Behavioural Addictions in Adolescents and Young
Adults: Results from a Prevalence Study
Corrado Villella•Giovanni Martinotti•Marco Di Nicola•
Maria Cassano•Giuseppe La Torre•Maria Daniela Gliubizzi•
Immacolata Messeri•Filippo Petruccelli•Pietro Bria•
Luigi Janiri•Gianluigi Conte
? Springer Science+Business Media, LLC 2010
lescent population, evaluating the effects of gender and age, and to assess the correlations
among different behavioural addictions. 2853 high school students were assessed in order
to evaluate the prevalence of behavioural addictions such as Pathological Gambling (PG),
Compulsive Buying (CB), Exercise Addiction (EA), Internet Addiction (IA), and Work
Addiction (WA), in a population of Italian adolescents. The South Oaks Gambling Screen-
Revised Adolescent (SOGS-RA), the Compulsive Buying Scale (CBS), the Exercise
Addiction Inventory (EAI), the Internet Addiction Test (IAT), and the Work Addiction
Risk Test (WART), were compiled anonymously by the students. Overall prevalence was
7.0% for PG, 11.3% for CB, 1.2% for IA, 7.6% for WA, 8.5% for EA. PG and EA were
more common among boys, while gender had no effect on the other conditions. CB was
more common among younger (\18 years old) students. The scores of all of these scales
were significantly correlated. The strong correlation among different addictive behaviours
is in line with the hypothesis of a common psychopathological dimension underlying these
phenomena. Further studies are needed to assess personality traits and other clinical dis-
orders associated with these problems behaviours.
Our study aims to assess the prevalence of behavioural addictions in an ado-
C. Villella (&) ? G. Martinotti ? M. Di Nicola ? P. Bria ? L. Janiri ? G. Conte
Institute of Psychiatry and Psychology, Universita ` Cattolica del Sacro Cuore, Largo Francesco Vito 1,
00168 Rome, Italy
Local Health Unit, Drug Addiction Service, via Alcide De Gasperi 20, 70051 Barletta, Italy
G. La Torre
Sapienza University of Rome, Clinical Medicine and Public Health Unit, viale Regina Elena 324,
00161 Rome, Italy
M. D. Gliubizzi
Institute of Hygiene, Universita ` Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168 Rome, Italy
I. Messeri ? F. Petruccelli
Department of Human and Social Sciences, University of Cassino, via Mazzaroppi 11, 03043 Cassino,
J Gambl Stud
Pathological Gambling ? Prevalence
Adolescence ? Behavioural addictions ? Epidemiology ?
Behavioural addictions are clinical entities—not classified in the DSM-IV-TR—, in which
repetitive impulsive behaviours occur, with negative effects on the patients’ and their
relatives’ lives; according to Brown’s (1993) paradigm the prominent features of such
conditions are: cognitive salience, as the activity dominates the person’s thoughts and
behaviours; conflict with other persons or activities; euphoria or relief, a feeling of short
term pleasure from engaging in the behaviour; tolerance or loss of control over the
behaviour; withdrawal, as experiencing unpleasant feelings when unable to engage in the
behaviour; relapse and reinstatement, indicated when people unsuccessfully attempt to cut
down on the behaviour, subsequently engaging in similar or higher levels than previously.
Pathological Gambling could be considered as an example of this behavioural addic-
tions (Petry 2006; Potenza 2006); it is the only condition of these to be classified in the
DSM-IV-TR, as an Impulse Control Disorder (American Psychiatric Association 2000). In
the fifth edition of this Manual, Pathological Gambling will be probably re-classified,
together with most of the Substance Related Disorders, in the Section Addiction and
Related Disorders, and other addiction-like behavioural disorders could be considered for
inclusion if sufficient data accumulate (American Psychiatric Association 2010). This
reflects a shift in attention from substance-induced physical dependence to other elements
of the addiction process.
