REVIEW
Reducing Eating Disorder Symptoms and Risk Factors
Using the Internet: A Meta-Analytic Review
Tiffany Melioli, MA1
*
Stephanie Bauer, PhD2
Debra L. Franko, PhD3
Markus Moessner, PhD2
Fikret Ozer, MA2
Henri Chabrol, MD, PhD1
Rachel F. Rodgers, PhD3,4
ABSTRACT
Objective: The purpose of this metaanalytic
review was, first, to evaluate
the efficacy of Internet-based programs
in decreasing eating disorder (ED)
symptoms, and, second, to identify
moderator variables these effects.
Method: Twenty studies were identified
and between-group effect sizes were calculated
for ED symptoms and risk factors.
Results: Compared with control conditions,
Internet-based programs successfully
decreased body dissatisfaction
(d 5 0.28, 95% CI [0.15–0.41], p < .001),
internalization of the thin ideal
(d 5 0.36, 95% CI [0.07–0.65], p < .05),
shape and weight concern (d 5 0.42, 95%
CI [0.13–0.71], p < .05), dietary restriction
(d 5 0.36, 95% CI [0.23–0.49], p < .001),
drive for thinness (d 5 0.47, 95% CI
[0.33–0.60], p < .001), bulimic symptoms
(d 5 0.31, 95% CI [0.20–0.41], p < .001),
purging frequency (d 5 0.30, 95% CI
[0.02–0.57], p < .05), and negative affect
(d 5 0.32, 95% CI [0.12–0.52], p < .001).
Moderator analyses revealed no impact
of data analytic strategy on intervention
effects. Similarly, participant risk status
was not a moderator for most outcomes.
Discussion: Internet-based programs
are successful in decreasing ED symptoms
and risk factors with small to
moderate between-group effect sizes.
Keywords: eating disorders; intervention;
prevention; internet; risk
factors; moderator
Resumen
Objetivo: El proposito de esta revision
meta-analıtica fue, primeramente, evaluar
la eficacia de los programas basados
en internet para disminuir los sıntomas
de trastorno de la conducta alimentaria
(TCA), y segundo, identificar variables
moderadoras de estos efectos.
Metodo: Se identificaron veinte estudios
y se calculo el tama~no del efecto entre
grupos para los sıntomas de TCA y los
factores de riesgo.
Resultados: En comparacion con las
condiciones de control, los programas
basados en Internet redujeron con exito
la insatisfaccion corporal (d 5 0,28; IC
del 95% [0,15-0,41], p <0,001), interiorizacion
del ideal de delgadez (d 5 0.36,
95% CI [0,07 hasta 0,65], p <0,05), la
preocupacion por el peso y la figura
(d 5 0,42; IC del 95% [0,13 a 0,71],
p <0,05), la restriccion dietetica
(d 5 0,36; IC del 95% [0,23 a 0,49], p
<0,001), la busqueda de la delgadez
(d 5 0,47; IC del 95% [0,33 a 0,60], p
<0,001), los sıntomas bulımicos (d 5.
31; IC del 95% [0,20-0,41], p <0,001), la
frecuencia de purgacion (d 5 0,30 IC
del 95% [,02-,57], p <0,05) y el afecto
negativo (d 5. 32; IC del 95% [0,12 hasta
0,52], p <0,001). Los analisis moderador
no revelaron ningun impacto de la
estrategia analıtica de datos sobre los
efectos de intervencion. Del mismo
modo, el estado de riesgo de los participantes
no fue un moderador para la
mayorıa de los resultados.
Discusion: Los programas basados en
Internet tienen exito en la reduccion de
los sıntomas de TCA y los factores de
riesgo con un tama~no de efecto peque~no
a moderado entre grupos. VC 2015 Wiley
Periodicals, Inc.
(Int J Eat Disord 2016; 49:19–31).
Accepted 1 October 2015
*Correspondence to: Tiffany Melioli, Octogone-Centre d’etude et de recherche en psychopathologie, Universite Toulouse II, 5 Allees
Antonio Machado, 31058 Toulouse cedex 9, France.
E-mail: tiffany.melioli@gmail.com
1
Octogone-Centre D’etude Et De Recherche En Psychopathologie, Universite Toulouse II, 5 Allee Antonio Machado, 31058, Toulouse
Cedex 9, France
2
Center for Psychotherapy Research, University Hospital Heidelberg, Bergheimerstr. 54, Heidelberg, 69115, Germany
3
Department of Counseling and Applied Educational Psychology, Northeastern University, Boston, Massachusetts
4
Laboratoire Du Stress Traumatique (EA 4560), Universite Toulouse-III Paul Sabatier, Toulouse, 31400, France
Published online 26 November 2015 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/eat.22477
VC 2015 Wiley Periodicals, Inc.
