Desire Thinking as a Predictor of Problematic Internet Use

Abstract

This study investigated the role of desire thinking in predicting problematic Internet use independently of weekly Internet use, anxiety, depression and craving for Internet use. A sample of 250 Internet users completed the following self-report instruments: Hospital Anxiety and Depression Scale, Internet Use Craving Scale, Desire Thinking Questionnaire, and Internet Addiction Test. The sample was then divided into two sub-groups: problematic Internet users (n=90) and non-problematic Internet users (n=140). Mann-Whitney U tests revealed that all variable scores were significantly higher for problematic Internet users than non-problematic Internet users. A logistic regression analysis indicated that imaginal prefiguration was a predictor of classification as problematic Internet user over and above weekly Internet use, anxiety, depression and craving for Internet use. A hierarchical regression analysis, on the combined sample, indicated that both verbal perseveration and imaginal prefiguration predicted problematic Internet use independently of weekly Internet use, anxiety, depression and craving for Internet use. These results add to the argument that the construct of desire thinking is relevant in understanding of addictive behaviours including problematic Internet use.

Full text

http://ssc.sagepub.com/
Social Science Computer Review
http://ssc.sagepub.com/content/early/2013/11/05/0894439313511318
The online version of this article can be found at:
DOI: 10.1177/0894439313511318
published online 24 November 2013Social Science Computer Review
Marcantonio M. Spada, Gabriele Caselli, Manuel Slaifer, Ana V. Nikcevic and Sandra Sassaroli
Desire Thinking as a Predictor of Problematic Internet Use
Published by:
http://www.sagepublications.com
can be found at:Social Science Computer ReviewAdditional services and information for
http://ssc.sagepub.com/cgi/alertsEmail Alerts:
http://ssc.sagepub.com/subscriptionsSubscriptions:
http://www.sagepub.com/journalsReprints.navReprints:
http://www.sagepub.com/journalsPermissions.navPermissions:
What is This?
- Nov 24, 2013OnlineFirst Version of Record >>
at Università degli studi di Pavia on January 30, 2014ssc.sagepub.comDownloaded from at Università degli studi di Pavia on January 30, 2014ssc.sagepub.comDownloaded from

Article
Desire Thinking as a Predictor
of Problematic Internet Use
Marcantonio M. Spada
1,2
, Gabriele Caselli
3
,
Manuel Slaifer
4
, Ana V. Nikc
ˇevic
´
5
, and
Sandra Sassaroli
3
Abstract
This study investigated the role of desire thinking in predicting problematic Internet use (PIU)
independently of weekly Internet use, anxiety, depression, and craving for Internet use. A sample
of 250 Internet users completed the following self-report instruments: Hospital Anxiety and
Depression Scale, Internet Use Craving Scale, Desire Thinking Questionnaire, and Internet Addic-
tion Test. The sample was then divided into two subgroups: problematic Internet users (n¼90)
and nonproblematic Internet users (n¼140). Mann–Whitney Utests revealed that all variable
scores were significantly higher for problematic Internet users than nonproblematic Internet
users. A logistic regression analysis indicated that imaginal prefiguration was a predictor of classi-
fication as problematic Internet user over and above weekly Internet use, anxiety, depression, and
craving for Internet use. A hierarchical regression analysis, on the combined sample, indicated that
both verbal perseveration and imaginal prefiguration predicted PIU independently of weekly Inter-
netuse,anxiety,depression,andcravingforInternet use. These results add to the argument that
the construct of desire thinking is relevant in understanding of addictive behaviors including PIU.
Keywords
anxiety, depression, craving for Internet use, desire thinking, problematic Internet use, weekly
Internet use
Introduction
Problematic, pathological, or addictive Internet use (e.g., Beard & Wolf, 2001; Spada, in press; Wal-
lace, 1999; Young, 1998a) can be defined as ‘‘use of the Internet that creates psychological, social,
1
Department of Mental Health & Learning Disabilities, Faculty of Health and Social Care, London South Bank University,
London, UK
2
North East London NHS Foundation Trust, London, UK
3
Studi Cognitivi, Milano, Italy
4
Universita di Pavia, Pavia, Italy
5
Kingston University, London, UK
Corresponding Author:
Marcantonio M. Spada, Department of Mental Health & Learning Disabilities, Faculty of Health and Social Care, London South
Bank University, 103 Borough Road, London SE1 0AA, UK.
