1-s2.0-s0272735814000312-main

7172019 1-s20-S0272735814000312-main

httpslidepdfcomreaderfull1-s20-s0272735814000312-main 119

Participation and outcome in manualized self-help for bulimia nervosaand binge eating disorder mdash A systematic review andmetaregression analysis

Ina Beintner a Corinna Jacobi a Ulrike H Schmidt b

a Institut fuumlr Klinische Psychologie und Psychotherapie Technische Universitaumlt Dresden Chemnitzer Straszlige 46 01187 Dresden Germanyb Kings College London Institute of Psychiatry Box P059 De Crespigny Park London SE5 8AF UK

H I G H L I G H T S

bull Adherence is an issue in self-help interventions for mental disorders

bull Dropout and treatment completion rates and de1047297nitions of treatment completion vary

bull BED patients complete self-help more often and bene1047297t more than BN patients

bull For BN patients guidance can reduce study dropout and enhance treatment outcome

bull For further research on adherence comparable measures are needed

a b s t r a c ta r t i c l e i n f o

Article history

Received 7 August 2013

Received in revised form 7 January 2014

Accepted 14 January 2014

Available online 23 January 2014

Keywords

Self-help

Adherence

Binge eating

Bulimia nervosa

Metaregression

There is a growing body of research on manualized self-help interventions for bulimia nervosa (BN) and binge

eating disorder(BED)Study andtreatment dropoutand adherence represent particular challenges in these stud-

ies However systematic investigations of the relationship between study intervention and patient characteris-

tics participation and intervention outcomes are lacking We conducted a systematic literature review using

electronic databases andhand searchesof relevantjournalsIn metaregressionanalyses we analyzedstudy drop-out as well as more speci1047297c measures of treatment participation in manualized self-help interventions their

association with intervention characteristics (eg duration guidance intervention type [bibliotherapy CD-

ROMor Internetbased intervention]) and their association with treatment outcomes Seventy-three publications

reporting on 50 different trials of manualized self-help interventions for binge eating and bulimia nervosa pub-

lished through July9th 2012 wereidenti1047297edAcross studies dropout rates rangedfrom1 to 88 Studydropout

rates were highest in CD-ROM interventions and lowest in Internet-based interventions They were higher

in samples of BNpatients samples ofpatientswithhigher degrees ofdietary restraintat baselinelowerage

and lower body mass index Between 6 and 88 of patients completed the intervention to which they had

been assigned None of the patient study and intervention characteristics predicted intervention comple-

tionrates Intervention outcomeswere moderated by the provisionof personal guidance by a health profes-

sional the number of guidance sessions as well as participants age BMI and eating disorder related

attitudes (Restraint Eating Weight and Shape Concerns) at baseline (after adjusting for study dropout

and intervention completion rates) Guidance particularly improved adherence and outcomes in samples

of patients with bulimia nervosa specialist guidance led to higher intervention completion rates and larger

intervention effects on someoutcomes thannon-specialist guidance Self-helpinterventionshave a placein

the treatment of BN and BED especially if the features of their delivery and indications are considered carefullyTo better determine who bene1047297ts most from what kind and ldquodosagerdquo of self-help interventions we recommend

the use of consistent terminology as well as uniform standards for reporting adherence and participation in

future self-help trials

copy 2014 Elsevier Ltd All rights reserved

Clinical Psychology Review 34 (2014) 158ndash176

Some of the results were presented at the 18th annual meeting of the Eating Disorder Research Society (EDRS) September 21th 2012 Porto (Portugal)

Corresponding author Tel +49 351 463 37460 fax +49 351 463 37208

E-mail addresses InaBeintnertu-dresdende (I Beintner) corinnajacobitu-dresdende (C Jacobi) ulrikeschmidtkclacuk (UH Schmidt)

0272-7358$ ndash see front matter copy 2014 Elsevier Ltd All rights reserved

httpdxdoiorg101016jcpr201401003

Contents lists available at ScienceDirect

Clinical Psychology Review

7172019 1-s20-S0272735814000312-main


Contents

1 Introduction 159

2 Methods 160

21 Study selection 160

22 Measures of participation 160

23 Effect size calculation for intervention outcomes 161

24 Coding 161

241 Study participation and study outcomes 161

242 Study and intervention characteristics 161243 Patient characteristics 162

25 Integration of outcomes 162

26 Moderator analyses 162

27 Sensitivity analyses 162

3 Results 162

31 Sample of studies 162

32 Participation 163

33 Moderators of participation 163

331 Study dropout rate 163

332 Intervention completion rate 163

333 High participation 165

334 Low participation 165

34 Intervention outcomes 165

35 Moderators of intervention outcomes across trials 167

351 Study and intervention characteristics 167

352 Patient characteristics 167


4 Discussion 170



43 Moderators of intervention outcomes 171

44 Implications for the design of future interventions 172

441 How should self-help interventions be designed to maximize participation and intervention outcome 172

442 Who bene1047297ts most from self-help interventions 173

45 Clinical recommendations 173

46 Limitations of our metaanalysis 174

5 Conclusion 174

Appendix A Supplementary data 174

References 175

1 Introduction

Around the world national strategy documents and in1047298uential

reviews highlight the need for urgent action to improve the state of

mental health care (eg Kazdin amp Blase 2011 Medical Research

Council 2010 Patel Boyce Collins Saxena amp Horton 2011) Access to

evidence-based psychological interventions poses a key determinant

of good outcomes (The Centre for Economic Performances Mental

Health Policy Group 2012) However given the cost of face-to-face in-

dividual psychological therapy (which is the currently predominant

model of intervention delivery) to health care systems and patients

cost-effective alternatives are needed (Kazdin amp Blase 2011) In this

context translating effective psychological interventions into self-helpprograms and delivering them as bibliotherapy CD-ROMs or via the

Internet represents a major advance

A recent review from the UK estimated that just under a quarter of

eating disorder sufferers receive any intervention at all mdash and only 15

receive psychological therapy (The Centre for Economic Performances

Mental Health Policy Group 2012) This intervention gap is particularly

large for bulimic disorders (Hoek 2009) Cognitivendashbehavioral interven-

tions for the treatment of bulimia nervosa and binge-eating disorder are

effective (Hay Bacaltchuk Stefano amp Kashyap 2009) Self-help versions

of these interventions (which sometimes are guided ie augmented

with a small amount of personal telephone or email contact with a

health care professional) can also be effective at least for a subgroup of

participants (Perkins Murphy Schmidt amp Williams 2006 Stefano

Bacaltchuk Blay amp Hay 2006 Sysko amp Walsh 2008 Wilson Vitousek

amp Loeb 2000 Wilson amp Zandberg 2012) Experts concluded that self-

help is lsquoa robust means of improving implementation and scalability of

evidence-based treatment for eating disordersrsquo (Wilson amp Zandberg

2012 p 343)

Despitesuch enthusiastic endorsement bothquantitative research on

self-help approaches for a range of mental disorders (eg Christensen

Grif 1047297ths amp Farrer 2009 Eysenbach 2005 Melville Casey amp Kavanagh

2010) and qualitative studies of self-help treatments capturing the

views of patientswith eating disorders suggest that many patients strug-

gle with adherence to these programs mdash some because they feel short-

changed and see self-help as a cheap substitute for lsquoproperrsquo face-to-face

therapy others because they 1047297nd it hard to motivate themselves to per-

sist with working through the program with limited or no support(McClay Waters McHale Schmidt amp Williams 2013 Murray et al

2003 Pretorius Rowlands Ringwood amp Schmidt 2010 Saacutenchez-Ortiz

House et al 2011 Saacutenchez-Ortiz Munro et al 2011) The personal

costndashbene1047297t-ratio for a certain intervention can be very different for

each patient Interventions may not address symptoms that are a major

burden for patients or the intervention itself may be experienced as a

burden Low adherence in an intervention study can indicate that pa-

tients experience the intervention as either unpleasant or not helpful

(Rand amp Sevick 2000) Pooradherencemaynegativelyaffect intervention

outcome and a negative treatment experience may demoralize users and

reduce the likelihood of future help-seeking While lsquothe traditional clini-

cal trial and evidence-based medicine paradigm stipulates that high

dropout rates make trials less believable hellip for many eHealth trials

in particular those conducted on the Internet and in particular with

175

159I Beintner et al Clinical Psychology Review 34 (2014) 158ndash176

7172019 1-s20-S0272735814000312-main


self-help applications high dropout rates may be a natural and typical

featurersquo (Eysenbach 2005) Yet despite the importance of adherence

its determinants and in1047298uence on intervention effectshave only been ex-

amined in a number of individualself-help trials (CarrardCrepinRouget

Lam vander Linden et al 2011 Carrard Fernandez-Aranda et al 2011

Carter et al 2003 Ghaderi 2006 Ghaderi amp Scott 2003 Schmidt et al

2008 Thiels Schmidt Troop Treasure amp Garthe 2001 Troop Schmidt

Tilleramp Todd 1996) but not been systematically reviewed across studies

and not been systematically linkedto intervention outcomes Thepresentpaper aims to bridge this gap

In the current review we de1047297ne adherence in accordance with the

de1047297nition put forward by Haynes Sackett and Taylor (1979) as lsquothe ex-

tent to which the patients behavior matches agreed recommendations

from the prescriberrsquo thus (in contrast to compliance) emphasizing the

patients freedom to decide to adhere to a recommendation ( Horne

Weinman Barber Elliott amp Morgan 2005) For psychotherapeutic

approaches and other behavioral interventions (like self-help interven-

tions) adherence is complex and dif 1047297cult to de1047297ne While in relation to

pharmacotherapy adherence commonly refers to whether the pre-

scribed dosage of a medication is taken or not (Vitolins Rand Rapp

Ribisl amp Sevick 2000) in behavioral interventions there is dissent

about what best indicatesadherence Some authors argue that interven-

tion ef 1047297cacy is linked to session attendance or simply staying in the in-

tervention long enough These authors view intervention dropout as an

indicator of adherence (Edlund et al 2002 Ogrodniczuk Piper amp Joyce

2006 Olfson et al 2009) Others suggest that homework completion is

a better indicator of patient commitment and adherence (Scheel

Hanson amp Razzhavaikina 2004) Assessments of behavioral adherence

indicators (other than mere attendance of intervention sessions or

visited web-pages in an Internet-based intervention) often rely on pa-

tients self-reports with their various sources of inaccuracy

When looking at adherence in self-help interventions we must

therefore deal with different de1047297nitions of adherence different adher-

ence measures and differences in the precision of these measures

Both providing and integrating this information will be a major chal-

lenge to this review as it can be expected that the different de1047297nitions

and measures will lead to diverse results Given these differences in def-

initions of adherence we chose to look at and integrate any informationgiven about how patients participated in a study We will use the word

participation as a broad term for measures of study and treatment drop-

out adherence and intervention completion

In self-helpinterventions several aspects of the intervention may in-

1047298uence patients participation whether there is guidance or not how

experienced the guide is with the target disorder whether patients

can utilize the intervention at home or if they have to come to an insti-

tutionhow much timethe interventionwill take andwhether there are

side effects from the intervention Several characteristicsof intervention

participants may also in1047298uence adherence how severe their illness is

how they perceive their impairment what bene1047297t they expect from

the intervention and what practical and emotional resources they

have Patients participation will not fully predict intervention outcome

but it will probably be closely associated with intervention outcomeTheobjectives of this systematic revieware (1)to identify measures

of patient participation reported in trials on manualized self-help

for bulimia nervosa and binge eating disorder1 and to integrate these

measures across different trials (2) to determine whether and to what

degree differences in participation contribute to the moderation of

intervention outcomes In order to do that we need to identify moder-

ators of participation moderators of intervention outcomes and exam-

ine if and how associations between those moderators and intervention

outcomes change when participation measures are taken into account

2 Methods

21 Study selection

We performed a search on PubMed PsychInfo PsychArticles and

Web of Knowledge and considered all available manuscripts published

through July 9th 2012 Search terms were self-help and eating disor-

der self-help and binge eating self-help and bulimia nervosa Internet

and eating disorder Internet and binge eating Internet and bulimia

nervosa CD-ROM and eating disorder CD-ROM and binge eating and

CD-ROMand bulimia nervosa Also we examined the referencesections

of all identi1047297ed articlesreviews and book chapters We contacted corre-

sponding authors of all relevant publications and asked for additional

unpublished data on published studies as well as unpublished studies

Due to resource constraints all searches were conducted by IB and we

limited our review to publications in English and German We includedstudies if they examined manualized self-help interventions (ie there

was an intervention book a CD-ROM or an Internet program with sub-

sequent sessions and pre-assigned contents and the intervention pro-

gram with reading assignments and behavioral exercises was the

same for each participant) We excluded studies on unstructured Inter-

net forums or customized email-therapy The intervention focus had to

be on modi1047297cation of disordered eating we therefore excluded studies

on behavioral weight loss interventions Due to the limited number of

randomized controlled trials on manualized self-help interventions

with an untreated control group we also included case series We did

not require studies to have a minimal sample size

For randomized controlled trials and controlled trials comparing

different types of self-help we entered each trial condition separately

into the analyses For randomized controlled trials and controlled trialscomparing self-help to an untreated control group or another active in-

tervention (eg weight loss intervention psychotherapy) we regarded

only data from the eating disorder speci1047297c self-help condition The

design of the original studies (case series RCT CT) was included as a

potential moderator for participation and outcomes (see below)

22 Measures of participation

We examined different measures of participation as primary out-

comes(1) Study dropoutrates were included as a very broad participa-

tion measure (2) Intervention completion rates and proportions of

participants with high and low participation were included as more

speci1047297c participation measures We calculated study dropout rates and

intervention completion rates based on intent-to-treat samples We de-1047297ned study dropout rate as the proportion of participants not available

for post-intervention assessments2 We de1047297ned intervention comple-

tion rate as the proportion of participantswho according to the individ-

ual authors completed the intervention irrespective of how it was

de1047297ned We documented de1047297nitions of intervention completion by

individual authors (see Coding section) Furthermore we recorded the

proportion of participants who completed less than half (low participa-

tion) or more than three-quarters (high participation) of the interven-

tion when data were available in the original publications or could be

obtained from the authors For trials with more than one self-help

1 Two major reasons prevented us from including self-help interventions for AN in our

meta-analysis1 Compared with BN andBED AN has a much higher potential formedical

complications Accordingly self-help in general does not seem to bean appropriate inter-

vention for most individuals with AN 2 To our knowledge only two studies on self-help

interventions for AN havebeen conducted so far bothby Manfred Fichterand colleagues

One intervention aimed at patients who had already been scheduled for inpatient treat-

ment and the main goalof the intervention wasto reduce the length of the upcomingin-

patienttreatment(Fichter CebullaQuad1047298iegamp Naab 2008) Theotherintervention wasa

relapse prevention program for women who had completed inpatient treatment (Fichter

et al2012) In bothcases theinterventionscannot be considered ldquotypicalrdquo self-helpinter-

ventions (ie were not designed to be stand-alone treatments)

2 Notethata participantmighthave completed theinterventionbut notprovided post-

intervention data and vice versa

160 I Beintner et al Clinical Psychology Review 34 (2014) 158ndash176

7172019 1-s20-S0272735814000312-main


intervention condition the respective rates were calculated separately

for each condition

23 Effect size calculation for intervention outcomes

We included studies for analyses of intervention effects if means and

standard deviations or other statistics allowing for effect size estimation

(eg median quartiles t-values) of core eating disorder outcomes

(frequencies of binge eating eating disorder related attitudes) hadbeen reported Measures for these outcomes had to be comparable

across studies For frequencies of binge eating the time span had to

be clearly speci1047297ed in the paper eating disorder related behaviors and

attitudes had to be assessed with standard (well-validated) measures

For reasons of clarity and readability of this metaanalysis we limited

outcome analyses to abstinence from binge eating binge eating fre-

quency and subscales of theEatingDisorderExamination(EDE EDE-Q)

