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Women with elevated food addiction symptoms show accelerated reactions, but no
impaired inhibitory control, in response to pictures of high-calorie food-cues
Adrian Meule
a,
⁎, Annika Lutz
b
, Claus Vögele
b
, Andrea Kübler
a,c
a
Department of Psychology I, University of Würzburg, Marcusstr. 9–11, 97070 Würzburg, Germany
b
Research Unit INSIDE, University of Luxembourg, Route de Diekirch —BP2, L-7220 Walferdange, Luxembourg
c
Institute of Medical Psychology and Behavioural Neurobiology, University of Tübingen, Gartenstr. 29, 72074 Tübingen, Germany
abstractarticle info
Article history:
Received 16 April 2012
Received in revised form 24 July 2012
Accepted 27 August 2012
Available online 5 September 2012
Keywords:
Food addiction
Food-cues
Behavioral inhibition
Impulsivity
Addictive behaviors are accompanied by a lack of inhibitory control, specifically when individuals are
confronted with substance-related cues. Thus, we expected women with symptoms of food addiction to be
impaired in inhibitory control, when confronted with palatable, high-calorie food-cues. Female college
students (N=50) were divided in low and high food addiction groups based on the symptom count of the
Yale Food Addiction Scale. Participants performed a Go/No-go-task with high-calorie food-cues or neutral pic-
tures presented behind the targets. Self-reported impulsivity was also assessed. The high food addiction
group had faster reaction times in response to food-cues as compared to neutral cues and reported higher
attentional impulsivity than the low food addiction group. Commission and omission errors did not differ
between groups or picture types. Hence, women with food addiction symptoms reported higher attentional
impulsivity and reacted faster in response to food-cues, although neither increased self-reported motor
impulsivity nor impaired behavioral inhibition was found. Food addiction symptoms seem to be related to
attentional aspects of impulsivity but not other facets of impulsivity.
© 2012 Elsevier Ltd. All rights reserved.
1. Introduction
Impulsivity has been found to be a prominent feature in substance
abuse. By way of illustration, individuals with substance abuse display
higher self-reported impulsivity and impulsive behaviors in a variety
of experimental tasks (de Wit, 2009; Moeller, Barratt, Dougherty,
Schmitz, & Swann, 2001; Perry & Carroll, 2008).Such tasks often involve
the assessment of motor response inhibition. Here, subjects are re-
quired to quickly respond to a frequently presented target and, thereby,
the response becomes pre-potent. Responses to infrequent non-targets,
however, have to be withheld (so-called Go/No-go-tasks). For instance,
cocaine users showed inhibitory deficits in a Go/No-go-task, which
involved distinct activation of frontal cortices (Garavan, Kaufman, &
Hester, 2008; Garavan, Ross, Murphy, Roche, & Stein, 2002; Kaufman,
Ross, Stein, & Garavan, 2003). Such behavioral disinhibition was even
more pronounced in response to substance-related material in alcohol
and polysubstance abusers (Noël et al., 2005, 2007).
In the past decade, accumulating evidence suggests that excessive
eating may be similar to addictive behavior (e.g. Davis & Carter, 2009;
Gearhardt, Corbin, & Brownell, 2009a; Meule, 2011; Pelchat, 2009),
with some authors conceptualizing addictions as a syndrome with a
common etiology but multiple opportunistic expressions including
substance use disorder, pathological gambling, or excessive eating
(Shaffer et al., 2004). Recently, Gearhardt et al. (2009b) introduced
the Yale Food Addiction Scale (YFAS) to assess addictive symptoms
related to eating behavior, thereby following the diagnostic criteria
for substance dependence (Gearhardt, Corbin, & Brownell, 2009b).
Accordingly, symptoms can be counted and can range between zero
and seven. Moreover, food addiction can be diagnosed if at least
three symptoms and a clinically significant impairment are present.