Email: spadam@lsbu.ac.uk
Social Science Computer Review
201X, Vol XX(X), 1–10
ªThe Author(s) 2013
Reprints and permission:
sagepub.com/journalsPermissions.nav
DOI: 10.1177/0894439313511318
ssc.sagepub.com
at Università degli studi di Pavia on January 30, 2014ssc.sagepub.comDownloaded from

school and/or work difficulties in a person’s life’’ (Beard & Wolf, 2001, p. 378). Research evidence
suggests that problematic Internet use (PIU) affects a large number of people with incidence rates
ranging between 0.7%and 18.3%(Aboujaoude, Koran, Gamel, Large, & Serpe, 2006; Bakken, Wenzel,
Go¨testam, Johansson, & Oren, 2009; Cao & Su, 2007; Ghassemzadeh, Sharraray, & Moradi, 2008;
Kaltiala-Heino, Lintonen & Rimpela, 2004; Kuss, Griffiths, & Binder, 2013; Morahan-Martin &
Schuimacher, 2000; Ni, Yan, Chen, & Liu, 2009; Niemz, Griffiths, & Banyard, 2005; Pallanti, Ber-
nardi, & Quercioli, 2006).
A variety of studies have investigated the relationship between PIU and psychological dysfunction,
revealing that anxiety and depression are common among problematic Internet users (Kim et al., 2006;
Sanders, Field, Diego, & Kaplan, 2000; Spada, Langston, Nikcˇevic´, & Moneta, 2008; Whang, Lee, &
Chang, 2003; Young & Rodgers, 1998). LaRose, Lin, and Easton (2003) have questioned whether
Internet use has become the primary means of relieving dysphoric symptoms and Caplan and High
(2007) have maintained that the motivation to use the Internet for mood regulation is a cognitive
symptom of PIU use in general. Additionally, negative emotions appear to differentiate problematic
from non-PIU with a reduction of negative emotions driving the former and an enhancement of
positive emotions driving the latter (Wan & Chiou, 2006).
Craving has been conceptualized as a powerful subjective experience that motivates individuals
to seek out and achieve a craved target, or practice a craved activity, in order to reach its desired
effects (Marlatt, 1987). Research evidence has demonstrated that the experience of craving is
qualitatively similar across a range of targets, including alcohol, food, soft drinks, tobacco, and
Internet use (e.g., Castellani & Rugle, 1995; Field, Schoenmakers, & Wiers, 2008; May, Andrade,
Panabokke, & Kavanagh, 2004; Moreno, Warren, Rodriguez, Fernandez, & Cepeda-Benito, 2009).
A variety of models for conceptualizing craving have been put forward over the last half century.
Conditioning models share in common the conceptualization of craving as an epiphenomenon of
addictive conditioning processes (e.g., Ludwig & Wikler, 1974; Siegel, 1983; Stewart, Dewit, &
Eikelboom, 1984) while cognitive models purport that higher order cognitive functioning and
information processing are central in the activation and escalation of craving (Tiffany, 1999).
More recently, in the elaborated intrusion theory of desire (Kavanagh, Andrade, & May, 2005;
Kavanagh, May, & Andrade, 2009; May et al., 2004), it has been suggested that the duration,
frequency, and intensity of craving, as a primarily affective and subjective response, may be the result
of the activation of a process of cognitive elaboration termed ‘‘desire thinking’’ (Green, Rogers, &
Elliman, 2000; Kavanagh et al., 2009). Desire thinking can be characterized as a voluntary cognitive
process involving the elaboration of a desired target at a verbal (repetitive self-talk regarding the need
to achieve the desired target and self-motivated statements; Caselli & Spada, 2010) and imaginal
(construction of mental images of the desired target or of its context of consumption; Kavanagh
et al., 2009) level. This thinking style has also been described as a preference or as a reaction to
preference awareness (Zajonc, 1980). The target of desire thinking may be an activity, an object, or
a state (Kavanagh et al., 2009). Desire thinking also appears to be a transdiagnostic process, with sub-
jective reports indicating that this experience is qualitatively similar across a range of targets, including
alcohol, food, soft drinks, and tobacco (Caselli, Ferla, Mezzaluna, Rovetto, & Spada, 2012; Caselli,
Nikcˇevic´, Fiore, Mezzaluna, & Spada, 2012; Caselli & Spada, 2010, 2011; May et al., 2004).