Because the majority of trials did not include an untreated control

group we calculated prendashpost-effect sizes only For trials with more

than one self-help intervention condition effect sizes were calculated

separately for each condition To account for small sample sizes in

some of the trials we calculated Hedges g which provides a better es-

timateof thepopulation variance than Cohens d (Hedges 1981Hedges

amp Olkin 1985) Mean differences were standardized by pooled standard

deviations (Hedges amp Olkin 1985) of pre- and post-intervention

measurements An adjustment for sample size was conducted (Hedges

amp Olkin 1985) Whenever possible we used data from intent-to-treat

analyses to calculate effect sizes If only completer data were reported

we 1047297rst calculated effect sizes based on these data and then adjusted

for the intent-to-treat sample assuming an effect of zero for non-

completers (gITT = gcompleter times Ncompleter divide NITT)

For three trials (Ruwaard et al 2012 Traviss Heywood-Everett amp

Hill 2011 Treasure et al1994) several effect sizes had to be calculated

using median and quartile or range measures (Hedges amp Olkin 1985)

For one trial (Carter et al 2003) effect sizes were recalculated from

t-values (Rosenthal1994)Authors ofone trial(Mitchell et al 2001)re-

ported only the mean percentage decrease of binge eating and purging

compared with baseline Post-intervention means and effect sizes were

calculated based on the baseline instead of the pooled SD for that trialWe calculated rates of participants abstinent from binge eating if

de1047297nitions of abstinence andor remission (especially the time span

covered) hadbeen clearly speci1047297ed in theoriginal manuscripts If neces-

sary we recalculated abstinence rates for the intent-to-treat samples

therefore they may differ from abstinence rates reported in the original

manuscripts

24 Coding

If a study included more than one self-help intervention condition

each condition was coded separately Information from all sections of

a research paper was included All intervention conditions were coded

by IB according to the following characteristics

241 Study participation and study outcomes

Study dropout rate Rate of participants not attending post-intervention

assessments (based on intent-to-treat sample size of intervention

group) Some authors did not count participants who had been allocat-

ed to the intervention but never started it towards dropouts If that was

thecase we added the proportion of patients who hadnot started inter-

vention to the reported dropout rate

Intervention completion rate Rate of participants completing the inter-

vention (based on intent-to-treat sample size of intervention group)

De 1047297nition of intervention completion De1047297nitions of intervention comple-

tion by authors of original manuscripts were categorized into four

groups(1) objective measure high requirements (2) objective mea-

sure low requirements (3) subjective measure and (4) no de1047297nition

given The intervention completion measure was deemed objective

when guidance session attendance or traceable participation in an

Internet-intervention was the relevant criterion The intervention com-

pletion measure was deemed subjective when it relied solely on self-

report Requirements were deemed high when intervention completion

implicated the attendance of a certain number of sessions or a certain

amount of traceable participation in an Internet-intervention Require-ments were deemed low when intervention completion just involved

staying in the intervention up to a certain time-point or attending post-

intervention assessment

Low participation Rate of participants who completed less than half of

the intervention based on the intent-to-treat sample size of the inter-

vention group (this includes participants who never started the inter-

vention after randomization)

High participation Rate of participants who completed at least three-

quarters of the intervention based on the intent-to-treat sample size

of the intervention group

Abstinence from binge eat ing Abstinence rates calculated as speci1047297ed

above

Binge eating frequency EDE-Q subscales Effect sizes calculated as speci-

1047297ed above

242 Study and intervention characteristics

Design (1) Randomized controlled trial (RCT) (2) controlled trial (CT)

and (3) case series

Sample size Number of participants in the intervention condition

Intervention type (1) Bibliotherapy (2) CD-ROM intervention and

(3) Internet intervention

Guidance (1) Unguided self-help and (2) guided self-help

Guides quali 1047297cation Quali1047297cation of guidance provider (1) non-

specialist (GP nurse social worker3) (2) mental health specialist

(eg psychiatrist psychologist psychology student) or (3) ED or

CBT specialist

Duration of the intervention period Number of weeks between baseline

and post-assessment

Number of sessionmodules in guided self-help Number of guidance ses-

sions (for bibliotherapy) or number of subsequent modules with thera-

pist feedback (for CD-ROM and Internet-based programs)

Medication Medication administered in addition to self-help

intervention (0) none (1) placebo (2) Fluoxetine or (3) Orlistat

Quality of diagnoses (1) Clinical assessment (2) standardized self-

report questionnaire and (3) standardized or structured interview

Quality of study (1) High quality of study (this wasassumed if the study

was a RCT participants were diagnosed with a standardized or

3 In two trials conducted in the UK (Cooper Coker amp Fleming 1994 Cooper et al

1996) guidance was provided by a social worker In the UK social workers need to com-

plete additionaltraining to becomeApproved Mental HealthProfessionalsSince no infor-

mationwas given on ifthe social workerengaged in bothof thestudies hadcompletedthis

training we classi1047297ed him as a non-specialist


7172019 1-s20-S0272735814000312-main


structured interview authors gave a de1047297nition of intervention comple-

tion and the sample size was suf 1047297cient to detect a medium effect for

continuous outcomes in a repeated measures ANOVA (N = 36 based

on a power calculation Mayr Erdfelder Buchner amp Faul 2007)) and

(2) low quality of study

243 Patient characteristics

For one trial (Furber Steele amp Wade 2004) pre-intervention data

were reported separately for completers and dropouts Here werecalculated pre-intervention means (MITT = (Ncompleter times Mcompleter +

Ndropout times Mdropout) divide N ITT) and standard deviations (SDpooled Hedges

amp Olkin 1985) for the intent-to-treat sample

Diagnoses (1) Bulimia nervosa (BN) or eating disorder not otherwise

speci1047297ed BN subtype (EDNOS-BN) (2) Binge eating disorder (BED)

and (3) mixed

Mean baseline number of binge eating episodes Mean number of binge

eating episodes during the past 28 days reported by participants in

the intervention group at baseline

Mean baseline EDE-Q scores Mean scores of EDE-Q subscales Restraint

Eating concern Weight concern and Shape concern of the intervention

group at baseline

Mean age Mean age of participants in the intervention group

Mean baseline BMI Mean BMI of participants in the intervention group

at baseline

25 Integration of outcomes

We conducted all analyses using IBM SPSS Statistics Version 19 and

21 in combination with SPSS macros to perform meta-analytic analyses

(Lipsey amp Wilson 2000 Wilson 2005) We integrated event rates using

a meta-analytic model for point estimates of single groups (Einarson

1997) The inverse variances of proportions (s 2 = p times (1 minus p) divide n)

(Fleiss 1981) were used as weights We added a score of 0005 toevent rates of zero to permit the calculation of a weight ( Sheehe

1966) Overall heterogeneity across studies was tested using the

Q-test (Hedges amp Olkin 1985) Analyses were based on the random

effects model (Hedges amp Olkin 1985) The random variance component

was estimated by a restricted maximum likelihood approach

26 Moderator analyses

To identify factors that may impact both intervention participation

and outcomes we conducted moderator analyses We included both

studyintervention and patient characteristics as described above as

potential moderators To be included in the moderator analysis data

from at least 10 studies had to be available to ensure a minimum of

power to detect moderator effects (Borenstein Hedges Higgins ampRothstein 2011)

We performed meta-regression analyses as moderator analyses

(Hedges amp Olkin 1985) All categorial independent variables were

transformed into lsquodummy variablesrsquo To facilitate interpretation of 1047297nd-

ings all independent variables were centered around their median

(Kraemer amp Blasey 2004) Primary analyses were based on the random

effects models However here the power to detect relationships be-

tween moderators and intervention effects is often low ( Borenstein

et al 2011) The 1047297xed effects model on the other hand yields more

statistical power than the random effects model yet generalizability is

limited (Rosenthal 1995) We therefore performed secondary analyses

based on the 1047297xed effects model to detect moderators that might have

an impact but may not have been detected in the random effects

model due to lack of statistical power When analyzing moderators of

intervention completion rates de1047297nition of intervention completion

(see above) was entered as a covariate in all analyses

27 Sensitivity analyses

Analyses of intervention effect moderators were1047297rst performed un-

adjusted as described aboveSinceintervention effects areunlikelyto be

independent from dropout rates and intervention completion rates we

repeated all analyses by (1) adjusting for dropout rates and the statisti-cal interaction between moderatorsand dropout rates and (2) adjusting

for intervention completion rates the statistical interaction between

moderators and intervention completion rates and intervention com-

pletion de1047297nitions It is likely that moderator analyses for treatment ef-

fect sizes based on intent-to-treat samples will lead to very different

results depending on whether we adjust for study dropout or treatment

completion rates or not When analyses are not adjusted we might mis-

take differences in treatment outcome that are solely due to differences

in dropout or treatment completion rates for true differences in treat-

ment ef 1047297cacy On the other hand we might miss true differences that

are masked by differences in dropout or treatment completion rates

Adjusting for dropout or treatment completion rates will both increase

statistical power to detect true differences and let associations that are

probably statistical artifacts disappear A participation outcome was

deemed predicted robustly if analyses in both the 1047297xed and random

effects models yielded signi1047297cant or almost signi1047297cant associations An

intervention effect was deemed predicted robustly if at least analyses

in both the 1047297xed and random effects model adjusted for study dropout

rates or in both the 1047297xed and random effects model adjusted for inter-

vention completion rates and intervention completion de1047297nitions

yielded signi1047297cant or almost signi1047297cant associations

We performed sensitivity analyses excluding interventions that

augmented self-help with pharmacotherapy or a placebo medication

Outliers of participationindicators (dropout rates intervention comple-

tion rates low and high participation rates) and intervention outcomes

were identi1047297ed by visual inspection of boxplots Analyses were then re-

peated with outliers excluded We limited those secondary sensitivity

analyses to the unadjusted analyses

3 Results

31 Sample of studies

Fig 1 shows the QUOROM diagram of study selection Of the identi-

1047297ed trials we excluded one study because the intervention consisted of

monthly self-help letters and was deemed dif 1047297cult to 1047297t into any of the

Fig 1 QUOROM statement 1047298ow diagram


7172019 1-s20-S0272735814000312-main


abovementioned coding categories (Huon 1985) Another study was

excluded because authors solely analyzed factors in1047298uencing failure to

engage in a self-help program (Bell amp Newns 2004) In one publication

preliminary data from an ongoing study were reported (Bell amp Hodder

2001) while 1047297nal results have never been published We therefore

excluded the preliminary data from the analyses Another trial was

excluded because the intervention examined non-manualized email

therapy (Robinson amp Serfaty 2008) Several publications exist on results

of a multicenter study on the effectiveness of an Internet-based in-tervention for the complete sample as well as for subsamples

(SALUT (Carrard Fernandez-Aranda et al 2011 Carrard et al 2006

Fernandez-Aranada et al 2008 2009 Liwowsky Cebulla amp Fichter

2006 Nevonen Mark Levin Lindstrom amp Paulson-Karlsson 2006))

In our review we included only data from the full sample ( Carrard

Fernandez-Aranda et al 2011)

Overall 73 different publications reporting on 50 different trials on

self-help and Internet-based interventions for binge eating and bulimia

nervosa including a total of 2586 participants could be identi1047297ed (see

Appendix A Table A1) 34 trials were (R)CTs of which 13 included a

non-intervention waitlist control group In the other (R)CTs different

types of interventionswere compared Twelve of the identi1047297ed 50 trials

examined two self-help interventions Sixty-two different intervention

conditions are included in the analyses 45 conditions from RCTs 16

conditions from case series and one condition from a controlled trial

The duration of the self-help interventions in those 62 conditions

ranged between 6 and 26 weeks (median 125 weeks) In 50 condi-

tions participants received bibliotherapy in 6 conditions they received

a CD-ROM-based intervention and in 6 conditions they received an

Internet-based intervention In two conditions self-help was accompa-

nied by medicationwith Fluoxetine in one by Orlistat and in three con-

ditions by a placebo medication In 9 of the remaining 55 intervention

conditions participants on antidepressants were explicitly excluded

from the studies in the remaining 46 conditions patients were either

included provided their dosage had been stable for a certain amount

of time or authors did not report any inclusion or exclusion criteria

regarding antidepressants In 43 intervention conditions participants

received some kind of guidance and in 19 conditions participants re-

ceived no guidanceThe de1047297nition of intervention completion varies considerably be-

tween studies In 18 conditions intervention completion was de1047297ned

objectively and requirements were high in 9 conditions intervention

completion was de1047297ned objectively but requirements were low In 12

conditions intervention completion was de1047297ned subjectively and in

11 conditions authors did not specify their criteria for intervention com-

pletion at all

Seven studies including 8 of the 62 conditions met the criteria for

high quality of study (RCT participants diagnosed with a standardized

or structured interview speci1047297c de1047297nition of intervention completion

and suf 1047297cient sample size to detect a medium effect in a repeated mea-

sures ANOVA Bailer et al 2004 Cassin 2008 Ljotsson et al 2007

Mitchell et al 2011 Saacutenchez-Ortiz House et al 2011 Saacutenchez-Ortiz

Munro et al 2011 Schmidt et al 2007 Striegel-Moore et al 2010)Intervention was provided for patients with bulimia nervosa (BN) or

sub-threshold bulimia in 33 conditions for patients with binge eating

disorder (BED) in 15 conditions and for both BN and BED patients in

14 conditions Diagnoses were made by standardized or structured in-

terviews in 36 conditions by a standardized questionnaire in 6 condi-

tions and by clinical assessment in 5 conditions Means of diagnostic

assessments were not reported for 5 conditions Mean age of partici-

pants ranged from 174 to 503 years (k = 57 median 295 years)

mean body mass index (BMI) from 200 to 396 kgm2 (k = 49 median

245 kgm2) Mean baseline binge eating frequency ranged from 10 to

36 binge eating episodes in the past 28 days (k = 41 median 176

episodes) Mean baseline EDE(-Q) Restraint score ranged from 16 to

53 (k = 29 median 31) mean baseline EDE(-Q) Eating Concern

score ranged from 19 to 45 (k = 25 median 34) mean baseline

EDE(-Q) Weight Concern score ranged from 31 to 52 (k = 27 median

42) and mean baseline EDE(-Q) Shape Concern score ranged from 34

to 54 (k = 28 median 45) Samples of studies recruiting BN patients

had substantially higher mean baseline EDE(-Q) Restraint scores

lower mean BMIs and involved younger patients than samples of stud-

ies recruiting BED patients (details available upon request)

32 Participation

Rates of study dropout intervention completion low participation

and highparticipation are substantially heterogeneous we therefore ab-

stain from reporting overall mean rates Between 1 and 88 of partici-

pants dropped out of the study (k = 51 median 25) Between 6

and 86 of participants completed the intervention (k = 51 median

59) Between 20 and 81 of participants were high participators

(ie they completed at least three-quarters of the assigned intervention

k = 11 median 41) Between 17 and 58 of participants were low

participators (ie theycompleted lessthan halfof theassignedinterven-

tion k = 13 median 38) Table A2shows study dropoutintervention

completion low participation and high participation rates for individual

studies as well as results of the Q-Test for heterogeneity

33 Moderators of participation

Table 1 illustrates the prediction of participation by study and inter-

vention characteristics Table 2 illustratesthe prediction of participation

by patient characteristics In Appendix C (Table C1) we report addi-

tional results of Q-Test subgroup analyses for categorial moderators

In what follows we will summarize signi1047297cant resultsof random effects

model analyses in detail and also brie1047298y report signi1047297cant results from

