write a 3-4 page Article critiques on the 6 documents attached, the document title and links are also posted below.

the paper

1. paper should briefly summarize the main research questions, with the majority of the paper focused on your critique of the paper (strengths, limitations, future directions) and your reflection on the study topic. It is important that you not simply restate what the authors said in the manuscript but that you convey your own ideas about the article. 

2.      paper should be easy   to read, topic introduced, organization clear with proper introduction, body,   conclusion

 

3. The   student’s reflection about the topic is explained in clear language;   immediately interesting and supported with detail

 

4. Each   paragraph has a central idea; ideas are connected, and paragraphs are   developed with details; paper is easy to read and “flows” naturally in an   organized pattern

 

5. Paper   provides evidence (using description, details, and use of research   literature) that the student has examined his/her own belief systems and   related this to their current views about the topic; use of research   literature to support thought

 
 

6. The paper demonstrates that the student fully understands and has applied concepts found in research.  Research and concepts are integrated in student’s own words. The writer provides concluding remarks that show insight, analysis, and synthesis of ideas.

 

7. It provides compelling and accurate evidence to support in-depth the central position beyond the required (5) research sources with at least 1 source from a   periodical database. Research sources are highly relevant, accurate, and reliable and add to the strength of the paper; and are effectively referenced and cited throughout the paper.

 

10. Paper shows exemplary evidence of an integrated and organized discussion of the results that take into account the strengths, weaknesses, and limitations of the research design, and the statistics that are utilized to analyze the data.

Outstanding integration and discussion of the current results in the context of previous research findings, including future research directions.

 
 

No errors whatsoever!

 

No wrong word choice or slang; uses correct verb tense and pronouns. Well   written and use of words convey meaning

articles.

AVOIDANT RESTRICTIVE FOOD INTAKE DISORDER (ARFID)

  

https://www.nationaleatingdisorders.org/learn/by-eating-disorder/arfid

Cognitive-Behavioral Treatment of Avoidant/Restrictive Food Intake Disorder

 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6235623/pdf/nihms-1511046  

An ARFID case report combining family-based treatment with the unified protocol for Transdiagnostic treatment of emotional disorders in children  

https://jeatdisord.biomedcentral.com/track/pdf/10.1186/s40337-019-0267-x

 

 Evaluation and Treatment of Avoidant/Restrictive Food Intake Disorder (ARFID) in Adolescents 

 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6534269/pdf/nihms-995861  

Update on eating disorders: current perspectives on avoidant/restrictive food intake disorder in children and youth

 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4725687/pdf/ndt-12-213  

Eating Disorder Core Symptoms and Symptom Pathways Across Developmental Stages: A Network Analysis

Use the attachment

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 +

© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
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: sarah.eckhardt@childrensmn.org
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
https://doi.org/10.1186/s40337-019-0267-x

http://crossmark.crossref.org/dialog/?doi=10.1186/s40337-019-0267-x&domain=pdf

http://orcid.org/0000-0003-0824-4328

http://creativecommons.org/licenses/by/4.0/

http://creativecommons.org/publicdomain/zero/1.0/

mailto:sarah.eckhardt@childrensmn.org

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

Eckhardt et al. Journal of Eating Disorders (2019) 7:34 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

Eckhardt et al. Journal of Eating Disorders (2019) 7:34 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.

Eckhardt et al. Journal of Eating Disorders (2019) 7:34 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

Eckhardt et al. Journal of Eating Disorders (2019) 7:34 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

References

1. American Psychiatric Association. Diagnostic and statistical manual of

mental disorders: DSM-5: American Psychiatric Association. Arlington:
DSM; 2013.

2. Thomas JJ, Lawson EA, Micali N, Misra M, Deckersbach T, Eddy KT. Avoidant/
restrictive food intake disorder: a three-dimensional model of neurobiology
with implications for etiology and treatment. Curr Psychiatry Rep. 2017;
19(8):54.

3. Sharp WG, Jaquess DL, Morton JF, Herzinger CV. Pediatric feeding disorders:
a quantitative synthesis of treatment outcomes. Clin Child Fam Psychol Rev.
2010;13(4):348–65.

4. Bryant-Waugh R. Avoidant restrictive food intake disorder: an illustrative
case example. Int J Eat Disord. 2013;46(5):420–3.

5. Fitzpatrick KK, Forsberg SE, Colborn D. Family-based therapy for avoidant
restrictive food intake disorder: families facing food neophobias. In: Loeb K,
Le Grange D, Lock J, editors. Family therapy for adolescent eating and
weight disorders. New York: Routledge; 2015. p. 276–96.

6. Loeb K, Le Grange D, Lock J. Family therapy for adolescent eating and
weight disorders: new applications. New York: Routledge; 2015.

7. Lock J, Robinson A, Sadeh-Sharvit S, Rosania K, Osipov L, Kirz N,
Derenne J, Utzinger L. Applying family-based treatment (FBT) to three
clinical presentations of avoidant/restrictive food intake disorder:
similarities and differences from FBT for anorexia nervosa. Int J Eat
Disord. 2019;52(4):439–46.

8. Mammel KA, Ornstein RM. Avoidant/restrictive food intake disorder: a new
eating disorder diagnosis in the diagnostic and statistical manual 5. Curr
Opin Pediatr. 2017;29(4):407–13.

9. Dumont E, Jansen A, Kroes D, de Haan E, Mulkens S. A new cognitive
behavior therapy for adolescents with avoidant/restrictive food intake
disorder in a day treatment setting: a clinical case series. Int J Eat Disord.
2019;52(4):447–58.

10. Thomas JJ, Eddy KT. Cognitive-behavioral therapy for avoidant/restrictive
food intake disorder: children, adolescents, and adults. Cambridge:
Cambridge University Press; 2018.

11. Zucker NL, LaVia MC, Craske MG, Foukal M, Harris AA, Datta N, Savereide E,
Maslow GR. Feeling and body investigators (FBI): ARFID division—an
acceptance-based interoceptive exposure treatment for children with
ARFID. Int J Eat Disord. 2019;52(4):466–72.

12. Nicely TA, Lane-Loney S, Masciulli E, Hollenbeak CS, Ornstein RM.
Prevalence and characteristics of avoidant/restrictive food intake
disorder in a cohort of young patients in day treatment for eating
disorders. J Eat Disord. 2014;2(1):21.

13. Duncombe Lowe K, Barnes TL, Martell C, Keery H, Eckhardt S, Peterson CB,
Lesser J, Le Grange D. Youth with avoidant/restrictive food intake disorder:
examining differences by age, weight status, and symptom duration.
Nutrients. 2019;11(8):1955.

14. Lock J, Le Grange D. Treatment manual for anorexia nervosa: a family-based
approach. 2nd ed. New York: Guilford Press; 2012.

15. Ehrenreich-May J, Kennedy SM, Sherman JA, Bilek EL, Buzzella BA, Bennett
SM, Barlow DH. Unified protocols for transdiagnostic treatment of
emotional disorders in children and adolescents: therapist guide. New York:
Oxford University Press; 2018.

16. Weisz JR, Chorpita BF, Frye A, Ng MY, Lau N, Bearman SK, Ugueto AM,
Langer DA, Hoagwood KE. Youth top problems: using idiographic,
consumer-guided assessment to identify treatment needs and to track
change during psychotherapy. J Consult Clin Psychol. 2011;79(3):369.

17. Thompson-Brenner H, Boswell JF, Espel-Huynh H, Brooks G, Lowe MR.
Implementation of transdiagnostic treatment for emotional disorders in
residential eating disorder programs: a preliminary pre-post evaluation.
Psychother Res. 2019;29(8):1045-61.

18. Barlow DH, Ellard KK, Fairholme CP, Farchione TJ, Boisseau CI, Allen LB,
Ehrenreich-May JT. Unified protocol for transdiagnostic treatment of
emotional disorders: therapist guide. 2nd ed. New York: Oxford University
Press; 2018.