The core elements of addictions are: craving state prior to behavioural engagement, or a
compulsive engagement; impaired control over behavioural engagement and continued
behavioural engagement despite adverse consequences (Potenza 2006); Behavioural
addictions may share clinical features with substance addictions, and similar phases seem
to occur for behavioural and substance addictions, with physiological and emotional
arousal before the act; pleasure, high, or gratification associated with the act; a decrease in
arousal and feelings of guilt afterward, and the possible development of tolerance and
physiological withdrawal (Hollander and Allen 2006). The reward circuits are implicated
in the development of both substance and behavioural addictions, and common genetic
vulnerabilities have been described (Grant et al. 2006), and common neuropsychological
features have been reported across these diagnostic categories (Goudriaan et al. 2006).
The definition of behavioural addictions remains however somewhat controversial, as
clinical associations have been described between these phenomena and mood disorders
(Kim et al. 2006; Di Nicola et al. 2010), obsessive–compulsive disorder (Dell’Osso et al.
2006), but the strongest associations remain those with substance use disorders (Petry et al.
Data from adult population have demonstrated the co-occurrence of different impulse
control disorders in pathological gamblers (Black and Moyer 1998), and in adult psychi-
atric inpatients (Grant et al. 2005), a correlation between different behavioural addictions
in patient suffering from bipolar disorder (Di Nicola et al. 2010), and an association
between exercise dependence and compulsive buying (Koran et al. 2006; Lejoyeux et al.
2007, 2008). Surveys in populations of college students have indicated correlations
between the use of multiple legal substances and gambling, exercising, and the usage of the
internet and television (Greenberg et al. 1999).
J Gambl Stud
Pathological Gambling has been the most studied of these conditions, but the others
may be of clinical relevance as well: Koran et al. (2006) found a point prevalence of 5.8%
for Compulsive Buying in the adult population of the U.S. with compulsive buyers being
younger and having lower incomes than non-compulsive buyers; compulsive buying is
associated with mood disorders, especially major depression, and with a family history of
depression, alcoholism and substance use disorders, and both compulsive buyers and their
relatives are at risk for other psychiatric conditions (Black et al. 1998). Magee (1994),
Hassay and Smith (1996), and Roberts (1998) in their early works demonstrated impaired
control in the buying behaviours in these subjects, compared with non-compulsive buyers.
Most research has focused on adult population or on college students so far, but little is
known about epidemiology of these behavioural addictions in adolescence. Adolescence is
a period at great risk for the development of addictive behaviours: nearly 60% of indi-
viduals who initiate drug use and 80% of those who start drinking alcohol (Johnston et al.
2005) or smoking cigarettes (Department of Health and Human Services 1994) do so at or
before 18 years of age, and problem and Pathological Gambling are highly prevalent in
adolescent populations (Shaffer et al. 1999). This susceptibility depends on both neuro-
biological (Schepis et al. 2008) and psychological processes (Marcelli and Braconnier
2004) taking place in this age of life.
Epidemiological studies on this field indicate that the prevalence of problem and
Pathological Gambling in adolescents is reported to be higher than in adults, maybe for
some interaction of adolescence and the current social setting. Approximately 4–8% of
adolescents have a serious gambling problem, and 10–14% may be at risk for developing
problems (Shaffer et al. 1999; Jacobs 2000).
Other epidemiological studies were conducted in Italy about behavioural addictions in
adolescence: Pallanti et al. (2006) enrolled 275 Students in Florence who were adminis-
tered the Shorter PROMIS Questionnaire, Internet Addiction Scale, and the Sheehan
Disability Scale. Di Martino et al. (2006), conducted an epidemiological survey on a larger
sample, but this study had a strong limitation as the authors did not use the scales that are
most commonly used to assess the presence of behavioural addictions, so their results are
not easily comparable with others.
In order to ameliorate the previous studies we planned to involve all of the schools in an
average Italian city, aiming to obtain a representative sample of Italian adolescent popu-
lation, enrolling a large number of students, and we selected assessment scales which had
already been used by previous studies.
An accurate prevalence estimate would help indicate the impact of these conditions on
public mental health and develop adequate prevention and treatment strategies.
