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Chocolate versions of the Food Cravings Questionnaires: Associations with chocolate exposure-induced salivary flow and ad libitum chocolate consumption

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Chocolate versions of the Food Cravings Questionnaires: Associations with chocolate exposure-induced salivary flow and ad libitum chocolate consumption

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The Food Cravings Questionnaires are the most commonly used instruments for the assessment of trait and state food craving. Chocolate is the most frequently craved food in Western societies. In the current studies, the Food Cravings Questionnaire-Trait-reduced (FCQ-T-r) and the Food Cravings Questionnaire-State (FCQ-S) were adapted to capture strong urges for chocolate. In study 1, students (n = 492; 81.3% female) completed chocolate versions of the FCQ-T-r and FCQ-S among other measures online. The FCQ-T-r (α = .94) comprised two subscales representing lack of control (α = .91) and thoughts about chocolate (α = .91). The FCQ-S (α = .87) comprised two subscales representing chocolate craving (α = .90) and hunger (α = .85). FCQ-T-r scores were significantly and positively correlated with self-reported frequency of consuming chocolate and with scores on the Attitudes to Chocolate Questionnaire, indicating good convergent validity. In study 2, students (n = 76; 73.7% female) underwent a chocolate exposure in the laboratory. FCQ-S scores increased during chocolate exposure and increases in momentary chocolate craving were significantly positively correlated with increases in salivary flow. Higher momentary chocolate craving was positively correlated with higher laboratory chocolate consumption. Exploratory analyses revealed that increases in salivary flow were only associated with increased chocolate consumption in participants scoring high, but not low on trait chocolate craving. The chocolate versions of the FCQ-T-r and FCQ-S represent reliable and valid self-report measures for the assessment of trait and state chocolate craving. Copyright © 2015. Published by Elsevier Ltd.
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Research report
Chocolate versions of the Food Cravings Questionnaires. Associations
with chocolate exposure-induced salivary flow and ad libitum
chocolate consumption
Adrian Meule a,b,*, Julia M. Hormes c
aInstitute of Psychology, University of Würzburg, Würzburg, Germany
bHospital for Child and Adolescent Psychiatry, LWL University Hospital, Ruhr University Bochum, Hamm, Germany
cDepartment of Psychology, University at Albany, State University of New York, Albany, NY, USA
ARTICLE INFO
Article history:
Received 28 January 2015
Received in revised form 21 March 2015
Accepted 15 April 2015
Available online 23 April 2015
Keywords:
Food craving
Chocolate
Food Cravings Questionnaires
Salivation
Salivary flow
Hunger
ABSTRACT
The Food Cravings Questionnaires are the most commonly used instruments for the assessment of trait
and state food craving. Chocolate is the most frequently craved food in Western societies. In the current
studies, the Food Cravings Questionnaire-Trait-reduced (FCQ-T-r) and the Food Cravings Questionnaire-
State (FCQ-S) were adapted to capture strong urges for chocolate. In study 1, students (n=492; 81.3% female)
completed chocolate versions of the FCQ-T-r and FCQ-S among other measures online. The FCQ-T-r (α =.94)
comprised two subscales representing lack of control =.91) and thoughts about chocolate =.91). The
FCQ-S (α =.87) comprised two subscales representing chocolate craving =.90) and hunger =.85). FCQ-
T-r scores were significantly and positively correlated with self-reported frequency of consuming chocolate
and with scores on the Attitudes to Chocolate Questionnaire, indicating good convergent validity. In study
2, students (n=76; 73.7% female) underwent a chocolate exposure in the laboratory. FCQ-S scores in-
creased during chocolate exposure and increases in momentary chocolate craving were significantly
positively correlated with increases in salivary flow. Higher momentary chocolate craving was positive-
ly correlated with higher laboratory chocolate consumption. Exploratory analyses revealed that increases
in salivary flow were only associated with increased chocolate consumption in participants scoring high,
but not low on trait chocolate craving. The chocolate versions of the FCQ-T-r and FCQ-S represent reli-
able and valid self-report measures for the assessment of trait and state chocolate craving.
© 2015 Elsevier Ltd. All rights reserved.
Introduction
Food craving refers to an intense desire to eat a specific food
(Hormes & Rozin, 2010). In Western societies, the most common-
ly craved food is chocolate, particularly in women (Rozin, Levine,
& Stoess, 1991; Weingarten & Elston, 1991). Food craving is usually
measured with self-report questionnaires, of which two of the most
frequently used are the Food Cravings Questionnaires (FCQs;
Cepeda-Benito, Gleaves, Fernández et al., 2000; Cepeda-Benito,
Gleaves, Williams, & Erath, 2000).
The FCQs consist of a trait version (FCQ-T) and a state version
(FCQ-S), designed to capture stable aspects of the craving experi-
ence and dynamic changes in craving, respectively. The FCQ-T
assesses the frequency of food craving experiences with 39 items,
response categories of which range from never/not applicable to
always. The original English and Spanish versions consist of nine
subscales representing the multiple dimensions of food craving: (1)
having intentions and plans to consume food, (2) anticipation of pos-
itive reinforcement that may result from eating, (3) anticipation of
relief from negative states and feelings as a result of eating, (4) lack
of control over eating, (5) thoughts or preoccupation with food, (6)
craving as a physiological state, (7) emotions that may be experi-
enced before or during food cravings or eating, (8) cues that may
trigger food cravings, and (9) guilt from cravings and/or for giving
into them (Cepeda-Benito, Gleaves, Fernández et al., 2000). However,
this factorial structure could not be replicated in several subse-
quent studies (Crowley et al., 2012, 2014; Meule, Lutz, Vögele, &
Kübler, 2012a; Rodríguez-Martín & Molerio-Pérez, 2014; Vander Wal,
Johnston, & Dhurandhar, 2007). Moreover, internal consistency of
the FCQ-T is very high (usually α >.90) and, therefore, researchers
often report FCQ-T total scores only.
In order to address these issues, a reduced version of the FCQ-T
(FCQ-T-r) was developed recently, which consists of 15 items and
has a one-factorial structure (Meule, Hermann, & Kübler, 2014). The
FCQ-T-r was initially validated in German, but its psychometric
Acknowledgments: The authors would like to thank Sophia Backhaus, Katrin Beck,
Ursula Becker, Julia Fischer, Marie Friedmann, Christian Ganster, Johannes Goldschmitt,
Tina Hermann, Nina Pfrommer, Stephen Pfrommer, Julia Semineth, Nina Vierheilig,
and Pauline Zahn for collecting the data.
* Corresponding author.
E-mail address: adrian.meule@rub.de (A. Meule).
http://dx.doi.org/10.1016/j.appet.2015.04.054
0195-6663/© 2015 Elsevier Ltd. All rights reserved.
Appetite 91 (2015) 256–265
Contents lists available at ScienceDirect
Appetite
journal homepage: www.elsevier.com/locate/appet
properties and correlates have since been replicated in Spanish,
Italian and English as well (Hormes & Meule, submitted; Innamorati
et al., 2015; Rodríguez-Martín & Molerio-Pérez, 2014).
The FCQ-S assesses momentary food craving with 15 items, re-
sponse categories of which range from strongly disagree to strongly
agree. The original English and Spanish versions consist of five
subscales representing (1) an intense desire to eat, (2) anticipa-
tion of positive reinforcement that may result from eating, (3)
anticipation of relief from negative states and feelings as a result
of eating, (4) lack of control over eating, and (5) craving as a phys-
iological state (i.e., hunger; Cepeda-Benito, Gleaves, Fernández et al.,
2000; Cepeda-Benito, Gleaves, Williams et al., 2000). Like for the
trait version, however, the proposed factor structure could only be
partially replicated in recent studies (Meule et al., 2012a; Vander
Wal et al., 2007) and internal consistency is usually very high
>.90), leading many researchers to report its total score only.
The wording of the FCQs simply asks respondents to indicate
agreement with the items of the scale and does not specify a spe-
cific food they should think of when completing the questionnaires.
While this is commonly considered an advantage of the FCQs over
other food craving questionnaires that are restricted to one or more
specific foods (cf. Martin, McClernon, Chellino, & Correa, 2011), the
general nature of the FCQs may be disadvantageous in some in-
stances, depending on the question of research. Rodriguez et al.
(2007) developed an adaptation of the FCQ-T for the assessment of
chocolate craving in British and Spanish women. They concluded
that the FCQ-T can be adapted successfully to assess specific food
cravings in addition to foods in general and that the chocolate-
adapted version is well suited to investigate chocolate craving in
English- and Spanish-speaking populations. To date, no study has
examined chocolate-adapted versions of the FCQ-T-r and FCQ-S. Thus,
the aim of the present studies was to develop and validate these
versions using the German versions of the FCQ-T-r and FCQ-S.