Desire thinking differs from craving because it is conceptualized as a perseverative, conscious,
and intentional process while craving is an automatic, motivational experience (Caselli & Spada,
2011). Desire thinking also differs from other perseverative thinking styles such as rumination and
worry because it is focused on the elaboration of a desired target and is characterized by positive
target-related experience and self-motivational statements (Caselli & Spada, 2011). Recent research
has shown that desire thinking is positively associated with, but distinct from, craving (Caselli &
Spada, 2011; May et al., 2004) and that its activation may induce a direct increase in levels of
craving (Caselli, Soliani, & Spada, 2013).
2Social Science Computer Review XX(X)
at Università degli studi di Pavia on January 30, 2014ssc.sagepub.comDownloaded from

The aim of the present study was to determine whether desire thinking could predict PIU inde-
pendently of weekly Internet use, anxiety, depression, and craving for Internet use. We proceeded
first by examining the independent contribution of desire thinking toward category membership as
a problematic Internet user, and second by investigating the independent contribution of desire
thinking as a predictor of PIU in a combined sample of problematic and nonproblematic users.
Method
Participants
The total sample consisted of 250 Internet users (103 female) recruited from the general popula-
tion. For purposes of inclusion in this study, participants were required to (1) use the Internet (for
at least 1 hr per week); (2) be 18 years of age or above; (3) consent to participate in the study; and
(4) understand spoken and written Italian. The mean age of the sample was 28.6 years (SD ¼9.4;
range ¼18–59). The average weekly Internet use was 13.7 hr (SD ¼12.0; range ¼2–70). The
average duration of Internet use was 8.6 years (SD ¼4.1; range ¼1–22). The majority of the
sample (98.0%) was Caucasian.
Participants were also divided into two subgroups: problematic Internet users and nonproble-
matic Internet users. The criterion for inclusion in the subgroups was the determined by the score
attained on the Internet Addiction Test (IAT; Widyanto & McMurran, 2004). Participants who
scored 40 or above were classified as problematic Internet users (Young, 1998b).
Ninety-six participants (38 females; MAge ¼24.3; SD ¼5.8) reported PIU (IAT 40:
M¼47.7; SD ¼7.3) and average weekly Internet use of 18.3 hr (SD ¼11.3 hr). One-hundred
and fifty-four participants (65 females; MAge ¼31.6; SD ¼10.2) reported non-PIU (IAT<40;
M¼29.1; SD ¼5.9) and average weekly Internet use of 10.8 hr (SD ¼11.7).
Self-Report Instruments
Hospital Anxiety and Depression Scale (HADS). The HADS (Zigmond & Snaith, 1983) consists of
14 items, 7 assessing anxiety and 7 assessing depression. Higher scores represent higher levels of
anxiety and depression. Overall, the scale possesses good validity and reliability (Herrmann,
1997; Mykletun, Stordal, & Dahl, 2001; Zigmond & Snaith, 1983) and has been widely used in both
clinical and nonclinical research samples (e.g., Alati et al., 2004; Wagena, van Amelsvoort, Kant, &
Wouters, 2005). The Cronbach’s afor the current study was .83 for anxiety and .81 for depression.
The Internet Use Craving Scale (IUCS). The IUCS is a modified version of the Penn Alcohol Craving
Scale (PACS; Flannery, Volpicelli, & Pettinati, 1999). The PACS includes 5 self-report items that
measure the duration, frequency, and intensity of craving. Each question is scaled from 0 to 6. In the
Internet use version adopted in the current study, the 5 self-report item structure was maintained, but
items were rephrased so as to refer to Internet use. For example, Item 1 of PACS was phrased as
‘‘How often have you thought about using the Internet or how good using the Internet would make
you feel?’’ Higher scores represent higher levels of craving for Internet use. The Cronbach’s afor the
current study was .78.
Desire Thinking Questionnaire (DTQ). The DTQ (Caselli & Spada, 2011) consists of two factors of
5 items each. The first factor concerns the perseveration of verbal thoughts about desire-related
content and experience (verbal perseveration) and includes items such as ‘‘I mentally repeat to
myself that I need to practice the desired activity.’’ The second factor concerns the tendency to
prefigure images about desire-related content and experience (imaginal prefiguration) and includes
items such as ‘‘I imagine myself doing the desired activity.’’ Items are general in content and refer to
Spada et al. 3
at Università degli studi di Pavia on January 30, 2014ssc.sagepub.comDownloaded from

the desired activity that may be specified in the instructions. Higher scores represent higher levels of
desire thinking. The DTQ total score and factor scores have shown good factor structure, internal
consistency, test–retest reliability, predictive and discriminative validity (Caselli & Spada, 2011). The
Cronbach’s afor the current study was .86 for verbal perseveration and .83 for imaginal prefiguration.
