found in Peterson and Mitchell (2005) or Túry et al. (2010).

Medical Assessment

Careful medical assessment, both initially and as indicated throughout the duration of eating disorder treatment, is critical for effective treatment (Crow, 2005). It is also important for emergency medicine physicians to be able to screen for and recognize patients with eating disorders, and to be aware of their medical complications and psychiatric comorbidities, in order to carry out a successful therapeutic intervention (Mascolo, Trent, Colwell, & Mehler, 2012; Trent, Moreira, Colwell, & Mehler, 2013). Documentation of medical complications is imperative, not only for treatment planning but also for service authorization by insurance companies. Although all eating disorder presentations require medical monitoring, low-weight patients, individuals with purging behaviors, and obese individuals with binge-eating behavior (or a combination of these behaviors) are typically at greatest risk for medical complications (e.g., Crow, Salisbury, Crosby, & Mitchell, 1997; Harris & Barraclough, 1998; Kohn, Golden, & Shenker, 1998).

Low-weight individuals are particularly vulnerable to medical morbidity and mortality (Harris & Barraclough, 1998). A BMI < 13 is associated with less favorable outcome (Hebebrand et al., 1997), and low weight is associated with increased likelihood of sudden cardiac death. AN, BN, and EDNOS are all associated with increased mortality (Crow et al., 2009). Evidence of medical complications might also encourage otherwise resistant patients to enter treatment. A standard initial assessment for low-weight individuals should include a complete blood count, an electrolyte battery (including phosphorus, calcium, and magnesium), an electrocardiogram, liver function tests, and a dual-energy X-ray absorptiometry (DEXA) scan (Crow, 2005). Blood pressure and pulse should also be documented, as dehydration can lead to orthostatic hypotension. The patient should be monitored carefully through the re-feeding process, because provision of adequate calories may lead to a drop in serum phosphorus, which is associated with mortality (Kohn et al., 1998) in both hospital (Ornstein, Golden, Jacobson, & Shenker, 2003) and outpatient settings (Winston & Wells, 2002).

Electrolyte disturbance is the most commonly recognized complication of purging behaviors (Crow et al., 1997). Although not sensitive to vomiting frequency, hypokalemia is a marker of vomiting behavior (Crow et al., 1997). Another common complication of self-induced vomiting is parotid hypertrophy, or painless swelling of the parotid glands, which may persist for months following cessation of purging (Ogren, Huerter, Pearson, Antonson, & Moore, 1987). Dental complications, including dental enamel erosion on the lingual surfaces of teeth (Little, 2002), may occur in individuals who vomit frequently, and thus continued dental monitoring is important. A smaller number of individuals with purging behaviors report gastrointestinal symptoms, including intestinal bleeding, hematemesis (vomiting blood), the passing of melanotic stools, or blood in the stools. Although rare, esophageal tears, gastric erosions, hemorrhoids, and gastric rupture may also occur (Cuellar, Kaye, Hsu, & Van Thiel, 1988; Cuellar & Van Thiel, 1986). Abuse of laxatives and emetics are also associated with significant medical morbidity. The use of syrup of Ipecac should signal a medical and cardiac evaluation, as it is associated with severe cardiac effects.

Binge-eating disorder, which is among the most common of eating disorder presentations, is often associated with co-occurring conditions (Crow, 2005), including type II diabetes mellitus and obesity. There is some evidence to suggest that obese individuals with type II diabetes mellitus who also binge-eat experience worse outcomes than their non-binge-eating peers (Goodwin, Hoven, & Spitzer, 2003; Mannucci et al., 2002). Binge eating appears to be associated with medical problems independent of obesity (Bulik et al., 2002). Moreover, BED may confer a risk of developing metabolic syndrome (a cluster of related risk factors for atherosclerotic cardiovascular disease, including abdominal obesity, dyslipidemia, hypertension, and abnormal glucose metabolism) beyond the risk attributable to obesity alone (Hudson et al., 2010). It is critical to remember that not all individuals with BED are overweight or obese. We await further data on the health impact of BED in normal-weight individuals.

The growing interest in eating disorders over the past 20 years has resulted in the development of numerous assessment tools for research and clinical purposes. Accurate assessment of individuals with disordered eating requires a multidisciplinary approach to address both the psychological and biological factors underlying etiology.

Etiological Considerations

Although numerous psychological, social, and biological factors have been implicated as potential causes of eating disorders, few specific risk factors have been consistently identified across studies, and the etiology of these disorders is not fully understood (Jacobi, Hayward, de Zwaan, Kraemer, & Agras, 2004; Striegel-Moore & Bulik, 2007). Common risk factors across eating disorders include female sex, race, or ethnicity, childhood eating and gastrointestinal problems, elevated concerns about shape and weight, negative self-evaluation, prior history of sexual abuse and other adverse events, and presence of additional psychiatric diagnoses (Jacobi et al., 2004). Developmentally, prematurity, smallness for gestational age, and cephalohematoma have been identified as possible risk factors for AN (Cnattingius et al., 1999).

Current studies suggest that eating disorders are caused by a variety of factors, including both genetic (e.g., Bulik, Slof-Op't Landt, van Furth, & Sullivan, 2007; Trace, Baker, Peas-Lled, & Bulik, 2013) and environmental influences (e.g., Becker & Hamburg, 1996; Garner & Garfinkel, 1980; Striegel-Moore & Bulik, 2007). Contemporary understanding of eating disorders incorporates both genetic and environmental factors into causal models. Previously, an overemphasis on sociocultural factors ignored the fact that, although social pressures toward thinness are ubiquitous, only a fraction of individuals exposed to these factors develop eating disorders. Therefore, a clearer understanding of vulnerability has led to the model that individuals who are more genetically predisposed to eating disorders are those who are also more vulnerable to environmental triggers of illness—typically ones that result in dieting, drive for thinness, and persistent negative energy balance.

Environmental influences that might serve as eating disorder triggers include the media's idealization of the thin body ideal and pressure to achieve an unrealistically thin body type (Irving, 1990; Levine & Harrison, 2004). Sociocultural models of disordered eating (e.g., Polivy & Herman, 1985; Striegel-Moore, Silberstein, & Rodin, 1986) suggest that the perception of a discrepancy between the self and the thin ideal leads to psychological discomfort. In turn, a desire to ameliorate this discomfort might result in eating-disordered behavior. Striegel-Moore and Bulik (2007) report that cultural models of eating disorders are supported by the following: (a) the high percentage of female cases of disordered eating; (b) the increase in incidence of eating disorders in women coinciding with the decreasing body-weight ideal for women; (c) the reported higher incidence of eating disorders in cultures that emphasize thinness; and (d) the significant association between thin ideal internalization and disordered eating. Fairburn et al. (1998) found significant differences in exposure to risk factors between women with BED and healthy controls, but surprisingly few differences between women with BED and BN. Specifically, compared with controls, women with BED reported more adverse childhood experiences, parental depression, personal vulnerability to depression, and exposure to negative comments about weight, shape, and eating.

Other studies have indicated that environmental factors, including parental and peer behaviors, contribute to both risk and protection from eating pathology (Enten & Golan, 2009; Twamley & Davis, 1999). For example, Twamley and Davis reported that low family pressures to control weight moderated the relation between exposure to thin norms and internalization of these messages. In addition, other environmental variables, including social pressure, could amplify or mitigate the risk of eating disorders (Striegel-Moore et al., 1986). For example, individuals exposed to peer teasing might be more likely to develop disordered eating (Thompson, Coovert, Richards, Johnson, & Cattarin, 1995; Thompson & Heinberg, 1993). Similarly, individuals from higher social classes might be more prone to develop disordered eating, as they presumably have more time, attention, and resources available to focus on the achievement of cultural beauty ideals (Striegel-Moore & Bulik, 2007). Although these factors might influence eating disorder etiology, they are likely not solely responsible for their development (Striegel-Moore & Bulik, 2007). Personality traits such as perfectionism, as well as social anxiety, elevated weight, and high impulsivity, might also play important etiological roles. These sociocultural and environmental factors likely combine with genetic influences (Strober, Freeman, Lampert, Diamond, & Kaye, 2000) to contribute to the development of disordered eating, as is described in the next section.

Behavioral Genetics and Molecular Genetics

The conceptualization of eating disorders has evolved rather radically across time (Vemuri & Steiner, 2007). Previously dominant sociocultural and psychodynamic theories have been supplanted by a biopsychosocial model. This evolution can be attributed in part to a systematic series of family twin and molecular genetics investigations of eating disorders, which have supported the role of familial and genetic factors in liability to eating disorders (Bulik et al., 2006; Klump, Miller, Keel, McGue, & Iacono, 2001). In this section, we review results of family, twin, and molecular genetic studies (for a more thorough review, see Trace et al., 2013).

Family studies investigate the degree to which a particular trait runs in families. Although they are a valuable tool, family studies cannot tell us why a trait runs in families—whether due to genetic factors, environmental factors, or some combination of both. The familial nature of AN is well established. For example, first-degree relatives of patients with AN (parents, children, and siblings) are 11 times more likely to have AN during their lifetime than are first-degree relatives of individuals who have never had AN (Strober et al., 2000). Population-based twin studies have provided additional support for the familiarity of AN.

Twin studies allow us to examine familial components of disordered eating by comparing similarities and differences in eating problems between monozygotic (MZ) and dizygotic (DZ) twins. MZ twins are generally assumed to share 100% of their genetic material, whereas DZ twins, on average, share 50% of their genetic material (like brothers and sisters). Variance in liability to a disorder can be dissected into additive genetic factors, shared environmental factors, and unique environmental factors. Additive genetic factors refer to the cumulative effects of many genes, each of which makes a small to moderate contribution. Shared environmental factors reflect environmental influences that affect both members of a twin pair and are believed to make twins more similar. Unique environmental factors (including measurement error), on the other hand, reflect environmental factors that only one twin is exposed to. Unique environmental factors are believed to make twins dissimilar. Twin studies have yielded heritability estimates between 28% and 74% for AN, with the remaining variability largely attributed to unique environmental factors (Bulik et al., 2006; Klump et al., 2001; Kortegaard, Hoerder, Joergensen, Gillberg, & Kyvik, 2001). Although twin studies can reveal the proportion of individual differences in a disorder that are due to genetic factors, they are unable to identify which specific genes are involved.

Molecular genetic studies have the potential to provide greater clarity regarding which genes influence risk for a trait or disorder. Association studies examine a genetic variant's association with a trait; if the variant and trait are correlated, there is said to be an association between the two. Association studies that involve a single gene or set of genes that have a hypothesized association with the trait under study are referred to as candidate gene studies. Molecular genetic designs that do not focus on one particular gene or set of genes include linkage and genome-wide association studies (GWAS). Linkage studies identify chromosomal regions that house predisposing or protective genes and allow us to narrow the search from the entire human genome to specific regions. GWAS examine millions of genetic markers scattered across the genome, comparing cases with the trait against controls. If a genetic variant is significantly more frequent in cases, the variant is said to be associated with the trait. GWAS represent an agnostic search of the human genome and, as such, is a genetic discovery tool.

Decades of candidate gene association studies for AN have primarily examined genes involved in the serotonergic, catecholaminergic, and dopaminergic systems and those affecting appetite and weight regulation. The practice of preselecting a single gene based on presumed biological involvement has fallen out of favor, and has given way to genome-wide approaches (described next). More detailed information on candidate gene association studies in AN and other eating disorders can be found elsewhere (Yilmaz et al., 2015).

Historically, using candidate gene approaches, serotonergic, dopaminergic, and neurotrophic system genes received significant attention, and results regarding its importance to eating disorders are inconclusive. For instance, meta-analyses of studies investigating 5-HTTLPR—a 43 base-pair repeat polymorphism in the promoter region of SLC6A4–and AN have yielded conflicting findings for the potential involvement of that short allele in AN risk (Calati, De Ronchi, Bellini, & Serretti, 2011; Solmi et al., 2016). In a similar fashion, meta-analyses of studies examining brain-derived neurotrophic factor (BDNF) and catechol-O-methyl transferase (COMT) also failed to confirm the associations reported by previous studies with small sample sizes (Brandys et al., 2012, 2013).

Linkage studies identified chromosomes 1, 4, 11, 13, and 15 as possible regions of interest in AN (Bacanu et al., 2005; Devlin et al., 2002; Grice et al., 2002). A follow-up study of candidate genes on chromosome 1 revealed associations with the serotonergic (5-HTR1D) and opioidergic (OPRD1) neurotransmitter system (Bergen et al., 2003). Chromosome 1 was also implicated in AN in a small genome-wide microsatellite study (Kazuhiko et al., 2009), but these finding have yet to be replicated. The first GWAS for AN was conducted by Wang et al. (2010), in 1,033 female AN cases and 3,733 pediatric controls. However, no single nucleotide polymorphism (SNP) reached genome-wide significance, which is typical for studies with small sample sizes. A GWAS conducted under the auspices of the Wellcome Trust Case Control Consortium 3, which was also underpowered, failed to identify genome-wide significant SNPs associated with AN (Boraska et al., 2014). However, 76% of the variants prioritized for replication were in the same direction in the replication sample as the discovery sample, which is a promising sign that true genetic signals exist for AN, but larger sample sizes are required to detect them. The most recent AN GWAS was carried out under the umbrella of the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and comprised updated versions of the previous two GWAS cohorts. In a sample of 3,495 AN cases and 10,982 controls, the first genome-wide significant locus for AN was identified (Duncan et al., 2016). This locus—located on chromosome 12—is multigenic, overlapping six genes with six additional genes located nearby. Although the index SNP has not been directly associated with a phenotype or trait in the literature, some of the other variants in high linkage disequilibrium (LD) with the index SNP have previously yielded significant GWAS associations with type I diabetes, asthma, polycystic ovary syndrome, rheumatoid arthritis, and height (Duncan et al., 2016). Of note, none of the candidate genes with previous reports of significant associations with AN reached genome-wide significance, which has also been the case for other psychiatric disorders. Large global efforts are under way and projected to boost sample sizes to over 25,000 AN cases over the next few years in order to identify more genetic variants that influence risk for AN (Yilmaz et al., 2015).

Cross-disorder analyses have provided strong evidence for shared etiology among psychiatric disorders (Cross-Disorder Group of the Psychiatric Genomics, 2013; Lee et al., 2013). Through the application of LD Score Regression—a computational method which accounts for LD for each genomic variant while estimating heritability and co-heritability (Bulik-Sullivan et al., 2015)—to the PGC-ED AN GWAS data and various publicly available consortia GWAS summary statistics, statistically significant positive genetic correlations were reported between AN and psychiatric phenotypes such as neuroticisim, schizophrenia, and results from a meta-analysis across the original PGC psychiatric phenotypes (i.e., schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, and attention-deficit/hyperactivity disorder; Duncan et al., 2016). These results mean that the common variants cumulatively associated with these psychiatric phenotypes also increase risk for AN, highlighting their shared genetic architectures. In addition to psychiatric disorders, positive genetic correlations between AN and educational attainment phenotypes (i.e., years of education and college attendance) have also been reported (Duncan et al., 2016). Outside of psychiatric traits, significant negative genetic correlations have been observed for AN with metabolic phenotypes such as high BMI, obesity, and low-density lipoprotein cholesterol, while high-density lipoprotein cholesterol has yielded a positive genetic correlation with AN (Duncan et al., 2016). Taken together, these results suggest a potential role for metabolic risk factors in the etiology of AN, and if replicated, may have important implications for the reconceptualization of AN as a psychiatric disorder with considerable metabolic involvement.

Like AN, BN runs in families. First-degree relatives of individuals with BN are four to 10 times more likely to have the disorder themselves (Lilenfeld et al., 1998). In studies of female twins, the estimated heritability of BN ranges between 54% and 83% in females (see Slof-Op‘t Landt et al., 2005, for a review). As is the case in AN, molecular genetic studies of BN have generally focused on the serotonergic, dopaminergic, catecholaminergic, and appetite systems.

Several meta-analyses (Calati et al., 2011; Lee & Lin, 2010; Polsinelli, Levitan, & De Luca, 2012) have examined the association between 5-HTTLPR polymorphisms and BN, with the large majority suggesting no significant association between 5-HTTLPR polymorphisms and BN. Investigations exploring associations between other serotonin receptor genes and BN have also yielded mixed results (see Scherag, Hebebrand, & Hinney, 2010, for a review).