Study 1
Study 1 was a questionnaire-based study in which factor struc-
ture and correlates of the chocolate-adapted FCQ-T-r and FCQ-S were
investigated. Based on the one-factorial structure of the FCQ-T-r, we
hypothesized that its chocolate version would also show a one-
factorial structure. However, as no study has used such a version
before, we used exploratory factor analysis for testing factor struc-
ture. As the FCQ-S contains three items assessing hunger (i.e., without
any reference to one or more specific foods; see method section),
we expected that its chocolate-adapted version would consist of two
factors, representing chocolate craving and hunger. Although trait and
state food craving can be clearly differentiated with the FCQs, scores
on the FCQ-T/FCQ-T-r and the FCQ-S have been shown to be weakly
and positively correlated (Meule, Beck Teran et al., 2014). Hence,
we expected that trait chocolate craving would be positively cor-
related with state chocolate craving, but not with state hunger.
Studies using the FCQ-T/FCQ-T-r consistently show that women
and current dieters have higher trait food craving scores than men
and non-dieters, respectively, and that higher trait food craving scores
are associated with higher body mass index (BMI) and lower dieting
success (e.g., Cepeda-Benito, Fernandez, & Moreno, 2003; Hormes,
Orloff, & Timko, 2014; Meule, Hermann et al., 2014; Meule et al.,
2012a; Meule, Westenhöfer, & Kübler, 2011). Accordingly, we ex-
pected to find similar associations between these variables and the
chocolate version of the FCQ-T-r in the present study.
The Attitudes to Chocolate Questionnaire (ACQ; Benton, Greenfield,
& Morgan, 1998) measures trait chocolate craving and guilt asso-
ciated with chocolate craving and consumption (see methods). Scores
on its craving subscale have been found to be associated with self-
reported frequency of consuming chocolate (Benton et al., 1998; Van
Gucht, Soetens, Raes, & Griffith, 2014). As the FCQ-T-r does not
contain any items of the FCQ-T’s guilt subscale (Meule, Hermann
et al., 2014), we expected that scores on the chocolate version of
the FCQ-T-r would be highly, positively correlated with scores on
the craving subscale of the ACQ and to a lesser extent with scores
on the guilt subscale of the ACQ. Moreover, similar to what has been
found with the ACQ, we expected that scores on the chocolate version
of the FCQ-T-r would be positively correlated with self-reported fre-
quency of consuming chocolate.
Scores on the FCQ-S have typically been found to be positively
correlated with current food deprivation, that is, the time since par-
ticipants’ last meal (Cepeda-Benito et al., 2003; Meule, Hermann
et al., 2014;Meule et al., 2012a). Accordingly, we hypothesized that
current general food deprivation would be positively correlated with
scores on the chocolate version of the FCQ-S and that this associ-
ation would be particularly pronounced for its hunger subscale, but
smaller for its craving subscale.
Methods
Participants and procedure
A link to the online survey was distributed via e-mail to student
mailing lists at several universities in Germany. Participation was
voluntary and participants did not receive any compensation. Study
duration was two weeks. Every question required a response in order
to continue. The website was visited 833 times and n=612 par-
ticipants started questionnaire completion. Of these, n=498
participants completed the entire set of questions. The website’s
(https://www.soscisurvey.de) data quality check, which is based on
the time participants spent on each page, was used to exclude par-
ticipants who answered the questions carelessly (i.e., spent little time
on each page). As a result, data of n=6 participants were ex-
cluded from analyses, leaving a final sample size of n=492.
Most participants were women (81.3%, n=400), students (86.8%,
n=427), and had German citizenship (92.9%, n=457). Mean age was
M=24.58 years (SD =5.05, Range: 18–56). Mean BMI was
M=22.05 kg/m2(SD =3.27; Range: 14.13–42.83; n=39 [7.9%] un-
derweight [BMI <18.50 kg/m2], n=395 [80.3%] normalweight
[BMI =18.50–24.99 kg/m2], n=48 [9.8%] overweight [BMI =25.00–
29.99 kg/m2], n=10 [2.0%] obese [BMI 30.00 kg/m2]). Note that this
sample is not representative of the general population in Germany,
where in a comparable age group (18–29 years) mean BMI is higher
(approximately 24 kg/m2) and only around 65% are in the normal-
weight range (Mensink et al., 2013). Mean latency since the last meal
consumed was M=2.79 hours (SD =3.73, Range: 0–24). One-
hundred and seventy-seven participants (36.0%) reported to be
current dieters.
Measures
Chocolate version of the Food Cravings Questionnaire-Trait-reduced
(FCQ-T-r)
The term ‘chocolate’ was incorporated into each item of the
general version of the German FCQ-T-r (Table 1). Response catego-
ries were the same as in the original version, that is, responses were
scored 1–6 ranging from never/not applicable to always.
Chocolate version of the Food Cravings Questionnaire-State (FCQ-S)
References to ‘one or more specific foods’ in the general version
of the German FCQ-S were substituted with ‘chocolate’ (Table 2).
As the FCQ-S contains three items for the measurement of hunger,
which do not allow for a reference to specific foods, these items were
not changed (items 13–15, Table 2). Response categories were the
same as in the original version, that is, responses were scored 1–5
ranging from strongly disagree to strongly agree.
257A. Meule, J.M. Hormes/Appetite 91 (2015) 256–265
Table 1
Factor loadings and item statistics of the chocolate version of the Food Cravings Questionnaire-Trait-reduced in study 1.
Item Factor MSDr
itc
Control Thoughts
1. When I crave chocolate, I know I won’t be able to stop eating once I start.
[Wenn ich ein starkes Verlangen nach Schokolade verspüre, weiß ich, dass ich nicht mehr aufhören kann zu essen, wenn ich erst mal angefangen habe.]
.96 2.88 1.45 .75
2. If I have a chocolate craving, I often lose control and eat too much.
[Wenn ich ein starkes Verlangen nach Schokolade verspüre, verliere ich oft die Kontrolle und esse zu viel davon.]
.95 3.03 1.51 .76
3. Chocolate cravings invariably make me think of ways how to get chocolate.
[Wenn ich ein starkes Verlangen nach Schokolade verspüre, denke ich ausnahmslos darüber nach, wie ich Schokolade bekomme.]
.66 2.28 1.28 .76
4. I feel like I have chocolate on my mind all the time.
[Ich habe das Gefühl, dass ich die ganze Zeit nur Schokolade im Kopf habe.]
.87 1.56 0.87 .71
5. I find myself preoccupied with chocolate.
[Ich ertappe mich dabei, wie ich mich gedanklich ständig mit Schokolade beschäftige.]
.89 1.57 0.84 .67
6. Whenever I have chocolate cravings, I find myself making plans to eat chocolate.
[Immer wenn ich ein starkes Verlangen nach Schokolade verspüre, merke ich, dass ich gleich plane welche zu essen.]
.61 2.83 1.40 .63
7. I crave chocolate when I feel bored, angry, or sad.
[Ich verspüre ein starkes Verlangen nach Schokolade, wenn ich mich gelangweilt, wütend oder traurig fühle.]
.45 2.96 1.42 .63
8. I have no will power to resist my chocolate crave.
[Ich habe nicht die Willensstärke, um meinen Schokoladengelüsten widerstehen zu können.]
.50 2.60 1.35 .65
9. Once I start eating chocolate, I have trouble stopping.
[Wenn ich einmal anfange Schokolade zu essen, fällt es mir schwer wieder aufzuhören.]
.97 3.10 1.53 .75
10. I can’t stop thinking about chocolate no matter how hard I try.
[Ich kann nicht aufhören über Schokolade nachzudenken, wie sehr ich mich auch bemühe.]
.87 1.53 0.85 .73
11. If I give in to a chocolate craving, all control is lost.
[Wenn ich dem starken Verlangen nach Schokolade nachgebe, verliere ich jegliche Kontrolle.]
.56 .33 1.84 1.28 .75
12. Whenever I have a chocolate craving, I keep on thinking about eating chocolate until I actually eat it.
[Immer wenn ich ein starkes Verlangen nach Schokolade verspüre, denke ich so lange weiter ans Schokolade essen, bis ich diese tatsächlich esse.]
.81 2.15 1.27 .73
13. If I am craving chocolate, thoughts of eating it consume me.
[Wenn ich ein starkes Verlangen nach Schokolade verspüre, verzehren mich die Gedanken daran diese zu essen geradezu.]
.85 1.69 1.09 .71
14. My emotions often make me want to eat chocolate.
[Meine Emotionen bringen mich oft dazu Schokolade essen zu wollen.]
.56 2.47 1.35 .61
15. It is hard for me to resist the temptation to eat chocolate that is in my reach.
[Wenn sich Schokolade in meiner Reichweite befindet, fällt es mir schwer der Versuchung zu widerstehen sie zu essen.]
.75 3.28 1.45 .69
Notes: German item wording in square brackets. Only factor loadings >.30 are displayed.
258 A. Meule, J.M. Hormes/Appetite 91 (2015) 256–265
Perceived Self-Regulatory Success in Dieting (PSRS)
The PSRS (Fishbach, Friedman, & Kruglanski, 2003; Meule, Papies,
& Kübler, 2012) consists of three items and measures how success-
ful participants are in watching their weight or losing weight and
how easy it is for them to stay in shape. Responses are scored on a
scale ranging from 1 (=not successful/not difficult)to7(=very
successful/very difficult). Internal consistency was α =.72 in the current
study.
