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Andrew Jen, Erika FH Saunders, Rollyn M Ornstein, Masoud Kamali and Melvin G McInnis

International Journal of Bipolar Disorders20131:13


  • Received: 15 June 2013
  • Accepted: 29 July 2013
  • Published: 6 August 2013

Eating disorders (ED) are noted to occur with bipolar disorder (BD), but relationships between additional comorbidities, clinical correlates, and personality factors common to both remain largely unknown.


Using data from the Prechter Longitudinal Study of Bipolar Disorder, we measured the prevalence and demographic factors of comorbid ED with BD, presence of additional comorbidity of anxiety and substance use disorders, psychosis, suicide attempts, mixed symptoms, childhood abuse, impact of NEO-Personality Inventory (NEO-PI) personality factors, and mood outcome in 354 patients with BD. We analyzed the prevalence of ED using both broad and narrow criteria.

Results and discussion

ED was more common in the Prechter BD sample than the general population, with the majority of those with ED being female. Anxiety disorders, alcohol abuse/dependence, and NEO-PI N5 impulsiveness were independently associated with ED in a multivariable linear regression analysis. BD age at onset was earlier in the ED group than that in the non-ED group and was earlier than the average onset of ED. Anxiety occurred before ED and alcohol use disorders after both BD and ED. Childhood trauma was associated with ED. Impulsivity and anxiety associated with BD may fuel ED and put patients at risk for other impulsivity-related disorders such as alcohol use disorders. ED was associated with more severe and variable moods and more frequent depression. Patients with BD should be regularly screened for ED, anxiety disorders, and alcohol use disorders, and comorbidity should be promptly addressed.


Bipolar disorder (BD) is an episodic, often disabling disorder of mood, energy, and cognition that has a high level of comorbidity with other psychiatric conditions including anxiety disorders (Simon et al. 2004; Saunders et al. 2012; Potash et al. 2007) and substance abuse (Merikangas et al. 2008; Saunders et al. 2009; Potash et al. 2007) and often results in suicidal ideation and attempts (Chen and Dilsaver 1996; Goodwin and Jamison 2007; Potash et al. 2007) and psychosis (Potash et al. 2007; Potash et al. 2003). Comorbidity with eating disorders (ED), including anorexia nervosa (AN), bulimia nervosa (BN), and binge eating disorder (BED), is a relatively understudied area that may illuminate opportunities for improved treatment for those with both disorders. EDs collectively include an alteration in hunger and satiation cues and overvaluing the role of body size and shape in self-image. Data demonstrate high comorbidity between BD and various EDs, especially among females (Fornaro et al. 2010; McElroy et al. 2011; Brietzke et al. 2011; Seixas et al. 2012). The estimated prevalence of ED in BD has varied widely but ranges between 6% and 27% in BD, many times greater than the population prevalence of 3.6% to 10% (McElroy et al. 2005 2006). EDs are associated with the depressive phases of BD (Mantere et al. 2010), and comorbidity confers greater disease burden (Brietzke et al. 2011). EDs were found to be significantly more common in patients experiencing subsyndromal affective symptoms of BD than patients who were euthymic or fully syndromal (McElroy et al. 2005).

Personality features and temperament may affect the predilection to psychiatric illness and influence the presentation of psychiatric illnesses with regards to comorbidities, biology, and course of illness (Evans et al. 2012a, b; McCrae and Costa 2003; Jylha et al. 2011). When rated with the NEO-Personality Inventory (NEO-PI), BD patients are typically found to have higher scores on neuroticism and openness to experience but lower scores on agreeableness, conscientiousness, and extraversion; and those who were prone to depression were high in neuroticism and low in extraversion, while those prone to mania were higher in extraversion than those prone to depression (Barnett et al. 2011). There may also be differences between bipolar disorder type I and bipolar disorder type II (BP II); in one study, BP II patients scored higher on neuroticism and facets of anxiety, depression, self-consciousness, and vulnerability and lower on extraversion and its facets of positive emotion, as well as conscientiousness and its facets of competence and achievement-striving (Kim et al. 2012).

Both patients with ED and those with BD are vulnerable to negative mood, scoring higher on neuroticism and lower on extraversion and openness to experience on the NEO-PI-R when compared to a representative general population (De Bolle et al. 2011). Patients with EDs and self-injurious behavior appear to be more anxious, more willing to please, and less cheerful, efficient, and ambitious (Claes et al. 2004; Davis and Karvinen 2002). Personality dimensions in patients with EDs may be independent of comorbidity with mood; BN patients had lower well-being compared to people without ED independent of depression, and elevated stress reactivity suggests that BN patients are generally more nervous, upset, and troubled by guilt than other groups of ED patients (Peterson et al. 2010). In the same study, BED patients, like BN patients, scored lower on well-being compared to normal weight comparisons; however, they also score higher on harm avoidance and lower than a normal weight comparison group on positive emotionality (Peterson et al. 2010). Obesity itself has strong associations with emotional distress and depression (Revah-Levy et al. 2011; Petry et al. 2008; de Wit et al. 2010). For example, obese patients have higher depression scores compared to normal weight controls; however, obese people with BED have even higher levels of depression than obese subjects without BED, and they also have a greater tendency towards outward expression of anger (Fau et al. 2003). Patients with BD have elevated rates of being overweight and obese compared to a control population (McElroy et al. 2005). In a systematic review of BD patients, 58% were overweight and 21% had comorbid obesity (Krishnan 2005). Obesity is also associated with an elevated risk of ED psychopathology among BD patients (Wildes et al. 2008). Given the common comorbidity and some shared symptoms such as impulsivity in BD and ED, personality dimensions may overlap in the two disorders. However, while both groups of disorders have been studied separately in the context of personality traits, literature comparing similarities and differences between these two classes is sparse.

To further assess the prevalence, clinical correlates, comorbidities, and personality factors involved in EDs in BD, we systematically examined co-occurring lifetime EDs, other psychiatric comorbidities, and personality traits in patients enrolled in the Prechter Longitudinal Study of Bipolar Disorder. The Prechter Longitudinal Study is a naturalistic, observational study designed to link detailed clinical assessment of psychiatric and medical history, as well as sleep, stress, environmental factors, substance use, personality, and cognition, to clinical outcomes and genetic and biological data for patients being treated with usual clinical care. We hypothesized that EDs would be more common among BD patients in our sample compared to the rates of reported ED in the general population from epidemiological studies, particularly among females, and that the presence of an ED comorbidity would be associated with more severe clinical correlates and additional significant psychiatric comorbidities, particularly anxiety disorders, substance abuse/dependence, and impulsive personality traits.


The Prechter Longitudinal Study of Bipolar Disorder is an ongoing naturalistic, observational study of bipolar disorder, conducted with IRB approval (IRBMED HUM000606) at the University of Michigan. De-identified data from the P5 cohort (the participants enrolled between 2005 and 2010) were used in the analysis performed at the Pennsylvania State University College of Medicine, and data were extracted in February 2012. Subjects may enter the study regardless of mood state, and clinical status at baseline is reported in Tables 1 and 2. In this analysis, we used the data from the baseline visit to investigate the lifetime prevalence of ED, comorbidities, and phenotype of BD with ED. Initial evaluation included the Diagnostic Interview for Genetic Studies (DIGS) (Nurnberger et al. 1994), NEO-Personality Inventory, Revised NEO-PI-R (Costa and McCrae 1992), clinician-driven rating scales of mood, questionnaires related to mood and environmental and family stress, personality, drug and alcohol use, neuropsychological testing, physical exam for height and weight, and a blood draw for genetics and saliva collection for cortisol. A best estimate process by at least two independent psychiatrists or psychologists was used to determine diagnoses (Leckman et al. 1982). For this analysis, the frequency, clinical correlates, and personality dimensions of ED was determined in BD individuals (bipolar disorder type I, n = 263; bipolar disorder type II, n = 59; bipolar disorder NOS, n = 23; schizoaffective disorder, bipolar type, n = 9). Diagnosis and features of illness were obtained from the DIGS and the best estimate process; personality factors including neuroticism, extroversion, openness, agreeableness, conscientiousness, and the N5 facet score for impulsiveness were obtained from the NEO-PI-R. In addition, some subjects completed the Barrett Impulsiveness Scale (BIS) (Barratt 1975) (n = 174) and the childhood trauma questionnaire (CTQ) (Bernstein et al. 1997 1994) (n = 272). Self-rated questionnaires, including the Patient Health Questionnaire (PHQ-9) (Kroenke et al. 2001) and the Altman Self-Rating Mania Scale (ASRM) (Altman et al. 1997), were completed every 2 months for 2 years (n = 277). Baseline depressive symptoms were measured using the Hamilton Depression Rating Scale (Hamilton 1960), and manic symptoms were measured with the Young Mania Rating Scale (Young et al. 1978). Mood outcomes were characterized by severity, variability, and frequency of clinically significant symptoms of depression or mania through the duration of follow-up, which differed for each participant. The severity of depression outcome was defined for each individual by the maximum PHQ-9 score over follow-up; the severity of mania outcome was defined for each individual by the maximum ASRM score over follow-up. The variability of the depression outcome was defined for each individual by the standard deviation in PHQ-9 scores over the duration of follow-up; the variability of the mania outcome was defined by the standard deviation in ASRM scores over the duration of follow-up. The frequency of clinically significant depressive or manic symptoms was defined as the proportion of the follow-up period that the individual had a PHQ-9 or ASRM score over 5.

Table 1

Demographics/description of sample

Non-ED (n = 291)

ED (n = 63)

p value

Mean (SD)

Mean (SD)

Age at interview

41.02 (13.20)

36.60 (11.80)


BD age at onset

18.41 (7.90)

15.08 (6.70)

2 × 10−3


28.95 (6.30)

29.78 (8.20)




61.97 (14.07)

67.40 (12.77)



49.62 (11.81)

50.76 (11.88)



56.84 (11.71)

61.06 (11.78)



49.15 (12.59)

43.83 (15.33)

4 × 10−3


42.81 (13.20)

39.95 (14.13)


 N5 impulsiveness

57.12 (10.71)

63.97 (11.06)

<1 × 10−3

 BIS total (n = 143/31)

66.00 (13.05)

70.81 (14.00)


 CTQ Total (n = 222/50)

48.19 (17.60)

57.18 (20.54)

2 × 10−3

Outcome measures (n = 228/49)

 Depression severity

14.2 (7.2)

18.6 (5.9)

<1 × 10−3

 Depression frequency

.59 (.37)

.78 (.26)

<1 × 10−3

 Depression variability

3.9 (2.4)

4.9 (2.4)


 Mania severity

7.7 (4.3)

8.5 (4.6)


 Mania frequency

.25 (.28)

.23 (.24)


 Mania variability

2.4 (1.4)

2.9 (1.8)


 Mixed symptoms frequency

.43 (.50)

.51 (.51)


Table 2

Clinical description of samples

n(% of Non-ED)

n(% of ED)

p value

Mean (SD)

Mean (SD)


185 (64)

52 (83)

4 × 10−3

Bipolar disorder type I

218 (75)

45 (71)

Bipolar disorder type II

48 (17)

11 (18)

Bipolar disorder NOS

18 (6)

5 (8)

Schizoaffective disorder, bipolar type

7 (2)

2 (3)


Mood state at baseline


135 (53)

13 (23)


88 (34)

34 (60)


34 (13)

10 (18)

<1 × 10−3

All narrow ED (% of all)

38 (11)

 Narrow anorexia (% of all)

6 (2)

 Narrow bulimia (% of all)

13 (4)

 Binge eating disorder (% of all)

29 (8)

Broad anorexia (% of all)

16 (5)

Broad bulimia (% of all)

36 (10)

Any anxiety disorder

102 (35)

40 (64)

<1 × 10−3

 Obsessive compulsive disorder

10 (3)

10 (16)

<1 × 10−3

 Panic disorder

64 (22)

26 (41)


 Social phobia

33 (11)

17 (34)

1 × 10−3

 Specific phobia

24 (8)

11 (18)



11 (4)

3 (5)


Alcohol use disorder

120 (41)

38 (60)

6 × 10−3

Drug use disorder

98 (34)

27 (43)



157 (58)

30 (49)


Suicide attempts

113 (40)

25 (40)


Mixed symptoms

109 (42)

34 (60)


Diagnoses and assessments

Subjects were classified into ED diagnostic categories using narrow and broad phenotypes. The narrow phenotypes included AN, BN, and BED as diagnosed using Diagnostic and Statistical Manual of Mental Disorders IV, Text Revision (DSM-IV-TR) criteria. Broader diagnoses for AN and BN were created consistent with proposed revisions to ED diagnosis for DSM-5. A broad AN diagnosis was determined if the patient at one point weighed less than somebody thought they ought to weigh, lost weight on purpose, and had a..

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Post-traumatic stress disorder (PTSD) is a disorder that develops in some people who have experienced a shocking, scary, or dangerous event.

It is natural to feel afraid during and after a traumatic situation. Fear triggers many split-second changes in the body to help defend against danger or to avoid it. This “fight-or-flight” response is a typical reaction meant to protect a person from harm. Nearly everyone will experience a range of reactions after trauma, yet most people recover from initial symptoms naturally. Those who continue to experience problems may be diagnosed with PTSD. People who have PTSD may feel stressed or frightened, even when they are not in danger.

Signs and Symptoms

Not every traumatized person develops ongoing (chronic) or even short-term (acute) PTSD. Not everyone with PTSD has been through a dangerous event. Some experiences, like the sudden, unexpected death of a loved one, can also cause PTSD. Symptoms usually begin early, within 3 months of the traumatic incident, but sometimes they begin years afterward. Symptoms must last more than a month and be severe enough to interfere with relationships or work to be considered PTSD. The course of the illness varies. Some people recover within 6 months, while others have symptoms that last much longer. In some people, the condition becomes chronic.

A doctor who has experience helping people with mental illnesses, such as a psychiatrist or psychologist, can diagnose PTSD.

To be diagnosed with PTSD, an adult must have all of the following for at least 1 month:

  • At least one re-experiencing symptom
  • At least one avoidance symptom
  • At least two arousal and reactivity symptoms
  • At least two cognition and mood symptoms
Re-experiencing symptoms include:
  • Flashbacks—reliving the trauma over and over, including physical symptoms like a racing heart or sweating
  • Bad dreams
  • Frightening thoughts

Re-experiencing symptoms may cause problems in a person’s everyday routine. The symptoms can start from the person’s own thoughts and feelings. Words, objects, or situations that are reminders of the event can also trigger re-experiencing symptoms.

Avoidance symptoms include:
  • Staying away from places, events, or objects that are reminders of the traumatic experience
  • Avoiding thoughts or feelings related to the traumatic event

Things that remind a person of the traumatic event can trigger avoidance symptoms. These symptoms may cause a person to change his or her personal routine. For example, after a bad car accident, a person who usually drives may avoid driving or riding in a car.

Arousal and reactivity symptoms include:
  • Being easily startled
  • Feeling tense or “on edge”
  • Having difficulty sleeping
  • Having angry outbursts

Arousal symptoms are usually constant, instead of being triggered by things that remind one of the traumatic events. These symptoms can make the person feel stressed and angry. They may make it hard to do daily tasks, such as sleeping, eating, or concentrating.

Cognition and mood symptoms include:
  • Trouble remembering key features of the traumatic event
  • Negative thoughts about oneself or the world
  • Distorted feelings like guilt or blame
  • Loss of interest in enjoyable activities

Cognition and mood symptoms can begin or worsen after the traumatic event, but are not due to injury or substance use. These symptoms can make the person feel alienated or detached from friends or family members.