The IAT. The IAT (Young, 1998b) consists of 20 items assessing the degree of PIU. Examples of
items include ‘‘How often do you choose to spend more time on-line over going out with others?’’;
‘‘How often do you lose sleep due to late-night log-ins?’’ Higher scores represent higher levels of
PIU. The scale has been found to possess good psychometric properties (Widyanto & McMurran,
2004). For the purposes of the current study, a single-factor model was used (Faraci, Craparo,
Messina, & Severino, 2013). The Cronbach’s afor the current study was .87.
Procedure
Ethics approval for the study was obtained from an Italian university ethics board. Participants were
recruited from e-mail contacts in a viral-like fashion, starting from the University of Pavia (Italy)
mailing list. Participants who received the e-mail request to visit the study website were also asked
to forward the address to individuals in their e-mail contacts and ask those individuals to do the
same.
The first page of the study website explained the purpose of the study: ‘‘To investigate the
relationship between weekly Internet use, mood, craving and desire thinking.’’ Participants were
then directed, if consenting to participate in the study, to a second page containing basic demographic
questions and the self-report instruments. Once both were completed, participants were again informed
that, should they consent to participate in the study, they should click on the ‘‘Submit’’ button. Once
participants had clicked on Submit, their data were forwarded to a generic postmaster account. This
ensured that participants’ responses were anonymous. All participants were then debriefed. If on click-
ing Submit, participants had omitted to respond to any items a window would appear informing them
of this. Their data would not be e-mailed until all items were responded to. This ensured that only
completed data were used for the analysis. A second submission from the same IP address was not
allowed so as to avoid multiple submissions from the same participant.
Results
Data Configuration
An inspection of histograms, skewness, and kurtosis showed that PIU, the dependent variable, was
normally distributed and that several predictor variables were not normally distributed. We cal-
culated the distance of Mahalanobis (D
2
) which identified 10 participants as multivariate outliers
who were eliminated from further analyses to ensure a linear relationship between variables. The
coefficient of Mardia and an inspection of graphical distribution of D
2
on Q–Q plots indicated a mul-
tivariate normal distribution. We then examined multicollinearity using the tolerance index (T
i
) and
the variance inflation factor (VIF). The range for the T
i
(from 0.41 to 0.74) and for the VIF (from 1.3
to 2.3) support the absence of multicollinearity between variables. An inspection of residual Q–Q
plots, skewness, and kurtosis support the homoscedasticity of variables. The Durbin–Watson statis-
tic supports the absence of autocorrelation (d¼1.67; Durbin & Watson, 1951). Correlation analyses
for the total sample, without outliers, showed that all predictors were significantly correlated with
PIU with correlation coefficients ranging from .43 to .73. Descriptive statistics for both the proble-
matic and the nonproblematic Internet users subgroups, without outliers, are presented in Table 1.
Mann–Whitney tests indicated that on all variables problematic Internet users scored higher than
nonproblematic Internet users.
4Social Science Computer Review XX(X)
at Università degli studi di Pavia on January 30, 2014ssc.sagepub.comDownloaded from

Binary Logistic Regression Analysis
Next, we analyzed the data using binary logistic regression analysis which is used to find the odds
of being in one category or another. In the current study, the category was problematic Internet
usersornonproblematicInternetusers.Thisisrepresented by the exponential of the coefficient
(Exp B) which indicates the change in the dependent variable, given a one-unit change in the pre-
dictor variable. The grouping variable was taken to be PIU caseness. Weekly Internet use, anxiety,
depression, and craving for Internet use were entered in Block 1, while the desire thinking factors
were entered in Block 2. Weekly Internet use, anxiety, craving for Internet use, and imaginal
prefiguration were found to be significant predictors of PIU caseness (see Table 2). The overall
statistics for the final equation were as follows: w
2
¼133.78, df ¼6, p< .0005, with 85%of cases
correctly classified.
Hierarchical Regression Analysis on the Combined Sample
To evaluate whether desire thinking predicted PIU independently of weekly Internet use, anxiety,
depression, and craving for Internet use, a hierarchical regression analysis was run on the total
sample (see Table 3). Weekly Internet use, anxiety, depression, and craving for Internet use were
entered on Step 1, and desire thinking factors were entered on Step 2. Both verbal perseveration and
imaginal prefiguration were found to account for a significant 7.9%(p< .0005) in variance over and
above all other predictors. A closer inspection of the final equation in the analysis reveals that all
predictors, with exception of anxiety and depression, were significant.
Table 2. Summary Statistics for the Logistic Regression Equation Predicting Categorization as a Problematic
Internet User.