Attitudes to Chocolate Questionnaire (ACQ)
The ACQ (Benton et al., 1998) consists of 24 items and was orig-
inally proposed to measure craving for chocolate and eating chocolate
for emotional reasons (craving), negative feelings associated with
eating chocolate (guilt), and eating chocolate for functional reasons
(functional). Responses were recorded on a 10 cm visual analog scale
anchored not at all like me and very much like me. However, subse-
quent studies revealed that a 22-item, two-factor solution
representing craving and guilt ought to be preferred over the orig-
inal factor structure (Cramer & Hartleib, 2001; Müller, Dettmer, &
Macht, 2008; Van Gucht et al., 2014). Thus, we calculated those two
subscales in the current study. Participants indicated their re-
sponses using a slider bar that were scored 1–10. Internal consistency
was α =.85 for the craving subscale and α =.90 for the guilt subscale
in the current study.
Sociodemographic, anthropometric and other information
Participants were asked to report their age (in years), sex (male/
female), body height (in m), body weight (in kg), occupation (student/
other), citizenship (German/other), and time since their last meal
(in hours). Current dieting status (yes/no) was determined with a
single question (“Are you currently restricting your food intake to
control your weight [e.g. by eating less or avoiding certain foods]?”;
cf. Meule, Lutz, Vögele, & Kübler, 2012b). Chocolate consumption
was assessed with the question “How often do you eat choco-
late?”, responses of which were recorded on a four-point scale (never/
rarely,once or several times a month,once or several times a week,
almost daily/daily).
Data analyses
Sample size far exceeded the minimum 5:1 subjects-to-item ratio
necessary for exploratory factor analysis (Costello & Osborne, 2005).
Factor analyses of FCQ-T-r and FCQ-S data were carried out with
the program FACTOR Version 9.2 (Lorenzo-Seva & Ferrando, 2013).
Principal Component Analysis was chosen as extraction method and
Promax =4) was selected as rotation method. The number of
factors was determined by Minimum Average Partial (MAP) test.
Pearson’s product moment correlation coefficients were used to
examine associations between trait and state chocolate craving, BMI,
food deprivation, chocolate consumption, ACQ scores, and dieting
success. Independent t-tests were used to examine associations
between trait and state chocolate craving WITH sex and dieting
status. Exact p-values (two-tailed) are reported in case of signifi-
cance (p.05), except for p<.001. P-values >.05 are denoted as ns.
Results
Factor structure and reliability
FCQ-T-r
The Kaiser–Meyer–Olkin Measure of Sampling Adequacy
(KMO =0.94) and statistically significant Bartlett’s Test of Spheric-
ity (χ2(105) =5640.7, p<.001) indicated that the data were adequate
for conducting an exploratory factor analysis. The MAP test indi-
cated two dimensions (lowest averaged partial .03), which explained
65.6% of variance (component 1: 56.0%, component 2: 9.6%). Items
Table 2
Factor loadings and item statistics of the chocolate version of the Food Cravings Questionnaire-State in study 1.
Item Factor MSDr
itc
Craving Hunger
1. I have an intense desire to eat chocolate.
[Ich verspüre den intensiven Wunsch Schokolade zu essen.]
.77 2.28 1.17 .70
2. I’m craving chocolate.
[Ich verspüre ein starkes Verlangen nach Schokolade.]
.81 2.14 1.12 .73
3. I have an urge for chocolate.
[Ich verspüre den Drang Schokolade zu essen.]
.78 2.13 1.12 .68
4. Eating chocolate would make things seem just perfect.
[Schokolade zu essen, würde mir alles einfach perfekt erscheinen lassen.]
.74 1.71 0.96 .61
5. If I were to eat chocolate, I am sure my mood would improve.
[Wenn ich Schokolade essen würde, würde sich sicher meine Stimmung verbessern.]
.70 2.59 1.23 .63
6. Eating chocolate would feel wonderful.
[Schokolade zu essen würde sich großartig anfühlen.]
.72 2.78 1.26 .63
7. If I ate chocolate, I wouldn’t feel so sluggish and lethargic.
[Wenn ich Schokolade essen würde, würde ich mich nicht so träge und antriebslos fühlen.]
.56 1.82 0.95 .52
8. Satisfying my chocolate craving would make me feel less grouchy and irritable.
[Wenn ich mein Verlangen nach Schokolade stillen könnte, würde ich mich weniger schlecht gelaunt und gereizt fühlen.]
.69 1.97 1.09 .59
9. I would feel more alert if I could satisfy my chocolate craving.
[Wenn ich mein Verlangen nach Schokolade stillen könnte, würde ich mich munterer fühlen.]
.66 1.99 1.02 .60
10. If I had chocolate, I could not stop eating it.
[Wenn ich Schokolade hätte, könnte ich nicht aufhören davon zu essen.]
.54 2.71 1.43 .38
11. My desire to eat chocolate seems overpowering.
[Mein Verlangen Schokolade zu essen scheint überwältigend zu sein.]
.72 1.64 0.97 .55
12. I know I’m going to keep on thinking about chocolate until I actually have it.
[Ich weiß, dass ich solange an Schokolade denken werde, bis ich sie tatsächlich habe.]
.67 1.78 1.08 .53
13. I am hungry.
[Ich habe Hunger.]
.91 2.20 1.29 .28
14. If I ate right now, my stomach wouldn’t feel as empty.
[Wenn ich jetzt etwas essen würde, würde sich mein Magen nicht mehr so leer anfühlen.]
.90 2.36 1.37 .32
15. I feel weak because of not eating.
[Ich fühle mich schwach, weil ich nichts gegessen habe.]
.79 1.55 0.89 .25
Notes: German item wording in square brackets. Only factor loadings >.30 are displayed.
259A. Meule, J.M. Hormes/Appetite 91 (2015) 256–265
of the first factor (3, 4, 5, 6, 7, 10, 12, 13, 14) included items of the
original version’s subscales thoughts or preoccupation with food (5
items), intentions and plans to consume food (2 items) and emo-
tions (2 items) (Cepeda-Benito, Gleaves, Williams et al., 2000). Thus,
we termed this the thoughts subscale. Items of the second factor
(1, 2, 8, 9, 11, 15) included items of the original version’s subscales
lack of control over eating (5 items) and cues that may trigger food
cravings (1 item) (Cepeda-Benito, Gleaves, Williams et al., 2000). Thus,
we termed this the control subscale. Internal consistencies were
α=.91 (control subscale), α =.91 (thoughts subscale), and α =.94 (total
scale). Items, factor loadings, and item statistics are displayed in
Table 1.
FCQ-S
The Kaiser–Meyer–Olkin Measure of Sampling Adequacy
(KMO =0.87) and Bartlett’s Test of Sphericity (χ2(105) =4254.4, p<.001)
indicated that the data were adequate for conducting an explor-
atory factor analysis. The MAP test indicated two dimensions (lowest
averaged partial .04), which explained 55.4% of variance (compo-
nent 1: 39.9%, component 2: 15.4%). Items of the first factor (12,
13, 14) were the items of the original version’s subscale craving as
a physiological state (Cepeda-Benito, Gleaves, Williams et al., 2000).
Thus, we termed this the hunger subscale. Items of the second factor
(1–12) included items of the original version’s subscales intense desire
to eat,anticipation of positive reinforcement,anticipation of negative
reinforcement, and lack of control over eating (Cepeda-Benito, Gleaves,
Williams et al., 2000). Thus, we termed this the craving subscale.
Internal consistencies were α =.90 (craving subscale), α =.85 (hunger
subscale), and α =.87 (total scale). Items, factor loadings, and item
statistics are displayed in Table 2.
Correlates of trait and state chocolate craving
Higher trait chocolate craving was strongly correlated with higher
scores on the craving subscale of the ACQ, moderately correlated
with higher scores on the guilt subscale of the ACQ, higher choc-
olate consumption, lower dieting success, and higher state chocolate
craving, and weakly correlated with higher BMI (Table 3). Higher
state chocolate craving was also positively associated with ACQ
craving and guilt scores, frequency of chocolate consumption, and
perceived dieting success, but not with BMI (Table 3). Only FCQ-S
hunger subscale scores were significantly correlated with current
food deprivation (Table 3). Women reported higher trait and state
chocolate craving than men, but did not differ in current hunger
(Table 4). Current dieters reported higher trait chocolate craving than
non-dieters, but did not differ in state chocolate craving or hunger
(Table 4).
Conclusion of study 1
The chocolate versions of the FCQ-T-r and FCQ-S had good to ex-
cellent internal consistencies. Contrary to our initial hypotheses, the
FCQ-T-r contained two subscales assessing (1) a lack of control over
eating chocolate and (2) thoughts about and preoccupation with
chocolate. In line with expectations, the FCQ-S combined the
subscales assessing momentary (1) chocolate craving and (2) hunger.
Higher levels of trait chocolate craving were associated with higher
BMI, more frequent chocolate consumption, higher scores on the
ACQ, and lower dieting success. Current dieters and women had
higher FCQ-T-r scores than non-dieters and men. Higher scores on
the FCQ-S hunger subscale, but not on its craving subscale were
Table 3
Descriptive statistics of and correlations between continuous study variables in study 1.
n=492 M(SD) Range 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.
