httpswww.nationaleatingdisorders.orglearnby-eating-disordera.docx

https://www.nationaleatingdisorders.org/learn/by-eating-
disorder/arfid
AVOIDANT RESTRICTIVE FOOD INTAKE DISORDER
(ARFID)
Avoidant Restrictive Food Intake Disorder (ARFID) is a new
diagnosis in the DSM-5, and was previously referred to as
“Selective Eating Disorder.” ARFID is similar to anorexia in
that both disorders involve limitations in the amount and/or
types of food consumed, but unlike anorexia, ARFID does not
involve any distress about body shape or size, or fears of
fatness.
Although many children go through phases of picky or selective
eating, a person with ARFID does not consume enough calories
to grow and develop properly and, in adults, to maintain basic
body function. In children, this results in stalled weight gain
and vertical growth; in adults, this results in weight loss.
ARFID can also result in problems at school or work, due to
difficulties eating with others and extended times needed to eat.
DIAGNOSTIC CRITERIA
According to the DSM-5, ARFID is diagnosed when:
· An eating or feeding disturbance (e.g., apparent lack of
interest in eating or food; avoidance based on the sensory
characteristics of food; concern about aversive consequences of
eating) as manifested by persistent failure to meet appropriate
nutritional and/or energy needs associated with one (or more) of
the following:
· Significant weight loss (or failure to achieve expected weight
gain or faltering growth in children).
· Significant nutritional deficiency.
· Dependence on enteral feeding or oral nutritional supplements.
· Marked interference with psychosocial functioning.
· The disturbance is not better explained by lack of available
food or by an associated culturally sanctioned practice.
· The eating disturbance does not occur exclusively during the

course of anorexia nervosa or bulimia nervosa, and there is no
evidence of a disturbance in the way in which one’s body
weight or shape is experienced.
· The eating disturbance is not attributable to a concurrent
medical condition or not better explained by another mental
disorder. When the eating disturbance occurs in the context of
another condition or disorder, the severity of the eating
disturbance exceeds that routinely associated with the condition
or disorder and warrants additional clinical attention.
RISK FACTORS
As with all eating disorders, the risk factors for ARFID involve
a range of biological, psychological, and sociocultural issues.
These factors may interact differently in different people, which
means two people with the same eating disorder can have very
diverse perspectives, experiences, and symptoms. Researchers
know much less about what puts someone at risk of developing
ARFID, but here’s what they do know:
· People with autism spectrum conditions are much more likely
to develop ARFID, as are those with ADHD and intellectual
disabilities.
· Children who don’t outgrow normal picky eating, or in whom
picky eating is severe, appear to be more likely to develop
ARFID.
· Many children with ARFID also have a co-occurring anxiety
disorder, and they are also at high risk for other psychiatric
disorders.
WARNING SIGNS & SYMPTOMS OF ARFID
Behavioral and psychological
· Dramatic weight loss
· Dresses in layers to hide weight loss or stay warm
· Reports constipation, abdominal pain, cold intolerance,
lethargy, and/or excess energy
· Reports consistent, vague gastrointestinal issues (“upset
stomach”, feels full, etc.) around mealtimes that have no known
cause
· Dramatic restriction in types or amount of food eaten

· Will only eat certain textures of food
· Fears of choking or vomiting
· Lack of appetite or interest in food
· Limited range of preferred foods that becomes narrower over
time (i.e., picky eating that progressively worsens).
· No body image disturbance or fear of weight gain
Physical
Because both anorexia and ARFID involve an inability to meet
nutritional needs, both disorders have similar physical signs and
medical consequences.
· Stomach cramps, other non-specific gastrointestinal
complaints (constipation, acid reflux, etc.)
· Menstrual irregularities—missing periods or only having a
period while on hormonal contraceptives (this is not considered
a “true” period)
· Difficulties concentrating
· Abnormal laboratory findings (anemia, low thyroid and
hormone levels, low potassium, low blood cell counts, slow
heart rate)
· Postpuberty female loses menstrual period
· Dizziness
· Fainting/syncope
· Feeling cold all the time
· Sleep problems
· Dry skin
· Dry and brittle nails
· Fine hair on body (lanugo)
· Thinning of hair on head, dry and brittle hair
· Muscle weakness
· Cold, mottled hands and feet or swelling of feet
· Poor wound healing
· Impaired immune functioning
HEALTH CONSEQUENCES OF ARFID
In ARFID, the body is denied the essential nutrients it needs to
function normally. Thus, the body is forced to slow down all of
its processes to conserve energy, resulting in serious medical

consequences. The body is generally resilient at coping with the
stress of eating disordered behaviors, and laboratory tests can
generally appear perfect even as someone is at high risk of
death. Electrolyte imbalances can kill without warning; so can
cardiac arrest. Therefore, it’s incredibly important to understand
the many ways that eating disorders affect the body.
Cognitive-Behavioral Treatment of Avoidant/Restrictive Food
Intake Disorder
Jennifer J. Thomas, Ph.D.1,2, Olivia Wons, B.S.3, and Kamryn
Eddy, Ph.D.1,2
1Eating Disorders Clinical and Research Program,
Massachusetts General Hospital
2Department of Psychiatry, Harvard Medical School
3Neuroendocrine Unit, Massachusetts General Hospital
Abstract
Purpose of review: Avoidant/restrictive food intake disorder
(ARFID) was added to the
psychiatric nomenclature in 2013, but little is known about its
optimal treatment. The purpose of
this paper is to review the recent literature on ARFID treatment
and highlight a novel cognitive-
behavioral approach presently under study.
Recent findings: The current evidence base for ARFID

treatment relies primarily on case
reports, case series, and retrospective chart reviews, with only a
handful of randomized controlled
trials in young children. Studies in adults are lacking. ARFID
treatments recently described in the
literature include family-based treatment and parent training;
cognitive-behavioral approaches;
hospital-based re-feeding including tube feeding; and adjunctive
pharmacotherapy. A novel form
of outpatient cognitive-behavioral therapy for ARFID (CBT-
AR) is one treatment currently under
study. CBT-AR is appropriate for children, adolescents, and
adults ages 10 and up; proceeds
through four stages across 20–30 sessions; and is available in
both individual and family-
supported versions.
Summary: There is no evidence-based psychological treatment
suitable for all forms of ARFID
at this time. Several groups are currently evaluating the efficacy
of new psychological treatments
for ARFID—particularly family-based and cognitive-behavioral
approaches—but results have not
yet been published.
Keywords

Avoidant/restrictive food intake disorder; ARFID; family-based
treatment; cognitive-behavioral
therapy; tube feeding
Correspondence to: Jennifer J. Thomas, Ph.D., Eating Disorders
Clinical and Research Program, Massachusetts General
Hospital, 2
Longfellow Place, Suite 200, Boston, MA 02114.
[email protected] Phone: (617) 643-6306.
Conflicts of interest. Drs. Thomas and Eddy will receive
royalties from Cambridge University Press for the sale of their
book
Cognitive-Behavioral Therapy for Avoidant/Restrictive Food
Intake Disorder: Children, Adolescents, and Adults, scheduled
to be
published in late 2018.
HHS Public Access
Author manuscript
Curr Opin Psychiatry. Author manuscript; available in PMC
2019 November 01.
Published in final edited form as:
Curr Opin Psychiatry. 2018 November ; 31(6): 425–430.
doi:10.1097/YCO.0000000000000454.
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Introduction
Avoidant/restrictive food intake disorder (ARFID) made its
diagnostic debut in 2013 with
the publication on DSM-5 [1]. ARFID is a reformulation and
expansion of the former DSM-
IV diagnosis of feeding disorder of infancy and early childhood,
and can occur across the
lifespan. The hallmark feature of ARIFD is food avoidance or
restriction, motivated by
sensitivity to the sensory characteristics of food, fear of
aversive consequences of eating, or
lack of interest in eating or food. To meet criteria for ARFID,
the food restriction or
avoidance must lead to one or more consequences such as
weight loss or faltering growth,
nutritional deficiency, dependence on oral nutritional
supplements or tube feeding, or

psychosocial impairment. DSM-5 describes three example
presentations of ARFID. In the
first, individuals eat a very limited range of foods due to an
inability to tolerate certain tastes
and textures. In the second, individuals avoid specific foods or
categories of food, or may
stop eating altogether, for fear of aversive consequences of
eating, such as choking,
vomiting, anaphylaxis, or gastrointestinal distress. In the third,
individuals exhibit a lack of
interest in food or eating. It is important to note that these three
presentations are not
mutually exclusive and can co-occur within the same individual
[2].
In addition to the heterogeneity of clinical presentation, ARFID
is also quite diverse in terms
of age, demographics, and comorbidities, highlighting the
difficulty in identifying a
universally applicable treatment approach. For example, ARFID
has been reported in very
young children [3 **], adolescents [4 *], and adults [5], and
several studies have highlighted
that both males and females present with the disorder [6,7].
Other investigations have

underscored numerous potential psychiatric and medical
comorbidities, including autism
spectrum disorder [8] and gastrointestinal disorders [6], which
may further individualize
treatment needs.
Available data on the treatment of ARFID
Because ARFID is so new, there is currently no evidence-based
treatment suitable for all
forms of the disorder. A robust literature that pre-dates DSM-5
supports the efficacy of
behavioral interventions for young children with pediatric
feeding disorders [9,10].
However, the generalizability of these approaches to individuals
with ARFID—especially
adolescents and adults—remains unclear. Below we summarize
studies published since the
2013 advent of DSM-5 that describe the treatment of ARFID
specifically. ARFID treatments
recently described in the literature include family-based
treatment and parent training;
cognitive-behavioral approaches; hospital-based re-feeding
including tube feeding; and
adjunctive pharmacotherapy.
Family-based treatment and parent training

Several recently published case reports have described the use
of family-based treatment
(FBT) for children and adolescents with ARFID [11,12,13].
Such approaches are similar to
FBT for anorexia nervosa (AN) in that parents are charged with
the task of feeding, but
differ from FBT for AN in that parents are asked to support
their children in increasing not
only dietary volume, but also dietary variety through repeated
exposure to novel foods. At
least two clinical trials of FBT for ARFID are currently
underway [14,15]. Another case
Thomas et al. Page 2
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report described the use of a behavioral parent-training
intervention comprising differential
reinforcement, gradual exposure to novel foods, and
contingency management, resulting in
the acceptance of 30 novel foods in a six-year-old with limited
dietary variety [16].
Cognitive-behavioral approaches
Multiple published case reports and case series have described
the use of various forms of
cognitive-behavioral therapy (CBT) for children [13,17,18] and
adults [19,5] with ARFID.
Common elements across CBT interventions for ARFID include
regular eating [5,13], self-
monitoring of food intake [5], exposure and response prevention
[13,16], relaxation training
[17,16, and behavioral experiments [5]. In one case study, a 16-
year-old boy was able to
significantly increase his consumption of proteins, fruits, and

vegetables, and significantly
decrease his eating-related distress after 11 sessions of CBT
supplemented with in-home
meal interventions in which his mother reinforced the
consumption of novel foods [16].
Hospital-based re-feeding including tube feeding
Several hospital-based re-feeding programs have reported
positive outcomes on eating and
weight for children and adolescents with low-weight ARFID.
One randomized controlled
study prospectively evaluated the efficacy, among 20 boys and
girls (ages 13–72 months)
with ARFID, of a five-day manualized behavioral treatment
comprising structured
mealtimes, escape extinction, and reinforcement procedures in a
day hospital setting.
Patients randomized to the study treatment exhibited
significantly greater bite acceptance,
grams of food consumed at mealtime, and fewer mealtime
disruptions post-treatment
compared to those in the wait list control condition 3 **].
Another study described treatment
response among 32 children and adolescents with ARFID
treated in an eating disorders

partial hospitalization program, reporting significant increases
in weight and significant
decreases in eating pathology and anxiety from pre- to post-
treatment after an average of
seven weeks [4 *]. Treatment gains were maintained for at least
12 months in the subset of
20 patients who completed a follow-up assessment [20].
Several case studies have described the use of tube feeding to
support inpatient nutritional
rehabilitation among low-weight children and adolescents (ages
5–17 years old) with
ARFID [21,22,23]. Of note, at least two studies have reported
that patients with ARFID
were significantly more likely than those with other eating
disorders to require tube feeding
during inpatient hospitalization [24,25 *]. Although tube
feeding can be a life-saving
measure in some cases of acute food refusal, a recent review
described potentially iatrogenic
effects of tube feeding, including long-term tube dependence
and decreased oral intake [26],
highlighting the urgent need for future research on effective
tube weaning protocols for

individuals who require tube feeding.
Adjunctive pharmacotherapy
Three groups have recently published studies on
pharmacotherapy as an adjunct to hospital-
based treatment to facilitate meal consumption and/or weight
gain in low-weight children
and adolescents with ARFID. In one retrospective chart review,
14 children and adolescents
demonstrated a significantly faster rate of weight gain after
(versus before) being prescribed
mirtazapine [27 *]. In another retrospective chart review, nine
youth who took olanzapine
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showed significant increases in weight from pre- to post-
treatment [28 *]. The only double-
blind randomized placebo-controlled trial of medication for
ARFID evaluated the efficacy of
D-cycloserine (DCS) augmentation of a five-day behavioral
intervention for chronic and
severe food refusal in 15 children (ages 20–58 months). Those
randomized to the DCS
condition showed a significantly greater percentage of bites
rapidly swallowed, and
significantly fewer mealtime disruptions, compared to those
receiving placebo [29 **].
Summary of available data
Available data on the treatment of ARFID are sparse, and
limited to child and adolescent
populations. Studies are limited to case reports, case series, and
retrospective chart reviews,

with a handful of randomized controlled trials in very young
children treated in day hospital
settings. Findings in adults are limited to case reports, with no
larger-scale studies on
patients over the age of 18. Several groups are currently
evaluating the efficacy of new
psychological treatments for ARFID [14,15,30], but results have
not yet been published.
Case reports and case series have highlighted the promise of
family-based treatment,
cognitive-behavioral therapy, and hospital-based re-feeding,
with pharmacotherapy as an
adjunctive rather than a stand-alone treatment. Prospective
randomized controlled trials are
needed, particularly for adolescents and adults.
The cognitive-behavioral formulation of ARFID
To fill the need for manualized treatments suitable for testing in
randomized controlled
trials, our team at Massachusetts General Hospital has
developed a novel form of cognitive-
behavioral therapy for ARFID that is currently being tested in
an open trial in which 20
participants ages 10–22 are receiving either individual of
family-based versions of the

treatment [30,31 **]. The goal of CBT-AR is to help patients
achieve a healthy weight,
resolve nutrition deficiencies, increase variety to include
multiple foods from each of the
five basic food groups, eliminate dependence on nutritional
supplements, and reduce
psychosocial impairment. CBT-AR is based on our cognitive-
behavioral conceptualization
of the disorder (Figure 1), which posits that some individuals
have a biological
predisposition to sensory sensitivity, fear of aversive
consequences, and/or lack of interest in
food or eating [2]. Specifically, those with sensory sensitivity
may have heightened response
to unfamiliar tastes and smells, those with fear of aversive
consequences may have high trait
anxiety, and those with lack of interest in eating or food may
have lower homeostatic or
hedonic appetites.
The CBT model posits that individuals with such
predispositions will be vulnerable to
developing negative feelings and predictions about eating. For
example, the patient with

sensory sensitivity might feel disgust about novel foods and
predict, “Every time I have
tasted a vegetable, I have gagged, so I will probably hate any
other vegetable.” These
negative feelings and predictions would logically lead the
patient to begin restricting food
intake. Unfortunately, this food avoidance has both
physiological and psychological
consequences that reinforce negative feelings and predictions.
Physiologically, the patient
may experience nutritional compromise, such as weight loss or
nutrition deficiencies. Under
these auspices the patient may experience the predictable
consequences of starvation such as
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becoming satisfied on smaller portions of food, and
experiencing altered taste perception
from nutrition deficiencies, thus reinforcing the cycle of
restricting volume. Psychologically,
the more the patient relies on the same foods again and again,
the greater the just noticeable
difference will become between the patient’s preferred foods
and novel foods, thus
reinforcing the cycle of restricting variety.
Cognitive-behavioral therapy for ARFID (CBT-AR)
Based on our cognitive-behavioral model of ARFID, CBT-AR is
designed reduce nutritional
compromise and increase opportunities for exposure to novel
foods to reduce negative
feelings and predictions about eating. CBT-AR is appropriate
for the outpatient treatment of

children, adolescents, and adults with ARFID (ages 10 and up).
CBT-AR is a flexible,
modular treatment designed to last approximately 20 (for
patients who are not underweight)
to 30 (for patients who have significant weight to gain) sessions
over six to 12 months. CBT-
AR is appropriate for individuals with ARFID who are
medically stable, currently accepting
at least some food by mouth, and not receiving tube feeding.
Patients who are under the age
of 16 and/or older adolescents and young adult patients who
have significant weight to gain
can be offered a family-supported version of CBT-AR, whereas
patients ages 16 years and
up without significant weight to gain can be treated with an
individual version.
CBT-AR proceeds through four broad stages (Table 1) [31 **].
In Stage 1, the therapist
provides psychoeducation about ARFID and CBT-AR. In
addition, the therapist encourages
the patient to establish a pattern of regular eating and self-
monitoring by relying primarily
on preferred foods, but also encourages early change by asking
the patient who is not

underweight to begin introducing minor variations in the
presentation of preferred foods
and/or reintroducing previously dropped foods. In contrast, the
therapist encourages early
change for patients who are underweight by asking them (often
with family support) to
increase their intake by at least 500 calories per day to support
a weight gain of
approximately 1–2 lbs per week.
In Stage 2, the therapist provides psychoeducation about
nutrition deficiencies and supports
the patient in selecting novel fruits, vegetables, proteins, dairy,
and grains to learn about in
Stage 3 that will support resolution of these deficiencies,
encourage further weight gain,
and/or ameliorate psychosocial impairment.
In Stage 3—the heart of the treatment—the therapist selects the
module(s) most appropriate
to the patient’s ARFID maintaining mechanisms(s) including
sensory sensitivity, fear of
aversive consequences, and/or lack of interest in food or eating.
For patients with multiple
maintaining mechanisms, the therapist starts with the module

addressing the primary or most
impairing mechanism. Although Stage 3 interventions differ
based on the specific module,
the common element across all modules is exposure. For
patients with sensory sensitivity,
the therapist invites the patient (or family) to bring five novel
foods to each session and asks
the patient to non-judgmentally describe each food’s
appearance, feel, smell, taste, and
texture. The patient then selects foods to practice tasting
throughout the week to facilitate
habituation, and later works to incorporate larger portions of
these novel foods into his or
her day-to-day diet. For patients with fear of aversive
consequences, the therapist works with
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the patient (or family) to create a fear and avoidance hierarchy
of foods and eating-related
situations that the patient fears will lead to negative outcomes.
The therapist then conducts
in-session exposures to these foods and situations, and asks the
patient to repeat these
exposures for homework, to test the patient’s predictions that
the feared outcome will
actually occur. Lastly, for patients with lack of interest in
eating, the therapist introduces a
series of interoceptive exposures (e.g., pushing one’s belly out,
gulping water, and spinning
in a chair) to help the patient habituate to sensations associated
with eating and fullness. The
therapist also helps the patient remember what he or she enjoys

about his or her preferred
foods by describing their appearance, feel, smell, taste, and
texture.
Lastly, in Stage 4, the therapist supports the patient in
evaluating progress, co-creating a
relapse prevention plan, and setting goals for the future.
Conclusion and future directions
The addition of ARFID to DSM-5 has drawn attention to the
urgent need for research into its
optimal treatment. Available data are limited to case reports,
case series, and randomized
controlled trials in specialized populations of children and
adolescents; treatment studies in
adults are lacking. New psychological therapies are currently
being tested. One such
approach is a novel form of cognitive-behavioral therapy for
children, adolescents, and
adults that can be offered over 20–30 sessions in an individual
or family-supported format.
Given the heterogeneity of ARFID, it is likely that different
presentations will require
different interventions, and that once clinical trials have been
completed, patients can be
matched to the treatment that is the best fit for their unique

clinical needs.
Acknowledgments
Disclosure of funding. The authors would like to gratefully
acknowledge funding for the work described in this
paper from the National Institute of Mental Health
(1R01MH108595), Hilda and Preston Davis Foundation, and
American Psychological Foundation.
References and Recommended Reading
Papers of particular interest, published within the annual period
of review, have been
highlighted as:
* of special interest
** of outstanding interest
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behaviors. 2015; 19:106–9.
[PubMed: 26276708]