BSEWald df Sig. Exp(B)
1. Weekly Internet Use in hours 0.04 0.02 4.41 1 0.04 1.04
2. Hospital Anxiety and Depression Scale—Anxiety 0.16 0.07 5.30 1 0.02 1.20
3. Hospital Anxiety and Depression Scale—Depression 0.03 0.08 0.18 1 0.67 0.97
4. Internet Use Craving Scale 0.25 0.05 21.42 1 0.005 1.28
5. Desire Thinking Questionnaire—Verbal Perseveration 0.07 0.14 0.27 1 0.60 0.93
6. Desire Thinking Questionnaire—Imaginal Prefiguration 0.57 0.15 12.93 1 0.005 1.77
7. Constant 6.80 0.97 49.49 1 0.005 0.001
Note:n¼240.
Table 1. Means and Standard Deviation (in Brackets) of Study Variables.
Problematic Internet
Users (n¼90)
Nonproblematic Internet
Users (n¼150)
1. Weekly Internet use in hours 24.0 (5.3)
a
9.8 (9.5)
2. Hospital Anxiety and Depression Scale—Anxiety 6.7 (3.9)
a
3.5 (3.2)
3. Hospital Anxiety and Depression Scale—Depression 4.3 (3.1)
a
2.6 (2.9)
4. Internet Use Craving Scale 11.1 (4.2)
a
4.8 (4.1)
5. Desire Thinking Questionnaire—Verbal Perseveration 7.8 (2.4)
a
5.9 (1.4)
6. Desire Thinking Questionnaire—Imaginal Prefiguration 7.5 (2.1)
a
5.6 (1.1)
7. Internet addiction test 46.9 (5.9)
a
28.9 (5.8)
a
Pairs significantly different from each other (p.05) on the basis on Mann-Whitney tests.
Spada et al. 5
at Università degli studi di Pavia on January 30, 2014ssc.sagepub.comDownloaded from

Discussion
The goal of this study was to explore the role of desire thinking in PIU. Our findings showed that,
controlling for weekly Internet use, anxiety, depression, and craving for Internet use, imaginal
prefiguration predicted category membership as a problematic Internet user and both verbal perse-
veration and imaginal prefiguration predicted PIU.
These results provide support for the conceptualization of desire thinking as an independent
construct in predicting PIU. The combination of repetitive self-talk regarding the need to use the
Internet (verbal perseveration) and the active construction of mental images of Internet use (imagi-
nal prefiguration) may be reinforcing, in the short term, as they help to manage craving and negative
affect by temporarily shifting attention away from these experiences and onto the elaboration of the
desired target (Caselli & Spada, 2010, 2011). In the medium to longer term, however, engagement
in desire thinking would bring to an escalation of craving and negative affect, as the desired target
(Internet use) is perseveratively elaborated upon but not achieved. This, in turn, would lead to
the desired target being perceived as the only, and increasingly urgent, route to attain relief from
escalating distress.
The clinical implications of these findings are that desire thinking may be conceptualized,
assessed, and treated in order to reduce the risk of PIU. In terms of assessment, it may be helpful
to gather information not only in relation to negative affect and the experience of craving for Internet
use but also to desire thinking. With respect to interventions, the development of techniques that
promote a direct change in desire thinking may be helpful to reduce the risk of uncontrolled Internet
use; for instance, interventions aimed at increasing the level of flexible control over attention. These
may include attention training and detached mindfulness, as well as questioning beliefs about the
benefits of desire thinking and its uncontrollability (Caselli & Spada, in press).
This study has several limitations that will have to be addressed in future research. First, it relies
solely on self-report data that are subject to errors in measurement. Second, a cross-sectional design
was adopted which precludes causal inferences. Third, the presence of concurrent psychological
Table 3. Hierarchical Multiple Linear Regression Statistics with PIU as the Outcome Variable and Weekly
Internet Use, Anxiety, Depression, and Craving for Internet Use as Predictor Variables.
bTp
Step 1
1. Weekly Internet Use in hours .08 1.72 .09
2. Hospital Anxiety and Depression Scale—Anxiety .06 0.87 .39
3. Hospital Anxiety and Depression Scale—Depression .11 1.84 .07
4. Internet Use Craving Scale .63 11.72 .005
r
2
¼.55
Fchange ¼73.27
Step 2
1. Weekly Internet Use in hours .12 2.60 .01
2. Hospital Anxiety and Depression Scale—Anxiety .02 0.40 .70
3. Hospital Anxiety and Depression Scale—Depression .08 1.34 .18
4. Internet Use Craving Scale .46 8.42 .005
5. Desire Thinking Questionnaire—Verbal Perseveration .15 2.34 .02
6. Desire Thinking Questionnaire—Imaginal Prefiguration .22 3.64 .005
r
2
¼.63
Fchange ¼25.00
Note. PIU ¼problematic Internet use.
