The Wiley Handbook of Eating Disorders, First Edition. Edited by Linda Smolak and Michael P. Levine.
© 2015 John Wiley & Sons, Ltd. Published 2015 by John Wiley & Sons, Ltd.
Screening for Eating Disorders: An
Updated Guide
Rachel F. Rodgers and Debra L. Franko
Department of Counseling and Applied Educational Psychology,
Northeastern University, USA
38
While base rates of eating disorders (EDs) in the general population are relatively low (see
Chapters 5 & 37), early identification is strongly associated with better prognosis (Becker,
Franko, Nussbaum, & Herzog, 2004). Furthermore, subthreshold disorders are associated
with high levels of distress, and identifying individuals suffering from partial forms of EDs
may provide a target for early intervention (Becker et al., 2004). While the literature is not
fully convergent, it has been suggested that subthreshold forms of EDs may constitute
­precursors of full‐syndrome EDs, at least among certain groups (Stice, Ng, & Shaw, 2010).
Early referral may therefore assist with both improved prognosis and prevention of
­progression. In addition to early referral, screening for EDs may be conducted with the
intention of better targeting an intervention, or establishing prevalence data. Screening
tools therefore need to provide accurate information regarding ED status, but also be
­suitable for use with large groups such as school or university settings, to provide national
prevalence data (e.g., Youth Behavior Risk Survey). Developing accurate screens may
­therefore contribute to better targeting of existing resources and improving the mental
health of individuals suffering from or at risk for EDs.
Properties of Screening Instruments:
How to Know When a Screening Tool is Useful
An important requirement for a screening instrument is validity, and in particular criterion
validity, defined as how well the screen identifies real cases and non‐cases. The criterion validity
of a screening instrument can be determined by comparing the results obtained with the
screen to the results obtained using a “gold standard” test in the same population, that is, the
best available test at the time.
Rodgers, R. F., & Franko, D. L. (2015). Screening for eating disorders: An updated guide. In U. Chichester, L. Smolak, & M. P. Levine (Eds.), The Wiley handbook of eating
disorders (Vol. 2, pp. 509–523). Chichester, UK: John Wiley & Sons.
510	 Rachel F. Rodgers and Debra L. Franko
Sensitivity and Specificity
Sensitivity and specificity are two indices of a scale’s diagnostic performance, with high values
indicating that the scale is highly accurate at classifying cases and non‐cases in the correct
­category. Thus, an instrument with low sensitivity and specificity would both “miss” some of
the individuals who actually should have the diagnosis, and misclassify healthy individuals
(false positives). The sensitivity of a screening instrument refers to the proportion of cases
accurately detected, that is, the proportion of true positives (i.e., cases) correctly identified by
the screen. In other words, sensitivity tells us the proportion of people who should have been
identified as having an ED who are identified as having an ED.
The specificity refers to the proportion of true negatives identified by the screen. Negatives
are people who do not suffer from the disorder, in this case EDs. True negatives are those
identified as not having the disorder who don’t, while false negatives are those who actually
have an ED but are identified as healthy. Thus it assesses the proportion of healthy people who
do not have an ED who are classified as not having an ED. The specificity is equal to the
number of non‐cases correctly identified by the screen over the number of “true” non‐cases as
determined by the gold standard.
Importantly, there are no fixed guidelines for what constitutes acceptable sensitivity and
specificity. Values around 80% are generally considered good; however, it has been suggested
that among low‐prevalence disorders such as EDs the sensitivity and specificity should be close
to 90% (Williams, Hand, & Tarnopolsky, 1982).
Positive and Negative Predictive Value
The specificity and sensitivity of a test are useful parameters in that they respectively indicate
how many individuals will be correctly classified as healthy or presenting the diagnosis.
However, sometimes it may be more useful to know how many of the cases identified by a
screening test are true cases. In other words, is the screening measure overinclusive in the
cases it identifies, or on the contrary, too narrow? For example, are people who are healthy
being mistakenly ­identified as having EDs? Positive and negative predictive values address
such questions.
The positive predictive value refers to the proportion of individuals who are identified as
cases by the screen who actually are cases. Thus it evaluates the capacity of the test to include
only real cases as cases and not be overinclusive. The positive predictive value is highly
dependent on the prevalence of the disorder. A correlate of the importance of prevalence in
determining positive and negative predictive values is that for low‐prevalence disorders, such
as anorexia nervosa (AN), the positive predictive value can be very low even when sensitivity
and specificity are high (Jacobi, Abascal, & Taylor, 2004). The negative predictive value correspondingly
refers to the proportion of non‐cases who are correctly identified as healthy by
the screen. It evaluates the capacity of the measure to capture all of the cases.