19. Marchette LK, Weisz JR. Practitioner review: empirical evolution of youth
psychotherapy toward transdiagnostic approaches. J Child Psychol
Psychiatry. 2017;58(9):970–84.

20. Farchione TJ, Fairholme CP, Ellard KK, Boisseau CL, Thompson-Hollands J,
Carl JR, Gallagher MW, Barlow DH. Unified protocol for transdiagnostic
treatment of emotional disorders: a randomized controlled trial. Behav Ther.
2012;43(3):666–78.

21. Bullis JR, Fortune MR, Farchione TJ, Barlow DH. A preliminary investigation
of the long-term outcome of the unified protocol for Transdiagnostic
treatment of emotional disorders. Compr Psychiatry. 2014;55(8):1920–7.

22. Kennedy SM, Bilek EL, Ehrenreich-May J. A randomized controlled pilot trial
of the unified protocol for transdiagnostic treatment of emotional disorders
in children. Behav Modif. 2019;43(3):330–60.

23. Kennedy SM, Tonarely NA, Sherman JA, Ehrenreich-May J. Predictors of
treatment outcome for the unified protocol for transdiagnostic treatment of
emotional disorders in children (UP-C). J Anxiety Disord. 2018;57:66–75.

24. Ehrenreich-May J, Rosenfield D, Queen AH, Kennedy SM, Remmes CS,
Barlow DH. An initial waitlist-controlled trial of the unified protocol for

Eckhardt et al. Journal of Eating Disorders (2019) 7:34 Page 6 of 7

the treatment of emotional disorders in adolescents. J Anxiety Disord.
2017;46:46–55.

25. Ehrenreich JT, Goldstein CR, Wright LR, Barlow DH. Development of a
unified protocol for the treatment of emotional disorders in youth. Child
Family Behav Ther. 2009;31(1):20–37.

26. Queen AH, Barlow DH, Ehrenreich-May J. The trajectories of adolescent
anxiety and depressive symptoms over the course of a transdiagnostic
treatment. J Anxiety Disord. 2014;28(6):511–21.

27. Lesser JK, Eckhardt S, Le Grange D, Ehrenreich-May J. Integrating family
based treatment with the unified protocol for the transdiagnostic treatment
of emotional disorders: A novel treatment for avoidant restrictive food
intake disorder. Prague: Academy of Eating Disorders International
Conference; 2017. [Clinical teaching day]

28. McHugh RK, Barlow DH. The dissemination and implementation of
evidence-based psychological treatments: a review of current efforts. Am
Psychol. 2010;65(2):73.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.

Eckhardt et al. Journal of Eating Disorders (2019) 7:34 Page 7 of 7

Abstract
Background
Case presentation
Conclusions
Background
Case presentation
Discussion and conclusions
Abbreviations
Acknowledgements
Authors’ contributions
Funding
Availability of data and materials
Ethics approval and consent to participate
Consent for publication
Competing interests
Author details
References
Publisher’s Note

Evalua

t

ion 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, Massachusetts General Hospital

2Department of Pediatrics, Harvard Medical School

3Eating Disorders Clinical and Research Program, Massachusetts General Hospital

4Department of Psychiatry, Harvard Medical School

# These authors contributed equally to this work.

Abstrac

t

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, KBRIGHAM@mgh.harvard.edu.

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.

A

u
th

o
r M

a
n
u
scrip

t
A

u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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

Curr Pediatr Rep. Author manuscript; available in PMC 2019 June 01.

A
u
th

o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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,

Brigham et al. Page 3

Curr Pediatr Rep. Author manuscript; available in PMC 2019 June 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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.,

Brigham et al. Page 4

Curr Pediatr Rep. Author manuscript; available in PMC 2019 June 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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).

Brigham et al. Page 5

Curr Pediatr Rep. Author manuscript; available in PMC 2019 June 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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

Brigham et al. Page 6

Curr Pediatr Rep. Author manuscript; available in PMC 2019 June 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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

Brigham et al. Page 7

Curr Pediatr Rep. Author manuscript; available in PMC 2019 June 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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.

References

(1). American Psychiatric Association, American Psychiatric Association DSM-5 Task Force.
Diagnostic and statistical manual of mental disorders : DSM-5. 5th ed. ed. Arlington, VA; 2013.

(2). American Psychiatric Association, American Psychiatric Association Task Force on DSM.
Diagnostic and statistical manual of mental disorders : DSM-IV. 4th ed. ed. Washington, DC;
1994.

(3). Thomas JJ, Lawson EA, Micali N, Misra M, Deckersbach T, Eddy KT. Avoidant/Restrictive Food
Intake Disorder: a Three-Dimensional Model of Neurobiology with Implications for Etiology and
Treatment. Curr Psychiatry Rep 2017 8;19(8):54–017–0795–5. [PubMed: 28714048]

(4). Fisher MM, Rosen DS, Ornstein RM, Mammel KA, Katzman DK, Rome ES, et al. Characteristics
of avoidant/restrictive food intake disorder in children and adolescents: a “new disorder” in
DSM-5. J Adolesc Health 2014 7;55(1):49–52. [PubMed: 24506978]

(5). Norris ML, Spettigue WJ, Katzman DK. Update on eating disorders: current perspectives on
avoidant/restrictive food intake disorder in children and youth. Neuropsychiatr Dis Treat 2016 1
19;12:213–218. [PubMed: 26855577]

(6). Eddy KT, Thomas JJ, Hastings E, Edkins K, Lamont E, Nevins CM, et al. Prevalence of DSM-5
avoidant/restrictive food intake disorder in a pediatric gastroenterology healthcare network. Int J
Eat Disord 2015 7;48(5):464–470. [PubMed: 25142784]

(7). Hay P, Mitchison D, Collado AEL, Gonzalez-Chica DA, Stocks N, Touyz S. Burden and health-
related quality of life of eating disorders, including Avoidant/Restrictive Food Intake Disorder
(ARFID), in the Australian population. J Eat Disord 2017 7 3;5:21-017-0149-z. eCollection
2017.

(8). Kurz S, van Dyck Z, Dremmel D, Munsch S, Hilbert A. Early-onset restrictive eating disturbances
in primary school boys and girls. Eur Child Adolesc Psychiatry 2015 7;24(7):779–785. [PubMed:
25296563]

Brigham et al. Page 8

Curr Pediatr Rep. Author manuscript; available in PMC 2019 June 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

(9). Forman SF, McKenzie N, Hehn R, Monge MC, Kapphahn CJ, Mammel KA, et al. Predictors of
outcome at 1 year in adolescents with DSM-5 restrictive eating disorders: report of the national
eating disorders quality improvement collaborative. J Adolesc Health 2014 12;55(6):750–756.
[PubMed: 25200345]

(10). Norris ML, Robinson A, Obeid N, Harrison M, Spettigue W, Henderson K. Exploring avoidant/
restrictive food intake disorder in eating disordered patients: a descriptive study. Int J Eat Disord
2014 ;47(5):495–499. [PubMed: 24343807]

(11). Ornstein RM, Rosen DS, Mammel KA, Callahan ST, Forman S, Jay MS, et al. Distribution of
eating disorders in children and adolescents using the proposed DSM-5 criteria for feeding and
eating disorders. J Adolesc Health 2013 ;53(2):303–305. [PubMed: 23684215]

(12). Nicely TA, Lane-Loney S, Masciulli E, Hollenbeak CS, Ornstein RM. Prevalence and
characteristics of avoidant/restrictive food intake disorder in a cohort of young patients in day
treatment for eating disorders. J Eat Disord 2014 8 2;2(1):21-014-0021-3. eCollection 2014.

