The concept of addiction involving non-substance behaviors as repeated urges to engage in counter-productive activities was introduced in 1990. At the time, behavioral addictions were proposed to encompass obsessive-compulsive disorder (OCD), "compulsive spending" (including gambling), "overeating" (binge eating), "hypersexuality," and kleptomania. It was thought these behaviors were linked to addiction by poor impulse control and self-regulation, which led to repetitive engagement of the behavior despite negative consequences[1,2]. The concept of an obsessive-compulsive spectrum of disorders was proposed in 1993; disorders that featured an inability to control or delay repetitive behaviors were thought to fall on a spectrum from impulsivity to compulsivity [3]. Numerous psychiatric and neurologic disorders were included in this spectrum [4].

Further research suggested that impulsivity and compulsivity appeared in substance and behavioral addictions at different stages, and the "impulsive-compulsive disorder" model was proposed. In this model, impulsivity was dominant in earlier-stage addiction, when behavior is motivated and reinforced by reward, and compulsivity was dominant in later stages, when behavior is motivated and reinforced by avoidance of negative emotional states [5].

An influential 2006 study broadened the definition and core features of addiction as 1) a state of craving or urge that immediately precedes the behavior, 2) impaired ability to control the behavior, and 3) the behavior continues despite negative consequences [6]. Criterion 3 suggested addiction was no longer tethered to substance use. This was cemented in 2011, when the American Society of Addiction Medicine (ASAM) released their definition of addiction. The core features of this definition are [7]:

The DSM-5 contributed to this confusion in the introductory text for Internet gaming disorder by stating that it was also commonly referred to as Internet use disorder or Internet addiction [11]. This message was unclear, but some features unique to the Internet may promote excessive or addictive behaviors, including [16,17,18,19,20,21]:

Compulsive behaviors are inappropriate and have no obvious relationship to a goal. When reward-driven substance use or behavioral pursuits persist over an extended period, reward-based learning mechanisms are thought to develop into compulsive behaviors [26].

The reward deficit disorder model describes addictions as chronic relapsing disorders characterized by a compulsion to seek and take the drug or experience the behavior, loss of control over stimuli intake, and emergence of a negative emotional state (e.g., dysphoria, anxiety, irritability) when unable to access the stimulus. The negative emotional state is termed motivational withdrawal syndrome. A key component of addiction is negative reinforcement, which describes engagement in potentially harmful behaviors to alleviate a negative emotional state [45].

The components model of addiction defines addiction as any behavior with all six core addiction components [17,55]:

The cognitive-behavioral model addresses the role of motivational drives for reward-seeking and stress-reduction; behavioral control (related to executive inhibition); and decision-making (involving weighing the pros and cons of engaging in motivated behaviors) in addictive behaviors.

Predisposing personality factors include high impulsivity, shyness, neuroticism, low self-esteem, conscientiousness, self-directedness, and procrastination. Affective/cognitive responses to environmental stimuli influence the preference of specific Internet genres. For example, a perceived lack of social support, feelings of isolation, and loneliness are linked to the use (and potential misuse) of Internet genres with prominent communication features (e.g., social networking sites) [64,65]. Specific Internet-mediated addictions are associated with specific personality profiles, such as greater rates of ADHD and impulsivity.

The PFC region is involved in executive processes important in risk-reward decision-making, but is among the last brain regions to mature. Compared with mature adults, this aspect of brain development renders adolescents more vulnerable to addictions, other risky behaviors, and mental health disorders [44]. The brain mechanisms that mediate cognitive control, impulsivity, and sensitivity to reward mature during adolescence and young adulthood, and this is the period when substance use initiation and other problem behaviors most commonly emerge [67].

Immature connections between the PFC, the nucleus accumbens, and the amygdala are thought to largely influence goal-directed behaviors in adolescents [68,69]. Reduced prefrontal cognitive control may allow greater influence of affective systems over decision-making and behavior, which increases adolescent vulnerability to social and peer pressure [70]. Addiction can interrupt the normal neurodevelopmental trajectory from adolescence to early adulthood, and addiction in adolescence can be both a cause and effect of cognitive, affective, and behavioral dysfunction.

Stress intolerance and poor stress coping are strongly associated with behavioral addictions. Mindfulness-based stress reduction interventions target stress reduction, and efficacy is supported in substance addictions. This approach may be particularly helpful in patients with behaviors driven by negative-reinforcement motivations [80].

Dialectical behavior therapy also helps patients learn multiple methods of tolerating distress without resorting to self-defeating or self-destructive behavior. One method involves self-soothing by engaging the five senses when experiencing acute interpersonal anxiety or distress. This can involve listening to or singing a favorite song; watching a travel video of a beautiful location; savoring the taste of a favorite food; lighting a candle with a favorite scent; and/or touching or rubbing soft material or a smooth stone.

Preliminary studies suggest that combining several therapeutic strategies may be more effective than a single approach. Such approaches may include CBT, cognitive bias modification, CET, and/or mindfulness-based stress reduction, delivered in group, individual, family therapy, or school-based formats, with different strategies complementing aspects of the others. Combining behavioral and pharmacologic therapies can also be considered.