Studies investigating genes within the dopamine and catecholamine systems and genes involved in appetite regulation have also yielded inconsistent findings. Nisoli et al. (2007) examined the prevalence of TaqA1 polymorphisms of the ANKK1 gene (rs1800497) in individuals with eating disorders, including BN, and in controls. No significant associations were found between the A1+ allele in BN for either the A1/A1 or A1/A2 genotypes. Sporadic associations were reported by small studies for BN and the dopamine transporter gene (SLC6A3; also referred to as DAT1) (Shinohara et al., 2004), COMT (Mikołajczyk, Grzywacz, & Samochowiec, 2010), preproghrelin (Miyasaka et al., 2006) and BDNF; however, these results failed to replicate in other studies (see Yilmaz et al., 2015, for a review; Yilmaz et al., 2014).

Only one linkage study has been conducted for BN, which examined 308 multiplex families identified through a patient with BN. Significant linkage was found on chromosome 10, and another region on chromosome 14 met criteria for genome- wide-suggestive linkage (Bulik et al., 2003). No GWAS of BN have been conducted to date. In sum, results of molecular genetic studies of BN remain inconclusive and are limited by the use of small samples, which provide relatively low power.

The study of BED has burgeoned in the past decade. However, as the disorder has been operationalized more recently than AN and BN, less research on the genetics of BED has emerged. Nonetheless, extant family, twin, and molecular research largely suggests that familial and genetic factors influence risk for BED. A small number of family studies have been conducted (Fowler & Bulik, 1997; Hudson et al., 2006; Lee et al., 1999). With the exception of the Lee et al. (1999) investigation, these studies suggest that BED is familial. This has been further corroborated by twin studies. Two population-based twin studies have examined the heritability of BED (Javaras et al., 2008; Mitchell et al., 2010) and reported heritability estimates ranging from 39% to 45%.

Candidate gene association studies of binge eating and BED have focused on serotonin and dopamine neurotransmitter systems, as well as genetic variants implicated in appetite regulation and obesity. One small case–control investigation, reported an association between the long-allele of the 5-HTTLPR polymorphism and BED (Monteleone, Tortorella, Castaldo, & Maj, 2006). While these results may suggest a role of the 5-HTTLPR polymorphism in BED, they should be considered preliminary, as the study was underpowered. Several investigations have also examined the role of dopamine polymorphisms, and particularly polymorphisms of the DRD2 gene, in BED (Davis et al., 2008, 2009, 2012). Overall, studies exploring the association between BED and polymorphisms of the DRD2 gene have been inconsistent, likely due to small sample sizes and a lack of statistical power.

Genes associated with obesity have also been investigated for their potential role in BED, given the positive correlation between these conditions. MC4R (which is associated with obesity) was examined as an early candidate for BED (Branson et al., 2003), although this finding is not consistently replicated across studies (Hebebrand et al., 2004). Positive associations with SLC6A3, BDNF, and ghrelin have also been identified in BED (Davis et al., 2007; Monteleone, Tortorella, Castaldo, Di Filippo, & Maj, 2007; Monteleone et al., 2006; Shinohara et al., 2004); however, these results require confirmation and replication as there have not been any meta-analyses of genetic studies carried out in BED, and, importantly, the field awaits more comprehensive genome-wide approaches.

Neuroanatomy and Neurobiology

Neurobiological vulnerabilities contribute to eating disorder pathogenesis (Culbert et al., 2015; Kaye, 2008; Kaye, Wierenga, Bailer, Simmons, & Bischoff-Grethe, 2013; Treasure & Campbell, 1994), and brain structural and functional abnormalities are consistently found in individuals with eating disorders (Fonville et al., 2014; Frank, 2015; Frank, Bailer, Henry, Wagner, & Kaye, 2004; Kaye, Fudge, & Paulus, 2009). In addition, numerous behavioral traits associated with AN, including premorbid anxiety, obsessive behaviors, negative emotionality, impaired cognitive flexibility, increased harm avoidance and perfectionism, and altered interoceptive awareness, are hypothesized to be related to underlying abnormalities or alterations in brain structure and function (Kaye et al., 2013). Neuroimaging studies have consistently shown that the reward pathway may play a central role in ED pathophysiology (Frank, 2015; Wu et al., 2016). Frank et al. (2016) reported evidence of structural and functional differences within the energy-homeostasis and food reward-regulating circuitry of individuals with both AN and BN. Individuals with BN and AN tasted varying intensity of sucrose solutions paired with a visual stimulus while in the MRI. This paradigm allowed the researchers to look at reward circuitry patterns. They suggested that functional connectivity pattern provides a possible biological correlate that individuals with ED are able to override homeostatic signals.

Brain structural abnormalities in eating disorders have been investigated using computed tomography (CT) and magnetic resonance imaging (MRI). Functional imaging studies, including positron emission tomography (PET), single photon emission computer tomography (SPECT), and functional magnetic resonance imaging (fMRI), have also been employed to provide information about the cerebral activity of a system or receptor being studied. Improvements in technology over the last decade, particularly in neuroimaging and genetics, have greatly enhanced our ability to characterize the complex neuronal systems involved in disordered eating (Kaye, 2008; Kaye et al., 2013). However, these techniques are still relatively new, and our understanding of the relation between biological vulnerabilities and subsequent changes in brain pathways contributing to disordered eating are limited. Neurobiological investigations of disordered eating are further complicated by state-related effects from changes in diet and weight, which impact neuronal processes. One advancement in the field of neuroscience is the shift from focusing on isolated brain regions to focusing on neural circuits (Insel, 2009). Neurocircuitry is assessed using multimodal MRI to look at both structural and functional activity patterns of the brain, providing a better understanding of the molecular mechanism associated with brain function. Using longitudinal and multimodal MRI, Cha et al. (2016) studied connectivity between the nucleus accumbens and the orbitofrontal cortex (OFC), structures implicated in reward processing, using resting-state images in AN before and after weight restoration. The AN group showed an effective connectivity direction from the OFC to the nucleus accumbens, as well as greater anatomical connectivity strength using probabilistic tractography between two regions of interest (Cha et al., 2016). The findings suggest that hyperconnectivity in reward circuitry may be an important neural substrate in AN and may not fully resolve with weight restoration.

Brain imaging is not yet at a point where it can be used diagnostically; however, with the refinement of imaging hardware and improved models of the neurobiology and genetics of psychiatric illness, scientists are hopeful that in the future, imaging will allow us to untangle the complexities of eating disorders, predicting illness development, treatment response, and long-term prognosis (Frank, 2013, 2015). At present, central nervous system (CNS) dysregulation of neuropeptides (Bailer & Kaye, 2003) and monoamines (Bailer et al., 2007; Kaye, 2008), as well as brain structural abnormalities (Artmann, Grau, Adelmann, & Schleiffer, 1985; Heinz, Martinez, & Haenggeli, 1977; Joos et al., 2010; Krieg, Lauer, & Pirke, 1989), are implicated in the neurobiology of disordered eating.

Neuropeptides

Neuropeptides involve a complicated interplay between the peripheral system and the CNS (Morton, Cummings, Baskin, Barsh, & Schwartz, 2006), and opioid peptides, corticotropin-releasing hormone (CRH), vasopressin, oxytocin, neuropeptide-Y (NPY), peptide YY (PYY), cholecystokinin (CCK), leptin, ghrelin, and gastrin-releasing peptides are reported to play an important role in the regulation of feeding behavior (Akio et al., 2012; Bailer & Kaye, 2003; Monteleone, 2011). A growing body of literature documents alterations in neuropeptides in individuals with eating disorders (for a recent in-depth review, see Monteleone & Maj, 2013). Briefly, individuals with AN have state-dependent altered levels of CRH (Licinio, Wong, & Gold, 1996), NPY, beta-endorphin, and leptin that normalize with weight restoration (Bailer & Kaye, 2003; Kaye, 2008), whereas individuals with BN demonstrate state-related reductions in CCK response (Brewerton, Lydiard, Laraia, Shook, & Ballenger, 1992; Hannon-Engel, 2012; Kaye et al., 1987; Lesem, Berrettini, Kaye, & Jimerson, 1991) and beta-endorphin levels.

A number of the CNS neuropeptides implicated in AN and BN are also involved in regulating cognitive functioning, mood, the autonomic nervous system, and hormone secretion (Jimerson & Wolfe, 2006). While abnormalities in neuropeptide systems typically remit following recovery from AN and BN, malnutrition in combination with neuropeptide alterations can exaggerate symptoms of increased satiety and dysphoric mood, which might perpetuate eating-disordered behavior (see Bailer & Kaye, 2003; Monteleone & Maj, 2013 for full reviews of how neuropeptides influence AN and BN).

Neuropeptides are also implicated in BED, and both human and animal studies suggest that binge eating alters the endogenous opioid system (Bencherif et al., 2005; Blasio, Steardo, Sabino, & Cottone, 2014; Munsch, Biedert, Meyer, Herpertz, & Beglinger, 2009). Individuals with BED have higher meal-induced levels of CCK and PYY than controls (Munsch et al., 2009). Furthermore, both obese and nonobese women with binge eating demonstrate decreased levels of ghrelin in the morning, compared with nonobese healthy women and obese non-binge-eating women (Monteleone et al., 2005). However, these findings have not been consistently replicated across studies (Geliebter, Hashim, & Gluck, 2008; Munsch et al., 2009).

Monoamines

The monoamine system, including serotonin (5-HT), dopamine, and norepinephrine (NE), has also been implicated in the development and maintenance of disordered eating (Hildebrandt, Alfano, Tricamo, & Pfaff, 2010; Kaye et al., 2009; Steiger, 2004; Vaz-Leal, Rodríguez-Santos, García-Herráiz, & Ramos-Fuentes, 2011). The 5-HT system is critical in regulating appetite, anxiety, and impulse control (Fairbanks, Melega, Jorgensen, Kaplan, & McGuire, 2001), and the effects of 5-HT manipulation on eating behaviors have been demonstrated in both animal and human models (e.g., Blundell, 1986; Hardaway et al., 2015; Mancilla-Dı́az, Escartı́n-Pérez, López-Alonso, & Cruz-Morales, 2002).

Studies of individuals with eating disorders document alterations in 5-HT metabolism, receptor sensitivity, and transporter activity (Bailer et al., 2011; Frank & Kaye, 2005; Kaye, 2008). As a general trend, decreased 5-HT is associated with increased feeding (Brewerton, 1995), leading to the expectancy that AN would coincide with increased 5-HT.

At first glance, individuals with AN appear to contradict expectation with regard to levels of 5-HT. Individuals with AN have significant reductions in cerebral spinal fluid 5-hydroxyindoleacetic acid (CSF 5-HIAA) compared with controls (Kaye et al., 2009), suggesting reduced 5-HT activity. However, CSF 5-HIAA levels are elevated following long-term recovery from AN (Kaye, 2008), indicating that AN may correspond to a primary state of increased 5-HT and that diminished 5-HT activity may be a result of malnutrition, rather than a trait-related feature.

Positron emission tomography and SPECT have been used to investigate the role of the 5-HT1A and 5-HT2A receptors in AN (Bailer & Kaye, 2011). Although studies have not been entirely consistent, most have shown that both ill and weight-restored individuals with AN have reduced binding of 5-HT2A (Bailer et al., 2004; Frank et al., 2002; Kaye et al., 2001) and increased binding of 5-HT1A (Bailer et al., 2005, 2011). In an animal model, interactions between 5-HT1A and 5-HT2A in the medial prefrontal cortex have been implicated in anxiety, attention, impulsivity, and compulsive behavior (Carli, Baviera, Invernizzi, & Balducci, 2006; Krebs-Thomson & Geyer, 1998; Winstanley et al., 2003). This is an interesting finding given that these traits have been implicated in AN, and particularly AN binge-purge type (AN-BP).

Findings in acute BN are generally compatible with a low 5-HT hypothesis (decreased 5-HT promotes increased feeding). Individuals with BN demonstrate decreased CSF 5-HIAA levels (Kaye, 2008) that are inversely related to binging and purging frequency (Jimerson, Lesem, Kaye, & Brewerton, 1992), platelet binding of 5-HT uptake inhibitors, reduced availability of central transporters, and decreased neuroendocrine responses to 5-HT precursors and 5-HT agonists/partial agonists. However, similar to individuals with AN, following recovery, they have elevated levels of CSF 5-HIAA compared with controls (Kaye, 2008). Abnormalities in 5- HT have also been implicated in binge eating (Akkermann, Nordquist, Oreland, & Harro, 2010) and in the frequency of binge eating for individuals with BN (Jimerson et al., 1992; Monteleone, Brambilla, Bortolotti, Ferraro, & Maj, 1998). Decreased 5-HT responses are hypothesized to contribute to blunted satiety, which may increase propensity for binge eating (Chiodo et al., 1986).

Further support of the role of 5-HT in eating disorders is provided by studies indicating that selective serotonin reuptake inhibitors (SSRIs) are fairly efficacious in treating BN and BED (see Brownley et al., 2015, 2016 for reviews). Fluoxetine is the only Food and Drug Administration (FDA)-approved medication for the treatment of AN and BN. Vyvanse was approved by the FDA for the treatment of BED in 2015. Fewer investigations have examined the effectiveness of SSRIs in treating AN, and in the small number of available studies, results were mixed (Attia, Haiman, Walsh, & Flater, 1998; Ferguson, La Via, Crossan, & Kaye, 1999; Kaye et al., 2001; Rosenblum & Forman, 2003; Vaswani, Linda, & Ramesh, 2003; Walsh et al., 2006).

In summary, there is significant evidence to suggest an overall dysregulation of 5-HT in eating disorders (Kaye et al., 2013; Steiger, 2004), which persists following recovery. Together, these results suggest that patterns of 5-HT dysregulation might vary by eating disorder subtype, suggesting that underlying pathophysiology might differ across varying eating disorder presentations (Bailer et al., 2013; Frank, 2015; Kaye, 2008).

Dopamine is another monoamine hypothesized to contribute to disordered eating (Bailer et al., 2013; Bello & Hajnal, 2010; Frank & Kaye, 2005; Jimerson et al., 1992; Kaye, Frank, & McConaha, 1999), and it is known to be involved in the reward and motivational aspects of feeding behavior (Erlanson-Albertsson, 2005; Szczypka, Rainey, & Palmiter, 2000). Individuals in recovery from restricting-type AN (AN-R) show lower CSF levels of the dopamine metabolite homovanillic acid (HVA; Kaye et al., 1999), which is typically considered an indicator of reduced dopamine function and reduced dopamine turnover (dopamine:HVA ratio). Individuals recovered from AN-R and AN-BP also demonstrate increased binding of D2/D3 receptors in the anteroventral striatum (Bailer et al., 2013; Frank et al., 2005), including the nucleus accumbens, a brain region implicated in the response to reward stimuli (Delgado, Nystrom, Fissell, Noll, & Fiez, 2000; Montague, Hyman, & Cohen, 2004).

Individuals with BN, particularly those with high binge frequency, also have significantly lower HVA levels (Jimerson et al., 1992; Kaplan, Garfinkel, Warsh, & Brown, 1989; Kaye et al., 1990). However, Jimerson et al. (1992) found that after weight restoration and normalization of food intake, individuals who recovered from BN did not differ significantly from controls on HVA concentrations, suggesting that abnormalities in the dopamine system in BN might be state-dependent. Lastly, dopamine has also been hypothesized to play a role in BED by modulating reward pathways (Bello & Hajnal, 2010; Mathes, Brownley, Mo, & Bulik, 2009; O'Hara, Campbell, & Schmidt, 2015).

Norepinephrine transmission in the medial prefrontal cortex is also implicated in food-related motivational behavior in animal models (Ventura, Latagliata, Morrone, La Mela, & Puglisi-Allegra, 2008; Ventura, Morrone, & Puglisi-Allegra, 2007). Although few investigations have specifically examined the role of NE in disordered eating, it plays a central role in CNS modulation of energy balance, which has downstream effects on satiety, hunger, and feeding behavior (Hainer, Kabrnova, Aldhoon, Kunesova, & Wagenknecht, 2006).