2019 November 01.
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20. Bryson AE, Scipioni AM, Essayli JH et al. Outcomes of
low‐weight patients with avoidant/
restrictive food intake disorder and anorexia nervosa at
long‐term follow‐up after treatment in a
partial hospitalization program for eating disorders.
International Journal of Eating Disorders.
2018; 51:470–474. [PubMed: 29493804]
21. Guvenek-Cokol PE, Gallagher K, Samsel C. Medical
traumatic stress: a multidisciplinary approach

for iatrogenic acute food refusal in the inpatient setting.
Hospital pediatrics. 2016; 6:693–8.
[PubMed: 27803075]
22. Pitt PD, Middleman AB. A focus on behavior management
of avoidant/restrictive food intake
disorder (ARFID): a case series. Clinical pediatrics. 2018;
57:478–80. [PubMed: 28719985]
23. Schermbrucker J, Kimber M, Johnson N et al.
Avoidant/restrictive food intake disorder in an 11-
year old south American boy: medical and cultural challenges.
Journal of the Canadian Academy
of Child and Adolescent Psychiatry. 2017; 26:110–113.
[PubMed: 28747934]
24. Strandjord SE, Sieke EH, Richmond M, Rome ES.
Avoidant/restrictive food intake disorder: illness
and hospital course in patients hospitalized for nutritional
insufficiency. Journal of Adolescent
Health. 2015; 57:673–8. [PubMed: 26422290]
25 *. Peebles R, Lesser A, Park CC et al. Outcomes of an
inpatient medical nutritional rehabilitation
protocol in children and adolescents with eating disorders.
Journal of eating disorders. 2017; 5:1–
14.
This paper describes the Children’s Hospital of Philadelphia
(CHOP) Malnutrition Protocol for the
inpatient re-feeding of children and adolescents with restrictive
eating disorders, including
ARFID.

[PubMed: 28053702]
26. Dovey TM, Wilken M, Martin CI, Meyer C. Definitions and
clinical guidance on the enteral
dependence component of the avoidant/restrictive food intake
disorder diagnostic criteria in
children. Journal of Parenteral and Enteral Nutrition. 2018;
42:499–507.
27 *. Gray E, Chen T, Menzel J et al. Mirtazapine and weight
gain in avoidant and restrictive food
intake disorder. Journal of the American Academy of Child &
Adolescent Psychiatry. 2018;
57:288–9.
This retrospective chart review describes adjuctive
pharmacotherapy with mirtazipine for children and
adolescents with ARFID.
[PubMed: 29588055]
28 *. Brewerton TD, D’Agostino M. Adjunctive use of
olanzapine in the treatment of avoidant
restrictive food intake disorder in children and adolescents in an
eating disorders program.
Journal of child and adolescent psychopharmacology. 2017;
27:920–2.
This retrospective chart review describes adjunctive
pharmacotherapy with olanazapine for children
and adolescents with ARFID.
[PubMed: 29068721]

29 **. Sharp WG, Allen AG, Stubbs KH et al. Successful
pharmacotherapy for the treatment of severe
feeding aversion with mechanistic insights from cross-species
neuronal remodeling. Translational
psychiatry. 2017; 7:1–9.
This double blind randomized placebo controlled trial describes
adjunctive pharmacotherapy with D-
cycloserine for young children with chronic and severe food
refusal.
30. Thomas JJ, Becker KR, Wons O et al. Cognitive behavioral
therapy for avoidant/restrictive food
intake disorder (CBT-AR): A pilot study demonstrating
feasibility, efficacy, and acceptability.
Submitted to the XXIVth Annual Meeting of the Eating
Disorders Research Society 2018.
31 **. Thomas JJ, Eddy KT. Cognitive-behavioral therapy for
children, adolescents, and adults. Cambridge, UK: Cambridge
University Press; in press.
This book describes a novel cognitive-behavioral model of the
maintenance of ARFID and is the first
treatment manual to describe the implementation of cognitive-
behavioral therapy for the disorder.
2019 November 01.
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Key points
• There are no evidence-based psychological treatments suitable
for all forms
of avoidant/restrictive food intake disorder at this time.
• The current evidence base for ARFID treatment relies
primarily on case
reports, case series, retrospective chart reviews, and a handful
of randomized
controlled trials in very young children. Treatment studies in
adults are
lacking.

• ARFID interventions recently described in the literature
include family-based
treatment and parent training; cognitive-behavioral approaches;
hospital-
based re-feeding including tube feeding; and adjunctive
pharmacotherapy.
• New psychological treatments are currently being tested,
including a novel
form of cognitive-behavioral therapy for children, adolescents,
and adults that
can be offered over 20–30 sessions in an individual or family-
supported
format.
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Figure 1.
Cognitive-behavioral model of avoidant/restrictive food intake
disorder
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Table 1.
Four stages of cognitive-behavioral therapy for
avoidant/restrictive food intake disorder (CBT-AR)
Stage Primary interventions
1. Psychoeducation and
early change

(2–4 sessions)
• Psychoeducation on ARFID and its treatment
• Self- or parent-monitoring of food intake
• Establishing a pattern of regular eating to normalize hunger
cues
• Increasing volume of preferred foods (for patients who are
underweight) and variety (for all patients)
• Individualized formulation of mechanisms that maintain
avoidant/restrictive eating (i.e., sensory sensitivity,
fear of aversive consequences, lack of interest in eating or food)
2. Treatment planning (2
sessions)
• Continue increasing volume and/or variety
• Reviewing intake from Primary Food Group Building Blocks
and selecting foods to learn about in Stage 3
3. Maintaining mechanisms
in order of priority (14–22
sessions)
• Sensory sensitivity: Systematic desensitization to novel foods
by repeated in-session exploration of sight,
smell, texture, taste, chew; specific, detailed plans for out-of-
session practice with tasting and incorporation
• Fear of aversive consequences: Psychoeducation about how
avoidance maintains anxiety, development of
fear/avoidance hierarchy, graded exposure to feared foods and
situations in which choking, vomiting, or other
feared consequence may occur
• Apparent lack of interest in eating or food: Interoceptive
exposure to bloating, fullness, and/or nausea; in-
session exposure to highly-preferred foods

4. Relapse prevention(2
sessions)
• Evaluating whether treatment goals have been met, identifying
treatment strategies to continue at home, and
developing a plan for maintaining weight gain (if needed)
continuing to learn about novel foods
2019 November 01.
AbstractIntroductionAvailable data on the treatment of
ARFIDFamily-based treatment and parent trainingCognitive-
behavioral approachesHospital-based re-feeding including tube
feedingAdjunctive pharmacotherapySummary of available
dataThe cognitive-behavioral formulation of ARFIDCognitive-
behavioral therapy for ARFID (CBT-AR)Conclusion and future
directionsReferencesFigure 1.Table 1.
Eating Disorder Core Symptoms and Symptom Pathways Across
Developmental Stages: A Network Analysis
Caroline Christian
University of Louisville
Victoria L. Perko
University of Kansas
Irina A. Vanzhula
Jenna P. Tregarthen
Recovery Record, Inc., San Francisco, California
Kelsie T. Forbush

University of Kansas
Cheri A. Levinson
Eating disorders (EDs) often develop during adolescence and
early adulthood but may persist, arise, or
reemerge across the life span. Research and treatment efforts
primarily focus on adolescent and young
adult populations, leaving large knowledge gaps regarding ED
symptoms across the entire developmental
spectrum. The current study uses network analysis to compare
central symptoms (i.e., symptoms that are
highly connected to other symptoms) and symptom pathways
(i.e., relations among symptoms) across
five developmental stages (early adolescence, late adolescence,
young adulthood, early-middle adult-
hood, middle-late adulthood) in a large sample of individuals
with EDs (N � 29,902; N � 32,219) in two
network models. Several symptoms related to overeating, food
avoidance, feeling full, and overvaluation
of weight and shape emerged as central in most or all
developmental stages, suggesting that some core
symptoms remain central across development. Despite
similarities in central symptoms, significant
differences in network structure (i.e., how symptom pathways
are connected) emerged across age groups.
These differences suggest that symptom interconnectivity (but
not symptom severity) might increase
across development. Future research should continue to
investigate developmental symptom differences
in order to inform treatment for individuals with EDs of all
ages.
General Scientific Summary
Connections between eating disorder symptoms vary across

stages of development. Consistent with
Habit Formation Theory, symptoms were more tightly connected
in older individuals, who have on
average a longer duration of illness. In contrast, eating disorder
central symptoms (symptoms related
to overeating, food avoidance, fullness, and overvaluation of
weight and shape) were relatively
consistent across age groups.
Keywords: eating disorder symptoms, development, age,
network analysis, eating disorders
Supplemental materials:
http://dx.doi.org/10.1037/abn0000477.supp
This article was published Online First November 11, 2019.
X Caroline Christian, Department of Psychological and Brain
Sciences,
University of Louisville; Victoria L. Perko, Department of
Psychology,
University of Kansas; Irina A. Vanzhula, Department of
Psychological and
Brain Sciences, University of Louisville; Jenna P. Tregarthen,
Recovery
Record, Inc., San Francisco, California; Kelsie T. Forbush,
Department of
Psychology, University of Kansas; Cheri A. Levinson,
Department of
Psychological and Brain Sciences, University of Louisville.
The present study is a new analysis of previously analyzed data.
This
study is the investigation of developmental differences in eating
disorder
symptoms using network analysis using this dataset. No other

papers have
addressed similar questions as those addressed in this article.
All study
procedures were approved by the University of Kansas
Institutional Re-
view Board (Study IRB STUDY00003260). Authors complied
with APA
ethical standards in the treatment of their participants. The
manuscript has
not been and is not posted on a website. Jenna P. Tregarthen is a
co-founder
and shareholder of Recovery Record, Inc. Jenna P. Tregarthen
made a
substantial contribution as part of data collection and curation
and ap-
proved the final manuscript, but she did not participate in the
analysis,
interpretation, or drafting of the manuscript. Kelsie T. Forbush
received an
industry-sponsored grant from Recovery Record, Inc. No other
authors
have conflicts of interest to disclose.
Correspondence concerning this article should be addressed to
Cheri A.
Levinson, Department of Psychological and Brain Sciences,
University of
Louisville, Life Sciences Building 317, Louisville, KY 40292.
E-mail:
[email protected]
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Journal of Abnormal Psychology
© 2019 American Psychological Association 2020, Vol. 129,
No. 2, 177–190
ISSN: 0021-843X http://dx.doi.org/10.1037/abn0000477
177
https://orcid.org/0000-0001-7741-1498
mailto:[email protected]
http://dx.doi.org/10.1037/abn0000477
Eating disorders (EDs) are serious mental illnesses associated
with negative health consequences, significant impairment, and
high mortality (Crow et al., 2009; Rome & Ammerman, 2003;
Stice, Marti, & Rohde, 2013). Peak age of ED onset is during
adolescence, between 16 and 20 years of age (Stice et al.,
2013).
Although EDs most commonly develop during this period, evi-
dence suggests that eating pathology may persist, return, or de-
velop throughout an individual’s life (Fulton, 2016; Patrick &
Stahl, 2009). Indeed, studies indicate that ED symptoms occur
across all developmental stages, with approximately 11% of
adults
aged 42–55 and 4% of adults aged 60 –70 engaging in ED
behav-
iors, such as binge eating, laxative/diuretic misuse, or self-
induced
vomiting (Mangweth-Matzek et al., 2006; Marcus, Bromberger,
Wei, Brown, & Kravitz, 2007). The presence of disordered

eating
among middle and older adults suggests that it is important to
examine EDs across the full developmental spectrum; however,
to
date, research has primarily focused on EDs in adolescence and
early adulthood.
Past research suggests that ED symptoms may change across
development. However, the nature of these differences remains
unclear. In terms of diagnoses, older individuals are more likely
to
be diagnosed with binge eating disorder, as compared to
younger
individuals with EDs (Jenkins & Price, 2018). Additionally,
diag-
nostic migration is extremely common in EDs, which suggests
that
symptomatology may shift as the person and illness develop
(Cas-
tellini et al., 2011; Fichter & Quadflieg, 2007). In terms of
sever-
ity, some research suggests that disordered eating behaviors,
body
dissatisfaction, and distorted cognitions surrounding food
decline
with age (Gadalla, 2008; Forman & Davis, 2005; Tiggemann &
McCourt, 2013). Reduction of ED cognitions may be related to
the
changing social environment over the life span. In one study,
the
association between negative commentary about one’s weight
and
shape and bulimic symptoms diminished with older age
(Tzoneva,
Forney, & Keel, 2015).

However, other studies indicated body dissatisfaction and diet-
ing behaviors remain prevalent and may strengthen with age
(e.g.,
Fulton, 2016). Indeed, research supports that overvaluation of
weight and shape is pervasive among middle age and older
adults
(Forman & Davis, 2005; Patrick & Stahl, 2009; Mangweth-
Matzek
et al., 2006). The Habit Formation Theory of EDs suggests that
maladaptive eating behaviors may begin as goal-driven (e.g., di-
eting to lose weight), but with repetition, these behaviors (e.g.,
restriction), coupled with the reward (e.g., praise from others on
losing weight), develop into a deeply engrained habit (Walsh,
2013). Similarly, binge eating and purging behaviors may begin
impulsively to cope with negative emotions but can develop into
compulsive rituals with repetition (Pearson, Wonderlich, &
Smith,
2015). Thus, Habit Formation Theory posits that maladaptive
eating behaviors and cognitions will become more deeply en-
grained and habitual in later developmental stages. Indeed,
studies
indicate that older age of onset and longer duration-of-illness
are
associated with poor treatment outcomes (Noordenbos, Olden-
have, Muschter, & Terpstra, 2002; Norring & Sohlberg, 1993),
highlighting the clinical importance of researching eating
pathol-
ogy across development.
Overall, the current state of eating disorder research provides an
incomplete picture of cognitions and behaviors across the life
span.
Thus, additional research examining the differences in eating
dis-
order symptoms across developmental stages is urgently needed.

Specifically, it is unknown how specific symptoms and
symptom
relationships might change across developmental periods to
main-
tain ED psychopathology.
One novel way to conceptualize EDs is network theory. Net-
work analysis (NA) is a statistical methodology based on
network
theory, which conceptualizes psychopathology as a web of
inter-
connecting nodes (symptoms) and edges (associations between
symptoms) that are theorized to maintain a specific illness state
(Borsboom, 2017). NA allows researchers to identify specific
relationships among many symptoms at once and provides
oppor-
tunities to visualize illness pathways (relationships among
individ-
ual symptoms) and identify central symptoms (symptoms that
are
highly connected with other symptoms in the network). NA can
also identify if two networks are significantly different from
each
other in structure (i.e., if two symptoms are similarly associated
in
both networks) and global strength (how strongly symptoms are
associated with each other; van Borkulo et al., 2015). This tech-
nique allows researchers to investigate if (and how) two popula-
tions or subgroups of a population differ in symptom connected-
ness.
Several studies have used NA to understand ED psychopathol-
ogy. These studies found body checking (Forbush, Siew, &
Vite-
vitch, 2016), fear of weight gain (Elliott, Jones, & Schmidt,
2018;

Forrest, Jones, Ortiz, & Smith, 2018; Levinson et al., 2017), and
other symptoms related to overvaluation of weight and shape
(DuBois, Rodgers, Franko, Eddy, & Thomas, 2017; Elliott et
al.,
2018; Forrest et al., 2018; Goldschmidt et al., 2018; Wang,
Jones,
Dreier, Elliott, & Grilo, 2018) to be central, maintaining symp-
toms, consistent with the cognitive– behavioral theory of EDs
(Cooper & Shafran, 2008; Fairburn, 2008). A few additional
studies have identified additional important symptoms, such as
dietary restraint (Goldschmidt et al., 2018; Solmi et al., 2018),
interoceptive awareness, (Olatunji, Levinson, & Calebs, 2018;
Solmi et al., 2018), and ineffectiveness (Olatunji et al., 2018;
Solmi et al., 2018; Solmi, Collantoni, Meneguzzo, Tenconi, &
Favaro, 2019), and the relationships among depression, anxiety,
and ED symptoms (Solmi et al., 2018, 2019).
Although NA has been applied to increase the broad understand-
ing of eating pathology, no research has examined differences
in
network models of ED symptoms across developmental stages.
Past research suggests that there may be unique differences in
ED
presentations across the life span, including diagnostic
differences,
physical changes, and differences in treatment outcomes (Cas-
tellini et al., 2011; Forman & Davis, 2005; Hudson & Pope,
2018;
Jenkins & Price, 2018; Peat, Peyerl, & Muehlenkamp, 2008).
Thus, it seems likely that ED symptom relationships may also
differ across developmental stages. Better understanding of the
differences in central ED symptoms across developmental
stages
could help determine if alternative treatments would be more
beneficial for different age groups.