Almost all behavioral addictions were originally understood through the obsessive-compulsive spectrum model. By extension, and based on efficacy in OCD, selective serotonin reuptake inhibitors (SSRIs) became the most widely used drug class in the treatment of behavioral addictions, but they showed minimal benefit. More recently, neuroscience research identified similarities in the core features of behavioral and substance addictions, and the obsessive-compulsive spectrum model was discarded in favor of better-fitting addiction disorder models. Naltrexone, an opioid receptor antagonist with efficacy in substance use disorders, has suggested benefit in behavioral addictions, but there is evidence of possible adverse effect [22,85].

Among treatment-seeking disordered gamblers, women initiate gambling at an older age than men (31.3 years versus 22.4 years) and have a significantly shorter time from gambling initiation to meeting DSM criteria for gambling disorder (8.33 years versus 11.97 years). As noted, this phenomenon is consistently found in women with substance use disorders as well [91].

Gambling disorder is highly comorbid with other mental health disorders, particularly substance use disorders, and shows a heritability rate of 50% to 60% [94]. Data published before widespread access to online gambling indicate that, compared with non-pathologic gamblers, pathologic gamblers show a six-fold greater risk for substance use, a four-fold greater risk for illicit substance use disorder, and a three-fold greater risk for mood disorders [95]. At-risk gamblers have higher rates of psychiatric comorbidity relative to the general population [96].

Many attributes of online gambling have led to assumptions that Internet gambling may facilitate earlier onset, more rapid progression, and greater consequences related to gambling disorder compared with off-line gambling [96]. Land-based gamblers, characterized as older, female, and more likely to be divorced, show greater use of electronic gambling machines and table games and greater problem gambling rates than online gamblers [96]. Mixed (off-line and online) gamblers, characterized by younger age, less likely to be married, and more likely to consume alcohol and illicit drugs when gambling, show a propensity to greater involvement in gambling, sustaining higher losses and consequent harms [96]. Online gamblers, consistently identified as male, younger age, higher in education and income, and employed full-time, are significantly less likely to report gambling-related problems than other gambler subgroups [96]. Unlike other behavioral addictions, online gambling is not associated with greater risk of problem or disordered behaviors, which seems more likely to develop in gamblers who prefer offline gambling in casinos or other venues [97].

In Australia in 2010, gambling generated $19 billion in revenue; 55% came from electronic gaming machines in clubs and hotels, and 40% of electronic gaming machine revenue came from problem gamblers (only 0.6% of the population) [10]. Termed the "crack cocaine of gambling," electronic gaming machines are considered the most hazardous form of gambling, because they incorporate features that promote gambling-related cognitive distortions to perpetuate gambling, including near-win (or near-miss) outcomes and "loss disguised as a win." These features activate the sympathetic nervous system and reward-related neural circuitry, amplified further in disordered gamblers [99,100].

Smoking status is associated with more severe gambling and psychiatric symptoms. Among patients seeking treatment for gambling disorder, daily smokers (compared with non-daily smokers) were more likely to have histories of substance use disorder treatment, more severe gambling, family and social problems, and more frequent psychiatric symptoms, especially anxiety-related symptoms [101,102]. In a study of the association between smoking and gambling in adolescents, those with "at-risk/problem gambling" who smoked were more likely to report poor grades, lifetime use of cannabis and other drugs, current heavy alcohol use, depression, aggressive behaviors, and less likely participation in extracurricular activities [103].

According to the DSM-5-TR, gambling disorder is categorized as a substance-related or addictive disorder. Diagnosis of gambling disorder requires four or more of the following [11]:

The exclusion of illegal activity from the DSM-5-TR criteria was not an endorsement to downplay its relevance. The presence of illegal behavior in patients with gambling disorder is directly linked to more severe pathologic outcomes and resistance to treatment; specific and more intensive treatment may be required for these patients [108].

Despite serious psychosocial and financial consequences, most disordered gamblers do not seek treatment or may seek treatment only after being pressured by family members. Patient motivation and treatment adherence importantly contribute to successful treatment outcome for patients with gambling disorder [110].

Many disordered gamblers can trace the course of their disease to an early win, followed by increasing gambling frequency and expenditure. Even early wins of $100 to $500 can increase excitement about gambling, distort self-perceptions of skill or expected returns, and strengthen irrational beliefs about gambling (e.g., illusion of control) [112,113]. Many erroneous beliefs and inaccurate perceptions are rewarded, learned, or become habitual during disordered gambling, and several cognitive distortions are emblematic of gambling disorder, including [71,114]:

Behavioral therapies target gambling urges primarily with exposure-based therapies. Exposure therapy is based on classical conditioning paradigms, whereby gambling urges are eliminated through cue exposure with extinction processes. Exposure therapy is thought by some to be more beneficial in gambling disorder than other behavioral therapies, such as aversive therapy [71].