Overall, the field is embracing more complex systems and pathway-driven models of disease to understand the complicated way in which monoamines and other neurotransmitters are implicated in disease etiology (Kaye, 2008; Kaye et al., 2009). Further, there is evidence to suggest that these neurotransmitter systems likely act in concert, contributing to behaviors associated with disordered eating. For example, a recent study by Bailer et al. (2013) using PET showed that an interaction between the 5-HT transporter and striatal dopamine D2/D3 receptor radioligand binding measures was associated with harm avoidant symptoms in women who had recovered from eating disorders. Based on this finding, authors hypothesize that interactions between the 5-HT and dopamine systems may contribute to eating disorder symptoms.

Structural Abnormalities

Neuroimaging studies with CT show neuroanatomical changes in individuals with AN, including cerebral atrophy and enlarged ventricles (Artmann et al., 1985; Heinz et al., 1977; Krieg et al., 1989; Lankenau, Swigar, Bhimani, Quinlan, & Luchins, 1985; Nussbaum, Shenker, Marc, & Klein, 1980; Titova, Hjorth, Schiöth, & Brooks, 2013). A 2012 systematic review by Van Den Eynde et al. (2012) reported that the eight studies they included found reduced gray matter volume in AN in the insula, frontal operculum, and occipital, medial temporal, or cingulate cortex. MRI studies in AN also demonstrate increased volumes of CSF in association with deficits in both total gray matter and total white matter volumes (Castro-Fornieles et al., 2010; Joos et al., 2010; Katzman et al., 1996; Titova et al., 2013) and enlarged ventricles (Golden et al., 1996). There is much debate over whether these changes persist after successful treatment and weight restoration. Several investigations have reported that neuroanatomical changes persist following normalization of weight (Artmann et al., 1985; Krieg et al., 1989), whereas other studies have found that brain tissue may increase with weight restoration in AN (Roberto et al., 2011) and that structural brain abnormalities are reversible after long-term recovery (Golden et al., 1996; Wagner et al., 2006) but not short-term recovery (Friederich et al., 2012). A 2015 study used a more sensitive measure of cortical thickness, surface-based morphometry (Hogstrom, Westlye, Walhovd, & Fjell, 2013), and found that the cortical thinning and decreased subcortical volume in AN are largely state-dependent and due to malnutrition (King et al., 2015). Although definitive conclusions cannot be drawn, if lasting brain abnormalities in AN do occur, they might represent residual damage to the brain or persistent abnormal metabolism (Husain et al., 1992). They could also represent under-developed areas that originally contributed to the eating pathology (Artmann et al., 1985).

Findings regarding structural abnormalities are mixed (Frank, 2013). Several studies support structural changes in BN, including cerebral atrophy and decreased ventricle size (Hoffman et al., 1989; Krieg et al., 1989). Other studies suggest normal or increased localized gray matter in the orbitofrontal cortex and striatum (Joos et al., 2010). A 2010 study by Schäfer, Vaitl, and Schienle (2010) found that individuals with BN had greater medial orbitofrontal cortex volume relative to controls. Further, in individuals with BN who had increased ventral striatum volumes, purging severity and BMI were correlated with striatal gray matter volume, suggesting a potential correlation between behavioral and neuroanatomical findings. Reductions in inferior frontal regions correlated inversely with symptom severity, age, and Stroop interference scores in the BN group. Marsh et al. (2015) reported significant reductions, in 34 adolescent and adult patients with BN relative to healthy controls, of local volumes on the brain surface in frontal and temporoparietal areas in the BN participants. The authors suggested that this difference could be related to deficits in self-regulation seen in BN. Other studies, however, have found no evidence for neuroanatomical abnormalities in BN (Husain et al., 1992; Joos et al., 2010). Taken together, results from these studies indicate that neuroanatomical abnormalities often occur in individuals with eating disorder, particularly AN. Additional prospective studies are needed to understand whether these abnormalities are a cause or an effect of the disordered eating behavior.

Learning, Modeling, and Life Events

As noted previously, biology only accounts for part of the liability to developing an eating disorder. It is hypothesized that environment, via channels such as learning, modeling, and life events, can contribute to eating disorder risk either directly or indirectly through their influence on genetic expression.

Life Events

Stressful life events have long been hypothesized to play an important role in eating disorder etiology (Klump, Wonderlich, Lehoux, Lilenfeld, & Bulik, 2002; Pike et al., 2006; Schmidt, Troop, & Treasure, 1999). However, research in this area is fraught with methodological challenges. Many studies have included exclusively clinical samples of individuals with eating disorder symptomatology, did not include controls, and assessed life events retrospectively (Berge, Loth, Hanson, Croll-Lampert, & Neumark-Sztainer, 2012; Degortes et al., 2014; Raffi, Rondini, Grandi, & Fava, 2000; Schmidt et al., 1999).

Nonetheless, one investigation that did include a community-recruited sample of women with BN and matched controls suggested that individuals with BN were more likely than controls to experience certain stressful life events (e.g., a major move, illness, pregnancy, physical abuse, and sexual abuse) during the year prior to the beginning of their illness (Welch, Doll, & Fairburn, 1997). There was no association between BN status and the occurrence of other life events (e.g., bereavement, illness of a close relative, friend, or partner, and beginning or ending a romantic relationship) in the last year. In addition, 29% of women with BN experienced none of the life events assessed in the 12 months prior to the onset of their diagnosis.

Adverse life events were also associated with BED risk (in the year prior to the onset of the disorder; Pike et al., 2006), in a study comparing women with BED with psychiatric and nonclinical controls. Specifically, individuals with BED were most likely to report significant changes in life circumstances and relationships during the previous year. Furthermore, compared with the nonclinical controls, women with BED more commonly reported specific adverse events, including physical abuse, perceived risk of physical abuse, safety concerns, stress, and experiences of weight- and shape-related criticism. A major limitation of both the Welch et al. (1997) and Pike et al. (2006) studies, as well as many others (e.g., Berge et al., 2012; Mitchell, Mazzeo, Schlesinger, Brewerton, & Smith, 2012; Raffi et al., 2000; Reyes-Rodríguez et al., 2011; Schmidt et al., 1999), is that they relied on participants’ retrospective recall of stressful life events, and thus are vulnerable to memory biases.

A small number of studies of community samples have used a longitudinal approach to investigate the potential role of stressful life events in the onset of disordered eating. For example, Loth, van den Berg, Eisenberg, & Neumark-Sztainer (2008) evaluated these constructs in a sample of adolescents and emerging adults enrolled in Project EAT. Respondents reported whether they had experienced a broad range of stressful events within the year prior to assessment. Participants also reported their engagement in “extreme weight control behaviors” (defined as laxative diuretic or diet pill use, and vomiting), and binge eating (assessed via a single item) at both time 1 (approximately 5 years earlier) and time 2 (when the sample had a mean age of 20.4 years).

This study is relatively unique in its inclusion of men and women. The most common stressful life event among men was “excessive credit card debt” (reported by 17.8% of men and 19.3% of women). Among women, the most commonly reported stressor was “termination of a long personal relationship” (reported by 22.9% of women and 17.2% of men). For both men and women, the number of stressful life events was positively associated with binge eating and extreme weight control behaviors. This study adds to the literature because of its longitudinal approach, use of a community sample, and inclusion of men and women. It also assessed stressors not often evaluated in other studies (and not typically considered traumas), such as financial concerns.

The relative influence of both major and minor (i.e., daily) life stressors on eating disorder symptomatology was also evaluated in a recent study of college students (Woods, Racine, & Klump, 2010). Major stressors were assessed for the 12 months prior to the study. Results suggested that daily stress moderated the link between restraint and binge eating, but only in the context of high levels of major life stress. Interestingly, the link between restraint and binge eating was not significant under conditions of high major life stress and low daily stress. The authors concluded that the cumulative effects of both major and daily stressors might overwhelm individuals' coping resources, and lead to eating disturbances, consistent with many prominent theories of eating disorder etiology (e.g., Heatherton & Baumeister, 1991). This study's cross-sectional design is a limitation; however, it does highlight the importance of considering daily stressors when evaluating life events and coping resources, and suggests this is an important construct to consider in future clinical and research efforts.

Smyth, Heron, Wonderlich, Crosby, & Thompson (2008) investigated the influence of traumatic events on young adults' eating disorder symptomatology during their transition to college. Participants reported not only whether they had experienced each trauma in their lifetime, but also its perceived severity (rated on a five-point scale). Thus, this study incorporated cognitive appraisal of stressors, an important construct discussed further in the following section. Traumas were assessed at time 1 only. Trauma severity was positively associated with increases in both restrictive eating and binge-eating symptomatology over the course of the first semester of college. There were some differences in the specific types of trauma associated with binge and restrictive eating, respectively. For example, nonpersonal traumas were the only specific trauma type associated with increases in restrictive eating. In contrast, several trauma types (e.g., death of a loved one, parents' separation/divorce) were associated with increases in binge eating over the first semester. A study by Bodell, Smith, Holm-Denoma, Gordon, & Joiner (2011) also found that the number of life stressors experienced by college students between the fall and spring semesters was associated with some eating disorder symptoms (as measured by the EDI-Bulimia subscale) but not others (restrictive eating, as measured by the EDI-Drive for thinness subscale). This study also assessed a range of stressors, including some especially relevant to college students, such as academic performance.

The influence of stressful life events on relapse following remission from BN and EDNOS was investigated in a 6-year longitudinal study (Grilo et al., 2012). Both the total number of stressful life events and specific types of stressors, such as social and work-related issues, were positively associated with relapse. These findings suggest that some stressful life events might increase susceptibility to eating disorder symptomatology, but this risk is not uniform and is likely mediated by cognitive processes, such as appraisal distress tolerance, and general coping ability, which are discussed in the following section.

Eating disorder symptomatology might also influence both perceptions of stress and the likelihood that stressful events occur. Bodell et al. (2011) investigated this possibility in a study with undergraduates, and found that eating disorder symptomatology (bulimic symptoms and drive for thinness) was not associated with negative life events beyond that accounted for by depression. However, in a subsequent study, with a similar sample, dietary restraint was predictive of the occurrence of negative life events between the two data collection points. Nonetheless, other eating disorder symptoms (i.e., body dissatisfaction, weight concern, bulimic symptoms, eating concern, and shape concern) were not associated with negative life events. Thus, one must be cautious in interpreting this finding, which could be spurious given the number of tests conducted. Yet it does suggest that future research should investigate whether specific eating disorder-related behaviors might put individuals at particular risk for stress.

Distress Tolerance

Perhaps one reason for the somewhat inconsistent findings regarding the impact of stressful life events on eating disorder symptomatology is that the impact of these experiences is influenced by the way in which they are appraised and how well individuals cope in response to them. Numerous studies have documented the link between cognitive appraisal and psychological outcomes (Folkman, Lazarus, Dunkel-Schetter, Delongis, & Gruen, 1986a; Folkman, Lazarus, Gruen, & Delongis, 1986b). More recently, the construct of distress tolerance has received attention in the area of eating disorders. This construct seems especially relevant to individuals with eating disorders, as emotion regulation difficulties have long been identified in affected individuals and across eating disorder subtypes (Brockmeyer et al., 2012; de Zwaan, Biener, Bach, Wiesnagrotzki, & Stacher, 1996; Harrison, Sullivan, Tchanturia, & Treasure, 2009; Heatherton & Baumeister, 1991), and research has linked poor distress tolerance and eating disorder symptomatology (Anestis, Selby, Fink, & Joiner, 2007). There is also significant comorbidity between eating disorders and post-traumatic stress disorder (PTSD; Mitchell et al., 2012; Reyes-Rodríguez et al., 2011). In addition, a recent study found that the link between PTSD and eating disorder severity was mediated by psychological distress (Isomaa, Backholm, & Birgegård, 2015). Gene–environment interactions also likely play an important role in the relations among adverse events, coping, and eating disorder outcomes. In one of the few studies in this area, Akkermann et al. (2012) investigated the role of the 5-HTTLPR genotype and environmental stressors on eating disorder symptoms. The short (s) allele of the 5-HTT polymorphic region is positively associated with several mental health outcomes, including neuroticism (Sen et al., 2004). Akkerman et al.'s (2012) sample included girls from the longitudinal Estonian Children Personality, Behaviour and Health Study. Two assessment points were used in the analyses (time 1, mean age = 14.8; time 2, mean age = 17.8). Participants reported the lifetime occurrence of specific life events at time 1; eating disorder symptoms (EDI- Bulimia and EDI-Drive for thinness) were assessed at time 2. Results indicated that the 5-HTTLPR genotype was not significantly associated with eating disorder symptomatology; however, this polymorphism interacted with life events to predict higher scores on the EDI-Bulimia subscale at time 2. Individuals with both this genotype and more negative life events by age 15 were more likely than their peers to report bulimic symptoms at age 18. There was no significant main or interaction effect between genotype and drive for thinness.

Mixed results were obtained in related study investigating interactions between genetic influences and a specific life stressor, parental divorce, in a sample of female twins (Suisman, Alexandra Burt, McGue, Iacono, & Klump, 2011). Parental divorce was not associated with most forms of eating disorder symptomatology measured (binge eating, weight preoccupation, and total disordered eating); however, it was associated with body dissatisfaction. A limitation of both the Akkermann et al. (2012) and Suisman et al. (2011) studies is that it is unclear when the stressor(s) occurred in relation to the precise onset of eating disorder symptomatology. Nonetheless, these two studies extend the prior literature on life events, eating disorders, and the stress response, and highlight the complexity of these relations.

A more recent investigation (Fairweather-Schmidt & Wade, 2015) looked at the impact of genetic influences, weight-related teasing, and negative life events (occurring during the 12 months prior to data collection) on eating disorder symptoms in twins using longitudinal data from early and late adolescence. Parents completed the measure of negative life events; adolescents completed the other measures. Negative life events were not associated with eating pathology in late adolescence. However, weight-related teasing did significantly contribute to eating disorder symptomatology. A limitation of the negative life events measure used in this study is that it included only those events occurring in the prior 12 months. Further, parents completed this measure and might not be aware of all of their daughters' experiences. It is also important to note that, in this study, genetic factors accounted for a substantial proportion of variance in disordered eating symptomatology. The authors concluded that these findings suggest a potential interaction between a critical period genetic risk and a specific environmental stressor, weight teasing, in the development of eating disorders during mid-to-late adolescence.

Cognitive Functioning

The possibility that there is CNS dysfunction in affected individuals has been explored through a variety of mechanisms, including neuropsychological performance (Duchesne et al., 2004; Jáuregui-Lobera, 2013; Weider, Indredavik, Lydersen, & Hestad, 2015). Cognitive functions implicated in AN include decreased attentional capability (Ferraro, Wonderlich, & Jocic, 1997; Giel et al., 2011; Green, Elliman, Wakeling, & Rogers, 1996; Jones, Duncan, Brouwers, & Mirsky, 1991) memory (Kingston, Szmukler, Andrewes, Tress, & Desmond, 1996; Mathias & Kent, 1998), visuo-spatial construction (Thompson & Spana, 1991), learning capacity (Witt, Ryan, & Hsu, 1985), and executive functioning (Kingston et al., 1996; Szmukler et al., 1992). Cognitive functioning in BN and BED has been less extensively studied and has largely focused on decreased attention and executive functioning (Aloi et al., 2015; Manasse et al., 2015; Weider et al., 2015).

Various deficits in executive functioning have been noted in the eating disorder literature (Cooper, Anastasiades, & Fairburn, 1992; Fassino et al., 2002; Jáuregui-Lobera, 2013; Kemps, Tiggemann, & Marshall, 2005; Koba, Horie, & Nabeta, 2002; Tchanturia et al., 2012, 2004; Zastrow et al., 2009). Executive functioning is an umbrella term that refers to a set of neuropsychological processes in the frontal lobe of the brain that govern higher-level, goal directed behavior (Miyake et al., 2000). A set of systematic reviews and meta-analyses provides strong evidence that deficits in set shifting, central coherence, and working memory are present within ED diagnostic groups (Lang, Lopez, Stahl, Tchanturia, & Treasure, 2014a; Lang, Stahl, Espie, Treasure, & Tchanturia, 2014b; Lopez, Tchanturia, Stahl, & Treasure, 2008b; Roberts, Tchanturia, Stahl, Southgate, & Treasure, 2007; Wu et al., 2014). Furthermore, the magnitude of impairment appears to be similar across BN and AN subtypes (Lang et al., 2014b; Roberts et al., 2007). Set shifting, or the ability to move back and forth between tasks or mental sets, is an important component of executive functioning (Miyake et al., 2000). Set-shifting ability is essential for cognitive and behavioral flexibility, allowing an individual to adapt his or her behavior to meet the changing demands of the environment. Problems in set shifting might manifest in a variety of forms of cognitive inflexibility (e.g., rigid approaches to problem-solving) or response inflexibility (e.g., perseverative or stereotyped behavior; Roberts et al., 2007). Recent research has suggested that set-shifting difficulties might be related to the development of disordered eating (Danner et al., 2012; Kanakam, Raoult, Collier, & Treasure, 2013; Roberts et al., 2007; Steinglass, Walsh, & Stern, 2006; Tchanturia et al., 2004; Wu et al., 2014; Zastrow et al., 2009).