It is natural to have some of these symptoms after a dangerous event. When people have very serious symptoms that go away after a few weeks, it is called acute stress disorder. When the symptoms last more than a month, seriously affect one’s ability to function, and are not due to substance use, medical illness, or anything except the event itself, they might be PTSD. Some people with PTSD don’t show any symptoms for weeks or months. PTSD is often accompanied by depression, substance abuse, or one or more of the other anxiety disorders.

Do children react differently than adults?

Children and teens can have extreme reactions to trauma, but some of their symptoms may not be the same as adults. Symptoms sometimes seen in very young children (less than 6 years old), these symptoms can include:

  • Wetting the bed after having learned to use the toilet
  • Forgetting how to or being unable to talk
  • Acting out the scary event during playtime
  • Being unusually clingy with a parent or other adult

Older children and teens are more likely to show symptoms similar to those seen in adults. They may also develop disruptive, disrespectful, or destructive behaviors. Older children and teens may feel guilty for not preventing injury or deaths. They may also have thoughts of revenge.

Risk Factors

Anyone can develop PTSD at any age. This includes war veterans, children, and people who have been through a physical or sexual assault, abuse, accident, disaster, or other serious events. According to the National Center for PTSD, about 7 or 8 out of every 100 people will experience PTSD at some point in their lives. Women are more likely to develop PTSD than men, and genes may make some people more likely to develop PTSD than others.

Not everyone with PTSD has been through a dangerous event. Some people develop PTSD after a friend or family member experiences danger or harm. The sudden, unexpected death of a loved one can also lead to PTSD.

Why do some people develop PTSD and other people do not?

It is important to remember that not everyone who lives through a dangerous event develops PTSD. In fact, most people will not develop the disorder.

Many factors play a part in whether a person will develop PTSD. Some examples are listed below. Risk factors make a person more likely to develop PTSD. Other factors, called resilience factors, can help reduce the risk of the disorder.

Some factors that increase risk for PTSD include:

  • Living through dangerous events and traumas
  • Getting hurt
  • Seeing another person hurt, or seeing a dead body
  • Childhood trauma
  • Feeling horror, helplessness, or extreme fear
  • Having little or no social support after the event
  • Dealing with extra stress after the event, such as loss of a loved one, pain and injury, or loss of a job or home
  • Having a history of mental illness or substance abuse

Some factors that may promote recovery after trauma include:

  • Seeking out support from other people, such as friends and family
  • Finding a support group after a traumatic event
  • Learning to feel good about one’s own actions in the face of danger
  • Having a positive coping strategy, or a way of getting through the bad event and learning from it
  • Being able to act and respond effectively despite feeling fear

Researchers are studying the importance of these and other risk and resilience factors, including genetics and neurobiology. With more research, someday it may be possible to predict who is likely to develop PTSD and to prevent it.

Treatments and Therapies

The main treatments for people with PTSD are medications, psychotherapy (“talk” therapy), or both. Everyone is different, and PTSD affects people differently, so a treatment that works for one person may not work for another. It is important for anyone with PTSD to be treated by a mental health provider who is experienced with PTSD. Some people with PTSD may need to try different treatments to find what works for their symptoms.

If someone with PTSD is going through an ongoing trauma, such as being in an abusive relationship, both of the problems need to be addressed. Other ongoing problems can include panic disorder, depression, substance abuse, and feeling suicidal.


The most studied type of medication for treating PTSD are antidepressants, which may help control PTSD symptoms such as sadness, worry, anger, and feeling numb inside. Other medications may be helpful for treating specific PTSD symptoms, such as sleep problems and nightmares.

Doctors and patients can work together to find the best medication or medication combination, as well as the right dose. Check the U.S. Food and Drug Administration website for the latest information on patient medication guides, warnings, or newly approved medications.


Psychotherapy (sometimes called “talk therapy”) involves talking with a mental health professional to treat a mental illness. Psychotherapy can occur one-on-one or in a group. Talk therapy treatment for PTSD usually lasts 6 to 12 weeks, but it can last longer. Research shows that support from family and friends can be an important part of recovery.

Many types of psychotherapy can help people with PTSD. Some types target the symptoms of PTSD directly. Other therapies focus on social, family, or job-related problems. The doctor or therapist may combine different therapies depending on each person’s needs.

Effective psychotherapies tend to emphasize a few key components, including education about symptoms, teaching skills to help identify the triggers of symptoms, and skills to manage the symptoms. One helpful form of therapy is called cognitive behavioral therapy, or CBT. CBT can include:

  • Exposure therapy. This helps people face and control their fear. It gradually exposes them to the trauma they experienced in a safe way. It uses imagining, writing, or visiting the place where the event happened. The therapist uses these tools to help people with PTSD cope with their feelings.
  • Cognitive restructuring. This helps people make sense of the bad memories. Sometimes people remember the event differently than how it happened. They may feel guilt or shame about something that is not their fault. The therapist helps people with PTSD look at what happened in a realistic way.

There are other types of treatment that can help as well. People with PTSD should talk about all treatment options with a therapist. Treatment should equip individuals with the skills to manage their symptoms and help them participate in activities that they enjoyed before developing PTSD.

How Talk Therapies Help People Overcome PTSD
Talk therapies teach people helpful ways to react to the frightening events that trigger their PTSD symptoms. Based on this general goal, different types of therapy may:

  • Teach about trauma and its effects
  • Use relaxation and anger-control skills
  • Provide tips for better sleep, diet, and exercise habits
  • Help people identify and deal with guilt, shame, and other feelings about the event
  • Focus on changing how people react to their PTSD symptoms. For example, therapy helps people face reminders of the trauma.
Beyond Treatment: How can I help myself?

It may be very hard to take that first step to help yourself. It is important to realize that although it may take some time, with treatment, you can get better. If you are unsure where to go for help, ask your family doctor. You can also check NIMH’s Help for Mental Illnesses page or search online for “mental health providers,” “social services,” “hotlines,” or “physicians” for phone numbers and addresses. An emergency room doctor can also provide temporary help and can tell you where and how to get further help.

To help yourself while in treatment:

  • Talk with your doctor about treatment options
  • Engage in mild physical activity or exercise to help reduce stress
  • Set realistic goals for yourself
  • Break up large tasks into small ones, set some priorities, and do what you can as you can
  • Try to spend time with other people, and confide in a trusted friend or relative. Tell others about things that may trigger symptoms.
  • Expect your symptoms to improve gradually, not immediately
  • Identify and seek out comforting situations, places, and people

Caring for yourself and others is especially important when large numbers of people are exposed to traumatic events (such as natural disasters, accidents, and violent acts).

Next Steps for PTSD Research

In the last decade, progress in research on the mental and biological foundations of PTSD has lead scientists to focus on better understanding the underlying causes of why people experience a range of reactions to trauma.

  • NIMH-funded researchers are exploring trauma patients in acute care settings to better understand the changes that occur in individuals whose symptoms improve naturally.
  • Other research is looking at how fear memories are affected by learning, changes in the body, or even sleep.
  • Research on preventing the development of PTSD soon after trauma exposure is also under way.
  • Other research is attempting to identify what factors determine whether someone with PTSD will respond well to one type of intervention or another, aiming to develop more personalized, effective, and efficient treatments.
  • As gene research and brain imaging technologies continue to improve, scientists are more likely to be able to pinpoint when and where in the brain PTSD begins. This understanding may then lead to better targeted treatments to suit each person’s own needs or even prevent the disorder before it causes harm.
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. Author manuscript; available in PMC 2018 Oct 3.
Published in final edited form as:
PMCID: PMC6169314
PMID: 28102908
The publisher’s final edited version of this article is available at Int J Eat Disord
See other articles in PMC that cite the published article.

Remarkable progress has been made in developing psychosocial interventions for eating disorders and other mental disorders. Two priorities in providing treatment consist of addressing the research-practice gap and the treatment gap. The research-practice gap pertains to the dissemination of evidence-based treatments from controlled settings to routine clinical care. Closing the gap between what is known about effective treatment and what is actually provided to patients who receive care is crucial in improving mental health care, particularly for conditions such as eating disorders. The treatment gap pertains to extending treatments in ways that will reach the large number of people in need of clinical care who currently receive nothing. Currently, in the United States (and worldwide), the vast majority of individuals in need of mental health services for eating disorders and other mental health problems do not receive treatment. This article discusses the approaches required to better ensure: 1) that more people who are receiving treatment obtain high-quality, evidence-based care, using such strategies as train-the-trainer, web-centered training, best-buy interventions, electronic support tools, higher-level support and policy; and 2) that a higher proportion of those who are currently underserved receive treatment, using such strategies as task shifting and disruptive innovations, including treatment delivery via telemedicine, the Internet, and mobile apps.


Eating disorders are associated with high medical and psychiatric comorbidity, poor quality of life, and high mortality. Mortality from anorexia nervosa (AN) is the highest of all mental disorders, and eating disorders rank as the 12th leading cause of disability in young women in high-income nations. The development and evaluation of evidence-based psychosocial interventions (EBPIs) for eating disorders and other psychiatric disorders are remarkable advances. EBPIs refer to interventions that have been evaluated in randomized controlled clinical trials, where treatments, client samples, and outcomes have been well specified, and where the effects have been replicated by an independent research team. A current priority is to disseminate—transmit information about a treatment (e.g., its nature, effectiveness, indications, characteristics)—from research to practice, and implement, or actually adopt and use, those treatments in routine clinical practice, thus addressing the “research-practice gap.” Extending interventions from research to practice is a critical step in the process of improving mental health care, but another crucial step is extending treatments in ways that will reach the large number of people in need of clinical care but who are not receiving services, which we will refer to here as addressing the “treatment gap.” Disseminating EBPIs to clinical practice alone will not necessarily address this latter need. This paper discusses these critical gaps in the treatment of eating disorders, that is, the research-practice gap and the treatment gap, and the approaches that are needed to address them effectively.

Critical Gaps in Treatment
Research-Practice Gap

The research-practice gap refers to the discrepancy between what is known about effective treatment and what is actually provided to patients who receive care. Among those who actually receive services for mental health problems, what do they receive? As part of the National Comorbidity Survey-Replication in the United States (US), over 9,000 individuals with psychiatric disorders answered questions about their treatment that included who the service provider was (e.g., psychiatrist, family physician, social worker, spiritual advisor, other) and the type of treatment they received (e.g., self-help group, medication, hospital admission). Minimally adequate treatment was defined as receiving an intervention (e.g., medication, psychotherapy) that followed evidence-based guidelines for the specific disorder and included multiple contacts (rather than only one visit). For individuals with a psychiatric disorder, 21.5% received treatment from a mental health specialist; 41.7% received treatment if this is expanded to include contact with any health-care person, in addition to those trained in mental health. For those who did not meet full criteria for disorder (subclinical disorder), 4.4% received treatment from a mental health specialist and 10.1% received treatment if this is expanded to include any contact. Overall, across the entire sample, only 32.7% were classified as receiving at least minimally adequate treatment based on evidence-based treatment guidelines. This issue has been studied internationally as well. The World Health Organization (WHO) provided extensive data on mental disorder treatment receipt from surveys of over 60,000 adults in 14 countries in the Americas, Europe, the Middle East, Africa, and Asia. The proportion of respondents who received treatment for emotional or substance-use disorders during the previous 12 months ranged from a low of 0.8% (Nigeria) to a high of 15.3% (US)—percentages refer to those who received treatment among those in need. “Receiving services” was based on asking respondents if they ever saw anyone from a long list of caregivers as an outpatient or inpatient for problems with emotions, nerves, mental health, or use of alcohol or drugs. Included were mental health professionals (e.g., psychiatrist, psychologist), general medical or other professionals (e.g., general practitioner, occupational therapist), religious counselors (e.g., minister, sheikh), and traditional healers (e.g., herbalist, spiritualist). The precise service provided by these individuals was not identified and the duration of the intervention was not specified, but receiving services required at least one contact. Thus when we say that 15% of individuals in the US with any type of mental health disorder received treatment, information is ambiguous and could be one contact with someone who has had no training in mental health.

There is worrisome evidence that access to EBPIs is actually diminishing. Based on service use data from two representative surveys of the US general population in 1998 (N = 22,953) and 2007 (N = 29,370), spending on psychotherapy declined by more than a third, from $12.74 billion in 1998 to $8.35 billion in 2007 (for ease of interpretation, these amounts are in current dollars, as of 2016); in contrast, the use of patients receiving psychotropic medication only increased from 44.1% to 57.4%. Importantly, it is not known the extent to which the treatments delivered were EBPIs but tempting to speculate that it might be a small proportion. Also there is the issue that the programs training the major providers of psychotherapy (i.e., psychiatrists, psychologists, social workers) are generally not providing competency-based instruction in EBPIs; although programs may provide exposure to EBPIs, few programs require the acquisition of competence through both a didactic and clinical supervision., Notably, the most recent American Psychological Association Standards of Accreditation, which go into effect in 2017, mandate some training in EBPIs (e.g., “must demonstrate a fundamental understanding of and competency in…evidence-based professional practice”), but it is unknown how this will be enforced, and further, how to do competency-based training has yet to be fully delineated. Also, this only affects accredited psychology training programs, and there are far more practitioners who are not psychologists as well as many who come from unaccredited programs for which these standards would not apply.

Likewise, when individuals with eating disorders receive care, more often than not, it is not an EBPI. The number of eating disorder specialist clinicians who report adhering to evidence-based protocols is between 6 and 35%, with far more clinicians reporting using an eclectic mix of techniques derived from EBPIs and some techniques that are not even supported at that level. Even when clinicians say that they are using an EBPI for eating disorders, such as cognitive-behavioral therapy (CBT) or family-based treatment (FBT), they often omit key elements of those approaches.,

There are a number of reasons to believe that translation from research to practice and dissemination of EBPIs in the field of eating disorders is warranted. First, it has been reliably demonstrated that there is specificity of effects for specialist psychological treatments for eating disorders. For example, 5 months of enhanced cognitive-behavioral therapy (CBT-E) has been shown to be markedly superior to 2 years of psychoanalytic psychotherapy for bulimia nervosa (BN), standing in stark contrast to the widespread claim that there are no differences in outcomes between psychological treatments and that they all work through common or non-specific processes. This study provides strong support for the specificity of a key EBPI for BN, and per Hollon and Wilson, provides one of the clearest examples of the superiority of one well-implemented psychological treatment over another. Many other randomized controlled trials demonstrate specificity of effects for other psychological treatments for eating disorders as well., Furthermore, pharmacological treatments for eating disorders have reliably shown small to moderate effects, whereas evidence-based psychological treatments have reliably demonstrated large effects and combining medication with psychotherapy interventions fails to significantly enhance outcomes.

Second, data suggest that EBPIs are superior to TAU for eating disorders. For instance, CBT guided self-help (CBTgsh), delivered in 8 sessions in a health maintenance organization setting, resulted in greater abstinence from binge eating at 6- and 12-month follow-ups than TAU offered within the health plan among individuals with binge-type eating disorders. Furthermore, CBTgsh was also found to be more cost-effective, due to reduced use of TAU services in that group, resulting in lower net costs for the CBTgsh group despite the additional cost of CBTgsh itself. For adolescents with AN, FBT has been compared to standardized versions of the “usual” treatments offered in the community, including psychodynamic individual therapy, non-specific individual therapy, and systemic family therapy, and has consistently been demonstrated to be superior.