International Journal of Eating Disorders 49:1 19–31 2016 19
Introduction
Eating disorders (EDs), including subthreshold
forms, are increasingly common, and among the
most severe of mental disorders.1–3
Successful prevention
and treatment programs for young women
have been developed4–8
; however, these face-toface
interventions present a number of limitations,
and are costly and difficult to disseminate, leading
to calls capitalize on the possibilities offered by the
Internet.6,9
The Internet may have great potential
for enhancing the treatment and prevention of EDs
due to advantages in accessibility, cost, and ease of
dissemination.6,10
Internet-based psychotherapeutic
intervention programs have been suggested to
offer specific advantages for EDs.11–13
Although the
number of Internet-based programs has multiplied,
their success in decreasing ED symptoms is
still unclear. Because of the potential advantages
of Internet-delivered programs, establishing their
efficacy is an important step toward greater
dissemination.12,14,15
Existing Internet-based ED intervention programs
have been identified in two systematic
reviews,11,16
which have reported encouraging
findings, concluding that Internet-based programs
are emerging as a successful approach for the treatment
of ED symptomatology. The efficacy of ED
prevention programs delivered exclusively through
the Internet (as opposed to other forms of technology)
has been explored through two meta-analy-
ses.17,18
The first found little evidence for their
efficacy,18
whereas the second documented moderate
improvements in ED symptoms.17
As both of
these reviews focused on the same prevention program
(Student Bodies), the difference might stem
from the fact that the second was far more inclusive
and might have greater statistical power17
than
the first one.18
A third meta-analysis has explored
the efficacy of technology-based intervention and
both selective and universal prevention programs
and provided an overview of e-therapy delivered
through computers, CD-Rom, the Internet, or
mobile-device applications.19
The authors concluded
that the efficacy of such programs should
be considered with caution and that further
research was needed.
Although these three meta-analyses have explored
the efficacy of ED Internet-based programs,17–19
their
findings are limited by the lack of focus on variables
that might account for the efficacy of Internet-based
programs. To our knowledge, only one meta-analysis
has reported exploratory moderator analyses.17
Moderator
analyses were performed on weight concern
outcomes to evaluate the efficacy of the Student
Bodies program between U.S. versus German samples
and universal versus selective prevention samples.
The authors reported heterogeneity on the
Weight and Shape Concern Scale (WCS) and suggested
differences on weight concern outcomes
depending on country and risk status. Regarding
individual studies, moderators of intervention effects
have been identified in two studies,20,21
with the
greatest effects found among participants with high
BMI and compensatory behaviors at baseline20
and
the lowest effects found among participants with
FIGURE 1. Sample search strategy for PsycInfo.
MELIOLI ET AL.
20 International Journal of Eating Disorders 49:1 19–31 2016
high purge behaviors and restrictive eating at base-
line.21
Exploring the impact of risk status on effects
across a larger number of interventions would
increase our understanding of the impact of initial
symptomatology on intervention effects.
While face-to-face selected prevention programs
have been found to result in greater decreases in
ED symptoms compared with universal prevention,
little is known regarding the potential moderators
of their effects. Given the lack of consensus
between previous meta-analyses regarding the efficacy
of ED Internet-based programs, conducting a
meta-analysis incorporating all studies published
to date in symptomatic individuals (selective prevention)
and those meeting diagnostic criteria
(intervention) might help clarify previous
results.17–19
Moreover, it will be useful to clinicians
to provide a clearer picture of the efficacy of
Internet-based programs in reducing ED symptoms
along a continuum of severity. Furthermore,
to our knowledge, to date, little is known regarding
the influence of potential moderator variables on
the efficacy of Internet-based programs. Thus, the
aim of this meta-analytic review was twofold: first,
to evaluate the efficacy of Internet-based programs
in decreasing ED-related risk symptoms among
symptomatic individuals as well those with diagnosed
ED; second, to identify moderator variables
of these effects.
Method
The literature review was conducted according to the
Preferred Reporting Items for Systematic Review and
Meta-Analyses (PRISMA) guidelines.22
Eligibility Criteria
We included studies that (1) were published in English
between January 2000 and January 2015; (2) used experimental
or quasi-experimental study designs with a waitlist
condition or another type of control group with a
minimal intervention such as a brochure (studies with
an active control group such as bibliotherapy or comparing
face-to-face and Internet-based programs were
excluded); (3) included symptomatic participants or
FIGURE 2. Study selection process.
REDUCING ED SYMPTOMS USING THE INTERNET
International Journal of Eating Disorders 49:1 19–31 2016 21
participants with full EDs; (4) provided measures of EDrelated
symptoms; and (5) provided sufficient data to
compute between-group effect sizes. Programs that
screened for or used advertisements designed to select
symptomatic individuals were considered to be selective
prevention programs.7
Studies that included individuals
with an ED diagnosis based on Diagnostic and Statistical
Manual of Mental Disorders, Fourth Edition (DSM-IV)
criteria were identified as intervention programs.