For example, individuals with EDs perform poorly on set-shifting tasks compared with controls. A 2014 systematic review and meta-analysis (Wu et al. 2014) examined set shifting in eating disorders and obesity (for the scope of this chapter, we review only the ED findings). A total of 64 eating disorder papers that administered at least one of the seven set-shifting tasks—including the Wisconsion Trail Making Task (TMT; Halstead, 1947; Reitan, 1958), Wisconsin Card Sorting Test (WCST; Heaton, Chelune, Talley, Kay, & Curtis, 1993), Verbal Fluency Test (VFT; Delis, Kaplan, & Kramer, 2001), the Intra-Dimensional/Extra-Dimensional (ID/ED) set-shifting tasking (Robbins et al., 1998), the Brixton spatial anticipation test (Burgess & Shallice, 1997), the Object Alternation Test (OAT; Freedman, 1990) and Weigl's Sorting Test (WST; Weigl, 1941)—were reviewed (for obesity/overweight findings see Wu et al., 2014). A significant deficit was found across the whole spectrum of EDs, AN, BED, and BN, regardless of age, with small to medium effect sizes across assessment measures used. This is consistent with a 2007 systematic review and meta-analysis (Roberts et al., 2007) finding a similar deficit in set shifting that traversed diagnoses, state of illness, and the majority of the set-shifting assessment measures used. Although this study employed a limited amount of data from recovered/weight-restored subgroups of individuals with AN, preliminary results suggest that deficits in set shifting, particularly as measured by the TMT, the Haptic Illusion, and the CatBat, remain following weight restoration (Roberts et al., 2007).

A study by Tchanturia et al. (2004) examined whether suboptimal set shifting was state- or trait-related by examining set shifting in individuals with current or past AN. The association of these deficits with obsessive-compulsive behaviors and traits was also explored. The authors compared set-shifting abilities in females with current AN (AN-R, n = 20; AN-BP, n = 14) prior to receiving treatment, individuals with past AN in long-term recovery (n = 18, stable body mass for minimum of a year, regular menses for a year, and no psychotropic medication for a year), and healthy controls (n = 36). Participants were given a battery of neuropsychological tests assessing various facets of set shifting and executive functioning. A computerized version of the TMT (Kravariti, Morris, Rabe-Hesketh, Murray, & Frangou, 2003; Reitan, 1958) assessed rapid simple alternation between mental sets; the Brixton Test (Burgess & Shallice, 1997), the Set Flexibility Picture Test (Surguladze, 1995), and the CatBat Task were used to assess problem-solving and set shifting. The Uznadze Illusion Task (Uznadze, 1966) was used to assess perceptual set shifting. Lastly, a verbal fluency test (as described in Lezak, Howieson, & Loring, 2004) assessed cognitive retrieval and flexibility in cognitive search options. In addition, a semistructured interview evaluated obsessive-compulsive traits in childhood and adulthood.

Scores of individuals with current AN-R or AN-BP on several set-shifting tasks (e.g., including the TMT and the Brixton Illusion) were significantly lower than those of the recovered and control groups. Individuals recovered from AN had significantly more illusions on the Uznadze Illusion Task and made more errors on the Set Flexibility Picture Test, relative to the control group. Overall, the individuals who had recovered from AN obtained scores that were between those of individuals with current AN and healthy controls, suggesting that nutritional status might play some role but is not entirely responsible for the mental inflexibility associated with AN.

To better understand the relationship between starvation and set-shifting deficits, recent studies assessing set shifting in adolescents with AN have begun to emerge. Conducting neuropsychological investigations in younger populations increases the chances that the change in set shifting is more likely related to the illness rather than to starvation, as the duration of the illness is shorter. In a preliminary systematic review and meta-analysis, children with AN typically showed poorer performance on set shifting compared with health controls, although this finding was nonsignificant (Lang et al., 2014b). The results from the preliminary meta-analysis suggest that set-shifting inefficiencies are less pronounced in children/adolescents than in adults; however, more research is needed to clarify the neuropsychological profile of children and adolescents with AN.

Although less research has examined executive functioning deficits in BN and BED, there is some emerging evidence of cognitive flexibility deficits in BN (Wu et al., 2014) and BED (Aloi et al., 2015; Wu et al., 2014). However, it is unknown if theses deficits persist after recovery in BN or BED. Familial data provide some evidence for a trait-related dysfunction in BN. For example, nonaffected biological sisters of individuals with BN demonstrated problems with cognitive flexibility compared with controls (Tchanturia et al., 2012).

Weak central coherence refers to an emphasis on small details and weak ability to integrate information globally (Happé & Booth, 2008) and is one of the three main neurocognitive theories of autism to explain its characteristic behavioral impairments (Oldershaw, Treasure, Hambrook, Tchanturia, & Schmidt, 2011). Weak central coherence has been observed in AN and BN (Aloi et al., 2015; Lopez et al., 2008a,b; Lopez, Tchanturia, Stahl, & Treasure, 2008c; Southgate, Tchanturia, & Treasure, 2008) and there is some evidence that this deficit persists after recovery (Lopez, Tchanturia, Stahl, & Treasure, 2009). In a 2014 systematic review and meta-analysis, Lang et al. found that individuals with EDs display a bias towards detail at the expense of global integration, providing support for a weak central-coherence hypothesis. A bias towards details over the global “gist” was consistently demonstrated with all studies using the Group/Embedded Figures Task (G/EFT), with medium effect sizes, across ED diagnosis (Lang et al., 2014b). Very few studies have looked specifically at BED central coherence specifically. However, when comparing AN with BED subjects and healthy controls, weak central coherence characterizes AN patients, while poor attention is the distinctive trait of BED patients (Aloi et al., 2015).

Across studies, findings suggest that executive functioning deficits might be related to an underlying biological vulnerability to EDs. Neurobiological deficits in set shifting and central coherence found among individuals with AN might mirror the behavioral and personality characteristics, such as rigidity and inflexibility, observed within this diagnostic group (see reviews by Braun & Chouinard, 1992; Jáuregui-Lobera, 2013; Lauer, 2002), whereas poor inhibitory control best typifies the EDs characterized by binge eating.

Effortful control may represent one domain that differs clearly between the restricting subtype of AN, in which it is presumed that individuals use high levels of cognitive control, especially in relation to eating (van Elburg & Treasure, 2013), and those with eating disorders characterized by binge eating or purging, which may represent a deficit in top-down control of biological reactivity to reward and emotion (Claes, Mitchell, & Vandereycken, 2012).

Finally, many individuals with AN also appear to have social cognitive deficits (van Elburg & Treasure, 2013; Zucker et al., 2007). Some patients report long-standing interpersonal discomfort even premorbidly, and long-term outcome studies of AN suggest a higher proportion of individuals with traits characteristic of the autism spectrum (see Zucker et al., 2007 for a comprehensive review). Of course, all studies of cognitive function in eating disorders must carefully consider the impact of nutritional state on functioning. Planned and ongoing investigations of high-risk cohorts, unaffected relatives, and long-term recovered individuals have the potential to disambiguate state from trait deficits.

Racial-Ethnic Considerations

For many years, eating disorders were often considered illnesses that affected White women nearly exclusively (Becker, Franko, Speck, & Herzog, 2003). This cultural stereotype appears to have influenced clinicians as well, as studies show that women of color are less likely to be identified as having an eating disorder (even when their symptoms are consistent with diagnosis) or referred for eating disorder treatment (Becker et al., 2003).

As noted previously, lifetime prevalence estimates of DSM-IV AN, BN, and BED from a nationally representative population sample of women over age 18 are 0.9%, 1.5%, and 3.5%, respectively (Hudson et al., 2007). Prevalence estimates vary across racial and ethnic groups, however. The lifetime prevalence of eating disorders among African American adult females from a US population-based survey is 0.14% for AN, 1.90% for BN, 2.36% for BED, and 5.82% for any binge-eating behavior (Taylor, Caldwell, Baser, Faison, & Jackson, 2007). Other studies have reported slightly lower prevalence estimates in African American women (Striegel-Moore et al., 2003). One set of lifetime prevalence estimates among Latinas are 0.12% for AN, 1.91% for BN, 2.31% for BED, and 5.80% for any binge eating (Alegria et al., 2007). Relatively similar estimates were obtained in a more recent population-based sample (Marques et al., 2010).

The prevalence of eating disorders among Asian women has been estimated to be 0.12% for AN, 1.42% for BN, 2.67% for BED, and 4.71% for any binge eating (Nicdao, Hong, & Takeuchi, 2007). Further, more recent research (Lee-Winn, Mendelson, & Mojtabai, 2014) found a significant discrepancy between rates of BED and all binge eating in Asian women in a national sample of adults in the US. Asian Americans were less likely than Whites to report experiencing distress related to binge eating, or loss of control. However, rates of lifetime BED were similar among Whites and Asian Americans. The authors of this report conclude that rates of threshold BED are likely underestimated, due to potential cultural differences in the interpretation of loss of control eating and distress in response to this behavior.

African American women's risk for binge eating and BED may indeed be equal to, or possibly even greater than, that of White women (Striegel-Moore et al. 2000b). For example, Taylor et al. (2007) found that BED was not only more common than either AN or BN among African American women, but also was the most chronic eating disorder diagnosis, with a mean duration of over 7 years. These findings are consistent with those of other studies with respect to the clinical significance and prevalence of binge-eating behaviors among African American adults (Marcus et al., 2007; Striegel-Moore et al., 2000b). Another significant concern regarding eating disorders among African Americans is that rates of treatment-seeking for eating disorders are significantly lower among this group than among White women (Becker et al., 2003; Cachelin, Veisel, Barzegarnazari, & Striegel-Moore, 2000; Marques et al., 2010). These findings suggest that many African American women with clinically significant binge-eating behaviors remain untreated.

The few extant studies on eating disorders in Latinos suggest prevalence estimates on a par with Whites in the United States (Alegria et al., 2007; Reyes-Rodríguez et al., 2010). A few investigations have suggested that Latinas were more likely than White women to report eating disorder symptomatology (Austin et al., 2011; Fitzgibbon et al., 1998; Marques et al., 2010). Other research has found that BED is the most common eating disorder within this ethnic group (Alegria et al., 2007).). Studies suggest eating pathology and related attitudes are a significant concern among Latinas. Pumariega (1986) found that 20% of young Hispanic urban high school students scored at or above the clinical screening threshold on the Eating Attitudes Test. Binge eating has also been reported to be more severe in Latinas than in Whites or African Americans (Fitzgibbon et al., 1998). Latina girls report greater body dissatisfaction than do White girls (Robinson et al., 1996) and more disturbed eating attitudes and behaviors than do African American girls (Vander Wal & Thomas, 2004).

Although research is emerging regarding the prevalence of eating disorders across racial and ethnic groups, much less is known about the treatment of eating disorders in diverse populations. The majority of studies constituting the evidence base have been conducted primarily on White samples. This is especially concerning, as results of one recent study indicated that African Americans were more likely than Whites to drop out of treatment for BED (Thompson-Brenner et al., 2013).

Further, a qualitative investigation of Latina women with eating disorder histories found that multiple factors, including systemic (e.g., health insurance, availability of bilingual services) and cultural (e.g., emphasis on family privacy, fatalism) barriers, influenced treatment-seeking and retention. In addition, women in this study reported encountering the perception that individuals from their cultural group do not experience eating disorders, which also discouraged treatment-seeking (Reyes-Rodríguez, Ramírez, Davis, Patrice, & Bulik, 2013). A few small studies have investigated the feasibility of adapting existing evidence-based eating disorder treatments, such as cognitive-behavioral therapy (CBT) for Latina populations. One pilot trial (Cachelin et al., 2014) involved a sample of 31 Mexican American women diagnosed with either BN, BED, or recurrent binge eating. All were enrolled in guided self-help CBT treatment. This treatment was specifically adapted for this ethnic group based on the results of prior qualitative research conducted with Mexican American women (Shea et al., 2012). Results of the pilot trial indicated that the adapted intervention was effective; binge eating was significantly reduced, and participants rated the intervention as helpful. Attrition rates were comparable to those of other studies, but were, nonetheless, a bit high (35% dropout after enrollment). Participants with less education and those with BN were more likely to drop out, highlighting the importance of offering a range of interventions in subsequent clinical trials.

Research testing the appropriateness of standard eating disorder treatments and the optimal approaches to cultural adaptation of treatments for diverse populations remains urgently needed.

Course and Prognosis

Anorexia nervosa has serious medical and psychological consequences, many of which persist even after recovery. In addition to the eating-related symptomatology, many other comorbidities of this disorder, including depression, anxiety, social withdrawal, heightened self-consciousness, fatigue, and multiple medical complications, cause considerable impairment (Berkman, Lohr, & Bulik, 2007). For example, the social toll of AN interferes with normal adolescent development (Bulik, 2002). Across psychiatric disorders, the highest risks of premature death, from both natural and unnatural causes, are from substance abuse and eating disorders (Harris & Barraclough, 1998).

Anorexia nervosa history is further associated with reproductive problems (Bulik et al., 1999; Micali, Simonoff, & Treasure, 2007; Micali & Treasure, 2009), osteoporosis (Mehler & Mackenzie, 2009), continued low BMI (Sullivan et al., 1998), and major depression (Fernandez-Aranda et al., 2007). Given the high morbidity and mortality associated with AN, it is critical to develop effective treatments. Initial treatment typically includes a comprehensive medical evaluation and nutritional counseling. Less medically compromised cases of AN are most often treated on an outpatient basis by mental health providers, with primary-care physicians managing medical issues.

Treatment guidelines or position papers outlining recommended AN treatment have been developed by numerous professional organizations, including the American Psychiatric Association (APA, 2006), the National Institute for Clinical Excellence (NICE, 2004), the Society for Adolescent Medicine (Golden et al., 2003), the American Academy of Pediatrics (AAP, 2003) and the Royal Australian and New Zealand College of Psychiatrists (Beumont et al., 2004).

Anorexia nervosa treatment also typically involves psychotherapeutic intervention. Individual, family, and group psychotherapy for AN are conducted from a multitude of theoretical perspectives (e.g., cognitive-behavioral, interpersonal, behavioral, and psychodynamic). For children, family-based therapy has received considerable attention, and it is generally suggested that family members be included in treatment, when feasible and sensible. The current evidence base for treatment of AN suggests some benefit for family-based treatment for young people and recommends a combination of renourishment and psychotherapy (specialist supportive clinical management, CBT, or interpersonal therapy [IPT]) for adults (Watson & Bulik, 2013). Adults with AN have typically been treated entirely on an individual basis, often leaving partners unsure about how best to assist. A new intervention currently being studied, Uniting Couples in the treatment of Anorexia Nervosa (UCAN), leverages the power of interpersonal relationships by incorporating the partner into treatment using a cognitive-behavioral couple therapy approach. UCAN explores several domains (core AN symptoms, body image, affection, sexuality, relapse, and recovery) and helps partners learn to provide support for the patient and reinforce appropriate eating and healthy behaviors, while also improving general relationship functioning (Bulik, Baucom, Kirby, & Pisetsky, 2011).

The APA Working Group on Eating Disorders recommends hospitalization for individuals below 75% of ideal body weight (APA, 2006). However, in addition to weight, parameters such as medical complications, suicidality, previous treatment success, psychiatric comorbidities, social support, role impairment, and availability of other treatment options should all be considered in level-of-care decisions (APA, 2006). Currently, no medications are effective in the treatment of AN (Bulik, Berkman, Brownley, Sedway, & Lohr, 2007). Although commonly prescribed, SSRIs tend to be ineffective in the underweight state, especially in the absence of dietary tryptophan to subsidize the synthesis of serotonin. All treatment commonly involves highly specialized multidisciplinary teams, including psychologists, psychiatrists, internists or pediatricians, dietitians, social workers, and nurse specialists.