Brief motivational intervention shows promise in reducing gambling when delivered alone or with other therapies. Brief motivational interventions are often directed at patients with subclinical diagnoses, defined as negative gambling-related consequences without meeting the criteria for gambling disorder. Brief motivational intervention is useful for engaging patients with poor problem recognition in further treatment or for spurring self-directed change. Therapy sessions focus on personalized feedback, brief advice, review of options (e.g., treatment options, change goals), and building self-efficacy, delivered in an empathic manner. In one study, telephone brief motivational intervention combined with a self-help workbook was effective in improving gambling outcomes in problem gamblers [121]. Single-session stand-alone motivational sessions are effective compared with assessment-only control groups [117]. Direct comparisons of motivational therapy and CBT suggest both interventions are equally effective compared with control groups [122].

Founded in the 1950s, Gamblers Anonymous (GA) is a mutual help fellowship based on the 12-step program of AA. With meetings in most North American communities, GA is established worldwide as a resource for people struggling with gambling problems. GA groups are peer-led and abstinence-focused and represent the most widely available option for recovery from gambling disorder [136]. Some GA meetings welcome family and friends to attend "open meetings," recognizing the impact of disordered gambling often extends far beyond the patient and that support from non-gambling family and friends can be integral to recovery. Local groups can be found online at http://www.gamblersanonymous.org/ga/content/about-us [113].

Addictive sexual behavior is more common in men, with onset usually in late adolescence. It can involve a wide range of sexual behaviors, often including a mixture of paraphilic and nonparaphilic behaviors. Sexual urges and behaviors are often distressing and uncontrollable, triggered by certain mood states, and result in feelings of shame [143,144].

Cue reactivity, or the level of sexual arousal to Internet pornography, is the greatest single predictor of Internet pornography addiction, severity of the addiction, and impairment from the addiction. Hours of use alone is unrelated to addiction. Cue reactivity is an established correlate of addictive behavior across addiction disorders [151,159]. Internet pornography addiction severity is directly related to cue-induced activation of the dorsolateral PFC and thalamus [151,159].

Pornography use is inversely related to satisfaction with partners, as measured by affection, physical appearance, sexual curiosity, and sexual performance [171]. The caudate is involved in approach-attachment behaviors and motivational states associated with romantic love [172]. Putamen activation is associated with sexual arousal and penile tumescence [173]. Users of more extensive Internet pornography show smaller right caudate and lower putamen activation when viewing sexually explicit still photos. This reflects down-regulation of natural neural response to sexual stimuli from intense, prolonged exposure to pornographic stimuli [174]. Men with greater use of degrading or extreme pornography report more frequent concerns of sexual performance, penis size, and ability to maintain an erection (compared with moderate or non-users) [151,175].

Early sexual conditioning impacts sexual arousal templates. A critical developmental period of sexual behavior forms around initial experiences with sexual arousal and desire, masturbation, intercourse, and orgasm. Younger age of onset for regular Internet pornography use and greater preference for pornography over partnered sex is associated with persistence of this pattern. In 2014, nearly 50% of college-age men reported they were first exposed to Internet pornography before 13 years of age, compared with 14% in 2008 [176,177]. Young adults with addictive Internet pornography use show greater impairments in sexual arousal and erectile function in intimate relationships, but not with pornographic material.

Areas to inquire about in order to identify hypersexuality subtypes during patient assessment include [138]:

The first step in the treatment begins with accurate diagnosis that rules out medical causes of hypersexuality. Neurologic disorders associated with hypersexual behavior include Alzheimer disease (4.3% to 9% of these patients experience sexual disinhibition as a result of disease effects on the frontal and temporal lobes), frontotemporal degeneration (associated with impaired regulation of socially acceptable behaviors), and Kleine-Levin syndrome (causes hypersomnia that may lead to abnormal behavior, such as hypersexuality). Some medications or illicit drugs can elevate sexual drive, such as cocaine, methamphetamine, and dopamine agonists used in Parkinson disease [140,179,180].

Variously worded diagnostic entities describing addictive sexual behavior have appeared in the iterations of the DSM and the ICD [181]. Diagnostic criteria for hypersexual disorder were created and proposed for the DSM-5. These criteria are [140,182]:

Diagnostic criteria for compulsive sexual behavior disorder also appear in the ICD-11, published in 2018. These diagnostic criteria are [109]:

Paraphilic hypersexuality is remarkable for the sizeable number reporting gynandromorphophilia, a rarely discussed erotic interest in persons with both male and female anatomy (usually full breasts and intact penis) typified by incompletely transitioned male-to-female transgender women. For many, this specific enduring erotic interest leads to confusion over sexual orientation or gender identity and hesitant self-reference as ''mostly heterosexual'' or as bisexual [138].

Romantic partners of designated patients demand they get help and instigate sex disorder clinical assessments. These demands may reflect highly restrictive sexual beliefs with zero-tolerance for masturbation, pornography, or non-procreative sex. Designated patients may self-label as sex addicts (or a similar term) but lack the sexual behavioral patterns. These patients state their partners explicitly believe the problem is theirs to solve. Designated patients are best helped by including the partner in psychoeducation on healthy masturbation and pornography use and communication and assertiveness training. Sex-positive clinicians quickly see partner demands as unnecessarily restrictive. Some patients know this, but agree to the restrictions for the benefit of the relationship.