(13). Ornstein RM, Essayli JH, Nicely TA, Masciulli E, Lane-Loney S. Treatment of avoidant/
restrictive food intake disorder in a cohort of young patients in a partial hospitalization program
for eating disorders. Int J Eat Disord 2017 9;50(9):1067–1074. [PubMed: 28644568]

(14). Mammel KA, Ornstein RM. Avoidant/restrictive food intake disorder: a new eating disorder
diagnosis in the diagnostic and statistical manual 5. Curr Opin Pediatr 2017 8;29(4):407–413.
[PubMed: 28537947]

(15). Thomas JJ, Brigham KS, Sally ST, Hazen EP, Eddy KT. Case 18-2017 – An 11-Year-Old Girl
with Difficulty Eating after a Choking Incident. N Engl J Med 2017 6 15;376(24):2377–2386.
[PubMed: 28614676]

(16). Marild K, Stordal K, Bulik CM, Rewers M, Ekbom A, Liu E, et al. Celiac Disease and Anorexia
Nervosa: A Nationwide Study. Pediatrics 2017 5;139(5):10.1542/peds.2016-4367. Epub 2017
Apr 3.

(17). De Souza MJ, Nattiv A, Joy E, Misra M, Williams NI, Mallinson RJ, et al. 2014 Female Athlete
Triad Coalition Consensus Statement on Treatment and Return to Play of the Female Athlete
Triad: 1st International Conference held in San Francisco, California, May 2012 and 2nd
International Conference held in Indianapolis, Indiana, May 2013. Br J Sports Med 2014 2;48(4):
289-2013-093218.

(18). Setnick J Micronutrient deficiencies and supplementation in anorexia and bulimia nervosa: a
review of literature. Nutr Clin Pract 2010 ;25(2):137–142. [PubMed: 20413694]

(19). Society for Adolescent Health and Medicine, Golden NH, Katzman DK, Sawyer SM, Ornstein
RM, Rome ES, et al. Position Paper of the Society for Adolescent Health and Medicine: medical
management of restrictive eating disorders in adolescents and young adults. J Adolesc Health
2015 1;56(1):121–125. [PubMed: 25530605]

(20). Bryant-Waugh R, Micali N, Cooke L, et al. The Pica, ARFID, and Rumination Disorder
Interview: Development of a multi-informant, semi-structured interview of feeding disorders
across the lifespan. In preparation

(21). Hilbert A, van Dyck Z. Eating Disorders in Youth-Questionnaire. English version . 2016 6 21;
Available at: http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-197246. Accessed Feb 28, 2018.

(22). Zickgraf HF, Ellis JM. Initial validation of the Nine Item Avoidant/Restrictive Food Intake
disorder screen (NIAS): A measure of three restrictive eating patterns. Appetite 2018 4 1;123:32–
42. [PubMed: 29208483]

(23). Strandjord SE, Sieke EH, Richmond M, Rome ES. Avoidant/Restrictive Food Intake Disorder:
Illness and Hospital Course in Patients Hospitalized for Nutritional Insufficiency. J Adolesc
Health 2015 12;57(6):673–678. [PubMed: 26422290]

(24). Brown J, Kim C, Lim A, Brown S, Desai H, Volker L, et al. Successful gastrostomy tube weaning
program using an intensive multidisciplinary team approach. J Pediatr Gastroenterol Nutr 2014
6;58(6):743–749. [PubMed: 24509305]

(25). Sharp WG, Stubbs KH, Adams H, Wells BM, Lesack RS, Criado KK, et al. Intensive, Manual-
based Intervention for Pediatric Feeding Disorders: Results From a Randomized Pilot Trial. J
Pediatr Gastroenterol Nutr 2016 4;62(4):658–663. [PubMed: 26628445]

Brigham et al. Page 9

Curr Pediatr Rep. Author manuscript; available in PMC 2019 June 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-197246

(26). Sant’Anna AM, Hammes PS, Porporino M, Martel C, Zygmuntowicz C, Ramsay M. Use of
cyproheptadine in young children with feeding difficulties and poor growth in a pediatric feeding
program. J Pediatr Gastroenterol Nutr 2014 11;59(5):674–678. [PubMed: 24941960]

(27). Thomas J, Eddy K. Cognitive-behavioral therapy for avoidant/restrictive food intake disorder:
Children, adolescents, and adults Cambridge, UK: Cambridge University Press; In press 2018.

(28). Kardas M, Cermik BB, Ekmekci S, Uzuner S, Gokce S. Lorazepam in the treatment of
posttraumatic feeding disorder. J Child Adolesc Psychopharmacol 2014 6;24(5):296–297.
[PubMed: 24813692]

(29). 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. J
Child Adolesc Psychopharmacol 2017 12;27(10):920–922. [PubMed: 29068721]

(30). Mueller C editor. The ASPEN Adult Nutrition Support Core Curriculum 3rd ed. Silver Spring,
MD: American Society for Parenteral and Enteral Nutrition; 2017.

(31). Office of Dietary Supplements, National Institutes of Health (US). Folate 2016 4 20; Available at:
https://ods.od.nih.gov/factsheets/Folate-HealthProfessional/. Accessed Feb 6, 2018.

(32). Office of Dietary Supplements, National Institutes of Health (US). Calcium 2016 11 17;
Available at: https://ods.od.nih.gov/factsheets/Calcium-HealthProfessional. Accessed Feb 6,
2018.

(33). Office of Dietary Supplements, National Institutes of Health (US). Iron 2016 2 11; Available at:
https://ods.od.nih.gov/factsheets/Iron-HealthProfessional/. Accessed Feb 6, 2018.

(34). Office of Dietary Supplements, National Institutes of Health (US). Vitamin A 2016 8 31;
Available at: https://ods.od.nih.gov/factsheets/VitaminA-HealthProfessional/. Accessed Feb 6,
2018.

(35). Office of Dietary Supplements, National Institutes of Health (US). Vitamin B12 2016 2 11;
Available at: https://ods.od.nih.gov/factsheets/VitaminB12-HealthProfessional/. Accessed Feb 6,
2018.

(36). Office of Dietary Supplements, National Institutes of Health (US). Vitamin C 2016 2 11;
Available at: https://ods.od.nih.gov/factsheets/VitaminC-HealthProfessional/. Accessed Feb 6,
2018.

(37). Office of Dietary Supplements, National Institutes of Health (US). Vitamin D 2016 2 11;
Available at: https://ods.od.nih.gov/factsheets/VitaminD-HealthProfessional/. Accessed Feb 6,
2018.

(38). Office of Dietary Supplements, National Institutes of Health (US). Vitamin K 2016 2 11;
Available at: https://ods.od.nih.gov/factsheets/VitaminK-HealthProfessional/. Accessed Feb 6,
2018.

(39). Office of Dietary Supplements, National Institutes of Health (US). Zinc 2016 2 11; Available at:
https://ods.od.nih.gov/factsheets/Zinc-HealthProfessional/. Accessed Feb 6, 2018.

(40). Office of Dietary Supplements, National Institutes of Health (US). Riboflavin 2016 2 11;
Available at: https://ods.od.nih.gov/factsheets/Riboflavin-HealthProfessional/. Accessed Mar 1,
2018.

Brigham et al. Page 10

Curr Pediatr Rep. Author manuscript; available in PMC 2019 June 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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/

A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

Brigham et al. Page 11

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)

Curr Pediatr Rep. Author manuscript; available in PMC 2019 June 01.

• Abstract

Introduction
What is known about ARFID?
Clinical presentation.
Epidemiology.
Contributing factors.
Evaluation
Medical evaluation.
Psychological evaluation.
Treatment
Medical.
Psychological treatment.
Psychiatric medications.
Conclusions
References
Table 1:

© 2016

Norris et al

. This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php
and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you

hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission
for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).

Neuropsychiatric Disease and Treatment 2016:12 213–

218

Neuropsychiatric Disease and Treatment

Dovepress

submit your manuscript | www.dovepress.com

Dovepress
213

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 mnorris@cheo.on.ca

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

http://www.dovepress.com/permissions.php

https://www.dovepress.com/terms.php

http://creativecommons.org/licenses/by-nc/3.0/

https://www.dovepress.com/terms.php

www.dovepress.com

www.dovepress.com

www.dovepress.com

http://dx.doi.org/10.2147/NDT.S82538

mailto:mnorris@cheo.on.ca

Neuropsychiatric Disease and Treatment 2016:12submit your manuscript | www.dovepress.com
Dovepress

Dovepress

214

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

www.dovepress.com

www.dovepress.com

www.dovepress.com

Neuropsychiatric Disease and Treatment 2016:12 submit your manuscript | www.dovepress.com
Dovepress

Dovepress

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

www.dovepress.com

www.dovepress.com

www.dovepress.com

Neuropsychiatric Disease and Treatment 2016:12submit your manuscript | www.dovepress.com
Dovepress
Dovepress

216

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

www.dovepress.com

www.dovepress.com

www.dovepress.com

Neuropsychiatric Disease and Treatment 2016:12 submit your manuscript | www.dovepress.com
Dovepress
Dovepress

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.