1. FCQ-T-r – control 16.73 (7.19) 6–36 .73*** .92*** .48*** .12 *.40*** .14** .08 .34*** .70*** .52*** .30***
2. FCQ-T-r – thoughts 19.03 (8.03) 9–49 .94*** .54*** .05 .47*** .06 .03 .42*** .79*** .40*** .31***
3. FCQ-T-r – total 35.76 (14.15) 15–82 .55*** .09 .47*** .11*.06 .41*** .80*** .49*** .33***
4. FCQ-S – craving 25.52 (9.32) 12–54 .15** .95*** .00 .03 .42*** .59*** .24*** .12 **
5. FCQ-S – hunger 6.11 (3.15) 3–15 .44*** .05 .39*** .01 .06 .08 .01
6. FCQ-S – total 31.63 (10.28) 15–65 .01 .10*.38*** .52*** .19*** .1 1*
7. Body mass index
(kg/m2)
22.05 (3.27) 14.13–42.83 .04 .06 .06 .14** .41***
8. Food deprivation
(hours)
2.79 (3.73) 0–24 .05 .06 .07 .05
9. Chocolate consumption
frequency
3.05 (0.88) 1–4 .52*** .00 .05
10. ACQ – craving 4.02 (1.60) 1.00–8.75 .41*** .28***
11. ACQ – guilt 3.87 (2.01) 1.00–9.30 .39***
12. PSRS 12.98 (3.58) 3–21
Notes: FCQ-T-r =Food Cravings Questionnaire-Trait-reduced, FCQ-S =Food Cravings Questionnaire – State, ACQ =Attitudes to Chocolate Questionnaire, PSRS =Perceived Self-
Regulatory Success in Dieting Scale.
*p<.05, **, p<.01, ***p<.001.
Table 4
Comparison of trait and state chocolate craving between women and men and between current dieters and non-dieters in study 1.
Sex t(490) pCurrent dieting status t(490) p
Women (n=400) M(SD) Men (n=92) M(SD) Dieters (n=177) M(SD) Non-dieters (n=315) M(SD)
FCQ-T-r
Control 17.20 (7.31) 14.70 (6.29) 3.04 .003 18.53 (7.61) 15.72 (6.75) 4.22 <.001
Thoughts 20.03 (8.19) 14.70 (5.54) 5.94 <.001 20.58 (8.71) 18.17 (7.49) 3.23 .001
Total 37.23 (14.41) 29.39 (10.88) 4.90 <.001 39.10 (15.31) 33.89 (13.10) 3.98 <.001
FCQ-S
Craving 26.02 (9.43) 23.33 (8.58) 2.52 .01 25.88 (9.11) 25.31 (9.45) 0.65 ns
Hunger 6.01 (3.14) 6.55 (3.18) 1.50 ns 6.18 (3.24) 6.08 (3.11) 0.33 ns
Total 32.03 (10.36) 29.88 (9.78) 1.82 ns 32.06 (10.38) 31.39 (10.23) 0.69 ns
Notes: FCQ-T-r =Food Cravings Questionnaire-Trait-reduced, FCQ-S =Food Cravings Questionnaire – State.
260 A. Meule, J.M. Hormes/Appetite 91 (2015) 256–265
related to longer food deprivation. Trait and state chocolate craving
were positively associated with each other, whereby this associa-
tion was driven by the FCQ-S craving, but not its hunger subscale.
To conclude, study 1 provided initial support for validity of both choc-
olate adapted versions of the FCQs. Interrelationships between and
correlates of the chocolate versions of the FCQ-T-r and FCQ-S were
comparable to those found in prior studies using the general ver-
sions (Meule, Beck Teran et al., 2014;Meule, Hermann et al., 2014;
Meule et al., 2012a). It appears, however, that current craving vs.
hunger, as measured with the FCQ-S, can be more clearly differen-
tiated when specifically assessing chocolate craving, as compared
to the general version of the FCQ-S.
Study 2
In study 2, changes in FCQ-S scores during chocolate exposure
were investigated in the laboratory. Furthermore, associations with
salivary flow and ad libitum chocolate intake were tested. There are
different techniques for the measurement of salivary flow, all of
which are intercorrelated (Nederkoorn, Smulders, & Jansen, 1999;
White, 1977). The most common technique for measuring saliva-
tion in the context of food and eating is the use of cotton dental
rolls (Wooley & Wooley, 1981), often referred to as the Strongin–
Hinsie–Peck Test (Peck, 1959). This method was chosen in the current
study as well, because it is easier to apply than counting the number
of swallows (which requires recording of electromyography;
Nederkoorn et al., 1999) and it is more comfortable for both the ex-
perimenter and the participant than collecting saliva in a cup (White,
1977).
Salivary flow increases during exposure to palatable foods as com-
pared to baseline measurement (e.g., Nederkoorn, Smulders, &
Jansen, 2000; Nirenberg & Miller, 1982; Sahakian, 1981; Wooley &
Wooley, 1981) and this increase may be related to increased desire
for these foods. For example, there are few studies in which self-
reported hunger or desire to eat correlated with salivary response
as measured with dental rolls during food exposure (e.g., Booth &
Fuller, 1981; Legenbauer, Vögele, & Rüddel, 2004). However, note
that although salivary flow increases during food exposure (as mea-
sured either with dental rolls or with other techniques such as the
number of swallows), it did not correlate with subjective craving
or food intake in the majority of studies (e.g., Legenbauer et al., 2004;
Nederkoorn et al., 2000; Nirenberg & Miller, 1982; Sahakian, 1981;
Wooley & Wooley, 1981).
Given that the FCQ-S was developed to capture dynamic changes
in craving intensity, we expected that scores on the FCQ-S craving
subscale would remain stable during a baseline period, increase
during chocolate exposure, and decrease after chocolate exposure
when participants were allowed to eat the chocolate. Regarding the
FCQ-S hunger subscale, we expected that scores would not change
throughout the experiment. Salivary flow was expected to be higher
during chocolate exposure, as compared to baseline, and this in-
crease was hypothesized to be correlated with increases in state
chocolate craving. As higher FCQ-T/FCQ-T-r scores have previously
been found to predict increases in state food craving in response
to food-cue exposure (Meule, Hermann et al., 2014; Meule & Kübler,
2014; Meule, Skirde, Freund, Vögele, & Kübler, 2012), both in-
creases in salivation and chocolate craving were expected to be
positively correlated with trait chocolate craving, that is, FCQ-T-r
scores.
Similar to study 1, we expected that trait and state chocolate
craving would be positively correlated with chocolate intake. In ad-
dition, higher salivation was also hypothesized to be related to higher
chocolate intake. On an exploratory basis, we also examined if trait
chocolate craving was a moderator of the relationships between in-
creases in state chocolate craving or salivation and chocolate
consumption.
Methods
Participants
Participants were n=76 students (73.7% female, n=56) at the
University of Würzburg (Würzburg, Germany). Mean age was
M=23.59 years (SD =3.92, Range: 18–37). Mean BMI was
M=21.82 kg/m2(SD =2.89, Range: 16.65–36.88). Participants were
asked to estimate the time that elapsed since their last meal: mean
food deprivation was M=3.54 hours (SD =4.09, Range: 0–16). Eigh-
teen participants (23.7%) reported to be current dieters. Three
participants (3.9%) reported to be smokers. Participants received
course credits for compensation.
Measures and materials
Chocolate versions of the FCQ-T-r and FCQ-S
The chocolate-adapted German versions of the FCQ-T-r and
FCQ-S, which were used in study 1, were also used in study 2. As
the two subscales of the FCQ-T-r were highly correlated with each
other in study 1 and in this study (r=.81, p<.001), only its total score
was used in the current analyses. Internal consistency was excel-
lent (Cronbach’s α =.94). Participants completed the FCQ-S four times
and internal consistencies ranged from good to excellent for both
the craving =.89–.92) and hunger =.88–90) subscales, as well
as the total scale (α =.88–90).
Chocolate bars
Five different types (crunchy cookie, crunchy flakes, yogurt,
nougat, alpine milk) of 100 g chocolate bars (Ritter Sport, Alfred Ritter
GmbH & Co. KG, Waldenbuch, Germany, a brand that is popular and
widely available in Germany) were used for the chocolate exposure.
Salivation
Two cotton dental rolls (10 ×38 mm) were used each for mea-
suring baseline salivary flow and salivary flow during chocolate
exposure.
Weighing scales and body height
A micro scales (0.01 g precision; DIPSE/SSR-Produkt GmbH &
Co.KG, Oldenburg, Germany) was used for weighing the dental rolls
and the chocolate. A personal scale (PS 22, Beurer GmbH, Ulm,
Germany) was used for determining body weight of participants.
Body height was measured with a body height meter.