Psychodynamic therapy has relatively few published clinical studies in sexual addiction treatment, but it appears to offer unique advantages [186]. Specifically, psychodynamic treatment can address the factors related to the individual's unique personal history and personality organization and can clarify the specific meaning the addictive behavior holds for the patient. For instance, sexual addiction can reflect a rebellion against a puritanical and authoritarian parent; a form of self-soothing in the context of parental abandonment; a narcissistic need for constant affirmation of one's attractiveness; or a desperate attempt to stave off feelings of emptiness. In most cases, sexually addictive behavior is thought to reflect a disturbance in the core self-concept and/or the capacity for intimate relationships [76].

Sex Addicts Anonymous (SAA) is a support group with a purpose of helping others with sex addiction find recovery. This organization operates similarly to AA and uses the 12-step program of recovery. Another 12-step program is Sex and Love Addicts Anonymous (SLAA) [140]. Most SAA, SLAA, and Sexual Recovery Anonymous ("S" meetings) groups admit new members only after screening and approval by the group members. Meetings focus on the goal of helping the new member stop or control his/her pathologic sexual behavior and learn new coping strategies. "S" meeting groups can play an important role in the recovery of patients by helping them become honest with themselves and their families in an atmosphere of support and fellowship [137].

Massive, multiplayer, online role-playing games (MMORPGs) are unique in pathogenic potential among game genres. A 2015 report described a case of two brothers (22 and 19 years of age), high academic achievers from an intact, upper-middle class family who lived at home. Both began MMORPGs two years before hospital admission for Internet gaming disorder. In the initial months, time spent gaming progressed from 2 to 4 hours to 14 to 18 hours daily. Gaming interfered with their sleep and daily routine. Both deteriorated to the point that when engaged in MMORPGs, they urinated and defecated in their clothes, did not change clothes for days, did not bathe, skipped meals, and did not answer the phone. Fixated on gaming, they were indifferent to the presence of a burglar robbing their home. Both failed their classes, became abusive and violent when their gaming was disrupted, and were admitted to inpatient care by their parents [194].

MMORPGs are played online by thousands of gamers simultaneously, spanning vast time zone differences without spatial or temporal boundaries. The design of MMORPGs borrows from operant conditioning, incorporating random, unpredictable reward structures to maximize player engagement and time involvement. The same intermittent schedule of rewards is featured in slot machines and other gambling modes [194].

Social anxiety is lowest in FPS gamers. FPS players control the game character from a first-person view, making self-confidence crucial for high scores and engagement in competition. Most online FPS players do not play in isolation, and social interaction motivation highly predicts FPS time involvement. FPS players are drawn to competition and challenge [201]. The highly immersive nature and potential for online competition, achievements, and social interaction can reinforce excessive FPS involvement. Social-seeking behavior is inversely related to social anxiety and avoidance [195].

The pooled prevalence estimates from more than 30 countries showed problematic Internet game use in 8% to 12% of young persons and addictive use in 2% to 5% of children, adolescents, and college students [17]. Nationally representative American samples show an Internet gaming disorder prevalence of 8.5% among those 8 to 18 years of age [203,204].

Internet gaming disorder is associated with increased neuroticism, aggression/hostility, avoidant and schizoid interpersonal tendencies, loneliness, introversion, social inhibition, boredom inclination, sensation-seeking, low agreeableness, diminished self-control, narcissistic personality traits, low self-esteem, state and trait anxiety, and low emotional intelligence. These personality factors are not specific to pathologic gaming and contribution to, or direction of, causality is unclear from the research designs [17]. Gamers with Internet gaming disorder show high rates of comorbidity, including ADHD, generalized anxiety disorder, panic disorder, depression, social phobia, school phobia, and various psychosomatic symptoms [17].

Numerous studies indicate that, for a player subgroup, excessive online gaming can lead to diverse negative psychosocial consequences, including sacrificing work, education, hobbies, socializing, time with partner/family, and sleep, as well as increased stress, absence of real-life relationships, lower psychosocial well-being, loneliness, worse social skills, decreased academic achievement, increased inattention, aggressive/oppositional behavior and hostility, maladaptive coping, decreases in verbal memory performance, maladaptive cognitions, and suicidal ideation [17].

Internet gaming disorder is linked to impulsivity and poor self-regulation, supported by the multidimensional UPPS-P model of impulsivity that describes impulsivity as five related but specific dimensions [213]:

As discussed, maladaptive cognitions are a core feature of Internet gaming disorder and include self-regulation deficits, preference for a virtual life, cognitive bias, impaired cognitive control abilities, cognitive deficits, poor cognitive error processing, and decision-making deficits [204]. CBT addresses these cognitions and is the most widely used psychological treatment for Internet gaming disorder. The first stage of CBT treatment for Internet gaming disorder deals with the behavioral aspects of addicted gaming, and subsequent stages gradually shift the focus toward the development of positive cognitive assumptions. During therapy, addicted gamers identify false beliefs and learn how to modify them into more adaptive ones. CBT also trains patients to monitor their thoughts and to identify affective and situational triggers associated with their addictive gaming behavior [204].