Information Sources and Search Strategy
A literature search (Fig. 1) was conducted via PubMed,
PsychINFO, Science Direct, and Google Scholar, using
the criteria: Language (English), date (2000–2015), and
published studies. An ancestry approach was used to
complete computer searches.23
Keywords were
“Disordered Eating” and “Internet Intervention”; “EDs”
and “Internet Prevention”; “Anorexia” and “Internet
Intervention”; “Bulimia” and “Internet Intervention.”
TABLE 1. PICOS (participants, intervention, comparison, outcome, study design) characteristics in identified studies
Study Participants, Mage (SD) Intervention Comparisons Outcomes Design
Type of
Control
Group
Winzelberg et al.29a–c
Women students with desire
to improve body image satisfaction
20.0 (2.8)
IBPP: SB Web-based group
(n 5 31); control
(n 5 29)
BSQ, EDI-DT, EDI-BN,
EDE-Q
NR WLC
Celio et al.30a–c
Women with high BD 19.6
(2.2)
IBPP: SB Web-based group
(n 5 27); control
(n 5 24)
EDE-Q, BSQ, EDI-DT,
EDI-BN
R WLC
Zabinski et al.31a–c
Women students with body
shape concern 19.3 (1.4)
IBPP: SB Web-based group
(n 5 31); control
(n 5 31)
BSQ, EDI-DT, EDI-BN,
EDE-Q
R WLC
Zabinski et al.32
Women students at risk for
developing an ED 18.9 (2.4)
IBPP Web-based group
(n 5 28); control
(n 5 30)
EDE-Q R WLC
Taylor et al.20b,c
Women with high weight and
shape concern 20.8 (2.6)
IBPP: SB Web-based group
(n 5 192); control
(n 5 199)
WCS, EDI-DT, EDI-BN,
EDE-Q, CES-D
R WLC
Low et al.33b,c
Women students with desire
to improve body image
IBBP:SB Web-based group
(n 5 14); control
(n 5 14)
EDI-DT, EDI-BN, EDIBD,
WSC; SATAQ
R WLC
Heinicke et al.34
Adolescent girls selfidentifying
as having body
image or eating problems
14.4 (1.5)
IBPP: My body,
my life
Web-based group
(n 5 40); control
(n 5 43)
BSQ, BCS, DEBQ-R,
EWLB, EDI-BN,
SATAQ-3, BDISF
R WLC
Paxton et al.35
Women with high BD 25.6
(5.8)
IBPP Web-based group
(n 5 37); control
(n 5 37)
BSQ, PACS, BULIT-R,
DEBQ-R, BDI-II
R WLC
Jacobi et al.36b,c
Women students who wanted
to improve their body
image 22.5 (2.7)
IBPP: SB Web-based group
(n 5 47); control
(n 5 50)
EDI-DT, EDI-BN WCS,
EDE-Q
R WLC
Doyle et al.37c
Overweight or at risk for
overweight adolescents
14.5 (1.7)
IBPP: SB2 Web-based group
(n 5 40); control
(n 5 40)
EDE-Q R TAU
Jones et al.38c,d
Adolescent at risk for
overweight 15.1 (1.0)
IBPP: SB 2 Web-based group
(n 5 52); control
(n 5 53)
EBI, CES-D R WLC
Fernandez-Aranda
et al.39d,e
Women with BN 23.7 (3.6) IBIP Web-based group
(n 5 31); control
(n 5 31)
EDI, EAT-40, BITE NR WLC
Sanchez-Ortiz
et al.40c–e
Women students with BN or
EDNOS 23.9 (5.9)
IBIP Web-based group
(n 5 38); control
(n 5 38)
EDE-Q R WLC
Carrard et al.41c–e
Women with full or subthreshold
BED 36 (11.4)
IBIP Web-based group
(n 5 37); control
(n 5 37)
EDE-Q, EDI-DT, EDIBN,
EDI-BD, T-FEQ
R WLC
Carrard et al.42d,e
Obese women and men with
BED 42.8 (9.8)
IBIP Web-based group
(n 5 22); control
(n 5 20)
EDO, EDE-Q, TFEQ NR WLC
Fichter et al.43c
Women with full or subthreshold
AN 24.1 (5.6)
IBPP Web-based group
(n 5 106); control
(n 5 113)
EDI R TAU
Jacobi et al.44c,d
Women with subthreshold ED
22.3 (2.9)
IBPP: SB1 Web-based group
(n 5 51); control
(n 5 52)
EDE-Q, WCS, EDI-DT,
EDI-BN, EDI-BD,
BDI
R WLC
MELIOLI ET AL.