Procedure
Participants were tested individually. After participants were wel-
comed by the experimenter, they completed the informed consent
process. They were asked to take at least one sip of water or as many
as needed to quench their thirst. Participants then completed a paper-
and-pencil version of the FCQ-S for the first time. Next, the
experimenter handed out two dental rolls and instructed partici-
pants to place these between their lower gums and cheeks. After
one minute, the experimenter removed the dental rolls with tweez-
ers and put them in a small plastic bag. Participants then completed
the FCQ-S for the second time. Following this, five sorts of choco-
late bars were placed in front of the participants and they were
instructed to choose the one they liked the most at that moment.
Participants were then again instructed to place two dental rolls
between their lower gums and cheeks, and, subsequently, to unwrap
the chocolate, to snap off one piece with their fingers, and to smell
it. After one minute, the experimenter again removed the dental
rolls with tweezers and put them in a small plastic bag. Partici-
pants then completed the FCQ-S for the third time. Participants
were then told that they could now eat as much of the remaining
261A. Meule, J.M. Hormes/Appetite 91 (2015) 256–265
chocolate bar as they wished during completion of the final set of
questionnaires, which assessed sociodemographic information, time
since participants’ last meal, and included the chocolate versions
of the FCQ-T-r and FCQ-S, and additional measures. During ques-
tionnaire completion, the experimenter unobtrusively left the room
and returned after ten minutes. Finally, participants’ body weight
and height were measured and the dental rolls and the remaining
chocolate were weighed.
Data analyses
Changes in current chocolate craving and current hunger were
examined via repeated measures analyses of variance of the re-
spective subscale scores of the FCQ-S. Analyses were followed-up
with paired samples t-tests. For subsequent correlation analyses,
change scores were computed by subtracting FCQ-S scores prior to
chocolate exposure from FCQ-S scores after chocolate exposure, that
is, higher values indicate an increase in current chocolate craving
and hunger, respectively, during chocolate exposure.
Baseline salivation was computed by subtracting the weight of
the dental rolls prior to baseline measurement from the weight of
the dental rolls after baseline measurement. Chocolate exposure sal-
ivation was computed by subtracting the weight of the dental rolls
prior to the chocolate exposure from the weight of the dental rolls
after the chocolate exposure. Change in salivation between base-
line and chocolate exposure was tested with a paired t-test. For
subsequent correlation analyses, a change score was computed by
subtracting baseline salivation from chocolate exposure saliva-
tion, that is, higher values indicate an increase in salivary flow from
baseline to chocolate exposure.
Regarding chocolate consumption, the weight of the remain-
ing chocolate after the experiment was subtracted from the initial
weight, that is, higher values indicate a higher amount of choco-
late consumed. Pearson product moment correlation coefficients
were computed to examine the strength of the relationships between
food deprivation (i.e., hours since the last meal), current chocolate
craving, current hunger, trait chocolate craving (i.e., FCQ-T-r scores),
salivary flow, and chocolate consumption.
Finally, we explored if possible relationships between changes
in chocolate craving and salivation with chocolate consumption were
moderated by individual differences in trait chocolate craving. For
this, a linear regression analysis was calculated with chocolate craving
change score, FCQ-T-r scores, and the interaction of chocolate craving
change score ×FCQ-T-r as predictor variables and consumed choc-
olate as dependent variable. Similarly, a linear regression analysis
was calculated with salivation change score, FCQ-T-r scores, and the
interaction of salivation change score ×FCQ-T-r as predictor vari-
ables and consumed chocolate as dependent variable. Sex, dieting
status and food deprivation were initially included as predictors but
did not change results as neither variable was associated with choc-
olate consumption or salivation and, thus, results are presented
without these variables. All regression analyses were computed using
the program Interaction! Version 1.7.2211 (Freeware available at
http://www.danielsoper.com/interaction). Exact p-values (two-
tailed) are reported in case of significance (p.05), except for p<.001.
P-values >.05 are denoted as ns.
Results
Changes in current chocolate craving and hunger
Current chocolate craving changed over the course of the ex-
periment (F(3,225) =28.12, p<.001, ηp2=.27; Fig. 1). Craving did not
change between the first and second measurement (t(75) =0.41, ns),
but was significantly higher after chocolate exposure (M=31.00,
SD =9.39) than before (M=26.82, SD =8.75, t(75) =6.81, p<.001). At
the end of the experiment (M=24.36, SD =8.81), craving de-
creased significantly, that is, was lower as compared to after
chocolate exposure (t(75) =7.46, p<.001; Fig. 1).
Current hunger changed over the course of the experiment
(F(3,225) =8.53, p<.001, ηp2=.10; Fig. 1). Hunger did not change
between the first and second measurement (t(75) =0.76, ns), but was
higher after chocolate exposure (M=7.38, SD =3.22) than before
(M=6.97, SD =3.08, t(75) =3.31, p<.001). At the end of the experi-
ment (M=6.38, SD =3.09), hunger decreased, that is, was lower as
compared to after chocolate exposure (t(75) =4.17, p<.001; Fig. 1).1
Changes in salivary flow
Salivation during chocolate exposure (M=0.49 g, SD =0.35) was
significantly higher than baseline salivation (M=0.38 g, SD =0.22,
t(75) =3.57, p=.001).
1We also conducted these analyses with sex as between-subject factor. For state
chocolate craving, there was main effect of sex, indicating that men had lower scores
than women (F(1,74) =3.89, p=.05). However, there was no significant interaction of
sex ×measurement (F(3,222) =1.44, ns), indicating that although men and women dif-
fered in absolute state chocolate craving, changes in state chocolate craving throughout
the experiment were not different for men and women. For hunger, there was neither
a main effect of sex (F(1,74) =0.50, ns) nor an interaction of sex ×measurement
(F(3,222) =1.25, ns). Replicating findings of study 1, men reported lower trait choco-
late craving than women (t(74) =2.76, p=.009). However, men and women did not
differ in current food deprivation, salivary flow, or chocolate consumption (all
t(74)s<1.08, ns). Accordingly, controlling for sex in the subsequent correlational and
regression analyses did not affect results.
Including dieting status as between-subject factor in the analysis of variance for
state chocolate craving did neither reveal a main effect of dieting status (F(1,74) =0.56,
ns) nor an interaction of dieting status ×measurement (F(3,222) =1.41, ns). Similarly,
for hunger, there was neither a main effect of dieting status (F(1,74) =0.01, ns) nor
an interaction of dieting status ×measurement (F(3,222) =0.45, ns). Replicating find-
ings of study 1, dieters reported higher trait chocolate craving than non-dieters,
although this difference was not statistically significant (t(74) =1.69, ns). Dieters and
non-dieters did not differ in current food deprivation, salivary flow, or chocolate con-
sumption (all t(74)s<1.42, ns). Accordingly, controlling for dieting status in the
subsequent correlational and regression analyses did not affect results.
Fig. 1. Mean scores of the craving and hunger subscales of the chocolate version of
the Food Cravings Questionnaire-State in study 2. Both chocolate craving and hunger
scores remained stable during baseline salivation measurement, increased during
chocolate exposure, and decreased afterwards. Note that analyses are based on sum
scores, but mean scores are used for presentation purposes here. Error bars indi-
cate the standard error of the mean.
262 A. Meule, J.M. Hormes/Appetite 91 (2015) 256–265
Correlations between study variables
Food deprivation was positively correlated with all four mea-
surements of current hunger (rs=.38-.48, ps.001), but not with
current chocolate craving. Vice versa, trait chocolate craving was
positively correlated with all four measurements of current choc-
olate craving (rs=.42-.50, ps<.001), but not with current hunger.
Changes in salivary flow were positively correlated with changes
in chocolate craving during chocolate exposure (r=.30, p=.008), but
not with changes in hunger during chocolate exposure (r=.06, ns;
Fig. 2).
Participants consumed on average M=25.76 g (SD =23.46) of
chocolate (or M=140.49 kcal, SD =127.06). Chocolate intake was pos-
itively correlated with all four measurements of current chocolate
craving (rs=.42–.50, ps<.001), but not with current hunger.
Predictors of chocolate intake
In the regression analysis including chocolate craving, neither
trait chocolate craving (β =.15, ns), chocolate craving change score
=−.02, ns), nor the interaction term (β =−.02, ns) were signifi-
cant predictors of chocolate intake. In the regression analysis
including salivation, trait chocolate craving (β =.18, ns) and saliva-
tion change score (β =.23, ns) were non-significant predictors of
chocolate intake. However, there was a significant interaction
between trait chocolate craving and salivation change score (β =.37,
p=.005). Increases in salivary flow from baseline to chocolate ex-
posure were only related to higher chocolate intake in individuals
scoring high on trait chocolate craving (+1SD=.68, p =.007), but
not in individuals scoring low on trait chocolate craving (1SD,
β=−.22, ns;Fig. 3).
Conclusion of study 2
As expected, state chocolate craving as measured with the choc-
olate version of the FCQ-S remained stable across the baseline period,
increased during chocolate exposure, and decreased afterwards. Un-
expectedly, hunger ratings followed the same pattern of dynamic
change, although effect size was smaller than for the craving ratings.
Furthermore, additional analyses showed a clear differentiation
between current chocolate craving and hunger: similar to study 1,
length of food deprivation was positively correlated with hunger
(but not chocolate craving), while trait chocolate craving was pos-
itively correlated with state chocolate craving (but not hunger).