Depending on the objective of the screening, it may be desirable to maximize different
properties. In the case of screening for cases for treatment, for example, it is desirable to minimize
the number of falsely identified negatives, thus increasing sensitivity, so as to be sure not
to miss cases. In the context of wide screening for risk factors for EDs, however, such as might
be conducted as an initial step on a multiphase screening program, a screening measure should
minimize the proportion of false positives among those scoring above the cut‐offs (i.e., the
positive predictive value should be maximized) to reduce the number of interviews to be
­carried out in the second phase.
	 Screening for Eating Disorders: An Updated Guide	 511
Caution in the Use of Screening Instruments for ED
In their review, Jacobi et al. (2004) called for caution in the use of screening instruments,
identifying a number of limitations of the available instruments, including an overwhelming
focus on diagnosis rather than on identifying high‐risk individuals. Jacobi et al. also questioned
the external validity of existing screens, in particular their usefulness among diverse populations.
They suggested the use of a two‐stage procedure that would begin with an initial broad
screen with an instrument designed to assess risk status, such as the Weight Concerns Scale
(Killen et al., 1993), followed by the administration of a more specific diagnostic instrument,
such as the Eating Disorder Examination Questionnaire (Mond, Hay, Rodgers, Owen, &
Beumont, 2004; see also Chapters 9 & 40), to those screening positive on the initial measure.
Ideally, individuals identified as cases would then be referred for further evaluation and potential
treatment. Although Jacobi et al.’s (2004) in‐depth review was conducted over a decade
ago, in many cases their criticisms are still valid.
Screening for Cases
Widely Used Screening Tools
Eating Attitudes Test (EAT) Both the original 40‐item version of the EAT (Garner &
Garfinkel, 1979), as well as the shorter 26‐item version (Garner, Olmsted, Bohr, & Garfinkel,
1982), have been extensively used as screening instruments for EDs. Cut‐off scores—defined
as the score that identifies individuals warranting further evaluation for EDs or subclinical
forms—of 30 and 20 have been established for the EAT‐40 and EAT‐26, respectively
(Garner et al., 1982). Early studies of the EAT highlighted its low positive predictive power,
particularly for classifying cases of AN (Mann et al., 1983). It was, however, suggested that
this failing might stem from changes in diagnostic criteria, as the EAT was developed at a
time when eating disorders were not included the Diagnostic and Statistical Manual of
Mental Disorders (DSM), and the clinical population included in the initial validation met
the Research and Diagnostic Criteria established by Feighner et al. (1972; cited in Spitzer,
Endicott, & Robins, 1978), which were very different from those used in DSM‐III (3rd ed.;
American Psychiatric Association, 1980; Mintz & O’Halloran, 2000). In a later validation
study of 136 college women using the DSM‐IV (American Psychiatric Association, 1994)
ED criteria, the EAT‐40 and EAT‐26 demonstrated a sensitivity of 77%, specificity of 95%
and 94% respectively, positive predictive power of 82% and 79% respectively, and negative
predictive power of 93% and 94% respectively (Mintz & O’Halloran, 2000). These findings
suggested that the EAT may in fact be a useful instrument for differentiating between individuals
with EDs, regardless of diagnosis, and those without. The EAT has been widely
translated and is available in Arabic, Brazilian, Chinese, French, Greek, Italian, Japanese,
Portuguese, Spanish, and Turkish.
Eating Disorder Examination Questionnaire (EDE‐Q)  The EDE‐Q (Mond et al., 2004) is a
36‐item self‐report questionnaire derived from the DSM‐IV (American Psychiatric Association,
1994) criteria for EDs, assessing eating behaviors over the last 28 days. As noted previously,
the interview version of the EDE is one of the gold standard instruments often used in the
validation of screening instruments (Cooper & Fairburn, 1987). A global score can be calculated
as well as four subscales: Restraint, Weight Concerns, Shape Concerns, and Eating
512	 Rachel F. Rodgers and Debra L. Franko
Concerns. An initial analysis identified a cut‐off score of 56 on the summed total score
(2.3 on the global score). Using this cut‐off among a community sample of 208 young
women resulted in a sensitivity of 92%, specificity of 86%, and positive predictive value of 30%
(Mond et al., 2004). Including two extra criterion items, namely the frequency of objective
binge episodes and exercising for weight/shape reasons at least once a week, in addition to
the cut‐off score resulted in an increase in positive predictive value to 56%. In a later examination
of the properties of the EDE‐Q among 25 ED cases, analysis suggested 2.8 on the
global scale as the optimum cut‐off point, resulting in a sensitivity of 96%, specificity of 56%,
and positive predictive value of 30% (Mond et al., 2008). Lowering the cut‐off score to 1.61,
so as to increase sensitivity, resulted in a value of 92% but did not affect the specificity (56%)
and positive predictive value (30%).