Using this approach Gearhardt et al. (2011) could show that women
with food addiction symptoms had elevated activation in reward
circuitries, but also in frontal areas related to self-control, during an-
ticipation of food intake. Furthermore, activation of inhibitory regions
was reduced in response to food intake (Gearhardt et al., 2011).
Like other addictive behaviors, excessive eating has been related to
impulsivity (Guerrieri, Nederkoorn, & Jansen, 2008). For instance,
self-reported impulsivity is positively correlated with both body-mass-
index (BMI) and the YFAS (Meule, Vögele, & Kübler, 2011, 2012a).
At a behavioral level, overeating and binge eating are associated
with decreased response inhibition (Jansen et al., 2009; Nederkoorn,
Smulders,Havermans,Roefs,&Jansen,2006;Nederkoorn,VanEijs,&
Jansen, 2004; Rosval et al., 2006). Like in patients with substance
abuse, where behavioral disinhibition was particularly found in
response to substance-related stimuli, behavioral disinhibition was
enhanced in response to eating-related words in patients with bulimia
(Mobbs, Van der Linden, d'Acremont, & Perroud, 2008).
Eating Behaviors 13 (2012) 423–428
⁎Corresponding author. Tel.: +49 931 31 808 34; fax: + 49 931 31 824 24.
E-mail address: adrian.meule@uni-wuerzburg.de (A. Meule).
1471-0153/$ –see front matter © 2012 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.eatbeh.2012.08.001
Contents lists available at SciVerse ScienceDirect
Eating Behaviors
Author's personal copy
Nevertheless, findings about the influence of food stimuli on
behavioral inhibition are inconsistent. For example, Mobbs et al.
(2011) could not replicate the finding that eating-related stimuli in
particular increased behavioral disinhibition in patients with obesity
and binge eating disorder, although this had been shown previously
for patients with bulimia. Obese participants exhibited general
deficits in response inhibition as compared to controls regardless if
food or neutral stimuli were presented. Moreover, all participants,
i.e. both patients and controls, made more commission errors in
response to neutral words (i.e. when food words were the targets)
as compared to food words (i.e. when neutral words were the tar-
gets) (Mobbs, Iglesias, Golay, & Van der Linden, 2011). In contrast,
both obese and normal-weight participants committed more errors
in response to food words (i.e. when neutral words were the targets)
as compared to neutral words (i.e. when food words were the tar-
gets) in a study by Loeber et al. (2012). Finally, in our own studies
we found increased behavioral inhibition in response to both food
and neutral stimuli in restrained eaters as compared to unrestrained
eaters after food intake (Meule, Lukito, Vögele, & Kübler, 2011). To
conclude, studies that investigated the direct effects of exposure to
food stimuli on behavioral inhibition either did not find any or even
contradictory effects (i.e. impairment or enhancement).
Based on the similarities between addiction and excessive eating, we
hypothesized that individuals with food addiction symptoms are im-
paired in response inhibition when confronted with food-related mate-
rial. Therefore, we expected that women with multiple food addiction
symptoms show decreased response inhibition, i.e. more commission
errors in a Go/No-go-task, in response to food-cues compared to
women with no or fewer food addiction symptoms. With regard to reac-
tion times, it is unclear if presentation of substance- and eating-related
stimuli leads to acceleration or slowing of responses in response to inhi-
bition tasks (Loeber et al., 2012; Meule, Lukito, et al., 2011; Meule,
Vögele, & Kübler, 2012b; Mobbs et al., 2008, 2011; Noël et al., 2005,
2007). Therefore, we had a non-directional hypothesis that reaction
times in response to food-cues would differ from responses to neutral
cues particularly in the high food addiction group. Finally, we expected
that the high food addiction group would show higher self-reported im-
pulsivity as measured with the short form of the Barratt Impulsiveness
Scale (BIS-15) as compared to the low food addiction group.