1047297xed effects model analyses of studyintervention and patient modera-

tors of the different parameters of participation If a categorial modera-

tor signi1047297cantly predicts participation in the unadjusted random effects

model we report overall subgroup effects and con1047297dence intervals to

illustrate differences between groups

331 Study dropout rate

Intervention type signi1047297cantly predicts study dropout rates in therandom effects model The overall study dropout rate is highest in CD-

ROM interventions (30 95 CI 13ndash46) followed by bibliotherapy

(29 95 CI 24ndash35) and Internet-based interventions (16 95 CI

3ndash29) In addition design guidance the guides quali1047297cation and the

duration of the intervention signi1047297cantly predict study dropout rates

in the 1047297 xed effects model (see Tables 1 and C1)

Diagnoses of participants mean EDE(-Q) Restraint score and mean

body mass index (BMI) in theintervention group at baseline signi1047297cantly

predict study dropout rates in the random effects model The overall study

dropout rate is highest in studies with both bulimia nervosa (BN) and

binge eating disorder (BED) patients (35 95 CI 26ndash44) followed by

studies with BN patients (29 95 CI 23ndash35) and studies with BED pa-

tients(14 95 CI 5ndash24) A higherscore on the EDE(-Q) Restraint scale

and a lower BMI at baseline are associated with a higher study dropoutrate In addition mean number of binge eating episodes in the past

4 weeks mean EDE(-Q) Eating Concern Weight Concern and Shape Con-

cern scores and mean age in the intervention group at baseline signi1047297-

cantly predict study dropout rates in the 1047297 xed effects model (see Table 2)

332 Intervention completion rate

We entered the de1047297nitions of intervention completion (objective

high requirements vs objective low requirements vs subjective vs

not speci1047297ed) as described in the Methods section as a covariate in all

analyses Therefore we cannot provide overall intervention completion

rates for subgroups to illustrate results of categorial moderators

None of the study and intervention characteristics predict interven-

tion completion rates in the random effects model In the 1047297 xed effects

model design intervention type guidance the guides quali1047297cation


7172019 1-s20-S0272735814000312-main


Table 1

Results of metaregression analyses for potential moderators of study dropout and intervention completion study and intervention characteristics

Measure

Potential moderators Study dropout rate Intervention completion rate (by Author de1047297nition)

(Adjusted for intervention completion de1047297nition

see Methods section for further detail)

Rate of pa

at least 75

Design (RCT vs CT vs case series degno data on CTs available) k 50 51 10

FEM bcase series = 1522 bCT =minus1378 bCT =minus2

bcase series

REM ns ns bcase series

Intervention type (book vs CD-ROM vs Internet) k 50 51 10

FEM bCD-ROM = 1320 bCD-ROM =minus1472

bInternet =minus1859

bCD-ROM =

bInternet =

REM bInternet =minus1371 p = 0590 ns bCD-ROM =

bInternet =Guidance (unguided self-help vs guided self-help (GSH)) k 50 51 10

FEM bGSH = 1658 bGSH = 1342 bGSH = 15

REM ns ns ns

Quali1047297cation of guide (GSH only) basic vs medium vs higha k 35 38 9

FEM bmedium =minus1007

bhigh =minus1308

bhigh = 1807 a

REM ns bhigh = 2045 p = 0587 a

Number of sessionsmodules (GSH only) k 40 40 10

FEM ns ns ns

REM ns ns ns

Duration of the intervention (weeks) k 48 49 10

FEM b = 0084 b = 0063 b =minus00

REM ns ns ns

FEM 1047297xed effects model REM random effects model b linear regression slope See end of Table 2 for guidance on reading these results pb 05 pb 01 pb 001a Basic non-specialist medium non-specialist mental health professional high ED or CBT specialist

7172019 1-s20-S0272735814000312-main


and the duration of the intervention signi1047297cantly predict intervention

completion rates (see Table 1)None of the patient characteristics predict intervention completion

rates in the random effects model In the 1047297 xed effects model diagnoses

of participants mean EDE(-Q) Shape Concern scores and mean BMI in

the intervention group at baseline signi1047297cantly predict intervention

completion rates (see Table 2)

333 High participation

Intervention type signi1047297cantly predicts high participation rates

(ie the proportion of participants who completed more than three

quarters of the intervention) in the random effects model The overall

proportion of patients with high participation is highest in biblio-

therapy (65 95 CI 54ndash75) followed by CD-ROM interventions

(38 95 CI 22ndash54) and Internet-based interventions (37 95

CI 20ndash54) In addition design guidance and duration of the inter-vention signi1047297cantly predict high participation rates in the 1047297 xed

effects model (see Tables 1 and C1)

None of the patient characteristics predict high participation rates in

the random effects model In the 1047297xed effects model diagnoses of partic-

ipants signi1047297cantly predict high participation rates (see Tables 2 and

C1)

334 Low participation

Guidance signi1047297cantly predicts low participation rates (ie the

proportion of participants who completed less than half of the interven-

tion) in the random effects model The overall proportion of patients

with low participation was higher in unguided self-help (52 95

CI 38ndash66) than in guided self-help (35 95 CI 29ndash42) In addition

the guides quali1047297cation and the durationof the intervention signi1047297cantly

predict low participation rates in the 1047297 xed effects model (see Tables 1

and C1)Diagnoses of participants mean age and mean BMI in the interven-

tion group at baseline signi1047297cantly predict low participation rates in the

randomeffects model Theoverall proportion of patients withlow partic-

ipation is highest in studies with BN patients (43 95 CI 38ndash48)

followed by studies with both BN and BED patients (26 95 CI

15ndash37) and studies with BED patients (22 95 CI 6ndash37) A lower

age and a lower BMI are associated with a higher proportion of patients

with low participation No additional patient moderators signi1047297cantly

predict low participation rates in the 1047297 xed effects model

34 Intervention outcomes

Mean effect sizes for all analyzed outcomes were substantially het-erogeneous andwe thereforeabstain from reporting mean overall effect

sizes across trials Effect sizes for the frequency of binge eating episodes

range from g = 03 to g = 268 (k = 48 median 68) Between 9 and

64 of participants had achieved abstinence from binge eating at post-

intervention assessment (k = 32 median 298) Effect sizes for the

EDE(-Q) Restraint scale range from g = minus 22 to g = 118 (k = 29

median 44) Effect sizes for the EDE(-Q) Eating Concern scale range

from g = minus 11 to g = 163 (k = 26 median 85) Effect sizes for

the EDE(-Q) Weight Concern scale range from g = 05 to g = 120

(k = 27 median 70) Effect sizes for the EDE(-Q) Shape Concern

scale range from g = 01 to g = 127 (k = 28 median 75) Table A3

shows abstinence rates and effect sizes for individual studies as well

as results of the Q-Test for heterogeneity Appendix B shows forest

plots of individual effect sizes and con1047297dence intervals

Table 2

Results of metaregression analyses for potential moderators of study dropout and intervention completion patient characteristics

Outcome measure


(Controlled for intervention completion de1047297nition

coding (1) objective high requirements vs (2) objective

low requirements vs (3) subjective vs (4) not speci1047297ed


Rate of participants who

completed at least 75

of intervention


completed less than 50

of intervention

Diagnoses

(BED vs BN vs mixed)

k 50 51 10 13

FEM bBED =minus2473

bBN =minus0531

bBED =minus0721

bBN =minus0591

bBED =minus1237

bBN =minus2975

bBN = 1759

REM bBED =minus2042 ns ns bBN = 1726

Baseline 4 week binge eating

frequency

k 31 35 4 6

FEM b =minus0045a nsa b b

REM ns ns

Baseline EDE-Q Restraint k 23 25 5 4

FEM b = 2015 ns b b

REM b = 1620a ns

Baseline EDE-Q Eating Concern k 20 22 5 4

FEM b =minus1103 nsa b b

REM ns ns

Baseline EDE-Q Weight Concern k 21 23 5 4

FEM b = 0749 ns b b

REM ns ns

Baseline EDE-Q Shape Concern k 22 24 5 4

FEM b =minus1331 b =minus1307 b b

REM ns nsAge k 47 49 9 12

FEM b =minus0114 ns b b = minus0132

REM b =minus0062 p = 0752 ns b =minus0134

BMI k 40 44 9 12

FEM b =minus02 19 b = 00 86 b b = minus0191

REM b =minus0156 ns b =minus0190

FEM 1047297xed effects model REM random effects model b linear regression slope See Results section for further details pb 05 pb 01 pb 001

How to read Tables 1 and 2

Studydropoutandintervention completionrateswere coded using values between0 and1 Forcategorial moderatorswith twosubgroups b is thedifference betweenthe twogroups The

reference group is indicated in the subscript For categorial moderators with three subgroups b is the difference between one group and the other two groups The reference group is

indicated in the subscript For continuous moderators b indicates the change in effect sizes if the value of the moderator is increased by one unita Substantial changes of results in sensitivity analysesb No analyses conducted due to small number of studies


7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main


35 Moderators of intervention outcomes across trials

Table 3 illustrates the prediction of intervention outcomes by study

and intervention characteristics Table 4 illustrates the prediction of

intervention outcomes by patient characteristics Analyses were 1047297rst

performed unadjusted then repeated separately adjusting for dropout

rates and adjusting for intervention completion rates and intervention

completion de1047297nitions Both tables provide an overview of results de-

pending on what type of analysis was performed and how differentmoderators predict different outcomes A guide to reading Tables 3

and 4 is provided at the end of Table 4 In Appendix C (Table C2) we

report additional results of Q-Test subgroup analyses for categorial

moderators Subsequently we will summarize signi1047297cant results of un-

adjusted and adjusted random effects model analyses in detail and also

brie1047298y report signi1047297cant results from 1047297xed effects model analyses of

studyintervention and patient moderators of the different outcomes

If a categorial moderator signi1047297cantly predicts an intervention out-

come in the unadjusted random effectsmodel we report overall sub-

group effects and con1047297dence intervals to illustrate differences between

groups


Design does not predict intervention effects in the random effects

model It predicts effect sizes for the frequency of binge eating episodes

abstinence from binge eating and effect sizes for the EDE(-Q) Eating

Concern and Shape Concern scales in the 1047297 xed effe cts model (see

Tables 3 and C2) All results are consistentIntervention type predicts abstinence from binge eating and effect

sizes for the EDE(-Q) Restraint scale in the random effects model Absti-

nence rates are highest for Internet-based interventions (38 95

CI 20ndash55) followed by bibliotherapy (31 95 CI 25ndash36) and

CD-ROM interventions (9 95 CI minus10ndash28) in the unadjusted

random effects model Effect sizes for the EDE(-Q) Restraint Scale are

higher in Internet-based interventions than in bibliotherapy in the ran-

domeffects model adjusted for intervention completionratesand inter-

vention completion de1047297nitions In addition intervention type predicts

effect sizes for the frequency of binge eating episodes and for the

EDE(-Q) Shape Concern scale in the 1047297 xed effects model (see Tables 3and C2) All results are consistent

Guidance predicts abstinence from binge eating effect sizes for the

EDE(-Q) Eating Concern Weight Concern and Shape Concern scales in

the random effects model More patients in guided self-help were absti-

nent from binge eating (35 95 CI 30ndash41) compared with unguided

self-help (16 95 CI 7ndash24) in the unadjusted and both the adjusted

random effects models Guided self-help yields larger effect sizes for the

EDE(-Q) Eating Concerns scale than unguided self-help in both the

adjusted random effects models Guided self-help yields larger effect

sizes for the EDE(-Q) Weight Concerns scale than unguided self-help

in the random effects model adjusted for dropout rates Effect sizes for

the EDE(minusQ) Shape Concern scale are medium to large in guided

self-help(g = 79 95CI 65ndash93) and small to medium in unguided

self-help (g = 48 95 CI 20ndash77) in the unadjusted random effectsmodel Guided self-help yields larger effect sizes for the EDE(-Q) Shape

Concerns scale than unguided self-help in the random effects model

adjusted for dropout rates

In addition guidance predicts effect sizes for the frequency of binge

eating episodes and the EDE(-Q) Restraint scale in the 1047297 xed effects model

(see Tables 3 and C2) All results are consistent

The guides quali 1047297cation in guidedself-help predicts effect sizes for the

frequency of binge eating the EDE(-Q) Restraint and Shape Concern

scales in the random effects model Effect sizes for the frequency of

binge eating episodes are medium to large in interventions guided by

ED or CBT specialists (g = 68 95 CI 21ndash116) large in interventions

guided by other mental health specialists (g = 101 95 CI 78ndash124)

and medium in interventions guided by non-specialists (g = 49 95

CI 03ndash094) in the unadjusted random effects model while variations

are greatest in interventions guided by non-specialists Effect sizes are

also larger in interventions guided by specialists than in interventions

guided by non-specialists in the random effects model adjusted for inter-


Effect sizes for the EDE(-Q) Restraint Scale were larger in interventions

guided by non-specialists than in interventions guided by ED or CBT

specialists or guided by other mental health specialists in the random

effects model adjusted for intervention completion rates and interven-

tion completion de1047297

nitions Effect sizes for the EDE(-Q) Shape Concernscale are larger in interventions guided by ED or CBT specialists than in

interventions guided by other mental health specialists and interven-

tions guided by non-specialists in the random effects model adjusted

for intervention completion rates and intervention completion de1047297ni-

tions In addition the guides quali1047297cation predicts abstinence from

binge eating and EDE(-Q) Eating and Weight Concern in the 1047297 xed effects

model (see Tables 3 and C2) All results are consistent

The number of sessions or modules in guided self-help predicts absti-

nence from binge eating and effect sizes for the EDE(-Q) Restraint

Weight Concern and Shape Concern scales in the random effects model

Abstinence rates are higher in interventions with more sessions

modules in the random model adjusted for intervention completion

rates and intervention completion de1047297nition Interventions with more

sessions yield larger effect sizes for the EDE(-Q) Restraint scale in the

random effects model adjusted for intervention completion rates and in-

tervention completion de1047297nitions Interventions with more sessions

yield larger effect sizes for the EDE(-Q) Weight Concern scale in all

models Interventions with more sessions yield larger effects sizes for

the EDE(-Q) Shape Concern scale in both the unadjusted random effects

model and the random effects model adjusted for dropout rates In addi-

tion the number of sessions or modules in guided self-help predicts ef-

f ect sizes for the EDE(-Q) Eating Concern scale in the 1047297 xed effects model

(see Table 3) All results are consistent

The duration of the intervention predicts effectsizes for the EDE(minusQ)

Eating Concern scale in the random effects model Longer interventions

yield smaller effect sizes for the EDE(minusQ) Eating Concerns scale in the

unadjusted random effects model In addition the duration of the inter-

vention predicts abstinence from binge eating and effect sizes for the

EDE(minus

Q) Restraint scale in the 1047297 xed effects model (see Table 3)