The usefulness of the EDE‐Q in relation to the proposed DSM‐5 (American Psychiatric
Association, 2013) criteria (see Chapters 8–11) has also been explored. In a recent study
validating the EDE‐Q against the EDE‐interview version among 217 treatment‐seeking
individuals, Berg et al. (2012) reported that when using the proposed DSM‐5 criteria, the
EDE‐Q demonstrated sensitivity ranging from 36.8% to 80.8% according to the diagnosis,
specificity ranging from 77.3% to 98%, positive predictive values ranging from 41.2% to
81.5%, and negative predictive values ranging from 76.5% to 98.5%. The EDE‐Q performed
poorest for binge eating disorder (BED), but reasonably well for AN, bulimia nervosa (BN),
and eating disorders not otherwise specified (ED‐NOS).
Fairburn, Cooper, Doll, and Davies (2005) explored the longitudinal predictive validity of
the EDE‐Q among 2,992 young women who screened positive for dieting but did not have a
present or past ED. The women were contacted every 6 months over a 2‐year period to assess
present ED symptomatology. Based on their findings, the authors developed an eight‐item
screening instrument, which included seven items from the EDE‐Q, as well as body mass
index (BMI). Using this screening instrument, sensitivity ranged from 69.5% to 79% and specificity
from 52% to 76%, depending on the decision tree used, with the final survey therefore
displaying good sensitivity and specificity of 79% and 76% respectively. This brief screening
instrument therefore appears useful in detecting dieting young women at risk of developing a
future ED. The EDE‐Q has been translated into many languages including Spanish, Fijian,
and Turkish.
Bulimia Test‐Revised (BULIT‐R)  The BULIT‐R (Thelen, Farmer, Wonderlich, & Smith,
1991) is a 28‐item self‐report ­measure designed to assess the presence and degree of
bulimic symptomatology according to the DSM‐III‐R (American Psychiatric Association,
1987). Using a cut‐off score of 104, initial examinations of the BULIT‐R in a sample of 23
women with BN versus 153 controls, as well as a second sample of 53 subjects with scores
above and below the cut‐off, revealed rates of sensitivity of 83% and 62% respectively, and
a specificity of 96% (Thelen et al., 1991). A second study explored the properties of the
BULIT‐R among 243 female college students (Welch, Thompson, & Hall, 1993). Using
the original cut‐off of 104, the sensitivity of the scale was 80%, the specificity was 99.5%,
the positive predictive value was 80%, and the negative predictive value was 99.5%. In order
to increase the positive predictive value, the authors proposed a new cut‐off score of 98.
Using this threshold, the measure’s sensitivity was 100%, the positive predictive value was
71.3%, and the negative ­predictive value was 100%. A later validation study using DSM‐IV
diagnostic criteria for BN and the initial cut‐off score of 104 in a sample of 147 women
	 Screening for Eating Disorders: An Updated Guide	 513
revealed a sensitivity of 91%, a specificity of 96%, a positive predictive value of 81%, and a
negative predictive value of 98% (Thelen, Mintz, & Vander Wal, 1996). Taken together,
these data indicate that the BULIT is a useful and valid screen for identifying bulimic symptomatology.
The BULIT has been translated into Korean and Spanish.
SCOFF  The SCOFF (Morgan, Reid, & Lacey, 1999) is a five‐item (Yes/No) screening instrument
focusing on the core features of AN and BN:
•	 Sick (self‐induced vomiting);
•	 Control (loss of control);
•	 One stone (weight loss of 14 lb [6.35 kg]);
•	 Fat (feelings of fatness);
•	 Food (preoccupation with food).
In an initial examination among 116 patients with EDs and 96 controls, the threshold of
two positive answers to SCOFF questions had 100% sensitivity for detecting AN or BN and an
87.5% specificity (Morgan et al., 1999). Confirmation of the two positives cut‐off came from
a study comparing the SCOFF and the EDE‐Q in a sample of 257 primary care patients, which
reported a sensitivity of 72% and specificity of 81% (Mond et al., 2008).