In the treatment of Internet gaming disorder, CBT typically involves 8 to 28 sessions that address psychoeducation, problem identification, healthy communication, Internet awareness, and cessation techniques. Treatment of Internet gaming disorder may also include short-term therapy, group therapy, and systemic therapy with parents/teachers/peer support and multilevel interventions that incorporate motivational interviewing [204].

CBT is combined with motivational enhancement therapy (MET/CBT) to move patients from ambivalence to engagement concerning behavioral change. MET/CBT is structured by stages:

There is increasing concern that consumption of food with high sugar content may be "addictive" and promote weight gain. Claims that sugar has addictive potential are based on animal studies, but direct human evidence for symptoms of sugar-related substance dependence is lacking [236]. A study evaluated 1,495 university students for potential "food addiction" (with DSM-IV substance dependence criteria applied to food) involving high-sugar foods. In this group, 12.6% met food addiction criteria; of these, 5% mainly consumed sugar-laden foods. Overweight/obesity was unrelated to sugary food preference. "Food addiction" was concluded to result from unique individual characteristics that determined reward response to food and promoted excessive eating [236,237].

Binge eating disorder is more common in women (3.5%) than men (2%), and in younger and middle-aged adults than those older than 60 years of age [81]. The prevalence is higher in obese than non-obese persons. The lifetime prevalence of binge eating disorder appears slightly lower among Latino and Asian Americans (1.9% and 2.0%, respectively) compared with the general population; the prevalence is similar among Hispanic and non-Hispanic White individuals [239,241].

Binge eating disorder is typically first diagnosed during the early to mid-20s, with symptoms usually persisting well beyond mid-life. The disease course may crossover to and from bulimia nervosa and anorexia nervosa. Binge eating disorder is associated with significant role impairment and relationship dissatisfaction. It is considered a significant public health problem independently as well as for its association with chronic pain, other psychiatric disorders, obesity, and diabetes [246,247,248].

A sense of loss of control during binge episodes is a core feature of binge eating disorder. The term "loss-of-control eating" is used to describe these episodes, but it is also used more broadly throughout the literature to describe binge-like eating behavior accompanied by a sense of loss of control that occurs across a wide spectrum of individuals. That spectrum includes, among others, individuals who exhibit some features of binge eating disorder but do not meet full diagnostic criteria for the disorder (i.e., subthreshold binge eating disorder) and individuals with other eating disorders [81].

Therapy variants in binge eating disorder include CBT combined with body image exposure or cognitive restructuring components, and ecologic momentary assessment to increase self-monitoring adherence [81,259,262]. A meta-analysis of studies that randomized patients to CBT or non-treatment (control) found improved binge frequency and abstinence outcomes with therapist-led, partially therapist-led, structured self-help, and guided self-help CBT. Therapist-led CBT outcomes were compelling, with a higher rate of abstinence (59% CBT vs. 11% control), reduction of binge episodes, reduced patient hunger and eating concerns, and improved sense of control over eating. Guided self-help CBT reduced global eating-related psychopathology. When all study results were pooled, CBT and control groups were similar in weight lost and depressive symptom reductions. Therapist-led CBT was much more effective in improving key behavioral and eating-specific psychological domains [81].

The prodrug lisdexamfetamine is the sole FDA-approved drug for the treatment of moderate-to-severe binge eating disorder. The FDA has withdrawn several investigational or approved binge eating disorder pharmacotherapies from the U.S. market over safety concerns and adverse effects (e.g., sibutramine, rimonabant, d-fenfluramine) [81].

Bariatric surgery is a treatment option for binge eating disorder with severe obesity (BMI ≥40 or BMI ≥35 with comorbid conditions). In the past, an eating disorder diagnosis was a contraindication to bariatric surgery, but this restriction has been relaxed. The disability and difficulty achieving stable weight loss with standard behavioral interventions has increasingly led to surgery candidates with binge eating disorder [245,274]. Bariatric surgery can be suitable for selected patients with binge eating disorder, but the extent of weight loss depends on post-surgery binge episode reduction, and 20% to 40% fail to lose sufficient weight or regain significant weight post-surgery [275]. Patients may experience emergent post-bariatric surgery psychiatric comorbidities. Considering the demonstrable and durable behavioral and neuroplastic changes associated with addictive eating behavior, obesity treatment is not realistic for some of these patients [276].

In one study, among 1,441 shopping mall visitors, the rate of compulsive buying disorder was 8.7% [283]. Compared with non-compulsive buyers, compulsive buyers were younger, less educated, more likely female, and more likely to have used licit and illicit substances. They also showed higher levels of impulsivity and obsessive-compulsive symptoms, lower levels of well-being and self-esteem, and greater psychological distress. Patients identified as compulsive buyers were five times more likely to meet diagnostic criteria for borderline personality disorder. These findings suggest that, among shopping mall visitors, compulsive buyers are prevalent and have high rates of important indicators for psychopathology [283].