2. Material and methods
2.1. Participants
Female participants were recruited among students at the University
of Würzburg. Advertisements were posted on campus and distributed
using a mailing list of a student council. Women who responded to
the advertisements were contacted by phone (N=82) and screened
for exclusion criteria which included mental disorders, psychoactive
medication,under-oroverweight(BMIb17.5 or >25 kg/m
2
), and
age> 40 years. We decided to restrict the sample to women with
normal-weight because only few participants of the screened sample
were in the overweight range and, therefore, BMI distribution would
have been skewed. A total of n= 50 participants were included in the
study. Mean age was M=22.3 years (SD=3.0;range:19–32) and
mean BMI M=21.5 kg/m
2
(SD= 2.7). Participants either received course
credits or €20 for participation.
1
2.2. Questionnaires
2.2.1. Yale Food Addiction Scale (YFAS)
The YFAS (Gearhardt et al., 2009b) measures addictive eating
behavior and consists of 27 items (e.g., “There have been times when I
consumed certain foods so often or in such large quantities that I started
to eat food instead of working, spending time with my family or friends,
or engaging in other important activities or recreational activities I
enjoy.”,“Ifind that when certain foods are not available, I will go out
of my way to obtain them. For example, I will drive to the store to
purchase certain foods even though I have other options available to
me at home.”,or“Over time, I have found that I need to eat more
and more to get the feeling I want, such as reduced negative emotions
or increased pleasure.”). The questionnaire is based on the diagnostic
criteria for substance dependence of the DSM-IV (American Psychiatric
Association, 1994). Validity of the YFAS has been indicated by positive
associations with BMI, eating disorder symptomatology, emotional
eating, food cravings, binge eating, difficulties in emotion regulation,
and impulsivity in non-clinical samples and obese patients (Davis et
al., 2011; Gearhardt et al., 2009b; Gearhardt et al., 2012; Meule, 2012;
Meule, Heckel, & Kübler, 2012; Meule & Kübler, 2012; Meule et al.,
2012a). Internal consistency of the German version is α=.81 (Meule
et al., 2012a)andwasα= .83 in the current study.
2.2.2. Center for Epidemiologic Studies Depression Scale (CES-D)
The CES-D (Radloff, 1977) was used to assess whether high versus
low food addiction participants differed in depressive symptoms
during the past week. Validity of the CES-D has been shown by high
positive correlations with other measures for depression, e.g. the
Beck Depression Inventory or interviewer ratings, and personality
variables, e.g. neuroticism or trait anxiety (Hautzinger, 1988; Orme,
Reis, & Herz, 1986; Radloff, 1977). Internal consistency of the German
version varies between α=.85–.91 (Hautzinger, 1988)andwasα=.90
in the current study.
2.2.3. Barratt Impulsiveness Scale —Short Version (BIS-15)
The BIS-15 was proposed by Spinella (2007) as short version of the
BIS-11 (Patton, Stanford, & Barratt, 1995) for the measurement of
impulsivity. Instead of 30 items as in the long version, it consists of
15 items only. The three-factor solution on the dimensions motor,
attentional,andnon-planning impulsivity could also be confirmed for
the German version (Meule, Vögele, & Kübler, 2011). Convergent
validity of the BIS-15 has been shown by moderate to strong relation-
ships with the Frontal Systems Behavior Scale and the UPPS Impulsive
Behavior Scale while discriminant validity has been indicated by weak
correlations with sensation seeking (Meule, Vögele, et al., 2011;
Spinella, 2007). Internal consistency of the German version is α=.81
(Meule, Vögele, et al., 2011). In the current study, internal consistency
was α=.79 and ranged between α=.68–.82 for the subscales.