Finally, there appears to be indication of an association between therapist competence and outcome, suggesting that implementing a treatment better has value and setting up the need for further training in EBPIs. Although these studies are not eating disorder-specific, they are suggestive. For example, among patients with depression receiving cognitive therapy, competence predicted session-to-session symptom change early in treatment and also predicted evaluator-rated end-of-treatment depressive symptom severity. Likewise, competence has been found to be significantly associated with outcome for patients with anxiety disorders receiving CBT,, accounting for 48% of the variance in outcome in one study. Even amongst work that has not found a general competence-outcome association, relations between these constructs are suggested. For example, the relationship between competence and patient outcome with CBT was investigated among 43 therapists treating 1247 patients over the period of one year in England. Results found little support of a general association between CBT competence and patient outcome. However, significantly more patients of the most competent therapists demonstrated a reliable improvement in their symptoms of anxiety than would be expected by chance alone, and fewer experienced no reliable change. Likewise, significantly more patients treated by the least competent therapists experienced a reliable deterioration in their anxiety symptoms than would be expected. Taken together, these lines of study—the demonstrated specificity of effects for specialist psychological treatments for eating disorders, the superiority of EBPIs over TAU for eating disorders, and the competence-outcome association—indicate that translation from research to practice in the field of eating disorders is clearly warranted.

Treatment Gap

The treatment gap refers to the difference in the proportion of people who have disorders or a particular disorder (prevalence) and the proportion of those individuals who actually receive care., In the US, millions of children, adolescents, and adults experience eating disorders and other significant mental health problems and receive no help whatsoever. Based on results of the National Comorbidity Survey-Replication, lifetime prevalence estimates of AN, BN, binge eating disorder (BED), subthreshold BED, and any binge eating in the US are 0.6%, 1.0%, 2.8%, 1.2%, and 4.5%. From a US population of approximately 300 million when this study was published, this translates to 30 million people being affected, and likely even more if we consider the US population growth since that time. In terms of mental disorders more generally, based on results of the National Comorbidity Survey and its Replication, 26% of the US population meet criteria for a psychiatric disorder within the past 12 months,, and 46% of the US population have met criteria for a psychiatric disorder at some point in their lives. For ease of computation, consider that approximately 25% of the US population experience a psychiatric disorder during a given year and 50% in their lifetime. This translates to 75 million and 150 million people, respectively, using the US population of 300 million from the time period when these studies were published. Remarkably, these may even be conservative estimates, as some disorders (e.g., schizophrenia) as well as subclinical disorders often are omitted from prevalence surveys. Separate lines of research have addressed the extent to which individuals in need of services actually receive them. In the US, approximately 70% in need of services do not receive any services, with the problem of access to care being even worse for certain groups. For example, racial/ethnic minority groups (e.g., African American, Hispanic, Native American) have much less access to care for mental disorders than do European Americans. African Americans are less likely to have access to services than are European Americans (12.5 vs. 25.4%), and Hispanic Americans are less likely to have adequate care than are European Americans (10.7 vs. 22.7%). Internationally, as many as 97% or more of those with severe mental health disorders go untreated in some countries.

The statistics regarding receipt of any treatment for eating disorders are equally dire—in the National Comorbidity Survey-Replication, only 16% of individuals with BN and 29% of individuals with BED had received treatment for emotional problems in the past 12 months. Similarly, less than 20% of college students with eating disorders report receiving treatment. There is a paradox such that few individuals with an eating disorder receive treatment specifically for the eating disorder, yet these individuals are actually more likely to receive treatment and incur higher health services use costs than individuals who do not have an eating disorder. Furthermore, individuals from racial/ethnic minority backgrounds with eating disorders are significantly less likely than their White counterparts to be diagnosed with an eating disorder, receive care or a referral for further evaluation, or to even be asked by a doctor about eating disorder symptoms. The lack of available services for most people and systematic disparities in accessibility of services underlie the importance of delivering services in ways that can reach many more people as well as target special groups.

Barriers to mental health care.

Many impediments or barriers stand in the way of people receiving mental health interventions

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. 2015 Jun; 17(2): 229–236. PMCID: PMC4518705
PMID: 26246796

Stephanie Knatz, PhD

Stephanie Knatz, University of California San Diego, Department of Psychiatry, San Diego, California, USA;

Christina E. Wierenga, PhD

Christina E. Wierenga, University of California San Diego, Department of Psychiatry, San Diego, California, USA;

Stuart B. Murray, DClinPsych, PhD

Stuart B. Murray, University of California San Diego, Department of Psychiatry, San Diego, California, USA;

Laura Hill, PhD

Laura Hill, Ohio State University, Department of Psychiatry, Columbus, Ohio, USA;

Walter H. Kaye, MD*

Walter H. Kaye, University of California San Diego, Department of Psychiatry, San Diego, California, USA;

Anorexia nervosa (AN) is a severe and debilitating disorder with significant medical and psychological sequelae. To date, there are no effective treatments for adults, resulting in high rates of chronicity, morbidity, and mortality. Recent advances in brain imaging research have led to an improved understanding of etiology and specific neurobiological mechanisms underlying symptoms. Despite this, there are no treatments focused on targeting symptoms using this empirically supported mechanistic understanding of the illness. Updated treatment approaches focused on targeting neurobiological mechanisms underlying core AN symptomatology are necessary to improve treatment out-comes for this population. Neurobiologically Enhanced With Family Eating Disorder Trait Response Treatment (NEW FED TR) is a neurobiologically informed treatment targeting key temperament constructs associated with the illness through the delivery of psychoeducation and skills training to patients and nominated carers.


Anorexia nervosa (AN) is a pernicious psychiatric illness associated with significant medical risk and a refractory course. Approximately 50% of individuals develop a chronic and relapsing illness course characterized by significant physical and psychological impairment. Given the magnitude of associated medical and psychological sequelae and the risk for prolonged illness, the development of effective treatments is of critical importance. To date, there are no behavioral or psychiatric treatments that have been proven to reverse core symptoms, and currently available treatments for AN adults have failed to demonstrate efficacy.,, Consequently, AN is associated with costly medical morbidity and high mortality rates. There is a critical need for continued research to address the dearth of efficacious treatments for this dangerous illness.

Several psychosocial, behavioral, and pharmacologic interventions have been investigated in adult AN5,,; however, evidence supporting currently available treatments is weak, and treatment effects, when found, are generally small., For instance, controlled medication trials examining selective serotonin reuptake inhibitors,, tricyclic antidepressants, and antipsychotic medication tend to be conflicted and uncertain as to whether there are changes in AN symptoms over time. Yet, despite the absence of a strong evidence base for these psychotropic medications, more than 50% of those with AN report the use of medication. With respect to behavioral treatments, some controlled trials indicate that long-term cognitive behavioral therapy may offer some efficacy in assisting with weight restoration,, although large-scale randomized trials suggest that specialist cognitive and psychodynamic treatments do not differ from treatment as usual in terms of weight restoration. Furthermore, attrition rates are high and the majority of patients remain underweight upon completion of treatment. A landmark study in 2002 illustrated that less than half of all those with AN recover. Relative to other psychiatric illnesses, advances in effective treatment approaches have been marginal and there are relatively few randomized controlled trials. The lack of response to currently available treatments suggests that new models of treatment are necessary, and improvements in methods for targeting core AN symptomatology are needed.

Despite the lack of advances in treatments for adult AN, a robust evidence base exists supporting familybased treatment (FBT) for adolescents with AN. FBT is a manualized form of specific eating disorder-focused family therapy in which parents are enlisted as the primary agents of change to oversee their adolescents’ recovery by ensuring appropriate food intake and other health-oriented behaviors associated with recovery. FBT demonstrates promising empirical evidence, in that up to 70% of patients are weight restored within a year of commencing treatment, and up to 40% of patients report being remitted of cognitive symptoms within a year.

To date, there are no published clinical trials examining the use of FBT in adults. A small case series applying a modification of FBT to adults demonstrated promising outcomes; however, the small sample consisted of young adults under the care of family members FBT may be an appropriate fit for young adults, but because of its reliance on parental control as the primary agent of change, it is less suitable for older adults who are more autonomous and less likely to be under the direct care of family. As such, effective treatments for older individuals who tend to have a longer duration of illness and a greater level of severity continue to be lacking. In summary, treatments are gravely needed for this subpopulation of “severe and enduring” individuals given that chronicity contributes to a poorer prognosis and significant health concerns leading to morbidity and mortality. Although the level of parental control prescribed in FBT is likely not well-suited for older adult individuals, elements of FBT should be considered for adult treatments, such as the encouragement of familial support and involvement, albeit in a more developmental appropriate fashion.

Using neurobiology to advance treatment

Despite the lack of gains in establishing effective clinical treatments for adult AN, there have been significant advances in our understanding of etiological influences associated with the illness. Genetic studies indicate that heritability accounts for approximately 50% to 80% of the risk of developing an eating disorder. Recent imaging, neurocognitive, and behavioral studies reveal that AN individuals tend to have specific temperament and personality traits related to neural circuit function, which are heavily implicated in the development and maintenance of the disorder., Associated traits known to contribute to AN symptomatology include anxiety, negative emotionality, perfectionism, inflexibility, and harm avoidance (HA). These temperament traits are interrelated and together contribute to appetite deregulation and mealtime behavior in AN, suggesting treatments that target these constructs may see improved clinical effects. Inarguably the most critical issue in treating individuals with AN is addressing food refusal and pursuit of emaciation. There is an anxiety-reducing effect of dietary restraint and caloric restriction for AN individuals,, whereas food consumption stimulates dysphoric mood. Moreover, enhanced inhibition, self-control, and/or an ability to delay reward may help to maintain persistent food restriction. Finally, disturbed interoceptive awareness of satiety or hunger, or even an alteration of primary gustatory processes, could play a role in assessing body states and responding to hunger cues. Imaging data further suggest that anticipatory anxiety contributes to restricted eating. For example, individuals with the ability to restrict their eating have an exaggerated anticipatory response to food cues that is anxious and aversive,, along with a diminished insular and striatal response to receipt of food. A disturbance of both anticipating and experiencing food stimuli may contribute to restricted eating in AN. This finding is consistent with the notion of reduced reward and/or enhanced satiety signals in regions that compute hunger-satiety homeostasis.

Clinical treatment approaches have not been developed and/or updated to reflect this mechanistic understanding of the disease. To date, the most widely used behavioral treatment models, such as cognitive behavioral therapy (CBT), used to address core AN symptomatology, are adaptations of treatments that were originally developed to address pathology specific to other psychiatric disorders. As such, they do not adequately address the unique and disease-specific mechanisms that underlie AN. These reasons may explain the limited efficacy of currently available treatments.

In order to continue to make advances in AN treatment, a paradigm shift is necessary in which interventions are developed based on empirically supported theoretical models describing underlying neurobiological mechanisms that may contribute to AN pathology and symptomatology. Indeed, a recent shift in psychiatric research has emphasized the exploration of the mechanistic pathways and constructs underpinning psychopathology, as opposed to focusing on a symptomoriented understanding of psychiatric illness. Treatments constructed using a bottom-up approach, where an understanding of underlying mechanisms inform specific treatment approaches are needed to improve effectiveness, but such treatments are only in early stages of development and testing.,

The neurobiological features underpinning AN have been comprehensively reviewed by our group.,,, This brief review is focused mainly on the potential application of these findings to the development of new, more effective clinical treatments. In addressing this gulf between evidence illustrating the neurobiological profile of AN, and current treatments designed to target core symptomatology, we have previously provided a preliminary overview of the development of a novel clinical treatment which is rooted in the unique neurobiology of AN. See Kaye et al for this more comprehensive review of theory and application. It is important to emphasize that there is very limited empirical evidence for this new approach. Rather, this paper speculates on constructs, in order to generate new ideas for innovative approaches. It is worth noting that many of these concepts have been incorporated into a brief treatment approach for adolescents with AN which has shown some efficacy in terms of improved long-term outcomes. Still, this current paper articulates hypotheses rather than conclusions regarding treatments for adults with AN. It remains unknown whether this treatment will prove to be effective. But perhaps what is most critical is stimulating the eating disorder field to devise treatments that address contributory neurobiological features.


In response to the critical need for effective treatments in adult AN, we have developed a neurobiologically informed treatment that draws upon the specific etiology characterizing AN. Neurobiologically Enhanced With Family Eating Disorder Trait Response Treatment (NEW FED TR) is a neurobiologically based treatment delivered to individuals with AN and their carers (eg, parents, siblings, spouses/significant others, friends, or anyone else in their support network who they would like to be involved in their recovery) developed to target AN-specific temperament, cognition, and eating behaviors. The comprehensive treatment aims to achieve a reduction in core symptoms by using behavioral approaches to target disease-specific neurobiological mechanisms. The treatment approach is informed by the understanding that underlying traits are stable and pervasive (versus transitory), and thus focuses on teaching AN individuals and their carers to manage AN symptoms by using these traits constructively (versus destructively through the pursuit of emaciation). Neuroimaging findings suggest mechanisms underlying anticipatory anxiety, reward insensitivity, and/or deficits in awareness of homeostatic needs (interoceptive awareness) contribute to AN. These alterations contribute to appetite dysregulation in AN, and are likely related to enhanced executive ability to inhibit incentive motivational drives. As such, they may reflect mechanisms of action to be targeted to regulate eating behavior in AN. NEW FED TR consists of modules aimed at targeting each of these constructs, delivered to both patients and carers. Each module is formatted to deliver: (i) neurobiological psychoeducation aimed at reducing blame and enlisting support; (ii) neurobiological skills training consisting of teaching skills to address deficits and facilitate constructive methods for using temperament; (iii) carer management strategies consisting of teaching carers effective response and management strategies; and (iv) experiential learning focused on practicing the implementation of skills and strategies in a therapeutic environment. Below we describe key aspects of the treatment in more detail.


The treatment is delivered in two segments that are conducted with the patient and nominated carers. The first segment is delivered via an intensive course, with patients and carers receiving 8 to 9 hours of treatment over 5 consecutive days. The 5-day intensive treatment is delivered in a multifamily format, with multiple families attending jointly. This intensive course is then followed by weekly outpatient follow-up sessions focused on monitoring weight and symptoms and facilitating continued practice of skills developed over the intensive 5-day course. The intensive nature of the treatment is intended to establish an ecologically valid meal structure, while allowing for immersive experiential learning, massed practice, and in-vivo therapist-guided training on key factors involved in recovery. Real-time therapist observation and intervention during target events such as mealtimes, acute emotional outbursts, and family interactions allows for both patients and carers to receive applicative, hands-on training and management skills. Tenets of neuroplasticity dictate that increased treatment frequency and intensity are critical components needed to elicit behavior change., Treatment models for anxiety indicate that intense, repeated, and focused in vivo practice is key to altering biologically driven avoidance behaviors by maximizing learning through massed practice and allowing close monitoring of compliance. The initial intensive course is intended to improve treatment adherence and maximize the possibility of initial success,

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John G. Gunderson M.D.  Published Online:1 May 2009

Objective: The purpose of this article is to describe the development of the borderline personality disorder diagnosis, highlighting both the obstacles encountered and the associated achievements.

Method: On the basis of a review of the literature, the author provides a chronological account of the borderline construct in psychiatry, summarizing progress in decade-long intervals.