The current study utilizes NA to examine ED symptoms in five
distinct developmental stages: early adolescence (11–14), late
ad-
olescence (15–18), young adulthood (19 –25), early-middle
adult-
hood (26 – 45), and middle-late adulthood (46�). These age
ranges
represent unique developmental stages in several aspects,
includ-
ing social environment, physiological and neurological develop-
ment, maturity, and autonomy (Blonigen, Carlson, Hicks,
Krueger,
& Iacono, 2008; Steinberg, 2005; Williams & Currie, 2000). We
examine symptom relationships across two widely used ED
mea-
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178 CHRISTIAN ET AL.
sures: the Eating Pathology Symptoms Inventory (EPSI;
Forbush
et al., 2013) and Eating Disorder Examination Questionnaire
(EDE-Q; Fairburn & Beglin, 1994). Both questionnaires are
con-

sidered “gold-standard” measures of ED symptoms and are fre-
quently used for network investigations (DuBois et al., 2017;
Forbush et al., 2016; Forrest et al., 2018), yet they assess
slightly
different aspects of ED symptoms, such that the EDE-Q is based
on the cognitive– behavioral model of EDs and the EPSI is de-
signed to be a multidimensional assessment of ED symptoms.
Thus, we include both measures to allow for a more comprehen-
sive overview of ED symptoms and to gain insight into the
replicability of networks.
We hypothesized that symptoms that were central in past studies
using NA (e.g., overvaluation of weight and shape; Levinson,
Vanzhula, Brosof, & Forbush, 2018) would remain central
regard-
less of age, as suggested by the literature (Forman & Davis,
2005;
Patrick & Stahl, 2009; Mangweth-Matzek et al., 2006). Further,
we
hypothesized that there would be a significant difference in net-
work structure across networks. Despite some common threads
across EDs, specific connections between symptoms are likely
to
differ across developmental stages, given what the literature has
described in terms of differences in symptom severity and treat-
ment effectiveness (Hudson & Pope, 2018; Jenkins & Price,
2018;
Peat et al., 2008; Forman & Davis, 2005). For example,
although
fear of weight gain may remain central across diverse ED
presen-
tations, the connection between fear of weight gain and binge
eating may become stronger over time, consistent with the Habit
Formation Theory (Walsh, 2013). This change would result in
differences in network structure, which has implications for im-
plementing effective treatments across age groups.

Additionally,
we predict that the global strength would increase for networks
with older participants compared to younger participants,
reflec-
tive of Habit Formation Theory, indicating increased severity
across developmental stages.
Method
Participants
Participants were Recovery Record users (N � 29,902; N �
32,219), a smartphone application that is based on cognitive–
behavioral treatment for EDs (Tregarthen, Lock, & Darcy,
2015).
Participants provided consent for data to be used for research
purposes when they agreed to the “Terms and Conditions” in the
initial application setup. Participants who completed the EPSI
(n �
29,902) were 11 to 85 years old (M � 26.23, SD � 10.46), and
94.0% identified as female. These participants reported their av-
erage length of ED was 9.71 years (SD � 9.72, range � 0 – 65
years). Recovery Record allows users to connect their account
with
a clinician in order to share information and inform treatment
planning. In our sample, 34.5% of participants had accounts
con-
nected with a treatment provider and had an official diagnosis
of
an ED based on clinician-report.
Participants who completed the EDE-Q (n � 32,219) were 11 to
79 years old (M � 23.43, SD � 8.89), and 96.5% identified as
female. Average length of ED was 7.60 years (SD � 8.23, range
�

0 – 60 years). In the present sample, 8.8% of participants had
accounts connected with a treatment provider and had an
official
diagnosis of an ED based on clinician-report. See Table 1 for
Table 1
Demographic Breakdown
Demographic
characteristic
Early adolescence
n (%)
Late adolescence
n (%)
Young adult
n (%)
Early-middle adult
n (%)
Middle-late adult
n (%)
EDE-Q 1523 (100) 9838 (100) 11709 (100) 7955 (100) 1194
(100)
Gender
Female 1468 (96.4) 9498 (96.5) 11310 (96.6) 7671 (96.4) 1131
(94.7)
Male 42 (2.8) 248 (2.5) 288 (2.9) 228 (2.9) 56 (4.7)
Missing 13 (.9) 92 (.9) 111 (.7) 56 (.7) 7 (.6)
Diagnosis

AN 13 (.9) 85 (.9) 159 (1.4) 133 (1.7) 19 (1.6)
BN 2 (.1) 37 (.4) 99 (.8) 104 (1.3) 12 (1.0)
BED 4 (.3) 12 (.1) 49 (.4) 104 (1.3) 55 (4.6)
Other 3 (.2) 42 (.4) 93 (.8) 102 (1.3) 18 (1.5)
Missing 1501 (98.6) 9662 (98.2) 11309 (96.6) 7522 (94.6) 1090
(91.3)
Duration of illness (M[SD]) 1.71 (1.71) 2.92 (2.27) 5.82 (3.96)
13.86 (8.37) 29.00 (14.60)
EPSI 1028 (100) 6171 (100) 10701 (100) 9929 (100) 2073 (100)
Gender
Female 959 (93.3) 5786 (93.8) 10108 (94.5) 9412 (94.8) 1857
(89.6)
Male 46 (4.5) 228 (3.7) 381 (3.6) 438 (4.4) 201 (9.7)
Missing 23 (2.2) 157 (2.5) 212 (2.0) 79 (.8) 15 (.7)
Diagnosis
AN 152 (14.8) 796 (12.9) 1456 (13.6) 995 (10.0) 172 (8.3)
BN 30 (2.9) 307 (5.0) 870 (8.1) 825 (8.3) 81 (3.9)
BED 31 (3.0) 165 (2.7) 514 (4.8) 1144 (11.5) 527 (25.4)
Other 62 (6.0) 354 (5.7) 795 (7.4) 830 (8.4) 222 (10.7)
Missing 753 (73.2) 4549 (73.7) 7066 (66.0) 6134 (61.8) 1071
(51.7)
Duration of illness (M[SD]) 2.06 (2.11) 3.19 (2.44) 6.05 (4.12)
14.54 (8.58) 29.12 (15.20)
Note. EDE-Q � Eating Disorder Examination Questionnaire;
EPSI � Eating Pathology Symptoms Inventory; AN � anorexia
nervosa; BN � bulimia
nervosa; BED � binge eating disorder.
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br
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y.
179EATING DISORDER AGE NETWORKS
participants’ gender, ED diagnoses, and duration of illness
across
developmental categories.
Measures
EPSI. The EPSI is a 45-item multidimensional measure de-
signed to assess ED symptoms. The EPSI has eight scales corre-
sponding to unique facets of eating pathology: Body
Dissatisfac-
tion (i.e., satisfaction with body shape and body parts; e.g.,
hips,
thighs), Binge Eating (i.e., tendency to overeat or eat
mindlessly),
Cognitive Restraint (i.e., attempting to restrict eating, whether
successful or not), Excessive Exercise (i.e., intense or
compulsive
exercise), Restricting (i.e., efforts to avoid or reduce eating),
Purging (i.e., self-induced vomiting and laxative/diuretic use),
Muscle Building (i.e., cognitions and behaviors [supplement
use]
related to increasing muscularity), and Negative Attitudes
Toward
Obesity (i.e., negative judgment of individuals who are over-

weight/obese). Between 32.6% and 73.6% of our sample scored
above EPSI subscale means in an ED treatment sample (Forbush
et
al., 2013). Two scales of the EPSI, Negative Attitudes Toward
Obesity and Muscle Building, were not included in the
Recovery
Record app; thus, these items were not included in the network.
The EPSI has excellent convergent and discriminant validity, as
well as excellent test-retest reliability (Forbush et al., 2013).
The
internal consistency of all items included in the EPSI network
was
adequate for the current sample (� � .73).
EDE-Q. The EDE-Q version 6.0 is a 28-item self-report ques-
tionnaire designed to assess ED behaviors and thoughts. This
version of the EDE-Q has four scales: Eating Concern (i.e.,
inter-
fering thoughts about food, eating, or calories), Shape Concern
(i.e., interfering thoughts about shape), Weight Concern (i.e.,
in-
terfering thoughts about weight), and Restraint (i.e., attempts to
reduce food intake; e.g., skipping meals, food rules). The mean
EDEQ global score in our sample is 4.17 (SD � 1.10), and
63.3%
(n � 20,390) of our sample scored above the recommended
clinical cutoff (a score of 4.0 or higher) for EDs (Fairburn,
Wilson,
& Schleimer, 1993). One EDE-Q item (15) was excluded
because
it measures the same symptom (binge eating) as the previous
question. Networks should not include two questions targeting
the
same symptom because it may artificially inflate centrality,
poten-
tially leading to false interpretation of that symptom as central

(Fried & Cramer, 2017). The EDE-Q has demonstrated excellent
test-retest reliability and internal consistency (Luce &
Crowther,
1999) and good criterion and concurrent validity (Mond, Hay,
Rodgers, Owen, & Beumont, 2004). The internal consistency of
all
items included in the EDE-Q network was good for the current
sample (� � .86).
Procedure
Participants used the Recovery Record application to self-
monitor ED cognitions and behaviors. The application
encourages
monthly completion of the EDE-Q and the EPSI. The present
study
used data from the initial completion of EDE-Q and EPSI by
participants using the mobile application.
Participant data were categorized into five developmental stag-
es: early adolescence (11–14), late adolescence (15–18), young
adulthood (19 –25), early-middle adulthood (26 – 45), and
middle-
late adulthood (46�). Our ranges may not fully distinguish be-
tween all stages of development because we had few
participants
above the age of 45 (n � 1,194 for EPSI, n � 2,073 for EDE-Q)
relative to the entire sample, so we used 45 as a cutoff for
middle-late adulthood in order to ensure a large sample size for
the
networks. Using younger age ranges is not uncommon for
clinical
studies on EDs due to difficulty recruiting older adults with
EDs
(Forman & Davis, 2005; Jenkins & Price, 2018).

Glasso networks using the EDE-Q and EPSI were estimated at
each developmental stage using the “estimateNetwork” function
in
the bootnet package in R (Epskamp, Maris, Waldorp, & Bors-
boom, 2018). The Glasso function estimates partial correlations
between nodes, meaning each correlation is unique, accounting
for
all other symptoms in the network while minimizing spurious
relationships. We first created networks using the default
setting
(cor_auto), which uses polychoric correlations. However,
because
some networks did not have adequate stability, we estimated the
networks again using Spearman correlations to obtain stable
net-
works, as suggested by Epskamp and Fried (2018). Stability
esti-
mates were calculated using the bootnet package in R (Epskamp
et
al., 2018).
Three indices of centrality were calculated using the “centrali-
typlot” function in the qgraph package in R: strength (i.e., the
sum
of the absolute value of all of a node’s edges), closeness (i.e.,
degree of direct connections to other nodes), and betweenness
(i.e.,
degree to which a node falls on the path between other nodes;
Epskamp, Cramer, Waldorp, Schmittmann, & Borsboom, 2012).
We interpret only strength centrality because it was the most
stable, as has been done in prior NA investigations (e.g.,
DuBois
et al., 2017; Epskamp et al., 2012). Centrality difference tests
were
conducted using the bootnet package in R (Epskamp et al.,

2018)
to determine if central symptoms were significantly more
central
than other symptoms. We included three to six central
symptoms
for each network based on the network centrality difference
test.
The number of symptoms included per network is based on
sharp
observable decreases in centrality differences among top symp-
toms that were used as cutoffs for inclusion. We did not use a
standard cutoff value across networks due to internetwork vari-
ability.
Differences between networks across developmental stages
were identified using the NetworkComparisonTest package in R
(van Borkulo et al., 2015). Three metrics were utilized to
analyze
network differences: network invariance test (M; i.e.,
significant
differences in the maximum edge strength in the networks),
edge
invariance test (E; i.e., significant differences between specific
edges in the networks), and global strength invariance test (GSI;
i.e., significant differences in the sum of the edge strengths; van
Borkulo et al., 2015). Edge invariance was calculated for
networks
with significant network invariance in order to quantify the
nature
of these structural differences. Global strength is a particularly
useful measure, as it may be related to symptom severity (van
Borkulo et al., 2015).
A one-way ANOVA was conducted across developmental
stages for both the EDE-Q and EPSI to investigate whether sig-
nificant differences in symptom severity across groups were re-

lated to global strength across networks, as has been theorized
(van
Borkulo et al., 2015). We conducted these analyses using the
EDE-Q global score, as factor validity is strongest for the
global
index rather than the four subscales (Aardoom, Dingemans,
Sloft
Op’t Landt, & Van Furth, 2012) and six EPSI subscales, as the
T
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EPSI was designed as a multidimensional measure of eating pa-
thology, rather than a global subscale of severity (Forbush et
al.,
2013). A post hoc Bonferroni correction was used for multiple
comparisons. The cutoff value after this correction is p � .007.
Results
Networks and Stability
See Figure 1 for EPSI networks and Figure 2 for EDE-Q
networks. Table 2 includes descriptions of each of the EPSI and

EDE-Q items. Stability for strength was excellent (strength �
.75)
for all the EPSI and EDE-Q networks (Epskamp, Borsboom, &
Fried, 2018).
Central Symptoms
EPSI. See Figure 3 for the strength centrality of all symptoms
in the EPSI networks. All central symptoms were significantly
more central than other symptoms in the network at p � .05.
Overeating and feeling full after eating a small amount of food
emerged as central symptoms across every developmental stage.
Avoiding high calorie foods and planning days around exercise
are
central symptoms in late adolescence, young adulthood, early-
middle adulthood, and middle-late adulthood. Fasting is a
central
symptom in early adolescence, late adolescence, young
adulthood,
and early-middle adulthood. Stuffing oneself to the point of
feeling
sick is a central symptom in young adulthood, early-middle
adult-
hood, and middle-late adulthood. The most central symptoms in
the EPSI networks are described in Table 3.
EDE-Q. See Figure 4 for the strength centrality of all symp-
toms in the EDE-Q networks. All central symptoms were signif-
icantly more central than other symptoms in the network at
p � .05. Desire for an empty stomach emerged as a central
symptom across every developmental stage. Concentration prob-
lems due to weight and shape is a central symptom in early
adolescence, late adolescence, young adulthood, and early-
middle

A. Early Adolescence
B. Late Adolescence C. Young Adulthood
D. Early-middle Adulthood E. Middle-late Adulthood
clothesfit
unhealthyfood
nothungry
eatlittle
exercisedaily
supriseeat
exercisehard
snacking
fulleasy thinkdiuretics
outfits
thinklaxatives
dietteas
dietpills
dislikebody
full
countcals

planexercise
butt thighs
shapediff
vomit
noticeate
strenexercise
fullsmall
hips
eatmore
resist
stuffed
avoidhighcal
exerciseexhaust
diureticsuse
fast
autopilot
overeat
clothesfit

unhealthyfood
nothungry
eatlittle
exercisedaily
supriseeat
exercisehard
snacking
fulleasy
thinkdiuretics
outfits
thinklaxatives
dietteas
dietpills
dislikebody
full
countcals
planexercise
butt

thighs
shapediff
vomit
noticeate
strenexercise
fullsmall
hips
eatmore
resist
stuffed
avoidhighcal
exerciseexhaust
diureticsuse
fast
autopilot
overeat
clothesfit
unhealthyfood

nothungry
eatlittle
exercisedaily
supriseeat
exercisehard
snacking
fulleasy
thinkdiuretics
outfits
thinklaxatives
dietteas
dietpills
dislikebody
full
countcals
planexercise
butt
thighs
shapediff

vomit
noticeate
strenexercise
fullsmall
hips
eatmore
resist
stuffed
avoidhighcal
exerciseexhaust
diureticsuse
fast
autopilot
overeat
clothesfit
unhealthyfood
nothungry
eatlittle

exercisedaily
supriseeat
exercisehard
snacking
fulleasy
thinkdiuretics
outfits
thinklaxatives
dietteas
dietpills
dislikebody
full
countcals
planexercise
butt
thighs
shapediff
vomit
noticeate

strenexercise
fullsmall
hips
eatmore
resist
stuffed
avoidhighcal
exerciseexhaust
diureticsuse
fast
autopilot
overeat
clothesfit
unhealthyfood
nothungry
eatlittle
exercisedaily
supriseeat

exercisehard
snacking
fulleasy
thinkdiuretics
outfits
thinklaxatives
dietteas
dietpills
dislikebody
full
countcals
planexercise
butt
thighs
shapediff
vomit
noticeate
strenexercise
fullsmall

hips
eatmore
resist
stuffed
avoidhighcal
exerciseexhaust
diureticsuse
fast
autopilot
overeat
Figure 1. EPSI networks for (A) early adolescence (11–14), (B)
late adolescence (15–18), (C) young adulthood
(19 –25), (D) early-middle adulthood (26 – 45), and (E) middle-
late adulthood (46�). Blue (solid) edges
represent positive partial correlations. Red (dashed) lines
represent negative partial correlations. Line thickness
represents the strength of the partial correlation. See Table 2 for
EPSI items corresponding to each node. See the
online article for the color version of this figure.
T
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adulthood. Feeling dissatisfied about one’s weight is a central
symptom in early adolescence, young adulthood, early-middle
adult-
hood, and middle-late adulthood. Overeating is a central
symptom in
late adolescence, young adulthood, early-middle adulthood, and
middle-late adulthood. Desire to lose weight is a central
symptom in
early and late adolescence. Judgment of self due to shape is a
central
symptom in early adolescence. Binge eating is a central
symptom in
young adulthood. Dissatisfaction about one’s shape is a central
symp-
tom in middle-late adulthood. The most central symptoms in the
EDE-Q networks are described in Table 4.
EPSI networks. The network invariance test indicated that the
early adolescence network was significantly different than late
ado-
lescence (M � 0.12, p � .05), young adulthood (M � 0.52, p �
.05),
early-middle adulthood (M � 0.23, p � .001), and middle-late
adult-
hood (M � 0.29, p � .001). The late adolescence network was
significantly different from early-middle adulthood (M � 0.17,
p �
.001) and middle-late adulthood (M � 0.24, p � .001), but not

young
adulthood (p � .05). The young adulthood network was not
signifi-
cantly different from early-middle adulthood or middle-late
adulthood
(p � .05). The early-middle adulthood network was
significantly
different than middle-late adulthood (M � 0.10, p � .02).
The edge invariance test indicated that two edges were
significantly
different (p � .05) between early adolescence and late
adolescence,
one edge significantly differed between early adolescence and
young
adulthood, 16 edges significantly differed between early
adolescence
and early-middle adulthood, 13 edges significantly differed
between
early adolescence and middle-late adulthood, 20 edges
significantly
differed between late adolescence and early-middle adulthood,
19
edges significantly differed between late adolescence and
middle-late
adulthood, and two edges significantly differed between early-
middle
adulthood and middle-late adulthood. See online supplemental
mate-
rials for all significantly different edges and corresponding E-
values.
The Global Strength Invariance test indicated that there were no
significant differences in global strength among the EPSI
networks of
different developmental stages (p � .05).