References
1. American Psychiatric Association. Diagnostic and Statistical Manual of

Mental Disorders. 5th ed. Arlington, VA: American Psychiatric Publishing;
2013.

2. Bryant-Waugh R, Markham L, Kreipe RE, Walsh BT. Feeding and eat-
ing disorders in childhood. Int J Eat Disord. 2010;43(2):98–111.

3. Nationalpost.com. Picky eaters could join ranks of mentally ill. Available
from: http://news.nationalpost.com/news/canada/picky-eaters-could-
join-ranks-of-mentally-ill. Accessed September 15, 2015.

4. Dovey TM, Staples PA, Gibson EL, Halford JC. Food neophobia
and ‘picky/fussy’ eating in children: a review. Appetite. 2008;50:
181–193.

5. Addessi E, Galloway AT, Visalberghi E, Birch LL. Specific social
influences on the acceptance of novel foods in 2–5-yearold children.
Appetite. 2005;45:264–271.

6. Cashdan E. A sensitive period for learning about food. Human Nature.
1994;5:279–291.

7. McFarlane T, Pliner P. Increased willingness to taste novel foods: effects
of nutrition and taste information. Appetite. 1997;28:227–238.

8. Marchi M, Cohen P. Early childhood eating behaviors and adolescent
eating disorders. J Am Acad Child Adolesc Psychiatry. 1990;29:
112–117.

9. Mascola AJ, Bryson SW, Agras WS. Picky eating during childhood:
a longitudinal study to age 11 years. Eat Behav. 2010;11:253–257.

10. Dubois L, Farmer A, Girard M, Peterson K, Tatone-Tokuda F. Problem
eating behaviors related to social factors and body weight in preschool
children: a longitudinal study. Int J Behav Nutr Phys Act. 2007;4:9.

11. Carruth BR, Ziegler PJ, Gordon A, Barr SI. Prevalence of picky eaters
among infants and toddlers and their caregivers’ decisions about offer-
ing a new food. J Am Diet Assoc. 2004;104:s57–s64.

12. Micali N, Simonoff E, Elberling H, Rask CU, Olsen EM, Skovgaard AM.
Eating patterns in a population-based sample of children aged 5 to
7 years: association with psychopathology and parentally perceived
impairment. J Dev Behav Pediatr. 2011;32:572–580.

13. Cardona Cano S, Tiemeier H, Van Hoeken D, et al. Trajectories of picky
eating during childhood: a general population study. Int J Eat Disord.
2015;48(6):570–579.

14. Nicholls DE, Lynn R, Viner RM. Childhood eating disorders: British
national surveillance study. Br J Psychiatry. 2011;198(4):295–301.

15. Pinhas L, Morris A, Crosby RD, et al. Incidence and age-specific presen-
tation of restrictive eating disorders in children: a Canadian Paediatric
Surveillance Program study. Arch Pediatr Adolesc Med. 2011;165(10):
895–899.

16. Kurz S, van Dyck Z, Dremmel D, Munsch S, Hilbert A. Early-
onset restrictive eating disturbances in primary school boys and girls.
Eur Child Adolesc Psychiatry. 2015;24(7):779–785.

17. Norris ML, Robinson A, Obeid N, Harrison M, Spettigue W,
Henderson K. Exploring avoidant/restrictive food intake disorder in
eating disordered patients: a descriptive study. Int J Eat Disord. 2014;
47(5):495–499.

18. Fisher MM, Rosen DS, Ornstein RM, et al. Characteristics of avoidant/
restrictive food intake disorder in children and adolescents: a “new
disorder” in DSM-5. J Adolesc Health. 2014;55(1):49–52.

19. Ornstein RM, Rosen DS, Mammel KA, et al. Distribution of eating
disorders in children and adolescents using the proposed DSM-5 cri-
teria for feeding and eating disorders. J Adolesc Health. 2013;53(2):
303–305.

20. Nicely TA, Lane-Loney S, Masciulli E, Hollenbeak CS, Ornstein RM.
Prevalence and characteristics of avoidant/restrictive food intake disor-
der in a cohort of young patients in day treatment for eating disorders.
Int J Eat Disord. 2014;2(1):21.

21. Forman SF, McKenzie N, Hehn R, et al. Predictors of outcome at 1 year
in adolescents with DSM-5 restrictive eating disorders: report of the
national eating disorders quality improvement collaborative. J Adolesc
Health. 2014;55(6):750–756.

22. Toufexis MD, Hommer R, Gerardi DM, et al. Disordered eating and
food restrictions in children with PANDAS/PANS. J Child Adolesc
Psychopharmacol. 2015;25(1):48–56. doi:10.1089/cap.2014.0063.

23. Eddy KT, Thomas JJ, Hastings E, et al. Prevalence of DSM-5 avoidant/
restrictive food intake disorder in a pediatric gastroenterology healthcare
network. Int J Eat Disord. 2015;48(5):464–470. doi:10.1002/eat.22350.

24. Strandjord SE, Sieke EH, Richmond M, Rome ES. Avoidant/
Restrictive Food Intake Disorder: Illness and Hospital Course in
Patients Hospitalized for Nutritional Insufficiency. J Adolesc Health.
2015;57(6):673–678.

www.dovepress.com

www.dovepress.com

www.dovepress.com

http://news.nationalpost.com/news/canada/picky-eaters-could-join-ranks-of-mentally-ill

http://news.nationalpost.com/news/canada/picky-eaters-could-join-ranks-of-mentally-ill

Neuropsychiatric Disease and Treatment

Publish your work in this journal

Submit your manuscript here: http://www.dovepress.com/neuropsychiatric-disease-and-treatment-journal

Neuropsychiatric Disease and Treatment is an international, peer-
reviewed journal of clinical therapeutics and pharmacology focusing
on concise rapid reporting of clinical or pre-clinical studies on a
range of neuropsychiatric and neurological disorders. This journal
is indexed on PubMed Central, the ‘PsycINFO’ database and CAS,

and is the official journal of The International Neuropsychiatric
Association (INA). The manuscript management system is completely
online and includes a very quick and fair peer-review system, which
is all easy to use. Visit http://www.dovepress.com/testimonials.php to
read real quotes from published authors.

Neuropsychiatric Disease and Treatment 2016:12submit your manuscript | www.dovepress.com
Dovepress
Dovepress
Dovepress
218
Norris et al

http://www.dovepress.com/neuropsychiatric-disease-and-treatment-journal

http://www.dovepress.com/testimonials.php

www.dovepress.com

www.dovepress.com

www.dovepress.com

www.dovepress.com

1. Publication Info 4:
2. Nimber of times reviewed 2:

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
University of Louisville

Jenna P. Tregarthen
Recovery Record, Inc., San Francisco, California

Kelsie T. Forbush
University of Kansas

Cheri A. Levinson
University of Louisville

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:
cheri.levinson@louisville.edu

T
hi

s
do

cu
m

en
t

is
co

py
ri

gh
te

d
by

th
e

A
m

er
ic

an
P

sy
ch

ol
og

ic
al

A
ss

oc
ia

ti
on

or
on

e
of

it
s

al
li

ed
pu

bl
is

he
rs

.
T

hi
s

ar
ti

cl
e

is
in

te
nd

ed
so

le
ly

fo
r

th
e

pe
rs

on
al

us
e

of
th

e
in

di
vi

du
al

us
er

an
d

is
no

t
to

be
di

ss
em

in
at

ed
br

oa
dl

y.