Additional studies have confirmed the high sensitivity and specificity of the SCOFF. An
examination of the properties of the written and orally administered SCOFF in a sample of
178 college students revealed a high level of agreement between these two forms in the prediction
of possible EDs using the two positives cut‐off (Perry et al., 2002). Among 341 female
primary care patients, the questionnaire demonstrated a sensitivity of 86.4% and a specificity
of 89.6% (Luck et al., 2002). Using the cut‐off of two positives, all women confirmed to be
suffering from an ED were detected, in addition to 34 false positives.
Other authors, however, have reported lower levels of sensitivity for the SCOFF. In a sample
of 305 graduate students, the SCOFF demonstrated a sensitivity of only 53.3% with a specificity
of 90.3% (Parker, Lyons, & Bonner, 2005). The resulting positive predictive value was
66.7%, while the proportion of those who were correctly identified as not having an ED by the
screen (NPV) was 88.7%. These findings suggested that the SCOFF may not be as sensitive as
previously suggested among this population. Similarly, among a sample of 1,891 Finnish adolescents,
the agreement between SCOFF ratings and nurse evaluations was low, with only a
20% agreement for students scoring above the two‐positives cut‐off (Hautala et al., 2009).
The authors suggested that among adolescents, when it is preferable to be overinclusive rather
than fail to detect an at‐risk individual, a cut‐off of one positive might be useful. Chinese,
Finnish, French, Italian, Japanese, and Spanish versions of the SCOFF are available.
Less Widely Used Screening Measures
Bulimic Investigatory Test, Edinburgh (BITE)  The BITE (Henderson & Freeman, 1987) is a
36‐item self‐report questionnaire that yields symptom (cut‐off score = 20) and severity subscale
scores (cut‐off = 5), as well as a total score (cut‐off = 25). The validity of the BITE was
assessed in a sample of 55 ED patients and 27 control women (Waller, 1992). Findings revealed
that the BITE performed well in identifying ­restricting AN cases as well as individuals suffering
from BN with and without history of AN; however, the BITE performed poorly (false negative
514	 Rachel F. Rodgers and Debra L. Franko
rate = 60%) in the identification of AN/bulimic subtype. The author cautioned against the use
of the BITE for screening, as it appeared to lack sensitivity, in particular regarding cases of
normal‐weight BN. A number of translations of the BITE exist, including Italian and a
Portuguese version developed among a Brazilian sample.
Eating Disorder Diagnostic Scale (EDDS) The EDDS (Stice, Telch, & Rizvi, 2000) is a
22‐item self‐report measure designed to assess the presence of the DSM‐IV (American
Psychiatric Association, 1994) criteria for AN, BN, and BED. The EDDS was validated
against the EDE in a sample of 367 women aged 13 to 61. For the three disorders, the
EDDS demonstrated a sensitivity ranging from 77% to 93%, a specificity ranging from 96%
to 100%, positive predictive values ranging from 80% to 93%, and negative predictive values
ranging from 95% to 100%. Similarly, strong validity was found in a second study in which
the EDDS was again examined against the EDE in a sample of 443 female adolescents and
young adults, yielding a sensitivity of 88%, specificity of 98%, positive predictive value of
74%, and negative predictive value of 98% (Stice, Fisher, & Martinez, 2004). The validity
of the Dutch version of the EDDS was also evaluated in a sample of 40 ED patients and
45 control undergraduate students (Krabbenborg et al., 2012). The EDE was again used
as the gold standard. The EDDS demonstrated high sensitivity (>95%) and positive predictive
value among patients suffering from AN and BN, but lower sensitivity (57%) and
positive predictive value (80%) among patients suffering from BED. The authors further
identified a cut‐off point of 16.5 to distinguish patients from healthy controls. Together
these findings suggest that the EDDS is a very useful screening tool. It is unclear why it is
not widely used.
Questionnaire for Eating Disorders Diagnosis (Q‐EDD)  The Q‐EDD (Mintz, O’Halloran,
Mulholland, & Schneider, 1997) is a 50‐item self‐report questionnaire, based on the DSM‐
IV (American Psychiatric Association, 1994) diagnostic criteria, that aims to evaluate the
presence of AN, BN, and four types of ED‐NOS (subthreshold bulimia, menstruating
anorexia, nonbingeing bulimia, and binge eating disorder). The Q‐EDD was validated
against a clinical interview and demonstrated a sensitivity of 97%, specificity of 98%, positive
predictive value of 94%, and negative predictive value of 99% in distinguishing between
eating‐disordered individuals all diagnoses combined, and non‐eating‐disordered individuals.
The Q‐EDD has been used in large screening studies among young women (Franko
et al., 2005).