Comorbidities associated with compulsive buying disorder include [281,284]:

Compulsive buying is a chronic, repetitive behavior that becomes a primary response to negative events and feelings [286]. Four distinct phases in compulsive buying events are described: anticipation, preparation, shopping, and spending. Negative emotions, such as anger, anxiety, boredom, and self-critical thought, were the most common antecedents to shopping binges, with euphoria or relief from negative emotions the most common immediate effects [281].

Sociodemographic and personality characteristics may help determine different clinical subtypes of compulsive buying disorder to consider during assessment and treatment planning. Three clusters of compulsive buying disorder were identified among patients attending a specialized treatment program [290]:

Compulsive buying disorder was classified in the DSM-III-R as an impulse control disorder not elsewhere specified, but it was omitted from the DSM-5 [11,300]. Since 2013, research demonstrates that compulsive buying disorder has several features that characterize addictions, including cue reactivity and cravings [289].

Group psychotherapy that uses a CBT approach or cognitive-behavioral methods within an eclectic approach appears beneficial, with durable improvements in reducing distress associated with compulsive buying disorder and maladaptive buying behavior. Research suggests that impulse control training should be a core component of compulsive buying disorder treatment [289]. Attrition rates show that group psychotherapy is not acceptable to all patients with compulsive buying disorder; patient choice and suitability are important considerations [289].

Evidence suggests that a low-intensity, guided self-help approach to treating compulsive buying disorder was comparable to high-intensity group therapy. If patients can be treated with effective, brief, and less intensive psychological interventions first, this may increase service throughput and efficiency [304]. Studies of Internet-based, therapist-assisted self-help programs also usefully mimic the shift of behavior in online shopping [305]. Research indicates that excitability regarding online shopping and compulsive buying disorder are mediated by Internet use expectancies [294]. Treatments clearly need to reflect the context within which compulsive buying occurs [289].

Reward and punishment sensitivity was studied for impact on treatment outcome (12 weekly CBT sessions) in female patients with compulsive buying disorder or gambling disorder [46]. In compulsive buying disorder, higher reward sensitivity was related to poorer treatment adherence but reduced risk of dropout. Patients were likely to have stronger intrusive urges to buy, interfering with ability to curb buying behavior and carry out practice homework for CBT. The lower dropout risk may reflect patient motivation by social factors, with patients more likely to form a therapeutic alliance and not abandon treatment. High punishment sensitivity correlated with harm avoidance; these patients had increased risk of treatment drop-out.

A review of compulsive buying disorder treatment found few published pharmacotherapy studies. SSRI antidepressants are the most-studied pharmacotherapy, based on the same premise as their use in other behavioral addictions [85]. Evaluations of citalopram, escitalopram, and fluvoxamine have reported mostly negative results, and clinicians should consider psychotherapeutic options before pharmacotherapy [289]. A systematic review of treatment studies found that group CBT is effective in reducing symptoms of compulsive buying disorder, whereas pharmacotherapy with SSRIs or topiramate did not indicate superiority over placebo [306]. One literature review found that a combination of antidepressants and CBT is effective for management of compulsive buying disorder. Serotoninergic antidepressants are effective as monotherapy [302].

Community prevalence studies suggest that trichotillomania occurs in 0.5% to 2.0% of the population [309,310]. Lifetime prevalence is estimated to be 1% to 3% [311]. In adults, trichotillomania predominately affects women (4:1 female to male), but childhood trichotillomania shows equal sex distribution [309,310]. As a behavior, hair pulling appears quite common and often presents along a continuum from mild to severe. When hair pulling meets the criteria for trichotillomania, interventions should be considered [312].

With hair pulling in trichotillomania, the scalp is the most common site (72.8% of patients) followed by the eyebrows (56.4%) and the pubic region (50.7%) [312]. Triggers to pull can be sensory (e.g., physical sensations on the scalp, hair thickness, length, and location), emotional (e.g., feeling anxious, bored, tense, angry), or cognitive (e.g., thoughts about hair and appearance, rigid thinking, cognitive errors). Many patients report not being fully aware of their pulling behaviors at least some of the time—a phenomenon termed "automatic" pulling. "Focused" pulling, in contrast, generally occurs when the patient sees or feels a hair that is "not right" or if the hair feels coarse, irregular, or "out of place" [312,314].

Unwanted medical consequences from trichotillomania include skin damage or infection that results from using sharp instruments (e.g., tweezers, needles) to pull hair. More than 20% of patients eat hair after pulling it out (trichophagia); gastrointestinal obstruction and formation of intestinal hair-balls (trichobezoars) can ensue, requiring surgical intervention in extreme cases [317].

Patients with trichotillomania have high rates of comorbidity, including major depressive disorder (39% to 65%), anxiety disorders (27% to 32%), and substance use disorders (15% to 19%). Trichotillomania is often misdiagnosed as OCD. Rates of comorbid OCD are significantly higher in clinical (13% to 27%) than community (1% to 3%) populations [312,318].