Results: Borderline personality disorder has moved from being a psychoanalytic colloquialism for untreatable neurotics to becoming a valid diagnosis with significant heritability and with specific and effective psychotherapeutic treatments. Nonetheless, patients with this disorder pose a major public health problem while they themselves remain highly stigmatized and largely neglected.

Conclusions: Despite remarkable changes in our knowledge about borderline personality disorder, increased awareness involving much more education and research is still needed. Psychiatric institutions, professional organizations, public policies, and reimbursement agencies need to prioritize this need.

On April 1, 2008, the U.S. House of Representatives unanimously passed House Resolution 1005 supporting the month of May as borderline personality disorder awareness month. The resolution stated that “despite its prevalence, enormous public health costs, and the devastating toll it takes on individuals, families, and communities, [borderline personality disorder] only recently has begun to command the attention it requires.” House Resolution 1005, which was the outcome of public advocacy efforts, drew attention to the disproportion between the high public health significance of borderline personality disorder and the low levels of public awareness, funded research, and treatment resources associated with the disorder. A recurrent theme in this review is the persistence of borderline personality disorder as a suspect category largely neglected by psychiatric institutions, comprising a group of patients few clinicians want to treat.

The review highlights the major clinical, scientific, and public health issues, as well as some of the remarkable personalities, that have shaped the development of this diagnosis. It is necessarily selective. It is organized chronologically, beginning with the period before the diagnosis was used clinically and then dividing the subsequent period somewhat arbitrarily into decade-long intervals. This approach allows the review of the trials and tribulations of borderline personality disorder to proceed within the framework of the changes that were concurrently transforming psychiatry.

Before 1970—From Untreatable Patients to Personality Organization: “A Psychoanalytic Colloquialism”

The identification of patients as “borderline” first arose in an era when the psychoanalytic paradigm dominated psychiatry and our classification system was primitive. At that time classification was tied to analyzability: patients with neuroses were considered analyzable—and therefore treatable—and those with psychoses were considered not analyzable—and therefore untreatable.

The psychiatrists most responsible for introducing the label “borderline” were Stern (1) and Knight (2) . By identifying the tendency of certain patients to regress into “borderline schizophrenia” mental states in unstructured situations, these authors gave initial clinical meaning to the borderline construct. The primary category to which these patients were “borderline” was schizophrenia (37) . Still, until the 1970s the term “borderline” remained a rarely and inconsistently used “colloquialism within the psychoanalytic fraternity” (8) .

The construct took its next major step forward in 1967, when Kernberg (9) , a psychoanalyst concerned with the boundaries of analyzability, defined borderline as a middle level of personality organization bounded on one side by sicker patients who had psychotic personality organization and on the other by those who were healthier and had neurotic personality organization. As such, borderline personality organization was a broad form of psychopathology defined by primitive defenses (splitting, projective identification), identity diffusion, and lapses in reality testing (9) . Kernberg then went on to suggest that these patients could be successfully treated with psychoanalytic psychotherapy (10) .

Beyond the substance of Kernberg’s contributions, their significant impact must be appreciated in part as the product of his authoritative Old-World style and his tireless campaigning on their behalf. He, and to a lesser extent Masterson (11) , who highlighted abandonment issues and poor early parenting, fueled the enthusiastic pursuit of ambitious long-term intensive psychoanalytic psychotherapies for these patients.

Even as this therapeutic optimism was swelling, Klein (12) voiced a cynical counterpoint: “Analysts’ progressive disillusionment with their ability to make permanent change in nonpsychotic patients has been masked by terminological revision. The diagnosis of borderline disorder preserves intact the belief that classical psychoanalysis is the uniformly effective treatment of choice for neurosis, since failures occur only with the borderline patients” (p. 366).

Despite the doubts about this diagnosis’s parentage, important contributions to the borderline construct from these early psychoanalytic observations have endured, among them recognition of these patients’ “stable instability” (13) ; their desperate need to attach to others as transitional objects (14) ; their unstable, often distorted sense of self and others; their reliance on splitting; and their abandonment fears.

1970–1980—From Personality Organization to Syndrome: “An Adjective in Search of a Noun”

In the decade after “borderline” achieved the status of a colloquialism, the advent of descriptive psychiatry and psychopharmacology brought significant changes to psychiatry. The initial effort to describe borderline patients was made by Grinker, an early and powerful advocate of empiricism, and his colleagues in a seminal book entitled The Borderline Syndrome(15) . This development set the stage for the publication of a review of this syndrome’s place within the context of a broader literature in a paper entitled “Defining Borderline Patients” (16) and for the borderline syndrome to become reliably assessable with discriminating criteria (17) . Soon afterward, it entered DSM-III (18) as “borderline personality disorder.”

Borderline personality disorder was official, but what was it? Even before its inclusion in DSM, it had become clear that the disorder was not related to schizophrenia, and the inclusion in DSM-III of another new category, schizotypal personality disorder, finalized this cleavage (19 , 20) . Even without that, the distinctive phenomenology of borderline personality disorder made a spectrum relationship with schizophrenia unlikely. Borderline patients were interpersonally needy, very emotional, and with the exception of occasional lapses in reality testing, they were definitely not psychotic ( Table 1 ). What was also apparent was that they were “difficult” patients and had considerable suicidal risk. Klein (21) described them as “fickle, egocentric, irresponsible, love-intoxicated.” Houck (22) found that they were “intractable, unruly” patients who used hospitals to escape from responsibilities. Thus, these patients attracted pejorative descriptions that discouraged charitable understanding.

Given the high levels of comorbid depression in “borderline” patients, some clinicians felt that they had an atypical form of depression (8 , 2931) . Akiskal (32) famously wrote that “borderline was an adjective in search of a noun”—and at that time, in many people’s minds, that noun was clearly “depression.” Others, echoing Klein’s earlier cynicism (12) about the origins of this disorder, felt that borderline personality disorder had been included in DSM-III simply as a conciliatory gesture intended to placate the psychoanalytic plurality, many of whom were opposed to DSM-III’s operationalization of psychiatric diagnoses.

During the 1970s, the literature on treatment for borderline personality disorder was almost exclusively about psychoanalytic psychotherapy. Numerous conferences on psychoanalytic therapy for borderline personality disorder were held, drawing large audiences. The featured speakers all achieved local, regional, or national recognition for what was considered at that time to be their heroic tolerance and remarkable skills (10 , 11 , 3338) . The subsequent flood of books on the disorder ( Figure 1 ) provided compelling accounts of the many serious problems encountered during these therapies, among which were the signal problems of “countertransference hatred” (39) and “negative therapeutic reactions” (10 , 40) . Kernberg (40) wrote that negative therapeutic reactions were common and that they derived from the borderline patient’s “1) unconscious sense of guilt (as in masochistic character structures); 2) the need to destroy what is received from the therapist because of unconscious envy …; and 3) the need to destroy the therapist as a good object because of the patient’s unconscious identification with a primitive and sadistic object” (p. 288). In retrospect, it is notable how the failures of psychoanalytic therapies were explained solely by the borderline patient’s pernicious motivations.

Figure 1. Books on Borderline Personality Disorder Published From 1968 to 2008 aa Data from the Library of Congress database, October 2008.

Thus, by 1980, when borderline personality disorder officially entered the DSM classification system, its validity rested primarily and still quite precariously on its clinical utility, and specifically on the ability of the diagnosis to predict a set of clinical dilemmas that were more or less specific to these patients ( Figure 2 ).

Figure 2.Treatment Dilemmas Predicted by the Borderline Syndrome
1980–1990—From Syndrome to Personality Disorder: “Wisdom Is Never Calling a Patient Borderline”

During the 1980s, biological psychiatry came to the fore and the recession of psychoanalysis began. After DSM-III defined many disorders with specific and measurable criteria, their validity was now being tested using standards set forth by Robins and Guze (41) . This meant that the validity of borderline personality disorder, like other diagnostic syndromes, was measured via examinations for discriminating descriptors, familiality, longitudinal course, treatment response, and biological markers. The systematic examination of these areas was carried out in numerous clinical research projects on borderline personality disorder. Until 1980, fewer than 15 research reports on borderline personality disorder had been published; in the decade from 1980 to 1990, more than 275 appeared. With only one exception, these projects were conducted without federal funding.

This research showed that the borderline personality disorder syndrome was an internally consistent, coherent syndrome (42 , 43) with a course that differed from those of schizophrenia and major depression (4446) . It also showed that the syndrome was familial and that the prevalence of schizophrenia and depression was not increased in the families of borderline patients (44 , 47 , 48) . The decade’s research also indicated that borderline personality disorder had modest and inconsistent responses to multiple classes of medications (4951) . One conclusion from this considerable body of clinical research was that borderline personality disorder was not simply a variation of—and was probably not closely related to—depression (23 , 52) ( Table 1 ).

The research drew attention to a previously unrecognized diagnostic interface—that with posttraumatic stress disorder (PTSD). Here, the differential diagnostic issues were based less on descriptive overlaps than on etiologic considerations. Studies of childhood physical and sexual abuse showed that there were reports of abuse in the histories of 70% of borderline personality disorder patients (53) . This observation occurred at the same time that feminist concerns were raised about DSM-III diagnoses, including borderline personality disorder, that pathologized women or that implicitly blamed victims. Feminist clinicians suggested that descriptions of borderline psychopathology were fueled by men’s anger (54) and that men’s use of this diagnosis for female patients reflected their negative gender biases (55) . Herman wrote that the borderline syndrome was a “disguised presentation hiding underlying PTSD” (53) .

The high frequency of early dropouts from psychoanalytic therapy was now well documented (5658) , as was the infrequency of success with this therapy (5860) . The harm of neutrality, passivity, poor maintenance of boundaries, and countertransference enactment had become clearer, and out of the crucible of popular debates between Kernberg and other analysts (such as Adler [35] and Kohut [ 61 , 62 ]) and relational psychologists (such as Jordan et al. [63] ), the essential role of empathy and support became more widely appreciated.

Thus, the emerging trauma data and the feminist concerns about the borderline label were joined by the ever-growing chronicle of the problems borderline patients allegedly created within psychoanalytic therapies to consolidate a highly pejorative meaning for the borderline diagnosis. From this confluence, Vaillant wrote that “the beginning of wisdom is never calling a patient borderline” (64) .

By this time, sufficient clinical wisdom had accumulated that while we may not have become clear about what we should do, we had learned a lot about what not to do. For example, hospitals knew that borderline patients were not simply feigning symptoms to get admitted; rather, the symptoms were real, but they remitted as a result of the hospital’s..

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Open Access Peer-reviewed Research Article

Eiko I. Fried, Randolph M. Nesse


Previous studies have established that scores on Major Depressive Disorder scales are correlated with measures of impairment of psychosocial functioning. It remains unclear, however, whether individual depressive symptoms vary in their effect on impairment, and if so, what the magnitude of these differences might be. We analyzed data from 3,703 depressed outpatients in the first treatment stage of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. Participants reported on the severity of 14 depressive symptoms, and stated to what degree their depression impaired psychosocial functioning (in general, and in the five domains work, home management, social activities, private activities, and close relationships). We tested whether symptoms differed in their associations with impairment, estimated unique shared variances of each symptom with impairment to assess the degree of difference, and examined whether symptoms had variable impacts across impairment domains. Our results show that symptoms varied substantially in their associations with impairment, and contributed to the total explained variance in a range from 0.7% (hypersomnia) to 20.9% (sad mood). Furthermore, symptoms had significantly different impacts on the five impairment domains. Overall, sad mood and concentration problems had the highest unique associations with impairment and were among the most debilitating symptoms in all five domains. Our findings are in line with a growing chorus of voices suggesting that symptom sum-scores obfuscate relevant differences between depressed patients and that substantial rewards will come from close attention to individual depression symptoms.


Citation: Fried EI, Nesse RM (2014) The Impact of Individual Depressive Symptoms on Impairment of Psychosocial Functioning. PLoS ONE 9(2): e90311. https://doi.org/10.1371/journal.pone.0090311

Editor: Qiyong Gong, West China Hospital of Sichuan University, China

Received: October 14, 2013; Accepted: January 30, 2014; Published: February 28, 2014

Copyright: © 2014 Fried, Nesse. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The STAR*D study was supported by NIMH Contract # N01MH90003 to the University of Texas Southwestern Medical Center (http://www.nimh.nih.gov). The ClinicalTrials.gov identifier is NCT00021528. This manuscript reflects the views of the authors and may not reflect the opinions or views of the STAR*D study investigators or the NIMH. Mr. Fried is supported by fellowships from the Cluster of Excellence “Languages of Emotion” (grant no. EXC302, http://www.loe.fu-berlin.de) and the German Research Foundation (www.dfg.de). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.


About 60% of individuals who meet criteria for Major Depressive Disorder (MDD) as defined by the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) [1] report severe or very severe impairment of functioning [2]. Impairment associated with depression is long-lasting [3] and equal or greater than impairment caused by other common, chronic medical conditions such as diabetes, hypertension, heart attack, and congestive heart failure [4], [5]. Moreover, depression impairs functioning in various domains such as home life, workplace, friends, and family [6], [7] – severely compromising the capacity for self-care and independent living in many cases.

A recent review found moderate correlations between scores on various screening instruments for depression and measures of impairment [8]. It has been unclear, however, whether certain symptoms are more impairing than others, and if so, what the magnitude of these differences might be. This question is highly relevant because of large differences in the symptoms experienced by patients diagnosed with MDD.

Qualifying for a diagnosis of MDD requires experiencing at least five of the nine DSM symptomatic criteria, among which at least one has to be either sad mood or loss of interest, for at least 2 weeks. Four symptoms are compound symptoms comprised by different subsymptoms (feelings of worthlessness or inappropriate guilt) or opposite subsymptoms (insomnia or hypersomnia, psychomotor agitation or retardation, weight loss or weight gain), leading to 1,497 unique symptom profiles that all qualify for the same diagnosis [9], including profiles that do not have a single symptom in common. Considerable symptom variability has been reported across individuals [10][12] and within individuals across time [13], [14].

Specific depressive symptoms have received comparably little attention because they are assumed to be diagnostically interchangeable indicators of a common diagnosis. This assumption of symptom equivalence [15] goes hand in hand with the conceptualization of depression within the framework of reflective latent variable modeling [16], [17]: variation in the latent disorder depression causes variation of the observable symptoms. Depression is viewed as the common cause for diverse symptoms such as insomnia, psychomotor agitation, or loss of interest – which is the reason why symptoms are measured in order to assess depression. Since all symptoms indicate the same latent disease, only the number of symptoms is relevant, not their natures. The notion that different symptoms are diagnostically equivalent justifies the common practice of summing the number of symptoms to reflect depression severity.

However, several authors have suggested that there are substantial benefits to analyzing depressive symptoms individually [15], [18][20]. This is supported by evidence showing that symptoms differ from each other in their associations with demographic variables, personality traits, lifetime comorbidities, and risk factors [15], [21], and it has been established that specific stressful life events are predictive of distinct MDD symptom profiles [22][25]. Furthermore, particular gene polymorphisms are associated with specific depressive symptoms [26], [27], and a recent study of 7,500 twins concluded that the DSM symptomatic criteria for depression do not reflect a single underlying genetic factor [28].

We are aware of only a single previous study that explored concurrent effects of individual depressive symptoms on impairment of psychosocial functioning [29]. In this analysis of a general population sample, six DSM-III [30] symptoms were significantly associated with impairment (depressed mood, dysthymia, cognitive difficulties, suicidal ideation, fatigue, and sexual disinterest).