Among individuals hospitalized for AN, lengths of stay are much shorter in the United States compared with those in Europe and New Zealand. For example, Striegel-Moore et al. (2000a) found the average length of stay within the United States was 26 days (according to an insurance database of approximately 4 million individuals) (Striegel-Moore, Leslie, & Petrill, 2000a). This is substantially shorter than stays found in other countries, including New Zealand (72 days; McKenzie & Joyce, 1992) and Europe, which ranges from 40.6 days (Finland) to 135.8 days (Switzerland) (Matthias, 2005). Moreover, AN treatment costs in the United States were higher than those for obsessive-compulsive disorder and comparable to those for schizophrenia, both of which occur at similar rates to AN (Striegel-Moore et al., 2000a).

Patients with BN report physical symptoms such as fatigue, lethargy, bloating, and gastrointestinal problems. Frequent vomiting is associated with electrolyte abnormalities, metabolic alkalosis, erosion of dental enamel, swelling of the parotid glands, and scars and calluses on the backs of their hands (Mitchell & Crow, 2006). Laxative misuse often causes edema, fluid loss and subsequent dehydration, electrolyte abnormalities, metabolic acidosis, and potentially permanent loss of normal bowel function (Mitchell & Crow, 2006).

In the United States, most BN treatment is conducted on an outpatient basis. A comprehensive medical evaluation is typically recommended, given the frequency of medical and nutritional complications within this patient population. If significant medical complications related to BN are present, or if the affected individual is pregnant or unable to bring her or his binge-purge behaviors under control in outpatient treatment, partial hospitalization or inpatient treatment may be warranted.

Once medical issues are assessed and under control, psychotherapy (individual and/or group) is typically the primary treatment for BN. As is the case with AN, the theoretical perspectives used in these psychotherapeutic interventions can vary; however, CBT and IPT are commonly used. In 1996, the FDA approved fluoxetine for the treatment of BN. Currently, this is the only FDA-approved medication for the treatment of any eating disorder.

Given that BED has only recently entered the psychiatric nomenclature, minimal population-based data are available regarding the morbidity and mortality related to this diagnosis. However, most adults with BED are obese and, thus, are at risk for medical complications associated with overweight (Hudson et al., 2007; Hudson et al., 2010; Striegel-Moore et al., 2001). Global community surveys suggest that the majority of individuals with a lifetime BED diagnosis (79.0%) also meet diagnostic criteria for at least one additional psychiatric disorder (including mood, anxiety, behavioral, and substance use disorders). BED also predicts subsequent onset of arthritis, chronic back/neck pain, chronic headaches, diabetes, hypertension, and ulcers (Kessler et al., 2013). Many adults with BED report that their symptoms began in childhood (Abbott et al., 1998). Thus, it seems important that future research investigate further the correlates of binge eating in childhood. Within the United States, BED treatment is typically conducted on an outpatient basis. Psychological and nutritional interventions aim to reduce binge eating and control weight (Brownley, Berkman, Sedway, Lohr, & Bulik, 2007). Common psychotherapeutic approaches include CBT and IPT; nutritional approaches include behavioral self-management strategies and facilitating hunger and satiety awareness (Brownley et al., 2007). Pharmacotherapy that targets both the core symptom of binge eating and weight loss (when appropriate) is also available as an off-label intervention (Brownley et al., 2007; Peat, Brownley, Berkman, & Bulik, 2012).

Case Study

Referral

Wendy was a 35-year-old married White female who was referred for treatment for an eating disorder after passing out at the finish line of a half marathon.

Presenting Complaints

The emergency room discharge note indicated that Wendy was 5 feet 6 inches tall and weighed 90 pounds (BMI 14.5 kg/m2). She was severely dehydrated, her potassium was 2.5 (normal range 3.5–5 mEq/L), and her EKG indicated a prolonged QT interval. Pulse and blood pressure were low. The emergency room physician was vigilant and noted scrapes on her knuckles (Russell's sign) and bloodshot eyes, both indicative of purging.

History

Wendy was a competitive runner with hopes of qualifying for the Olympics. Two years ago, while on a training run on trails, she was attacked by a man who tried to rape her. She screamed and fought and managed to get away by running out of the forest as fast as she could, but she continued to have flashbacks to this attack every day when she was training on the streets or trails. Prior to the attack, all her attention was on training. She had been a healthy eater, she was always focused on performance rather than appearance, and adhered strictly to the recommendations of her trainer and sports dietitian. After the attack, she became increasingly anxious, had difficulty sleeping, and had trouble keeping up her training schedule. Her race times were getting slower and she was gaining weight. She often found herself eating mindlessly in front of the pantry—sometimes not even being aware of what she was eating. Wendy lost two races to one of her main competitors, and when she saw a picture in the newspaper of herself coming in second in the paper, she became fixated on her weight. She was up to 125 pounds, which was higher than she had ever been before. She started cutting back on calories, which she found easy to do. Wendy stated, “I was training hard and pushing through pain to get through marathons, so dealing with hunger is a piece of cake in comparison.”

One evening she went out for a post-run pizza and beer with her husband and some friends. She went to the restroom and was overcome by anxiety about how much she had eaten. Although she had never done it before, she decided to vomit and even though she was horrified at what she had done, she felt a huge sense of relief and felt much less anxious afterward. She didn't intend for it to become a habit, but soon the urge to vomit after she ate became overwhelming, and it seemed to be the only way she could control her anxiety. At first she was just vomiting after dinner, but within a few months, she was doing it up to five to 10 times a day. She started vomiting even if she hadn't eaten anything. Her weight continued to drop and her race times kept getting slower. Her coach and trainer were worried about her health, but she denied any problems. She started having difficulty concentrating at work, was sleeping poorly, and withdrew almost completely from her family and friends. She also withdrew from her husband. Even though they had been talking about starting a family, she became less and less interested in having sex and would pull away whenever he tried to touch her. She spent hours in the bathroom scrutinizing her body—checking to see if her shape had changed, pinching the skin on her waist to make sure her shape wasn't changing, and weighing herself—sometimes 10 times per day. She became convinced that the only way to start winning races again was to get below 90 pounds. She was limiting her intake to about 800 calories per day, restricting how much she drank, and continued to vomit several times per day. Wendy made it through the half marathon on sheer will, but passing out at the finish line was the final event that brought her into treatment.

Assessment

On clinical interview, Wendy demonstrated significant weight loss below 85% of expected weight for her age and sex. She presented with clear drive for thinness, fear of weight gain, and a failure to recognize the seriousness of her underweight state. Her body image was distorted, as she continued to see herself as fat, even though she was 90 pounds and 5 feet 6 inches tall. There were no other medical explanations for her weight loss. She denied objective binge eating (eating unusually large amounts of food and feeling out of control) but endorsed subjective binge eating (feeling out of control when eating regular or small amounts of food). She also admitted to regular purging via self-induced vomiting. She had not menstruated for the previous 6 months. Wendy met the diagnostic criteria for anorexia nervosa, binge-purge subtype.

Clinical interview also indicated that she experienced post-traumatic stress symptoms secondary to the attack while running. She completed three self-report forms—the Eating Disorders Inventory (EDI) and the Beck Depression and Anxiety Inventories (BDI, BAI). Results indicated high scores on drive for thinness, body dissatisfaction, and perfectionism on the EDI. Her BDI scores indicated mild depression and no suicidal ideation, and a BAI score of 38 indicated high anxiety consistent with her clinical interview.

Summary

Our understanding of eating disorders continues to advance. We know that both genetic and environmental factors contribute to their etiology. After vulnerable individuals start to lose weight, even if it is voluntary, the illness often takes on a life of its own and the weight loss becomes uncontrollable. Advances in neurobiological and genetic research are helping us understand why some individuals are more vulnerable to eating disorders than others. Ironically, the thorough study of biology may provide the biggest boost for our understanding of the role of environment as causal in eating disorders. This work may also assist in identifying environmental risk factors, which will fuel prevention efforts.

As work in the eating disorders field is additionally challenged by the new-world context of escalating obesity, eating disorder researchers must partner with obesity researchers to share findings and ensure that prevention and treatment efforts in one area do not increase the risk for development of pathology in the other area. For example, obesity prevention efforts cannot inadvertently lead to more disordered eating behavior in attempts to control weight. Similarly, eating disorder treatment should not inadvertently increase the risk for the development of obesity. Animal models of component features of eating disorders (e.g., driven physical activity, binge eating) are also shedding valuable light on underlying neurobiological processes that initiate and maintain dysregulated eating and activity behavior. The integration of research findings from cell to population is required to complete the complex picture of these perplexing disorders that stand at the intersection of psyche and soma.

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Chapter 19 Substance-Related and Addictive Disorders: Drugs

Stacey B. Daughters and Jennifer Y. Yi

Introduction

Substance use disorder is a prevalent and pervasive public health concern in the United States, incurring major costs to individuals, families, and society at large. In 2014, approximately 21.5 million Americans age 12 or older had a substance use disorder in the past year (SAMHSA, 2015). The financial burden on society from substance use is estimated to be greater than $600 billion annually in substance use-related treatment and prevention, health care expenditures, lost wages, reduced job production, accidents, and crime (SAMHSA, 2014a). In addition to the substantial economic cost, substance use disorder is associated with engagement in multiple health-compromising and risk-taking behaviors (e.g., condom nonuse, multiple partners, impulsive spending, driving while intoxicated) that contribute significantly to public health costs (Office of National Drug Control Policy [ONDCP], 2004).

Diagnostic Considerations

The Diagnostic and Statistical Manual (DSM-5; APA, 2013) provides a comprehensive classification system for the assessment and subsequent diagnosis of a substance use disorder across 10 drug classes, including alcohol, cannabis, phencyclidine, other hallucinogens, inhalants, opioids, sedatives, stimulants, tobacco, and other/unknown. Each substance is defined as a separate substance use disorder. The essential feature of a substance use disorder is continued substance use in spite of clinically and functionally significant impairment or distress, such as negative social and financial consequences, legal problems, and failure to meet responsibilities at work, school, or home. A key characteristic of a substance use disorder is an underlying change in the user's neurological circuitry, a side-effect that may persist even after substance use is discontinued, especially in individuals with a severe substance use disorder. This altered circuitry is believed to increase the vulnerability for repeated relapse, particularly when individuals encounter substances or substance-related stimuli.

The diagnostic criteria for a substance use disorder specify a maladaptive pattern of behaviors related to substance use. These behaviors fall into four categories: impaired control, social impairment, risky use, and pharmacological criteria.

Impaired control (criteria 1–4) is often characterized by using for longer periods of time or using larger amounts than intended, or engaging in unsuccessful efforts to follow through with intended plans to reduce use. Impaired control may also be evidenced by spending an excessive amount of time getting, using, or recovering from substance use. Additionally, impaired control can involve craving, a perceived need to engage in substance use operationalized as the extent to which the desire to use consumes an individual's thoughts. Craving often arises in the context of prior use (e.g., the presence of people with whom one had used; being in a location where one had previously used).

Social impairment (criteria 5–7) pertains to an inability to carry out the needs of daily life in all facets of one's environment, whether it involves failing to fulfill obligations or opting to use rather than engaging in social activities. It may also include giving up or reducing engagement in important and meaningful social activities. Further, social impairment is characterized by persistent substance use in spite of the negative social impact (e.g., having arguments and losing relationships with loved ones due to substance use).

Risky use (criteria 8, 9) involves the continued use of a substance that is known to present a danger to the user. This risk might entail using in a dangerous situation (e.g., driving, using machinery, unsafe sex) or using with a known vulnerability to a physical or psychological issue that would likely be made worse by further use.

Pharmacological criteria (criteria 10, 11) focus on tolerance and withdrawal. Tolerance is a state that develops wherein the user needs progressively larger doses of the drug in order to feel the desired effect. Withdrawal is a physical response to specific substances that can occur after extended, consistent use.

Substance use disorders can be further defined on a continuum as mild (two to three symptoms), moderate (four to five symptoms), or severe (six or more symptoms), indicating the level of severity that is determined by the number of 11 possible diagnostic criteria met. Substance use disorders can also be detailed by specifying “in early remission” (at least 3 months but less than 12 months without meeting criteria), “in sustained remission” (at least 12 months without meeting criteria), “on maintenance therapy,” and/or “in a controlled environment.”

Clinical Picture

In 2015, there were an estimated 2.3 million admissions to treatment for substance use at a specialty facility (Lipari, Park-Lee, & Van Horn, 2016). Between 2004 and 2014, five substance categories, alcohol, opiates, marijuana, cocaine, and methamphetamine/amphetamines accounted for between 96% and 97% of treatment admissions for substance use (SAMHSA, 2016). Among the different treatment settings available, most admissions (61%) received ambulatory care. In addition, 22% received detoxification and 17% received rehabilitation or residential treatment.

Specific populations are more vulnerable to initiation and continued substance use. In particular, youth and young adults are special populations of interest, because early use increases the likelihood of developing substance use problems. In 2014, approximately 1.3 million (5.0%) adolescents between the ages of 12 and 17 had a substance use disorder (SAMHSA, 2015).

Physiological and Psychological Effects

Substance use disorder can involve the recurrent use of a single or multiple substances. Commonly, substances are grouped based on categories that vary in their physiological and behavioral effects. In this section, we discuss the different substance categories, excluding nicotine and alcohol, which are discussed in other chapters. This discussion includes street and slang names, physiological and psychological effects of each category, and the withdrawal symptoms that occur with continued use and as tolerance develops. Interested readers are referred to Advokat, Comaty, & Julien (2014) for an extensive review.

Cannabinoids, such as marijuana, sinsemilla, and hashish (street names include dope, pot, weed, grass, hash), produce mild euphoria, sedation, enhanced sensory perception, increased appetite and pulse, psychomotor impairment, and confusion. Tolerance can occur with habitual use, and discontinuation of use can result in uncomfortable withdrawal effects, including anxiety, depression, irritability, and insomnia. Although cannabinoids are increasingly being used for medical purposes, they are still considered illegal under federal law.

Alternatively, hallucinogens, which include LSD (acid, blotter), mescaline (buttons, peyote, mesc), and psilocybin (magic mushrooms, shrooms), create an altered state of consciousness, detachment from self and environment, and dissociative symptoms. Hallucinogens are not physically addictive; however, LSD and mescaline produce negative physiological reactions such as increased body temperature, blood pressure, and heart rate. Psychologically, hallucinogen use can result in persistent mental disorders characterized by panic attacks and psychosis.

While both cannabinoids and hallucinogens are illegal street drugs, central nervous system (CNS) depressants, including benzodiazepines (e.g., alprazolam [Xanax], diazepam [Valium], lorazepam [Ativan], clonazepam [Klonopin]; benzos, xannies), and barbiturates (Seconal, Amytal, Phenobarbital; reds, yellows, yellow jackets, barbs) are legal substances which can be prescribed by a medical doctor. With low or moderate doses, they produce euphoria and disinhibition as well as decreased respiration, pulse, and blood pressure. At higher doses, confusion, impaired judgment, coordination, and memory loss occur. CNS depressants are particularly dangerous when combined because this increases the risk of respiratory depression and arrest. With long-term use, tolerance occurs and discontinuation of use can cause symptoms ranging from anxiety, insomnia, nausea, and muscle tension to more severe symptoms such as seizures, hallucinations, and psychosis.

Opioids (e.g., codeine, fentanyl, oxycodone) can be prescribed by a medical doctor for pain relief, yet are also commonly misused. Illicit opioids include opium (big O, tar) and heroin (dope, H, junk, smack). The effects of intoxication include euphoria, sedation, drowsiness, confusion, nausea, constipation, and respiratory depression. High doses of opioids can lead to coma and death. With prolonged use, tolerance occurs and, in the absence of the drug, users experience craving, sweating, fever, diarrhea, vomiting, and pain.