Diagnoses of participants signi1047297cantly predict effect sizes for the fre-

quency of binge eating episodes abstinence from binge eating and ef-

fects sizes for the EDE(-Q) Eating Weight and Shape Concern scales in

the random effects model Effect sizes for the frequency of binge eating

are large in studies with BED patients (g = 119 95 CI 93ndash145)

medium to large in studies with BN patients (g = 75 95 CI 55ndash94)

and small to medium in studies with both BN and BED patients (g =

50 95 CI 19ndash80) in theunadjusted random effects model In the ran-

dom effects model adjusted for intervention completion rates and inter-

vention completion de1047297nitions studies with BN patients yield lower

abstinence rates than studies with BED patients and both BN and BEDpatients Effect sizes for the EDE(-Q) Eating Concern scale are large for

studies with BED patients (g = 128 95 CI 100ndash156) medium to

large for studies with BN patients (g = 68 95 CI 39ndash96) and small

to medium for studies with both BN and BED patients (g = 53 95

CI 27ndash79) in the unadjusted random effects model Effect sizes for the

EDE(-Q) Weight Concern scale are medium to large for studies with

BED patients (g = 93 95 CI 72ndash114) and studies with BN patients

(g = 68 95 CI 48ndash88) and small to medium for studies with both

BN and BED patients (g = 48 95 CI 29ndash67) in the unadjusted ran-

dom effects model Effect size EDE(-Q) Shape Concern is large for studies

with BED patients (g = 101 95 CI 82ndash120) medium to large for

studies with BNpatients(g = 7195 CI 52ndash90) andsmallto medium

for studies with both BN and BED patients (g = 47 95 CI 30 ndash66)

in the unadjusted random effects model In addition diagnoses of


7172019 1-s20-S0272735814000312-main


Table 4

Results of metaregression analyses for potential intervention effect moderators patient characteristics

Outcome measure

Potential moderators 4 week binge eating

frequency

Abstinence from binge

eating

EDE(-Q) Restraint EDE(-Q) Eating

Concern

k k k k

Diagnoses (BED vs BN vs mixed) FEM 48 bBED = 7006

bBN = 1374

31 bBED = 0844 29 bBN = 2227 26 bBED = 8198

adj dropout 41 bBED = 2896 26 bBED =minus1351 24 bBN = 2981 21 bBED = 12998

adj intervention completion 40 bBED = 3276 29 bBED =minus1152

bBN =minus1673

26 bBED =minus4803 23 ns

REM 48 bBED = 6946 31 ns 29 ns 26 bBED = 7495

adj dropout 41 ns 26 ns 24 ns 21 ns

adj intervention completion 40 ns 29 bBN =minus1709 26 ns 23 ns


frequency

FEM 35 ns 22 ns 23 ns 20 ns

adj dropout 28 ns 17 b = 0083 18 ns 15 b =minus0358

adj intervention completion 31 ns 22 ns 22 b = 0347 19 ns

REM 35 ns 22 ns 23 ns 20 ns

adj dropout 28 ns 17 ns 18 ns 15 b =minus

0371 adj intervention completion 31 ns 22 ns 22 b = 0310 p = 0594 19 ns

Baseline EDE-Q Restraint FEM 26 b =minus2503 19 b =minus1115 28 b = 1443 25 b =minus1929

adj dropout 21 ns 14 ns 23 b = 3404 20 ns

adj intervention completion 23 b =minus2729 17 b =minus0857 25 b = 3391 22 b =minus1845

REM 26 b =minus3000a 19 b =minus1100 p = 0715a 28 b = 1525 p = 0636a 25 b =minus2613 p = 0893


adj intervention completion 23 b =minus3080 17 b =minus0857 25 b = 3674 22 ns

Baseline EDE-Q Eating Concern FEM 23 ns 18 b = 1282 25 b = 2394 25 b = 2993

adj dropout 18 ns 13 b = 0834 20 b = 2566 20 b = 2363

adj intervention completion 15 ns 11 b = 1232 17 ns 17 ns

REM 23 ns 18 b = 0986 p = 0862a 25 b = 2329 a 25 b = 2575 p = 0887

adj dropout 18 ns 13 b = 0836 20 b = 2502 p = 0573 20 b = 2168 p = 0851


7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main


participants signi1047297cantly predict effect sizes for the EDE(-Q) Restraint

scale in the 1047297 xed effects model (see Tables 4 and C2)

The frequency of binge eating at baseline predicts effect sizes for the

EDE(-Q) Eating Concerns scale in the random effects model Higher fre-

quencies of binge eating at baseline are associated with smaller effect

sizes for the EDE(-Q) Eating Concern scale in the random effects model

adjusted for dropout rates In addition the frequency of binge eating

at baseline predicts abstinence from binge eating and effect sizes for

the EDE(-Q) Restraint scale in the 1047297 xed effects model (see Table 4) All re-sults are consistent

EDE(-Q) Restraint scores at baseline predict effect sizes for the fre-


fect sizes for the EDE(-Q) Restraint scale in the random effects model

Higher scores on the EDE(-Q) Restraint scale at baseline are associated

with a smaller effect size for the frequency of binge eating episodes

and with lower abstinence rates in the unadjusted random effects

model and in the random effects model adjusted for intervention com-

pletion rates and intervention completion de1047297nitions Higher scores

on the EDE(-Q) Restraint scale at baseline are associated with a larger

effect size for the EDE(-Q) Restraint scale in all models In addition

EDE(-Q) Restraint scores at baseline predict effect sizes for the EDE(-Q)

Eating Weight and Shape Concern scales in the random effects model


EDE(-Q) Eating Concern scores at baseline predict abstinence from

binge eating and effect sizes for the EDE(-Q) Restraint scale in the

random effects model Higher scores on the EDE(minusQ) Eating Concern

scale at baseline are associated with higher abstinence rates in both

the adjusted randomeffects modelsHigher scoreson theEDE(-Q) Eating

Concern scale at baseline are associated with a larger effect size for the

EDE(-Q)Restraint scale in the unadjusted random effects model Inaddi-

tion EDE(-Q) Restraint scores at baseline predict effect sizes for the

EDE(-Q) Eating Weight and Shape Concern scales in the 1047297 xed effects

model (see Table 4) All results are consistent

EDE(-Q) Weight Concernscores at baseline predict effect sizes for the

EDE(-Q) Eating and Weight Concern scales in the random effects model

Higherscores on theEDE(-Q) Weight Concernscaleat baselineare asso-

ciated with larger effect sizes for the EDE(-Q) Eating and Weight Con-

cern scales in the random 1047297 xed effects model adjusted for dropoutrates In addition EDE(-Q) Weight Concern scores at baseline predict

effect sizes for the frequency of binge eating episodes abstinence from

binge eating and effect sizes for the EDE(-Q) Restraint and Shape

Concern scales in the 1047297 xed effects model (see Table 4) All results are

consistentEDE(-Q) Shape Concern scores at baseline predict abstinence from

binge eating and effect sizes for the EDE(-Q) Eating Concern scale in

the random effects model Higher scores on the EDE(-Q) Shape Concern

scale at baseline are associated with larger effect sizes for the frequency

of binge eating episodes in the unadjusted random effects model Higher

scores on the EDE(-Q) Shape Concern scale at baseline are associated

withlarger effectsizesfor theEDE(-Q) EatingConcern scale in theunad-

justed random effects model and inthe random effects model adjusted for

dropout rates In addition EDE(-Q) Shape Concern scores at baselinepredict effect sizes for the frequency of binge eating episodes effect

sizes for the EDE(-Q) Restraint Weight and Shape Concern scales in

the 1047297 xed effects model (see Table 4) All results are consistent

Participants age predicts effectsizesfor thefrequency of binge eating

episodes abstinence from binge eating and effect sizes for the EDE(-Q)

Restraint Eating Weight and Shape Concernscales in the random effects

model A higher age is associated with larger effect sizes for the frequen-

cy of binge eating episodes in all models A higher age is associated with

higher abstinence rates in the unadjusted random effects model and the

random effects model adjusted for intervention completion rates and

intervention completion de1047297nitions A higher age is associated with

smaller effects for the EDE(-Q) Restraint scale in the random effects

model adjusted for intervention completionrates and intervention com-

pletion de1047297nitions A higher age is associated with larger effects for the

EDE(-Q) Eating Concern scale in the unadjusted random effects model

and the random effects model adjusted for dropout rates A higher age

is associated with larger effects for the EDE(-Q) Weight Concern scale

in the unadjusted random effects model and the random effects model

adjusted for dropout rates A higher age is associated with larger effect

sizes for the EDE(-Q) Shape Concern scale in the unadjusted random

effects model and the random effects model adjusted for dropout rates

All results are consistent

Participants BMI predicts effect sizes for the frequency of binge eatingepisodes and the EDE(-Q) Restraint Eating Weight and Shape Concern

scales in the random effects model A higher BMI is associated with larger

effect sizes for the frequency of binge eating episodes in all models A

higher BMI is associated with smaller effects for the EDE(-Q) Restraint

scale in the random effects model adjusted for intervention completion

rates and intervention completion de1047297nitions A higher BMI is associated

withlarger effects for the EDE(-Q) Eating Concern scale in the unadjustedrandom effects model A higher BMI is associated with larger effectsfor the

EDE(-Q) Weight Concern scale in the unadjusted random effects model A

higher BMI is associated with larger effects for the EDE(-Q) Shape Con-

cern scale in the unadjusted random effects model and the random effects

model adjusted for intervention completion rates and intervention com-

pletion de1047297nitions In addition participants BMI predicts effect sizes for

the frequency of binge eating episodes abstinence from binge eating

and effect sizes for the EDE(-Q) Restraint Eating Weight and Shape

Concern scales in the random effects model (see Table 4) All results are

consistent


All unadjusted analyses were repeated with exclusion of interven-

tions which had allowed additional pharmacotherapy or a placebo

medication to the self-help intervention Results are summarized in

Appendix D

4 Discussion

The objective of this meta-analysis analysis was to shed light on the

complex associations between study intervention and patient charac-teristics patient participation measures and intervention outcomes in

manualized self-help-trials for bulimia nervosa and binge eating disor-

der We examined the different measures of patient participation re-

ported in the individual studies and integrated these measures across

the different trials Subsequently we identi1047297ed moderators of participa-

tion and intervention outcomes Lastly we examined if and how associ-

ations between moderators and intervention outcomes are affected by

participation measures Results from metaregression analyses are

prone to aggregation bias especially when investigating the role of pa-

tientcharacteristics The associationbetween average patient character-

istics and outcomes across trials may be entirely different from the

association between patients individual data and the same outcome

within individual trials (Thompson amp Higgins 2002) We therefore

compare our 1047297ndings to 1047297ndings regarding moderators from the indi-vidual studies and discuss potential discrepancies


Authors reported study dropout rates (ie rates of participants not

completing post-intervention assessments) for 51 of the intervention

conditions as a rather broad participation measure The range of study

dropout rates was very large (1 to 88 with a median of 25) The

range of these rates is comparable to that reported for self-help inter-

ventions for other mental disorders (eg 2-83 in Internet-based treat-

ment programs for psychological disorders in general (Melville et al

2010) and 1ndash50 in randomized controlled trials examining Internet-

based interventions for anxiety and depression (Christensen et al

2009)) Similarly mean drop-out rates in outpatient psychotherapy


7172019 1-s20-S0272735814000312-main


trials for eating disordersrange from 29 to 73 (Fassino Piero Tomba

amp Abbate-Daga 2009)

Between 1 and 88 of participants in 51 intervention conditions

completed the intervention to which they had been assigned However

intervention completion was de1047297ned inconsistently by study authors

Most frequently authors used objective measures to de1047297ne intervention

completion such as the number of guidance sessions a participant had re-

ceived or the number of times a participant had logged on to an Internet

platform (k = 18) In a substantial number of conditions interventioncompletion was merely de1047297ned as the provision of post-intervention

data (k = 9) Also in some studies intervention completion was de1047297ned

based on participants report rather thanon objective measures (k = 12)

Lastly in a considerable number of studies authors did not specify their

de1047297nition of intervention completion at all (k = 11)

Some of theauthors provided very detailed information on interven-

tion participation thus enabling us to determinethe number of patients

who received a certain dosage of the intervention In 11 conditions in-

formation was given on how many participants completed three-

quarters of the intervention these rates range from 20 to 81 In 13

conditions informationwas givenon how manyparticipants completed

less than half of the intervention these rates range from 17 to 58


A number of study intervention and patient characteristics were

found to be signi1047297cantly associated with participation measures How-

ever only some of the associations turned out to be robust based on

the results of both 1047297xed and random effects models and only these

will be discussed here in more detail

Study dropout which is the weakest albeit most commonly reported

indicator of participation is robustly predicted by the type of interven-

tion participants diagnoses age and body mass index (BMI) and base-

line EDE(minusQ)-Restraint Study dropout rates are lowest in Internet-

based interventions and highest in CD-ROM interventions More

patients in studies recruiting patients with binge eating disorder

(BED) completed post-intervention assessments than in studies

recruiting patients with bulimia nervosa (BN) Participants in studies

recruiting patients with BED exhibited less EDE(minus

Q) Restraint wereolder and had higher BMIs than participants in studies recruiting pa-

tients with BN mdash and a higher age higher BMI and lower baseline

EDE(-Q) Restraint are also associated with lower study dropout rates

When comparing our results withthe 1047297ndings from individualstud-

ies study dropout in patients with bulimia nervosa exceeded study

dropout in patients with binge eating disorder (Graham amp Walton

2011) in one individual study Also in line with our 1047297ndings in two

studies patients with higher dietary restraint (Ramklint Jeansson

Holmgren amp Ghaderi 2012 Wilson et al 2000) were more prone to

dropout None of the individual studies showed associations contrary

to our own 1047297ndings In addition to the moderators detected in the

metaanalysis eating concern (Pritchard Bergin amp Wade 2004 Wilson

et al 2000) weight concern ( Jones et al 2012 Wilson et al 2000)

and shape concern (Carrard Crepin Rouget Lam Golay et al 2011Pritchard et al 2004 Wilson et al 2000) were associated with study

dropout A higher binge eating frequency at baseline was associated

with a higher dropout rate in a subsample of the SALUT study

(Carrard et al 2006) but not in the full sample (Carrard Fernandez-

Aranda et al 2011) In one study associations between patient charac-

teristicsand dropoutvaried greatly between sites (Mitchell et al 2011)

In a number of other individual studies authors did not 1047297nd any signif-

icant differences between study dropouts and study completers

(Banasiak Paxton amp Hay 2005 Cassin 2008 Furber et al 2004

Ghaderi 2006 Loeb Wilson Gilbert amp Labouvie 2000 Schmidt et al

2008 Treasure Schmidt Troop amp Todd 1996)

Treatment completion rates could not be robustly predicted by any of

the study treatment and patient characteristics even after adjusting for

intervention completion de1047297nitions

In the subset of studies with more detailed information on the dos-

age of intervention participants had received the rate of participants

who completed more than 75 of the intervention was robustly predicted

by study designand intervention type More patients in RCTs and in bib-

liotherapy completed at least three quarters of theintervention Therate

of participants who completed less than 50 of the intervention was ro-

bustly predicted by guidance and participants diagnoses age and

BMI More participants in unguided self-help and more participants in

studies recruiting BN patients younger patients and patients with alower BMI completed less than half of the intervention