Binge Eating Disorder: The New Addition to DSM‐5
BULIT
The BULIT has been suggested to be well suited to the evaluation of binge eating as it
­contains items assessing compensatory behaviors (Vander Wal, Stein, & Blashill, 2011). In a
sample of 15 individuals suffering from BED and 26 assessed as having neither full‐syndrome
nor subclinical BED, using a cut‐off score of 80, the BULIT demonstrated a sensitivity of
100%, specificity of 96%, positive predictive value of 94%, and negative predictive value of
100%. Although provided by a single study, these findings confirm that the BULIT can
­successfully be used to classify individuals suffering from BED.
	 Screening for Eating Disorders: An Updated Guide	 515
The Patient Health Questionnaire Module for Eating Disorders (PHQ‐ED)
The PHQ‐ED (Spitzer, Kroenke, & Williams, 1999) is composed of six binary (yes/no) items
assessing binge eating and compensatory behaviors, and up to two optional follow‐up ­questions
that are asked only when binge eating or purging has been endorsed. A recent study examined
the properties of the PHQ‐ED as a screening instrument in a sample of 348 adults that included
259 cases of BED, BN, or Recurrent Binge Eating (Striegel‐Moore et al., 2010). The PHQ‐
ED showed excellent sensitivity of 100% across all three diagnoses, and good specificity of
91.7% for BED and BN, and 92.4% for Recurrent Binge Eating. However, the positive ­predictive
value was fairly low, with 10.4% for BED and BN, and 18.5% for Recurrent Binge Eating. The
authors suggested that the low positive predictive value may have been due to the study sample,
which was drawn from a community population with a low prevalence of BED. Clinicians
should be cautious in inferring the likely presence of a disorder from a positive screen, ­particularly
when using the PHQ‐ED in community samples.
Bulimic Investigation Test, Edinburgh (BITE)
The BITE, as described above, has also been explored in the context of screening for BED.
The BITE’s psychometric properties were examined in a sample of 360 consecutive patients
attending an outpatient clinic, using both a cut‐off of 10 and a cut‐off of 20 (Ricca et al.,
2000). With the lower cut‐off, the BITE displayed a sensitivity of 91%, specificity of 51.4%,
positive predictive value of 71.8%, and negative predictive value of 98.2%. Using the higher
cut‐off of 20, the sensitivity decreased to 33.3%, while the specificity increased to 92.0%, with
a positive predictive value of 30.5% and a negative predictive value of 92.9%.
Binge Eating Scale (BES)
The BES (Gormally, Black, Daston, & Rardin, 1982) is a 16‐item self‐report questionnaire,
scored on a 0–3 scale. A cut‐off score of 17 has been established as indicating the presence of
binge eating. In a sample of 125 women attending a weight‐loss program, only 51.8% of those
identified as binge eaters using the BES cut‐off score of 17 had a concordant diagnosis using
the EDE (Greeno, Markus, & Wing, 1995). In a recent study among 473 consecutive patients
presenting for psychological evaluation prior to gastric bypass surgery, using the conventional
cut‐off score of 17, the BES displayed a sensitivity of 94%, specificity of 76%, positive predictive
value of 37%, and negative predictive value of 99% (Grupski et al., 2013). To increase the
positive predictive value, the authors conducted the analysis using a higher cut‐off score of 27.
With this new threshold, the BES displayed a much lower sensitivity of 37%, a specificity of 96%,
a positive predictive value of 56%, and a negative predictive value of 91%. An analysis confirmed
17 as the optimal cut‐off score in order to maximize both sensitivity and specificity.
Questionnaire for Eating and Weight Patterns (QEWP)
The QEWP (Spitzer et al., 1992) is a 13‐item self‐report questionnaire assessing the presence
of BED according to the DSM‐IV (American Psychiatric Association, 1994) criteria. Data
regarding the usefulness of the QEWP as a screening instrument have been mixed. In a sample
of 157 adults screened for a BED treatment study, the QEWP demonstrated a sensitivity of
74% and a specificity of 35%. Using the Structured Clinical Interview for DSM‐IV (SCID) as
516	 Rachel F. Rodgers and Debra L. Franko
a comparison (First, Spitzer, Williams, & Gibbon, 1995), the QEWP demonstrated a ­sensitivity
of 55%, specificity of 80%, and positive predictive value of 79%. Further research is necessary
to clarify the validity of the QEWP.