Furthermore, only increases in current chocolate craving (but not
hunger) were correlated with increases in salivation and current
chocolate craving (but not hunger) was correlated with higher choc-
olate consumption.
Contrary to hypotheses, trait chocolate craving was unrelated to
increases in state chocolate craving, increases in salivary flow, and
chocolate consumption. However, trait chocolate craving was found
to be a moderator of the relationship between increases in saliva-
tion and chocolate consumption. Increased salivary flow was only
associated with higher chocolate intake in individuals with high trait
chocolate craving scores, but not in those with low trait chocolate
craving scores. To conclude, study 2 replicated and extended the
findings from study 1, providing further support for the validity of
the chocolate adapted FCQs by demonstrating associations with ob-
jective measures such as salivary flow and ad libitum chocolate
intake.
Discussion
In the current studies, the FCQ-T-r and FCQ-S were adapted to
refer to chocolate, their factor structures were explored and their
correlates examined. Both versions had good to excellent internal
consistencies. Contrary to hypotheses and findings from prior val-
idation studies, however, the chocolate version of the FCQ-T-r
contained two factors representing (1) a lack of control over eating
chocolate and (2) thoughts about and preoccupation with choco-
late. However, both subscales were highly correlated with each other.
Thus, future research may investigate if use of the two subscales
in the assessment of correlates of trait cravings has significant ad-
vantages over the use of FCQ-T-r total scores.
Between-group differences and correlates of the chocolate version
of the FCQ-T-r were largely similar to those of the general ver-
sions of the FCQ-T/FCQ-T-r, indicating construct validity. For example,
Fig. 2. Scatterplot showing associations between changes in salivary flow and scores
on the chocolate version of the Food Cravings Questionnaire-State in study 2. In-
creases in salivary flow from baseline to chocolate exposure were correlated with
increasing craving scores from pre- to post-exposure, but not with changes in hunger
scores from pre- to post-exposure. Note that analyses are based on differences of
sum scores, but z-scores are used for presentation purposes here.
Fig. 3. Simple slopes showing the moderating effect of scores on the chocolate version
of the Food Cravings Questionnaire-Trait-reduced on the relationship between changes
in salivary flow and chocolate consumption in study 2. Increases in salivary flow from
baseline to chocolate exposure were associated with higher chocolate intake at the
end of the experiment in participants scoring high on trait chocolate craving, but
not in those scoring low on trait chocolate craving.
263A. Meule, J.M. Hormes/Appetite 91 (2015) 256–265
women had higher trait chocolate craving scores than men. While
there are marked gender differences in chocolate craving in North
America, cultural differences have been found. For example, it
appears that this gender effect is less pronounced in Spain (Osman
& Sobal, 2006) and Spanish women reported less frequent choco-
late craving than British women (Rodriguez et al., 2007). In Germany,
it has been previously found that women had higher scores than
men on the ACQ (Müller et al., 2008). In the current studies, a clear
gender effect was found and, thus, results suggest that the rela-
tionship between chocolate craving and gender may be more similar
between Germany and North America as opposed to other Euro-
pean countries. Interestingly, it has been found recently that there
is a positive relationship between chocolate craving and disor-
dered eating behavior in women, but not in men in the US (Hormes
et al., 2014). Future research may investigate if such interactive effects
are culture-specific or if similar findings can be obtained in (at least
some) European countries.
Trait chocolate craving was higher in current dieters than in non-
dieters and scores were weakly and positively correlated with BMI
and negatively correlated with dieting success, similar to findings
from studies in which the general version of the FCQ-T-r was used
(Innamorati et al., 2015; Meule, Hermann et al., 2014;
Rodríguez-Martín & Molerio-Pérez, 2014). Moreover, trait choco-
late craving scores were highly correlated with a conceptually similar
measure (the ACQ) and were related to more frequent chocolate con-
sumption, similar to what has been found using the ACQ (Benton
et al., 1998; Van Gucht et al., 2014). Although FCQ-T-r scores were
positively correlated with FCQ-S scores in both studies, FCQ-T-r scores
were, unexpectedly, neither associated with increases in state choc-
olate craving or salivation during chocolate exposure nor with ad
libitum chocolate consumption in the laboratory. This may be due
to ceiling effects as chocolate craving increased during chocolate ex-
posure in most participants and state chocolate craving was
associated with chocolate consumption independent of trait choc-
olate craving. However, we found that trait chocolate craving was
a significant moderator of the relationship between increases in sal-
ivation during chocolate exposure and subsequent chocolate intake.
Specifically, increased salivation was only associated with higher
chocolate intake in those with high trait craving scores, but not in
those with low trait craving scores. Hence, increased salivation, which
prepares the body for ingestion and was associated with in-
creased desire to eat chocolate, only results in chocolate intake in
those who report habitual strong chocolate craving, but not in those
who report having a higher level of control over their chocolate
consumption.
As expected, the chocolate version of the FCQ-S combined two
subscales representing chocolate craving and hunger. Although scores
on the hunger subscale also changed as a function of chocolate ex-
posure, it appears that craving and hunger can be more clearly
differentiated when there is a specific food specified in the wording
of the craving-related items, compared to the general version of the
measure. For example, food deprivation was exclusively related to
scores on the hunger subscale, but not to scores on the craving
subscale in both studies. Vice versa, trait chocolate craving was ex-
clusively related to scores on the craving subscale, but not to scores
on the hunger subscale in both studies. Moreover, only increases
in state chocolate craving, but not increases in current hunger were
related to increased salivary flow and only state chocolate craving,
but not hunger, was related to laboratory chocolate intake.
Interpretation of results is limited by the fact that most partici-
pants were normal-weight, female university students. Future studies
should extend the present findings to larger samples of men or to
clinical samples, for example, individuals with eating disorders or
obesity. Such research appears to be particularly worthwhile given
the differential relationships between chocolate craving and disor-
dered eating as a function of gender (Hormes et al., 2014). Moreover,
we only had one experimental condition in study 2 (namely choc-
olate exposure) and, thus, future research on chocolate craving and
salivation may include additional conditions such as a control group
with no chocolate exposure or an imaginal craving induction pro-
tocol (Kemps & Tiggemann, 2007). Finally, we used German versions
of the chocolate adapted FCQs and, thus, it is yet to be demon-
strated that they can be equally used in other languages, particularly
given the cultural differences in chocolate craving (Hill, 2007; Osman
& Sobal, 2006; Rodriguez et al., 2007). If proven successful, the choc-
olate versions of the FCQ-T-r and FCQ-S may be useful instruments
for the transcultural investigation of chocolate craving. As has been
demonstrated in the current studies, we conclude that the choco-
late versions of the FCQ-T-r and FCQ-S represent reliable and valid
self-report measures for the assessment of trait and state choco-
late craving.
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... In a laboratory study on chocolate craving, for example, current chocolate craving intensity was positively correlated with current hunger, but unrelated to the length of food deprivation. Moreover, only current chocolate craving intensity-but not current hunger-related to higher salivary flow during a chocolate exposure and to higher chocolate consumption [12]. ...
... The experience of a food craving is multidimensional. Physiologically, it is associated with several processes that prepare the body for ingestion and motivates food seeking and consumption such as increased salivary flow [12,13] and activation of reward-related brain areas such as the striatum [14][15][16]. It also includes cognitive (i.e., thinking abou the food) and emotional (e.g., desire to eat or changes in mood) components. ...
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Purpose of Review: Dieting is often blamed for causing food cravings. Such diet-induced cravings may be mediated by physiological (e.g., nutritional deprivation) or psychological (e.g., ironic effects of food thought suppression) mechanisms. However, this notion is often based on cross-sectional findings and, thus, the causal role of food deprivation on food cravings is unclear. Recent Findings: Experimental studies suggest that a short-term, selective food deprivation seems to indeed increase cravings for the avoided foods. However, experimental studies also show that food craving can be understood as a conditioned response that, therefore, can also be unlearned. This is supported by intervention studies which indicate that long-term energy restriction results in a reduction of food cravings in overweight adults. Summary: Dieting’s bad reputation for increasing food cravings is only partially true as the relationship between food restriction and craving is more complex. While short-term, selective food deprivation may indeed increase food cravings, long-term energy restriction seems to decrease food cravings, suggesting that food deprivation can also facilitate extinction of conditioned food craving responses.
... Food Cravings Questionnaire-Trait-reduced (FCQ-T-r). Craving for chocolate in general was assessed with the German 15-item version of the FCQ-T-r, consisting of the subscales lack of control and thoughts about chocolate (Meule & Hormes, 2015). Items were re-phrased to specifically assess craving for chocolate. ...
... Food Cravings Questionnaire-State (FCQ-S). To assess momentary craving specifically for chocolate the German 15-item version of the FCQ-S was administered (Meule & Hormes, 2015). Participants had to indicate whether they agree with each item (1 = strongly disagree to 5 = strongly agree). ...