The present study extends the previous report [29] in four important aspects: (1) we examine the differential impact of symptoms on impairment in a large and highly representative sample of 3,703 depressed patients; (2) we use the updated DSM-5 criterion symptoms; (3) we investigate subsymptoms (e.g., psychomotor agitation and psychomotor retardation) instead of compound symptoms (e.g., psychomotor problems); (4) lastly, we test whether symptoms vary in their impacts across five impairment domains.

Materials and Methods

Study description

Data from the first treatment stage (level 1) of the NIH-supported “Sequenced Treatment Alternatives to Relieve Depression” (STAR*D) study [31], [32] were analyzed for this report. Data can be obtained from the NIMH and were provided to the authors under terms of an NIHM Data Use Certificate that protects confidentiality; dataset version 3 was used. STAR*D was a multisite randomized clinical trial conducted in the USA to investigate which of several treatment options would be most effective for nonpsychotic MDD outpatients; 4,041 patients were enrolled into the first treatment stage, in which all participants received citalopram, a selective serotonin reuptake inhibitor (SSRI) antidepressant. Outcome data were obtained via telephone interviews that were conducted either by interviewers, or by an interactive voice response system (IVR). STAR*D was approved and monitored by the institutional review boards at each of the 14 participating institutions, a national coordinating center, a data coordinating center, and the data safety and monitoring board at the NIMH. All participants provided written informed consent at study entry. Detailed information about design, methods, exclusion criteria, and the rationale of STAR*D are described elsewhere [31], [32].


STAR*D used relatively inclusive selection criteria in order to obtain a highly representative sample of patients seeking treatment for MDD. Participants had to be between 18 and 75 years, fulfill DSM-IV criteria for single or recurrent nonpsychotic MDD, and have at least moderately severe depression corresponding to a score of at least 14 on the 17-item Hamilton Rating Scale for Depression (HAM-D) [33]. Participants with a history of bipolar disorder, schizophrenia, schizoaffective disorder, or psychosis were excluded, as were patients with current anorexia, bulimia, or primary obsessive compulsive disorder. Further exclusion criteria were a history of intolerability to antidepressant medication, lack of response to an adequate trial of SSRI in the current episode of MDD, or failure to respond to 16 or more sessions of cognitive therapy in the current episode of MDD. Our analyses are limited to the 3,703 individuals that were assessed within the first week of level 1 via IVR.

Outcomes measures

STAR*D used the Quick Inventory of Depressive Symptoms (QIDS-16 [34]) to assess depressive symptoms. The QIDS-16 has good psychometric properties [34], and the results of the IVR version are comparable to the results produced by the self-rated and the clinician-rated QIDS-16 [35]. The QIDS-16 assesses the nine DSM symptom domains with 16 questions (Table 1). Each domain yields a score between 0 and 3, 0 indicating no problems, 3 indicating severe problems. While six symptoms are measured with single questions, the three compound symptoms (sleep problems, psychomotor problems, appetite/weight problems) are assessed with multiple questions. The QIDS-16 constructs these compound symptoms by using the highest symptom score in each symptom group, resulting in one score on each of the nine DSM criterion symptoms. Since we were interested in individual symptoms, we used all available items instead of symptom domains. Detailed information for the domain appetite and weight problems was not available, since either appetite decrease or appetite increase, and either weight decrease or weight increase was scored. Overall, this resulted in twelve individual symptoms plus the two compound symptoms appetite problems and weight problems (Table 1).

The Work and Social Adjustment Scale (WSAS [36]) was used to measure impairment of functioning. The WSAS is a simple, reliable, and valid self-report instrument that uses Likert-scale ratings of 5 items to assess impairment in the domains of work, home management, social activities, private activities, and close relationships. Each question is rated on a 0–8 Likert scale, with 0 indicating no impairment and 8 indicating very severe impairment. WSAS scores below 10 are associated with subclinical populations; scores of 10–20 are associated with significant functional impairment, while scores above 20 suggest at least moderately severe functional impairment (total range 0–40). The WSAS has been used mainly in samples with mood and anxiety disorders, and has been shown to have good internal consistency (0.70 to 0.94) and retest-reliability (0.73), and high concurrent validity of IVR administrations with clinician interviews (0.81 and 0.86) [37]. In STAR*D, the WSAS specifically queried participants how much their depression impaired work and social activities. For instance, work impairment was measured via the following item: “Because of my depression, my ability to work is impaired. 0 means not at all impaired and 8 means very severely impaired to the point I can’t work.”

Statistical analysis

Three analyses were performed. First, we used the 14 QIDS-16 depression symptoms to predict overall impairment as measured by the WSAS sum-score, controlling for age and sex. We then compared two linear regression models: in model I (heterogeneity model), regression weights for symptoms were free to vary, whereas model II (homogeneity model) constrained regression weights to be equal. While model I allows for differential impairment-symptoms associations, model II represents the hypothesis that symptoms have equal associations with impairment. A χ2-test was used to compare the two models. Because depressive symptoms are generally correlated with each other, we performed multicollinearity diagnostics for both regression analyses. The variance inflation factor (VIF) did not exceed the value of five for any symptom, indicating no multicollinearity problems [38].

Second, we aimed to allocate unique R2 shares (proportion of explained variance) to each regressor to examine how much unique variance each individual symptom shared with impairment. We used the LMG metric via the R-package RELAIMPO [39] to estimate the relative importance (RI [40][42]) of each symptom. LMG estimates the importance of each regressor by splitting the total R2 into one non-negative R2 share per regressor, all of which sum to the total explained R2. This is done by calculating the contribution of each predictor at all possible points of entry into the model, and taking the average of those contributions. In other words, an estimate of RI for each variable is obtained by calculating as many regressions as there are possible orders of regressors (in the present case, 8.7×1010 regressions), and then averaging individual R2 values over all models. RI estimates are then adjusted to sum to 100% for easier interpretation. Confidence interval (CI) estimates of the RI coefficients, as well as p-values indicating whether regressors differed significantly from each other in their RI contributions (in an exploratory sense), were obtained using the bootstrapping capabilities of the RELAIMPO package. It is important to note that predictors with a non-significant regression coefficient can nonetheless contribute to the total explained variance, that is, have a non-zero LMG contribution. This is the case when regressors are correlated with each other and thus can indirectly influence the outcome via other regressors [42]. Therefore, all symptoms, even those without significant regression coefficients, were included in subsequent RI calculations.

Third, we tested whether individual symptoms differed in their associations across the five WSAS impairment domains work, home management, social activities, private activities and close relationships. We estimated two structural equation models (SEM), using the Maximum-Likelihood Estimator. Both models contained five linear regressions, one for each domain of impairment. In each of these five regressions, we used the 14 depressive symptoms as predictors of one impairment domain, controlling for age and sex. While the first SEM allowed free estimation of all regression coefficients (model I), the second constrained each symptom to have equal effects (i.e. regression coefficients) across the five impairment domains (model II). This second model represents the hypothesis that a given symptom has similar impacts on all five domains. We compared the models using a χ2-test.

Analyses one and three were performed in MPLUS v7.0 [43], and analysis two was estimated in R v2.13.0

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Eric Russ M.A. Jonathan Shedler Ph.D. Rebekah Bradley Ph.D. Drew Westen Ph.D.

Objective: Narcissistic personality disorder has received relatively little empirical attention. This study was designed to provide an empirically valid and clinically rich portrait of narcissistic personality disorder and to identify subtypes of the disorder. Method: A random national sample of psychiatrists and clinical psychologists (N=1,201) described a randomly selected current patient with personality pathology. Clinicians provided detailed psychological descriptions of the patients using the Shedler-Westen Assessment Procedure-II (SWAP-II), completed a checklist of axis II diagnostic criteria, and provided construct ratings for each axis II personality disorder. Descriptions of narcissistic patients based on both raw and standardized SWAP-II item scores were aggregated to identify, respectively, the most characteristic and the most distinctive features of narcissistic personality disorder. Results: A total of 255 patients met DSM-IV criteria for narcissistic personality disorder based on the checklist and 122 based on the construct ratings; 101 patients met criteria by both methods. Q-factor analysis identified three subtypes of narcissistic personality disorder, which the authors labeled grandiose/malignant, fragile, and high-functioning/exhibitionistic. Core features of the disorder included interpersonal vulnerability and underlying emotional distress, along with anger, difficulty in regulating affect, and interpersonal competitiveness, features that are absent from the DSM-IV description of narcissistic personality disorder. Conclusions: These findings suggest that DSM-IV criteria for narcissistic personality disorder are too narrow, underemphasizing aspects of personality and inner experience that are empirically central to the disorder. The richer and more differentiated view of narcissistic personality disorder suggested by this study may have treatment implications and may help bridge the gap between empirically and clinically derived concepts of the disorder.

Despite its severity and stability (1 , 2) , narcissistic personality disorder is one of the least studied personality disorders. The goals of this study were to gain a richer understanding of narcissistic personality disorder by identifying the most characteristic and the most distinctive features of the disorder and to identify subtypes of the disorder.

Previous research indicates that the phenomenon of narcissism may be broader than the DSM-IV formulation. In one study, a random national sample of psychologists and psychiatrists described patients with personality disorders by using the Shedler-Westen Assessment Procedure–200 (3 , 4) , an instrument that allows clinicians to record their psychological observations systematically and reliably. The portrait that emerged of narcissistic personality disorder encompassed DSM-IV criteria but also included psychological features absent from DSM-IV, notably painful insecurity, interpersonal vulnerability, and feelings of fraudulence.

An emerging literature also supports the long-held clinical hypothesis that there are two subtypes of narcissistic individuals, grandiose and vulnerable (511) . The former has been described as “grandiose, arrogant, entitled, exploitative, and envious” and the latter as “overly self-inhibited and modest but harboring underlying grandiose expectations for oneself and others” ( 5 , pp. 188–189). The two subtypes have different correlates with external criterion variables, supporting the validity of the distinction (see reference 10 , for example).

In this article, we report data from a national sample of patients described by their treating clinicians using the Shedler-Westen Assessment Procedure–II (SWAP-II; 3 , 4 , 1214) , the latest edition of the instrument. The study has two goals: to refine the construct of, and diagnostic criteria for, narcissistic personality disorder and to empirically identify subtypes of the disorder. Our research approach is analogous to a diagnostic field trial that tests alternative diagnostic criteria. However, the logistical constraints of field trials (e.g., limited time available for patient assessment, patient contact at only a single time point) limit the number of alternative diagnostic criteria that can be tested and place the diagnostic emphasis on relatively overt signs and symptoms that can be assessed by asking participants direct questions. Overreliance on direct questions may be especially problematic for patients with narcissistic personality disorder, who lack self-awareness or minimize their own psychopathology (see also reference 15 ).

In previous studies, we identified the most descriptive or characteristic features of narcissistic personality disorder but not necessarily the most distinctive features (3 , 12) . For example, lack of empathy is highly descriptive of narcissistic personality disorder but is not specific to the disorder—patients with other personality disorders also lack empathy. In this study, we performed separate analyses to identify the most characteristic and the most distinctive features of narcissistic personality disorder. To identify the most characteristic features, we created composite personality descriptions by aggregating raw SWAP-II item scores across patients diagnosed with narcissistic personality disorder. To identify the most distinctive features, we created composite personality descriptions by aggregating standardized SWAP-II item scores (z scores). The latter procedure deemphasizes items that are descriptive of personality disorder patients in general and highlights items specific to each personality disorder.


We contacted a random national sample (unstratified) of psychiatrists and psychologists with at least 5 years of posttraining experience, drawn from the membership registers of the American Psychiatric Association and the American Psychological Association. Because clinicians provided all data and no patient identifying information was disclosed to the investigators, clinicians rather than patients provided informed consent, as approved by the Emory University institutional review board. Participating clinicians received a $200 consulting fee.

We asked clinicians to describe “an adult patient you are currently treating or evaluating who has enduring patterns of thoughts, feelings, motivation, or behavior—that is, personality patterns—that cause distress or dysfunction.” To obtain a broad range of personality pathology, we emphasized that patients need not have a DSM-IV personality disorder diagnosis. Patients had to meet the following additional inclusion criteria: at least 18 years of age, not currently psychotic, and known well by the clinician (using the guideline of at least 6 clinical contact hours, but less than 2 years overall to minimize confounds due to treatment). To ensure random selection of patients from clinicians’ practices, we instructed clinicians to consult their calendars to select the last patient they saw during the previous week who met study criteria. In a subsequent follow-up, over 95% of clinicians reported having followed the procedures as instructed. Each clinician contributed data on one patient.

Clinical data form

We used a clinician-report form to gather information on a wide range of demographic, diagnostic, and etiological variables.

Shedler-Westen Assessment Procedure–II

The SWAP-II consists of 200 personality-descriptive statements, each of which may describe a given patient well, somewhat, or not at all. Clinicians sort the statements into eight categories, from least descriptive of the patient (assigned a value of 0) to most descriptive (assigned a value of 7). (A web-based version of the instrument can be viewed at www.swapassessment.org.)

Axis II criterion checklist

Clinicians received a randomly ordered checklist of the criteria for all axis II disorders and checked which criteria the patient met. To generate DSM-IV diagnoses, we applied the DSM-IV diagnostic decision rules (e.g., five of nine criteria met for a diagnosis of narcissistic personality disorder). This method tends to produce results that mirror those of structured interviews (16 , 17) .

Personality disorder construct ratings

As another means of obtaining personality disorder diagnoses, we asked clinicians to rate the extent to which the patient resembled or “matched” each DSM-IV personality disorder construct, irrespective of specific criteria, on a 5-point scale ranging from 1, “little or no match,” to 5, “very good match, prototypical case.” To guide clinicians, we reproduced the single-sentence summary that introduces each disorder in DSM-IV. Scale anchors indicated that ratings ≥4 signified a positive diagnosis or “caseness.” The construct rating method is less wedded to existing DSM-IV diagnostic criteria than the criterion checklist method, and it helps avoid the circularity inherent in attempting to identify new diagnostic criteria by examining only patients diagnosed by existing criteria.


The total sample included 1,201 patients. Of these, 255 met DSM-IV criteria for narcissistic personality disorder based on the axis II checklist (five or more diagnostic criteria checked), 122 received the diagnosis based on the personality disorder construct ratings (ratings ≥4), and 101 received the diagnosis by both methods; thus, 83% of those who received a diagnosis via the construct ratings also met DSM-IV criteria. Narcissistic personality disorder construct ratings correlated highly with the number of DSM-IV criteria met (r=0.71, df=1194, p<0.001). Of patients who met criteria using both methods, 71% were male; their mean age was 44 years (SD=14.01); and 87% were Caucasian, 8% African American, 3% Hispanic, and 2% other.

Composite Portraits of Narcissistic Personality Disorder: Characteristic Features

To identify the SWAP-II items that are most central and defining of narcissistic personality disorder, we created composite descriptions by aggregating (averaging) the SWAP-II item scores across all patients diagnosed with the disorder. The psychometric effect of aggregation is that idiosyncrasies of individual patients and clinicians (i.e., error variance) cancel out (18 , 19) , and only those items that consistently receive high scores across patients with narcissistic personality disorder receive high scores in the composite description. Thus, the high-scoring SWAP-II items reflect the core psychological features shared by patients with narcissistic personality disorder. Table 1 lists the SWAP items that are most defining of the disorder.