Note.n¼240.
6Social Science Computer Review XX(X)
at Università degli studi di Pavia on January 30, 2014ssc.sagepub.comDownloaded from

disorder was not assessed; however, controlling for anxiety and depression should provide a degree
of confidence in the specificity of the results. Fourth, the variance explained by desire thinking was
relatively small in view of the reasonably sized sample. Fifth, demand characteristics may have
affected outcomes. Finally, previous treatment may have exposed individuals to the identification
and the exploration of cognitive constructs, nevertheless desire thinking is a relatively new construct
and standard treatment for PIU does not include its examination.
Directions for future research include ascertaining further the role of desire thinking in predis-
position toward, and maintenance of, PIU, as well as considering the influence of PIU on desire
thinking. It would also be interesting to examine whether changes in desire thinking occur during
the treatment for PIU, and if so, if they are associated with relapse in longitudinal studies. Finally,
future research should explore, through experimental designs, the effect of desire thinking induc-
tion on the craving experience for Internet use and perception of control over own behavior.
In conclusion, desire thinking may be a risk factor for PIU. If future research confirms this, then
cognitive–behavioral therapy interventions for treating PIU may benefit from targeting specifically
desire thinking.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publica-
tion of this article.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
References
Aboujaoude, E., Koran, L., Gamel, N., Large, M. D., & Serpe, R. T. (2006). Potential markers for problematic
internet use: A telephone survey of 2,513 adults. CNS Spectrums,11, 750–755.
Alati,R.,Kinner,S.,Najman,J.M.,Fowler,G.,Watt, K., & Green, D. (2004). Gender differences in the
relationship between alcohol, tobacco and mental health in patients attending an emergency department.
Alcohol and Alcoholism,39, 464–469.
Bakken, I. J., Wenzel, H. G., Go¨ testam, K. G., Johansson, A., & Oren, A. (2009). Internet addiction among
Norwegian adults: A stratified probability sample study. Scandinavian Journal of Psychology,50, 121–127.
Beard, K. W., & Wolf, E. M. (2001). Modification in the proposed diagnostic criteria for Internet addiction.
CyberPsychology & Behavior,4, 377–383.
Cao, F., & Su, L. (2007). Internet addiction among Chinese adolescents: Prevalence and psychological features.
Child: Care, Health and Development,33, 275–281.
Caplan, S. E., & High, A. C. (2007). Beyond excessive use: The interaction between cognitive and behavioral
symptoms of problematic Internet use. Communication Research Reports,23, 265–271.
Caselli, G., Ferla, M., Mezzaluna, C., Rovetto, F., & Spada, M. M. (2012). Desire thinking across the continuum
of drinking behaviour. European Addiction Research,18, 64–69.
Caselli, G., Nikcˇevic´, A. V., Fiore, F., Mezzaluna, C., & Spada, M. M. (2012). Desire thinking across the
continuum of nicotine dependence. Addiction Research & Theory,20,382–388.
Caselli, G., Soliani, M., & Spada, M. M. (2013). The effect of desire thinking on craving: An experimental
investigation. Psychology of Addictive Behaviors,27, 301–306.
Caselli, G., & Spada, M. M. (2010). Metacognitions in desire thinking: A preliminary investigation. Behavioural
and Cognitive Psychotherapy,38, 629–637.
Caselli, G., & Spada, M. M. (2011). The Desire Thinking Questionnaire: Development and psychometric
properties. Addictive Behaviors,36, 1061–1067.
Caselli, G., & Spada, M. M. (2013). The metacognitions about desire thinking questionnaire: Development and
psychometric properties. Journal of Clinical Psychology,69, 1284–1298.
Spada et al. 7
at Università degli studi di Pavia on January 30, 2014ssc.sagepub.comDownloaded from

Castellani, B., & Rugle, L. (1995). A comparison of pathological gamblers to alcoholics and cocaine misusers
on impulsivity, sensation seeking and craving. International Journal of Addiction,30, 275–289.
Durbin, J., & Watson, G. S. (1951). Testing for serial correlation in least squares regression. Biometrika,37,
409–428.