2.2.4. Food Cravings Questionnaires —State Version (FCQ-S)
The FCQ-S (Cepeda-Benito, Gleaves, Williams, & Erath, 2000)was
used to measure current food cravings. This 15-item questionnaire
assesses momentary food cravings on the dimensions intense desire to
eat,anticipation of positive reinforcement that may result from eating,
anticipation of relief from negative states and feelings as a result of eating,
lack of control over eating,andcraving as a physiological state
(Cepeda-Benito et al., 2000). Validity of the FCQ-S has been indicated
by positive associations with length of food deprivation and current
negative affect (Cepeda-Benito, Fernandez, & Moreno, 2003; Meule,
Lutz, Vögele, & Kübler, 2012a). Moreover, the FCQ-S has been found to
be sensitive to meal consumption and food-cue exposure such that
state cravings decreased after breakfast (Cepeda-Benito et al., 2000;
Vander Wal, Johnston, & Dhurandhar, 2007)andincreasedafter
performing a cognitive task involving food pictures (Meule, Skirde,
Freund, Vögele, & Kübler, 2012). Subscales are highly inter-correlated
1
The reported data were part of a study that also included other tasks and physio-
logical recordings on three occasions, which are reported elsewhere (cf. Meule, Lutz,
Vögele, & Kübler, 2012b). The order of tasks was counterbalanced, i.e. subjects
performed the XY-task either on the first, second, or third session. None of the stimuli
used in the XY-task were used in the other tasks.
424 A. Meule et al. / Eating Behaviors 13 (2012) 423–428
Author's personal copy
and internal consistency of the total score is α=.92(Meule, Lutz, et al.,
2012a). Therefore, we only used the total score for our analyses and in-
ternal consistency was α=.90 in the current study.
2.3. XY-task
Amodification of the XY-task (Garavan et al., 2002; Meule, Lukito,
et al., 2011) was used in this study. The program was compiled using
E-prime 2.0 (Psychology Software Tools Inc., Pittsburgh, PA) and
displayed on a LCD TFT 22″screen. In this task, participants were required
to press a button in response to every target (i.e. the letters X and Y) that
was different from the preceding one. When the same target appeared
consecutively, the response had to be withheld (= No-go-trials). In addi-
tion, pictures of either high caloric food (F) or neutral objects (N) were
presented behind the targets (Fig. 1). Food items were pictures of high
caloric sweet and savory foods, which were selected from a set of pictures
previously used (Blechert, Feige, Hajcak, & Tuschen-Caffier, 2010;
Blechert, Feige, Joos, Zeeck, & Tuschen-Caffier, 2011; Meule, Lukito, et
al., 2011). Neutral pictures were common household items. All pictures
were edited to be homogeneous with respect to background color.
The task was separated into four counterbalanced blocks (F–N–F–N
or N–F–N–F). Each block consisted of 315 trials including 20
no-go-trials. A practice block of 80 trials without any pictures behind
the targets was presented prior to the experimental blocks. The
whole task lasted for approximately 20–30 min. Reaction times
(ms) in Go-trials and the number of commission and omission errors
were recorded as outcome measures.
2.4. Procedure
All participants were asked not to consume food, caffeine, nico-
tine, or alcohol at least 3 h before the experiment. After participants
had performed the XY-task, they immediately filled out the FCQ-S
and reported the hours that had elapsed since their last meal. Com-
pletion of the other questionnaires and measurement of participants'
height and weight were conducted either on the same day or within
1–2 weeks after the experiment, depending on individual assignment
to experimental conditions.
1
2.5. Data analysis
Participants were divided in low (n=30) and high food addiction
groups (n=20) based on a median split of the YFAS symptom count
(Mdn= 1). Participants with ≤1 food addiction symptoms were includ-
ed in the low food addiction group. In this group, 83.3% (n=25)
endorsed one symptom and 16.7% (n=5) reported no symptom.
Mean food addiction symptom count was M=.83 (SD =.38) in the
low food addiction group and M=2.65 (SD= .75; range: 2–4symp-
toms) in the high food addiction group. Groups were compared for
age, BMI, hours since the last meal, current food cravings (FCQ-S),
food addiction symptoms (YFAS), depressive symptoms (CES-D), and
impulsivity (BIS-15) using t-tests. In addition, we calculated correla-
tions between food addiction symptoms and those variables.