Overview of Tools for Screening for High‐Risk Individuals
The McKnight Investigators
The McKnight Investigators (2003) conducted a 4‐year longitudinal study of 1,358 high‐
school students. The McKnight Risk Factor Survey IV includes seven different factors: thin‐
body preoccupation and social pressure; substance use; parental influences; general
psychological influences; social support; number of negative life‐events; and school
performance. The items from the thin body preoccupation and social pressure factors were
examined for their usefulness as a potential screen for ED cases. With the aim of deriving the
most parsimonious screening tool, three criteria were derived from four questions:
1	 A score of 4 or 5 in response to “How often have you been on a diet to lose weight?”
2	 A score of 5 in response to “How often does your weight make boys not like you?”
3	 An average score ≥3.5 in response to the two questions: “How often do you change your
eating around boys?” and “How often do you change your eating around girls?”
When considering participants who scored above the cut‐off for any of these three questions,
the screen demonstrated a sensitivity of 72% and a specificity of 80%. The predictive value of a
positive test was 10% (of a base rate of cases of 2.9%), and the predictive value of a negative test
was 99% (of a base rate of non‐cases of 97.1%).
Weight Concerns Scale
Using data from the first wave of a large longitudinal study of 967 sixth‐ and seventh‐grade
girls, Killen et al. (1993) developed a five‐item Weight Concerns measure assessing worry over
weight and body shape, fears of gaining weight, importance of weight, perceived fatness, and
diet history. Their initial analysis revealed that, compared to SCID diagnoses (First et al.,
1995), a score of 57 on this scale yielded a sensitivity of 86% and specificity of 63%. Their measure
demonstrated excellent 7‐month stability and longitudinal validity, as scores were significantly
associated with the onset of ED symptoms 3 years later (Killen et al., 1994). The Weight
Concerns Scale is one of the few screening instruments available to identify high‐risk individuals
rather than cases and is supported by evidence for longitudinal validity.
Stanford‐Washington Eating Disorder Screen (SWED)
The SWED (Wilfley, Agras, & Taylor, 2013) contains 11 items taken from the Weight Concerns
Scale, the EDE‐Q, the EDDS, and the Clinical Impairment Assessment (Bohn et al., 2008). The
scale properties have been examined among college women compared to the SCID and the EDE‐Q,
and the SWED demonstrated high sensitivity and specificity (>90%) for AN and BN when using
DSM‐IV‐TR (American Psychiatric Association, 2000) and DSM‐5 criteria (Wilfley et al., 2013).
Further investigations of the criterion validity of the instrument using DSM‐5 (2013) criteria are
underway, and the SWED appears to be a very promising instrument for screening for ED risk.
	 Screening for Eating Disorders: An Updated Guide	 517
Specific Populations: Children, Adolescents, Athletes, and Men
Children’s Eating Attitudes Test (ChEAT)
The ChEAT is a modified version of the EAT (see above) with language adapted for children
(Vacc & Rhyne, 1987). However, data on the properties of the ChEAT as a screening instrument
are somewhat lacking. One study conducted among 152 preadolescents aged from 8 to
12, testing a variety of potential cut‐offs, suggested 25 as an optimal cut‐off, but concluded that
the sensitivity of the ChEAT was overall somewhat low and varied with age (Erickson & Gerstle,
2007). Using the threshold of 25, overall sensitivity was 36%; however, this increased to 53%
among girls aged between 10 and 12 years. In a sample of 409 girls aged 9–13 years, compared
to the child version of the EDE using the cut‐off score of 20, the ChEAT demonstrated a sensitivity
of 17%, specificity of 98%, positive predictive value of 63%, and negative predictive value of
87% (Colton, Olmsted, & Rodin, 2007). Decreasing the cut‐off score improved the sensitivity,
which reached 76% with a cut‐off of 5; however, the specificity then fell to 59%. Taken together
these findings suggest that the usefulness of the ChEAT as a screening instrument among children
may be limited. Translations of the ChEAT exist in Croatian, Portuguese, and Spanish.
Children’s Binge Eating Disorder Scale (C‐BEDS)
The C‐BEDS (Shapiro et al., 2007) is a seven‐item self‐report questionnaire designed to assess
the core behaviors of BED as defined by Marcus and Kalarchian (2003), including eating in
the absence of hunger, eating in response to strong emotions or external cues, and eating in
secret. Among a sample of 55 children aged 5–13 years, using the SCID as a gold standard,
the C‐BEDS demonstrated a sensitivity of 71% and specificity of 89%. The authors concluded
that the C‐BEDS may be more useful than the SCID for screening for BED in children but
additional evaluations in larger and more diverse samples are warranted.