22 International Journal of Eating Disorders 49:1 19–31 2016
Study Selection and Data Collection Process
Data were collected by the first author (Fig. 2). The
data collection form contained the following items: literature
(authors, date, title), program (intervention vs. prevention),
participants (N, Mage, standard deviation [SD],
gender), outcomes, and study design (randomized or
non-randomized).
Risk of Bias in Individual Studies
Quality assessment and data extraction were conducted
by the first author. All studies screened were published
in English.
Data Analysis
Statistical heterogeneity across studies was determined
using the Q-test for heterogeneity (substantial
heterogeneity when p < .1024
) and the I2
statistic (unimportant
to moderate heterogeneity when I2
< 50%, and
substantial when I2
> 50%25
). We calculated summary
between-group effect sizes for studies testing the effects
of Internet programs against a control group. Potential
outliers for each outcome were identified using standardized
residuals with 1.96 as a cut-off.26
Betweengroup
effect sizes were interpreted using Cohen’s
guidelines27
with 0.20 representing a small effect size,
0.50 a medium effect size, and 0.80 a large effect size.
Given the small sample size in some studies, Hedges’ g
was also calculated for all outcomes as this coefficient
provides a better estimation in such cases.28
Analyses
of moderation were conducted to explore the effect of
ED symptom severity at baseline (nonclinical/mixed
vs. high-risk samples) and data analysis method
(intent-to-treat [ITT] vs. completers]. Studies that
TABLE 1. Continued
Study Participants, Mage (SD) Intervention Comparisons Outcomes Design
Type of
Control
Group
Stice et al.45c
Women students with BD
21.6 (6.6)
IBPP Web-based group
(n 5 19); control
(n 5 39)
DRES, SDBPS, IBSR,
BDI
R BC
H€otzel et al.46c
Women with AN or BN symptoms
27.1 (7.8)
IBPP Web-based group
(n 5 49); control
(n 5 76)
EDE-Q, SEED R WLC
Ruwaard et al.47c–e
Women with BN symptoms
31 (10)
IBPP Web-based group
(n 5 35); control
(n 5 35)
EDE-Q, BAT R WLC
Notes: ED, Eating Disorders; BED, Binge Eating Disorder; BN, Bulimia; BD, Body Dissatisfaction; EDNOS, Eating Disorder Not Otherwise Specified;
IBPP, Internet-Based Prevention Program; IBIP, Internet-Based Intervention Program; SB, Student Bodies; R, Randomized; NR, No Randomized; WLC,
Waiting-List Condition; TAU, Treatment As Usual; BC, Brochure Condition; BSQ, Body Shape Questionnaire48
; EDI, Eating Disorders Inventory (DT, Drive
for Thinness; BN, Bulimia; BD, Body Dissatisfaction)49
; EDE-Q, Eating Disorder Examination-Questionnaire50
; WCS, Weight and Shape Concern Scale51;
SATAQ, Sociocultural Attitudes Toward Appearance Questionnaire52
; PACS, Physical Appearance Comparison Scale53
; BULIT-R, Bulimia Test-Revised54
;
DRES Dutch Restrained Eating Scale, DEBQ-R, Dutch Eating Behavior Questionnaire-Restraint Subscale55;
BCS, Body Comparison Scale56
; EWLB, Extreme
Weight Loss Behaviors Scale57
; EDDS, Eating Disorder Diagnostic Scale58
; IBSS-R, The Ideal-Body Stereotype Scale-Revised59
; MBSRQ, Multidimensional
Body Self-Relations Questionnaire60
; BES, Body Esteem Scale61
; T-FEQ, Three-Factor Eating Questionnaire Symptom Checklist-90-Revised62
; EDO, Eating
Disorders in Obesity63
; BAT, Body Attitude Test64
; EAT-40, Eating Attitudes Test65
; BITE, Bulimic Investigatory Test Edinburgh66
; SEED, Short Evaluation of
Eating Disorders67
; SDBPS, Satisfaction and Dissatisfaction with Body Parts Scale68
; EBI, Eating Behaviors Inventory69
; BDISF, Beck Depression Inventory
short form70
; BDI, Beck Depression Inventory71
; CES-D, Center for Epidemiologic Studies Depression Scale72
; BDI-II, Beck Depression Inventory-Second
Edition73
; PANAS-X, Positive Affect and Negative Affect Scale-Revised Form.74
a
Studies identified by Newton and Ciliska.18
b
Studies identified by Beintner et al.17
c
Studies identified by Loucas et al.19
d
Studies identified by Aardoom et al.11
e
Studies identified by D€olemeyer et al.16
TABLE 2. Methodological quality in identified studies
Study Randomization
ITT
Analysis Dropout < 15% Score
Winzelberg et al.29
No No Yes (13%) 1
Celio et al.30
Yes No No (23%) 1
Zabinski et al.31
Yes No Yes (2%) 2
Zabinski et al.32
Yes Yes Yes (2%) 3
Taylor et al.20
Yes No No (16%) 1
Low et al.33
Yes Yes Yes (6%) 3
Paxton et al.35
Yes Yes No (26%) 2
Heinicke et al.34
Yes Yes No (22%) 2
Jacobi et al.36
Yes No Yes (3%) 2
Doyle et al.37
Yes Yes No (20%) 2
Jones et al.38
Yes Yes No (17%) 2
Fernandez-Aranda
et al.39
No No No (35%) 0
Sanchez-Ortiz
et al.40
Yes Yes No (21%) 2
Carrard et al.41
Yes Yes No (17%) 2
Carrard et al.42
No No Yes (9%) 1
Fichter et al.43
Yes Yes Yes (6%) 3
Jacobi et al.44
Yes Yes No (18%) 2
Stice et al.45
Yes No Yes (2%) 2
H€otzel et al.46
Yes Yes No (41%) 2
Ruwaard et al.47
Yes Yes No (26%) 2
Notes: Quality scores range from 0 5 high risk of bias to 3 5 low risk
of bias. ITT 5 intention to treat.