In some of the individual studies moderators of participation were

reported but 1047297ndings are heterogeneous and none of the 1047297ndings

from individual studies are consistent with the 1047297ndings from our

metaanalysis A higher frequency of binge eating and vomiting was as-

sociated with failure to engage in the intervention in one study (Bara-

Carril et al 2004) while in another there were no differences in symp-

tom severity between patients who engaged in the intervention and

those who did not (Murray et al 2003) In one study participants

who completed more than half of the sessions had higher baseline

EDE(-Q) Eating Concern scores at baseline (Pretorius et al 2009)

while higher EDE(-Q) Weight Concern scores were associated with

poorer overall compliance in another study (Troopet al 1996) Patients

who exhibited greater dietary restraint at baseline reported having read

more chapters of the self-help book provided in one study (Thiels et al

2001) while in another no differences between intervention com-

pleters and noncompleters were found (Steele amp Wade 2008) These in-

consistencies are likely to at least in part result from inconsistent

de1047297nitions and measures of participation

43 Moderators of intervention outcomes

As anticipated associations between study intervention and patient

characteristics and intervention outcomes varied depending on whether

study dropout or intervention completion rates were taken into account

or not Not all associations were robust and remained statistically signi1047297-

cant after adjusting For an overview of associations that proved to be

statistical artifacts after adjusting and associations that could only be de-

tectedafter adjustingpleaseview Tables3 and 4 Here we will discuss ro-bust 1047297ndings (ie those con1047297rmed in both the 1047297xed and random effects

model adjusted for study dropout rates or in both the 1047297xed and random

effects model adjusted for intervention completionrates and intervention

completion de1047297nitions)

Intervention type predicted the reduction in binge eating frequency

and in EDE(-Q) Restraint scores with Internet-based interventions

yielding better outcomes Guidance predicted the reduction in binge

eating frequency abstinence from binge eating and the reduction in

EDE(-Q) Eating Weight and Shape Concerns with guided self-help

yielding better outcomes A higher number of sessions in guided self-

help predicted abstinence from binge eating the reduction in EDE(-Q)

Restraint Weight and Shape Concerns with more sessions yielding bet-

ter outcomes

Participants diagnoses predicted abstinence from binge eating withsamples of BED patients yielding better outcomes Participants baseline

EDE(-Q) Eating and Shape Concern scores predicted abstinence from

binge eating and the reduction in EDE(-Q) Restraint with patients

with higher baseline scores yielding better outcomes Participants base-

line EDE(-Q) Eating Weight and Shape Concern scorespredicted the re-

duction in binge eating frequency and in EDE(-Q) Eating Concern with

patients with higher baseline scores yielding better outcomes Partici-

pants baseline binge eating frequency predicted the reduction in

EDE(-Q) Restraint and Eating Concern with patients reporting more

binge eating episodes at baseline yielding better outcomes of EDE(-Q)

Restraint and poorer outcomes of EDE(-Q)Eating Concern Participants

baseline EDE(-Q)Restraint level predicted the reduction in binge eating

frequency and abstinence from binge eating with patients with higher

baseline scores achieving poorer outcomes However associations


7172019 1-s20-S0272735814000312-main


between participants baseline levels of EDE(-Q) Restraint EDE(-Q)

Eating and Weight Concern scores and reductions in the respective

scales must be interpreted with caution since 1047298oor effects are likely to

in1047298uence these effects Participants age predicted the reduction in

binge eating frequency abstinence from binge eating and the reduction

in EDE(-Q)Restraint Eating Weight andShape Concernssamples with

older patients showing poorer outcomes in EDE(-Q) Restraint and better

outcomes in the other outcome measures Participants BMI predicted the

reduction in binge eating frequency abstinence from binge eating andthe reduction in EDE(-Q) Restraint Eating and Shape Concerns samples

of patients with higher BMIs yielding poorer outcomes in EDE(-Q) Re-

straint and better outcomes in the other outcome measures

Overall participants age predicted the highest number of out-

comes (all 6 analyzed outcomes) followed by guidance partici-

pants BMI the number of sessions in guided self-help and participants

baseline EDE(-Q) Restraint scores (3 outcomes) Participants age could

either be a proxy for illness duration ndash and illness related distress and

thus motivation to change is increasing along with illness duration ndash or

it could be related to participants diagnoses as the mean age of onset

for BN is lower than for BED (Kessler et al 2013) Both abstinence from

binge eating and binge eating frequency as the core outcomes of BN and

BED were robustly predicted by guidance participants baseline

EDE(-Q) Restraint and Shape Concerns and participants BMI and age

Within individual studies reports on moderators of intervention

outcomes were scarce and 1047297ndings were heterogeneous In our

metaanalysis abstinence rates were higher in samples of BED patients

when not adjusting for dropout rates However when adjusting for

dropout rates abstinence rates in samples of BED patients were lower

so acrossstudies differences in abstinence rates must partly be attribut-

ed to differences in dropout In one individual study improvements re-

garding binge eating episodes were greater for patients with BED than

for those with BN (Ljotsson et al 2007) while in another study there

were no differences in improvements made by patients with BN and

BED(Grahamamp Walton 2011) Baseline bingeeating frequencypredict-

ed improvements in EDE(-Q) Restraint and Eating Concern but not in

binge eating in our metaanalysis In two of the individual studies a

higher binge eating frequency at baseline was associated with a poorer

outcome (Loeb et al 2000 Thiels Schmidt Troop Treasure amp Garthe2000) while symptom severity did not predict intervention response

in two other studies (Cooper Coker amp Fleming 1996 Masheb amp Grilo

2008) In our metaanalysis higher EDE(minusQ) Shape Concern scores at

baseline were associated with greater improvements regarding binge

eating In one of the individual studies the opposite was the case a

greater overevaluation of weight and shape at baseline was associated

with a higher binge eating frequency at post-intervention (Steele

Bergin amp Wade 2011) In our metaanalysis abstinence rates were

higher in samples of older patients while in one of the individual stud-

ies binge remission was not associated with age (Masheb amp Grilo

2008)

44 Implications for the design of future interventions

In the absence of clear guidelines to determine the clinical relevance

of a statistically signi1047297cant association between a moderatorand an out-

come we decided to consider and discuss each association separately

This approach was chosen to illustrate the cost and bene1047297ts of changes

in the design and other characteristics of the interventions for both the

provider of the intervention (usually the clinician) and the patient

441 How should self-help interventions be designed to maximize

participation and intervention outcome

Study dropout rates in bibliotherapy and CD-ROM based interven-

tions are up to twice as high as study dropout rates in Internet-based

interventions (mean difference 14) Partly this may be due to the

fact that in all but one of the CD-ROM intervention conditions partici-

pants had to come to a clinic to access the intervention In unguided

self-help about half of the patients completed less than 50of thetreat-

ment In guided self-help this wastrue for only just a third of patients mdash

patients are less likely to drop out of the intervention in the 1047297rst half if

they receive guided self-help In bibliotherapy almost two out of three

patients completed more than 75 of the intervention while in CD-

ROM and Internet-based interventions just over one out of three

patients did so Participation is de1047297ned differently though In Internet-

based interventions participation is usually measured electronically

with every page opened recorded in a participant log Completing morethan 75 of the intervention was therefore de1047297ned as having ldquoworkedrdquo

through 75 of the Internet modules On the other hand all of the biblio-

therapy interventions with suf 1047297cient information to determine how

many patients had completed more than 75 of the intervention were

guided self-help interventions and completing more than 75 of the in-

tervention here was de1047297ned as having attended 75 of the guidance ses-

sions Not surprisingly patients mayfeel more obligedto keep face to face

appointments with a person than to log on to an Internet-platform and

although all Internet-based interventions were guided too by email per-

sonal contact may help patients keep up with the self-help program

However if similar intervention completion rates could be achieved in

Internet-based interventions they might be superior to bibliotherapy

and CD-ROM interventions regarding the reduction of binge eating fre-

quency and dietary restraint mdash supported by the larger effect sizes (49

and 72) of these interventions

Guidance had the strongest impact on effect sizes of eating disorder

related attitudes with guided self-help yielding effect sizes by 42ndash67

larger than unguided self-help when assuming similar dropout or inter-

vention completion rates Impact on the reduction of binge eating and

abstinence from binge eating was smaller but abstinence rates in guid-

ed self-help were still more than twice as high as in unguided self-help

and effect sizes for the reduction of binge eating was by 25 larger in

guided self-help The number of sessions in guided self-help had the

strongest impact on the reduction of dietary restraint with just one ad-

ditional session to the mediannumber of 8 sessions increasing theeffect

sizes by 20 Effects on abstinence from binge eating and weight and

shape concernswere smaller Five additional sessions would raise absti-

nence rates by 10 and two to four additional sessions would raise the

effect sizes for weight and shape concerns by 20 Previous research hasshown that especially patients with chronic bulimia nervosa are less

motivated and con1047297dent to change dietary restraint in comparison to

binge eating (Perkins et al 2007) Guidance may play an important

role in tackling patients fears of giving up restrained eating

Our 1047297ndings show that in self-help for bulimia nervosa and binge

eating disorder guidance can improve both intervention participation

and outcomes The same was true for self-help studies addressing men-

tal disorders other than eating disorders (eg Christensen Grif 1047297ths

Korten Brittliffe amp Groves 2004 Clarke et al 2005 Kenwright

Marks Graham Franses amp Mataix-Cols 2005 Simon et al 2011) Like-

wise interventions such as counseling or social support have also been

shown to facilitate adherence to medical regimens and other self-

management behaviors (Roter et al 1998) Across all guided self-help

conditions the guides quali1047297cation was associated with interventioncompletion and key outcomes namely the reduction of binge eating

and weight and shape concerns with guidance by eating disorder

specialists CBT therapists or mental health specialists yielding better

results than nurse or GP Findings also indicate that face-to-face guid-

ance may lead to better intervention participation than email guidance

Internet-based interventions may have some advantages over biblio-

therapy regarding outcomes but ways to improve participation in

such interventions areneeded In theSALUTstudyauthors reported sig-

ni1047297cant differences in study dropout rates between coaches with two

coachesretaining a markedly highernumber of patients in the interven-

tion Interviews with the coaches showed that these coaches ldquoprovided

more support and had a more therapeutic approachrdquo or monitored par-

ticipants ldquoin a more diligent wayrdquo (Carrard Fernandez-Aranda et al

2011) The advantages of face-to-face guidance in bibliotherapy could


7172019 1-s20-S0272735814000312-main


be combined with the possible advantages of Internet-based interven-

tions such as interactive elements or immediate feedback by augment-

ing email guidance with (view)phone guidance or by providing

guidance by specialists

442 Who bene 1047297ts most from self-help interventions

Study dropoutrates are up to twice as high in studies with either BN

patients only or studies with mixed samples of both BN and BED pa-

tients compared with studies with BED patients only Each additionalpoint on the mean EDE(-Q) Restraint Scale score (with scores ranging

from 0 to 6) in a study sample adds 16 to the dropout rate Each addi-

tional 10 years of mean age in a study sample reduces the dropout rate

by 6 Similarly each additional 10 BMI points of mean BMI in a study

sample reduces the dropout rate by 16 In summary study dropout

rates are substantially lower in studies with BED patients mdash who also

tend to exhibit less dietary restraint are older and have higher BMIs

While almost every secondpatient in samples with BN patients dropped

out of the intervention in the 1047297rst half only about one in four patients

did so in samples with BED patients and mixed samples with both BN

and BED patients

Participants diagnoses were clearly associated with only one out-

come participantsin studiesrecruiting only BN patients were less likely

to be abstinent from binge eating than participants in studies recruiting

only BED patients or both BN and BED patients with 17 lower absti-

nence rates when assuming similar intervention completion rates

Age BMI and EDE-(Q) Restraint (which are very likely to be confound-

ed with the diagnoses) showed associations with more outcomes To

illustrate these 1047297ndings we compare a hypothetical sample of patients

on average40 years of agewith a hypotheticalsample of patients on av-

erage 30 years of age assuming similar study dropout and intervention

completion rates Based on our data the older sample would for exam-

ple yield an effect size smaller by 44 in the reduction of dietary re-

straint an effect size higher by 20ndash28 for the reduction in binge

eating and an effect size higher by 33 for the reduction in eating con-

cerns compared with the younger sample We found a similar pattern

for participants BMI Again based on a hypothetical sample of patients

in the normal weight range with an average BMI of 225 kgm 2 com-

pared with a hypothetical sample of overweight and obese patientswith an average BMI of 325 kgm2 and assuming similar study dropout

and intervention completion rates the sample of overweight and obese

patients wouldhavean effect size smaller by 53for the reductionin di-

etary restraint larger effect sizes higher by 27ndash36 for the reduction in

binge eating and effect sizes larger by 32 and 29 for the reduction of

eating and shape concerns Also abstinence rates would differ by 11

in favor of the sample of overweight and obese patients

Higher degrees of baseline EDE(-Q) Restraint will less likely result in

lower rates of binge eating at post-intervention Again translated to a

hypothetical sample whose average baseline EDE(-Q) Restraint score

is 30 the effect size for the reduction in binge eating would be larger

by 30 and the abstinence rate would be 9 higher compared with a


is 40 assuming similar intervention completion ratesBaseline binge eating frequency which is a proxy for symptom se-

verity was positively associated with the reduction in EDE(-Q) Restraint

and negatively associated with the reduction of EDE(-Q) Eating Con-

cern A higher symptom severity at baseline was linked to both higher

baseline EDE(-Q) Restraint and Eating Concern thus in theory allowing

for a larger improvement in both measures When looking across indi-

vidual studies effect sizes for the reduction of EDE(-Q) Eating Concern

tend to be larger than for EDE(-Q) Restraint However our1047297ndings sug-

gest especially that in samples of patients with more severe baseline

symptoms the reduction of dietary restraint might be easier to achieve

than the reduction of concerns about eating

Eating concern at baseline is positively associated with abstinence

rates of binge eating and the reduction in EDE(-Q) Restraint The

EDE(-Q) Eating Concern scale covers several items regarding shame or

guilt about eating hence this scale might indirectly measure theamount

of suffering from the eatingdisorderindividuals who experience higher

levels of suffering might have a higher motivation to change and hence

bene1047297t more from an intervention

Weight and shape concerns at baseline are positively associated

with the reduction of binge eating and eating concern Again higher

weight and shape concerns may be associated with higher levels of suf-

fering and a higher motivation to change

45 Clinical recommendations

Our1047297ndings suggest that BED patients (whoare older have a higher

BMI and exhibit less dietary restraintat baseline)are more likelyto per-

sist with the self-helpintervention and even beyond the effect of differ-

ent intervention completion rates might bene1047297t substantially more

from self-helpinterventions than BN patients In the treatment of eating

disorders reestablishing a pattern of regular eating is usually the 1047297rst

step From our own clinical experience BN and BED patients differ in

their motivation fears and ambivalence regarding those changes in eat-

ing behavior BED patients even after learning that weight loss will not

be the focus of treatment often hope to lose weight once their eating

behavior has changed Their eating behavior outside binge eating epi-

sodes is often unstructured while they do not feel more guilty about

eating than healthy controls (Wil1047298ey Schwartz Spurrell amp Fairburn

2000) To normalize their eating behavior they need to structure their

meals but they do not need to increase the amount of calories con-

sumed between binge eating episodes BN patients have an intense

fear of gaining large amounts of weight (Treasure amp Schmidt 2008)

once they exchange their pattern of alternately dieting binge eating

and compensating for regular meals and snacks Their eating behavior

outside binge eating episodes is often restricted and they feel guilty

about eating (Wil1047298ey et al 2000) To normalize their eating behavior

they need to increase the amount of calories consumed between binge

eating episodes and their initial motivation to do this is often low

(Perkins et al 2007) The initial changes during treatment might thus

be a lot harder for BN than BED patients and their fears may not have

been addressed adequately by some of the previous self-help interven-

tions causing them to drop out of treatment more frequently orresulting in poorer outcomes