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:cheri.levinson@louisville.edu

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-

T
hi
s
do
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.

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.

T
hi
s
do
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
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
hi
s
do
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.

180 CHRISTIAN ET AL.

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

think

laxatives

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
hi
s
do
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.

181EATING DISORDER AGE NETWORKS

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

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
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
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.

182 CHRISTIAN ET AL.

http://dx.doi.org/10.1037/abn0000477.supp

http://dx.doi.org/10.1037/abn0000477.supp

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
s
do
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.

183EATING DISORDER AGE NETWORKS

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
hi
s
do
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.

184 CHRISTIAN ET AL.

http://dx.doi.org/10.1037/abn0000477.supp

http://dx.doi.org/10.1037/abn0000477.supp

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.

T
hi
s
do
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.

185EATING DISORDER AGE NETWORKS

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.

T
hi
s
do
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.

186 CHRISTIAN ET AL.

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-

T
hi
s
do
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.

187EATING DISORDER AGE NETWORKS

http://dx.doi.org/10.1037/abn0000477.supp

http://dx.doi.org/10.1037/abn0000477.supp

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.

References

Aardoom, J. J., Dingemans, A. E., Slof Op’t Landt, M. C., & Van Furth,
E. F. (2012). Norms and discriminative validity of the Eating Disorder
Examination Questionnaire (EDE-Q). Eating Behaviors, 13, 305–309.
http://dx.doi.org/10.1016/j.eatbeh.2012.09.002

Blonigen, D. M., Carlson, M. D., Hicks, B. M., Krueger, R. F., & Iacono,
W. G. (2008). Stability and change in personality traits from late
adolescence to early adulthood: A longitudinal twin study. Journal of
Personality, 76, 229 –266. http://dx.doi.org/10.1111/j.1467-6494.2007
.00485.x

Boettcher, H., Brake, C. A., & Barlow, D. H. (2016). Origins and outlook
of interoceptive exposure. Journal of Behavior Therapy and Experimen-
tal Psychiatry, 53, 41–51. http://dx.doi.org/10.1016/j.jbtep.2015.10.009

Borsboom, D. (2017). A network theory of mental disorders. World Psy-
chiatry, 16, 5–13. http://dx.doi.org/10.1002/wps.20375

Bos, F. M., Fried, E. I., Hollon, S. D., Bringmann, L. F., Dimidjian, S.,
DeRubeis, R. J., & Bockting, C. L. H. (2018). Cross-sectional networks
of depressive symptoms before and after antidepressant medication
treatment. Social Psychiatry and Psychiatric Epidemiology, 53, 617–
627. http://dx.doi.org/10.1007/s00127-018-1506-1

Bringmann, L. F., & Eronen, M. I. (2018). Don’t blame the model:
Reconsidering the network approach to psychopathology. Psychological
Review, 125, 606 – 615. http://dx.doi.org/10.1037/rev0000108

Castellini, G., Lo Sauro, C., Mannucci, E., Ravaldi, C., Rotella, C. M.,
Faravelli, C., & Ricca, V. (2011). Diagnostic crossover and outcome
predictors in eating disorders according to DSM–IV and DSM-V pro-
posed criteria: A 6-year follow-up study. Psychosomatic Medicine, 73,
270 –279. http://dx.doi.org/10.1097/PSY.0b013e31820a1838

Cooper, Z., & Dalle Grave, R. (2017). Eating disorders: Transdiagnostic
theory and treatment. In S. G. Hofmann & G. J. G. Asmundson (Eds.),
The Science of Cognitive Behavioral Therapy (pp. 337–357). http://dx
.doi.org/10.1016/B978-0-12-803457-6.00014-3

Cooper, Z., & Shafran, R. (2008). Cognitive behaviour therapy for eating
disorders. Behavioural and Cognitive Psychotherapy, 36, 713–722.
http://dx.doi.org/10.1017/S1352465808004736

Crow, S. J., Peterson, C. B., Swanson, S. A., Raymond, N. C., Specker, S.,
Eckert, E. D., & Mitchell, J. E. (2009). Increased mortality in bulimia
nervosa and other eating disorders. The American Journal of Psychiatry,
166, 1342–1346. http://dx.doi.org/10.1176/appi.ajp.2009.09020247

DuBois, R. H., Rodgers, R. F., Franko, D. L., Eddy, K. T., & Thomas, J. J.
(2017). A network analysis investigation of the cognitive-behavioral
theory of eating disorders. Behaviour Research and Therapy, 97, 213–
221. http://dx.doi.org/10.1016/j.brat.2017.08.004

Elliott, H., Jones, P. J., & Schmidt, U. (2018). Central symptoms predict
post-treatment outcomes and clinical impairment in anorexia nervosa: A
network analysis in a randomized-controlled trial. http://dx.doi.org/10
.31234/OSF.IO/HW2DZ

Epskamp, S., Borsboom, D., & Fried, E. I. (2018). Estimating psycholog-
ical networks and their accuracy: A tutorial paper. Behavior Research
Methods, 50, 195–212. http://dx.doi.org/10.3758/s13428-017-0862-1

Epskamp, S., Cramer, A. O., Waldorp, L. J., Schmittmann, V. D., &
Borsboom, D. (2012). qgraph: Network visualizations of relationships in
psychometric data. Journal of Statistical Software, 48, 1–18.

T
hi
s
do
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.

188 CHRISTIAN ET AL.

http://dx.doi.org/10.1016/j.eatbeh.2012.09.002

http://dx.doi.org/10.1111/j.1467-6494.2007.00485.x

http://dx.doi.org/10.1111/j.1467-6494.2007.00485.x

http://dx.doi.org/10.1016/j.jbtep.2015.10.009

http://dx.doi.org/10.1002/wps.20375

http://dx.doi.org/10.1007/s00127-018-1506-1

http://dx.doi.org/10.1037/rev0000108

http://dx.doi.org/10.1097/PSY.0b013e31820a1838

http://dx.doi.org/10.1016/B978-0-12-803457-6.00014-3

http://dx.doi.org/10.1016/B978-0-12-803457-6.00014-3

http://dx.doi.org/10.1017/S1352465808004736

http://dx.doi.org/10.1176/appi.ajp.2009.09020247

http://dx.doi.org/10.1016/j.brat.2017.08.004

http://dx.doi.org/10.31234/OSF.IO/HW2DZ

http://dx.doi.org/10.31234/OSF.IO/HW2DZ

http://dx.doi.org/10.3758/s13428-017-0862-1

Epskamp, S., & Fried, E. I. (2018). A tutorial on regularized partial
correlation networks. Psychological Methods, 23, 617– 634. http://dx.doi
.org/10.1037/met0000167

Epskamp, S., Maris, G., Waldorp, L. J., & Borsboom, D. (2018). Network
Psychometrics. In P. Irwing, T. Booth, & D. J. Hughes (Eds.), The Wiley
handbook of psychometric testing (pp. 953–986). http://dx.doi.org/10
.1002/9781118489772.ch30

Fairburn, C. G. (2008). Cognitive behavior therapy and eating disorders.
New York, NY: Guilford Press.

Fairburn, C. G., & Beglin, S. J. (1994). Assessment of eating disorders:
Interview or self-report questionnaire? International Journal of Eating
Disorders, 16, 363–370.

Fairburn, C. G., Wilson, G. T., & Schleimer, K. (1993). Binge eating:
Nature, assessment, and treatment. New York, NY: Guilford Press.