Unlike CNS depressants and opiates, stimulants increase respiration, heart rate, and blood pressure, and decrease appetite. Stimulants include cocaine (crack, coke, blow, yayo), methamphetamine (meth, speed, crystal, crank), MDMA (ecstasy, E, X, Adam), amphetamines (e.g., Adderall, Dexedrine; speed), and methylphenidate (e.g., Ritalin, Concerta, Daytrana; vitamin R, skippy, R-ball). Some stimulants can be obtained with a prescription from a medical doctor (e.g., amphetamines, methylphenidate), although they are categorized as controlled substances and their use is illegal without the appropriate prescription. Meanwhile, other stimulants (e.g., cocaine, methamphetamine) are illegal. Stimulant intoxication produces euphoria, mental alertness, and increased energy. Impulsive behavior, aggressiveness, anxiety, and irritability are also common features experienced by users. Additionally, prolonged use or high doses of stimulants can result in stimulant-induced psychosis. Due to the stress placed on the cardiovascular system, stimulant use can cause cardiac arrest, stroke, and death. Tolerance can occur quickly, and withdrawal symptoms include anxiety, anhedonia, irritability, insomnia, and depression.

Dissociative anesthetics include ketamine (special K, vitamin K) and PCP (angel dust, hog, ozone, rocket fuel, wack). They can be, but are rarely, prescribed by a medical doctor for mental health conditions. They create a dream-like state, euphoria, numbness, increased heart rate and blood pressure, and impaired memory and motor function. At high doses, ketamine can cause delirium, respiratory depression, and arrest. PCP use can result in panic, aggression, depression, and violence. Users of dissociative anesthetics quickly experience increasing tolerance, and a permanent tolerance may develop after several months of use. Although tolerance occurs, these drugs do not appear to have withdrawal symptoms.

Inhalants include a range of obtainable solvents (e.g., glues, paint thinners, gasoline, lighter fluid), gases (e.g., propane, butane, aerosol propellants, nitrous oxide; laughing gas, whippets, chloroform), nitrates (isobutyl, isoamyl; poppers, snappers), and aerosols (e.g., hair spray, spray paint). Inhalants are “huffed” through the nose and mouth and enter the lungs and subsequently the bloodstream rather quickly. The effects of intoxication include loss of motor skills and inhibition, slurred speech, headache, nausea, wheezing, and loss of consciousness. Extended use can lead to muscle weakness, memory impairment, depression, damage to the nervous and cardiovascular systems, and sudden death. There is little known about the tolerance and withdrawal of inhalants.

Synthetic cathinones (bath salts, vanilla sky, cloud nine, plant food) typically take the form of white or brown crystal-like powder that can be used in a variety of methods such as swallowing, snorting, smoking, or injection. They were originally manufactured and marketed as “legal highs,” but have since been subject to federal bans. The physiological effect of synthetic cathinones is still largely unknown, but they are known to have similar chemical properties to amphetamines, cocaine, and MDMA. Users of synthetic cathinones report increased energy and agitation, accompanied by increased heart rate and blood pressure. Additional effects include paranoia, hallucinations, increased sociability and sex drive, panic attacks, and excited delirium (e.g., extreme agitation and violent behavior). Withdrawal symptoms include depression, anxiety, tremors, insomnia, and paranoia.

Comorbidity

Substance use disorders co-occur with many clinical disorders, ranging from depression and anxiety disorders to personality disorders. National epidemiological data suggest that among individuals with any substance use disorder, the prevalence rates for any mood and anxiety disorder are 40.9% and 29.9%, respectively (Conway, Compton, Stinson, & Grant, 2006). Mood and anxiety disorders are the most common comorbidities, followed by antisocial personality disorder (Jane-Llopis & Matysina, 2006) and schizophrenia-spectrum disorders (Kushner, Abrams, & Borchardt, 2000). Among personality disorders, borderline and antisocial personality disorders have the highest rates of co-occurrence with substance use disorders, with estimates ranging from 5% to 32% and 14% to 69%, respectively (e.g., Goldstein et al., 2007; Trull, Sher, Minks-Brown, Durbin, & Burr, 2000). Additionally, prevalence of disorders differs by substance. For example, among individuals with DSM-IV lifetime opioid abuse or dependence, nearly 50% met the criteria for a personality disorder (Grella, Karno, Warda, Niv, & Moore, 2009b). These statistics are particularly alarming given that individuals with co-occurring disorders generally have worse treatment outcomes (e.g., noncompliance and relapse), higher rates of suicidal ideation, chronic physical health problems, distorted perception and cognition, social exclusion, aggression, legal problems, and homelessness (e.g., Horsfall, Cleary, Hunt, & Walter, 2009; McCauley, Killeen, Gros, Brady, & Back, 2012).

The causal direction of co-occurring conditions is mixed, with some evidence that mental disorders serve as risk factors predicting the onset of substance use disorders (Kessler, 2004; NIDA, 2009). Stronger predictors of the onset of substance use disorders include major depression, disruptive behavior disorders, bipolar disorder, as well as anxiety disorders, excluding generalized anxiety disorder, post-traumatic stress disorder (PTSD), and agoraphobia (Swendsen et al., 2010). Alternatively, other studies have found that substance use disorders predict later mental illness (Kessler, 2004; NIDA, 2009), as well as suicide (Yen et al., 2004) and mortality (Clark, Martin, & Cornelius, 2008). In addition, there is growing evidence for substance-induced disorders, such as stimulant- and cannabinoid-induced psychosis. Psychotic symptoms are estimated to occur in approximately 40% of amphetamine-dependent patients, although these symptoms are very likely to dissipate in 1–3 days. Cannabinoid use has been found to exacerbate the risk for psychosis in individuals who already carry a predisposition for psychosis. Additional studies have found differences in demographic (e.g., homelessness, older), familial (e.g., less family support), and clinical characteristics (e.g., greater awareness of psychotic symptoms) distinguishing substance-induced psychosis from a primary psychotic disorder (Caton et al., 2005). Temporary substance-induced depressive and anxiety symptoms have also been reported in the context of drug intoxication and withdrawal (Ahmadi & Ahmadi, 2005; Schuckit, 2006).

Assessment

Several variables need to be considered when determining the best method of assessment. It is important to determine if the goal of the assessment is to screen for potential substance use problems, to determine if an individual meets diagnostic criteria for a substance use disorder, to develop treatment goals and a treatment plan, or to assess treatment outcome. Commonly used psychological measures for screening, diagnosis, treatment planning, and post-treatment outcome measurement in line with DSM-5 criteria and diagnoses are outlined in  Table 19.1 .

Table 19.1  Instruments for the Screening and Diagnosis of DSM-5 Substance Use Disorders

Instrument	Summary	Method of Administration	Population
Screening
CAGE-AID (Brown & Rounds, 1995)	A four-item screener for substance use problems. Each “have you ever?” question can be answered either “yes” or “no,” and each positive response gets one point. A score of 1 out of 4 indicates “possible” and a score of 2 detects most cases of substance misuse.	Interview or self-report	Adults; Adolescents
Drug Abuse Screening Test – 10 (DAST-10) (Skinner, 1982)	A 10-item measure adapted from the original DAST to be a brief screening tool for drug use in the past 12 months.	Interview or self-report	Adults
National Institute on Drug Abuse (NIDA) Quick Screen (NIDA, 2009)	An online, clinician screening tool used in general medical settings to identify risky substance use. It generates a substance involvement score (SI), determines risk and a recommended level of intervention, and provides additional resources.	Interview; clinician-administered	Adults
Diagnostic status
Structured Clinical Interview for DSM-5 (SCID-5; First, Williams, Karg, & Spitzer, 2014)	A precise method for identifying substance use disorder across 10 drug classes according to DSM-5 criteria. It is the most frequently used instrument in clinical trials.	Interview; clinician-administered	Adults: Adolescents
Mini International Neuropsychiatric Interview 7.0 (MINI 7.0; Sheehan, 2014)	A structured interview used for identifying substance use disorder and severity according to DSM-5 criteria.	Interview; clinician-administered	Adults
Treatment planning and outcome
Addiction Severity Index (ASI; McLellan et al., 1992)	The most comprehensive and widely used measure. Assesses substance use in the context of seven domains: medical status, employment status, family history, legal status, psychiatric status, and family and social relationships. It identifies problem areas in need of targeted intervention and is often used in clinical settings for treatment planning and outcome evaluation.	Interview or self-report	Adults
Drug Use Screening Inventory (revised) (DUSI-R; Kirisci, Hsu, & Tarter, 1994)	A 149-item measure assessing the severity of drug and alcohol problem in 10 psychosocial and psychiatric domains: behavior patterns, drug consequences, health status, psychiatric disorder, social competency, family system, school performance, work adjustments, recreation, and peer relationships. A “lie scale” is built in to ensure truthfulness and increase reliability by identifying inconsistencies.	Interview or self-report	Adults; Adolescents
Inventory of Drug Use Consequences (InDUC-2R for recent or -2L for lifetime use; Tonigan & Miller, 2002)	A 50-item inventory of alcohol-related consequences. It is distinct from screening instruments in that it measures adverse consequences of substance use, including items referring to pathological use practices (e.g., rapid use), items reflecting dependence symptoms (e.g., craving), and items concerning help-seeking (e.g., Narcotics Anonymous). Includes five scales including impulse control, social responsibility, and physical, interpersonal, and intrapersonal domains.	Self-report	Adults
Timeline Followback (TLFB; Fals-Stewart, O'Farrell, & Freitas, 2000)	Assesses recent substance use by asking the client to retrospectively report use in a defined period prior to the interview date. In addition to capturing use, the TLFB can also identify frequency of use.	Interview or self-report	Adults; Adolescents
Motivation and treatment readiness
University of Rhode Island Change Assessment (URICA; McConnaughy, Prochaska, & Velicer, 1983)	Measures the stages of change (pre-contemplation, contemplation, action, and maintenance) using a five-point Likert scale. Assesses readiness to change when clients enter treatment.	Self-report	Adults; Co-occurring disorders
Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES; Miller & Tonigan, 1996)	Assesses motivation for change, in relation to alcohol and drug use, using three factorially derived scores: (1) recognition, (2) ambivalence, and (3) taking steps.	Self-report	Adults
Circumstances, Motivation, Readiness, and Suitability (CMRS) Scales (De Leon, Melnick, Kressel, & Jainchill, 1994)	Scales used to predict retention in therapeutic community treatment across four interrelated domains: (1) circumstances (external pressures), (2) motivation (intrinsic pressures), (3) readiness, and (4) suitability.	Self-report	Adults; Adolescents

Screening and Treatment Planning

Given the high rate of comorbidity between substance use disorders and other psychological disorders, particularly mood, anxiety, or thought disorders, patients often present to treatment for problems other than substance use. As such, screening measures are useful for identifying substance use disorders in other settings. Several diagnostic instruments are available for use in both research and clinical settings, with advantages and disadvantages inherent in each instrument with regard to administration, cost, and interviewer qualification and training requirements.

Once a substance use problem or diagnosis is established, it is important to assess how the patient's frequency and severity of substance use has affected other life areas (e.g., social and occupational functioning) in order to develop appropriate treatment goals and a treatment plan. For example, by assessing how much time the patient spends obtaining and using the substance, in addition to time spent recovering, the clinician will likely gain a better sense of the extent of impairment and, as such, which intervention might be most efficacious. Additional assessment techniques are utilized prior to and during treatment in order to target processes such as treatment planning, utilization of services, and goal attainment. Traditional models of substance use assessment and treatment planning have been based upon the transtheoretical model, which outlines stages of change in behavior in efforts to improve treatment outcomes (DiClemente & Prochaska, 1998). However, more recent evidence suggests that these models need to be reconsidered in order to integrate factors that will more clearly characterize the development and maintenance of substance use (Sutton, 2001), such as cognitive (e.g., executive control dysfunction; Blume & Marlatt, 2009), environmental, and social components (Selbekk, Sagvaag, & Fauske, 2015).

Functional analysis is often employed in substance use treatment to help patients effectively problem-solve ways to reduce the probability of future use. Within this model, an analysis of the antecedents and consequences of substance use is used to develop alternative cognitive and behavioral skills to reduce the risk of future substance use. Working together, the therapist and patient identify five high-risk situations and the (1) trigger for that situation, (2) thoughts during that situation, (3) feelings/emotions experienced in response to the trigger and thoughts, (4) substance use behavior, and (5) positive and negative consequences of substance use. In the context of consequences, emphasis is placed on acknowledging the short-term and immediate positives (e.g., relief) versus the larger-magnitude and longer-term negative (e.g., legal trouble, relationship problems, health) consequences. After constructing this personalized behavior chain, the therapist and patient engage in treatment planning to develop empirically supported strategies for altering behaviors and/or thoughts when faced with those same situations. Such strategies include behavioral activation (i.e., generating value-based alternative behaviors), mindfulness, assertiveness training, and fostering social support. Those interested in the use of functional analysis in treatment are directed to Marlatt and Donovan (2007).

Comprehensive outcome assessments include a wide range of dimensions beyond substance use behavior, such as changes in social, occupational, and psychological functioning. It is therefore ideal to readminister comprehensive measures such as the Addiction Severity Index (ASI), Drug Use Screening Inventory – Revised (DUSI-R), and Inventory of Drug Use Consequences (InDUC-2R) (see  Table 19.1 ). In addition, self-report and biological indicators can be used to determine return to substance use, substance use behavior, and psychiatric symptoms.

Recent developments in Ecological Momentary Assessment (EMA) provide a suitable method to collect data on substance use behaviors, prompting individuals to answer brief information about their behaviors, thoughts, and feelings while continuing to interact in their natural environment (see Ferguson & Shiffman, 2011 for a detailed discussion). It provides the unique opportunity to track episodic behavior, emphasizing the role of immediate situations, while also recording information on an individual's internal experience (e.g., mood, craving). Notably, this assessment method avoids the pitfalls of retrospective recall and the difficulty of cultivating ecological validity in laboratory or medical settings. In addition, EMA boasts high compliance by utilizing signaled assessments, prompting individuals to report symptomology and measures of functioning in real time.

Biological Detection

The following is a brief overview of recent trends in the biological assessment of substance use (for a review, see Vearrier, Curtis, & Greenberg, 2010). Although recent work has identified cutting-edge technologies for biological testing of substance use, urinalysis remains the preferred method of detection for several reasons. First, because urinalysis has been used historically, it is well known and many of the problems associated with it have been addressed. Second, urine contains high concentrations of the target substance or its metabolites. Third, it is inexpensive and may be acquired in a minimally invasive manner compared with other biological approaches. Self-contained urine-based testing kits that can reliably detect the most commonly used psychoactive substances are becoming increasingly available, allowing practitioners and researchers to conduct on-site testing across a wide range of settings. Finally, recently developed quantitative and semi-quantitative tests are more sensitive to changes in the pattern, frequency, and amount of use (Preston, Silverman, Schuster, & Charles, 2002). Thus, in addition to indicating the presence or absence of a drug, quantitative urinalysis can be useful in detecting initial efforts to reduce substance use and monitor the effects of treatments.

While urinalysis has several advantages and obvious clinical utility, several limitations remain. Urine can only reliably indicate drug use in the previous 1–3 days (except for cannabis, methadone, and diazepam), thereby increasing the reliance on self-report for longer-term follow-up periods. In addition, urine is easily adulterated by using chemicals such as bleach, vinegar, or liquid soap, and can be easily diluted by using old urine or someone else's urine. Conversely, over-the-counter medications and certain foods can produce positive test results in the absence of illicit drug use. As such, careful attention to detail and procedures is needed to ensure accurate collection, and positive tests may need additional confirmation.

Blood collection can detect very recent drug use and is considered an ideal method for assessing quantitative levels when accuracy is the primary criterion for measure selection. However, blood is often not collected due to its invasive nature and reliance on trained personnel. Accordingly, blood is predominately used in forensic environments.

Saliva is the only body fluid that can be used as a substitute for blood, as drug concentration levels are comparable. Saliva collection has the advantage of being easy to obtain and is cost-effective because, similar to urinalysis, self-contained testing kits are widely available, eliminating the need for trained personnel and off-site testing. Saliva testing is typically used in outreach units and prisons. One collection procedure often utilized is the Salivette sampling device. It consists of a cotton wool swab, which is placed in the patients' buccal (cheek) cavity for saliva collection by absorption. Drawbacks to saliva collection include difficulty collecting an adequate amount for drug detection, and the possible contamination of the oral cavity as a result of oral, intranasal, and nicotine drug use. In addition, the validity of saliva collection is not yet well established.