REDUCING ED SYMPTOMS USING THE INTERNET
International Journal of Eating Disorders 49:1 19–31 2016 23
included symptomatic individuals were categorized as
nonclinical/mixed and studies that included participants
with ED diagnoses were classed as high risk.
Nonclinical/mixed- and high-risk samples are presented
in Table 1 as IBPP (Internet-Based Prevention
Program) and IBIP (Internet-Based Intervention Program),
respectively.
The analyses were conducted using Comprehensive
Meta-Analysis.26
Effect sizes were calculated with preand
post-mean and SD information; follow-up data were
not used. We calculated overall between-group effect
sizes for outcomes assessing symptoms or risk factors of
EDs: body dissatisfaction,48,49,68
thin-ideal internaliza-
tion,52,59
shape and weight concern,50,51,61,69
dietary
restriction,50,55
drive for thinness,49
bulimic symptoms
and purging frequency,49,50,54,75
and negative affect.70–74
A random effects model was used to calculate betweengroup
effect size. Moderator analyses were conducted by
calculating effect sizes within each group (without pooling
within-group estimates of heterogeneity) and effect
sizes were then compared.
Results
Study Selection and Study Characteristics
The search strategy led to an initial pool of 590
articles of which 20 were eligible and included
(Table 1). Study sample sizes ranged from 28 to 391
and mean age was 23.33 years (SD 5 7.13). Among
the 20 identified studies, 4 were categorized as IBIP
and 16 as IBPP. Seventeen of the 20 studies were
randomized controlled studies. Among the 20 studies
identified, 19 were based on cognitivebehavioral
therapy principles (e.g., associations
between thoughts, feelings, and behaviors) and 1
study46
was based on motivational interviewing
(i.e., motivational enhancement therapy). A flow
diagram with reasons for exclusions is displayed in
Figure 2.
Study Quality and Risk of Bias
The Cochrane collaboration’s risk of bias tool was
adapted to identify risk of bias.25
Thus, three criteria
were used to assess study quality and risk of bias: (1)
“sequence generation” through randomization; (2)
“incomplete outcome data” through ITT analysis;
and (3) “other bias” through dropout rates. Among
the 20 identified studies, 17 included randomization,
12 were based on ITT, and 8 had a dropout rate below
15% (dropout rates varied between 2% and 41%). The
methodological quality of included studies is summarized
in Table 2. Studies were assessed according
to each of the three criteria, and a score of 1 was
attributed when the study presented methodological
strengths (randomization, ITT, or dropout rate<
15%). Thus, total study quality scores ranged from
0 (presence of the three sources of bias) to 3 (high
quality, absence of bias). The methodological criteria
of ITT and dropout rates by condition are displayed
in Table 3. Among the 20 controlled studies identified,
12 conducted ITT analyses. Five methods of ITT
analyses were identified: “baseline-observationcarried-forward
method” (BOCF; n5 7), “lastobservation-carried-forward
method” (LOCF; n5 1),
“maximum likelihood estimation algorithm method”
(MLE; n 5 1), “on available complete data method”
(OACD; n 5 1), and “mixed-effects models” (MEM;
n 5 2).