Fichter, M. M., & Quadflieg, N. (2007). Long-term stability of eating
disorder diagnoses. International Journal of Eating Disorders, 40, S61–
S66. http://dx.doi.org/10.1002/eat.20443

Forbush, K. T., Siew, C. S. Q., & Vitevitch, M. S. (2016). Application of
network analysis to identify interactive systems of eating disorder psy-
chopathology. Psychological Medicine, 46, 2667–2677. http://dx.doi
.org/10.1017/S003329171600012X

Forbush, K. T., Wildes, J. E., Pollack, L. O., Dunbar, D., Luo, J., Patterson,
K., . . . Watson, D. (2013). Development and validation of the Eating
Pathology Symptoms Inventory (EPSI). Psychological Assessment, 25,
859 – 878. http://dx.doi.org/10.1037/a0032639

Forman, M., & Davis, W. N. (2005). Characteristics of middle-aged
women in inpatient treatment for eating disorders. Eating Disorders: The
Journal of Treatment & Prevention, 13, 231–243. http://dx.doi.org/10
.1080/10640260590932841

Forrest, L. N., Jones, P. J., Ortiz, S. N., & Smith, A. R. (2018). Core
psychopathology in anorexia nervosa and bulimia nervosa: A network
analysis. International Journal of Eating Disorders, 51, 668 – 679. http://
dx.doi.org/10.1002/eat.22871

Fried, E. I., & Cramer, A. O. J. (2017). Moving forward: Challenges and
directions for psychopathological network theory and methodology.
Perspectives on Psychological Science, 12, 999 –1020. http://dx.doi.org/
10.1177/1745691617705892

Fulton, C. L. (2016). Disordered eating across the lifespan of women
[PDF]. Retrieved from https://www.counseling.org/docs/default-source/
vistas/disordered-eating ?sfvrsn�769e4a2c_4

Gadalla, T. M. (2008). Eating disorders and associated psychiatric comor-
bidity in elderly Canadian women. Archives of Women’s Mental Health,
11, 357–362. http://dx.doi.org/10.1007/s00737-008-0031-8

Goldschmidt, A. B., Crosby, R. D., Cao, L., Moessner, M., Forbush, K. T.,
Accurso, E. C., & Le Grange, D. (2018). Network analysis of pediatric
eating disorder symptoms in a treatment-seeking, transdiagnostic sam-
ple. Journal of Abnormal Psychology, 127, 251–264. http://dx.doi.org/
10.1037/abn0000327

Hallquist, M., Wright, A. G. C., & Molenaar, P. C. M. (2019). Problems
with centrality measures in psychopathology symptom networks: Why
network psychometrics cannot escape psychometric theory. Multivariate
Behavioral Research. Advance online publication. http://dx.doi.org/10
.1080/00273171.2019.1640103

Hudson, J. I., & Pope, H. G., Jr. (2018). Evolving perspectives on the
public health burden of eating disorders. Biological Psychiatry, 84,
318 –319. http://dx.doi.org/10.1016/j.biopsych.2018.06.011

Jenkins, P. E., & Price, T. (2018). Eating pathology in midlife women:
Similar or different to younger counterparts? International Journal of
Eating Disorders, 51, 3–9. http://dx.doi.org/10.1002/eat.22810

Lampard, A. M., Tasca, G. A., Balfour, L., & Bissada, H. (2013). An
evaluation of the transdiagnostic cognitive-behavioural model of eating
disorders. European Eating Disorders Review, 21, 99 –107. http://dx.doi
.org/10.1002/erv.2214

Levinson, C. A., Vanzhula, I. A., Brosof, L. C., & Forbush, K. (2018).
Network analysis as an alternative approach to conceptualizing eating
disorders: Implications for research and treatment. Current Psychiatry
Reports, 20, 67– 82. http://dx.doi.org/10.1007/s11920-018-0930-y

Levinson, C. A., Zerwas, S., Calebs, B., Forbush, K., Kordy, H., Watson,
H., . . . Bulik, C. M. (2017). The core symptoms of bulimia nervosa,
anxiety, and depression: A network analysis. Journal of Abnormal
Psychology, 126, 340 –354. http://dx.doi.org/10.1037/abn0000254

Linehan, M. M., & Chen, E. Y. (2005). Dialectical behavior therapy for
eating disorders. In A. Freeman, S. H. Felgoise, C. M. Nezu, A. M.
Nezu, M. A. Reinecke (Eds.), Encyclopedia of Cognitive Behavior
Therapy (pp. 168 –171). http://dx.doi.org/10.1007/0-306-48581-8_50

Luce, K. H., & Crowther, J. H. (1999). The reliability of the Eating
Disorder Examination—Self-Report Questionnaire version (EDE-Q).
International Journal of Eating Disorders, 25, 349 –351. http://dx.doi
.org/10.1002/(SICI)1098-108X(199904)25:3�349::AID-EAT15�3.0
.CO;2-M

Mangweth-Matzek, B., Rupp, C. I., Hausmann, A., Assmayr, K., Mari-
acher, E., Kemmler, G., . . . Biebl, W. (2006). Never too old for eating
disorders or body dissatisfaction: A community study of elderly women.
International Journal of Eating Disorders, 39, 583–586. http://dx.doi
.org/10.1002/eat.20327

Marcus, M. D., Bromberger, J. T., Wei, H.-L., Brown, C., & Kravitz, H. M.
(2007). Prevalence and selected correlates of eating disorder symptoms
among a multiethnic community sample of midlife women. Annals of
Behavioral Medicine: A Publication of the Society of Behavioral Med-
icine, 33, 269 –277. http://dx.doi.org/10.1007/BF02879909

McNally, R. J. (2016). Can network analysis transform psychopathology?
Behaviour Research and Therapy, 86, 95–104. http://dx.doi.org/10
.1016/j.brat.2016.06.006

Mond, J. M., Hay, P. J., Rodgers, B., Owen, C., & Beumont, P. J. (2004).
Validity of the Eating Disorder Examination Questionnaire (EDE-Q) in
screening for eating disorders in community samples. Behaviour Re-
search and Therapy, 42, 551–567. http://dx.doi.org/10.1016/S0005-
7967(03)00161-X

Noordenbos, G., Oldenhave, A., Muschter, J., & Terpstra, N. (2002).
Characteristics and treatment of patients with chronic eating disorders.
Eating Disorders: The Journal of Treatment & Prevention, 10, 15–29.
http://dx.doi.org/10.1080/106402602753573531

Norring, C. E. A., & Sohlberg, S. S. (1993). Outcome, recovery, relapse
and mortality across six years in patients with clinical eating disorders.
Acta Psychiatrica Scandinavica, 87, 437– 444. http://dx.doi.org/10
.1111/j.1600-0447.1993.tb03401.x

Olatunji, B. O., Levinson, C., & Calebs, B. (2018). A network analysis of
eating disorder symptoms and characteristics in an inpatient sample.
Psychiatry Research, 262, 270 –281. http://dx.doi.org/10.1016/j
.psychres.2018.02.027

Patrick, J. H., & Stahl, S. T. (2009). Understanding disordered eating at
midlife and late life. The Journal of General Psychology, 136, 5–20.
http://dx.doi.org/10.3200/GENP.136.1.5-20

Pe, M. L., Kircanski, K., Thompson, R. J., Bringmann, L. F., Tuerlinckx,
F., Mestdagh, M., . . . Gotlib, I. H. (2015). Emotion-network density in
major depressive disorder. Clinical Psychological Science, 3, 292–300.
http://dx.doi.org/10.1177/2167702614540645

Pearson, C. M., Wonderlich, S. A., & Smith, G. T. (2015). A risk and
maintenance model for bulimia nervosa: From impulsive action to
compulsive behavior. Psychological Review, 122, 516 –535. http://dx
.doi.org/10.1037/a0039268

Peat, C. M., Peyerl, N. L., & Muehlenkamp, J. J. (2008). Body image and
eating disorders in older adults: A review. The Journal of General
Psychology, 135, 343–358. http://dx.doi.org/10.3200/GENP.135.4.343-
358

Rodebaugh, T. L., Tonge, N. A., Piccirillo, M. L., Fried, E., Horenstein, A.,
Morrison, A. S., . . . Heimberg, R. G. (2018). Does centrality in a

T
hi
s
do
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.