In line with these considerations we also found that in studies with

BN patients guidance was associated with higher intervention comple-

tion rates higher abstinence from binge eating and greater reduction

of dietary restraint (detailed data available upon request) It therefore

seems that BN patients compared with BED patients need more en-

couragement and support during self-help interventions which can be

better provided by a non-virtual guide Also our data suggest that the

guides quali1047297cation is not trivial and guidance provided by mental

health specialists is associated with better treatment completion rates

and larger effects on key outcomes than non-specialist guidance

It can be argued that specialist guidance is more costly and makes

treatment dissemination more dif 1047297cult than non-specialist guidance

From a pragmatic point of view smaller effect sizes sometimes mayneed to be accepted in order to reach more people However one has

to consider that patients with mental disordersmay attribute treatment

failure to internal factors rather than the treatment and thus their mo-

tivation and con1047297dence to change their behavior are likely to be com-

promised by poorly delivered initial treatment Therefore guides

should be chosen carefully and should be trained suf 1047297ciently in how

to guide patients and intervention 1047297delity should be regularly moni-

tored and maximized Studies on adherence in medicine taking behav-

ior have consistently shown that ndash in general ndash interventions to

promote adherence areef 1047297cacious (Horne et al 2005) Consideringvar-

iables associated with guidance might however be only one means of

improving adherence A variety of other variables not reported in the

studies included in our review such as patients health beliefs illness-

related attitudes or other variables related to the patients speci1047297c


7172019 1-s20-S0272735814000312-main


needs and preferences as well as other characteristics of the interven-

tion might also be important to increase adherence behavior

46 Limitations of our metaanalysis

For reasons of clarity and readability we limited the treatment out-

comes included in our meta-analyses As the reduction of compensatory

behaviors is relevant as an outcome only in patients with BN we chose

to exclude this outcome from our analyses In studies on treatment out-come and long-term course of bulimia nervosa binge eating and com-

pensatory behaviors are usually highly correlated (eg Edler Haedt amp

Keel 2007) However we are awarethat in patients with BN thereduc-

tion of compensatory behavior might be a more conservative indicator

for overall symptom reduction and long-term outcome than the reduc-

tion of binge eating (Agras et al 2000 Fahy amp Russell 1993)

Our1047297ndings are limited by the inclusion of case series and the calcu-

lation of prendashpost-effect sizes for the intervention groups only rather

than controlled effect sizes However since the number of randomized

controlled trials on manualized self-help interventions with an untreat-

ed control groupis limitedto 13 studies so far moderator effects would

have been dif 1047297cult to detect and very likely hard to interpret

A major limitation of our meta-analysis is the high variability of def-

initions of intervention completion across the included studies Re-

searchers vary in their use of terms to describe the premature

termination of an intervention or study terms like ldquodropoutrdquo ldquotreat-

ment dropoutrdquo ldquoattritionrdquo ldquonon-usagerdquo ldquonon-compliancerdquo are some-

times used interchangeably de1047297nitions are arbitrary or unclear and

the evaluation of dropoutrates is complicated by thelack of a consistent

operationalization (Melville et al 2010) Not surprisingly in our meta-

analysis the number of de1047297nitions of intervention completion was al-

most as high as the number of included studies At this point it must

therefore remain unclear if the absence of con1047297rmed moderators of in-

tervention completion is related solely to the lack of a gold standard of

reporting intervention participation in self-help or if patient character-

istics other than those primarily included in intervention trials may

moderate participation in self-help interventions

Other limitations may result from the employment of metaregression

to identify potential moderatorsof participation and outcomes Causal in-terpretations are impossible with this approach Associations with one

trial characteristic may re1047298ect an underlying association with another

possibly unknown correlated characteristic Also as stated above patient

characteristics need to be averaged for each trial and associations ob-

served across trials may be different from associations observed within

each trial (aggregation bias) Also information on potential moderators

was only available for a subset of studies Analyses are therefore based

on these subsets rather than on the full sample which could also bias re-

sults (Thompson amp Higgins 2002) Findings of our moderator analyses

can however be used to generate hypotheses to be investigated in future

trials

To enhance comparability between effect sizes we used or calculat-

ed ITT effect sizes for all studies To estimate ITT effect sizes from com-

pleter data for pragmatic reasons we assumed a zero effect for studydropouts This method resemblesthe simple and highly criticized impu-

tation method of carrying the baseline observation forward utilized in

clinical trials which arbitrarily assumes that participants who drop

out from a studydo not change between pre- and post-intervention as-

sessments While for clinical trials more adequate methods of data im-

putation are available (Little et al 2012) this is not the case for

metaanalyses In our review effect sizes in trials with large dropout

rates may thereby be systematically underestimated However when

adjusting metaregression analyses of potential moderators for dropout

rates this bias is likely to be minimized Lastly we cannot be sure how

many of the trial participants received a self-help intervention solely

or some additional intervention (eg counseling medication other

treatment) The majority of trials testing self-help interventions did

not explicitly exclude patients currently on medication nor did they

report how many participants took antidepressants at a dosage that

might have affected their eating disorder We therefore decided not to

exclude studies augmenting self-help with medication (or vice versa)

Nevertheless it can be assumed that the effect of medication on core

eating disorder symptoms and related behaviors and attitudes is differ-

ent from the effect of a self-help intervention Fluoxetine for example

has been shown to reduce binge eating and purging but little is

known about its effect on speci1047297c eating disorder related attitudes and

behaviors such as dietary restraint and weight concern (Steinglassamp Walsh 2004) Also recovery rates are low (Flament Bissada amp

Spettigue 2012) Orlistat on theother hand works by preventing theab-

sorption of fat in the body (Guerciolini 1997) (with a number of highly

unpleasant gastrointestinal side effects) and is unlikely to affect appe-

tite theurge to binge or eatingdisorderrelated attitudesand behaviors

Orlistat would potentially prevent patients from binge eating high fat

foods but not prevent them from binge eating at all in the long run In

the sensitivity analyses we could not detect any systematic differences

between interventions augmentingself-helpwith medicationand those

providing self-help only

5 Conclusion

Self-help interventionscan contribute to bridging the treatment gap

for bulimia nervosa (BN) and binge eating disorder (BED) especially if

the features of their delivery and indications are considered carefully

While patients with BED might bene1047297t from both guided and unguided

self-help guidance seems especially important for patients with BN

both to help them keep up with the self-help intervention and to

achieve symptom improvements

Also our 1047297ndings suggest that interventions guided by mental

health specialists are more effective than interventions guided by non-

specialists Partly this could result from specialists detailed knowledge

on eating disorders and their treatment but specialists might also pur-

sue a more patient centered approach to guidance which has been

thought to impact both adherence and outcomes of interventions

(Horne et al 2005)

However further qualitative and quantitative research is needed to

determine what optimal guidance is what a good guide should andshould not do if poor guidance can do any harm or what kind or dosage

of guidance would meet the needs of the majority of patients Such re-

search could follow investigations on the patient provider interaction

and on health care communication examining the context process

and content of guidance In addition examining the patients beliefs

and their perspectives of illness and treatment and addressing these in

interventions might help explain individual variations in adherence

and thus increase adherence behavior (Horne et al 2005)

According to the WHO ldquoadherence is an important indicator of

health system effectivenessrdquo (Sabateacute 2001 p 8) and thus for the effec-

tiveness of self-help interventions Because we could show that associ-

ations between moderators and treatment effects based on intent-to-

treat samples are noticeably affected by study drop-out or treatment

completion rates we suggest that information about dropout and treat-ment completion be taken into account in future metaregression-

analyses

A major challenge in our meta-analysis wasthe lack of a standard for

reporting adherence or participation in the studies As a consequence

we were unable to determine to what degree participation depends

on either intervention or patient characteristics and what degree of

participation is neededto achieve a certain outcome To further improve

self-help interventions andto be able to tailor them to the speci1047297c needs

of different subgroups of participants ldquoa number of usage and dropout

attrition metrics can (and should) be provided in addition to ef 1047297cacy

measuresrdquo (Eysenbach 2005) when reporting the results of self-help

studies and there should be a more consistent approach to operationalize

those measures Firstly authors should clearly distinguish between study

dropout (ie the failure to complete assessments) and intervention


7172019 1-s20-S0272735814000312-main


dropout (ie the failure to complete the intervention) Secondly partici-

pants who terminated the intervention prematurely should not per se

be excluded from post-intervention assessments Thirdly authors should

provide detailed information on how and to what degree or ldquodosagerdquo

participants used the program Especially with online interventions

these data would be relatively easy to obtain and report and could be

illustrated as attrition curves (Eysenbach 2005) Reporting measures of

participation more consistently and explicitly will further contribute to

ourunderstandingof what kind of interventions will be utilized most like-ly by patientswhospeci1047297cally will bene1047297t most from them and how they

work best

Appendix A Supplementary data

Supplementary data to this article can be found online at httpdx

doiorg101016jcpr201401003

References

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Bailer U Zwaan MD Leisch F Strnad A Lennkh-WolfsbergC amp El-Giamal N (2004)Guided self-help versus cognitivendashbehavioral group therapy in the treatment of bulimia nervosa International Journal of Eating Disorders 35(4) 522

Banasiak S J Paxton S J amp Hay P (2005) Guided self-help for bulimia nervosa in pri-mary care A randomized controlled trial Psychological Medicine 35(9) 1283ndash1294

Bara-Carril N Williams C J Pombo-Carril M G Reid Y Murray K amp Aubin S (2004)A preliminary investigation into the feasibility and ef 1047297cacy of a CD-ROM-basedcognitivendashbehavioral self-help intervention for bulimia nervosa International Journal of Eating Disorders 35(4) 538

Bell Lamp HodderL (2001)An evaluation of a supervised self-help programme forbulim-ic disorders Clinical Psychology amp Psychotherapy 8(4) 252ndash262

Bell L amp Newns K (2004) What factors in1047298uence failure to engage in a supervisedself-helpprogramme for bulimia nervosa and binge eating disorder European Eating Disorders Review 12(3) 178

Borenstein M Hedges L V Higgins J P T amp Rothstein H R (2011) Introduction tometa-analysis Chichester John Wiley amp Sons

Carrard I Crepin C Rouget P Lam T Golay A amp Van der Linden M (2011)Randomised controlled trial of a guided self-help treatment on the Internet forbinge eating disorder Behaviour Research and Therapy 49(8) 482ndash491

CarrardI CrepinC RougetP Lam T vanderLindenMamp Alain G(2011) Acceptanceand ef 1047297cacy of a guided internet self-help treatment program for obese patients withbinge eating disorder Clinical Practice and Epidemiology in Mental Health 7 8ndash18

Carrard I Fernandez-Aranda F Lam T Nevonen L Liwowsky I amp Volkart AC (2011)Evaluation of a guided internetself-treatmentprogrammefor bulimianervosain sev-eral European countries European Eating Disorders Review 19(2) 138ndash149

Carrard IRouget PFernandez-ArandaF Volkart AC DamoiseauM amp Lam T (2006)Evaluation and deployment of evidence based patientself-management support pro-gramfor bulimia nervosa International Journal of MedicalInformatics 75(1)101ndash109

Carter J C Olmsted M P Kaplan A S McCabe R E Mills J S amp Aimeacute A (2003)Self-help for bulimia nervosa A randomized controlled trial American Journal of Psy-chiatry 160(5) 973

Cassin S E (2008) Adaptedmotivational interviewing for women with binge eating disorder Arandomized control trial (68) US ProQuest Information amp Learning (Retrieved fromhttpsearchebscohostcomloginaspxdirect=trueampdb=psyhampAN=2008-99100-301ampsite=ehost-live )

Christensen H Grif 1047297ths KM amp FarrerL (2009) Adherence in internet interventions foranxiety and depression Journal of Medical Internet Research 11(2) e13

Christensen H Grif 1047297ths K M Korten A E Brittliffe K amp Groves C (2004) A compar-ison of changes in anxiety and depression symptoms of spontaneous users and trialparticipants of a cognitive behavior therapy website Journal of Medical Internet Research 6 (4) 13ndash22

Clarke G Eubanks D Reid E Kelleher C OConnor E amp DeBar L L (2005) Overcom-ing depression on the Internet (ODIN) (2) A randomized trial of a self-help depres-sion skills program with reminders Journal of Medical Internet Research 7 (2)

Cooper P J Coker S amp Fleming C (1994) Self-help for bulimia nervosa A preliminaryreport International Journal of Eating Disorders 16 (4) 401

Cooper P J Coker S amp Fleming C (1996) An evaluation of the ef 1047297cacy of supervisedcognitive behavioral self-help for bulimia nervosa Journal of Psychosomatic Research 40(3) 281

Edler C Haedt A A amp Keel P K (2007) The use of multiple purging methods as anindicator of eating disorder severity International Journal of Eating Disorders 40(6)515ndash520

EdlundM JWang PS BerglundP A Katz S J Lin Eamp Kessler R C (2002) Droppingout of mental health treatment Patterns and predictors among epidemiological sur-vey respondents in the UnitedStatesand Ontario American Journal of Psychiatry 159845ndash851

Einarson T R (1997) Pharmacoeconomic applications of meta-analysis for single groupsusing antifungal onychomycosis lacquers as an example Clinical Therapeutics 19(3)559ndash569

Eysenbach G (2005) The law of attrition Journal of Medical Internet Research 7 (1)Fahy T A amp Russell G F M (1993) Outcome and prognostic variables in bulimia

nervosa International Journal of Eating Disorders 14(2) 135ndash145FassinoS Piero A Tomba E amp Abbate-Daga G (2009) Factors associated with dropout

from treatment for eating disorders A comprehensive literature review BMC Psychiatry 9 67

Fernandez-Aranada F Santamaria J Nunez A Martinez C Krug I amp Cappozzo M(2008) Internet-based cognitive-behavioral therapy for bulimia nervosa A con-

trolled study European Psychiatry 23 S186-S186Fernandez-Aranda F Nunez A Martinez C Krug I Cappozzo M amp Carrard I (2009)Internet-based cognitivendashbehavioral therapy for bulimia nervosa A controlled studyCyberPsychology amp Behavior 12(1) 37ndash41

Fichter M Cebulla M Quad1047298ieg N amp Naab S (2008) Guided self-help for bingeeatingpurging anorexia nervosa before inpatient treatment PsychotherapyResearch 18(5) 594ndash603

Fichter M M Quad1047298ieg N Nisslmuumlller K Lindner S Osen B amp Huber T (2012) Doesinternet-based prevention reduce the risk of relapse for anorexia nervosa Behavior Research amp Therapy 50 180ndash190

Flament M F Bissada H amp Spettigue W (2012) Evidence-based pharmacotherapy of eating disorders International Journal of Neuropsychopharmacoly 15(2) 189ndash207

Fleiss J L (1981) Statistical methods for rates and proportions (2nd ed) New York JohnWiley and Sons

FurberG Steele A amp Wade T D (2004) Comparison of six- and eight-session cognitiveguided self-help for bulimia nervosa Clinical Psychologist 8(2) 64

Ghaderi A (2006) Attrition and outcome in self-help treatment for bulimia nervosa andbinge eating disorder A constructive replication Eating Behaviors 7 (4) 300ndash308

Ghaderi A amp Scott B (2003) Pure and guided self-help for full and sub-threshold bulimia

nervosa and binge eating disorder British Journal of Clinical Psychology 42(3) 257Graham L amp Walton M (2011) Investigating the useof CD-Rom CBTfor bulimianervosa

and binge eating disorder in an NHS adult outpatient eating disorders serviceBehavioural and Cognitive Psychotherapy 39(4) 443ndash456

Guerciolini R (1997) Mode of action of orlistat International Journal of Obesity andRelated Metabolic Disorders 21(S3) S12ndashS23