The age of trichotillomania onset is generally earlier than its common comorbidities. In a large trichotillomania survey, patients sought to alleviate negative feelings associated with hair pulling through use of tobacco products (17.7%), alcohol (14.1%), or illicit drugs (6.0%). Also, 83% reported anxiety and 70% reported depression due to pulling, indicating that clinicians should screen for trichotillomania and the secondary manifestations of the behavior to better ensure successful treatment outcomes [318,319].

The similarity between repetitive motor symptoms of hair pulling and repetitive compulsive rituals in OCD led to proposals that both disorders shared common neurobiologic pathways. However, evidence indicates that trichotillomania and OCD are distinct. In contrast to OCD, patients with trichotillomania are more commonly female, and body-focused repetitive behavior disorders (e.g., skin picking, compulsive nail biting) more frequently occur in these patients and their first-degree relatives. In OCD, compulsions are often driven by intrusive and obsessional thoughts, which are seldom found in patients with trichotillomania and are not listed in diagnostic criteria. The typical age of onset is early adolescence for trichotillomania and late adolescence for OCD. Treatment response also differs, with SSRIs effective in OCD but not trichotillomania [320,321].

Hair pulling is considered a means of escaping or avoiding aversive experiences, and the temporary relief from negative emotions can maintain the behavior through a cycle of negative reinforcement. Patients with trichotillomania have demonstrated greater difficulty regulating negative affective states than controls. In some individuals, boredom may trigger hair pulling. Some have hypothesized that in a subgroup of patients, hair pulling alleviates negative emotions resulting from perfectionism and an inability to relax, with pulling serving the function of releasing tension [322].

In the few trichotillomania neuroimaging studies conducted, patients with trichotillomania showed volume deficits and disorganization in neurocircuits that mediate affective regulation, motor habit generation, and suppression (compared with healthy controls) [323]. An analysis of MRI scans of 23 girls/women with trichotillomania (compared with 16 healthy controls) implicated somatosensory, sensorimotor, and frontal-striatal circuitry, and partially overlapped with structural connectivity findings in OCD [324]. One study sought to determine whether recently identified subtypes of trichotillomania mapped to any unique neurobiological underpinnings [325]. In this study, 193 adults with trichotillomania and 58 healthy controls were recruited for a between-group comparison using structural neuroimaging. Differences in whole brain structure were compared across the subtypes, while controlling for age, sex, scanning site, and intracranial volume. Patients with trichotillomania with low awareness demonstrated increased cortical volume in the lateral occipital lobes compared to controls. Additionally, impulsive/perfectionist patients showed relative decreased volume near the lingual gyrus of the interior occipital-parietal lobe compared with controls [325]. Another study of subjects with trichotillomania failed to identify abnormalities in implicit learning or striatal/hippocampal activation, characteristics of OCD [326].

The evidence base for psychotherapy in trichotillomania is small, and habit reversal therapy has the greatest empirical support. Habit reversal therapy is a behavioral therapy initially introduced for the treatment of nervous habits and tics. The core components of habit reversal therapy include self-monitoring (e.g., asking the patient to track hair-pulling or skin-picking events), awareness training, competing response training, and stimulus control procedures (e.g., removing hair-pulling or skin-picking cues from the patient's environment) [322].

Habit reversal therapy is generally delivered in weekly 60-minute sessions for 4 to 22 weeks, with more frequent sessions for patients with greater symptom severity. It can be delivered individually, in a group format, or online using a self-help manual [328]. The clinical benefits of trichotillomania symptom reduction have been augmented by adding components of acceptance and commitment therapy or dialectical behavior therapy [329,330]. Patient gains from habit reversal therapy are usually maintained for three to six months. Many clinicians combine habit reversal therapy and CBT, but published data support habit reversal therapy use as a stand-alone, first-line psychotherapy approach in trichotillomania [307]. One small study reported success combining metacognitive therapy with habit-reversal techniques for treatment of trichotillomania [331].

The commonly quoted kleptomania prevalence of 0.6% in the general population was extrapolated from study data of patients with eating disorders [341]. A 2010 college student survey found a lower kleptomania prevalence rate of 0.38% [342]. This latter figure is likely more accurate because it was not derived from a specific subpopulation [341]. Among those arrested for shoplifting, kleptomania rates have ranged from 0% to 8%. This may be falsely low due to incomplete psychiatric evaluation, lack of strict diagnostic criteria for kleptomania, and/or selection bias [340].

In contrast to community prevalence rates, studies of patients with psychiatric disorders suggest prevalence rates of kleptomania sufficient to potentially represent a public health concern. Among 203 inpatients with diverse psychiatric disorders, 7.8% met current and 9.3% met lifetime criteria for a diagnosis for kleptomania. The similar current and lifetime prevalence suggests that untreated kleptomania is chronic. Other studies show increased rates of kleptomania in patients with depression (3.7%), alcohol use disorder (3.8%), and gambling disorder (2.1% to 5%) [340,343].