EDE-Q. The structure of the early adolescence network was
significantly different than young adulthood (M � 0.15, p �
.001),
early-middle adulthood (M � 0.17, p � .001), and middle-late
adult-
A. Early Adolescence B. Late Adolescence C. Young Adulthood
D. Early-middle Adulthood E. Middle-late Adult Adulthood
restrict
fast
excludefood
foodrules
emptystomach
flatstomach
foodconc
wsconc
losecontrolfeargain
feelfat
desirelose
overeat
binge

vomit
laxativescompex
eatsecret
guilty
otherseeeat
weightjudge
shapejudge
weighself
weighdiss
shapediss
seeself
otherseebody
restrict
fast
excludefood
foodrules
emptystomach
flatstomach

foodconc
wsconc
losecontrol
feargain
feelfat
desirelose
overeat
binge
vomit
laxatives
compex
eatsecret
guilty
otherseeeat
weightjudge
shapejudge
weighself
weighdiss
shapediss

seeself
otherseebody
restrict
fast
excludefood
foodrules
emptystomach
flatstomach
foodconc
wsconc
losecontrol
feargain
feelfat
desirelose
overeat
binge
vomit
laxatives

compex
eatsecret
guilty
otherseeeat
weightjudge shapejudge
weighself
weighdiss
shapediss seeself
otherseebody
restrict
fast
excludefood
foodrules
emptystomach
flatstomach
foodconcwsconc
losecontrol
feargain
feelfat

desirelose
overeat
binge
vomit
laxatives
compex
eatsecret
guilty
otherseeeat
weightjudge
shapejudge
weighself
weighdiss
shapediss
seeself
otherseebody
restrict
fast

excludefood
foodrules
emptystomach
flatstomach
foodconc
wsconc
losecontrol
feargain
feelfat
desirelose
overeat
binge
vomit
laxatives
compex
eatsecret
guilty
otherseeeat
weightjudge

shapejudge
weighself
weighdiss
shapediss
seeself
otherseebody
Figure 2. EDE-Q networks for (A) early adolescence (11–14),
(B) late adolescence (15–18), (C) young
adulthood (19 –25), (D) early-middle adulthood (26 – 45), and
(E) middle-late adulthood (46�). Blue (solid)
edges represent positive partial correlations. Red (dashed) lines
represent negative partial correlations. Line
thickness represents the strength of the partial correlation. See
Table 2 for EDE-Q items corresponding to each
node. See the online article for the color version of this figure.
T
hi
s
do
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m
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Table 2
Network Node (i.e., Symptom) Abbreviations
EPSI
clothesfit Dislike how clothes fit
unhealthyfoods Attempt to exclude “unhealthy” foods
nothungry Ate when not hungry
eatlittle Told that I do not eat much
exercisedaily Felt the need to exercise nearly daily
supriseeat People would be surprised by how little I ate
exercisehard Push myself hard when exercising
snacking Snacked without realizing
fulleasy Got full easily
thinkdiuretics Considered taking diuretics
outfits Tried on different outfits because of how I looked
thinklaxatives Thought laxatives are good to lose weight
dietteas Used diet teas or cleansing teas
dietpills Used diet pills
dislikebody Dislike how my body looked
full Ate until uncomfortably full
countcals Counted calories
planexercise Planned days around exercising
butt Thought butt was too big
thighs Dislike size of thighs
shapediff Wished shape of body was different
vomit Vomited to lose weight
noticeate Did not notice how much I ate until after
strenexercise Engaged in strenuous exercise at least 5 days per
week
fullsmall Got full after eating a small amount of food
hips Dissatisfied with the size of hips
eatmore Others encouraged to eat more

resist Felt I could not resist eating food offered
stuffed Stuffed myself with food
avoidhighcal Tried to avoid foods with high calories
exerciseexhaust Exercised to exhaustion
diureticsuse Used diuretics to lose weight
fast Skipped two meals in a row
autopilot Ate on autopilot
overeat Ate a large amount of food in a short period of time
EDE-Q
restrict Tried to limit the amount of food eaten for shape or
weight concerns
fast Gone for long periods of time without eating for shape or
weight concerns
excludefood Tried to exclude foods that you like for shape or
weight concerns
foodrules Tried to follow food rules for shape or weight
concerns
emptystomac Definite desire to have an empty stomach
flatstomach Definite desire to have a flat stomach
foodconc Thinking about food, eating, or calories made it
difficult to concentrate
wsconc Thinking about shape or weight made it difficult to
concentrate
losecontrol Definite fear of losing control overeating
feargain Fear that you might gain weight
feelfat Felt fat
desirelose Strong desire to lose weight
overeat Ate an unusually large amount of food
binge Had a sense of losing control over your eating and ate an
unusually large amount of food
vomit Made yourself sick (vomit) for shape or weight concerns
laxatives Taken laxatives for shape or weight concerns
compex Exercised in a “driven” or “compulsive” way for shape
or weight concerns

eatsecret Ate in secret
guilty Felt guilty for eating due to shape or weight concerns
otherseeeat Concerned about other people seeing you eat
weightjudge Weight influenced self-judgment
shapejudge Shape influenced self-judgment
weighself Upset if had to weigh once a week
weightdiss Dissatisfied with weight
shapediss Dissatisfied with shape
seeself Discomfort seeing your own body
otherseebody Discomfort with others seeing your body
T
hi
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y.
hood (M � 0.17, p � .01), but not late adolescence. The late
adolescence network was significantly different from young
adult-
hood (M � 0.07, p � .05), early-middle adulthood (M � 0.10, p
�
.001), and middle-late adulthood (M � 0.16, p � .001). The
young
adulthood network was significantly different than middle-late
adult-
hood (M � 0.14, p � .05), but not early-middle adulthood. The

early-middle adulthood network was not significantly different
than
middle-late adulthood.
Eight edges were significantly different (p � .05) between early
adolescence and young adulthood, 20 edges significantly
differed
between early adolescence and early-middle adulthood, 23
edges
significantly differed between early adolescence and middle-
late
adulthood, 12 edges significantly differed between late adoles-
cence and young adulthood, 13 edges significantly differed be-
tween late adolescence and early-middle adulthood, 19 edges
significantly differed between late adolescence and middle-late
adulthood, and seven edges significantly differed between
young
adulthood and middle-late adulthood. See online supplemental
materials for all significantly different edges and corresponding
E-values.
Figure 3. Centrality of EPSI symptoms for the (A) early
adolescence, (B) late adolescence, (C) young
adulthood, (D) early-middle adulthood, and (E) middle-late
adulthood networks. Red (large) dots denote most
central symptoms. See Table 2 for EPSI items corresponding to
each node abbreviation. See the online article
for the color version of this figure.
Table 3
EPSI Central Symptoms
Early adolescence Late adolescence Young adulthood Early-
middle adulthood Middle-late adulthood

Overeat (1.88) Overeat (1.68) Overeat (1.72) Overeat (1.58)
Overeat (1.98)
Fullsmall (2.35) Fullsmall (1.45) Fullsmall (1.88) Fullsmall
(1.92) Fullsmall (1.82)
Avoidhighcal (1.54) Avoidhighcal (1.44) Avoidhighcal (1.72)
Avoidhighcal (1.47)
Planexercise (1.29) Planexercise (1.57) Planexercise (1.69)
Planexercise (1.30)
Fast (1.75) Fast (2.53) Fast (2.19) Fast (1.27)
Stuffed (1.44) Stuffed (1.89) Stuffed (1.87)
Note. Standardized strength centrality coefficients included in
parentheses. All symptoms in the table were significantly more
central than over 75% of
other symptoms in the network. See Table 2 for EPSI items
corresponding to each node abbreviation.
T
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y.

The early adolescence network (global strength � 11.82) had
significantly lower global strength than middle-late adulthood
(global
strength � 12.56; GSI � 0.74, p � .05). Late adolescence
(global
strength � 12.73) had significantly lower strength than young
adult-
hood (global strength � 13.48; GSI � 0.75, p � .01) and early-
middle adulthood (global strength � 13.61; GSI � 0.89, p �
.05).
There were no other significant differences in global strength
among
the EDE-Q networks (p � .05). See Table 5 for an overview of
network differences across developmental stages.
ANOVA Across Developmental Stages
The results of the one-way ANOVAs indicated a significant
main effect of group for body dissatisfaction, F(4, 29,897) �
Figure 4. Centrality of EDE-Q symptoms for the (A) early
adolescence, (B) late adolescence, (C) young
adulthood, (D) early-middle adulthood, and (E) middle-late
adulthood networks. Red (large) dots denote most
central symptoms. See Table 2 for EDE-Q items corresponding
to each abbreviation. See the online article for
the color version of this figure.
Table 4
EDE-Q Central Symptoms
Early adolescence Late adolescence Young adulthood Early-
middle adulthood Middle-late adulthood
Emptystomach� (.98) Emptystomach�� (1.11)

Emptystomach�� (1.30) Emptystomach�� (1.72)
Emptystomach�� (1.73)
Wsconc�� (1.48) Wsconc�� (1.13) Wsconc� (1.07)
Wsconc�� (1.13)
Overeat� (1.32) Overeat�� (1.43) Overeat�� (1.56) Overeat�
(1.11)
Weightdiss� (.98) Weightdiss�� (1.13) Weightdiss�� (1.41)
Weightdiss� (1.09)
Desirelose� (.95) Desirelose� (1.05)
Shapejudge� (1.30)
Binge� (.99)
Shapediss� (1.11)
Note. Standardized strength centrality coefficients included in
parentheses.
� Symptom is significantly more central than over 50% of other
symptoms in the network. �� Symptom is significantly more
central than over 75% of
other symptoms in the network. See Table 2 for EDE-Q items
corresponding to each node abbreviation.
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10.03, cognitive restraint, F(4, 29,897) � 183.28, binge eating,
F(4, 29,897) � 183.28, purging, F(4, 29,897) � 189.43, restric-
tion, F(4, 29,897) � 700.49, excessive exercise, F(4, 29,897) �
215.31, and global ED symptoms, F(4, 32,214) � 107.64, p �
.001. Post hoc pairwise comparisons indicated that body
dissatis-
faction was highest in late adolescence, young adulthood, and
early-middle adulthood. Purging was highest in late adolescence
and young adulthood. Restriction, excessive exercise, cognitive
restraint, and global ED symptoms were highest in early adoles-
cence and significantly declined across development. Binge
eating
was lowest in early adolescence and significantly increased
across
development. See Table 6 for means and standard deviations for
these measures across each developmental stage.
Discussion
This study utilizes NA to explore ED symptoms across funda-
mental developmental stages of adolescence and adulthood in a
large sample of Recovery Record users. We hypothesized that
central symptoms would be consistent across developmental
stages
but that the individual connections or pathways (edges) between
symptoms may differ in strength. In support of our hypothesis,
several symptoms emerged as central across all or most
develop-
mental stages. In partial support of our second hypothesis, there
were significant differences in the network structure for all ED
networks across both measures, but only significant differences
in
global strength among some of the EDE-Q networks. However,
the

results of the ANOVA contradicted these findings, as for most
ED
symptoms, excluding binge eating, symptom severity was
highest
for adolescence and young adulthood and declined later in
adult-
hood, suggesting that the strength of the connections (but not
the
severity of symptoms) may increase across development.
Overall,
these network comparison results suggest that although many of
the central symptoms remain consistent across developmental
stages, the connections among symptoms significantly differ.
Central Symptoms
Several symptoms, including overeating and cognitions related
to fullness, were central symptoms at every developmental
stage.
Several additional symptoms were central in four of the five
networks, including symptoms related to food avoidance,
overeat-
ing, and overvaluation of weight and shape. The high proportion
of
symptoms that were central across most or all developmental
stages suggests that these ED symptoms may be central
regardless
of developmental stage. Thus, these symptoms may represent
important targets for intervention for individuals with EDs
across
all developmental stages. Some symptoms were unique to one or
two developmental stages, including additional symptoms
related
to overvaluation of weight and shape (e.g., dissatisfaction about
one’s shape; desire to lose weight). These symptoms may

represent
unique targets of intervention for the treatment of EDs in
specific
age populations.
Additionally, many of the central symptoms represent symp-
toms related to overvaluation of weight and shape, including
concentration problems due to weight and shape, dissatisfaction
Table 5
Network Comparison Tests
Early
adolescence Late adolescence Young adulthood
Early-middle
adulthood
Middle-late
adulthood
Developmental stage M GSI M GSI M GSI M GSI M GSI
Early adolescence — — .11 .92 .15� 1.67 .17� 1.80 .18� .75�
Late adolescence .12� .81 — — .07� .75� .10� .88� .17� .17
Young adulthood .52� 2.88 .52 2.07 — — .06 .13 .14� .92
Early-middle adulthood .23� 1.60 .17� .78 .49 1.29 — — .12
1.05
Middle-late adulthood .29� .33 .24� .48 .51 2.55 .10� 1.26 —
—
Note. Bottom left (not bold) values represent network
comparisons among EPSI networks. Upper right (bold) values
represent network comparisons
among EDE-Q networks. M � network invariance test statistic;

GSI � global strength invariance test statistic.
� p � .05.
Table 6
Means and Standard Deviations of Study Measures Across
Developmental Stages
Outcome
Early
adolescence
Late
adolescence
Young
adulthood
Early-middle
adulthood
Middle-late
adulthood
EDE-Q global 4.32 (1.07) 4.29 (1.07) 4.18 (1.11) 4.05 (1.10)
3.73 (1.14)
EPSI body dissatisfaction 20.70 (6.29) 21.36 (5.67) 21.19 (5.88)
21.36 (6.05) 20.59 (6.40)
EPSI cognitive restraint 8.26 (3.30) 8.11 (3.14) 7.84 (3.09) 7.20
(3.12) 6.44 (2.90)
EPSI binge eating 12.39 (9.04) 15.62 (9.37) 16.71 (9.37) 17.95
(9.02) 17.58 (8.16)
EPSI purging 5.63 (5.94) 6.58 (5.92) 6.10 (5.88) 5.08 (5.49)
3.08 (4.34)
EPSI restriction 13.98 (6.25) 12.62 (6.37) 10.75 (6.49) 8.22
(6.49) 6.91 (5.69)
EPSI excessive exercise 9.71 (5.81) 9.08 (5.65) 8.63 (5.82) 7.44

(5.67) 5.71 (4.82)
Note. Values reported as M (SD). Italicized values were not
significantly different (p � .007) than at least one
other developmental stage. Bolded values denote stages
significantly different than three or more other
developmental stages.
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about one’s weight, dissatisfaction about one’s shape, judgment
about one’s shape, and desire to lose weight. This finding is
consistent with past conceptualizations of eating pathology
using
NA (DuBois et al., 2017; Forrest et al., 2018; Levinson et al.,
2017; Wang et al., 2018) and supports the theory that overvalu-
ation of weight and shape are core ED symptoms (Fairburn,
2008).
A few symptoms that were highly central, including overeating
and food avoidance, had not previously emerged as central in
past
studies. Thus, more research should test if these results
replicate in

other samples.
Differences Across Development
Despite the number of central symptoms that remained similar
across developmental stages, the network comparison tests re-
vealed significant differences in how symptoms were related
across networks. The adolescent networks for both the EDE-Q
and
EPSI were significantly different from all the adulthood
networks,
suggesting that symptom relationships during adolescence
signif-
icantly vary from adulthood. Additionally, the networks
represent-
ing stages of adulthood were significantly different from each
other for both measures, indicating that symptom relationships
also
are highly variable across the developmental stages of
adulthood.
The edge invariance tests supported these findings, as there
were
many significantly different edges across networks. All signifi-
cantly different edges are included in online supplemental mate-
rials, as these edges represent pathways that may be differently
important across developmental stages and provide insight into
the
clinical significance of network structure differences.
Overall, these findings suggest that important illness pathways
may change across development, indicating that clinicians
should
expect fluctuations in the relationships among ED symptoms
that
occur with time and life experiences and that these changes may
alter intervention targets. For example, fear of weight gain may

be
a common driving symptom across stages of development, but it
may manifest differently over time (e.g., restriction may be
more
prevalent early on, but later shifts to judgment fears and
isolation).
Therefore, interventions may need to be tailored to address such
changes.
In terms of global strength, only the EDE-Q networks exhibited
significant differences, with trends indicating global strength
in-
creases for networks with older participants compared to
younger
participants. Higher global strength is theorized to be
representa-
tive of greater severity (Pe et al., 2015; van Borkulo et al.,
2015).
However, comparisons in EDE-Q global scores and EPSI
subscale
scores across stages of development indicated that symptoms
(based on total symptom scores) were more severe (i.e., higher)
in
the adolescent and young adult groups for all symptoms except
binge eating. Bos et al. (2018) also found increased network
connectivity corresponding with decreased severity, contrary to
findings by van Borkulo et al. and Pe et al. As such, global
strength
may not necessarily correspond to greater overall severity of
symptoms, but instead tighter connections between symptoms.
The
high interconnectivity of symptoms in the later developmental
stages may be attributed to the longer average duration of
illness of
older individuals with EDs in our sample, which would likely
indicate stronger, more reinforced pathways among symptoms,

as
suggested by Habit Formation Theory (Walsh, 2013).
Contrary to this finding, no significant differences in the global
strength emerged across EPSI networks. This result was surpris-
ing, as the network comparison test detects even small
differences.
However, group comparisons indicated that some symptoms
(e.g.,
binge eating) were stronger for older ages and other symptoms
(e.g., restriction) were stronger in younger ages, so these
opposing
trends potentially “cancelled” each other out in the summation
of
strength across networks. It is also possible that this is an
artifact
of different measurement techniques that should be investigated
in
future research. Given the conflicting findings in the literature,
future research should investigate how symptom
interconnectivity
(vs. symptom severity) may contribute to course of illness and
outcomes.
Limitations
This study examines ED symptoms across developmental stages
in the largest clinical ED sample used for NA to date, providing
important insight into how ED symptomology may change
across
development. However, this study has limitations. One
limitation
is the missing diagnostic information in the data sets, which
prevented us from using diagnosis-matched samples for each de-
velopmental stage. Recovery record only provides participant
di-