Athletic Milieu Direct Questionnaire (AMDQ)
Athletes have been reported to be two to three times more at risk for EDs compared to nonathletes
(Bratland‐Sanda & Sundgot‐Borgen, 2013; see also Chapter 35) and may have specific
risk factors (Torstveit, Rosenvinge, & Sundgot‐Borgen, 2008). The AMDQ, a screening
instrument for EDs specifically tailored to athletes, was developed and tested among 149
college athletes (Nagel, Black, Leverenz, & Coster, 2000). The initial pool of 119 items was
pared down to three statistical subsets including 35, 19, and 9 items, respectively. These three
subsets yielded sensitivity values ranging from 80% to 82%, specificity values ranging from
75.27% to 79.57%, positive predictive values ranging from 63.49% to 68.33%, and negative
predictive values ranging from 87.50% to 89.16%, indicating good psychometric properties.
Thus, the AMDQ may prove a highly useful tool among athletes.
Eating Disorder Assessment for Men (EDAM)
EDs are disproportionately diagnosed among women, and the large majority of the assessment
instruments were developed and normed among female populations (see Chapter 37). The
EDAM (Stanford & Lemberg, 2012b), a new instrument for assessing EDs in men, includes
50 self‐report items. The initial factor analysis revealed four underlying factors: BED, Muscle
Dysmorphic Disorder, Body Dissatisfaction, and Disordered Eating. In a subsequent study, a
518	 Rachel F. Rodgers and Debra L. Franko
sample of 108 individuals (78% male) completed the EDAM and the Eating Disorder
Inventory‐3 (EDI‐3; Stanford & Lemberg, 2012a). Criterion validity was not formally
assessed; however, using logistic regression the authors concluded that the EDAM successfully
predicted ED status above and beyond the EDI‐3. Further research on the usefulness of the
EDAM as a screening tool among men is warranted.
The Importance of Setting
Primary Care
General practitioners are in an ideal position to identify EDs that might otherwise go undetected
(Mond et al., 2008). However, EDs often are overlooked and underdiagnosed in primary care
practice, in part due to lack of time and the impact of nonclinical demographic variables such as
ethnicity and gender on the likelihood of being diagnosed (Currin, Schmidt, & Waller, 2007; see
also Chapter 25). One study found that screening was relatively acceptable, with approximately
one half of the female primary‐care patients aged 16–35 years agreeing to be screened (Johnston,
Fornai, Cabrini, & Kendrick, 2007). However, general practitioners were found to be uncertain
of the procedure to follow in the case of a positive screen, and referrals were rarely made. These
data suggest that, while primary care settings provide a highly useful context for screening for
EDs, there is a need for education surrounding EDs among general practitioners.
In a study exploring the comparative usefulness of the SCOFF versus the EDE‐Q in general
practice settings, Mond et al. (2008) concluded that the two instruments had relative merits
according to the situation. In the context of routine screening, the brevity and ease of the
SCOFF might make it more suitable; however, when seeking to confirm suspicion of an ED
diagnosis, the EDE‐Q could be preferable due to its higher specificity and positive predictive
value, as well as the more detailed information provided, which may guide referral. Cotton, Ball,
and Robinson (2003) compared the usefulness, in general practice, of the four‐question Eating
Disorder Screen for Primary Care (ESP) and the SCOFF. They found that, using a cut‐off of two
positive responses, the sensitivity and specificity of the SCOFF were 78% and 88% respectively,
while those of the ESP were 100% and 71%. The authors concluded that, while both instruments
were useful in detecting cases, the ESP performed somewhat better at ruling out potential cases.
Schools
Schools and college campuses provide an ideal setting for screening for EDs, due to the ­practical
advantages of having youths concentrated in one place and the on‐site presence of support staff
(Austin et al., 2008). The first National Eating Disorders Screening Program (NEDSP) was
launched on U.S. college campuses in 1996 as a confidential volunteer two‐stage screening
program for students (Becker, Franko, Speck, & Herzog, 2003). The first stage included a
­written self‐report questionnaire, which was followed by a face‐to‐face interview with a ­counselor
to review responses. In the 1996 wave of NEDSP, 9,069 students from 409 colleges returned
questionnaires, and 5,787 of these (64%) met with a counselor to discuss their responses.
Counselors were provided with a manual for identifying participants reporting potentially
­clinically significant symptoms (purging or binge eating at least once a month or significant
­distress), and were instructed to then make an appropriate referral for further ­evaluation and
treatment, with three possible outcomes: no referral at this time, professional evaluation, and
professional evaluation‐urgent. Of the 5,787 program participants who met with a counselor,
	 Screening for Eating Disorders: An Updated Guide	 519
4,398 (76%) met the criteria for clinically significant symptoms and were therefore referred
for professional evaluation, including 71 (1.2%) who were referred for urgent evaluation.