The items listed in Table 1 are based on four different composite descriptions of narcissistic personality disorder. The first is a composite description of patients who met DSM-IV criteria for the disorder based on the axis II criterion checklist ( Table 1 , column 1). The second is a composite description of patients diagnosed with the disorder on the basis of personality disorder construct ratings (with ratings ≥4 treated as positive diagnoses; Table 1 , column 2). The values in the table indicate the rank order of the SWAP items in each description. The rankings indicate the relative importance of the items in describing narcissistic personality disorder. For example, in the composite description based on personality disorder construct ratings (column 2), the five top ranked items were: “Has an exaggerated sense of self-importance (e.g., feels special, superior, grand, or envied)”; “Appears to feel privileged and entitled; expects preferential treatment”; “Tends to be angry or hostile (whether consciously or unconsciously)”; “Tends to be critical of others”; and “Tends to get into power struggles.” The first two descriptors resemble DSM-IV criteria; the next three do not. Thus, patients with narcissistic personality disorder appear more hostile, critical, and power-oriented than DSM-IV would lead us to expect.

Composite Portraits of Narcissistic Personality Disorder: Most Distinctive Items

The composite descriptions described above (created by aggregating raw SWAP-II scores) identify features that are characteristic of narcissistic personality disorder but are not necessarily specific to the disorder. For example, patients with narcissistic personality disorder are angry and hostile, but so are patients with other personality disorders (e.g., borderline, paranoid). Such descriptors are necessary for an accurate and comprehensive portrait of narcissistic personality disorder, but they do not necessarily distinguish this disorder from “near neighbor” disorders.

To identify the most distinctive diagnostic features, we mathematically transformed the SWAP-II item scores to create standardized scores (z scores), so that each SWAP-II item score would be expressed as a deviation from the sample mean for that item, expressed in standard deviation units. In practical terms, the effect of this transformation is to deemphasize items that have high scores in the psychiatric sample generally and emphasize items that uniquely distinguish specific personality disorders within the sample. For example, most patients in a psychiatric sample experience dysphoric affect (e.g., “Tends to feel unhappy, depressed, or despondent”), and so do patients with narcissistic personality disorder. However, the item is not particularly helpful for distinguishing narcissistic personality disorder from other personality disorders.

To identify the SWAP-II items most distinctive of narcissistic personality disorder, we created composite descriptions by aggregating standardized SWAP-II scores across patients with the disorder. In Table 1 , columns 3 and 4 contain the item rankings in the composite description of patients who met DSM-IV criteria for narcissistic personality disorder based, respectively, on the axis II criterion checklist and on personality disorder construct ratings.

Again, the rankings indicate the relative importance of the items. For example, the item “Seems to treat others primarily as an audience to witness own importance, brilliance, beauty, etc.” received the second highest rank in the composite description based on personality disorder construct ratings (column 4). This personality characteristic may not be prominent in all patients with narcissistic personality disorder; when it is prominent, however, it may be pathognomonic.

Identifying Optimal Diagnostic Criteria

The items in Table 1 are grouped to facilitate interpretation. The items in the top third of the table (no shading) are both highly characteristic and highly distinctive of narcissistic personality disorder. These items ranked among the top 30 most descriptive items in all four composite descriptions.

Items in the shaded region in the middle third of the table are highly descriptive of narcissistic personality disorder but not specific to it. These items are necessary to provide a clinically complete description of narcissistic personality disorder, even though they may apply to other personality disorders as well. Items in this section had top rankings in the composite descriptions based on raw SWAP-II scores (columns 1 and 2) but not in the composite descriptions based on standardized SWAP-II scores (columns 3 and 4).

Finally, items in the shaded region in the bottom third of the table are specific to narcissistic personality disorder but not necessarily characteristic of the average patient with the disorder. In other words, these personality features are not necessarily common in narcissistic personality disorder, but they are highly diagnostic when present.

Key findings are that interpersonal vulnerability and underlying emotional distress are core features of narcissistic personality disorder. The typical patient tends to fear rejection and abandonment; tends to feel misunderstood, mistreated, or victimized; tends to have extreme reactions to perceived slights or criticism; tends to feel unhappy, depressed, or despondent; and tends to feel anxious. Other prominent features include anger and hostility, difficulty in regulating affect, interpersonal competitiveness, power struggles, and a tendency to externalize blame. These features are absent from the DSM-IV description of narcissistic personality disorder, and they are unlikely to be identified using research methods that rely exclusively on what patients with the disorder report about themselves (e.g., via questionnaires or structured interviews).

Reliability of the Composite Swap-II Descriptions

The reliability of a composite SWAP-II description is measured by Cronbach’s alpha. The logic is identical to computing the reliability of a psychometric scale, except that patients are treated as “items” (columns in the data file) and SWAP-II items are treated as cases (rows in the data file). This approach is well established (14 , 20) . Values for Cronbach’s alpha for this study ranged from 0.94 to 0.98, suggesting that the descriptions of narcissistic personality disorder in Table 1 contain very little error variance.

Subtypes of Narcissistic Personality Disorder

Our second analysis was designed to identify subtypes or variants of narcissistic personality disorder. We applied Q-factor analysis to analyze the SWAP-II descriptions of patients meeting the diagnosis of narcissistic personality disorder by both diagnostic methods (DSM-IV and construct ratings). We conservatively included only those patients who met both sets of diagnostic criteria because DSM-IV criteria tend to overdiagnose all personality disorders. Thus, imposing the additional criterion of positive diagnosis using the construct ratings minimizes the possibility of identifying artifactual subtypes.

Q-factor analysis is computationally equivalent to conventional factor analysis except that it identifies groupings of similar people, whereas conventional factor analysis identifies groupings of similar variables. We used standard exploratory factor analysis with principal axis factoring and an oblique (promax) rotation. We retained the first three of the four rotated factors. The factor scores listed in Table 2 indicate the importance or centrality of the items in defining each subtype of narcissistic personality disorder. The Q-factors showed low to moderate intercorrelations with each other (r values ranging from –0.01 to 0.35), indicating that the subtypes do represent distinct groups.

We labeled the narcissistic personality disorder subtypes grandiose/malignant, fragile, and high-functioning/exhibitionistic. Grandiose/malignant narcissists exploit others with little regard for their welfare, and (unlike other narcissistic patients) their grandiosity appears to be primary rather than defensive or compensatory. Fragile narcissists experience feelings of grandiosity and inadequacy, suggesting alternating cognitive representations of self (superior versus inferior), defensive grandiosity, or a grandiosity that emerges under threat. High-functioning/exhibitionistic narcissists are grandiose, competitive, attention seeking, and sexually seductive or provocative, and also have significant psychological strengths (e.g., being articulate, energetic, interpersonally comfortable, achievement oriented).

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Anorexia nervosa (AN) has a prolonged course of illness, making both defining recovery and determining optimal outpatient treatments difficult. Here, we report the types of treatments utilized in a naturalistic sample of adult women with AN in Texas. Participants were recruited from earlier studies of women with AN (n = 28) and in weight recovery following AN (n = 18). Participants provided information about both their illness and treatments during their most severe period as well as during the 2–6 years following original assessments. Based upon their baseline and follow-up clinical status participants were classified as remaining ill (AN-CC, n = 17), newly in recovery (AN-CR, n = 11), and sustained weight-recovery (AN-WR, n = 18). Utilization of health care institutions and providers were compared across groups. There were no differences in groups related to symptoms or treatments utilized during the severe-period. During the follow-up period, intensive outpatient programs were utilized significantly more by the AN-CC group than the other groups, and dietitians were seen significantly less by the AN-WR group. Medical complications related to the ED were significantly more common in the AN-CC group. All groups maintained similar levels of contact with outpatient psychiatrists, therapists, and primary care physicians. Current treatments remain ineffective for a subset of AN participants. Future prospective studies assessing medical health and comorbidities in AN may provide additional insights into disease severity and predictors of clinical outcome.


Anorexia nervosa (AN) is a serious mental illness characterized by difficulties consuming sufficient calories to maintain body weight in conjunction with disturbances in self-perception. Although this disease often begins in adolescence and young adulthood, the course of disease is prolonged and outcomes are poor (Eddy et al., 2017). In examination of treatment outcomes in partial hospitalization and intensive outpatient settings, individuals with AN had worse outcomes for global eating disorder severity and quality of life than individuals with bulimia nervosa, binge eating disorder, and other specified feeding or eating disorder (Hayes et al., 2018). Additionally, a recent meta-analysis showed that treatment changed only short-term weight outcomes but did not significantly impact either short-term or long-term psychosocial outcomes or long-term recovery (Murray et al., 2018).

Anorexia nervosa has a relapse rate of approximately 31%, with the highest risk in the 1–2 years post-treatment (Berends et al., 2018). The dropout rate from outpatient treatment for AN is estimated to range from 20 to 40% (Dejong et al., 2012). Qualitative research on recovered women highlights the importance of psychosocial support as part of recovery (Stockford et al., 2018). Most longitudinal work in adults has focused on assessment of changes in clinical symptoms (Eddy et al., 2017; Harper et al., 2017) or follow-up of patients after specific types of interventions (Schmidt et al., 2016; Makhzoumi et al., 2017). However, there is little evidence that defines what is optimal outpatient treatment for adults with AN, and minimal data describing even the types of treatment utilized in the community in the United States.

Here, we evaluated the symptoms, medical complications and types of treatments utilized by women with AN in Texas. All participants were originally recruited to participate in studies comparing women with AN currently and those in long-term weight recovery following AN. Previously, we reported on the re-assessed clinical status of these participants 2–6 years after original measures were collected (Harper et al., 2017). Neuropsychological function and clinical symptoms were compared across groups based on clinical outcome. We found that women with continued eating disorder had poorer neuropsychological function and self-competence at baseline than those recently recovered. Additionally, recently recovered women showed changes in depression and externalizing bias, a measure of self-related attributions. Here, we report and compare the types of treatment obtained by these subjects at the most severe stage of their eating disorder and during the time period since participating in the study as well as the medical symptoms. We hypothesized that there would be less utilization of outpatient treatment providers amongst the women that relapsed and persisted with disease relative to those that recovered.

Materials and Methods

Forty-six women ages 20–61 participated (Figure 1). All subjects had completed baseline measures as part of one or more of three previous studies (enrollment period was 2011–2014) including both currently ill and weight-recovered women with AN (Acevedo et al., 2015; Mcadams et al., 2015, McAdams et al., 2016). Weight recovery was defined as having maintained a body mass index (BMI) of greater than 19 for at least 12 months. In addition, the weight-recovered participants could not have met DSM-IV criteria for bulimia nervosa in the last 12 months. Participants provided written informed consent approved by the UT Southwestern Institutional Review Board. The Structured Clinical Interview for DSM-IV (First et al., 2002) was conducted upon initial enrollment to confirm current or past AN and comorbid diagnoses; all interviews were conducted by trained assessors at the masters or doctoral level. BMI was measured at that time. Follow up self-reports were collected and managed using REDCap electronic data capture tools hosted at UT Southwestern (Harris et al., 2009), where participants also provided digital consent upon beginning their follow-up surveys.


Retrospective study design flowchart.

Outcome Criteria

For this study participants were classified at follow-up into one of 3 groups based upon baseline and follow-up clinical symptoms: remaining ill (AN-CC), in recovery from baseline ill status (AN-CR), and sustaining weight recovery (AN-WR). The primary outcome criterion was based on maintaining a BMI > 19 for at least 12 months without meeting criteria for bulimia nervosa; this matched the enrollment criteria utilized for weight-recovery in the original studies. BMI was obtained from medical records or clinician report. Participants in recovery could not have participated in intensive outpatient, partial hospital, residential, or inpatient treatment for at least 12 months.

Measurements of Treatment

Using a guided, semi-structured interview, each participant provided information about their eating disorder, focusing on characterization of their symptoms and interactions with clinical treatment providers. With regard to their eating disorder, each subject self-reported their age of onset, their age of first treatment, and their age during their worst period with the eating disorder. BMI, all care utilized immediately following the worst period (inpatient/residential, partial hospital, intensive outpatient, or outpatient), and the symptoms (restriction, binging, purging, depression, anxiety, alcohol, and other substance use) during the worst period were detailed. The duration and intensity of outpatient treatment following this period was queried, including interactions with five different types of clinical care (primary care physician, psychiatrist, therapist, dietitian, and group therapy). If answered affirmatively the type of clinical care was sought, then the frequency (annually, quarterly, monthly, biweekly, and weekly) and duration of that clinical interaction was inquired.

Separately, treatment utilization following the individuals’ participation in the research study was assessed. Two tables were completed for every subsequent 6 month period to present. The first table assessed a need for a higher level of care for the eating disorder (or a related comorbid condition such as suicidality or substance abuse) including both medical and psychiatric hospitalizations (further classified as inpatient, residential, partial hospital, and intensive outpatient), and ER visits. The second table assessed the participant’s interaction with five different types of outpatient clinical care, including frequency and duration, for each 6 month period.

Statistical Analysis

Statistical analyses were conducted using the IBM Statistical Package for Social Sciences (SPSS; v.23). To determine differences between groups, separate one-way analysis of variance (ANOVAs) were conducted on continuous data. Post hoc pairwise comparisons were conducted using a Bonferroni correction for multiple comparisons. Categorical and dichotomous (yes/no) data were analyzed by Chi-square analyses.


As previously reported, amongst the AN-C group, 17 participants remained ill (AN-CC) and 11 achieved recovery from a baseline ill status (AN-CR), a recovery rate of 39% (Table 1). In addition, all 18 of weight-recovered group remained weight-recovered at follow up (AN-WR). There were no differences in the distributions of subtypes of AN by group [AN binge-purge/restricting, AN-CC 9/8, AN-CR 5/6, AN-WR 11/7; X2(2) = 0.67, p = 0.71, V = 0.12].

Table 1

Participant Characteristics.

(N = 17) (N = 11) (N = 18) Statistical comparisons
Mean (SD) Mean (SD) Mean (SD) Test statistic p-value
Age of onset 16.29 (3.10) 19.18 (7.81) 14.22 (3.21) F(2,43) = 3.86 0.03
Age of first treatment 17.82 (3.03) 22.73 (7.92) 18.53 (4.35) F(2,42) = 3.35 0.045
Baseline BMI 17.54 (1.52) 18.39 (1.08) 22.87 (2.61) F(2,43) = 36.38 <0.001∗∧
Follow-up BMI 17.78 (1.52) 21.05 (1.56) 23.37 (3.66) F(2,43) = 20.86 <0.001∧†
N (%) N (%) N (%)
Race X2(6) = 8.73 0.19
   White 17 (100 %) 11 (100%) 13 (72%)
   Asian 0 (0%) 0 (0%) 2 (11%)
   Native American 0 (0%) 0 (0%) 2 (11%)
   African American 0 (0%) 0 (0%) 1 (6%)
Ethnicity X2(2) = 1.56 0.46
   Hispanic 2 (12%) 0 (0%) 1 (6%)
   Non-hispanic 15 (88%) 11 (100%) 17 (94%)
Education (years) X2(4) = 1.93 0.75
   ≤12 4 (24%) 1 (9%) 2 (11%)
   13–16 8 (47%) 6 (55%) 8 (44%)
   >16 5 (29%) 4 (36%) 8 (44%)
AN-CC, women remaining ill with anorexia nervosa; AN-CR, women recently recovered from anorexia nervosa; AN-WR, women sustaining recovery from anorexia nervosa; BMI, Body Mass Index; Significant differences are in bold and denoted by superscripts (Bonferroni correction for multiple comparisons). ∗AN-CR differs from AN-WR (p < 0.05); †AN-CC differs from AN-CR (p < 0.05); ∧AN-CC differs from AN-WR (p < 0.05).