agnostic information when the application is connected with a
clinician, which was only applicable for 27.0 –48.7% of the
EPSI
participants and 1.4 –9.7% of the EDE-Q participants. Among
the
participants that did have ED diagnoses, there were significant
differences in diagnoses across developmental stages. For exam-
ple, in the EPSI network, the early adolescence group was
primar-
ily comprised of anorexia nervosa (55.3% of individuals with a
clinician-provided diagnosis), and the middle-late adulthood
group
was primarily comprised of binge eating disorder (52.6% of
indi-
viduals with a clinician-provided diagnosis). Due to these
differ-
ences, it is possible that some of the network differences we
found
may be attributed to diagnostic differences as opposed to devel-
opmental stage. Future research should use diagnosis-matched
samples to test if our findings replicate. However, despite
differ-
ences in diagnoses across networks, many symptoms remained
central across all networks. This finding supports the idea that
despite differential diagnoses, EDs are transdiagnostic
phenomena
(Cooper & Dalle Grave, 2017; Lampard, Tasca, Balfour, & Bis-
sada, 2013). Additionally, the ubiquity of core symptoms across
diagnoses could contribute to the high diagnostic crossover in
EDs
(Castellini et al., 2011; Fichter & Quadflieg, 2007).
Further, because of the low prevalence of individuals above 46
that used the Recovery Record application, the middle-late
adults
network spans several decades (46 –79 years of age). Thus, this

study is unable to contribute to parsing out ED symptom differ-
ences across this large developmental category. Additional re-
search should be conducted in middle and older adults, focused
on
identifying developmental differences in ED symptoms. Further,
given that this is the first investigation of EDs across
development
from early adolescence to late adulthood, there are no
established
guidelines for distinct developmental periods in this population.
Our categories are based on non-ED-specific developmental the-
ories. Future research may refine these periods to ensure they
reflect distinct stages of development for this population. Addi-
tionally, data were self-reported from the Recovery Record app
and limited by self-awareness and self-report biases. Two sub-
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scales of the EPSI, Muscle Building and Negative Attitudes To-
ward Obesity, were not measured in the Recovery Record app,
so

it is unknown how these constructs might vary across develop-
mental stages.
One primary concern with NA is that there is currently no
empirical method for selecting items for inclusion. As depicted
by
differences in central symptoms and connections across the
EPSI
and EDE-Q, item inclusion can critically impact interpretation
of
the network. For example, the EPSI, comprised of more
behavioral
ED symptoms, had more behavioral symptoms emerge as
central,
as compared to the EDE-Q. Future research should develop and
validate empirical methods of selecting items for a network and
developing measures designed to perform well in NA.
Researchers
have also expressed concerns with sole reliance on centrality
indices to determine central symptoms (see Bringmann &
Eronen,
2018; Hallquist, Wright, & Molenaar, 2019). However, in
general,
many researchers have suggested that central symptoms may
serve
as useful targets for future interventions (McNally, 2016; Rode-
baugh et al., 2018), and growing empirical data shows that
central
symptoms predict important outcomes, specifically in EDs
(Elliott
et al., 2018; Olatunji et al., 2018). Finally, these networks were
conducted at the group level, so findings indicate trends across
developmental stages and may not be representative of symptom
relationships for an individual over time.
Implications and Future Research

This study examines ED symptoms across developmental stages
in a large clinical ED sample, which has broad implications for
future research and treatment development for individuals with
EDs. Significant network differences across stages suggest that
ED
research should be inclusive of individuals from all ages, espe-
cially older populations, who are typically left out of studies on
treatment development (Forman & Davis, 2005). Additionally,
differences across stages of development may impact treatment
needs for subpopulations of EDs. For example, as symptom con-
nections change in older populations, treatments may need to be
adapted to focus on the strongest connections in order to disrupt
the most salient illness pathways. Treatments for older
individuals
with EDs must also take into consideration the increased
connec-
tivity of symptoms, which may be contributing to the worse
treatment outcomes for this population (Noordenbos et al.,
2002;
Norring & Sohlberg, 1993).
In addition, symptoms that are central to eating pathology
across
developmental stages, including items related to overeating,
feel-
ings of fullness, food avoidance, and overvaluation of weight
and
shape, are hypothesized to be good targets for intervention for
individuals of all ages with EDs. Interventions that target these
symptoms, including cognitive– behavioral and dialectical–
behavior therapy interventions, such as thought challenging, ex-
posure therapy, distress tolerance, and behavior chaining, are
widely used and are among the most effective and empirically
supported treatments for EDs (Fairburn, 2008; Linehan & Chen,
2005). Feelings of fullness can also be addressed using

interocep-
tive exposures, which little research has investigated in EDs
(Boettcher, Brake, & Barlow, 2016). Central symptoms that are
unique to specific developmental stages may also be suggested
targets for treatment for individuals with EDs that fall within
that
stage. However, it should be noted that group-level trends
across
development might not be reflective of the most important treat-
ment targets for an individual. We hope that future research will
explore similar questions within-persons. Overall, this study
uti-
lizes an emerging statistical approach to explore ED symptom
differences across the life span, which future research will need
to
continue to address in order to develop more effective interven-
tions for individuals of all ages who struggle with an ED.
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Received February 11, 2019
Revision received August 16, 2019
Accepted August 19, 2019 �
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http://dx.doi.org/10.1177/0272431600020002002Eating
Disorder Core Symptoms and Symptom Pathways Across
Developmental Stages: A Network
AnalysisMethodParticipantsMeasuresEPSIEDE-
QProcedureResultsNetworks and StabilityCentral
SymptomsEPSIEDE-QEPSI networksEDE-QANOVA Across
Developmental StagesDiscussionCentral SymptomsDifferences
Across DevelopmentLimitationsImplications and Future
ResearchReferences
© 2016 Norris et al. This work is published and licensed by
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R e v i e w
open access to scientific and medical research
Open Access Full Text Article
http://dx.doi.org/10.2147/NDT.S82538
Update on eating disorders: current perspectives
on avoidant/restrictive food intake disorder in
children and youth
Mark L Norris1
wendy J Spettigue2
Debra K Katzman3

1Division of Adolescent Medicine,
Department of Pediatrics, Children’s
Hospital of eastern Ontario,
University of Ottawa, Ottawa, ON,
Canada; 2Department of Psychiatry,
Children’s Hospital of eastern
Ontario, University of Ottawa,
Ottawa, ON, Canada; 3Division of
Adolescent Medicine, Department of
Pediatrics, Hospital for Sick Children,
University of Toronto, Toronto, ON,
Canada
Abstract: Avoidant/restrictive food intake disorder (ARFID) is a
new eating disorder diagnosis
that was introduced in the Diagnostic and Statistical Manual of
Mental Disorders (DSM) fifth
edition. The fourth edition of the DSM had failed to adequately
capture a cohort of children,
adolescents, and adults who are unable to meet appropriate
nutritional and/or energy needs,
for reasons other than drive for thinness, leading to significant
medical and/or psychological
sequelae. With the introduction of ARFID, researchers are now
starting to better understand
the presentation, clinical characteristics, and complexities of
this disorder. This article outlines
the diagnostic criteria for ARFID with specific focus on
children and youth. A case example of

a patient with ARFID, factors that differentiate ARFID from
picky eating, and the estimated
prevalence in pediatric populations are discussed, as well as
clinical and treatment challenges
that impact health care providers providing treatment for
patients.
Keywords: avoidant/restrictive food intake disorder, ARFID,
eating disorder, picky eating,
prevalence, treatment
Introduction
Avoidant/restrictive food intake disorder, or ARFID, was
introduced in the Feeding
and Eating Disorders (EDs) section of the Diagnostic and
Statistical Manual of Mental
Disorders (DSM) fifth edition (DSM-5).1 The body of evidence
on the characteristics,
course, and outcome of children with “feeding disorders of
infancy or early childhood”
as defined in the fourth edition of the DSM (DSM-IV) is
limited. This DSM-IV diagnosis
relied on the presence of weight loss or failure to gain weight,
and failed to account for
circumstances that might allow a patient to stay adequately
nourished as a result of the
use of enteral feedings or oral nutritional supplements.2

Further, this diagnostic category
was restricted to children less than 6 years, and put a substantial
emphasis on negative or
maladaptive interactions between the child and caregiver. In the
years leading up to the
DSM-5, it became apparent that there was a group of children,
adolescents, and young
adults who displayed feeding issues that did not fit into the
diagnostic categories of
anorexia nervosa (AN) or bulimia nervosa (BN). These patients
were often given varying
diagnoses including the residual diagnosis of ED not otherwise
specified. Further, this
patient population often required the expertise of a
multidisciplinary treatment team to
provide nutritional rehabilitation, medical management, and
psychological treatment.
The DSM-5 Eating Disorder Working Group recognized that
this subset of individu-
als included children, adolescents, and adults and presented
with histories of weight
loss in the context of substantial restriction and often
pronounced physiological and/or
psy chosocial distress. These patients were distinct from those

with AN as they lacked
Correspondence: Mark L Norris
Division of Adolescent Medicine,
Department of Pediatrics, Children’s
Hospital of eastern Ontario, University
of Ottawa, 401 Smyth Road, Ottawa,
ON K1H 8L1, Canada
Tel +1 613 737 7600
Fax +1 613 738 4878
email [email protected]
Journal name: Neuropsychiatric Disease and Treatment
Article Designation: Review
Year: 2016
Volume: 12
Running head verso: Norris et al
Running head recto: Update on eating disorders: ARFID
DOI: http://dx.doi.org/10.2147/NDT.S82538
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Norris et al
body image preoccupation, fear of weight gain, or drive for
thinness. Field studies were conducted to better describe this
group. As such, the Working Group rearticulated the diagnosis
of “EDs of infancy and early childhood” and named this new
ED ARFID. At present, the body of literature that examines
rates and presentation of ARFID in adult patients is extremely
limited. As such, this article focuses on identification and
management of pediatric patients.
What is ARFID?
ARFID was introduced in an attempt to capture a cohort of
patients who struggle with impaired and distressing eating
behaviors and symptoms and who lack weight and body
image-related concerns associated with AN and BN. The
diagnostic criteria of ARFID are outlined in the DSM-5.1
In summary, ARFID occurs in cases where patients exhibit
restrictive or avoidant eating behaviors that result in
significant weight loss, growth compromise, a reliance on

nutritional supplements to meet daily energy requirements,
nutritional deficiency (like iron deficiency anemia) or marked
interference with the patient’s psychosocial functioning.
Patients with ARFID do not fear weight gain, are not dis-
satisfied with their body weight, shape, or size and lack
any cognitions typically associated with anorexia nervosa.
ARFID cannot be diagnosed in cases where the presence of a
concurrent medical or mental health disorder can account for
the behavior observed, but may be diagnosed if the severity
of the eating disturbance exceeds that typically associated
with the medical or psychiatric condition in question.1
Research that investigates the clinical utility and applica-
bility of these diagnostic criteria is ongoing and will likely
further inform future revisions of the DSM.
Illustrative case example
Susan (the patient’s name has been changed to protect
confidentiality) is a 10-year-old girl described by parents
as always being an anxious child. Her past medical history

was notable for a history of frequent stomach pains (without
medical cause) and school refusal. Six months before being
admitted to hospital, the patient developed recurrent viral
gastroenteritis separated by 1 week’s duration. The patient
believed that the recurrence of symptoms was triggered by the
resumption of eating, and complained of increased nausea,
vomiting, and abdominal cramps whenever she ate. As a
result, over the next few months she progressively ate less
and lost weight. She was assessed and tested for a variety
of medical illnesses (ie, food allergy, celiac disease, thyroid
dysfunction, etc), but no pathology was identified. She lacked
body image preoccupation, fear of weight gain, or drive for
thinness. Her parents began to progressively eliminate foods
that could potentially exacerbate her symptoms (ie, foods
with gluten, dairy products) but with limited effect. She was
eventually admitted to a local tertiary-care hospital where
she underwent a gastroenterology assessment, including
endoscopy, abdominal ultrasound, extensive blood work, and

a dietitian consult. All medical testing was unremarkable and
she was subsequently discharged. The patient continued to
lose weight and was readmitted weeks later having lost 33%
of her pre-morbid body weight.
She was hospitalized under the medical team but failed to
gain weight. The hospital’s multidisciplinary ED team was
consulted and diagnosed Susan with ARFID. The diagnosis
was made based upon the fact that the patient had demon-
strated persistent failure to meet appropriate nutritional and/
or energy needs and had lost a significant amount of weight
in the preceding months. The illness was causing significant
impairment in multiple aspects of her life and could not be
explained by culturally sanctioned practices, the presence of
body image or weight concerns, or a concomitant medical
condition. The patient was started on a treatment plan that
consisted of regular family therapy, individual therapy tar-
geting her anxiety, and olanzapine at bedtime; once weight
improved, her anxiety was also treated with a selective

serotonin reuptake inhibitor (fluoxetine).
The family therapist worked to raise parents’ anxiety
about the seriousness of the illness, and used this to mobi-
lize parents to take control of Susan’s nutritional intake.
Early in treatment, the patient was noted to have regular
temper tantrums, and to sob frequently during meals,
complaining of severe abdominal pain. Susan’s parents
were empowered to stay firm and compassionate and
help their daughter to eat what was expected. Slowly, the
patient began to increase the amount of food eaten, which
led to weight gain and eventually fewer temper tantrums.
Parents were able to consistently increase food intake
whenever weight gain slowed, targeting at least 1 kg of
weight gain per week. Parents were empowered to spend
as much time as possible out of hospital on passes with
Susan and to help her take nutrition at home. Two months
after starting family therapy, the patient was discharged
and at this point in treatment was consuming almost 3,000

calories per day. One month later she reached her expected
weight, at which point her nutrition was slowly tapered
to prevent further weight gain. She was far less anxious,
less labile, and no longer having temper tantrums. Her
only medication was fluoxetine for anxiety. She gained
insight and was able to identify that anxiety made her
stomach hurt. Through individual therapy, she also learned
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215
Update on eating disorders: ARFiD
some relaxation techniques. Parents were empowered to
set goals of normalizing eating, including helping Susan
to eat a variety of foods and to eat at restaurants. By the
end of therapy Susan was normal weight (having gained

11 kg), back to eating an appropriate amount of nutrition
for her age, and was much calmer and more mature with
better coping skills. She continued to be home schooled
and participated in community-based sports.
More than picky eating
As ED experts sought to better understand the clinical
characteristics associated with patients with ARFID, early
media reports stated that the DSM-5 had moved to patholo-
gize picky eating as a psychiatric condition.3 However, the
ARFID diagnosis was meant to identify only those patients
with clinically significant restrictive eating problems that
resulted in persistent failure to meet an individual’s nutri-
tional and/or energy needs, thus eliminating many patients
who are labeled as picky or fussy eaters. Part of the chal-
lenge is that there is no standardized definition for “picky
eating”. Picky eating is generally defined as occurring in
children who are normal weight but consume an inadequate
variety of foods through rejection of foods that may either

be familiar or unfamiliar to them.4 Common characteristics
include limitations in the variety of foods eaten, unwilling-
ness to try new foods (food neophobia), and aberrant eating
behaviors.4 Picky or fussy eating may include rejection of
foods of a particular texture, consistency, color, or smell.
Such food “neophobia” generally peaks between the 2nd and
6th year of life, with gradual reduction over time such that
few are affected beyond their early adult years.5–7 One of the
challenges regarding studies on picky eating relates to the
manner by which patients are identified, which in turn affects
the degree of compromise and impairment reported from
food-related behaviors. Studies have at times reported con-
flicting results depending on the specific population being
studied. This has resulted in a very heterogeneous cohort
that on one side of the spectrum has eating behaviors that
are within the expected developmental trajectory for many
normal children, and on the other side includes children
who exhibit extreme behaviors and severe impairment, more

in keeping with what would now be described as ARFID.
Given these and other challenges related to epidemiological
research, studies of picky eating have reported wide inci-
dence and prevalence ranges, depending on the specific
methodology employed. Prevalence rates for picky eating
ranges from 14% to 50% in preschool children and 7%–27%
in older children.8–13 Cardona Cano et al’s recent population
study on picky eating in children utilized two questions on
the Children’s Behaviour Checklist to establish a diagnosis
of picky eating.13 It was assumed that this would capture all
patients with picky eating, ranging from those who have a
developmentally normative course to those left with sig-
nificant impairment (and therefore possibly ARFID). At the
age of 14 months, infants identified as being picky eaters ate
less, had less variability in the amount of foods consumed,
and had lower caloric intake than non-picky eaters.13 By
the age of 4 years, picky eaters were rated as more fussy,
with higher satiety responses, greater desires to drink fluids,

less pleasure associated with eating, and overall lower food
responsiveness compared to the matched controls.13 Of all
the children sampled, 54.5% were classified as never picky
eaters, 32.3% remitting picky eaters, 4.0% late-onset picky
eaters, and 4.2% persistent picky eaters.13 Risk factors noted
among the persistent picky eater group included male sex,
low birth weight, non-Western maternal ethnicity, and lower
parental income.13 It will be interesting to compare these
results to epidemiological studies of children with ARFID.
However, in the future it will be important that researchers
undertaking nutritional and feeding studies in infants and
children use standardized methodologies and definitions to
ensure that results have applicability and can be compared
ideally across populations.
How common is ARFID?
At present, few population studies in EDs have focused or
reported on rates of ARFID; this is not surprising given that
the DSM-5 was released in 2013. As with all epidemiological
studies of EDs, there will be a number of challenges inherent

to answering this question effectively, including challenges
related to the types of studies and populations being studied
(eg, population-based studies, case registries, profiles of
patients attending clinics), the processes that are undertaken
to make diagnoses (eg, clinical interviews, survey questions),
and who develops the research questions (eg, ED experts,
psychiatrists, developmental pediatricians, dietitians). It will
also be important to better understand how eating problems
present in different age groups. There has been very little
research on rates of EDs in very young children. All of these
factors make it difficult to know just how prevalent ARFID
is in children and adolescents.
A British national surveillance study (2005–2006)
documented the incidence of early-onset EDs using modi-
fied DSM-IV criteria as 3.01 cases per 100,000 of which
19% (0.57 cases per 100,000) of those diagnosed lacked
body image issues or fear of weight gain.14 A Canadian
national surveillance study (2003–2005) suggested that