Measures of interest in the XY-task were reaction times (RTs) and
omission errors (OEs), which should reflect attentional processes, and
commission errors (CEs) as an indicator for inhibitory control. Trials
with an RT of less than 150 ms, reflecting anticipation, were excluded
from analyses. A 2 (picture type)×2 (group) ANOVA for repeated
measures was calculated for each of the dependent variables.
Post-hoc t-tests (Bonferroni-adjusted) were calculated in case of
significant interactions.
3. Results
3.1. Participant characteristics
Participants in the high food addiction group were younger
(M=21.15 years, SD = 1.81) and reported higher levels of self-reported
attentional impulsivity (M= 10.10, SD =2.10) compared to the low
food addiction group (age: M=23.10 years, SD =3.44, t
(48)
=2.33,
pb.05; attentional impulsivity: M= 8.70, SD =2.45, t
(48)
=−2.09,
pb.05). Self-reported attentional impulsivity was also positively correlat-
ed with food addiction symptoms (r=.34, pb.05). Using age and
kco
l
blartueN
(b)
kcolbdooF(a)
Go
Go
Go
1600 ms No-go
1600 ms
GoGo
Fig. 1. XY-task with representative screen displays from a (a) food and (b) neutral block. Targets were presented for 600 ms. Either a blank screen or a feedback, in the case of a false
reaction, was presented for 1000 ms during the inter-trial interval.
425A. Meule et al. / Eating Behaviors 13 (2012) 423–428
Author's personal copy
attentional impulsivity as covariates in the subsequent analyses of task
performance did not change results. Groups did not differ in BMI
(t
(48)
=−1.52, p>.05), current food cravings (t
(48)
=−.30, p>.05),
hours since the last meal (t
(48)
=.63, p> .05), depressive symptoms
(t
(48)
=−1.87, p>.05), self-reported motor impulsivity (t
(48)
=−.86,
p>.05) and self-reported non-planning impulsivity (t
(48)
=−.25,
p>.05). Although group differences were non-significant, food addiction
symptoms were positively correlated with BMI (r=.42, pb.01) and
depressive symptoms (r=.29, pb.05).
3.2. Task performance
3.2.1. Reaction times
Mean RTs in Go-trials were M=329.67 ms (SD = 25.24). There was
no main effect for group (F
(1,48)
=.75, p> .05). A significant main effect
for picture type (F
(1,48)
=4.78, pb.05, η
p
2
=.09) indicated that partici-
pants reacted faster in blocks with food pictures (M=327.38 ms,
SD= 28.21) than in blocks with neutral pictures (M=331.73 ms,
SD= 26.45). The interaction between group and picture type was sig-
nificant (F
(1,48)
=9.17, pb.01, η
p
2
=.16). Post-hoc tests revealed that
only in the high food addiction group participants reacted faster in
response to food (M=318.56 ms, SD=25.96) as compared to neutral
cues (M=332.90 ms, SD = 25.54, t
(19)
=−3.43, pb.01). Reaction
times did not differ between picture types in the low food addiction
group (t
(29)
=.66, p>.05;Fig. 2).
2
3.2.2. Commission errors
Mean number of CEs was M= 52.26 (SD= 14.03). There were neither
significant main effects for group (F
(1,48)
=.21, p> .05) and picture type
(F
(1,48)
=.01, p>.05) nor a significant interaction group × picture type
(F
(1,48)
=.58, p>.05).
3.2.3. Omission errors
Mean number of OEs was M= 27.04 (SD= 27.54). There were neither
significant main effects for group (F
(1,48)
=2.04, p>.05) and picture type
(F
(1,48)
=1.42, p>.05) nor a significant interaction group× picture type
(F
(1,48)
=1.83, p>.05).