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Behavioral tendencies in the Approach-Avoidance Task (AAT) have mostly been assessed using a joystick as a response device. In recent years, other hardware devices such as tablets, smartphones, and computer mice have also been used. However, it remains unclear whether different response devices yield similar results and show comparable psychometric properties. The aim of the present study was to assess approach biases towards chocolate with different response devices and to compare their reliability and validity. Forty-five individuals with regular chocolate consumption completed three different AATs (joystick, computer mouse, touchscreen), each comprised of two blocks. In the compatible block of trials, chocolate-related pictures had to be pulled near while object-related pictures had to be pushed away. In the incompatible block of trials, instructions were reversed. Preregistered analyses revealed that participants were faster to pull than to push chocolate-related pictures relative to object-related pictures, indicating an approach bias for chocolate with no significant differences between response devices. Correlations among the three response devices were low to medium. Exploratory analyses revealed that approach biases were moderated by block order such that biases were only present and associated with craving (joystick AAT only) when the incongruent block was completed first. Internal consistencies of the bias score ranged between rSB = .67-.76. Results of the present study point to the existence of an approach bias to chocolate regardless of response device, albeit each task seems to measure a different aspect of it. Order effects point to specific temporal dynamics in the acquisition of stimulus response (e.g., chocolate-pull) mappings that require further study.
... Food cravings are an important predictor of food consumption. Increased food cravings are linked with consuming craved foods, such as chocolate, more habitually [65]. Chocolate can act as a mood booster and may also increase cravings or impose negative emotions, such as guilt [66] when considered as an unhealthy snack. ...
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This research measured consumers’ emotions and change in emotion to the specific sensory taste properties and attitudes of chocolate-based biscuits. The sample size involved 216 respondents from South Africa (n = 106) and Switzerland (n = 110). Respondents tasted chocolate-based biscuits and completed an online questionnaire. The increase in consumers’ levels of guilt after chocolate-based biscuit consumption and the contribution of a chocolate taste and craving attitude to consumers’ subsequent positive emotions and change in positive emotions could help food and consumer scientists to understand the link between emotions and the sensory descriptors of chocolate-based biscuits. Investigating the association between the emotional responses and sensory attributes of sweet baked products could benefit product developers when formulating food products for specific target markets and aid in the understanding of the emotional profile of food products.
... The FCQ-S [21,22] consists of 15 items, 12 of which ask about the intensity of current food craving and three ask about the intensity of current hunger. Thus, we examined these two subscales separately instead of analyzing a total score [23]. Responses are recorded on a five-point scale ranging from 1 = strongly disagree to 5 = strongly agree. ...
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Purpose Plate clearing—eating a meal in its entirety—is common and may be a factor contributing to obesity. For the assessment of individual differences in plate clearing tendencies, Robinson et al. (Obesity 23:301–304, 2015) developed the Plate Clearing Tendency Scale (PCTS). However, little is known about the psychometric properties of this scale and its correlates. Methods In the current study, participants (N = 207, 76% female) completed a German translation of the PCTS and other questionnaires online. Results A one-factor structure had good model fit and the PCTS had acceptable internal reliability and good test–retest reliability across an average of four and a half weeks. Higher plate clearing tendencies related to more frequent parental encouragement to clear one’s plate in childhood and to stronger food waste concerns but were unrelated to sex, body weight, self-control, and eating behaviors. However, higher plate clearing tendencies related to higher body weight in unsuccessful dieters. Conclusion The current study shows that the PCTS has sound psychometric properties and that plate clearing tendencies appear to be largely driven by food waste concerns and not by automatic eating habits or low eating-related self-control. In dieters, however, high plate clearing tendencies may contribute to low dieting success and hinder weight loss. Level of evidence No level of evidence, basic science.
... Moreover, previous studies found positive associations between state and trait food craving and consumption of the craved food (Meule & Hormes, 2015). It should be noted, however, that several situational and individual factors influence consumption of a craved food and that food cravings do not always result in subsequent consumption (Hill, 2007). ...
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... The Chocolate version of the Food Cravings Questionnaires, for example, has a Cronbach's alpha of a = 0.85-0.90 (Meule & Hormes, 2015). Hofmann et al. (2016) used the FCQ-T in a sample of children and adolescents and indicated that trait food craving is related to high-calorie food consumption in children with obesity. ...
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... Dietary Fat and Free Sugar Short Questionnaire (DFS) (Fromm and Horstmann, 2019) that obtains data about monthly intake of saturated fat and free sugar within the last year. Moreover, we used the German versions of the Food Craving Questionnaires for food (FCQ) (Meule et al., 2014) and chocolate (FCQ-C) (Meule and Hormes, 2015). Both scales obtain information about experienced food cravings. ...
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... One of the psychological reactions that accompany cephalic phase responses is the experience of food craving [2,4]. Food craving is an intense desire for a specific food [5], which can also be experienced in the absence of hunger [6] According to the conditioning-based incentive sensitization theory, food craving is a state of sensitized incentive salience, i.e. a cue-triggered motivation to consume a food [7]. ...
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Palatable food can trigger appetitive responses, such as salivation and approach tendencies. Though evolutionarily functional, these conditioned responses can encourage overeating and obesity when food is abundant. The current study examines the neural correlates of ‘denovo’ Pavlovian appetitive conditioning, pairing one class of unknown objects (conditioned stimuli, CS) with their sweet taste (unconditioned stimulus, US) during a single trial. To do so, 23 participants consumed unknown (marzipan) objects of one particular color (CS+) while only interacting with control stimuli of different color and shape (CS-). After this single-trial conditioning procedure, participants viewed and rated images of the marzipan figures and the control objects during functional magnetic resonance imaging (fMRI). Relative to the CS-, the CS+ elicited stronger activation in the dorsal striatum, a brain region associated with cue-reward coupling. Furthermore, conditioning effects in subjective ‘craving’, defined as increased palatability and desire to eat, were observed, and these were positively related to conditioning effects in the amygdala, a brain region associated with the need-dependent value of a reward. Thus, the study identified reward-related brain regions involved in single-trial appetitive learning, thereby providing a potential mechanism that contributes to the etiology of food craving. These findings might help to understand clinically relevant food cravings in individuals with eating or weight related concerns and might support the development of extinction based treatments. •Pavlovian appetitive conditioning can occur after a single conditioning session •A single trial of appetitive conditioning was sufficient to increase ‘craving’ •A general conditioning effect was found in the dorsal striatum •The conditioning effect on ‘craving’ was related to amygdala activation •These conditioning effects may contribute to the etiology of food craving
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Virtual Reality (VR) is considered a promising tool for measurement of food choices (e.g., virtual supermarkets) and for interventions regarding eating behavior (e.g., cue exposure therapy). However, it is not yet known whether food cue responses (FCRs) are similar in VR as in real life, which creates uncertainty about the effectiveness of these interventions. Furthermore, the role of hunger in relation to FCRs is still unclear, both in real life and in VR. Therefore, this study explores to what extent exposure to food cues in VR and real life elicit similar psychological (i.e., craving) and physiological (i.e., salivation) FCRs, and whether this differs between hungry and satiated conditions. The study employed a 2 (stimulus type: food vs. non-food) x 2 (exposure mode: VR vs. real life) x 2 (hunger state: hungry vs. satiated) within-subjects design (N = 54). Exposure to food led to stronger cravings than exposure to non-food, both in VR and real life, albeit weaker in VR. Furthermore, exposure to food led to more salivation than exposure to non-food, however in real life only. In sum, craving (but not salivation) responses after exposure to virtual food (vs. non-food) approach real life responses. Craving is an important measure in several fields of therapy, and this study suggests that VR is a potentially useful intervention tool. Additionally, this study provides evidence that VR can be used as a tool when it comes to measuring food-related behavior, as virtual food approximates psychological FCRs in real life.
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Food cravings have been implicated in the development and maintenance of a range of eating- and weight-related pathology. The rapid and accurate assessment of food cravings is thus critical in clinical and research settings. Existing measures of specific food cravings are often not suitable for capturing the multiple facets of the craving experience. A short version of the Food Cravings Questionnaire-Trait (FCQ-T), the most widely used measure of general food cravings, was recently developed in German and shown to be a one-factorial, internally reliable measure. Other recent studies validated an Italian and Spanish version of the FCQ-T-reduced (FCQ-T-r) and successfully replicated its basic psychometrics. This study sought to examine the psychometric properties of the English version of the FCQ-T-r. Undergraduate students (n = 610, 51.0% female, 53.9% white/Caucasian) completed a battery of questionnaires containing the FCQ-T-r and measures of specific food cravings, eating style, eating disorder symptoms, weight dissatisfaction, and impulsivity. Even though results of a confirmatory factor analysis suggested poor fit with a one-factorial model, the FCQ-T-r was found to be a one-factorial measure in both principal component and parallel analysis. The FCQ-T-r demonstrated excellent internal consistency reliability (Cronbach's α = .94), and scores were significantly and positively correlated with measures of specific food cravings, restrained eating, eating disorder symptoms, and impulsivity. More work is needed to confirm the factor structure of the English FCQ-T-r, but preliminary findings suggest that it constitutes a valid and reliable alternative to lengthier measures of general food cravings.