the incidence of early-onset EDs in 5- to 12-year olds was
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Norris et al
2.6 cases per 100,000 person-years.15 In this sample, 26.7%
of cases diagnosed with EDs failed to endorse fears of get-
ting fat or gaining weight, suggesting the possibility of an
ARFID diagnosis (0.69 cases per 100,000).15 Although a
lower overall incidence of EDs was observed in those aged
5–9 years as compared to those aged 10–12 years, rates
of age-specific ED behaviors were not provided. To date,
there is only one community-based study of ARFID, which
documented a point prevalence of 3.2% in a Swiss school-

based sample of 1,444 children aged 8–13 years using a
self-report measure.16
The rates of ARFID have ranged from 5% to 14% among
pediatric inpatient ED programs and as high as 22.5% in a
pediatric ED day treatment program.17–21 Studies have con-
sistently demonstrated that, compared to those with AN or
BN, ARFID patients are younger, have higher proportion of
males, and are commonly diagnosed with comorbid psychi-
atric and/or medical symptoms.17–20
Two non-ED clinical studies have also reported on
rates and characteristics of ARFID patients. In the first,
authors described clinical findings drawn from a case series
of 29 patients presenting with pediatric acute-onset neu-
ropsychiatric syndrome and discussed how features over-
lapped those outlined for ARFID. These patients showed
some similarities to those drawn from ED samples in that
affected children were young, had a high proportion of male
patients (in fact, male to female ratio was 2:1), and also

exhibited comorbid psychiatric symptoms.22 In the second
study, researchers conducted a retrospective chart review of
2,231 consecutive new referrals to gastrointestinal specialty
clinics in an attempt to understand how commonly patients
with ARFID presented. They identified ARFID in 1.5% of
all patients assessed, but noted that some features of the
diagnosis were present in an additional 2.4%, suggesting that
the criteria do not lead to over-inclusion of cases.23 In this
setting, patients were again more likely to be male (67%).23
Although each of these studies adds a different piece to
the puzzle, in combination they only offer us a very crude
guess as to the prevalence rate of ARFID; well-designed
prospective surveillance and population studies are required
to provide a better understanding of the whole picture. The
epidemiology of ARFID in the general non-clinical popula-
tion remains unknown.
Clinical and treatment challenges
Patients with ARFID present with complicated and varied
histories and risk factors that include varied medical and psy-

chiatric factors affecting nutritional intake but with no body
image concerns, making referrals to the most appropriate
health care professional or facility challenging. Patients may
be fearful and stressed, reacting to stress or trauma; reacting
to messages about “dangerous” foods or chemicals (such as
fat, sugar, or chemical additives); restricting to avoid pain,
nausea, or risk of choking or vomiting; restricting to avoid
adverse tastes or textures; or reacting to stressful emotions
at meal times. This results in a variety of case presenta-
tions. Few hospitals have dedicated feeding programs that
span the entire pediatric age group and so patients are often
referred to a myriad of clinics depending on the age and
presenting features.18 According to the authors’ experience,
many patients’ first point of contact is usually with a family
physician or general pediatrician. Other children may be
referred to an occupational therapist, dietitian, developmental
pediatrician, gastroenterologist, psychologist, psychiatrist, or
adolescent health physician. The unpredictable referral and

treatment patterns for these cases increase the likelihood that
patients will be left with a vague diagnosis and disjointed
care plan that lacks the kind of specialized coordinated care
that is required to optimize successful outcomes. Clearly,
given the potential heterogeneity of the clinical presentation
of this population, it is critical for health care providers to
have an understanding of the varied presentations of children
and adolescents with ARFID, so they can best diagnose and
develop appropriate treatment recommendations. At present
there are no evidence-based treatment recommendations for
ARFID; however, clinical experience suggests that patients’
needs might differ depending on what factors are thought
to be driving the distress and eating disturbances. As an
example, patients who present with pronounced food restric-
tion and weight loss that has occurred as a result of a fear
of choking may respond best to cognitive strategies to help
address these underlying fears. On the other hand, young
children who present with longstanding histories of poor

growth as a consequence of severe selectivity may utilize
strategies that involve a combination of psychological and
behavioral approaches.
Given the lack of empirical data on the treatment strate-
gies of ARFID, best practice treatment guidelines have not
yet been developed, which potentially increases the risk of
prolonged resource-intensive hospital stays for complex
cases. Interestingly, a recent review examined multisite ED
outcome trajectories and demonstrated that patients with
ARFID were less likely to be followed for 1-year duration,
despite the fact that ARFID patients fared no better with
weight recovery than the other ED groups. The authors sug-
gested that one possible reason for this difference may be
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217
Update on eating disorders: ARFiD
related to the fact that patients with ARFID were referred into
different therapy modalities outside that offered by the ED
team.21 Further, because the study population was younger,
it is also possible that patients were followed by providers
outside of traditional adolescent medicine clinics. Another
recently published retrospective review revealed that ARFID
patients were more likely than those with AN to be admitted
at lower weights relative to estimated healthy weight, struggle
more with weight gain in hospital, rely on enteral nutrition
during inpatient hospitalizations, have longer hospital stays,
and require rates of readmission within 1 year that mirrored
those with AN.24 Further, patients with ARFID recovered
at a rate similar to patients with AN, although 38% of the
sample continued to struggle in some meaningful way 1 year
after initial diagnosis.24

Future directions
Now that ARFID has been identified and defined, research-
ers need to focus on determining prevalence rates, outlining
risk factors, describing patient demographics and case
presentations, comparing different treatments, studying
the effectiveness of medications, and describing the course
of illness and factors that affect outcomes in this patient
population. Studies are required that better define how this
illness presents across the entire life span. Given the real-
ity that many patients with ARFID have complex presen-
tations that often require specialized treatment, it will be
important that clinicians be educated about ARFID, have
knowledge of the diagnostic characteristics of the illness,
and have an understanding of how a patient’s needs should
be managed. Currently, there are no prospective studies that
have reported outcomes on interventions that have targeted
patients with ARFID. As these evidence-based treatments
become available, it will be important to apply treatments
that optimize outcomes in hopes of minimizing morbidity

associated with the illness.
Disclosure
The authors report no conflicts of interest in this work.
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Publication Info 4: Nimber of times reviewed 2:

Evaluation and Treatment of Avoidant/Restrictive Food Intake
Disorder (ARFID) in Adolescents
Kathryn S. Brigham, MD1,2, Laurie D. Manzo, RD1,3, Kamryn
T. Eddy, Ph.D#3,4, and Jennifer
J. Thomas, Ph.D#3,4
1Division of Adolescent and Young Adult Medicine,
2Department of Pediatrics, Harvard Medical School
3Eating Disorders Clinical and Research Program,
4Department of Psychiatry, Harvard Medical School
# These authors contributed equally to this work.
Abstract
Purpose of review: Avoidant/restrictive food intake disorder
(ARFID) was added to the
psychiatric nomenclature in 2013. However, youth with ARFID
often present first to medical—
rather than psychiatric—settings, making its evaluation and
treatment relevant to pediatricians.
Recent findings: ARFID is defined by limited volume or variety
of food intake motivated by
sensory sensitivity, fear of aversive consequences, or lack of
interest in food or eating, and

associated with medical, nutritional, and/or psychosocial
impairment. It appears to be as common
as anorexia nervosa and bulimia nervosa and can occur in
individuals of all ages. ARFID is
heterogeneous in presentation and may require both medical and
psychological management.
Summary: Pediatricians should be aware of the diagnostic
criteria for ARFID and the possibility
that these patients may require medical intervention and referral
for psychological treatment. The
neurobiology underlying ARFID is unknown, and novel
treatments are currently being tested.
Keywords
Avoidant/restrictive food intake disorder; ARFID; eating
disorder; nutrition deficiencies;
cognitive-behavioral therapy; CBT-AR
Introduction
The Diagnostic and Statistical Manual of Mental Disorders 5th
Edition (DSM-5) introduced
avoidant/restrictive food intake disorder (ARFID)(1) as a
reformulation of DSM-IV feeding
disorder of infancy and early childhood (2). According to DSM-
5 criteria, to be diagnosed
with ARFID, an individual must have problematic eating habits,
which may be due to an
inability to tolerate certain sensory properties of food (e.g.,

texture, taste, appearance); a fear
Corresponding author:Kathryn S. Brigham, MD, Division of
Adolescent and Young Adult Medicine, Massachusetts General
Hospital. 55 Fruit St- Yawkey 6D, Boston, MA 02114,
[email protected]
HHS Public Access
Author manuscript
Curr Pediatr Rep. Author manuscript; available in PMC 2019
June 01.
Published in final edited form as:
Curr Pediatr Rep. 2018 June ; 6(2): 107–113.
doi:10.1007/s40124-018-0162-y.
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of potential adverse consequences of eating (e.g., choking,
vomiting); and/or an overall lack
of interest in food or eating. These alterations must be
significant enough to cause either
weight loss or failure to gain appropriate weight in growing
children; nutritional
deficiencies; dependence on nutritional supplements (e.g.,
energy-dense drinks or tube-
feeding); or psychosocial dysfunction. However, these
behaviors cannot be due to food
insecurity or culturally accepted practices; are not motivated by
fear of weight gain or
weight/shape overvaluation as in anorexia nervosa (AN) or
bulimia nervosa (BN); and are
not better explained by another medical or psychological
disorder. If there is another medical
or psychiatric disorder present, food avoidance or restriction
must be more extreme than
what would typically be expected for the co-occurring
condition. ARFID can be diagnosed
in individuals of all ages. This new diagnosis provides a
framework to categorize, evaluate,
and treat individuals who are nutritionally deficient but did not
meet criteria for previously

defined eating or feeding disorders.
What is known about ARFID?
Clinical presentation.
ARFID is a heterogeneous psychiatric disorder in which
individuals present with avoidance
of certain foods or categories of food resulting in a diet that is
limited in variety, and/or
restriction of overall intake resulting in a diet that is limited in
volume. One of the most
common rationales for avoidance and restriction in ARFID is a
heightened sensitivity to the
sensory properties of food (e.g., taste, texture, appearance,
smell). Individuals with sensory
sensitivity may experience vegetables or fruits as intensely
bitter, for example, and therefore
avoid these foods and be fearful of or disgusted by the prospect
of trying novel foods. In
turn, these individuals frequently rely on highly processed
energy-dense foods and may have
significant deficiencies in vitamins and minerals. For
individuals with sensory sensitivity,
food avoidance is often longstanding, having developed in early
childhood.
Individuals with ARFID may also exhibit food avoidance or

restriction due to a fear of
aversive consequences, such as a fear of choking, vomiting, or
gastrointestinal pain. Often
these individuals have experienced a food-related trauma and
subsequently begin avoiding
the index food to guard against another negative experience.
While the avoidance reduces
anxiety momentarily, it reinforces anxiety over time by
preventing the opportunity for new
corrective learning to occur. In our clinical experience, these
individuals often have an
anxious predisposition and their food avoidance generalizes
beyond the index food to similar
foods, then to entire food groups, and in some of the most
severe cases, to avoidance of all
solid foods. When fear of aversive consequences is primary, the
onset is often acute.
A lack of interest in food or eating is also common in
individuals with ARFID and can be
maintained by a diet that is limited in volume. Individuals with
lack of interest describe
eating as a chore and present with low homeostatic and hedonic
appetites. Due to their low-
volume intake, they often present to treatment with low weight

or a failure to thrive, and
their lack of interest is often longstanding.
In ARFID, an individual can present with one, two, or even
three of these rationales for food
avoidance or restriction, resulting in a heterogeneous diagnostic
category. Rather than
Brigham et al. Page 2
June 01.
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existing as diagnostic subtypes, our clinical impression is that
these rationales for restriction
represent dimensions on which any given patient can be high or
low (3).
Epidemiology.
In pediatric, adolescent medicine, and eating disorder clinics,
preliminary studies suggest
that, compared to patients with AN or BN, cohorts of patients
with ARFID tend to be
younger (4,5), include a greater proportion of males (4,6),
experience a longer duration of
illness before treatment presentation (4), and are more likely to
be diagnosed with a co-
occurring medical condition (5). One retrospective case control
study showed that patients
with ARFID were more likely to have an anxiety disorder but
less likely to have a mood
disorder than patients with AN or BN (4). Since ARFID is a
relatively new diagnosis, there
have only been two population-based prevalence studies. An
Australian interview-based
study of males and females ages 15 and older reported a 3-
month point prevalence of

ARFID of 0.3% in 2013 and in 2014 (7). A study of
schoolchildren ages 8–13 in
Switzerland reported a point prevalence of 3.2% measured via
self-report questionnaire (8).
These emerging data suggest that ARFID may be as common as
AN and BN. Further,
studies from North America have shown that 5–12% of patients
presenting for eating
disorder care at outpatient clinics (9–11) and 22.5–24.6% of
patients presenting to an
outpatient day program for younger adolescents with eating
disorders (12,13) meet DSM-5
criteria for ARFID.
Contributing factors.
Because ARFID is so new, its etiology is unknown. Similar to
other eating and feeding
disorders, it is probable that both biological and environmental
factors—and their interplay
—contribute to pathogenesis. We hypothesize that there may be
biological bases that
underlie sensory sensitivity, trait anxiety, and both homeostatic
and hedonic appetites, which
may increase vulnerability to ARFID (3). Environmental factors
such as family meal milieu,

availability of fruits and vegetables in the local environment,
and exposure to models of
healthy eating and/or diverse foods may also play a role.
Evaluation
Medical evaluation.
In the initial medical evaluation, the pediatrician should obtain
a careful history of the
patient’s eating habits. Patients with ARFID can have a variety
of altered eating habits,
which can include apathy, dislike, or fear of specific foods, or
of eating in general. Some
patients may present with a lifelong history of picky eating and
avoidance of particular
textures, colors, tastes, or smells and unwillingness to eat news
foods; others may have had a
more recent change in eating habits secondary to
gastrointestinal discomfort or an acute
episode of choking or vomiting experienced as traumatic (4,5).
It is crucial to query the
patient’s attitudes towards weight and body image, in order to
rule out AN, BN, or a related
eating disorder.
Patients may report symptoms attributable to acute malnutrition,

including fatigue,
dizziness, and syncope and/or more long-standing malnutrition,
such as abdominal pain,
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constipation, cold intolerance, amenorrhea, dry skin, and hair
loss (14). On exam, signs of
malnutrition can include cachexia, hypothermia, bradycardia,

orthostatic tachycardia and
hypotension, scaphoid abdomen, lanugo, and pallor (14). The
wide variety of presentations
of ARFID can lead to a wide variety of sequelae, from specific
micronutrient deficiencies
(see Table 1) to more global malnutrition, weight loss, and/or
failure to appropriately gain
weight and height as the patient progresses through childhood
and adolescence. Pre-
menarchal females may experience primary amenorrhea while
post-menarchal females may
experience secondary amenorrhea due to weight loss and
chronic malnutrition. It is
important to consider other etiologies of these presenting signs
and symptoms, including
malignancies, chronic gastrointestinal disorders (e.g. celiac
disease, inflammatory bowel
disease), endocrine disorders (e.g. hyperthyroidism, Addison’s
disease, type 1 diabetes),
infectious diseases (e.g. tuberculosis or human
immunodeficiency virus), or conditions that
hinder chewing or swallowing of boluses of food (e.g. tonsillar
hypertrophy, oromotor
dysfunction, achalasia) (15).

Most patients should have screening blood work including
complete metabolic panel,
magnesium, phosphorus, complete blood count with differential,
thyroid stimulating
hormone, erythrocyte sedimentation rate, and c-reactive protein,
as well as a urinalysis. It is
worth considering screening for celiac disease with a total
immunoglobulin A (IgA) and
tissue transglutaminase IgA, as there is a high rate of co-
occurrence of celiac disease and
AN (16). Patients with bradycardia or hemodynamic instability
should have an
electrocardiogram. A human chorionic gonadotropin (HCG)
should be checked in post-
menarchal females who present with amenorrhea; bone density
can be assessed using dual-
energy X-ray absorptiometry (DXA) in patients who have
menstruated fewer than 6 times in
the past year (17). While blood tests are useful for determining
micronutrient deficiencies,
diet history as well as family reports of intake are often just as
or more important to identify
potential deficiencies (18).

Part of the initial evaluation should include determination of a
target weight for patients who
are underweight. Target weight and body mass index (BMI) is
typically determined for
patients with restrictive eating disorders by looking at the
patient’s BMI growth charts and
trying to return the patient to his or her pre-illness trajectory
(19). Target weights can be
more difficult to determine in patients presenting with lifelong
malnutrition due to ARFID,
as these patients may have been chronically underweight. In
these situations, the pediatrician
should set a target weight that is high enough to enable the
patient to progress through
puberty appropriately and gain the height at the expected rate
for age, sex, and genetic
potential; this is assessed by looking closely at the patient’s
growth charts throughout
treatment. For those under the age of 20, the goal weight will
increase with time, given
increases in height and expected increases in BMI. Often, the
physician will need to make
the case for the importance of frank weight gain in ARFID,
rather than weight restoration

(as in other eating disorders such as AN), with the patient and
parents.
Psychological evaluation.
A clinical interview with a mental health clinician is critical to
confer diagnosis. Ideally, the
psychological evaluation would include both the patient and his
or her caregivers (e.g.,
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parents). Clinical assessment comprises review of ARFID
diagnostic criteria, recall of a
typical day of eating, assessment of foods regularly accepted
across the five basic food
groups (fruits, vegetables, protein, dairy, and grains) vs. those
that are avoided,
determination of the impact of the patient’s eating on health or
psychosocial functioning,
and evaluation of the degree of caregiver accommodation
currently in place. As the
diagnosis is new, formal diagnostic assessment tools are still
under development. The Pica
ARFID and Rumination Disorder Interview (PARDI) (20) is a
comprehensive structured
clinical interview designed to confer diagnosis and to measure
global severity and severity
across rationales for restriction. In addition, patient responses
to brief self-report screening
tools, such as the Eating Disorders in Youth Questionnaire
(EDY-Q) (21) or the Nine-Item
ARFID Screen (NIAS) (22), may provide clues to appropriate
follow-up questions at the
clinical interview.