4. Discussion
In the present study, we found that women with symptoms of food
addiction responded faster to high-calorie food-cues as compared to
neutral cues. No such difference was observed in women with no or
only one food addiction symptom. Our hypothesis of a differential effect
of food-cues on behavioral inhibition as evidenced by commission
errors in the XY-task could not be confirmed. Women with food addic-
tion symptoms reported heightened levels of attentional impulsivity
while no group differences in self-reported motor and non-planning
impulsivity were found.
The finding of accelerated reaction times in response to pictorial
food stimuli in women with food addiction symptoms corresponds
to findings of studies in which comparable samples were investigat-
ed. For example, faster detection of food-related words and pictures
has been found for restrained eaters (Boon, Vogelzang, & Jansen,
2000; Hollitt, Kemps, Tiggemann, Smeets, & Mills, 2010; Meule,
Vögele, & Kübler, 2012b) and chocolate cravers (Smeets, Roefs, &
Jansen, 2009). In contrast, restrained eaters or chocolate cravers
who have been pre-exposed to craving-inducing food or food-cues
have been shown to respond more slowly in such tasks (Green,
Rogers, & Elliman, 2000; Kemps, Tiggemann, & Grigg, 2008; Meule,
Lukito, et al., 2011; Smeets et al., 2009). Longer reaction times have
also been found in individuals with substance use as a result of drug
craving or drug exposure (Baxter & Hinson, 2001; Cepeda-Benito &
Tiffany, 1996; Sayette & Hufford, 1994; Sayette et al., 1994).
In our study, groups did not differ with respect to craving. We
would argue that in cognitive tasks that involve simple reactions,
pre-exposure to food and thereby induced craving leads to slowed
reactions (i.e. distraction) in response to food-cues, similar to slowed
reactions after drug exposure and drug craving. On the other hand, if
there is no pre-exposure or craving induction, as was the case in the
present study, accelerated reactions to high-calorie food-cues can be
found. Smeets et al. (2009) interpreted their results such that faster
detection of food-cues could be the result of increased incentive
salience in chocolate cravers. A similar conclusion has been drawn
for cognitive bias to food-cues in eating disorder patients and
restrained eaters (Brooks, Prince, Stahl, Campbell, & Treasure, 2011).
Accordingly, we speculate that shortened reaction times in our
study may be a behavioral equivalent to increased activation of the
reward system in women with food addiction symptoms, when
they are confronted with highly palatable food-cues (Gearhardt et al.,
2011).
In the study by Gearhardt et al. (2011), however, activation of the
reward system during food-exposure, but before food intake, was
accompanied by activation of inhibitory areas of the brain. The
authors speculated that women with food addiction symptoms
“may respond to increased appetitive motivation for food by
attempting to implement self-control strategies”(Gearhardt et al.,
2011, p. 812). Hence, this activation pattern might account for the
lack of difference in commission errors between groups in the present
study.
Another possibility that might account for the lack in differences
in behavioral inhibition could be failure of the task to produce enough
commission errors. Nevertheless, the mean number of commission
errors made closely corresponded to, and was even higher compared
with our previous study in which we used this task (cf. Meule, Lukito,
et al., 2011).
A third possibility could be that food addiction is related to atten-
tional impulsivity rather than motor impulsivity. This line of argument
would be supported by our questionnaire data. This conclusion, howev-
er, should be drawn only with reservation, as there is generally only a
negligible relation between self-reported impulsivity and laboratory
tasks (Cyders & Coskunpinar, 2011). Accordingly, attentional impulsiv-
ity was unrelated to reaction times in our study.
The current study has several limitations. Firstly, sample size was
rather small and the high food addiction group consisted of merely 20
participants. Moreover, diagnoses of food addiction were rare. Indi-
viduals in this group only showed a tendency towards food addiction,
and can, therefore, not be taken as representing the full diagnosis of
310
315
320
325
330
335
340
Low food addiction
(n = 30)
High food addiction
(n = 20)
Reaction times (ms)
Food pictures Neutral pictures
Fig. 2. Mean reaction times in the XY-task as a function of food addiction symptoms
and picture type. Participants were divided in low (≤1 food addiction symptom) and
high food addiction groups (> 1 food addiction symptom) based on YFAS scores.