The AN-CR group had a later age of onset than the AN-WR [age of onset in years, AN-CC, 16.3, AN-CR 19.2, AN-WR 14.2, F(2, 43) = 3.86, p = 0.03; post hoc AN-WR < AN-CR, p = 0.02]. The AN-CC group had an earlier age of first treatment than the AN-CR group [age of first treatment, AN-CC 17.8, AN-CR 22.7, AN-WR 18.5, F(2, 42) = 3.35, p = 0.045; post hoc AN-CC < AN-CR, p = 0.05]. The AN-CC and AN-CR groups both had a lower BMI at baseline than the AN-WR group [BMI at baseline, AN-CC 17.5, AN-CR 18.4, AN-WR 22.8, F(2, 43) = 36.4, p =< 0.001; post hoc AN-CC < AN-WR, p = 0.05 and AN-CR < AN-WR, p = 0.05] but did not differ from each other.

Severe-Period Symptoms and Treatments

There were no differences in the clinical symptoms or treatments utilized in the worst period of the disease for any of the groups (Table 2). Eating disorder symptoms were considered most severe for all subjects on average at 22.6 years, and the lowest BMI was similar across all subjects (mean lowest BMI 15.32). Across all groups, 43.6% of subjects reported binge-eating behaviors, and 50% reported purging symptoms in the severe period. 84.8% of the subjects had comorbid depression and 82.6% had comorbid anxiety. Problems with alcohol and substance abuse were less prevalent across the sample, with 21.7% of subjects reporting an alcohol use disorder and 10.9% reporting substance abuse. No differences in the types of intensive treatment utilized following that severe-period were observed across the 3 groups, with 43.5% utilizing inpatient or residential treatments, 41.3% in partial hospital programs, 39.1% in intensive outpatient.

Table 2

Symptom and treatment comparisons for most severe period.

(N = 17) (N = 11) (N = 18) Statistical comparisons
Mean (SD) Mean (SD) Mean (SD) Test statistic p-value
Age at enrollment 25.00 (6.85) 26.00 (6.39) 29.44 (10.37) F(2,43) = 1.33 0.27
Age, most severe period 22.97 (8.32) 24.18 (6.94) 20.65 (7.33) F(2,42) = 0.79 0.46
Lowest BMI 14.59 (2.05) 15.72 (1.60) 15.64 (1.59) F(2,43) = 1.97 0.15
N (%) N (%) N (%)
   Restricting 17 (100%) 11 (100%) 18 (100%)
   Binging 8 (47%) 4 (36%) 8 (44%) X2(2) = 0.32 0.85
   Purging 11 (65%) 6 (55%) 6 (33%) X2(2) = 3.56 0.17
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Background and aims

The main aim of this study was to analyze and describe the clinical characteristics and shared personality traits in different impulsivity–compulsivity spectrum disorders: substance use disorders (SUD), gambling disorder (GD), and bulimia nervosa (BN). The specific aims were to compare personality differences among individuals with pure SUD, BN with and without SUD, and GD with and without SUD. In addition, we assessed the differential predictive capacity of clinical and personality variables in relation to diagnostic subtype.


The sample comprised 998 subjects diagnosed according to DSM-IV-TR criteria: 101 patients were diagnosed with SUD, 482 with GD, 359 with BN, 11 with GD + SUD, and 45 patients with BN + SUD. Various assessment instruments were administered, as well as other clinical measures, to evaluate their predictive capacity.


Marked differences in personality traits were observed between groups. Novelty seeking, harm avoidance, self-directedness, cooperation, and self-transcendence best differentiated the groups. Notably, novelty seeking was significantly higher in the two dual pathology subgroups. Patients with dual pathology showed the most dysfunctional personality profiles.

Discussion and conclusion

Our results indicate the existence of shared dysfunctional personality traits among the groups studied, especially in novelty seeking and self-directedness.


From a nosological perspective, controversy remains regarding the utility of dimensional versus categorical classifications of mental disorders. Although categorical models have been shown to be effective in many respects, dimensional approaches allow for grouping together a series of symptoms that overlap and complement one another, forming a continuum along which different disorders share common features (Berlin & Hollander, 2014; Jiménez-Murcia, Granero, Moragas et al., 2015). In this context, it has been suggested that the dimensional model may avoid some of the inherent limitations of categorical systems (el-Guebaly, Mudry, & Zohar, 2012; Jiménez-Murcia, Granero, Fernández-Aranda, et al., 2015). Various authors have questioned the empirical validity of diagnoses based on categorical models (Haslam et al., 2014; Krueger & Piasecki, 2002) and have raised concerns about the fact that a consensus among experts decides the limits between specific mental disorders, for example eating disorders (ED) (Fairburn, Cooper, & Shafran, 2003; Gleaves, Lowe, Snow, Green, & Murphy-Eberenz, 2000; Gordon, Holm-Denoma, Smith, Fink, & Joiner, 2007). Other researchers have even proposed combining categorical and dimensional models (Helzer, van den Brink, & Guth, 2006). In fact, the DSM-5 has included dimensional criteria of severity for the majority of disorders to establish whether clinical status is mild, moderate, or severe according to presented symptoms (American Psychiatric Association, 2013).

The impulsivity–compulsivity construct, one that is supported by the work of authors, such as Blanco et al. (2009), Bottesi, Ghisi, Ouimet, Tira, and Sanavio (2015), Fineberg et al. (2010), Hollander and Wong (1995), Leeman and Potenza (2012), McElroy, Phillips, and Keck (1994), Lavender et al. (2017), and Stein, Clemons, Newport, Shapiro, and Christophersen (2000), place gambling disorder (GD), behavioral addictions (sex, shopping, and gaming), substance use disorders (SUD), bulimia nervosa (BN), binge ED, and anorexia nervosa of the binging/purging type toward the impulsive end of the impulsive–compulsive spectrum. In contrast, disorders, such as restrictive-type anorexia nervosa, body dysmorphic disorder, hoarding disorder, excoriation, hair-pulling disorder, and obsessive–compulsive disorder, are placed toward the compulsive end of the spectrum. All these disorders share certain features such as the search for immediate gratification (which is highly present in the early stages of the disorders situated at the impulsive end of the continuum), as well as characteristics associated with compulsivity aimed at relieving negative emotions (becoming more common as impulsive disorders progress). Moreover, shared neurobiological features have been described between GD, SUD, and ED, specifically related to the reduced activation of the ventral striatum during reward anticipation, suggesting the possibility that this feature could be a biomarker for addictions.

SUD, GD, and ED (more specifically, BN) intuitively appear to be related to a common susceptibility linked to certain personality dimensions, including impulsivity and temperamental traits (Claes, Müller, et al., 2012; Engel & Cáceda, 2015; Hadad & Knackstedt, 2014). They also share features such as a sense of urgency and explosive, unpremeditated behavior (Salvo & Castro, 2013), as well as the intense and repetitive desire to perform an act despite it having negative consequences (Hamilton et al., 2015). In fact, recent studies have concluded that high levels of impulsivity are associated with GD, SUD, BN, and personality disorders (Farstad et al., 2015; Fischer & Smith, 2008; MacLaren & Fugelsang, 2011).

These conditions also show a substantial overlap in prevalence reports. For instance, high rates of SUD have been observed in patients diagnosed with ED, with rates ranging from 22% to 50% (Calero-Elvira et al., 2009; Krug et al., 2008; Root et al., 2010; Trace et al., 2013). Likewise, GD shows high rates of comorbidity with other disorders, particularly substance use. A meta-analysis of 11 studies demonstrated a mean prevalence of comorbid SUD of 57.5% in GD (Lorains, Cowlishaw, & Thomas, 2011), and other authors have reported similar comorbidity rates (Kessler et al., 2008; Martin, Usdan, Cremeens, & Vail-Smith, 2014).

There is evidence that SUD, GD, and ED are heterogeneous disorders involving various subgroups or subtypes that develop as a result of certain vulnerability factors (Janiri, Martinotti, Dario, Schifano, & Bria, 2007; Jiménez-Murcia et al., 2013; Mallorquí-Bague et al., 2016). Previous research has identified a subset of patients with ED, particularly those with BN or binge ED (Jiménez-Murcia, Granero, Moragas, et al., 2015), who are characterized by a particular behavioral dysregulation including SUD and impulsive behaviors (Thompson-Brenner et al., 2008). Likewise, in GD, it has been suggested that there may be a subset of subjects with high levels of impulsivity and sensation seeking, early age of onset, greater severity of gambling behavior, and a higher prevalence of comorbid SUD (Blaszczynski & Nower, 2002; Jiménez-Murcia et al., 2009, 2010).

Previous studies of personality traits have described both differences and overlap between SUD, GD, and ED. According to Cloninger’s model, personality is a complex hierarchical system which can be arranged in different psychobiological dimensions of temperament and character (Cloninger, Przybeck, Svrakic, & Wetzel, 1994). Personality traits are the substrate and the context in which more complex, differentiated forms of psychopathology (Widiger & Mullins-Sweatt, 2007) are expressed. In Cloninger’s Temperament and Character Inventory, patients with GD and SUD appear to score high on novelty seeking and low on cooperation and self-directedness (Janiri et al., 2007). These findings are consistent with other studies in GD and BN samples, with and without SUD, or other impulse-related disorders (Alvarez-Moya et al., 2007; Fernandez-Aranda, Jiménez-Murcia, et al., 2006; Krug et al., 2009). Similarities in personality profiles between BN and GD have also been described, including alterations in the temperament dimension of reward dependence (Atiye, Miettunen, & Raevuori-Helkamaa, 2015; Reuter et al., 2005; Sodersten & Bergh, 2006) and, in male patients, elevated scores in harm avoidance and lower scores in self-directedness (Claes, Jiménez-Murcia, et al., 2012). By contrast, the differential factor between BN and GD patients was the presence of lifetime weight fluctuations (Claes, Jiménez-Murcia, et al., 2012).

Patients who exhibit novelty seeking and impulsivity, and those with antisocial and borderline personality disorder, are considered vulnerable to SUD (Simmons & Havens, 2007). Although several authors suggest the existence of an “addictive personality” predisposing subjects to ED, GD, or SUD (Goodman, 2008), there is no conclusive empirical evidence to confirm this theory (Franques, Auriacombe, & Tignol, 2000). However, neurobiological and imaging data do support the existence of common features of addictive and ED (Volkow, Wang, Tomasi, & Baler, 2013), and there is strong biological support for impulsivity-related features in substance dependence (Parvaz, Alia-Klein, Woicik, Volkow, & Goldstein, 2011).

From both a conceptual and diagnostic point of view, the potential value of dimensional models is a topic of growing interest in the scientific community, and several studies have described risk factors that are shared by different behavioral addictions such as GD, compulsive eating, and SUD (Granero et al., 2017; Jiménez-Murcia, Granero, Moragas, et al., 2015; Monzani, Rijsdijk, Harris, & Mataix-Cols, 2014; Probst & van Eimeren, 2013). Some of these studies highlight similarities in clinical features and comorbidity (Berlin & Hollander, 2014; Hollander, 2008), whereas others focus on overlap in terms of emotion regulation and personality, genetic, and neurobiological factors (Granero et al., 2014; Mestre-Bach et al., 2016; Volkow et al., 2013). Research on shared personality traits associated with GD, SUD, and BN could therefore contribute to knowledge about similar characteristics across conditions and be useful in developing preventive interventions for such disorders. However, most research on personality traits, including this study, has been cross-sectional and does not allow for determining causality. Nonetheless, the identification of personality traits that are specific to each disorder could improve our understanding of why some people engage in these dysfunctional behaviors and others do not.

Based on dimensional theories of the classification of mental disorders, and considering the impulsive–compulsive spectrum, our hypothesis is that patients with SUD, GD, and BN show similarities in certain personality traits (specifically, high novelty seeking and harm avoidance, and low self-directedness). We also hypothesize that BN and GD patients who present a comorbid SUD may potentially display more pronounced shared personality traits than do patients diagnosed with SUD without a comorbid condition. Thus, the aim of this study was to analyze shared and differential personality traits among SUD, GD, and BN patients, and to compare each of these groups with dual disorder patients (i.e., GD + SUD and BN + SUD). We also sought to examine the differential predictive capacity of clinical variables and personality in relation to diagnostic subtype, with SUD as the category of reference.


The initial sample comprised n = 1,009 patients who were consecutively seeking treatment at the Substance Use Disorders, Pathological Gambling, and Eating Disorder Units at Bellvitge University Hospital (Barcelona, Spain), and who were diagnosed according to DSM-IV-TR criteria (American Psychiatric Association, 2000). Just over half of the participants (54%) were male.

From the initial sample (1,009 participants), 11 cases were excluded from the analysis: two due to language difficulties, one who obtained a score below 24 on the Mini Mental State Examination, due to mental retardation, and eight due to missing data. The final sample included N = 998 participants: 101 who met diagnostic criteria for SUD, 482 for GD, 359 for BN, 45 for BN + SUD, and 11 for GD + SUD. In the case of patients within the SUD group, these patients either presented a heroin/opioid (17.8%) or alcohol SUD (82.2%). However, for patients in the BN + SUD or GD + SUD groups, only alcohol SUD cases were permitted. Patients in these subgroups with other SUDs were referred to treatment centers specializing in these SUDs. Table 1 shows the sociodemographic characteristics of the sample of the study and the result of the comparison between the different groups.

Table 1.

Demographic characteristics of the sample (N = 998)

SUD (n = 101) BN (n = 482) GD (n = 359) SUD + BN (n = 45) SUD + GD (n = 11) p
Age, mean (SD) 44.9 (9.1) 26.9 (7.8) 41.8 (13.6) 25.1 (5.0) 36.8 (8.0) <.001
Sex (males), % 79.2 5.0 88.6 8.9 100 <.001
Civil status, %
 Single 47.5 71.3 25.8 85.3 36.4 <.001
 Married 23.8 21.2 56.6 0 36.4
 Divorced 25.7 7.2 14.3 14.7 27.3
 Widowed 3.0 0.3 3.4 0 0
Employment status (employed), % 26.0 40.5 66.3 41.2 54.5 <.001
Education level, %
 Primary 69.1 56.2 73.5 44.8 90.0 <.001
 Secondary 23.7 13.9 26.5 20.7 10.0
 University 7.2 29.9 0 34.5 0

Note. SUD: substance use disorders; BN: bulimia nervosa; GD: gambling disorder; SD: standard deviation.


Demographic/clinical information, including age, education, occupation, and marital status, was obtained via a semi-structured interview.

Assessment of impulse control disorders and substance abuse/dependence. Lifetime history of an impulse control disorder and alcohol and drug abuse/dependence were assessed via the Structured Clinical Interview for DSM-IV Axis I Disorders (First, Gibbon, Spitzer, & Williams, 1996).

Assessment of gambling disorder and bulimia nervosa severity. The South Oaks Gambling Screen (Lesieur & Blume, 1987) and the Diagnostic questionnaire for pathological gambling according to DSM-IV criteria (Stinchfield, 2003) were used to assess GD severity in GD patients. The Spanish validations of both these questionnaires have showed high reliability and validity. These instruments were only completed by GD patients.

The Eating Disorder Inventory-2 (Garner, 1991) was used to examine ED severity in BN patients. This is a reliable and valid 91-item multidimensional self-report questionnaire assesses cognitive and behavioral characteristics that are typical of EDs, and its Spanish validation has shown good psychometric properties (Garner, 1998). This questionnaire was only completed by BN patients.