Results of Individual Studies and Synthesis of
Results
Body Dissatisfaction. Among the 20 controlled
studies, 12 studies included a measure of body dissatisfaction
(Fig. 3). None of the 12 studies
emerged as outliers, and heterogeneity was unimportant
(Q 5 7.71, p 5.74, I2
5 0%). The summary
effect size was d 5 0.28, 95% CI [0.15–0.41],
p <.001, revealing a small but significant overall
effect (g 5 .28, 95% CI [0.15–0.41], p <.001). When
comparing ITT (n 5 6) versus completers (n 5 6),
the moderation analysis revealed no significant
TABLE 3. Methodological criterion of intention-to-treat
analysis and dropout rates by condition
Study (Reference) ITT Method
Dropout
Internet-Based
Program (n)
Dropout
Control
Condition
(n)
Winzelberg et al.29
NA 4 4
Celio et al.30
NA 1 3
Zabinski et al.31
NA 0 1
Zabinski et al.32
BOCF 2 0
Taylor et al.20
NA 38 21
Low et al.33
BOCF NA NA
Paxton et al.35
BOCF 13 7
Heinicke et al.34
BOCF 28 34
Jacobi et al.36
NA NA NA
Doyle et al.37
BOCF 7 7
Jones et al.38
BOCF 8 8
Fernandez-Aranda
et al.39
NA NA NA
Sanchez-Ortiz
et al.40
MEM 8 13
Carrard et al.41
MLE 13 4
Carrard et al.42
NA 2 2
Fichter et al.43
OACD 7 8
Jacobi et al.44
MEM 8 3
Stice et al.45
NA 2 0
H€otzel et al.46
BOCF 54 33
Ruwaard et al.47
LOCF 13 4
Notes: ITT 5 intention to treat; NA: not applicable or not found;
MEM: mixed-effects models; BOCF: baseline-observation-carried-forward
method; LOCF: last-observation-carried-forward method; MLE: maximum
likelihood estimation algorithm; OACD: on available complete data.
MELIOLI ET AL.
24 International Journal of Eating Disorders 49:1 19–31 2016
FIGURE 3. Body dissatisfaction, drive for thinness, and internalization of the thin ideal.
FIGURE 4. Shape and weight concerns.
REDUCING ED SYMPTOMS USING THE INTERNET
International Journal of Eating Disorders 49:1 19–31 2016 25
differences in the summary effect, p 5.89. Similarly,
when comparing high-risk (n 5 2) versus nonclinical/mixed
(n 5 10) participants, the
moderation analysis revealed no significant differences
in the summary effect size, p 5.85.
Drive for Thinness. Ten studies included a measure
of drive for thinness (Fig. 3). One study43
emerged
as an outlier with a standardized residuals value of
22.19 (>1.96) and was removed from this analysis.
Tests of homogeneity showed an unimportant heterogeneity
across the nine remaining studies
(Q 5 2.91, p 5.94, I2
5 0%). The summary effect
size was d 5 0.47, 95% CI [0.33–0.60], p <.001, indicating
a significant small effect on drive for thinness
(g 5 .46, 95% CI [0.33–0.60], p <.001). When
comparing ITT (n 5 3) versus completers (n 5 6), a
moderation analysis revealed no significant differences
in the summary effect size, p 5.60. Similarly,
when comparing high-risk (n 5 2) versus nonclinical/mixed
(n 5 7) participants, the moderation
analysis revealed no significant differences in the
summary effect size, p 5.27.
Internalization of the Thin Ideal. Three studies provided
effect sizes for internalization of the thin
ideal, and none emerged as outliers (Fig. 3). Tests
of homogeneity showed an unimportant heterogeneity
(Q 5 .73, p 5.70, I2
5 0%). The summary
effect size was d 5 0.36, 95% CI [0.07–0.65], p <.05,
revealing a moderate positive effect on internalization
of the thin ideal (g 5 .36, 95% CI [0.07–0.64],
p <.05). As the three studies aimed to prevent ED
using data from completers, no moderation analyses
were conducted.
FIGURE 5. Bulimic symptoms, negative affect, and restriction.
MELIOLI ET AL.
26 International Journal of Eating Disorders 49:1 19–31 2016
Shape and Weight Concern. Nine studies provided
effect sizes for shape concern, and none were outliers
(Fig. 4). Substantial heterogeneity emerged for
the shape concern outcome (Q 5 15.93, p <.05,
I2
5 50%). The summary effect was d 5 0.35, 95% CI
[0.13–0.57], p <.05, revealing a significant effect on
shape concern (g 5 .34, 95% CI [0.13–0.56], p <.05).
When comparing ITT (n 5 5) versus completers
(n 5 4), a moderation analysis revealed no significant
differences in the summary effect size, p 5.52.
When comparing high (n 5 3) versus nonclinical/
mixed (n 5 6) participants, the moderation analysis
revealed that the summary effect size for high-risk
participants (d 5 0.74, 95% CI [0.45–1.04], p < .001;
g 5 .73, 95% CI [0.44–1.02], p <.001) was significantly
larger than for nonclinical/mixed participants
(d 5 0.17, 95% CI [20.01 to 0.35], p 5 .066;
g 5 .17, 95% CI [20.01 to .34], p 5.066), Q 5 10.68,
p <.05.