Faraci, P., Craparo, G., Messina, R., & Severino, S. (2013). Internet Addiction Test (IAT): Which is the best
factorial solution. Journal of Medical Internet Research,15, e225.
Field, M., Schoenmakers, T., & Wiers, R. W. (2008). Cognitive processes in alcohol binges: A review and
research agenda. Current Drug Abuse Reviews,1, 263–279.
Flannery, B. A., Volpicelli, J. R., & Pettinati, H. M. (1999). Psychometric properties of the Penn alcohol craving
scale. Alcoholism: Clinical and Experimental Research,23, 1289–1295.
Ghassemzadeh, L., Shahraray, M., & Moradi, A. (2008). Prevalence of internet addiction and comparison
of internet addicts and non-addicts in Iranian high schools. CyberPsychology & Behavior,11, 731–733.
Green, M., Rogers, P., & Elliman, N. (2000). Dietary restraint and addictive behaviour: The generalisability of
Tyffany’s cue reactivity model. International Journal of Eating Disorder,27, 419–427.
Herrmann, C. (1997). International experiences with the hospital anxiety and depression scale: A review of
validation data and clinical results. Journal of Psychosomatic Research,42,17–41.
Kaltiala-Heino, R., Lintonen, T., & Rimpela, A. (2004). Internet addiction? Potentially problematic use of the
Internet in a population of 12-18 year-old adolescents. Addiction Research & Theory,12, 89–96.
Kavanagh, D. J., Andrade, J., & May, J. (2005). Imaginary relish and exquisite torture: The elaborated intrusion
theory of desire. Psychological Review,112, 446–467.
Kavanagh, D. J., May, J., & Andrade, J. (2009). Tests of the elaborated intrusion theory of craving and desire:
Feature of alcohol craving during treatment for an alcohol disorder. British Journal of Clinical Psychology,
48, 241–254.
Kim, K., Ryu, E., Chon, M., Yeun, E., Choi, S., Seo, J., & Nam, B. (2006). Internet addiction in Korean
adolescents and its relation to depression and suicidal ideation: A questionnaire survey. International
Journal of Nursing Studies,43, 185–192.
Kuss, D. J., Griffiths, M. D., & Binder, J. F. (2013). Internet addiction in students: Prevalence and risk factors.
Computers in Human Behaviour,29, 959–966.
Larose, R., Lin, C. A., & Easton, M. S. (2003). Unregulated Internet usage: Addiction, habit, or deficient
self-regulation? Media Psychology,5,225–253.
Ludwig, A. M., & Wikler, A. (1974). ‘‘Craving’’ and relapse to drink. Quarterly Journal of Studies on Alcoholism,
35, 108–130.
Marlatt, G. (1987). Craving notes. British Journal of Addiction,82, 42–43.
May, J., Andrade, J., Panabokke, N., & Kavanagh, D. (2004). Images of desire: Cognitive models of craving.
Memory,12, 447–461.
Morahan-Martin, J., & Schumacher, P. (2000). Incidence and correlates of pathological Internet use among
college students. Computers in Human Behavior,16,13–29.
Moreno, S., Warren, C. S., Rodriguez, S., Fernandez, M. C., & Cepeda-Benito, A. (2009). Food cravings
discriminate between anorexia and bulimia nervosa. Implications for ‘‘success’’ versus ‘‘failure’’ in dietary
restriction. Appetite 52, 588–594.
Mykletun, A., Stordal, E., & Dahl, A. A. (2001). Hospital anxiety and depression scale: Factor structure, item
analyses and internal consistency. British Journal of Psychiatry,179, 540–544.
Ni,X.L.,Yan,H.,Chen,S.L.,&Liu,Z.W.(2009).Factors influencing Internet addiction in a sample of
freshmen university students in China. CyberPsychology & Behavior,12,327–330.
Niemz, K., Griffiths, M., & Banyard, P. (2005). Prevalence of pathological Internet use among university
students and correlations with self-Esteem, the General Health Questionnaire (GHQ), and disinhibition.
CyberPsychology & Behavior,8,562–570.
Pallanti, S., Bernardi, S., & Quercioli, L. (2006). The Shorter PROMIS Questionnaire and the Internet addiction
8Social Science Computer Review XX(X)
at Università degli studi di Pavia on January 30, 2014ssc.sagepub.comDownloaded from

scale in the assessment of multiple addictions in a high-school population: Prevalence and related disability.
CNS Spectrums,11, 966–974.
Sanders, C. E., Field, T. M., Diego, M., & Kaplan, M. (2000). The relationship of Internet use to depression and
social isolation among adolescents. Adolescence,35, 237–242.