189EATING DISORDER AGE NETWORKS

http://dx.doi.org/10.1037/met0000167

http://dx.doi.org/10.1037/met0000167

http://dx.doi.org/10.1002/9781118489772.ch30

http://dx.doi.org/10.1002/9781118489772.ch30

http://dx.doi.org/10.1002/eat.20443

http://dx.doi.org/10.1017/S003329171600012X

http://dx.doi.org/10.1017/S003329171600012X

http://dx.doi.org/10.1037/a0032639

http://dx.doi.org/10.1080/10640260590932841

http://dx.doi.org/10.1080/10640260590932841

http://dx.doi.org/10.1002/eat.22871

http://dx.doi.org/10.1002/eat.22871

http://dx.doi.org/10.1177/1745691617705892

http://dx.doi.org/10.1177/1745691617705892

https://www.counseling.org/docs/default-source/vistas/disordered-eating ?sfvrsn=769e4a2c_4

https://www.counseling.org/docs/default-source/vistas/disordered-eating ?sfvrsn=769e4a2c_4

http://dx.doi.org/10.1007/s00737-008-0031-8

http://dx.doi.org/10.1037/abn0000327

http://dx.doi.org/10.1037/abn0000327

http://dx.doi.org/10.1080/00273171.2019.1640103

http://dx.doi.org/10.1080/00273171.2019.1640103

http://dx.doi.org/10.1016/j.biopsych.2018.06.011

http://dx.doi.org/10.1002/eat.22810

http://dx.doi.org/10.1002/erv.2214

http://dx.doi.org/10.1002/erv.2214

http://dx.doi.org/10.1007/s11920-018-0930-y

http://dx.doi.org/10.1037/abn0000254

http://dx.doi.org/10.1007/0-306-48581-8_50

http://dx.doi.org/10.1002/%28SICI%291098-108X%28199904%2925:3%3C349::AID-EAT15%3E3.0.CO;2-M

http://dx.doi.org/10.1002/%28SICI%291098-108X%28199904%2925:3%3C349::AID-EAT15%3E3.0.CO;2-M

http://dx.doi.org/10.1002/%28SICI%291098-108X%28199904%2925:3%3C349::AID-EAT15%3E3.0.CO;2-M

http://dx.doi.org/10.1002/eat.20327

http://dx.doi.org/10.1002/eat.20327

http://dx.doi.org/10.1007/BF02879909

http://dx.doi.org/10.1016/j.brat.2016.06.006

http://dx.doi.org/10.1016/j.brat.2016.06.006

http://dx.doi.org/10.1016/S0005-7967%2803%2900161-X

http://dx.doi.org/10.1016/S0005-7967%2803%2900161-X

http://dx.doi.org/10.1080/106402602753573531

http://dx.doi.org/10.1111/j.1600-0447.1993.tb03401.x

http://dx.doi.org/10.1111/j.1600-0447.1993.tb03401.x

http://dx.doi.org/10.1016/j.psychres.2018.02.027

http://dx.doi.org/10.1016/j.psychres.2018.02.027

http://dx.doi.org/10.3200/GENP.136.1.5-20

http://dx.doi.org/10.1177/2167702614540645

http://dx.doi.org/10.1037/a0039268

http://dx.doi.org/10.1037/a0039268

http://dx.doi.org/10.3200/GENP.135.4.343-358

http://dx.doi.org/10.3200/GENP.135.4.343-358

cross-sectional network suggest intervention targets for social anxiety
disorder? Journal of Consulting and Clinical Psychology, 86, 831– 844.
http://dx.doi.org/10.1037/ccp0000336

Rome, E. S., & Ammerman, S. (2003). Medical complications of eating
disorders: An update. Journal of Adolescent Health, 33, 418 – 426.
http://dx.doi.org/10.1016/S1054-139X(03)00265-9

Solmi, M., Collantoni, E., Meneguzzo, P., Degortes, D., Tenconi, E., &
Favaro, A. (2018). Network analysis of specific psychopathology and
psychiatric symptoms in patients with eating disorders. International
Journal of Eating Disorders, 51, 680 – 692. http://dx.doi.org/10.1002/eat
.22884

Solmi, M., Collantoni, E., Meneguzzo, P., Tenconi, E., & Favaro, A.
(2019). Network analysis of specific psychopathology and psychiatric
symptoms in patients with anorexia nervosa. European Eating Disorders
Review, 27, 24 –33. http://dx.doi.org/10.1002/erv.2633

Steinberg, L. (2005). Cognitive and affective development in adolescence.
Trends in Cognitive Sciences, 9, 69 –74. http://dx.doi.org/10.1016/j.tics
.2004.12.005

Stice, E., Marti, C. N., & Rohde, P. (2013). Prevalence, incidence, impair-
ment, and course of the proposed DSM–5 eating disorder diagnoses in an
8-year prospective community study of young women. Journal of Ab-
normal Psychology, 122, 445– 457. http://dx.doi.org/10.1037/a0030679

Tiggemann, M., & McCourt, A. (2013). Body appreciation in adult wom-
en: Relationships with age and body satisfaction. Body Image, 10,
624 – 627. http://dx.doi.org/10.1016/j.bodyim.2013.07.003

Tregarthen, J. P., Lock, J., & Darcy, A. M. (2015). Development of a
smartphone application for eating disorder self-monitoring. Interna-

tional Journal of Eating Disorders, 48, 972–982. http://dx.doi.org/10
.1002/eat.22386

Tzoneva, M., Forney, K. J., & Keel, P. K. (2015). The influence of gender
and age on the association between “fat-talk” and disordered eating: An
examination in men and women from their 20s to their 50s. Eating
Disorders: The Journal of Treatment & Prevention, 23, 439 – 454.
http://dx.doi.org/10.1080/10640266.2015.1013396

van Borkulo, C., Boschloo, L., Borsboom, D., Penninx, B. W. J. H.,
Waldorp, L. J., & Schoevers, R. A. (2015). Association of symptom
network structure with the course of depression. Journal of the American
Medical Association Psychiatry, 72, 1219 –1226. http://dx.doi.org/10
.1001/jamapsychiatry.2015.2079

Walsh, B. T. (2013). The enigmatic persistence of anorexia nervosa. The
American Journal of Psychiatry, 170, 477– 484. http://dx.doi.org/10
.1176/appi.ajp.2012.12081074

Wang, S. B., Jones, P. J., Dreier, M., Elliott, H., & Grilo, C. M. (2018).
Core psychopathology of treatment-seeking patients with binge-eating
disorder: A network analysis investigation. Psychological Medicine, 49,
1923–1928. http://dx.doi.org/10.1017/S0033291718002702

Williams, J. M., & Currie, C. (2000). Self-Esteem and Physical Develop-
ment in Early Adolescence. The Journal of Early Adolescence, 20,
129 –149. http://dx.doi.org/10.1177/0272431600020002002

Received February 11, 2019
Revision received August 16, 2019

Accepted August 19, 2019 �

E-Mail Notification of Your Latest Issue Online!

Would you like to know when the next issue of your favorite APA journal will be available
online? This service is now available to you. Sign up at https://my.apa.org/portal/alerts/ and you will
be notified by e-mail when issues of interest to you become available!

T
hi
s
do
cu
m
en
t
is
co
py
ri
gh
te
d
by
th
e
A
m
er
ic
an
P
sy
ch
ol
og
ic
al
A
ss
oc
ia
ti
on
or
on
e
of
it
s
al
li
ed
pu
bl
is
he
rs
.
T
hi
s
ar
ti
cl
e
is
in
te
nd
ed
so
le
ly
fo
r
th
e
pe
rs
on
al
us
e
of
th
e
in
di
vi
du
al
us
er
an
d
is
no
t
to
be
di
ss
em
in
at
ed
br
oa
dl
y.