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Background Food craving refers to an intense desire to consume a specific food. The Food Cravings Questionnaires (FCQs) assess food cravings on a trait and a state level. Method The current study examined half-year retest-reliability of the Food Cravings Questionnaire-Trait-reduced (FCQ-T-r) and the Food Cravings Questionnaire-State (FCQ-S) and reports associations with current food deprivation in female students. Results The FCQ-T-r had higher retest-reliability (rtt = .74) than the FCQ-S (rtt = .39). Although trait food craving was correlated with state food craving, it was unaffected by current food deprivation. Conclusions Although state and trait food craving are interdependent, the FCQs are able to differentiate between the two. As scores of the FCQ-T-r represent a stable trait, but are also sensitive to changes in eating behavior, they may be useful for the investigation of the course of eating disorders and obesity.
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Purpose: The aim of the present study was to investigate dimensionality and psychometric properties of the Italian Food Cravings Questionnaire-Trait-reduced (FCQ-T-r) in a sample of obese and overweight patients seeking weight loss treatment. Methods: Participants were 504 (416 women and 88 men) overweight and obese patients (BMI ≥ 25 kg/m(2)), and 289 (215 women and 74 men) Italian adults not currently seeking weight loss treatment. All participants were administered the Food Cravings Questionnaire-Trait (FCQ-T) and the Binge Eating Scale. Results: The fifteen items included in the FCQ-T-r explained 93% of the variance of the 39-item FCQ-T total score (R(2) = 0.93). A principal axis factoring analysis indicated a one-factor solution, explaining 55.6% of the variance of the data. The FCQ-T-r had high internal consistency and was also able to differentiate between individuals with various severities of binge eating behavior. Conclusions: The FCQ-T-r may be considered a useful instrument for measuring trait food craving, when time constraints impede the use of the 39-item FCQ-T.
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Impulsivity and food craving have both been implicated in overeating. Recent results suggest that both processes may interactively predict increased food intake. In the present study, female participants performed a Go/No-go task with pictures of high- and low-calorie foods. They were instructed to press a button in response to the respective target category, but withhold responses to the other category. Target category was switched after every other block, thereby creating blocks in which stimulus-response mapping was the same as in the previous block (non-shift blocks) and blocks in which it was reversed (shift blocks). The Food Cravings Questionnaires and the Barratt Impulsiveness Scale were used to assess trait and state food craving and attentional, motor, and non-planning impulsivity. Participants had slower reaction times and more omission errors (OE) in high-calorie than in low-calorie blocks. Number of commission errors (CE) and OE was higher in shift blocks than in non-shift blocks. Trait impulsivity was positively correlated with CE in shift blocks while trait food craving was positively correlated with CE in high-calorie blocks. Importantly, CE in high-calorie-shift blocks were predicted by an interaction of food craving × impulsivity such that the relationship between food craving and CE was particularly strong at high levels of impulsivity, but vanished at low levels of impulsivity. Thus, impulsive reactions to HC food-cues are particularly pronounced when both trait impulsivity and food craving is high, but low levels of impulsivity can compensate for high levels of trait food craving. Results support models of self-regulation which assume that interactive effects of low top-down control and strong reward sensitive, bottom-up mechanisms may determine eating-related disinhibition, ultimately leading to increased food intake.
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Food cravings refer to an intense desire to eat specific foods. The Food Cravings Questionnaire-Trait (FCQ-T) is the most commonly used instrument to assess food cravings as a multidimensional construct. Its 39 items have an underlying nine-factor structure for both the original English and Spanish version; but subsequent studies yielded fewer factors. As a result, a 15-item version of the FCQ-T with one-factor structure has been proposed (FCQ-T-reduced; see this Research Topic). The current study aimed to explore the factor structure of the Spanish version for both the FCQ-T and FCQ-T-reduced in a sample of 1241 Cuban adults. Results showed a four-factor structure for the FCQ-T, which explained 55% of the variance. Factors were highly correlated. Using the items of the FCQ-T-reduced only showed a one-factor structure, which explained 52% of the variance. Both versions of the FCQ-T were positively correlated with body mass index (BMI), scores on the Food Thoughts Suppression Inventory and weight cycling. In addition, women had higher scores than men and restrained eaters had higher scores than unrestrained eaters. To summarize, results showed that (1) the FCQ-T factor structure was significantly reduced in Cuban adults and (2) the FCQ-T-reduced may represent a good alternative to efficiently assess food craving on a trait level.
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One of the most often used instruments for the assessment of food cravings is the Food Cravings Questionnaire (FCQ), which consists of a trait (FCQ-T; 39 items) and state (FCQ-S; 15 items) version. Scores on the FCQ-T have been found to be positively associated with eating pathology, body mass index (BMI), low dieting success and increases in state food craving during cognitive tasks involving appealing food stimuli. The current studies evaluated reliability and validity of a reduced version of the FCQ-T consisting of 15 items only (FCQ-T-r). Study 1 was a questionnaire study conducted online among students (N = 323). In study 2, female students (N = 70) performed a working memory task involving food and neutral pictures. Study 1 indicated a one-factorial structure and high internal consistency (α = 0.94) of the FCQ-T-r. Scores of the FCQ-T-r were positively correlated with BMI and negatively correlated with dieting success. In study 2, participants reported higher state food craving after the task compared to before. This increase was positively correlated with the FCQ-T-r. Hours since the last meal positively predicted food craving before the task when controlling for FCQ-T-r scores and the interaction of both variables. Contrarily, FCQ-T-r scores positively predicted food craving after the task when controlling for food deprivation and the interaction term. Thus, trait food craving was specifically associated with state food craving triggered by palatable food-cues, but not with state food craving related to plain hunger. Results indicate high reliability of the FCQ-T-r. Replicating studies that used the long version, small-to-medium correlations with BMI and dieting success could be found. Finally, scores on the FCQ-T-r predicted cue-elicited food craving, providing further support of its validity. The FCQ-T-r constitutes a succinct, valid and reliable self-report measure to efficiently assess experiences of food craving as a trait.
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Food cravings are common, more prevalent in the obese, and may differ in those who pursue surgical treatment for obesity. Food craving tools are most often validated in non-clinical, non-obese samples. In this retrospective study, 227 bariatric surgery candidates at a large medical center completed the Food Cravings Questionnaire-Trait (FCQ-T). The aim was to explore the factor structure of the FCQ-T. Principal components analysis with varimax rotation revealed a seven-factor structure that explained 70.89 % of the variance. The seven factors were: (1) preoccupation with food, (2) emotional triggers, (3) environmental cues, (4) loss of control, (5) relief from negative emotions, (6) guilt, and (7) physiological response. The preoccupation with food factor accounted for 49.46 % of the variance in responses. Unlike other populations, food cravings in bariatric surgery candidates appear to be related most to preoccupations with food.
Chapter
Food cravings are discrete phenomena involving a strong desire to consume a specific food that is hard to resist. Food cravings are associated with hunger, but food cravings are only alleviated by consumption of a specific type of food, while hunger can be alleviated by eating any number of foods. Food cravings are common and are associated with food intake and body mass, and neuroimaging studies indicate that exposure to imagined or actual craved foods increases activation in brain regions subserving reward, motivation, and memory. A number of self-report inventories with good psychometric properties are available that measure food cravings, including inventories to measure cravings for specific types of foods, such as chocolate and carbohydrates. Although food cravings were once hypothesized to result from food restriction or nutrient deficiencies, there is little empirical support for this etiological model. For example, food restriction during dieting and weight loss decreases food cravings, and more restrictive diets are associated with larger craving decreases. An alternative etiological model with empirical support involves conditioning, where food cravings result from pairing food intake with stimuli such as hunger, emotional states, or environmental stimuli. Randomized controlled trials are warranted to evaluate the efficacy of interventions to manage food cravings, and further research is needed to evaluate changes in food cravings in response to: (1) short- and long-term restriction of specific foods, with and without energy restriction/weight loss and (2) restriction of specific types of foods during diets that vary in intensity/weight loss. Results from such studies will improve our understanding of the etiology of food cravings and provide information on effective methods to manage food cravings.
Article
We examined the psychometric properties of the Dutch version of the Attitudes to Chocolate Questionnaire (ACQ), comparing the original three-factor model to a later-suggested two-factor model. We evaluated the construct validity of the ACQ by investigating the associations between the resulting factors and other eating-related questionnaires such as the Three Factor Eating Questionnaire and the Food Thought Suppression Inventory. Finally, we compared the scores on several scales regarding eating behavior between different groups (men vs. women, dieters vs. non-dieters and cravers vs. non-cravers). A confirmatory factor analysis of the Dutch ACQ indicated the best global fit indices for the two-factor model, with the resulting factors being “Negative consequences and Guilt” and “Craving and emotional eating”. Both factors were associated with other eating-related dimensions. However, craving seemed to be uniquely associated with the amount of chocolate consumed per week, whereas guilt correlated strongly with restraint. Finally, women scored higher on nearly all scales, but there was no significant gender difference with regard to chocolate consumption. Dieters reported more disinhibition, restraint, food-thought suppression and guilt, but they did not significantly differ from non-dieters with regards to their levels of craving, hunger nor consumption.