Ascertaining the ARFID diagnosis requires differential
diagnosis from the other eating and
feeding disorders, as well as from other psychiatric diagnoses.
While ARFID is
characterized by restricted intake, which can overlap with AN,
in ARFID the restriction is
not due to fear of fatness or efforts to control weight or body
shape. ARFID is also
differentiated from garden variety picky eating, which often
develops in preschoolers but
ultimately remits without treatment. By contrast, ARFID is
more persistent, severe, and
associated with medical and psychosocial sequelae. Rather than
improving with age, the
selective eating associated with ARFID typically escalates,
becoming more entrenched
during childhood and adolescence if left untreated.
Psychiatric comorbidities including anxiety and mood disorders,
obsessive-compulsive
disorder, autism spectrum disorder, and attention deficit
hyperactivity disorder are
commonly seen in individuals with ARFID. When food
avoidance or restriction is primary

and associated with significant medical, nutritional, and/or
psychosocial compromise it
generally requires clinical attention outside of what would be
warranted in treating these
comorbid conditions alone, which can guide in determining the
threshold for an ARFID
diagnosis when comorbidity is present.
Treatment
Medical.
Treatment can range from an outpatient multidisciplinary team
treatment to inpatient
medical hospitalization (14). Because ARFID is such a new
diagnosis, there is little evidence
supporting treatment strategies and consensus guidelines have
not yet been developed (5).
Depending on the needs of the patient, an outpatient medical
team should comprise, at
minimum, a medical provider and mental health clinician, and
potentially other specialty
providers as needed, such as a dietitian, pediatric
gastroenterologist, occupational therapist,
and/or speech pathologist. Until there is further evidence to
guide practitioners, it seems

reasonable that treatment goals for ARFID be similar to goals
for other restrictive eating
disorders, including weight restoration and resumption of
menses in amenorrhoeic females
(19).
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Some patients with ARFID can become medically compromised

and require medical
hospitalization for monitoring and nutritional rehabilitation.
The Society for Adolescent
Health and Medicine has published guidelines for when an
individual with a restrictive
eating disorder should be medically hospitalized (19). In our
experience, many patients with
ARFID have been underweight for such an extended period that
they have developed a level
of homeostasis so they do not present with the same degree of
bradycardia and hypotension
as is seen in patients with AN who are actively losing weight. In
such cases, the physician
can use the patient’s weight as a guide to determine the need for
hospitalization: A medical
admission may still be necessary if the patient’s current BMI is
less than 75% of the median
BMI for sex and age. If a patient with ARFID is medically
hospitalized, he or she may
benefit from being placed on a structured refeeding protocol to
promote weight gain and
monitor for the electrolyte shifts that can be a harbinger of
refeeding syndrome. However,
given that patients with ARFID may have difficulty with both

variety and volume, it may be
necessary to rely on preferred foods to facilitate the initial
increase in volume that will be
necessary to support weight gain. One retrospective chart
review of patients medically
hospitalized showed that patients with ARFID experienced
electrolyte shifts similar to
patients with AN; compared to patients with AN, patients with
ARFID had a longer length
of stay, thought to be due to increased reliance on enteral
feeding and lower starting calorie
goals early in the admission (23).
Some of these patients require oral nutritional supplements,
nasogastric tube feedings, or
gastrostomy tube feedings to maintain adequate nutrition (1).
One study of patients
medically hospitalized for eating disorders showed that patients
with ARFID are more likely
to rely on enteral nutrition than patients with AN (23). The
patient’s current intake,
motivation for treatment, and diet limitations should be
considered when deciding whether
to use supplements or food alone. In our experience, patients
with ARFID are more likely

than those with other eating disorders (e.g., AN) to present for
initial evaluation relying on
long-term enteral feedings in an ambulatory setting, whereas
patients with other eating
disorders generally receive short-term enteral feedings in the
inpatient setting. We
hypothesize that the greater reliance on tube feeding in the
ARFID group is due to many of
these patients presenting to medical providers (e.g., pediatric
gastroenterologists) rather than
mental health clinicians, prior to the advent of ARFID as a
psychiatric diagnosis. Tube
feeding can be a life-saving treatment strategy in the setting of
acute malnutrition, but, in
most cases, should be considered a temporary measure to
support the ultimate treatment goal
of obtaining adequate nutrition through oral intake. Once
patients have gained to a healthy
weight and can take in at least some nutrition by mouth,
weaning off tube feeds is typically
done under close supervision in an inpatient (24) or day
treatment (25) setting.
For patients who are not medically compromised, the physician
should consider whether

outpatient psychotherapy is sufficient or whether referral to day
treatment or intensive
outpatient treatment eating disorder program is warranted. For
example, day treatment can
serve as a valuable source of structure and support to both
improve weight and increase
variety in eating habits. It is worth considering a higher level of
care with an eating disorder
program in patients who either have been unable to make
progress with an outpatient team
or are losing weight and may end up medically hospitalized if
changes are not made
relatively rapidly. In some patients, it can be difficult to
ascertain in a single evaluation
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whether the patient has ARFID or AN, and the close observation
of an eating disorder
program can provide diagnostic clarification. One study
demonstrated that patients with
ARFID could be successfully treated at eating disorder day
treatment programs,
demonstrating weight gain, decreased food restriction, and
decreased anxiety symptoms
(13).
There are limited studies that look at the prevalence of
nutritional deficiencies in eating
disorders and specifically in ARFID. The types and severity of
deficiencies this population
can vary greatly. Since decreased intake and elimination or
avoidance of food groups often

occur over an extended period of time, conservation and
adaptation mechanisms of
metabolism can result in laboratory values appearing normal
despite prolonged inadequate
intake (18). Supplementation or repletion of specific vitamins
and minerals should be
considered if labs or symptoms are clinically significant or if
diet remains limited. A prompt
repletion is required to avoid the negative effects that
deficiencies of B12, zinc, iron, vitamin
C and folate may have on appetite, taste, mood and energy
levels, which may in turn affect a
patient’s ability to fully participate in treatment. Most nutrients
require initial high doses that
would be difficult to achieve with food alone and may require
prolonged courses of
supplementation to reverse the deficiency effectively. Patients
should be encouraged to
include foods high in the deficient nutrients regardless of
supplementation because
continued intake of these nutrients is necessary to maintain
repletion and health.
Some low-weight individuals with the lack of interest
presentation of ARFID may benefit

from off-label use of cyproheptadine, a medication with
antihistaminergic and
antiserotingeric properties; a study in children ages 7 months to
6 years with a variety of
feeding difficulties showed that patients receiving
cyproheptadine had greater improvements
in weight gain and positive changes in mealtime and feeding
behaviors as compared to those
not taking cyproheptadine (26). In our experience, some but not
all patients benefit from
cyproheptadine promoting increased appetite and gastric
accommodation. It is important to
be aware that patients can develop tachyphylaxis to
cyproheptadine, so if the efficacy wanes
with time, it may be worth having the patient take a one week
medication holiday on a
monthly basis.
Psychological treatment.
Psychological treatments for ARFID are emerging. At
Massachusetts General Hospital, our
Eating Disorders Clinical and Research Program team has
developed a cognitive-behavioral
therapy for ARFID (CBT-AR) to treat individuals ages 10 and
older with all presentations of

ARFID who are medically stable and not reliant on enteral
feeding (27). This structured
time-limited outpatient intervention can be delivered in an
individual or family-supported
format depending on the patient’s age, and lasts between 20 to
30 sessions depending on the
degree of nutritional compromise. The treatment operates using
the principle of volume
before variety to support nutritional rehabilitation (i.e., weight
restoration, correction of
deficiencies). Specifically, patients who are underweight are
encouraged to eat larger
volumes of preferred food in the early stages of treatment,
before increasing dietary variety
in later stages. The key intervention is structured in-session
exposure to systematically
address the maintaining mechanisms most relevant for the
patient, including sensory
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sensitivity, fear of aversive consequences, and lack of interest
in food and eating. CBT-AR is
currently being tested in an open trial at Massachusetts General
Hospital, so efficacy data are
not yet available. However, preliminary results are promising in
terms of weight gain,
resolution of nutrition deficiencies, and modest expansion of
dietary variety, as illustrated in
a published case report utilizing the approach (15).
Psychiatric medications.
There is currently no psychotropic medication for treatment of
ARFID approved by the U.S.

Food and Drug Administration. However, case reports and small
case series have described
the use of mirtazapine (15) or lorazepam (28) to decrease
anxiety related to eating; and
olanzapine (29) to reduce cognitive rigidity in beliefs about
food and to promote weight
gain. Future randomized placebo-controlled trials are needed to
evaluate the efficacy of these
medications for the resolution of ARFID symptoms.
Conclusions
ARFID is a relatively new psychiatric diagnosis, which captures
a clinically significant and
prevalent restrictive eating problem that occurs in individuals of
all ages and across genders.
Emerging data suggest that ARFID is as common as the
classical eating disorders and can be
associated with important medical and psychological
consequences. Moreover, data from
pediatric and adolescent medicine clinics nationwide highlight
the prevalence of this
problem in medical settings, underscoring the need for
pediatricians to be familiar with the
evaluation and clinical management of this diagnosis.

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2018.
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https://ods.od.nih.gov/factsheets/Folate-HealthProfessional/
https://ods.od.nih.gov/factsheets/Calcium-HealthProfessional
https://ods.od.nih.gov/factsheets/Iron-HealthProfessional/
https://ods.od.nih.gov/factsheets/VitaminA-HealthProfessional/
https://ods.od.nih.gov/factsheets/VitaminB12-
HealthProfessional/
https://ods.od.nih.gov/factsheets/VitaminC-HealthProfessional/
https://ods.od.nih.gov/factsheets/VitaminD-HealthProfessional/
https://ods.od.nih.gov/factsheets/VitaminK-HealthProfessional/
https://ods.od.nih.gov/factsheets/Zinc-HealthProfessional/
https://ods.od.nih.gov/factsheets/Riboflavin-HealthProfessional/
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Table 1:
Signs and symptoms of specific vitamin and mineral
deficiencies due to dietary restrictions.
Foods
avoided
Potential
vitamin &
mineral
deficiencies
Potential signs & symptoms
Meat and
animal
products
Vitamin B12 Megaloblastic or Macrocytic anemia, low energy,
weakness,
numbness or tingling in hands or feet, trouble walking or
unsteadiness, constipation, anorexia, confusion and poor
memory, mood changes, psychosis, mouth/tongue discomfort
Zinc Poor growth and development, anorexia, weakened immune
system, impaired night vision, taste and smell changes, hair
loss, diarrhea, poor wound healing

Iron Microcytic anemia, pallor, weakness, fatigue or sleepiness,
irritability, poor concentration, learning and cognitive
difficulties, mood changes, decreased exercise endurance,
headaches, temperature intolerance, weakened immune system
Animal
products
and/or dairy
Riboflavin/
Vitamin B2
Low energy, poor growth, dry skin /skin problems, hair loss,
dry cracked lips or cracks at the corners of mouth, swollen
magenta-colored tongue, itchy and/ or red eyes, sore throat,
anemia and cataracts
Dairy Calcium A deficiency is rarely detected by lab values.
The body
closely regulates serum levels despite intake. Food history is
the best way to assess for a deficiency. Prolonged inadequate
intake can result in decreased bone mineral density,
osteopenia, weak or broken bones and osteoporosis.
Vitamin D Low bone mineral density, hypocalcemia, accelerated
bone
loss, bone pain, osteomalacia, rickets
Fruits and
vegetables
Vitamin C Petechiae and easy bruising, bleeding and swollen
gums,
anorexia, anemia, feeling unwell, muscle and joint pain,
corkscrew hair, perifollicular hemorrhage, impaired wound
healing, hyperkeratosis, weakness, mood disturbances

Fruits,
vegetables
and/ or
overall low
quality diet
Folate Megaloblastic or Macrocytic anemia, persistent fatigue,
pallor,
palpitations, shortness of breath, headaches, oral ulcerations,
increased risk of birth defects, poor concentration, increased
irritability, weight loss
Very low fat
or protein
diet
Vitamin A Poor night vision/ night blindness, weakened
immune system,
follicular hyperkeratosis, impaired wound healing
Vitamin K Bruising and easy bleeding, increased prothrombin
time
Protein Loss of lean body mass, decreased energy
Fat Weight loss, amenorrhea
Sources: (30–40)
June 01.
AbstractIntroductionWhat is known about ARFID?Clinical
presentation.Epidemiology.Contributing
factors.EvaluationMedical evaluation.Psychological
evaluation.TreatmentMedical.Psychological

treatment.Psychiatric medications.ConclusionsReferencesTable
1:
CASE REPORT Open Access
An ARFID case report combining family-
based treatment with the unified protocol
for Transdiagnostic treatment of emotional
disorders in children
Sarah Eckhardt1* , Carolyn Martell1, Kristina Duncombe
Lowe1, Daniel Le Grange2,3 and Jill Ehrenreich-May4
Abstract
Background: This case report discusses the presentation and
treatment of a nine-year-old female with a history of
significant weight loss and food refusal using a combined
approach of Family-Based Treatment (FBT) and the Unified
Protocol for Transdiagnostic Treatment of Emotional Disorders
in Children (UP-C).
Case presentation: The patient was diagnosed with
avoidant/restrictive food intake disorder (ARFID), separation
anxiety
disorder, and a specific phobia of choking, and subsequently
treated with a modified version of FBT, in conjunction with
the UP-C. At the end of treatment, improvements were seen in
the patient’s weight and willingness to eat a full range of
foods. Decreases in anxiety regarding eating/choking, fears of
food being contaminated with gluten, and fears of eating
while being away from parents were also observed.
Conclusions: These findings highlight promising results from
this combined treatment approach, referred to as FBT +

UP for ARFID. Further research is needed to evaluate the use of
this treatment in patients presenting with a variety of
ARFID symptoms.
Keywords: Avoidant/restrictive food intake disorder, Emotional
disorders, Family-based treatment, Unified protocol,
Transdiagnostic
Background
Avoidant/Restrictive Food Intake Disorder (ARFID), a com-
plex and heterogeneous diagnosis, has been hypothesized
along a dimensional model with presentations including
sensory sensitivity, fear of aversive consequences, and lack
of interest in eating [1, 2]. Significant literature exists on
the treatment of pediatric feeding disorders supporting the
use of behavioral feeding interventions among young chil-
dren [3]. Recently, individual case reports/series have sug-
gested other promising approaches for older children,
adolescents, and adults with ARFID, using as a base either
family-based treatment (FBT) [4–7];, cognitive behavioral
therapy (CBT) [8–10];, or other novel approaches [11].
Despite these new approaches being studied, no published,
randomized controlled trials have yet to evaluate their effi-
cacy for the treatment of ARFID [2]. What appears to be
lacking in the current treatment models is the ability to
concurrently address the high rates of comorbid mood
and anxiety disorders in patients with ARFID [12, 13],
while also remaining focused on the medical complica-
tions associated with those patients who present under-
weight or exhibit significant nutritional deficiencies as
part of this diagnosis. Consequently, this case presentation
proposes a novel treatment approach that attempts to ad-
dress both the psychological and emotional comorbidities
associated in children and adolescents with ARFID, as well
as the hallmark food avoidance features that appear across

a heterogeneous array of presentations.
This case study describes the treatment of a patient
with ARFID, using a combined approach of FBT [14]
and the Unified Protocol for Transdiagnostic Treatment
of Emotional Disorders in Children (UP-C) [15]. FBT +
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International License
(http://creativecommons.org/licenses/by/4.0/), which permits
unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate
credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were
made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to
the data made available in this article, unless otherwise stated.
* Correspondence: [email protected]
1Center for the Treatment of Eating Disorders, Children’s
Minnesota,
Minneapolis, MN, USA
Full list of author information is available at the end of the
article
Eckhardt et al. Journal of Eating Disorders (2019) 7:34
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UP for ARFID was developed through a 3 year case
consultation process with treatment developers of both
FBT and the UP-C. Treatment focuses on a combination
of techniques aimed at addressing both weight gain/
normalization of eating and additional symptoms includ-
ing fear, disgust, and worry or obsessive thoughts, as
well as varying forms of functionally-related avoidance
behavior and potential concomitant reinforcement of
avoidance by parents/caregivers. A major advantage of
this combined approach is that it allows the clinician to
personalize treatment based on the patient’s specific
presentation using a core set of evidence-based strategies
and assessment tools (e.g., Top Problems [16];). The
UP-C is transdiagnostic by definition, and contains
evidence-based strategies that are flexible enough to
address many of the maintaining symptoms that are
unique to ARFID. There is also an adolescent version of
the UP-C, which when combined with FBT makes this
treatment model acceptable for a wide range of patients
(named the Unified Protocol for Transdiagnostic Treat-
ment of Emotional Disorders in Adolescents; UP-A).
The UP for adults has previously been adapted for use
with other eating disorder populations (anorexia nervosa,
bulimia nervosa, and binge-eating disorder), with early
results indicating improvments in anxiety sensitivity, ex-
periential avoidance, and mindfulness [17].
While flexible, FBT + UP for ARFID always begins with
sessions focused on FBT principles, including collabora-
tive weighing, psychoeducation (specific to ARFID pa-
tients and their eating problems), family engagement,
separating the eating problem from the child, charging
parents with taking control of their child’s eating (includ-
ing increasing volume and variety of foods), promoting
weight gain as needed, and a family meal. The UP-C or

UP-A is then added to build skills that empower the
patient to cope with difficult emotions, address avoidance,
and increase tolerance of emotions or disgust responses.
The Unified Protocol for Transdiagnostic Treatment of
Emotional Disorders (UP) [18] is an emotion-focused,
evidence-based treatment that targets the core dysfunction
of neuroticism in adults [19]. It has subsequently been
adapted to address emotional disorders in youth with the
development of the Unified Protocols for Transdiagnostic
Treatment of Emotional Disorders in Children and Ado-
lescents (UP-C and UP-A respectively [15];). These proto-
cols bring together cognitive-behavioral techniques, such
as cognitive reappraisal, problem-solving and opposite
action strategies, including a variety of exposure para-
digms and behavioral activation, as well as mindfulness
techniques into a single treatment. The UP-C and UP-A
present the same skills as the UP; however, the skills have
been adapted to be developmentally sensitive in their
presentation, as well as in their delivery. Furthermore, the
UP-C and UP-A also target core emotional parenting
behaviors that are common across emotional disorders in
youth (i.e. high levels of criticism, over-control/over
protection, inconsistency, and modeling of avoidance
[15]). Research has provided support for the efficacy and
feasibility of the UP, UP-A and UP-C for individuals with
mood, anxiety, and other emotional disorders. The UP,
in particular, has been shown to lead to significant
improvements at post-treatment [20], as well as main-
tenance of gains at follow-up time points [21] . The
UP-C was originally designed as a group version of the
UP-A, with concurrent child and parent group content.
However, the UP-C may be delivered in an individual
therapy model and explicit directions for doing so are
presented in the therapist guide. Preliminary evidence
suggests the UP-C may be similarly effective to leading