Temperament and Character Inventory – Revised (TCI-R) (Cloninger, 1999). This is a reliable, valid questionnaire comprising 240 items scored on a 5-point Likert-type scale. Like the original TCI (Cloninger et al., 1994), the revised version measures seven personality dimensions. Four of them related with temperament: harm avoidance (fearful, pessimistic vs. courageous, energetic), novelty seeking (curious, impulsive vs. reflective, orderly), reward dependence (sociable, sensitive vs. cold, socially insensitive), and persistence (hardworking, perseverant vs. indolent, erratic) and three character dimensions: self-directedness (responsible, goal-directed vs. insecure, inept), cooperativeness (helpful, empathic vs. hostile, aggressive), and self-transcendence (imaginative, unconventional vs. controlling, materialistic) (Svrakic & Cloninger, 2010). The performance of the Spanish version of both the questionnaire (Gutierrez-Zotes et al., 2004) has been documented. The instrument showed excellent internal consistency (mean α = .87). This instrument was administered to all study participants.


The sample comprised patients who were consecutively seeking treatment at the aforementioned units of Bellvitge University Hospital. This public hospital is certified as a tertiary care center (high specialization) for the treatment of addictive behaviors and EDs, and it oversees the treatment of very complex cases. The catchment area of the hospital includes over two million people to the south of the Barcelona metropolitan area. All participants were interviewed and assessed by clinical psychologists and physicians with over 15 years experience in the diagnosis and treatment of these disorders. Semi-structured interviews focusing on different aspects of the problem, the clinical status of the patient, and DSM-IV-TR diagnostic criteria (American Psychiatric Association, 2000) were first conducted. Subsequently, all the scales and questionnaires described above were individually completed by patients. Once the interviews and psychological assessment were complete, clinical psychologists and physicians examined the results for each case. Based on the clinical and psychometric findings, the treatment of choice for each patient, and its duration, was decided upon by consensus; treatment could be psychological therapy alone or in combination with pharmacological treatment, and be either individual- or group-based, although treatment was always based on a manualized CBT protocol.

Statistical analysis

Statistical analysis was carried out using the SPSS 20 for Windows. Demographic variables were compared among groups using the chi-square test for categorical variables and one-way ANOVA for quantitative measures. ANOVA models, adjusted for the covariates age and sex, compared the TCI-R mean scores between the five diagnostic profiles. Due to the multiple comparisons, Finner’s correction was applied to the omnibus test and Bonferroni’s correction to post-hoc comparisons. A multinomial regression model was adjusted to explore..

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. Author manuscript; available in PMC 2018 Dec 5.
Published in final edited form as:
PMCID: PMC6281436
PMID: 28714048
Jennifer J. Thomas, Ph.D.,1,2 Elizabeth A. Lawson, M.D., M.M.Sc.,3,4 Nadia Micali, M.D., Ph.D.,5,6,7 Madhusmita Misra, M.D., M.P.H.,3,4 Thilo Deckersbach, Ph.D.,2,8 and Kamryn T. Eddy, Ph.D.1,2
The publisher’s final edited version of this article is available at Curr Psychiatry Rep
See other articles in PMC that cite the published article.
Purpose of review:

DSM-5 defined Avoidant/Restrictive Food Intake Disorder (ARFID) as a failure to meet nutritional needs leading to low weight, nutritional deficiency, dependence on supplemental feedings, and/or psychosocial impairment. We summarize what is known about ARFID and introduce a three-dimensional model to inform research.

Recent findings:

Because ARFID prevalence, risk factors, and maintaining mechanisms are not known, prevailing treatment approaches are based on clinical experience rather than data. Furthermore, most ARFID research has focused on children, rather than adolescents or adults. We hypothesize a three-dimensional model wherein neurobiological abnormalities in sensory perception, homeostatic appetite, and negative valence systems underlie the three primary ARFID presentations of sensory sensitivity, lack of interest in eating, and fear of aversive consequences, respectively.


Now that ARFID has been defined, studies investigating risk factors, prevalence, and pathophysiology are needed. Our model suggests testable hypotheses about etiology and highlights cognitive-behavioral therapy as one possible treatment.


Avoidant/Restrictive Food Intake Disorder (ARFID) was introduced to the psychiatric nomenclature four years ago as a reformulation of Feeding Disorder of Infancy and Early Childhood. ARFID expanded upon Feeding Disorder of Infancy and Early Childhood to acknowledge that avoidant and restrictive eating symptoms can occur across the lifespan. DSM-5 provides three example presentations of ARFID, which can occur independently or in combination. Specifically, individuals with sensory sensitivity may avoid eating specific foods—often meats, vegetables, and/or fruits—due to aversions to specific tastes, textures, or smells. Others with ARFID may restrict the amount they eat due to lack of interest in eating or low appetite. Still others may avoid specific foods or stop eating entirely following a traumatic experience with eating, such as choking, vomiting, or other forms of gastroenterological distress. In all cases, to warrant an ARFID diagnosis, the avoidant and restrictive eating must lead to significant medical or psychosocial problems that require independent clinical attention. Examples of ARFID sequelae that would meet diagnostic criteria include poor growth and/or low weight, vitamin deficiencies, dependence on tube feeding or high-energy supplements to meet calorie needs, and psychosocial impairment (e.g., avoidance of eating opportunities at work or school; difficulty eating with others). Below we summarize what is currently known about ARFID and highlight future research directions including our new three-dimensional model of neurobiology with implications for etiology and treatment.

What is currently known?

Given its status as a recently defined disorder, ARFID has not been included in any large-scale epidemiological studies. Therefore, its incidence and prevalence in the general population are unknown. A questionnaire-based study recently investigated the prevalence of ARFID in a primary school setting among 8–13 year olds in Switzerland, and found that 3.2% met criteria for ARFID via self-reported symptoms. The prevalence of ARFID in healthcare settings is generally higher. For example, a series of case reviews and clinical studies across eating disorder treatment programs in North America found that between 7.2% and 17.4% of patients across sites had ARFID,, In a similar retrospective chart review of individuals seeking treatment for eating disorders in Japan, 11% met criteria for ARFID. Further, ARFID was even more common (22.5%) among youth in a day treatment program for eating disorders. By contrast, a retrospective review of 2,231 consecutive referrals (aged 8–18 years) to pediatric gastrointestinal clinics in the Boston area showed an ARFID prevalence of only 1.5%. A recent latent class analysis of three pediatric surveillance studies (in which pediatricians and child psychiatrists were asked to report on any children < 12 years with a newly diagnosed restrictive type eating disorder) performed across Canada, the United Kingdom, and Australia suggested that one of two identified clusters representing between 25–34% of children with incident restrictive type eating disorders mapped onto symptoms consistent with ARFID. These studies suggest that despite variation in estimates, ARFID is commonly seen in clinical settings and might be common among children in the general population. Further studies are needed to investigate the epidemiology of ARFID in children, adults, and the elderly.


There are currently no validated assessment tools for the specific psychopathology of ARFID. This gap impacts identification of the condition in clinical settings, evaluation of treatment efficacy, and ascertainment of epidemiology and natural course. Prior research suggests that ARFID can be differentiated from anorexia nervosa (AN) based on the rationale for food restriction. A small study of treatment-seekers completing the Eating Pathology Symptoms Inventory (EPSI) found that while individuals with AN endorsed higher scores than those with ARFID on EPSI Restraint (a self-report measure of purposeful dieting), the two groups scored similarly on EPSI Restriction (a self-report measure of actual deficits in calorie intake).

A recently developed questionnaire for school-aged children, the Eating Disturbances in Youth-Questionnaire (EDY-Q), has been used as a self-report measure to identify ARFID, and was shown to have a four-factor structure, possibly distinguishing emotional food avoidance, selective eating, food restriction due to fear of aversive consequences, and weight problems. The Eating Disorder Assessment for DSM-5 (EDA-5) can be used to confer ARFID diagnoses; however its psychometric properties in relation to ARFID have not yet been tested. A new semi-structured multi-informant interview—the Pica, ARFID, and Rumination Disorder Interview (PARDI)—has recently been developed to diagnose ARFID in children and adults. The PARDI also provides dimensional ratings of relevant presentations (selective sensory-based eating; low interest or low appetite food avoidance; and restrictive eating due to fear of aversive consequences) and overall ARFID severity.

Course and Outcome

At this point, little is known about the longitudinal course and outcome of ARFID. Selective eating (though not necessarily ARFID) in childhood has been identified as a risk factor for future psychiatric symptoms. While picky eating (accepting a food one day but eschewing it the next, or systematically avoiding some non-preferred foods, such as broccoli) is common in youth—particularly in preschoolers—children typically expand their diets as they mature. However, there are no data evaluating spontaneous remission rates among individuals with frank ARFID, which differs from developmentally normative picky eating in that individuals with ARFID may not reincorporate previously dropped foods, or may avoid entire categories of food (e.g., all vegetables). Indeed, in our clinical experience, many individuals who present for treatment in adulthood report longstanding selective eating patterns dating back to infancy or childhood (e.g., refusal of all but one type of infant formula, difficulty with transition to solid foods).

ARFID can lead to severe medical sequelae due to malnutrition. Retrospective studies have shown that these patients are at risk for amenorrhea, bradycardia, prolonged QT interval on electrocardiogram, and electrolyte abnormalities such as hypokalemia. One recent case report of ARFID in an adolescent male of normal weight demonstrated vitamin A, E, B12, D, K, and folate deficiencies as well as spinal cord degeneration secondary to his significantly restricted diet. Indeed, while weight loss and faltering growth are common signs of avoidant or restrictive eating, nutritional deficiencies can be observed independent of low weight. In our clinical practice we have also seen nutritional excesses, such as elevated mercury levels due to repeated consumption of high-mercury foods (e.g., tuna) in the context of an otherwise very limited diet. Prior research suggests that ARFID often develops in the context of childhood medical problems that lead to gastrointestinal dysfunction or pain., Clinically we often find that individuals with the fear of aversive consequences presentation initially begin restricting intake due to their belief that certain foods will cause them pain or discomfort but then find that, rather than resolving the pain, restriction and associated weight loss only exacerbate gastric motility problems and make regular eating even more challenging.

Psychiatric comorbidities, including anxiety disorders,, autism spectrum disorder, and attention deficit hyperactivity disorder (ADHD) are common among individuals with ARFID. A retrospective chart review of 34 pediatric patients with ARFID indicated that 50% also had generalized anxiety disorder. Co-occurring psychiatric disorders have implications for treatment. Consistent with a recent case report, it has been our clinical experience that comorbid ADHD treated with stimulant medication is sometimes a barrier to increasing caloric intake in individuals with ARFID who are underweight, because a common side effect of stimulant medication is decreased appetite.

Only a handful of studies documenting clinical outcomes of ARFID exist. One recent medical record review of acute medical hospitalizations in an academic medical center demonstrated that youth with ARFID required longer hospital stays and were more likely to require enteral nutrition for stabilization compared to those with AN. Outcomes at one-year follow-up (stability and rates of readmission) were similar between groups. In another record review, Forman and colleagues found that youth with ARFID presenting to adolescent medicine services were followed for less time and were less likely to reach healthy weights compared to those with AN or atypical AN. By contrast, Nakai and colleagues examined outcomes of 15–40 year-olds with ARFID compared to individuals with AN, all of whom were treated in Japan, finding that individuals with ARFID were more likely to recover (51.9% vs. 35.5%) and less likely to die (0% vs. 15%). Again, there is a paucity of outcomes data in ARFID and more work in this area is needed. Current studies compare ARFID to AN, but many individuals with ARFID are not low-weight, so AN may not be the most appropriate comparison group.

Lastly, operationalizing a definition of recovery from ARFID is complex. Beyond no longer meeting full criteria for ARFID, it is unclear what degree of weight restoration, dietary diversity, and nutritional repletion is expected to categorize an individual as recovered. For example, for youth who have always followed a low-percentile trajectory on standard growth curves, restoration to the median height/weight or body mass index centile may not be realistic. Similarly, it is unclear how many foods within each of the basic food categories (e.g., fruits, vegetables, proteins, grains, dairy) must be regularly consumed to resolve nutritional deficiencies or reduce psychosocial impairment. Finally, for the many individuals with ARFID who take vitamin supplements (e.g., multivitamins) prophylactically, supplementation may mask the severity of malnourishment, thus thwarting assessment of baseline medical sequelae and their potential resolution with treatment. This problem is akin to the difficulty in assessing menstrual status in patients with AN who take oral contraceptives, which ultimately led, in part, to amenorrhea being omitted as a diagnostic criterion. Clearly further research is needed to inform the optimal definition of ARFID recovery to assist in evaluating both treatment response and longitudinal outcomes.


There is a vast literature on the treatment of pediatric feeding disorders in young children, particularly behavioral interventions designed to increase dietary volume and variety. However, no randomized controlled trials have evaluated the efficacy of any type of ARFID treatment in adolescents or adults. Although individual case reports have highlighted the potential efficacy of cognitive-behavioral therapy,and family-based therapy for adolescents with ARFID, larger-scale studies are lacking.

In young children with ARFID who are consuming insufficient calories, strategies to increase dietary volume include oral nutritional formula supplementation, tube feeding, and intensive behavioral interventions delivered in day treatment or inpatient settings. Medical supervision of refeeding—including monitoring of cardiopulmonary status and electrolyte balance—is important. Because tube feeding is typically intended as a temporary measure, tube weaning is often an important subsequent treatment component. Typical tube weaning approaches involve a reduction in caloric supplementation by tube feed in order to stimulate the drive to eat and transition to oral feeding. Medical monitoring (e.g., hydration status, weight) is necessary during tube weaning, which can result in weight loss due to inadequate nutrient intake. In a recent randomized controlled trial (RCT) of 1- to 6-year-olds with ARFID (n = 20, 9 of whom were reliant on tube feeds), a 5-day manualized behavioral intervention significantly increased grams consumed at each meal, increased bite acceptance, and reduced mealtime disruptive behaviors, compared to a no-treatment wait-list control condition. Moreover, a meta-analysis of 11 of studies (only two of which were RCTs) evaluating day or inpatient programs for increasing dietary volume in children with ARFID—most of whom had significant co-occurring medical problems—demonstrated an overall 71% success rate, with a range of 43–100%, in weaning those on tube feeds. In studies using tube weaning as the primary intervention, success rates ranged from 81.4% to 100%.,,However, while the studies involving behavioral intervention without tube weaning reported weight stabilization or gain,,,, those evaluating tube weaning resulted in weight loss.,,,, In other words, although tube weaning is often successful in eliminating tube dependence, it should only be undertaken when the patient is able to tolerate at least a small amount of short-term weight loss and there is a clear plan for replacing tube calories with oral intake.

While underscoring the potential efficacy of intensive behavioral interventions for increasing dietary volume in young people with ARFID, these findings highlight the need for stronger designs such as RCTs featuring credible control conditions and standardized outcome measures. Collecting both short- and long-term outcomes (e.g., oral intake, need for oral supplements or tube feeds, nutritional value of caloric intake, weight, nutritional deficiencies, amenorrhea, and psychosocial status) will also be important to establish best practices for increasing dietary volume in underweight patients with ARFID. In addition, there is a need to include older patients and those who have less severe clinical manifestations of ARFID in research. It is also notable to us that while tube feeding—particularly long-term ambulatory feeding by..

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