Siegel, S. (1983). Classical conditioning, drug tolerance, and drug dependence. In R. G. Smart, F. B. Glasser, Y.
Israel, H. Kalant, R. E. Popham, & W. Schmidt (Eds.). Research advances in alcohol and drug problems
(Vol. 7, pp. 207–246). New York, NY: Plenum.
Spada, M. M. (2013). An overview of problematic Internet use. Addictive Behaviors. Advance online
publication. doi: 10.1016/j.addbeh.2013.09.007
Spada, M. M., Langston, B., Nikcˇevic´, A. V., & Moneta, G. B. (2008). The role of metacognitions in problematic
internet use. Computers in Human Behavior,24, 2325–2335.
Stewart, J., Dewit, H., & Eikelboom, R. (1984). Role of unconditioned and conditioned drug effects in the
self-administration of opiates and stimulants. Psychological Review,91, 251–268.
Tiffany, S. (1999). Cognitive concepts of craving. Alcohol Research & Health,23, 215–224.
Wagena, E., van Amelsvoort, L. G. P. M., Kant, I., & Wouters, E. F. M. (2005). Chronic bronchitis, cigarette
smoking and the subsequent onset of depression and anxiety: results from a prospective population-based
cohort study. Psychosomatic Medicine,67, 656–660.
Wallace, P. M. (1999). The psychology of the internet. New York, NY: Cambridge University Press.
Wan, C. S., & Chiou, W. B. (2006). Psychological motives and online games addiction: A test of flow theory
and humanistic needs theory for Taiwanese adolescents. CyberPsychology & Behavior,9, 317–324.
Whang, L. S., Lee, S., & Chang, G. (2003). Internet over-users’ psychological profiles: A behavior sampling
analysis on Internet addiction. CyberPsychology & Behavior,6, 143–150.
Widyanto, L., & McMurran, M. (2004). The psychometric properties of the Internet addiction test.
CyberPsychology & Behavior,7,443–450.
Young, K. S. (1998a). Internet addiction: The emergence of a new clinical disorder. CyberPsychology &
Behavior,1,237–244.
Young, K. S. (1998b). Caught in the net. New York, NY: John Wiley.
Young, K. S., & Rogers, R. C. (1998). The relationship between depression and Internet addiction.
CyberPsychology & Behavior,1,25–28.
Zajonc, R. B. (1980). Feeling and thinking: Preferences need no inferences. American Psychologist,35,
151–175.
Zigmond, A. S., & Snaith, R. P. (1983). The hospital anxiety and depression scale. Acta Psychiatrica Scan-
dinavica,67,361–370.
Author Biographies
Marcantonio M. Spada, PhD, is Professor of Psychological Therapies at London South Bank University in
partnership with North East London NHS foundation Trust, UK. He is one of the leading researchers on the
application of metacognition to psychological disorders and has published over 50 journal articles in the area.
E-mail: spadam@lsbu.ac.uk.
Gabriele Caselli, PhD, is a lecturer in Psychology at the University of Pavia, Italy, and Researcher and
Teaching Fellow at the Cognitive Psychotherapy School and Research Institute ‘‘Studi Cognitivi’’ in Milan,
Italy. His clinical, teaching, and research efforts have been primarily focused on understanding and treating
addiction with particular attention paid to developing metacognitive conceptualizations of craving. E-mail:
g.caselli@studicognitivi.net.
Manuel Slaifer, MSc, is a psychologist working as a teaching assistant at the University of Pavia, Italy. E-mail:
manuel.slaifer01@ateneopv.it.
Spada et al. 9
at Università degli studi di Pavia on January 30, 2014ssc.sagepub.comDownloaded from

Ana V. Nikc
ˇevic
´,PhD, is a senior lecturer in Psychology at Kingston University, UK. She is an active researcher
in the area of metacognition as applied to addictive behaviors with a particular expertise in tobacco use problems.
E-mail: A.Nikcevic@kingston.ac.uk.
Sandra Sassaroli, MD, is Director of Studies for postgraduate training in cognitive behavior therapy at the
Cognitive Psychotherapy School and Research Institute Studi Cognitivi in Milan, Italy. She is a senior teaching
member of the Italian Society of Cognitive-Behavioural Therapy (SITCC) and has authored several journal
articles on cognitive psychopathology and therapy. E-mail: s.sassaroli@studicognitivi.net.
10 Social Science Computer Review XX(X)
at Università degli studi di Pavia on January 30, 2014ssc.sagepub.comDownloaded from