CBT approaches for childhood anxiety, with potential
benefits for those youth with higher levels of parent-
reported sadness, dysregulation or depressive symptoms
[22, 23]. The UP-A has also been shown to improve
symptoms of emotional disorders in adolescents. Re-
sults from multiple baseline, open-trial and initial wait-
list controlled trial studies showed that adolescents
evidenced significant improvement in their symptoms
after receiving 16 sessions of treatment using the UP-A
and gains were maintained at follow-up time points
[24–26]. While results of initial patient outcomes for
this combined FBT + UP for ARFID approach are not
yet available (given this treatment is currently being
studied as part of a larger, clinic-wide effectiveness
study), feedback from individual patients and practi-
tioners who have been trained in the model through a
clinical teaching day at the Academy of Eating Disor-
ders International Conference has been positive [27].
Consent to share the following case was provided by
the family and patient. Changes in identifying informa-
tion were made to protect patient privacy.
Case presentation
“Laura” is a nine-year-old female, who presented with 38
lbs. of weight loss, poor oral intake, and medical instability
in the context of fears about eating/choking secondary to
a recent diagnosis of gluten intolerance. Ten months be-
fore she presented for treatment, Laura felt unwell after
eating at a restaurant with her family. Following this ex-
perience, she became more anxious with eating, reporting
frequent stomach aches and headaches. Laura’s family
tried a variety of elimination diets, including stopping all
dairy and gluten. Laura was seen multiple times by her
pediatrician, who ultimately recommended allergy and
celiac testing. Over the course of this time Laura lost 29%
of her overall body weight. Laura’s symptoms continued

to worsen, and she was eating little due to anxiety and a
sensation of choking when eating. Parents noticed that
her hair was falling out, her eyes appeared sunken, and
Page 2 of 7
she felt tired every day. She became increasingly afraid of
separating from her parents, and her mother began getting
calls from Laura’s school (3–4 times per day) due to fre-
quent stomach aches or requests to see her mother.
Prior to presentation, Laura’s medical work-up showed
focal chronic-type peptic duodenitis and reflux esopha-
gitis. She was diagnosed with significant gluten sensitivity/
intolerance, with a likely diagnosis of celiac disease. Laura
had also been participating in weekly, individual play-
based therapy for approximately 4 months to address her
separation and other anxiety symptoms, without improve-
ment. Her therapist did not have any expertise or experi-
ence in treating ARFID, therefore she was not focusing on
weight regain or fears about eating. Laura was started on
20 mg of sertraline (liquid concentrate) 3 months prior to
presentation at our service, though family had not seen
any notable gains. Upon initial presentation to our team,
Laura required hospitalization for 12 days for medical
stabilization due to: symptomatic orthostasis, bradycardia,
and severe malnutrition. During her hospital stay, Laura
was diagnosed with ARFID, her sertraline was increased
to 50 mg, and she was started on hydroxyzine, 5 mg TID
to target pre-meal anxiety, nausea, and fullness. Following
medical stabilization, Laura then began weekly outpatient
treatment with her family to address the need for contin-
ued weight regain, anxiety/fears with eating, and separ-

ation anxiety. Given Laura had previously trended at or
above the 85th percentile for BMI, the goal was to return
her weight back to her personal healthy weight range.
The underlying assumption of FBT + UP for ARFID is
that patients diagnosed with ARFID need a combination
of treatment techniques that focus on both weight gain
and/or normalizing eating while also addressing add-
itional emotional disorder symptoms (i.e. anxiety, de-
pression, obsessive-compulsive symptoms, emotional/
situational avoidance). Patients and their parents begin
with traditional FBT for several sessions (see Table 1 for
content). Once progress with weight gain/regular eating
are underway, the UP-C or UP-A modules are intro-
duced. The UP-C has a flexible approach with core
evidence-based principles and concurrent parenting
content for emotional disorders that can be individual-
ized for specific ARFID presentations [15]. Once the
UP-C is added, the session breakdown continues as
follows: 5 min weigh-in and update from patient on how
eating is progressing, 30–40 min of individual therapy
with the patient focused on the UP-C content, and 10–
15 min with the patient and family to review session
content, discuss how eating/weight gain are progressing,
brainstorm challenges related to eating, and review
homework/exposure practice. For younger patients,
parents may be present for more/all of the session.
As illustrated in Table 2, over the course of treatment
Laura’s weight increased from 36.7 kg to 44.7 kg (percent
goal weight from 81.4 to 91.4%), with family noting
significant improvements in energy level and ability to
participate in school and other physical activities. During
initial FBT sessions, the focus was on weight gain using
foods that Laura felt were safe and could allow her to re-

gain weight efficiently. In session two, a family meal was
completed, where the therapist worked to separate the
illness from Laura and decrease blame (see FBT manual
[14]), as well as discuss rewards that could be utilized to
encourage Laura to challenge herself with eating. After
two sessions of FBT (and with Laura’s weight increas-
ing), the UP-C was added to sessions, though the focus
of each subsequent session also remained on weight
regain and parental support/empowerment. Of note,
Laura’s family took to the principles of FBT quickly, but
continued to benefit from each session’s focus on graph-
ing the patient’s weight, problem solving any challenges
during weeks where weight was stable or down, and
empowering parents to work closely together on how to
best refeed their daughter.
The patient and family identified three Top Problems
(an ideographic assessment tool by Weisz et al. [16]
modified for use in the UP-C and UP-A by Ehrenreich-
May et al. [15]) they wanted to address in treatment
including: 1) decrease fears of choking/eating feared
foods, 2) be away from/eat away from mother, and 3)
patient sleeping in her own bed again. Additionally, the
therapist reinforced an overarching goal of Laura return-
ing to a healthy weight range as crucial for her recovery.
All subsequent treatment sessions involved reviewing
Laura’s weight/eating, teaching content from the UP-C
modules, and discussing home learning assignments.
As treatment progressed and the patient learned skills
to better manage her emotions, she became more willing
to try foods that she was avoiding. With the help of the
treating clinician, Laura created an exposure hierarchy
with numerous feared foods and situations (e.g. meats,
pasta, nuts, eating with adults other than her mother,
eating at restaurants, being away from her mother, and

sleeping in her own bed). Because Laura’s fears of eating
most foods were greatly impacting her overall functioning,
the therapist chose to move up exposure work after intro-
ducing the three parts of the emotional experience,
discussing the cycle of avoidance, and describing true/false
alarms. During the exposure work, Laura created a ladder
to break down the steps of each exposure, beginning with
simply describing the food in a non-judgmental way and
later touching, licking, taking a tiny bite, and eventually
taking larger bites of these foods. Each of these skills were
taught to Laura using specific content from the UP-C.
Laura and her parents were encouraged by her success
and began implementing exposures outside of sessions.
Laura continued to add more new foods at home and
was able to attempt other types of foods in session. Once
Page 3 of 7
in-session exposures became easier for Laura, the therapist
had her add interoceptive exposures (e.g. running in place),
while also eating feared foods to attempt to evoke in-
creased feelings of anxiety and simulate a more naturalistic
experience of distress. As therapy progressed, Laura began
eating at restaurants again, as well as in more situations
away from her mother (e.g., church, school cafeteria). She
was able to stop the use of hydroxyzine, but continued on
her sertraline. Treatment ended when Laura returned to
eating nearly all foods, in numerous settings (school lunch-
room, other’s homes) away from her mother, and family
felt able to manage remaining avoidance (e.g. working on
eating at a greater variety of restaurants while away from

their hometown). Laura had also regained weight to the
Table 1 FBT + UP-C for ARFID session content
Session Content
FBT Session 1 Collaborative weighing, psychoeducation
(specific to ARFID patients), separating the
eating problem from the child, charging parents with taking
control of their child’s
eating, and beginning the discussion of utilizing rewards.
FBT Session 2 Engage family in family meal to further assess
patient’s eating, address any mealtime
behaviors that are getting in the way of success, and work to
empower parents to
begin helping their child make changes to their eating.
FBT Sessions 3+ For very underweight patients, additional FBT
sessions focus on building the parental
alliance and discussing ways to improve the parent’s ability to
work together on the
task of weight gain and related symptoms (food avoidance,
anxieties around eating,
etc). For patients who are not underweight or are gaining weight
appropriately, the
UP session content may begin to be added.
FBT + UP-C Module 1: Introduction to the Unified Protocol for
the Treatment of Emotional Disorders in Children
Introduces child/parents to the treatment model/structure and
describes the CLUES
skills (Consider how I feel, Look at my thoughts, Use detective
thinking and problem
solving, Experience my feelings, Stay healthy and happy),

discusses the purpose of
emotions and begins to build emotional awareness, and
identifies top problems and
treatment goals. Top problems may focus on ARFID related
goals or be more wide-
range to address other emotional avoidance or related
diagnoses.
FBT + UP-C Module 2: Getting to Know Your Emotions Learn
to identify and rate intensity of different emotions, normalizes
emotional
experiences, discusses the three parts of the emotional
experience and the cycle of
avoidance, explains true/false alarms, and identifies rewards for
new behaviors.
FBT + UP-C Module 3: Using Science Experiments to Change
our
Emotions and Behavior
Learn about the concept of “acting opposite” and using science
experiments to help
with acting opposite/emotional behaviors, explains the
connection between activity
and emotion and assigns emotion and activity tracking as an
experiment.
FBT + UP-C Module 4: Our Body Clues Describe the concept of
body clues and their relation to strong emotions, learn to
identify body clues for different emotions, teach the skill of
body scanning to develop
awareness of body clues, help child practice experiencing body
clues without using
avoidance/distraction through interoceptive exposures.
FBT + UP-C Module 5: Look at my Thoughts Introduce the

concept of flexible thinking and teach children to recognize
common
“thinking traps.”
FBT + UP-C Module 6: Use Detective Thinking Introduce and
apply detective thinking.
FBT + UP-C Module 7: Problem Solving and Conflict
Management
Introduce and apply problem solving, discuss use of problem
solving for interpersonal
conflicts or challenges related to eating.
FBT + UP-C Module 8: Awareness of Emotional Experiences
Teach children about present moment awareness, introduce non-
judgmental aware-
ness- especially with relation to strong disgust responses.
FBT + UP-C Module 9: Introduction to Emotion Exposure
Review skills learned to date in the UP-C, review the concepts
of emotional behaviors
and “acting opposite” in preparation for a new type of science
experiment called “ex-
posure,” complete a demonstration of an exposure using a toy or
other object, work
together with child and parents to begin developing plans for
upcoming exposures.
FBT + UP-C Module 10: Facing Our Feelings – Part 1 Review
the concept of using science experiments to face strong
emotions, introduce
the idea of safety behaviors and subtle avoidance behaviors
(e.g., distraction), practice
a science experiment to face strong emotions (sample
situational emotion exposure),

make plans for future science experiments for facing strong
emotions (individualized
situational emotion exposures).
FBT + UP-C Module 11: Facing Our Feelings – Part 2 Plan and
execute initial situational emotion exposure in session, plan and
execute
additional situational emotion exposure activities in future
sessions and at home.
FBT + UP-C Module 12: Wrap Up and Relapse Prevention
Review Emotion Detective skills learned in the UP-C program,
plan for facing strong
emotions in the future, celebrate progress made in treatment
program, create a plan
for sustaining and furthering progress after treatment,
distinguish lapses from relapses
and help family recognize warning signs of relapse.
Page 4 of 7
71st percentile for BMI (91.4% of her previously healthy
weight range), and her parents felt fully equipped in their
ability to continue helping her restore weight. Laura com-
pleted 29 sessions over the course of 10 months of weekly
or biweekly therapy.
Discussion and conclusions
This case study illustrates that the FBT + UP for ARFID
therapy model, which combines and modifies previously
developed evidence-based treatments, was feasible and
helpful in allowing this patient to gain weight, return to
eating a diverse range of foods in a variety of settings,

and decrease anxiety about eating/being away from her
mother. Notably, when this family returned for a follow-
up 5 months after completing treatment, the patient’s
weight had continued to increase (50.4 kg/81st percentile
for BMI/97.1% of goal weight), she had started menstru-
ating, and she was able to separate and eat apart from
her mother without significant difficulty. The patient
and parents also rated her fears of choking and eating
previously feared foods as 1 and 2’s on an 8-point likert
scale (see Table 2).
This patient was a good treatment candidate for FBT +
UP for ARFID given she endorsed significant anxiety prior
to treatment and also met criteria for several concurrent
anxiety disorder diagnoses. Another major benefit of the
treatment is the ability to flexibly offer the various modules
that may benefit each patient based on their specific needs
and ARFID presentations. For example, this patient bene-
fited from exposure work, learning non-judgmental aware-
ness, and improving awareness of physical sensations,
while other patients may need more focus on cognitive
reappraisal, problem-solving, and other types of opposite
action [15]. Additionally, given Laura had lost a significant
amount of weight she required a treatment that also
focused on weight restoration as one of its core principles.
A major advantage of this combined treatment approach is
the ability for clinicians to tailor each session to the specific
needs of their individual patient, including returning to
solely FBT sessions if weight gain or nutritional dificiencies
are not progressing appropriately.
While several novel approaches for the treatment of
ARFID have been suggested [7, 10, 11], randomized con-
trol trials have yet to be presented regarding their effi-
cacy. Even with some intervention research aiming to

address the heterogeneous symptoms of ARFID, no
treatment to date has proposed a model that addresses
both the varied presentations of ARFID, as well as its full
range of common comorbid disorders, in one cohesive
approach that is flexible and adaptable to the individual.
While the development of symptom specific treatment
approaches to ARFID is logical, it does not address the
heterogeneous nature of this disorder and can impede
dissemination [28]. With so many different presentations
of ARFID and high rates of comorbid disorders, one
clear treatment that can be used flexibly to adapt to the
range of ARFID presentations and co-occurring disorders
would provide an efficient and cohesive approach to treat-
ing youth with ARFID. Further examination of FBT + UP
for a wide-range of ARFID presentations among youth
continues. A study to establish an ideal combination of
FBT and UP strategies for youth with ARFID between the
ages of 6–18 years, and the preliminary efficacy of this ap-
proach, is a next logical step in this research.
Finally, some limitations with this case study should
be noted. First, it was not possible to ascertain whether
FBT in isolation would have worked as effectively for
this patient as this combined FBT + UP-C approach.
While anxiety reduction has been shown in nutritional-
based therapies, such as FBT, it is unclear if patients
with profound phobic and other concurrent anxiety
would benefit as greatly without specific skills and expos-
ure work inherent in the UP-C. Additional limitations of
this case study include the absence of objective assessment
of psychological outcomes. That said, this young person
made significant improvements in terms of weight, both at
completion of treatment and at follow-up. Moreover, Top
Problems rating by both the patient and parents also
appear to indicate meaningful improvements in a variety of
behavioral domains. However, without objective measures

it is difficult to ascertain whether anxiety reduction allowed
for behavioral change, or whether behavioral change
caused anxiety reduction over the course of the UP-C. Fu-
ture studies should attempt to parce out when and for
whom this combined treatment approach is most effective.
Table 2 Top problems and weight
Baseline End of
treatment
5 months
post
treatment
Top Problems (Parent)
Fear of choking/eating fear foods 8 3 2
Being away from mother/eating
away from mother
8 2 2
Sleeping alone 7 2 0–1
Top Problems (Child)
Fear of choking/eating fear foods 8 3 1
Being away from mother/eating
away from mother
8 2 2–3
Sleeping alone 8 0 0

Weight Presentation
Kilograms 36.7 44.7 50.4
BMI %ile 41.3 70.7 81.2
% Goal Weight 81.4 91.4 97.1
Top Problems were rated 0–8, with 0 being not a problem and 8
being very
much a problem. BMI %ile = Body Mass Index Percentile. %
Goal Weight =
Percentage of treatment goal weight utilizing the 85th percentile
for Body
Mass Index
Page 5 of 7
Abbreviations
ARFID: Avoidant/Restrictive Food Intake Disorder; FBT:
Family Based
Treatment; FBT+UP: Family Based Treatment with the Unified
Protocol;
Kg: Kilograms; TID: Three times a day; UP: Unified Protocol
for
Transdiagnostic Treatment of Emotional Disorders; UP-A:
Unified Protocol for
Transdiagnostic Treatment of Emotional Disorders in
Adolescents; UP-
C: Unified Protocol for Transdiagnostic Treatment of Emotional
Disorders in
Children

Acknowledgements
We acknowledge the generous financial support from the Goven
Family
Foundation. We would also like to thank Dr. Julie Lesser for her
contributions
in the initial conceptualization of this treatment model.
Authors’ contributions
SE took primary responsibility for the manuscript, including
reviewing
relevant literature and drafting the paper for publication. CM
and KDL
assisted with literature review and editing of the manuscript.
DLG and JEM
contributed to treatment protocol development and critical
review of the
manuscript. All authors read and approved the final manuscript.
Funding
A philanthropic grant from the Goven Family Foundation was
provided to
Children’s MN and supported the first author’s time (SE) in
writing this case
report.
Availability of data and materials
All authors had access to the relevant material in the generation
and review
of this manuscript. Due to ethical concerns, supporting data
cannot be
made openly available.
Ethics approval and consent to participate
Due to the nature of this case report, ethics approval was not
required by

the institution.
Consent for publication
Informed written consent was obtained from both the patient
and parents
for use of clinical history and publication of this case report. A
copy of the
written consent is available for review by the Editor-in-Chief of
this journal.
Competing interests
Dr. Le Grange receives royalties from Guilford Press as well as
Routledge. He
is Co-Director of the Training Institute for Child and
Adolescent Eating Disor-
ders, LLC. Dr. Jill Ehrenreich-May receives royalties from the
sales of the ther-
apist guide and workbooks for the Unified Protocols for
Transdiagnostic
Treatment of Emotional Disorders in Children and Adolescents
(UP-C and
UP-A) from Oxford University Press. She also receives
payments for UP-C and
UP-A clinical trainings, consultation and implementation
support services.
Author details
1Center for the Treatment of Eating Disorders, Children’s
Minnesota,
Minneapolis, MN, USA. 2Department of Psychiatry, University
of California,
San Francisco, CA, USA. 3Department of Psychiatry and
Behavioral
Neuroscience, The University of Chicago, Chicago, IL, USA.
4Department of
Psychology, University of Miami, Coral Gables, FL, USA.

Received: 21 June 2019 Accepted: 2 October 2019
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AbstractBackgroundCase
presentationConclusionsBackgroundCase
presentationDiscussion and
conclusionsAbbreviationsAcknowledgementsAuthors’
contributionsFundingAvailability of data and materialsEthics
approval and consent to participateConsent for
publicationCompeting interestsAuthor
detailsReferencesPublisher’s Note

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