Subsequently NEDSP was successfully extended to high schools, and in 2000 over 35,000
high‐school students from 152 schools completed a NEDSP screening measure, including
attitudinal and behavioral questions and the EAT‐26 (Austin et al., 2008). The NEDSP
screening measure was compared against the EAT within each gender separately (Haines et al.,
2011). Among girls, the combination of the attitudinal and behavioral items performed well,
with sensitivity ranging from 88% to 91%, specificity ranging from 73% to 82%, positive predictive
values ranging from 36% to 45%, and negative predictive value = 98%. Among boys, the
combination of attitudinal and behavioral items also performed well, although the positive
predictive values were somewhat low: sensitivity ranging from 88% to 91%, specificity ranging
from 87% to 94%, positive predictive values ranging from 22% to 36%, and negative predictive
value = 99%. The authors reiterated the recommendations of Jacobi et al. (2004) that screening
take place in two phases, with an initial screening (e.g., using the NEDSP screen) followed
by a more specific instrument.
Cultural and Ethnic Considerations
Rates of EDs have been found to vary according to ethnicity and cultural context (Franko,
Becker, Thomas, & Herzog, 2007; see also Chapters 23 & 25); however, to date, there has
been little focus on the impact of culture or race and ethnicity in screening for EDs. As
previously noted, the overwhelming majority of existing assessment instruments for EDs
were developed among White English‐speaking young women. While many of these scales
have been translated and validated in different languages and different cultural contexts, it
should not be assumed that they perform identically across cultural contexts (see
Chapter 16). For example, Mumford, Whitehouse, and Choudry (1992) validated the EAT
among a sample of 369 schoolgirls in Pakistan and reported that, despite a factor structure
almost identical to that of the original instrument, the optimal cut‐off score might be lower
among this population. Similarly, a validation of the EAT among a sample of 67 patients
suffering from BN and 109 patients suffering from AN in Hong Kong revealed that up to
41.5% of patients with typical AN scored below the traditional cut‐off score on the EAT,
suggesting that a much lower cut‐off score would be appropriate among this population
(Lee, Kwok, Liau, & Leung, 2002). Furthermore, the presentation of AN in this sample
was somewhat different to that usually seen in Western countries, with a high proportion
of patients described as non‐fat phobic, who attributed their restriction to reasons other
than fear of fatness. These considerations are not well assessed by the items of the EAT,
which focus strongly on fear of fatness as a core dimension of AN. Taken together, these
studies suggest that existing screening measures for EDs may indeed be ethnocentric, and
should only be transposed to other cultural contexts with caution.
Regarding race and ethnicity, findings from the high‐school NEDSP in 2000 documented
few ethnic differences in the prevalence of EDs (Austin et al., 2008). The authors concluded
that screening for EDs was necessary in schools with and without ethnic diversity and argued
that targeting specific ethnic groups for screening would be inappropriate. The necessity of
screening among all ethnic groups is particularly important in view of findings that Native
Americans and Hispanic students were less likely to be referred than White students with
comparable scores in the national college screening study (Becker et al., 2003).
520	 Rachel F. Rodgers and Debra L. Franko
Conclusions and Future Directions
Screening for EDs has a number of benefits for the mental health of individuals suffering from
or at risk for EDs. While a large number of screening instruments have been developed to date,
many of them still lack evidence of validity, both criterion and external. In addition, screening
instruments tailored to particular groups such as athletes or males are lacking. Overall, the last
decade has seen little effort to improve, refine, or seek to better establish the validity of existing
screening instruments. In view of these shortcomings, the field would benefit from increased
consensus regarding the use of screening instruments so as to facilitate the ­examination of
­psychometric properties as well as to conduct comparisons in terms of prevalence.
The success of programs such as NEDSP also highlights the usefulness of routine screening in
school and college settings. However, widespread screening would give rise to a number of
­challenges, including the processing of the screening forms, and the allocation of necessary resources
for the follow‐up of potential cases for referral and treatment where necessary. The ethical implications
of widespread screening in the absence of sufficient resources downstream are numerous.
In conclusion, screening offers a valuable opportunity for the early identification of EDs;
however, efforts to further explore the psychometric properties of existing instruments and
develop appropriate measures for specific vulnerable populations are warranted. In addition,
greater efforts should be made to screen for EDs among youth in school and college settings.
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