Hay P P Bacaltchuk JStefano S amp KashyapP (2009) Psychological treatments for bu-limia nervosa and binging Cochrane Database of Systematic Reviews(4) CD000562(Online)

Haynes R B Sackett D L amp Taylor D W (1979) Compliance in healthcare Baltimore Johns Hopkins University Press

Hedges L V (1981) Distribution theory for glasss estimator for effect size and relatedestimators Journal of Educational Statistics 6 107ndash128

Hedges L V amp Olkin I (1985) Statistical methods for meta-analysis Orlando FL AcademicPress

Hoek H W (2009) Planning an eating disorder service on the basis of epidemiologicaldata World Psychiatry 8(3) 157ndash158

Horne B Weinman J Barber N Elliott R amp MorganM (2005) Concordance adherenceand compliance in medicine taking National Co-ordinating Centre for NHS Service De-livery and Organisation R amp D (NCCSDO)

Huon G F (1985) An initial validation of a self-help program for bulimia International Journal of Eating Disorders 4(4) 573ndash588

Jones C Bryant- Waugh R Turner H M Gamble C Melhui sh L amp Jenkin s P E(2012) Who bene1047297ts most from guided self-help for binge eating An investiga-tion intothe clinical featuresof completers and non-completers EatingBehaviors 13(2)146ndash149

Kazdin A E amp Blase S L (2011) Rebooting psychotherapy research and practice to re-duce the burden of mental illness Perspectives on Psychological Science 6 (1) 21ndash37

Kenwright M Marks I GrahamC Franses A amp Mataix-Cols D (2005)Brief scheduledphone support from a clinician to enhance computer-aided self-help for obsessivendashcompulsive disorder Randomized controlled trial Journal of Clinical Psychology61(12) 1499ndash1508

Kessler R C Berglund P A Chiu W T Deitz AC Hudson J I amp Shahly V (2013) Theprevalence and correlates of binge eating disorder in the World Health O rganizationWorld Mental Health Surveys Biological Psychiatry 73(9) 904ndash914

Kraemer H C amp Blasey C M (2004) Centring in regression analyses A strategy to pre-vent errors in statistical inference International Journal of Methods in Psychiatric

Research 13(3) 141ndash151Lipsey M W amp Wilson D B (2000) Practical meta-analysis (applied social research

methods) Thousand Oaks SageLittle R J DAgostino R Cohen M L Dickersin K Emerson S S amp Farrar J T (2012)

The prevention and treatment of missing data in clinical trials New England Journal of Medicine 367 (14) 1355ndash1360

Liwowsky ICebulla Mamp Fichter M (2006)Neue Wegebei derBehandlungvon Bulim-ia nervosa MMW Fortschritte der Medizin 148(31ndash32) 31ndash33

Ljotsson BLundinC MitsellK CarlbringP Ramklint Mamp Ghaderi A (2007) Remotetreatment of bulimia nervosa and binge eating disorder A randomized trial of Internet-assisted cognitive behavioural therapy Behaviour Research and Therapy 45(4) 649ndash661

LoebK LWilsonG TGilbertJ S amp LabouvieE (2000)Guidedand unguidedself-helpfor binge eating Behaviour Research and Therapy 38(3) 259ndash272

Masheb R M amp Grilo C M (2008) Examination of predictors and moderators forself-help treatments of binge-eating disorder Journal of Consulting and ClinicalPsychology 76 (5) 900ndash904

Mayr S Erdfelder E Buchner Aamp Faul F (2007) A short tutorial of GPower Tutorials inQuantitative Methods for Psychology 3 51ndash59


7172019 1-s20-S0272735814000312-main


McClay C Waters L McHale C Schmidt U amp Williams C (2013) Online cognitivebehavioral therapy for bulimic type disorders delivered in the community by anonclinician qualitative study Journal of Medical Internet Research 15(3) e46

Medical Research Council (2010) MRC review of mental health research mdash Report of thestrategic review group London Medical Research Council

Melville K M Casey L M amp Kavanagh D J (2010) Dropout from Internet-based treat-ment for psychological disorders British Journal of Clinical Psychology 49(Pt 4)455ndash471

Mitchell J E Agras S Crow S Halmi K Fairburn C G amp Bryson S (2011) Steppedcare and cognitive behavioural therapy for bulimia nervosa Randomised trialBritish Journal of Psychiatry 198(5) 391ndash397

Mitchell J E Fletcher L Hanson K Mussell M P Seim H amp Crosby R (2001)The relative ef 1047297cacy of 1047298uoxetine and manual-based self-help in the treatmentof outpatients with bulimia nervosa Journal of Clinical Psychopharmacology 21(3)298

Murray K Pombo-CarrilM G Bara-Carril N Grover M Reid Y amp Langham C (2003)Factors determining uptake of a CD-ROM-based CBT self-help treatment for bulimiaPatient characteristics and subjective appraisals of self-help treatment EuropeanEating Disorders Review 11(3) 243

Nevonen L Mark M Levin B Lindstrom M amp Paulson-Karlsson G (2006) Evaluationof a new Internet-based self-help guide for patients with bulimic symptoms inSweden Nordic Journal of Psychiatry 60(6) 463ndash468

Ogrodniczuk J S Piper W E amp Joyce A S (2006) Treatment compliance in differenttypes of group psychotherapy mdash Exploring the effect of age Journal of Nervous andMental Disease 194(4) 287ndash293

Olfson M Mojtabai R Sampson N A HwangI Druss B amp Wang PS (2009) Dropoutfrom outpatient mental health care in the United States Psychiatric Services 60(7)898ndash907

Patel V Boyce N Collins P Y Saxena S amp Horton R (2011) A renewed agenda forglobal mental health The Lancet 378(9801) 1441ndash1442

PerkinsS J Murphy R SchmidtU amp Williams C (2006) Self-help and guided self-helpfor eating disorders Cochrane Database of Systematic Reviews 3 CD004191

Perkins S Schmidt U Eisler I Treasure J Berelowitz M amp Dodge E (2007) Motiva-tion to change in recent onset and long-standing bulimia nervosa Are there differ-ences Eating and Weight Disorders 12(2) 61ndash69

Pretorius N ArcelusJ Beecham J DawsonH DohertyF amp EislerI (2009) Cognitivendashbehavioural therapy for adolescents with bulimic symptomatology The acceptabilityand effectiveness of internet-based delivery Behaviour Research and Therapy 47 (9)729ndash736

Pretorius N Rowlands L Ringwood S amp Schmidt U (2010) Young peoples percep-tions of and reasons for accessing a web-based cognitive behavioural interventionfor bulimia nervosa European Eating Disorders Review 18(3) 197ndash206

Pritchard B J Bergin J L amp Wade T D (2004) A case series evaluation of guidedself-help for bulimia nervosa using a cognitive manual International Journal of Eating Disorders 36 (2) 144

Ramklint M Jeansson M Holmgren S amp Ghaderi A (2012) Guided self-help as the1047297rst step for bulimic symptoms Implementation of a stepped-care model withinspecialized psychiatry International Journal of Eating Disorders 45(1) 70ndash78

Rand C S amp Sevick MA (2000) Ethics in adherence promotion and monitoringControlled Clinical Trials 21 241Sndash247S

Robinson P amp Serfaty M (2008) Getting better byte by byte A pilot randomised con-trolled trial of email therapy for bulimia nervosa and binge eating disorderEuropean Eating Disorders Review 16 (2) 84ndash93

Rosenthal M (1994) The fugitive literature In H Cooperamp L V Hedges (Eds) The hand-book of research synthesis (pp 85ndash94) New York Russell Sage

Rosenthal R (1995) Writing meta-analytic reviews Psychological Bulletin 118 (2)183ndash192

Roter D L Hall J A Merisca R Nordstrom B Cretin D amp Svarstadt B (1998) Effec-tiveness of interventions to improve patient compliance A meta-analysis MedicalCare 36 (8) 1138ndash1161

Ruwaard J Lange A Broeksteeg J Renteria-Agirre A Schrieken B amp Dolan C V(2012) Online cognitivendashbehaviouraltreatmentof bulimicsymptomsA randomizedcontrolled trial Clinical Psychology and Psychotherapy 20(4) 308ndash318

SabateacuteE (2001) Adherence to Long-Term Therapies World Health Organisation Policy forAction

Saacutenchez-Ortiz V C House J Munro C Treasure J Startup H amp Williams C (2011) ldquoAcomputer isnt gonna judge yourdquo A qualitative study of users views of an

internet-based cognitive behavioural guided self-care treatment package for bulimianervosa and related disorders Eating and Weight Disorders 16 (2) e93ndashe101

Saacutenchez-Ortiz V C Munro C Stahl D House J Startup H amp Treasure J (2011) A ran-domized controlled trial of internet-based cognitivendashbehavioural therapy for bulimia

nervosa or related disorders in a student population Psychological Medicine 41(2)407ndash417

Scheel M J Hanson W E amp Razzhavaikina T I (2004) The process of recommendinghomework in psychotherapy A review of therapist delivery methods client accept-ability and factors that affect compliance Psychotherapy 41(1) 38ndash55

Schmidt U Andiappan M Grover M Robinson S Perkins S amp Dugmore O (2008)Randomised controlled trial of CD-ROM-based cognitivendashbehavioural self-care forbulimia nervosa British Journal of Psychiatry 193(6) 493ndash500

Schmidt U Lee S Beecham J Perkins S Treasure J amp Yi I (2007) A randomized con-trolled trial of family therapy and cognitive behavior therapy guided self care for ad-olescents with bulimia nervosa and related disorders American Journal of Psychiatry

164(4) 591ndash598Sheehe P R (1966) Combination of log relative risk retrospective studies of disease American Journal of Public Health 56 1745ndash1750

Simon G E Ludman E J Goodale L C Dykstra DM Stone E amp Cutsogeorge D(2011) An online recovery plan program Can peer coaching increase participationPsychiatric Services 62(6) 666ndash669

Steele A L Bergin J amp Wade T D (2011) Self-ef 1047297cacy as a robust predictor of outcomein guided self-help treatment for broadly de1047297ned bulimia nervosa International

Journal of Eating Disorders 44(5) 389ndash396Steele A L amp Wade T D (2008) A randomised trial investigating guided self-help to re-

duce perfectionism and its impact on bulimia nervosa A pilot study Behaviour Research and Therapy 46 (12) 1316ndash1323

Stefano SC Bacaltchuk J Blay S L amp Hay P (2006) Self-help treatments for disordersof recurrent binge eatingA systematicreview Acta Psychiatrica Scandinavica 113(6)452ndash459

Steinglass J E amp Walsh B T (2004) Psychopharmacology of anorexia nervosa bulimianervosa and binge eating disorder In T D Brewerton (Ed) Clinical handbook of eat-ing disorders New York Marcel Dekker Inc

Striegel-Moore R H Wilson G T DeBar L Perrin N Lynch F amp Rosselli F (2010)

Cognitive behavioral guided self-help for the treatment of recurrent binge eating Journal of Consulting and Clinical Psychology 78(3) 312ndash321

Sysko R amp Walsh B T (2008) A critical evaluation of the ef 1047297cacy of self-help interven-tions for the treatment of bulimia nervosa and binge-eating disorder International

Journal of Eating Disorders 41(2) 97ndash112The Centre for Economic Performances Mental Health Policy Group (2012) How mental

illness loses out on the NHS Centre for Economic Performance The London School of Economics and Political Science

Thiels C Schmidt U Troop N Treasure J amp GartheR (2000) Binge frequency predictsoutcome in guided self-care treatment of bulimia nervosa European Eating DisordersReview 8(4) 272

Thiels C Schmidt U Troop N Treasure J amp Garthe R (2001) Compliance with aself-care manual in guided self-change for bulimia nervosaEuropean Eating DisordersReview 9(2) 115

Thompson S G amp Higgins J P T (2002) How should meta-regression analyses be un-dertaken and interpreted Statistics in Medicine 21 1559ndash1573

Traviss G D Heywood-Everett S amp Hill A J (2011) Guided self-help fordisorderedeat-ing A randomised control trial Behaviour Research and Therapy 49(1) 25ndash31

Treasure J amp SchmidtU (2008)Motivational interviewing in the management of eatingdisorders In H Arkowitz H A Westra W R Miller amp S Rollnick (Eds) Motivationalinterviewing in the treatment of psychological problems (pp 194ndash224) New YorkGuildford Press

Treasure J Schmidt U Troop N TillerJ Todd Gamp Keilen M (1994) Firststepin man-aging bulimia nervosa Controlled trial of therapeutic manual British Medical Journal

308(6930) 686ndash689Treasure J Schmidt U Troop N amp Todd G (1996) Sequential treatment for bulimia

nervosa incorporating a self-care manual Br itish Journal of Psychiatry 168(1) 94Troop N Schmidt U Tiller J amp Todd G (1996) Compliance with a self-care manual for

bulimia nervosa Predictors and outcome British Journal of Clinical Psychology 35(3)435

VitolinsM ZRand C SRapp SR Ribisl PM amp Sevick MA (2000) Measuringadherenceto behavioral and medical interventions Controlled Clinical Trials 21 188Sndash194S

Wil1047298ey D E Schwartz M B Spurrell E B amp FairburnC G (2000)Using the eating dis-order examination to identify the speci1047297c psychopathology of binge eating disorderInternational Journal of Eating Disorders 27 (3) 259ndash269

Wilson D B (2005) Meta-analysis macros for SAS SPSS and Stata Retrieved16062012 2012 from httpmasongmuedudwilsonbmahtml

Wilson G T Vitousek K M amp Loeb K L (2000) Stepped care treatment for eating dis-orders Journal of Consulting and Clinical Psychology 68(4) 564ndash572

Wilson G T amp Zandberg L J (2012) Cognitivendashbehavioral guided self-help for eatingdisorders Effectiveness and scalability Clinical Psychology Review 32(4) 343ndash357


7172019 1-s20-S0272735814000312-main


Contents

1 Introduction 159

2 Methods 160

21 Study selection 160


23 Effect size calculation for intervention outcomes 161

24 Coding 161

241 Study participation and study outcomes 161

242 Study and intervention characteristics 161243 Patient characteristics 162

25 Integration of outcomes 162

26 Moderator analyses 162


3 Results 162

31 Sample of studies 162

32 Participation 163


331 Study dropout rate 163

332 Intervention completion rate 163

333 High participation 165

334 Low participation 165

34 Intervention outcomes 165

35 Moderators of intervention outcomes across trials 167

351 Study and intervention characteristics 167

352 Patient characteristics 167


4 Discussion 170



43 Moderators of intervention outcomes 171

44 Implications for the design of future interventions 172

441 How should self-help interventions be designed to maximize participation and intervention outcome 172

442 Who bene1047297ts most from self-help interventions 173

45 Clinical recommendations 173

46 Limitations of our metaanalysis 174

5 Conclusion 174

Appendix A Supplementary data 174

References 175

1 Introduction

Around the world national strategy documents and in1047298uential

reviews highlight the need for urgent action to improve the state of

mental health care (eg Kazdin amp Blase 2011 Medical Research

Council 2010 Patel Boyce Collins Saxena amp Horton 2011) Access to

evidence-based psychological interventions poses a key determinant

of good outcomes (The Centre for Economic Performances Mental

Health Policy Group 2012) However given the cost of face-to-face in-

dividual psychological therapy (which is the currently predominant

model of intervention delivery) to health care systems and patients

cost-effective alternatives are needed (Kazdin amp Blase 2011) In this

context translating effective psychological interventions into self-helpprograms and delivering them as bibliotherapy CD-ROMs or via the