Hair testing has been developed and theorized to have the potential benefits of drug detection over a longer period of time (up to 3 months), which is not possible with the aforementioned methods. However, quality control criteria and standard laboratory methods have yet to be established. In addition, evidence indicates that drug detection may differentially appear in darker hair (e.g., black), leading to a bias toward missing drug use in blond individuals or those with treated (e.g., bleached) hair. In addition, hair is sensitive to smoke in the air, resulting in a false-positive for individuals who abstain yet are surrounded by people who have smoked drugs.

Sweat testing may be used for detection of recent drug use (i.e., < 24 hours) using a cotton wipe or by utilizing “patch technology,” during which individuals wear a patch for a period of several weeks, providing a longer time period than other testing methods previously discussed (for a review, see De Giovanni & Fucci, 2013). Patch technology is often utilized for surveillance (i.e., continuous monitoring) of drug use. While oxygen, carbon dioxide, and water vapor are able to escape through the patch, drugs are retained in the patch. Advantages of this method include minimal invasiveness and fewer ethical issues than those surrounding blood or urine testing. Challenges utilizing sweat testing include difficulties creating a sweat collection device that is universal despite intra- and interindividual variation in sweat drug concentrations, environmental contamination of patches before application and after removal, and the unknown effect of vigorous or prolonged exercise on the deposition of drugs onto the patch. Further research needs to be conducted in order to more precisely establish the permeability of the patch membranes, as well as to characterize reabsorption properties of the patches across different drug classes.

Etiological Considerations

Genetics

Behavioral Genetics

Findings from twin, adoption, and family studies suggest that genetic factors account for a significant portion of the variance in liability for substance use disorders. Indeed, substance use disorders are some of the most highly heritable psychiatric disorders, with heritability estimates of 0.40 for stimulant use disorder, 0.43 for cannabis use disorder, 0.51 for sedative use disorder, 0.56 for alcohol use disorder, and 0.72 for cocaine use disorder (for a review, see Bienvenu, Davydow, & Kendler, 2011). The magnitude of genetic influence on substance use varies over the course of development, beginning with a negligible amount of genetic influence during early adolescence that increases over time until it stabilizes by age 35–40 years (Kendler, Schmitt, Aggen, & Prescott, 2008). Some research suggests that the majority of the genetic vulnerability for substance use disorders can be accounted for by shared genetic influences that are common across substance classes (Agrawal, Neale, Prescott, & Kendler, 2004; True et al., 1999; Tsuang et al., 1998), while other research demonstrates support for substance-specific genetic factors (Agrawal & Lynskey, 2008), such as genetic differences in metabolism and hedonic effects (Lyons et al., 1997). These findings point to significance of genetic factors in addiction liability, as well as the importance of studying genes that are involved in neurobiological substrates that are common and specific to substance use disorders.

Molecular Genetics

Evidence exists for a relationship between substance use disorder and specific genetic polymorphisms (variations in DNA structure), in particular the γ-aminobutyric acid (GABA) receptor genes on chromosome 4. Convergent evidence suggests that polymorphisms, specifically in GABA2, are associated with cannabis use and polysubstance abuse (Agrawal et al., 2008a,b; Drgon, D'Addario, & Uhl, 2006). In addition, dynorphin peptides, derived from the prodynorphin (PDYN) precursor polymorphisms are associated with opioid addiction (Clarke et al., 2012). Evidence from genome wide association studies (GWAS) has converged to implicate a cluster of nicotinic acetylcholine receptor (nAChR) subunit genes in drug use. More specific to heroin addiction, GWAS have provided evidence for the involvement of multiple genes, including μ-opioid receptor coding genes, metabotrpic receptors mGluR6 and mGluR8, nuclear receptor NR4A2, and cryptochrome 1 (Nielson et al., 2008). Meta-analytic approaches have also provided convergent evidence for the role of nAChR subunit genes, including CHRNA3 and CHRNA5, in cocaine dependence (Grucza et al., 2008).

Additional genes that increase the risk of substance use disorders include polymorphisms in dopamine receptor genes that play a role in reward and reinforcement behavior (Blum et al., 2000). A meta-analysis including 55 studies confirmed the A1+ allele of DRD2 as a marker of substance use and severe substance misuse (Young, Lawford, Nutting, & Noble, 2004). Similarly, a polymorphism in the DAT1 gene has been associated with cocaine use (Guindalini et al., 2006). Furthermore, the CNR1 gene has been associated with several types of substance use, including cocaine, amphetamine, heroin, and cannabis (Comings et al., 1997; Proudnikov et al., 2010). Recent meta-analyses provide additional support for the involvement of genes that play a role in reward and reinforcement behavior in the development and maintenance of substance use across substance classes (reviewed by Li & Burmeister, 2009), suggesting that genes encoding for dopaminergic functioning may modulate substance use disorder liability across substance classes.

Gene–Environment Interactions

Beyond examining genetic factors in isolation, environmental risk factors have been shown to interact with genes to contribute to the development of substance use disorders. Although the majority of research examining gene–environment interactions in substance use has focused on alcohol use disorder, accumulating evidence suggests that early-life stress may result in widespread alterations in stress circuitry, increasing the likelihood of physical changes serving as risk factors for substance use. For example, the GABRA2 gene has been associated with substance use, namely heroin and cocaine, particularly for individuals who have experienced severe childhood maltreatment (Enoch et al., 2010; Soyka et al., 2008). In addition, there is a significant interaction between the 7R+ genotype (variation in the DRD4 dopamine receptor gene) and attachment history, more specifically for avoidant and anxious attachments in predicting cannabis use in young adulthood (Olsson et al., 2011). Taken together, genetic risk factors for substance use may be moderated by environmental variables, suggesting that as genetic researchers continue to incorporate environmental measures into their studies, additional gene–environment interactions may be revealed.

Learning and Habituation

Theories of learning and conditioning have been utilized to understand the development and maintenance of substance use disorders, and as a result, studies have been initially conducted in laboratory animals and humans that support the notion of drugs as reinforcers (for a review, see Higgins, Heil, & Lussier, 2004), with drug use theorized to be a form of operant behavior influenced by antecedents and consequences. Drug self-administration studies with humans have been used to examine the powerful influence of nondrug reinforcers on heroin and cocaine use (Comer, Collins, & Fischman, 1997; Greenwald & Steinmiller, 2009; Higgins et al., 1994). Thus, with continued substance use, substance use-seeking and -taking become habit-based processes formed from reinforcement learning (McKim, Bauer, & Boettiger, 2016).

Accordingly, the behavioral economics perspective posits that delayed reinforcers are discounted by individuals with substance use disorders (Bickel & Marsch, 2001). In other words, the value of delayed reinforcers is discounted compared with immediate reinforcers. Most notably, during the development of substance use disorders, the more immediate and hedonic expectancies surrounding the effects of drugs are valued over the more long-term and positive consequences of being abstinent. Accordingly, substance users demonstrate higher discount rates for delayed rewards across substance classes (e.g., heroin, such that there is greater reduction in the value of a future reward as the delay to obtain that reward increases; for a review, see MacKillop et al., 2011).

In line with the behavioral economics perspective, the reinforcing value of drug use is critically influenced by the environmental context of other available reinforcers. Accordingly, research has revealed a relationship between the degree of substance use and engagement in substance-free activities. High rates of drug use are most likely in contexts without substance-free sources of reinforcement, and drug use will generally decrease if access to alternative reinforcers is increased (Higgins et al., 2004). Individuals with fewer alternative behavioral choices will be more likely to develop a substance use disorder. Additionally, clinical research has reported positive outcomes for treatments based upon reinforcement theories such as contingency management (e.g., Prendergast, Podus, Finney, Greenwell, & Roll, 2006), behavioral activation (Daughters, Magidson, Lejuez, & Chen, 2016a), and a community reinforcement approach (e.g., Abbott, 2009).

Executive Functioning

Executive functioning is implicated in behavior and emotion regulation and control, and includes the constructs of impulsivity, decision-making, and attentional bias. Neurobiological research has identified disruption of the prefrontal cortex (PFC), integrally involved in executive functioning processes, as a central feature of substance use disorders. Accordingly, disruption of the PFC is thought to lead to the impaired response inhibition and salience attribution syndrome (Goldstein & Volkow, 2011), which is characterized by behavioral manifestations of four core clinical symptoms: intoxication, bingeing, withdrawal, and craving. Through altered attentional processes, substance users attribute excessive salience to substances and substance-related cues, decreasing their ability to inhibit maladaptive behaviors. After habitual use, substance-seeking and -taking become the main motivational drive, culminating in persistent use despite experiencing negative consequences associated with substance use.

As a result of PFC disruption, processes critical to emotion, cognitive, and behavioral functioning are negatively affected, such as impulsivity, decision-making, and attention. Impulsivity has been associated with the initiation and continued use of substances (De Wit, 2009; Field, Schoenmakers, & Wiers, 2008; Johnson, Bickel, Moore, Badger, & Budney, 2010; Petry & Casarella, 1999), as well as the severity of substance use (Hester, Nestor, & Garavan, 2009). Such deficits in impulsivity have been evidenced by poorer behavioral performance on impulsivity tasks and aberrant activation in neural regions associated with impulsivity among substance users. In addition to impulsivity, reduced ability in decision-making has been found in substance users, such that chronic administration of substance use causes neuronal changes that alter a person's ability to choose nonrisky alternative behaviors, though others argue that the decision-making mechanism is already weak in individuals who are prone to addiction (Bechara, 2005). For instance, using the Game of Dice Task (Brand et al., 2004), Brand et al. (2008) found that opiate users exhibited a preference for decisions that led to more negative long-term consequences and made riskier choices compared with matched controls. In addition to impulsivity and decision-making, attentional processes have a central role in the development and maintenance of substance use disorders. The relationship between attentional bias and substance use disorders has demonstrated that substance users attend more to substances and substance-related stimuli, and this, in turn, is associated with greater subjective craving (Costantinou et al., 2010; Field, Munafo, & Franken, 2009; Hester, Dixon, & Garavan, 2006; McCusker & Gettings, 1997) and substance use (Stacey & Wiers, 2010). Thus, individuals with deficits in executive function are more likely to develop a substance use disorder, and also more likely to relapse after attempted abstinence. Additionally, clinical research utilizing brain stimulation techniques, such as transcranial magnetic stimulation and transcranial direct current stimulation, targeting the PFC and reward-related regions, report positive outcomes, such as reduced substance use and related symptomology as treatments (for a review, see Feil & Zangen, 2010).

Neuroanatomy and Neurobiology

Several neurobiological models have been proposed to explain how chronic substance use contributes to the development of substance use disorders and vulnerability to relapse, with a great deal of emphasis placed on the role of neuroadaptive changes that take place in brain reward and stress, incentive salience and habit formation, and executive function circuits over the course of chronic substance use (e.g., Koob & LeMoal, 2001, 2008; Koob & Volkow, 2016; Li & Sinha, 2008; Robinson & Berridge, 1993, 2001; Wise, 1980, 2002). The following sections will discuss neurobiological mechanisms that increase liability to substance use across substance classes, as well as the neurobiological changes that contribute to development and maintenance of substance use disorders.

Brain Reward Circuits

One pharmacological effect that is common to all drug addiction is increased activation in the mesocorticolimbic dopamine pathway of the brain (Koob & Volkow, 2010; Pierce & Kumaresan, 2006) underlying motivational and reward-related processes in substance use (Salamone & Correa, 2012). Dopamine neurons project from the ventral tegmental area to the ventral striatum and PFC, and dopaminergic functioning in these regions is believed to be a key component of the brain reward systems, which are critical for the reinforcing properties of drugs. Human neuroimaging studies show that acute administration of nearly all substances leads to increased activation in mesolimbic dopaminergic regions, and that this activation correlates with subjective ratings of high or euphoria and craving. However, chronic drug administration and acute withdrawal are associated with alterations in this pathway, characterized by decreases in extracellular dopamine, reduced D2 receptor availability, and reduced dopamine transmission in frontal and ventral striatal regions (for detailed reviews, see Koob & LeMoal, 2008; Sinha, 2008; Volkow, Wang, Fowler, Tomasi, & Telang, 2011). In sum, neuroadaptive changes take place in dopaminergic circuits over the course of chronic drug use. These changes contribute to the aversive affective symptoms that are common during withdrawal, which may drive individuals to relapse to drug use in order to escape this aversive state (Koob & LeMoal, 2008; Koob & Volkow, 2010). As such, alterations in dopaminergic functioning appear to be an important neurobiological mechanism underlying the development and maintenance of substance use disorders.

Brain Stress Circuits

The hypothalamic–pituitary–adrenal (HPA) axis and its primary hormone, cortisol, play a central role in mediating the body's response to stress, including behavioral, emotional, and additional physiological changes. The HPA axis is extremely sensitive to inputs from the limbic system and PFC, two brain areas that are important for modulating reinforcement and motivational processes (e.g., Li & Sinha, 2008; Schwabe, Dickinson, & Wolf, 2011). In animal models of substance use, evidence suggests that rats with elevated HPA axis reactivity to stress show greater self-administration of addictive substances (Piazza, Deminiere, Le Moal, & Simon, 1989, 1990; Piazza, Derouche, Rouge-Pont, & Le Moal, 1998; Piazza et al., 1991, 1996), and administration of exogenous corticosteroids to rats that were low-level responders led to an increased risk that these rats would begin to self-administer amphetamines (Piazza et al., 1991). Evidence also suggests that HPA axis activation, and subsequent release of adrenocorticotropic hormone and cortisol in response to stress, is associated with increased dopaminergic neurotransmission in mesolimbic reward circuits (Dunn, 1988; Kalivas & Duffy, 1989; Piazza & LeMoal, 1996; Prasad, Sorg, Ulibarri, & Kalivas, 1995; Thierry, Tassin, Blanc, & Glowinski, 1976), suggesting that reactivity in brain stress circuits plays an important role in both substance use liability and reinforcement.

Accordingly, population-based and epidemiological studies show evidence for the role of elevated stress, in the form of early life stress, trauma, and accumulated adversity in the development and maintenance of substance use, as well as substance use outcomes (Fox & Sinha, 2009; Sinha, 2008). Adolescent exposure to stressful life events, such as parental alcoholism or financial difficulty, has been shown to increase emotional and behavioral problems that intensify the risk for developing a substance use disorder (King & Chassin, 2007). Furthermore, populations dealing with chronic stress, including emotional stressors ranging from violence and loss to trauma, poor social support, and interpersonal conflict, have evidenced higher vulnerability to substance use disorders (Sinha, 2008).

Neuroadaptation in Reward and Stress Circuitry

Neurobiological models of drug addiction hypothesize that reward and stress circuits in the brain become dysregulated in response to chronic substance use, and this dysregulation contributes to the establishment of a “negative affect” or psychologically distressed state during withdrawal and continued abstinence, which increases the reinforcing effects of drugs and thus vulnerability to relapse following cessation (Koob, 2009; Koob & Le Moal, 2001, 2008; Koob & Volkow, 2010). Specifically, when reward pathways (i.e., the mesocorticolimbic dopamine system discussed previously) are activated by drug administration, opposing anti-reward systems (i.e., brain stress systems localized in the central nucleus of the amygdala and the bed nucleus of the stria terminalis) are recruited to limit reward function and maintain homeostasis. Over the course of chronic drug administration, neuroadaptive changes occur in response to the excessive utilization of brain reward systems, including subsequent decreases in activation of brain reward systems and increases in opposing brain stress circuits. Such a combination of depressed reward circuits and elevated anti-reward circuits is hypothesized to be the driving force motivating continued drug-seeking and -taking behaviors (Koob, 2008; Koob & Le Moal, 2008).