Nine of the studies provided effect sizes for
weight concern, with no outliers. Tests of homogeneity
revealed unimportant heterogeneity
(Q 5 5.13, p 5.74, I2
5 0%) with a summary effect
size of d 5 0.25, 95% CI [0.09–0.40], p <.05, revealing
a small significant effect on weight concern
(g 5 .25, 95% CI [0.09–0.40], p <.05). When comparing
ITT (n 5 5) versus completers (n 5 4), the moderation
analysis revealed no significant differences
in the summary effect size, p 5.54. When comparing
high (n 5 2) versus nonclinical/mixed (n 5 7)
participants, the moderation analysis revealed no
significant differences in the summary effect size,
p 5.06.
Five studies included combined measures of
shape and weight concern, with no outliers. Moderate
heterogeneity was found (Q 5 9.19, p 5.056,
I2
5 47%). The summary effect size was d 5 0.42,
95% CI [0.13–0.71], p <.05, indicating a moderate
significant effect on shape and weight concern
(g 5 .42, 95% CI [0.13–0.70], p <.05). When comparing
ITT (n 5 2) versus completers (n 5 3), a moderation
analysis revealed no significant differences in
the summary effect size, p 5.09. As the five studies
aimed to prevent ED, no comparison was made
with high-risk participants.
Dietary Restriction. Thirteen studies included a
measure of dietary restriction, with no outliers
(Fig. 5). Tests of homogeneity revealed an unimportant
heterogeneity (Q 5 7.96, p 5.79, I2
5 0%).
The summary effect size for dietary restriction was
d 5 0.36, 95% CI [0.23–0.49], p <.001, revealing a
small overall effect (g 5 .36, 95% CI [0.23–0.49],
p <.001). When comparing ITT (n 5 8) versus completers
(n 5 5), a moderation analysis revealed no
significant differences in the summary effect size,
p 5.38. Similarly, when comparing high-risk (n 5 3)
versus nonclinical/mixed (n 5 10) participants, a
moderation analysis revealed no significant differences
in the summary effect size, p 5.34.
Bulimic Symptoms and Purging Frequency. Eighteen
studies provided a measure for bulimic symptoms
(Figs. 5 and 6). Two studies42,47
emerged as outliers
and were removed from this analysis (standardized
residuals value of 3.95 and 2.02, respectively). Tests
of homogeneity revealed an unimportant heterogeneity
(Q 5 9.24, p 5.87, I2
5 0%). The overall effect
size was d 5 0.27, 95% CI [0.17–0.37], p <.001,
revealing a small but significant effect on bulimic
symptoms (g 5 .26, 95% CI [0.16–0.36], p <.001).
When comparing ITT (n 5 9) versus completers
(n 5 7), a moderation analysis revealed no significant
differences in the summary effect size, p 5.72.
Similarly, when comparing high-risk (n 5 3) versus
nonclinical/mixed (n 5 13) participants, the moderation
analysis revealed no significant differences
in the summary effect size, p 5.11. Five studies
provided a measure for purging frequency. One
study47
emerged as an outlier and was removed
FIGURE 6. Purging frequency.
REDUCING ED SYMPTOMS USING THE INTERNET
International Journal of Eating Disorders 49:1 19–31 2016 27
(standardized residuals value of 3.79). Tests of
homogeneity revealed a moderate heterogeneity
(Q 5 4.97, p 5.17, I2
5 40%). The summary effect
size for the remaining four studies was d 5 0.30,
95% CI [0.02–0.57], p <.05, indicating an overall
significant small effect on purging frequency
(g 5 .29, 95% CI [0.02–0.56], p <.05). When comparing
ITT (n 5 3) versus completers (n 5 1), a moderation
analysis revealed no significant differences in
the summary effect size, p 5.06. When comparing
high-risk (n 5 2) versus nonclinical/mixed (n 5 2)
participants, the moderation analysis revealed no
significant difference in the summary effect sizes,
p 5.13.
Negative Affect. Five studies provided a measure
for negative affect with no outliers (Fig. 5). Tests of
homogeneity revealed an unimportant heterogeneity
(Q 5 .916, p 5.92, I2
5 0%). The summary effect
size for the remaining five studies was d 5 0.32,
95% CI [0.12–0.52], p <.05, indicating an overall
significant small effect on negative affect (g 5 .32,
95% CI [0.12–0.52], p <.05). As the five studies
aimed to prevent ED using data from completers,
no moderation analyses were conducted.
Between-group effect sizes were also calculated
for all outcomes by excluding studies in which a
wait list condition (WLC) control group was not
reported (control group with minimal intervention
such as a brochure were removed from this analysis).
The summary effect sizes of studies exclusively
including a WLC group were not significantly different
from the effect sizes calculated for studies
including a WLC or another type of control group
(i.e., minimal intervention).