190 CHRISTIAN ET AL.

http://dx.doi.org/10.1037/ccp0000336

http://dx.doi.org/10.1016/S1054-139X%2803%2900265-9

http://dx.doi.org/10.1002/eat.22884

http://dx.doi.org/10.1002/eat.22884

http://dx.doi.org/10.1002/erv.2633

http://dx.doi.org/10.1016/j.tics.2004.12.005

http://dx.doi.org/10.1016/j.tics.2004.12.005

http://dx.doi.org/10.1037/a0030679

http://dx.doi.org/10.1016/j.bodyim.2013.07.003

http://dx.doi.org/10.1002/eat.22386

http://dx.doi.org/10.1002/eat.22386

http://dx.doi.org/10.1080/10640266.2015.1013396

http://dx.doi.org/10.1001/jamapsychiatry.2015.2079

http://dx.doi.org/10.1001/jamapsychiatry.2015.2079

http://dx.doi.org/10.1176/appi.ajp.2012.12081074

http://dx.doi.org/10.1176/appi.ajp.2012.12081074

http://dx.doi.org/10.1017/S0033291718002702

http://dx.doi.org/10.1177/0272431600020002002

• Eating Disorder Core Symptoms and Symptom Pathways Across Developmental Stages: A Network Analysis

Method
Participants
Measures
EPSI
EDE-Q
Procedure
Results
Networks and Stability
Central Symptoms
EPSI
EDE-Q
EPSI networks
EDE-Q
ANOVA Across Developmental Stages
Discussion
Central Symptoms
Differences Across Development
Limitations
Implications and Future Research
References

Cogni

t

ive-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

Abstrac

t

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. jjthomas@mgh.harvard.edu. 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.

A

u
th

o
r M

a
n
u
scrip

t
A

u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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

Curr Opin Psychiatry. Author manuscript; available in PMC 2019 November 01.

A
u
th

o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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

Thomas et al. Page 3

Curr Opin Psychiatry. Author manuscript; available in PMC 2019 November 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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

Thomas et al. Page 4

Curr Opin Psychiatry. Author manuscript; available in PMC 2019 November 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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

Thomas et al. Page 5

Curr Opin Psychiatry. Author manuscript; available in PMC 2019 November 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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

1. American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5).
American Psychiatric Pub; 2013.

2. Thomas JJ, Lawson EA, Micali N et al. Avoidant/restrictive food intake disorder: a three-
dimensional model of neurobiology with implications for etiology and treatment. Current psychiatry
reports. 2017; 19:54. [PubMed: 28714048]

3 **. Sharp WG, Stubbs KH, Adams H et al. Intensive, manual-based intervention for pediatric feeding
disorders: results from a randomized pilot trial. Journal of pediatric gastroenterology and
nutrition. 2016; 62:658–63.

This randomized wait list controlled trial describes an intensive five-day manualized behavioral

intervention for young children with

ARFID.

Thomas et al. Page 6

Curr Opin Psychiatry. Author manuscript; available in PMC 2019 November 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

[PubMed: 26628445]

4 *. Ornstein RM, Essayli JH, Nicely TA et al. Treatment of avoidant/restrictive food intake disorder in
a cohort of young patients in a partial hospitalization program for eating disorders. International
Journal of Eating Disorders. 2017; 50:1067–74.

This retrospective chart review describes outcomes for children and adolescents with ARFID treated in

a partial hospitalization program for eating disorders, which utilizes techniques from family-

based treatment and cognitive-behavioral therapy.

[PubMed: 28644568]

5. Steen E, Wade TD. Treatment of co‐occurring food avoidance and alcohol use disorder in an adult:
possible avoidant restrictive food intake disorder?. International Journal of Eating Disorders. 2018;
51:373–377. [PubMed: 29394459]

6. Eddy KT, Thomas JJ, Hastings E et al. Prevalence of DSM‐5 avoidant/restrictive food intake
disorder in a pediatric gastroenterology healthcare network. International Journal of Eating
Disorders. 2015; 48:464–70. [PubMed: 25142784]

7. Forman SF, McKenzie N, Hehn R et al. Predictors of outcome at 1 year in adolescents with DSM-5
restrictive eating disorders: report of the national eating disorders quality improvement
collaborative. Journal of Adolescent Health. 2014; 55:750–6. [PubMed: 25200345]

8. Lucarelli J, Pappas D, Welchons L, Augustyn M. Autism spectrum disorder and avoidant/restrictive
food intake disorder. Journal of Developmental & Behavioral Pediatrics. 2017; 38:79–80. [PubMed:
27824638]

9. Lukens CT, Silverman AH. Systematic review of psychological interventions for pediatric feeding
problems. Journal of pediatric psychology. 2014 6 13;39(8):903–17. [PubMed: 24934248]

10. Sharp WG, Volkert VM, Scahill L et al. A systematic review and meta-analysis of intensive
multidisciplinary intervention for pediatric feeding disorders: how standard is the standard of
care?. The Journal of pediatrics. 2017; 181:116–24. [PubMed: 27843007]

11. Fitzpatrick KK, Forsberg SE, Colborn. Family-based therapy for avoidant restrictive food intake
disorder: Families Facing Food Neophobias In: Family Therapy for Adolescent Eating and Weight
Disorders. 1 Loeb K. (Ed.), Le Grange D. (Ed.), Lock J. (Ed.). New York: Routledge; 2015 pp.
276–296

12. Norris ML, Spettigue WJ, Katzman DK. Update on eating disorders: current perspectives on
avoidant/restrictive food intake disorder in children and youth. Neuropsychiatric disease and
treatment. 2016; 12:213–218. [PubMed: 26855577]

13. Thomas JJ, Brigham KS, Sally ST et al. Case 18–2017—an 11-year-old girl with difficulty eating
after a choking incident. New England journal of medicine. 2017; 376:2377–86. [PubMed:
28614676]

14. Lesser J, Eckhardt S, Ehrenreich-May J, et al. Integrating family based treatment with the unified
protocol for the transdiagnostic treatment of emotional 351 disorders: a novel treatment for
avoidant restrictive food intake disorder. Clinical Teaching Day presentation at the International
Conference on Eating Disorders; 2017; Prague, Czech Republic.

15. Sadeh-Sharvit S, Robinson A, Lock J. FBT-ARFID for younger patients: lessons from a
randomized controlled trial. Workshop presented at the International Conference on Eating
Disorders; 2018; Chicago, Illinois.

16. Murphy J, Zlomke KR. A behavioral parent-training intervention for a child with avoidant/
restrictive food intake disorder. Clinical Practice in Pediatric Psychology. 2016; 4:23–34.

17. Fischer AJ, Luiselli JK, Dove MB. Effects of clinic and in-home treatment on consumption and
feeding-associated anxiety in an adolescent with avoidant/restrictive food intake disorder. Clinical
Practice in Pediatric Psychology. 2015; 3:154–166.

18. Bryant Waugh R Avoidant restrictive food intake disorder: an illustrative case example.
International Journal of Eating Disorders. 2013; 46:420–3. [PubMed: 23658083]

19. King LA, Urbach JR, Stewart KE. Illness anxiety and avoidant/restrictive food intake disorder:
cognitive-behavioral conceptualization and treatment. Eating behaviors. 2015; 19:106–9.
[PubMed: 26276708]

Thomas et al. Page 7

Curr Opin Psychiatry. Author manuscript; available in PMC 2019 November 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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 avoidant/restrictive food intake disorder:
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.

Thomas et al. Page 8

Curr Opin Psychiatry. Author manuscript; available in PMC 2019 November 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

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.

Thomas et al. Page 9

Curr Opin Psychiatry. Author manuscript; available in PMC 2019 November 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

Figure 1.

Cognitive-behavioral model of avoidant/restrictive food intake disorder

Thomas et al. Page 10

Curr Opin Psychiatry. Author manuscript; available in PMC 2019 November 01.
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t
A
u
th
o
r M
a
n
u
scrip
t

Thomas et al. Page 11

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

Curr Opin Psychiatry. Author manuscript; available in PMC 2019 November 01.

• Abstract

Introduction
Available data on the treatment of ARFID
Family-based treatment and parent training
Cognitive-behavioral approaches
Hospital-based re-feeding including tube feeding
Adjunctive pharmacotherapy
Summary of available data
The cognitive-behavioral formulation of ARFID
Cognitive-behavioral therapy for ARFID (CBT-AR)
Conclusion and future directions
References
Figure 1.
Table 1.

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.