Most kleptomania studies report female predominance. However, women are more likely to seek professional help, and the legal system is more likely to send female shoplifters for psychiatric evaluation and male shoplifters to jail [340]. So, the true prevalences in men and women may be more similar than reported. Among 101 adults meeting DSM-IV kleptomania criteria (73.3% female), the mean age of shoplifting onset was 19.4 years, persisting an average 8.2 years before full diagnostic criteria were met [344].

In contrast to community prevalence rates, studies of patients with psychiatric disorders suggest prevalence rates of kleptomania sufficient to potentially represent a public health concern. Among 203 inpatients with diverse psychiatric disorders, 7.8% met current and 9.3% met lifetime criteria for a diagnosis for kleptomania. The similar current and lifetime prevalence suggests that untreated kleptomania is chronic. Other studies show increased rates of kleptomania in patients with depression (3.7%), alcohol use disorder (3.8%), and gambling disorder (2.1% to 5%) [340,343].

Most kleptomania studies report female predominance. However, women are more likely to seek professional help, and the legal system is more likely to send female shoplifters for psychiatric evaluation and male shoplifters to jail [340]. So, the true prevalences in men and women may be more similar than reported. Among 101 adults meeting DSM-IV kleptomania criteria (73.3% female), the mean age of shoplifting onset was 19.4 years, persisting an average 8.2 years before full diagnostic criteria were met [344].

The average age for stealing behavior onset is adolescence, with the first professional evaluation in the mid- to late-30s. Women tend to present for evaluation at a younger age than men. The extended length of time between onset and mental health evaluation reinforces the guilt, shame, and secrecy involved in this disorder [340].

Kleptomania is a secretive disorder with a hidden nature. Patients often present for treatment from legal coercion after being arrested for shoplifting. The diagnosis is often missed in routine psychiatric evaluations, and clinicians do not usually inquire about it. Patients with kleptomania often do not initiate disclosure of the behavior, even when they are already in psychiatric treatment for another disorder, because of shame about their behavior [341]. One study found only 42% of married individuals with kleptomania had told their spouses about the behavior [340].

The DSM-5-TR diagnostic criteria for kleptomania are [11]:

Preliminary data from treatment-seeking patients show gender differences in clinical features and comorbid disorders that may reflect biologic and sociocultural factors with implication for prevention and treatment. Women and men with kleptomania both show substantial symptom severity and functional impairment. Women are more likely than men to be married (47.1% vs. 25.9%), experience shoplifting onset at a later age (20.9 years vs. 14 years), steal household items, hoard stolen items, and have a comorbid eating disorder. Men are more likely to steal electronic goods and have another impulse-control disorder [351].

Another study of patients with Parkinson disease identified addictive behaviors in 14% of patients receiving any dopaminergic medication and 17% of patients receiving dopamine agonists. Behaviors included compulsive gambling (5%), compulsive sexual behavior (3.5%), compulsive shopping (6%), and binge-eating disorder (4%). Compulsive behaviors were more common with dopamine agonists than levodopa and other medications (17.1% vs. 6.9%). The prevalence was similar with the two most commonly used dopamine agonists, pramipexole (17.7%) and ropinirole (15.5%) [357]. Underlying susceptibility factors are suggested by the relatively small proportion of patients with Parkinson disease exposed to dopamine agonists who develop impulse control disorders. In these patients, risk factors for impulse control disorder during dopamine agonist therapy include levodopa treatment, age younger than 65 years, being unmarried, high caffeine use, family history of gambling problems, and current cigarette smoking. Other associated factors were functional impairment, depression, anxiety, obsessive-compulsive symptoms, impulsivity, and novelty-seeking. These risk factors show similarity to those reported in substance use disorders and gambling disorder and suggest common neurobiologic substrates [357].

Aripiprazole, an atypical antipsychotic drug, has been linked to treatment-emergent pathologic gambling in eight adult male patients with schizophrenia or bipolar disorder [359]. All had histories of substance use disorders and non-pathologic gambling before taking aripiprazole. Patient histories showed aripiprazole initiation coincided with intensified urges to gamble or loss of control over gambling; discontinuation of aripiprazole coincided with cessation of severe gambling urges or loss of control [359]. While acknowledging this association, the authors of one analysis caution that since Parkinson disease is itself associated with pathologic gambling, further studies are warranted [360].

In patients with Parkinson disease, behavioral addiction symptoms improve after decreasing or discontinuing dopamine agonists; however, many patients do not tolerate replacement with levodopa for treatment of motor symptoms. Compared with patients without impulse control disorders, patients with Parkinson disease and impulse control disorders are at increased risk for dopamine agonist withdrawal syndrome, characterized by craving, autonomic, and psychiatric symptoms. Efforts to manage behavioral addiction symptoms while maintaining dopamine agonist therapy have been evaluated with amantadine and naltrexone. Research shows mixed or incomplete response. Preclinical studies identified possible efficacy with the atypical antidepressant mirtazapine [357].