Discussion
The primary aim of this meta-analysis was to evaluate
the efficacy of Internet-based selective prevention
and intervention programs for EDs, so as
to bridge the gap in meta-analytic reviews of the
success of Internet-based programs targeting ED
symptoms along a continuum of severity. Findings
indicated that Internet-based programs were successful
in decreasing ED symptomatology, suggesting
that efforts to move the field toward implementing
effectiveness trials are warranted. The secondary aim
was to identify variables that moderated the efficacy
of ED Internet-based programs. Overall, no differences
in effects were found between interventions
conducted in populations that included individuals
with clinical diagnoses compared to those with
“symptoms” only (except for shape concern) or
between ITT or completers analyses, suggesting that
these variables might not account for the efficacy of
ED Internet-based programs.
Compared with previous meta-analyses, the current
study provides an up-to-date more inclusive
review, including five studies32,34,35,39,42
that were
not present in the previous 2014 meta-analysis,19
and by excluding programs delivered by CD-Rom.
Furthermore, by excluding universal prevention
studies and controlled studies between two active
conditions, in contrast to the latest meta-analysis,19
our study provides summary effects of the reduction
in existing ED symptoms through Internet-based
programs. Finally, our study makes an important
original contribution by including moderation analyses,
and thus bridging a gap in the literature.
Regarding the efficacy of ED Internet-based programs,
consistent with previous research,17
small
to moderate effect sizes were found for decreases
in internalization of the thin ideal, shape and
weight concern, body dissatisfaction, bulimic
symptoms and purging behaviors, dietary restriction,
negative affect, and drive for thinness. In
addition, it is important to note that there was no
evidence of negative effects. Although previous
meta-analyses have reported contradictory findings
regarding the efficacy of IBPPs,17–19
our results
are consistent in supporting their efficacy.
To date, little is known regarding moderator variables
of the efficacy of Internet-based programs. Our
moderator analyses revealed no significant differences
between nonclinical/mixed and high-risk participants
on all outcomes excepted for shape concern; a
larger decrease was found among the high-risk sample.
The extant literature indicated that face-to-face
selected prevention produced larger decrease than
universal programs for most of the outcomes, and
that level of eating pathology may influence engagement
and intervention effects.7
The current study
suggests that Internet-based programs might be
equally effective for most outcomes among nonclinical/mixed
and high-risk participants. Therefore,
intervention effects might depend on other variables.
Regarding data analysis methodology, no difference
was found in program efficacy between ITT and
completer analyses. It has been argued that ITT analyses
might decrease the attrition biases associated
with dropout in randomized trials, and, therefore,
limit bias in estimates of intervention effects.76
Internet
programs have high dropout rates16
suggesting
that intervention effects might differ depending on
data analytic strategy (i.e., ITT and completer analyses).
Nevertheless, the current meta-analysis suggests
that completer analyses produce similar intervention
effects as compared with ITTanalyses.
MELIOLI ET AL.
28 International Journal of Eating Disorders 49:1 19–31 2016
Given the advantages of Internet-based programs,
evaluating their efficacy compared with face-to-face
ED programs is of particular interest. Although this
was not tested in the present study, a recent metaanalysis
comparing the efficacy of face-to-face and
Internet CBT on psychiatric and somatic diseases
concluded that both formats might be similarly effi-
cacious.77
Clearly, more research in this area, including
non-inferiority or equivalence studies, is
warranted. Our results showed a wide range of dropout
rates. As study design, implementation, guidance
(e.g., self-help guided by a therapist), and
intervention duration might explain dropout rates,78
further exploration of these variables as potential
moderators of programs engagement is an important
area for future research.17,79
Internet-based programs present numerous
advantages over face-to-face ones, thus our
encouraging findings highlight the importance of
further implementing and disseminating these programs
and extending their applications within
treatment and prevention settings. For example,
the Internet could offer many opportunities for
aftercare interventions,80
symptom-monitoring via
cell phones,81
or family-based programs.82
The
Internet might also provide training opportunities
for carers of individuals suffering from EDs.83–85
Moreover, as most studies have focused on interventions
for bulimia or binge ED, studies evaluating
Internet-based interventions for anorexia
nervosa are needed.39,40,86
Our study presents a number of limitations.
First, it does not provide evidence for the longterm
efficacy of Internet-based programs. In addition,
the lack of consensus across the literature
regarding the definition of selective prevention
might have led to studies being classified as one
category in the present study, but another in a different
meta-analysis, depending on the definition
used. Furthermore, regarding methodological
quality, studies reporting a low dropout rate were
considered to present a low risk of bias, which
could be considered as biased against studies with
high ecological validity (e.g., when assessment
and intervention occur entirely on-line). Nevertheless,
Internet-based programs have been found
to successfully decrease ED-related symptoms
and risk factors. These findings highlight the
importance of moving toward large-scale effectiveness
trials as there is little data in this
area.29,33,87
In the current study, risk status (high
and low) and data analytic strategy (ITT or completer)
were no moderator variables of intervention
effects. Future research should thus address
other moderator variables such as program interactivity,
guidance frequency, and participant age.
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