Furthermore, elevated brain stress activation is hypothesized to reduce an individual's ability to adapt to or cope with additional stressors during abstinence, thereby driving vulnerability to stress-induced relapse. This is in line with the negative reinforcement theory of addiction, which states that the motivation for substance use is the reduction or avoidance of negative emotional states (Baker, Piper, McCarthy, Majeskie, & Fiore, 2004). Similarly, evidence indicates that a behavioral proxy of negative reinforcement, namely low distress tolerance, is associated with poor substance use outcomes (Daughters et al., 2005a; Daughters, Lejuez, Kahler, Strong, & Brown, 2005b; Strong et al., 2012). In addition, reduced functional connectivity between neural regions is associated with goal-directed behavior during affective distress (Daughters et al., 2016b). Similarly, other studies have examined disruptions in medial prefrontal activity, implicated in self-control among substance users while under stress and during increased craving (Sinha, 2013). Taken together, neurobiological models suggest that chronic substance use is associated with neuroadaptive changes, including decreases in reward system activation and increases in anti-reward system functioning, particularly under the experience of stress and craving, which may serve to maintain compulsive drug-seeking and -taking behaviors, even after protracted periods of abstinence.

Specific Populations

Sex and Gender

Existing research has demonstrated that women differ from men in their pathways to drug addiction. Compared with men, women are less likely to have a substance use disorder, and onset of their substance use disorder tends to be later in life. Yet women become dependent at a quicker rate and experience more severe consequences of substance use over shorter periods of time (e.g., Hser, Huang, Teruya, & Anglin, 2004). This accelerated development to chronic use has been termed telescoping, and this trend has been consistently documented (Greenfield, Back, Lawson, & Brady, 2010). For women, the pathway to substance use is often relationship-based; for instance, women are more likely to initiate and continue substance use in the context of an intimate partner relationship (Frajzyngier, Neaigus, Gyarmathy, Miller, & Friedman, 2007; Tuchman, 2010), and following treatment, women's substance use is more likely to be influenced by their partners' continued substance use, as compared with men (Grella, Scott, Foss, & Dennis, 2008). Furthermore, women with substance use disorders are also more likely than men with substance use disorders to have a partner who uses illegal drugs (Westermeyer & Boedicker, 2000).

With regard to treatment, co-occurring psychiatric disorders are more common among women and also create a barrier to treatment. As indicated in a review by Greenfield et al. (2007), women have higher rates of comorbid eating disorders, mood and anxiety disorders, and PTSD, which subsequently make it difficult for them to find appropriate treatment to manage both disorders. Gender differences in stress reactivity may be one important mechanism underlying these differences. In a review, Fox and Sinha (2009) reported that, compared with substance-abusing men, women may experience increased emotional sensitivity to changes in the stress system, and the resulting neuroadaptations in autonomic function and affect may alter vulnerability to co-occurring disorders, possible relapse, and treatment outcome.

Women also face unique barriers to treatment engagement that may explain a reduced likelihood to enter treatment compared with men. For instance, barriers relating to child-rearing responsibilities, including limited access to child care services, as well as society's punitive attitude toward substance use by women as child bearers, present just some of the major treatment barriers for women suffering from substance use disorders (e.g., Greenfield et al., 2007). Moreover, women also differ from men in their response to treatment. Data on this topic have proven to be somewhat conflicting: whereas some researchers have reported that women are more likely than men to drop out of substance abuse treatment (King & Canada, 2004), others have proposed a complex interaction of gender and treatment modality (e.g., methadone vs. drug-free programs; Joe, Simpson, & Broome, 1999; McCaul, Svikis, & Moore, 2001; Simpson, Joe, Rowan-Szal, & Greener, 1997). There is also evidence that women are more likely than men to complete treatment (Hser, Huang, Teruya, & Anglin, 2004). The reasons underlying these discrepancies are unknown, but highlight the importance of investigating sex and gender differences in future research, which is particularly critical given the increasing prevalence of women with substance use disorders (Tuchman, 2010).

Race and Ethnicity

Studies suggest there are unique risk and protective factors arising from cultural differences such as acculturation-related stressors, cultural orientation, parenting styles, and discrimination that influence the developmental trajectories of substance use through adulthood (e.g., Gibbons et al., 2010; Kulis, Marsiglia, & Nieri, 2009; Thai, Connell, & Tebes, 2010), resulting in differential needs among minority substance users. For instance, racial-ethnic minorities who reside in inner city areas are particularly vulnerable to substance use and risky sexual behavior as a result of higher levels of poverty, violence, general risk practices, and availability of street drugs (e.g., Avants, Marcotte, Arnold, & Margolin, 2003). Importantly, there are large racial-ethnic disparities in access, referral, and utilization of treatment services, and evaluations of the substance abuse treatment system have shown that racial-ethnic minorities are underserved (Delphin-Rittmon et al., 2012; Marsh, Cao, Guerro, & Shin, 2009). Aside from Asian Americans, all racial groups have a larger treatment gap than Whites (Schmidt & Mulia, 2009), and among treatment-seeking individuals, African Americans and Hispanics are more likely than Whites to report unmet needs (Wells, Klap, Koike, & Sherbourne, 2001). Moreover, these differences exist even after adjusting for other demographic factors such as criminal history and socioeconomic status (Le Cook & Alegria, 2011).

As with other health care access issues, racial-ethnic differences in accessing substance use treatment services may result from underlying differences in barriers to care. Factors such as perceived discrimination, prior negative experiences associated with services, and limited knowledge of available services may provide a better understanding of why there is an unmet need among those who perceive need for substance use treatment in minority groups (Grella, Karno, Warda, Moore, & Niv, 2009a), and data indicate that Whites experience half the rate of barriers than do African Americans and Hispanics (Perron et al., 2009). Looking beyond access and utilization of treatment, treatment outcome studies suggest mixed findings when exploring racial-ethnic minorities compared with Whites. Some data indicate that members of minority groups are less likely to complete and/or seek treatment, receive fewer treatment services, and are less likely to achieve recovery (Jerrell & Wilson, 1997; Rebach, 1992). However, research indicates that minority clients do not differ from nonminority clients in their response to treatment (e.g., Pickens & Fletcher, 1991) and in treatment outcomes (Niv, Pham, & Hser, 2009).

Sexual Orientation

Adults and adolescents with a minority sexual orientation (e.g., lesbian, gay, bisexual) are at greater risk for substance use and are more likely to use substances than are their heterosexual peers (for reviews, see Green & Feinstein, 2012; Marshal et al., 2008). Some data indicate that increased odds of substance use among lesbian, gay, and bisexual adults may be due to experiences such as discrimination (McCabe, Bostwick, Hughes, West, & Boyd, 2010) and other stigma-related social stressors (Meyer, 2003). Additional studies focus on the central role of social influences, consistent with social learning theories suggesting that increased risk for substance use may result from importance of use among peers, expectancies, and social triggers (Green & Feinstein, 2012). Although there has been substantially less research on treatment utilization among sexual minority subgroups, what research there is suggests higher rates of substance use treatment utilization (McCabe, West, Hughes, & Boyd, 2013). However, increased prevalence does not ensure receipt of comparable treatment quality, due to high levels of discrimination against individuals with minority sexual orientations and a lack of knowledge among providers about their unique mental health needs (Eliason & Hughes, 2004). More research is needed to elucidate the contributing factors to disproportionate risk for substance use and improving treatment outcomes among individuals with minority sexual orientations.

Course and Prognosis

By the 12th grade, about half of adolescents have used an illicit substance at least once (Johnston, O'Malley, Miech, Bachman, & Schulenberg, 2016). The most common substance used by adolescents is marijuana; however, additional drugs are easily found in the home, such as prescription medications and an assortment of inhalants. It should be noted that although many adolescents may experiment with drugs, most do not progress to abuse or dependence (Newcomb & Richardson, 1995). There is an ongoing debate about the development and progression of substance use among adolescents. Some researchers subscribe to the “gateway theory,” which hypothesizes that for adolescents there is a distinct sequential pattern of substance use, beginning with licit substances (i.e., tobacco, alcohol) and progressing to illicit substance (e.g., marijuana), and finally advancing through a hierarchy of illicit substances (e.g., cocaine, heroin; Kandel, Yamaguchi, & Chen, 1992). However, more recent research finds that adolescent substance use does not always evidence a temporal sequence from licit to illicit substances, and the choice of substance used by adolescents is a function of contextual variables (e.g., availability, parental supervision) and association with other mental health symptoms (e.g., Lee, Humphreys, Flory, Liu, & Glass, 2011; Marmorstein, White, Loeber, & Stouthamer-Loeber, 2010) more than a normative sequential order (Tarter, Vanyukov, Kirisci, Reynolds, & Clark, 2006).

Although there are conflicting hypotheses as to adolescent use and progression, research has consistently evidenced similar risk factors for the development and maintenance of substance use disorders. Two primary risk factors include age of initiation and frequency of use during adolescence (Behrendt, Wittchen, Hofler, Lieb, & Beesdo, 2009; Degenhardt et al., 2009; King & Chassin, 2007). Age of initiation increases risk, in part, because earlier age of substance use allows for greater exposure to the substance. Considering that adolescence is a time of substantial neurological development, the adolescent brain may be particularly susceptible to substance use and addiction (Winters & Lee, 2008). In addition, substance-related problems (i.e., negative consequences of substance use) in adolescence significantly predict a future substance use disorder, elevated levels of depression, and antisocial and borderline personality disorder symptoms by age 24 (Rohde, Lewinsohn, Kahler, Seeley, & Brown, 2001).

Once a substance use disorder is present, recovery is notoriously difficult, even with exceptional treatment resources. For those who receive treatment, the next challenge is staying in treatment. Treatment dropout rates range from 21.5% to 43% for detoxification, 21.7% to 57% for inpatient treatment, and 23% to 50% for outpatient treatment (for a review, see Brorson, Arnevik, Rand-Hendriksen, & Duckert, 2013). Such high rates of premature treatment termination are of concern, because time in treatment is related to positive outcomes (e.g., Garner, Godley, Funk, Lee, & Garnick, 2010; Simpson, Joe, & Brown, 1997). As for relapse rates, estimates suggest that 90% of heroin- and cocaine-dependent users experience at least one relapse within 4 years after treatment, with many relapsing considerably sooner. Furthermore, of the patients admitted to the US public treatment system in 2007, approximately 57% were re-entering treatment (Office of Applied Studies, 2009). Retrospective and prospective treatment studies report that most participants initiate three to four episodes of treatment over multiple years before attaining abstinence (Hser, Maglione, Polinsky, & Anglin, 1998), and as many as 80% transition between treatment, recovery, using, and incarceration at least once over a 4-year follow-up period (Grella, Scott, Foss, & Dennis, 2008).

Treatment outcomes are dependent on a variety of factors, including individual characteristics and life problems, severity of addiction and substance use, aptness of treatment and linkage to services to treat other problems, and the quality of the transaction between the individual and the treatment program (NIDA, 2009). As previously stated, better treatment outcomes are related to length of stay, and for residential/inpatient and outpatient programs, treatment participation of 90 days or longer is recommended for sustaining recovery and positive results (NIDA, 2009). However, treatment duration of 90 days is not always feasible (i.e., lack of insurance and prohibitive cost). From 2010 to 2013, the most commonly reported barrier to receiving treatment was inability to afford the cost of treatment and lack of insurance coverage (SAMHSA, 2014b). Historically, persons with substance use disorders receive a traditional acute treatment approach involving assessment, treatment, and discharge all within a short time frame (i.e., 28 days or 2 months), with the supposition that the patient is treated and will be able to maintain abstinence following the single treatment episode (Dennis & Scott, 2007).

However, recent literature addresses substance use disorders as a chronic condition, analogous to other chronic medical diseases. For example, McLellan et al. (2000) illustrate the similarities in genetic heritability, environmental factors, and personal choice within addiction and other medical conditions with chronic care treatment (e.g., type 2 diabetes mellitus, hypertension, and asthma). Of note, they found that treatment compliance for individuals with a substance use disorder is no better than adherence rates to prescribed treatments for these other medically accepted chronic diseases. Similar to chronic diseases such as diabetes and congestive heart failure, multiple relapses are common (Saitz, Larson, LaBelle, Richardson, & Samet, 2008); therefore, adjusting treatment to involve a continuum of care may improve long-term outcomes for people with substance use disorders.

Case Study

Case Identification

The patient (Alaina) is a 38-year-old African American female who entered treatment voluntarily at an intensive outpatient substance use treatment center.

Presenting Complaints

Alaina reported that she relapsed to substance use 8 months ago, and her preferred drug is crack/cocaine accompanied by frequent alcohol use. She reported that she had success in treatment for the first time 4 years ago and she would like to try to get back on track, as she has hit a low point in the past few months. At the time of treatment entry, Alaina reported no stable living arrangement and that she has recently been splitting her time between the homes of her friends, ex-boyfriend, and uncle. She has one child, age 6, who lives temporarily with her aunt, and with whom she has intermittent contact. In her current environment, she reported spending most of her time alone, as she has lost contact with her sober friends.

History

Alaina was raised by her mother and her grandmother and has never met her father. She reported an extensive family history of substance use, including heroin and crack/cocaine use by her mother who still actively uses. Alaina first began using substances in high school. She graduated from high school, but at the age of 18 was arrested and spent a year in prison on a charge related to theft and possession of cocaine. Since that time, she reported regular crack/cocaine and alcohol use. She has worked intermittently as a hair stylist over the course of her life. Her most stable employment was during the past 4 years after she successfully completed a court-mandated treatment at a residential substance use treatment facility. She reported that she is committed to “learning from my mistakes” and “getting her daughter back” at this time, and that she had successfully remained abstinent up until her most recent relapse.

Assessment

The Addiction Severity Index and a clinical interview for DSM-5 were administered to determine existing psychopathology, including substance use history, frequency, and severity, environmental strengths and stressors, legal issues, and psychiatric symptoms. During the interview, Alaina displayed psychomotor retardation, clear thought processes, and no obvious perceptual abnormalities. Her speech volume and tone were within normal limits, yet her speech rate was somewhat slower than normal. Based on this assessment, Alaina met criteria for current cocaine use disorder (severe), current alcohol use disorder (mild), and major depressive disorder (MDD). She reported past crack/cocaine and alcohol use beginning at age 15 when using with peers. Her MDD symptoms include depressed mood most of the day, nearly every day, markedly diminished interest in almost all activities, feelings of worthlessness and excessive guilt, and a diminished ability to think or concentrate. After a careful assessment of her symptom timeline, it was concluded that her MDD was not substance-induced, as her symptoms preceded the onset of her relapse to substance use.

The assessment of legal issues indicated that she is not on probation with the court system and entered treatment voluntarily. Alaina evidenced difficulty in identifying strengths, but with some additional probing she was able to acknowledge potential support from her aunt, as well as the importance of her spirituality. She reported that her Narcotics Anonymous (NA) sponsor was a source of support but moved away from the area about 6 months ago. She would like to begin attending NA meetings and looking for a new sponsor.

It was determined that a functional analysis to identify the antecedents and consequences of her substance use and depression would provide the most useful information for treatment planning. First, following the loss of her job at a local hair salon, she reported that she had a lot of free time and got bored easily. She felt hopeless that she couldn't find a new job and often ruminated over the guilt she felt about her choices in life and her inability to provide for her daughter. She contacted her old friends, which was soon followed by cocaine and alcohol use. She also reported feeling lonely, guilty, and worthless when she realized she could not adequately support her daughter financially, so drug use helped her “bury” these feelings, although they would always resurface when she was sober, leading to a cycle of negative reinforcement. Finally, she reported intensifying feelings of sadness and shame that she had used crack/cocaine and alcohol again given how much progress she had made in the past few years. She felt that she had let her daughter and aunt down. Taken together, it appeared that a lack of substance-free environmental reinforcements following the loss of her job was strongly associated with her relapse to substance use. This was soon thereafter compounded by the negative thoughts and feelings surrounding her parenting skills, resulting in repeated substance use and the cycle of negative reinforcement.

Summary

Substance use problems are complex, and a comprehensive understanding requires knowledge of biological, genetic, neural, behavioral, and cognitive factors. This chapter provides an overview of current practices and cutting-edge advancements for understanding and assessing substance use disorders. Although much work is still needed, great progress has been made in understanding the etiology of substance use, with greatest promise evident in approaches that consider the interactive influence of multiple factors. Additionally, clear advances have been made in both initial and ongoing assessments using self-report, interview, behavioral, and biological methods. Also of great promise is the greater attention to neurobiological, genetic, sex and gender, and diversity issues when considering vulnerabilities to developing substance use disorders, as well as barriers to assessment and proper treatment. In summary, although the challenges of understanding and assessing substance use disorders remain, it is clear that the field has seen important advancements aimed at addressing these challenges.

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