Internet represents a major advance

A recent review from the UK estimated that just under a quarter of

eating disorder sufferers receive any intervention at all mdash and only 15

receive psychological therapy (The Centre for Economic Performances

Mental Health Policy Group 2012) This intervention gap is particularly

large for bulimic disorders (Hoek 2009) Cognitivendashbehavioral interven-

tions for the treatment of bulimia nervosa and binge-eating disorder are

effective (Hay Bacaltchuk Stefano amp Kashyap 2009) Self-help versions

of these interventions (which sometimes are guided ie augmented

with a small amount of personal telephone or email contact with a

health care professional) can also be effective at least for a subgroup of

participants (Perkins Murphy Schmidt amp Williams 2006 Stefano

Bacaltchuk Blay amp Hay 2006 Sysko amp Walsh 2008 Wilson Vitousek

amp Loeb 2000 Wilson amp Zandberg 2012) Experts concluded that self-

help is lsquoa robust means of improving implementation and scalability of

evidence-based treatment for eating disordersrsquo (Wilson amp Zandberg

2012 p 343)

Despitesuch enthusiastic endorsement bothquantitative research on

self-help approaches for a range of mental disorders (eg Christensen

Grif 1047297ths amp Farrer 2009 Eysenbach 2005 Melville Casey amp Kavanagh

2010) and qualitative studies of self-help treatments capturing the

views of patientswith eating disorders suggest that many patients strug-

gle with adherence to these programs mdash some because they feel short-

changed and see self-help as a cheap substitute for lsquoproperrsquo face-to-face

therapy others because they 1047297nd it hard to motivate themselves to per-

sist with working through the program with limited or no support(McClay Waters McHale Schmidt amp Williams 2013 Murray et al

2003 Pretorius Rowlands Ringwood amp Schmidt 2010 Saacutenchez-Ortiz

House et al 2011 Saacutenchez-Ortiz Munro et al 2011) The personal

costndashbene1047297t-ratio for a certain intervention can be very different for

each patient Interventions may not address symptoms that are a major

burden for patients or the intervention itself may be experienced as a

burden Low adherence in an intervention study can indicate that pa-

tients experience the intervention as either unpleasant or not helpful

(Rand amp Sevick 2000) Pooradherencemaynegativelyaffect intervention

outcome and a negative treatment experience may demoralize users and

reduce the likelihood of future help-seeking While lsquothe traditional clini-

cal trial and evidence-based medicine paradigm stipulates that high

dropout rates make trials less believable hellip for many eHealth trials

in particular those conducted on the Internet and in particular with

175


7172019 1-s20-S0272735814000312-main




























































2 Methods

21 Study selection




























































7172019 1-s20-S0272735814000312-main



for each condition






































manuscripts

24 Coding



































above


1047297ed above



and (3) case series








CBT specialist


and post-assessment
















7172019 1-s20-S0272735814000312-main














and (3) mixed






group at baseline



at baseline


































































3 Results







7172019 1-s20-S0272735814000312-main












































pletion at all



























32 Participation





















































7172019 1-s20-S0272735814000312-main


Table 1


Measure




Rate of pa

at least 75



bcase series





bCD-ROM =

bInternet =




REM ns ns ns



bhigh =minus1308

bhigh = 1807 a



FEM ns ns ns

REM ns ns ns


FEM b = 0084 b = 0063 b =minus00

REM ns ns ns


7172019 1-s20-S0272735814000312-main




















C1)

































Table 2


Outcome measure








of intervention



of intervention

Diagnoses


k 50 51 10 13

FEM bBED =minus2473

bBN =minus0531

bBED =minus0721

bBN =minus0591

bBED =minus1237

bBN =minus2975

bBN = 1759



frequency

k 31 35 4 6


REM ns ns


FEM b = 2015 ns b b

REM b = 1620a ns



REM ns ns


FEM b = 0749 ns b b

REM ns ns






BMI k 40 44 9 12









7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main



















groups
















































































EDE(minus




























7172019 1-s20-S0272735814000312-main


Table 4


Outcome measure


frequency


eating


Concern

k k k k


bBN = 1374

31 bBED = 0844 29 bBN = 2227 26 bBED = 8198



bBN =minus1673






frequency
















REM 23 ns 18 b = 0986 p = 0862a 25 b = 2329 a 25 b = 2575 p = 0887



7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main























































































consistent





Appendix D

4 Discussion




























7172019 1-s20-S0272735814000312-main














































































































ter outcomes
















7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main




























































2 Methods

21 Study selection




























































7172019 1-s20-S0272735814000312-main



for each condition






































manuscripts

24 Coding



































above


1047297ed above



and (3) case series








CBT specialist


and post-assessment
















7172019 1-s20-S0272735814000312-main














and (3) mixed






group at baseline



at baseline


































































3 Results







7172019 1-s20-S0272735814000312-main












































pletion at all



























32 Participation





















































7172019 1-s20-S0272735814000312-main


Table 1


Measure




Rate of pa

at least 75



bcase series





bCD-ROM =

bInternet =




REM ns ns ns



bhigh =minus1308

bhigh = 1807 a



FEM ns ns ns

REM ns ns ns


FEM b = 0084 b = 0063 b =minus00

REM ns ns ns


7172019 1-s20-S0272735814000312-main




















C1)

































Table 2


Outcome measure








of intervention



of intervention

Diagnoses


k 50 51 10 13

FEM bBED =minus2473

bBN =minus0531

bBED =minus0721

bBN =minus0591

bBED =minus1237

bBN =minus2975

bBN = 1759



frequency

k 31 35 4 6


REM ns ns


FEM b = 2015 ns b b

REM b = 1620a ns



REM ns ns


FEM b = 0749 ns b b

REM ns ns






BMI k 40 44 9 12









7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main



















groups
















































































EDE(minus




























7172019 1-s20-S0272735814000312-main


Table 4


Outcome measure


frequency


eating


Concern

k k k k


bBN = 1374

31 bBED = 0844 29 bBN = 2227 26 bBED = 8198



bBN =minus1673






frequency
















REM 23 ns 18 b = 0986 p = 0862a 25 b = 2329 a 25 b = 2575 p = 0887



7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main























































































consistent





Appendix D

4 Discussion




























7172019 1-s20-S0272735814000312-main














































































































ter outcomes
















7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main



for each condition






































manuscripts

24 Coding



































above


1047297ed above



and (3) case series








CBT specialist


and post-assessment
















7172019 1-s20-S0272735814000312-main














and (3) mixed






group at baseline



at baseline


































































3 Results







7172019 1-s20-S0272735814000312-main












































pletion at all



























32 Participation





















































7172019 1-s20-S0272735814000312-main


Table 1


Measure




Rate of pa

at least 75



bcase series





bCD-ROM =

bInternet =




REM ns ns ns



bhigh =minus1308

bhigh = 1807 a



FEM ns ns ns

REM ns ns ns


FEM b = 0084 b = 0063 b =minus00

REM ns ns ns


7172019 1-s20-S0272735814000312-main




















C1)

































Table 2


Outcome measure








of intervention



of intervention

Diagnoses


k 50 51 10 13

FEM bBED =minus2473

bBN =minus0531

bBED =minus0721

bBN =minus0591

bBED =minus1237

bBN =minus2975

bBN = 1759



frequency

k 31 35 4 6


REM ns ns


FEM b = 2015 ns b b

REM b = 1620a ns



REM ns ns


FEM b = 0749 ns b b

REM ns ns






BMI k 40 44 9 12









7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main



















groups
















































































EDE(minus




























7172019 1-s20-S0272735814000312-main


Table 4


Outcome measure


frequency


eating


Concern

k k k k


bBN = 1374

31 bBED = 0844 29 bBN = 2227 26 bBED = 8198



bBN =minus1673






frequency
















REM 23 ns 18 b = 0986 p = 0862a 25 b = 2329 a 25 b = 2575 p = 0887



7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main























































































consistent





Appendix D

4 Discussion




























7172019 1-s20-S0272735814000312-main














































































































ter outcomes
















7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main














and (3) mixed






group at baseline



at baseline


































































3 Results







7172019 1-s20-S0272735814000312-main












































pletion at all



























32 Participation





















































7172019 1-s20-S0272735814000312-main


Table 1


Measure




Rate of pa

at least 75



bcase series





bCD-ROM =

bInternet =




REM ns ns ns



bhigh =minus1308

bhigh = 1807 a



FEM ns ns ns

REM ns ns ns


FEM b = 0084 b = 0063 b =minus00

REM ns ns ns


7172019 1-s20-S0272735814000312-main




















C1)

































Table 2


Outcome measure








of intervention



of intervention

Diagnoses


k 50 51 10 13

FEM bBED =minus2473

bBN =minus0531

bBED =minus0721

bBN =minus0591

bBED =minus1237

bBN =minus2975

bBN = 1759



frequency

k 31 35 4 6


REM ns ns


FEM b = 2015 ns b b

REM b = 1620a ns



REM ns ns


FEM b = 0749 ns b b

REM ns ns






BMI k 40 44 9 12









7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main



















groups
















































































EDE(minus




























7172019 1-s20-S0272735814000312-main


Table 4


Outcome measure


frequency


eating


Concern

k k k k


bBN = 1374

31 bBED = 0844 29 bBN = 2227 26 bBED = 8198



bBN =minus1673






frequency
















REM 23 ns 18 b = 0986 p = 0862a 25 b = 2329 a 25 b = 2575 p = 0887



7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main























































































consistent





Appendix D

4 Discussion




























7172019 1-s20-S0272735814000312-main














































































































ter outcomes
















7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main












































pletion at all



























32 Participation





















































7172019 1-s20-S0272735814000312-main


Table 1


Measure




Rate of pa

at least 75



bcase series





bCD-ROM =

bInternet =




REM ns ns ns



bhigh =minus1308

bhigh = 1807 a



FEM ns ns ns

REM ns ns ns


FEM b = 0084 b = 0063 b =minus00

REM ns ns ns


7172019 1-s20-S0272735814000312-main




















C1)

































Table 2


Outcome measure








of intervention



of intervention

Diagnoses


k 50 51 10 13

FEM bBED =minus2473

bBN =minus0531

bBED =minus0721

bBN =minus0591

bBED =minus1237

bBN =minus2975

bBN = 1759



frequency

k 31 35 4 6


REM ns ns


FEM b = 2015 ns b b

REM b = 1620a ns



REM ns ns


FEM b = 0749 ns b b

REM ns ns






BMI k 40 44 9 12









7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main



















groups
















































































EDE(minus




























7172019 1-s20-S0272735814000312-main


Table 4


Outcome measure


frequency


eating


Concern

k k k k


bBN = 1374

31 bBED = 0844 29 bBN = 2227 26 bBED = 8198



bBN =minus1673






frequency
















REM 23 ns 18 b = 0986 p = 0862a 25 b = 2329 a 25 b = 2575 p = 0887



7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main























































































consistent





Appendix D

4 Discussion




























7172019 1-s20-S0272735814000312-main














































































































ter outcomes
















7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main


Table 1


Measure




Rate of pa

at least 75



bcase series





bCD-ROM =

bInternet =




REM ns ns ns



bhigh =minus1308

bhigh = 1807 a



FEM ns ns ns

REM ns ns ns


FEM b = 0084 b = 0063 b =minus00

REM ns ns ns


7172019 1-s20-S0272735814000312-main




















C1)

































Table 2


Outcome measure








of intervention



of intervention

Diagnoses


k 50 51 10 13

FEM bBED =minus2473

bBN =minus0531

bBED =minus0721

bBN =minus0591

bBED =minus1237

bBN =minus2975

bBN = 1759



frequency

k 31 35 4 6


REM ns ns


FEM b = 2015 ns b b

REM b = 1620a ns



REM ns ns


FEM b = 0749 ns b b

REM ns ns






BMI k 40 44 9 12









7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main



















groups
















































































EDE(minus




























7172019 1-s20-S0272735814000312-main


Table 4


Outcome measure


frequency


eating


Concern

k k k k


bBN = 1374

31 bBED = 0844 29 bBN = 2227 26 bBED = 8198



bBN =minus1673






frequency
















REM 23 ns 18 b = 0986 p = 0862a 25 b = 2329 a 25 b = 2575 p = 0887



7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main























































































consistent





Appendix D

4 Discussion




























7172019 1-s20-S0272735814000312-main














































































































ter outcomes
















7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main




















C1)

































Table 2


Outcome measure








of intervention



of intervention

Diagnoses


k 50 51 10 13

FEM bBED =minus2473

bBN =minus0531

bBED =minus0721

bBN =minus0591

bBED =minus1237

bBN =minus2975

bBN = 1759



frequency

k 31 35 4 6


REM ns ns


FEM b = 2015 ns b b

REM b = 1620a ns



REM ns ns


FEM b = 0749 ns b b

REM ns ns






BMI k 40 44 9 12









7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main



















groups
















































































EDE(minus




























7172019 1-s20-S0272735814000312-main


Table 4


Outcome measure


frequency


eating


Concern

k k k k


bBN = 1374

31 bBED = 0844 29 bBN = 2227 26 bBED = 8198



bBN =minus1673






frequency
















REM 23 ns 18 b = 0986 p = 0862a 25 b = 2329 a 25 b = 2575 p = 0887



7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main























































































consistent





Appendix D

4 Discussion




























7172019 1-s20-S0272735814000312-main














































































































ter outcomes
















7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main



















groups
















































































EDE(minus




























7172019 1-s20-S0272735814000312-main


Table 4


Outcome measure


frequency


eating


Concern

k k k k


bBN = 1374

31 bBED = 0844 29 bBN = 2227 26 bBED = 8198



bBN =minus1673






frequency
















REM 23 ns 18 b = 0986 p = 0862a 25 b = 2329 a 25 b = 2575 p = 0887



7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main























































































consistent





Appendix D

4 Discussion




























7172019 1-s20-S0272735814000312-main














































































































ter outcomes
















7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main



















groups
















































































EDE(minus




























7172019 1-s20-S0272735814000312-main


Table 4


Outcome measure


frequency


eating


Concern

k k k k


bBN = 1374

31 bBED = 0844 29 bBN = 2227 26 bBED = 8198



bBN =minus1673






frequency
















REM 23 ns 18 b = 0986 p = 0862a 25 b = 2329 a 25 b = 2575 p = 0887



7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main























































































consistent





Appendix D

4 Discussion




























7172019 1-s20-S0272735814000312-main














































































































ter outcomes
















7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main


Table 4


Outcome measure


frequency


eating


Concern

k k k k


bBN = 1374

31 bBED = 0844 29 bBN = 2227 26 bBED = 8198



bBN =minus1673






frequency
















REM 23 ns 18 b = 0986 p = 0862a 25 b = 2329 a 25 b = 2575 p = 0887



7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main























































































consistent





Appendix D

4 Discussion




























7172019 1-s20-S0272735814000312-main














































































































ter outcomes
















7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main


7172019 1-s20-S0272735814000312-main























































































consistent





Appendix D

4 Discussion




























7172019 1-s20-S0272735814000312-main














































































































ter outcomes
















7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main























































































consistent





Appendix D

4 Discussion




























7172019 1-s20-S0272735814000312-main














































































































ter outcomes
















7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main














































































































ter outcomes
















7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main
















































2008)















































































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main



















and BED patients












































































































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main














































trials



































5 Conclusion














(Horne et al 2005)
















analyses














7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main











work best




References


























































7172019 1-s20-S0272735814000312-main



























































7172019 1-s20-S0272735814000312-main



























































1-s2.0-s0272735814000312-main

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