Error bars indicate the standard error of the mean.
2
To further validate this finding, we correlated reaction times with the symptom
count of the YFAS. The amount of food addiction symptoms was negatively correlated
with reaction times in response to food-cues (r=−.35, pb.05), but not with reaction
times in response to neutral cues (r=−.04, p> .05).
426 A. Meule et al. / Eating Behaviors 13 (2012) 423–428
Author's personal copy
food addiction. This might have resulted in a lack of differences in
behavioral inhibition and also in self-reported motor impulsivity.
Also, we investigated a sample of female college students, which
may not be representative of the general population. Future studies
should investigate obese samples in which food addiction diagnoses
are more prevalent (Meule, 2011). Secondly, it has to be noted that
our concurrent picture presentation might have interfered with
pure response inhibition, because of additional attentional require-
ments. A possible solution would be to use food pictures as targets,
instead of presenting them behind targets, similar to studies that
used food-related words (e.g. Loeber et al., 2012). Thirdly, future
studies may investigate actual eating behavior in the presence of
food in individuals with an addiction-like eating behavior. The sight
and smell of real food may lead to a disinhibition of eating in this pop-
ulation which may not be observed in motor response inhibition tasks
using pictorial food stimuli.
In summary, this study showed that food addiction symptoms are
related to accelerated responses to high-calorie food-cues as well as
heightened self-reported attentional impulsivity. As outlined above,
we would argue that faster reactions to pictorial high-calorie
food-cues reflect an automatic approach bias associated with incen-
tive salience. This interpretation would be supported by results on
associations between impulsivity, external eating, reward sensitivity,
and attentional bias to food-cues (Hou et al., 2011). In contrast, food
addiction symptoms are not accompanied by behavioral disinhibition
in response to pictures of high-calorie food-cues and self-reported
motor impulsivity, highlighting the importance of affective reactions
beyond inhibitory control in eating behavior. For example, although
general inhibitory control moderated food intake, automatic positive
affective reactions towards candy were a more important predictor
of candy consumption in a study by Hofmann et al. (2009).
A clinical implication of those findings is that individuals with food
addiction symptoms may benefit from attentional retraining aiming at
a reduction of food-cue sensitivity. Recent evidence suggests that cogni-
tive bias modification procedures are effective in changing attentional
bias as well as reducing symptoms in mental disorders, including
eating- and addiction-related problems (MacLeod, 2012). For instance,
studies that investigated the effects of a retraining of automatic action
tendencies, e.g., by pairing food- or alcohol-related stimuli with a stop-
ping response, found a reduction of food or alcohol intake (Houben,
2011; Houben, Havermans, Nederkoorn, & Jansen, 2012; Houben &
Jansen, 2011; Houben, Nederkoorn, Wiers, & Jansen, 2011). Possible
mechanisms underlying this behavioral change may be a decrease of
positive implicit attitudes and automatic approach bias towards these
stimuli, respectively (Houben et al., 2012; Wiers, Eberl, Rinck, Becker,
& Lindenmeyer, 2011). Future studies should investigate whether
such a procedure will alter reactions to food-cues, thereby reducing
symptomatology in individuals presenting with addiction-like eating
behavior.
Role of funding sources
Funding for this study was provided by a grant of the research training group
1253/2 which is supported by the German Research Foundation (DFG) by federal
and Länder funds. DFG had no role in the study design, collection, analysis or interpre-
tation of the data, writing the manuscript, or the decision to submit the paper for
publication.
Contributors
All authors contributed to the design of the study. Annika Lutz collected the data.
Data analyses were performed by Annika Lutz and Adrian Meule who also wrote the
first draft of the manuscript. Claus Vögele and Andrea Kübler contributed to interpre-
tation of the data and manuscript preparation. All authors have approved the final
manuscript.
Conflict of interest
Neither author has any conflicts of interest.
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