Our study aims to assess the prevalence of behavioural addictions in an adolescent
population—selecting the conditions which had been most commonly described and those
which could be screened for with reliable and valid self-report questionnaires—evaluating
the effects of gender and age, and to assess the correlations among different behavioural
addictions in order to test the hypothesis which proposes a common psychopathological
dimension underlying these phenomena.
The behavioural addictions considered in this study were:
Pathological Gambling (PG), classified in the DSM-IV TR as an impulse control
disorder and defined as a persistent and recurrent maladaptive gambling behaviour as
indicated by at least five criteria, and not better accounted for by a manic episode (APA
J Gambl Stud
Compulsive Buying (CB), defined by the presence of repetitive impulsive and excessive
buying episodes leading to personal and familiar distress. Mc Elroy et al. (1994)
proposed diagnostic criteria for compulsive buying such as: Maladaptive preoccupations
with buying or shopping, or maladaptive buying or shopping impulses or behaviour, as
indicated by at least one of the following: Frequent preoccupation with buying or
impulses to buy that are experienced as irresistible, intrusive and/or senseless; frequent
buying of more that can be afforded, frequent buying of items that are not needed, or
shopping for longer periods of time than intended: the buying preoccupations, impulses
or behaviours cause marked distress, are time-consuming, significantly interfere with
social or occupational functioning, or result in financial problems (e.g. indebtedness or
bankruptcy); the excessive buying or shopping behaviour does not occur exclusively
during periods of hypomania or mania;
Exercise Addiction (EA), an inadequate pattern of exercise leading to clinically
significant impairment or distress, as manifested by three or more of the following: (1)
tolerance, which is defined as either a need for significantly increased amounts of
exercise to achieve the desired effect or a diminished effect with continued use of the
same amount of exercise; (2) withdrawal as manifested by anxiety and fatigue when the
amount of exercise decreases; (3) exercise is often taken in larger amounts or aver a
longer period than it was intended; (4) loss of control of the sportive or physical activity;
(5) excessive time spent in activities necessary to obtain or prepare exercise; (6)
conflicts: social, occupational or recreational activities are given up because of exercise;
and (7) continuance: exercise is continued despite knowledge of a physical problem
caused by exercise (Hausenblas and Giacobbi 2004);
Internet Addiction (IA), characterized by excessive or poorly controlled preoccupations,
urges or behaviours regarding computer use and internet access that lead to impairment
or distress. Its features are: excessive use, often associated with a loss of sense of time or
a neglect of basic drives; withdrawal, including feelings of anger, tension and/or
depression when the computer is inaccessible; tolerance, including the need for better
computer equipment, more software, or more hours of use; negative repercussions,
including arguments, lying, poor achievement, social isolation and fatigue (Beard and
Wolf 2001; Block 2008; Shaw and Black 2008);
Work Addiction (WA), defined by Robinson as an obsessive–compulsive disorder which
manifests itself through self-imposed demands, an inability to regulate work habits, and
an overindulgence in work to the exclusion of most other life activities. It is associated
with an impairment in familiar relationships, and difficulties for spouse and children of
workaholics (Robinson 2001; Bakker et al. 2009).
2853 students were evaluated during an information program about behavioural depen-
dencies held in the upper intermediate schools in Barletta, a town with around 100,000
inhabitants in Southern Italy.
All the upper intermediate schools in town were invited to take part. All the
schools joined the project except one, which was under renovation at the time of
J Gambl Stud
The program was designed by the Institute of Psychiatry of the Catholic University of
Rome together with the Addictive Disorders Service of the Local Health Unit. The study
protocol complied fully with the guidelines of the Ethics Committee of the Catholic
University of Rome, and was approved by the Institutional Review Boards in accordance
with local requirements. It was conducted in accordance with Good Clinical Practice
guidelines and the Declaration of Helsinki (World Medical Association 2009). The stu-
dents were informed about the aims of the study, their participation was voluntary and free.
The questionnaires were anonymous and they were administered at school, in the presence
of the teachers.
Pathological Gambling was evaluated with the South Oaks Gambling Screen-Revised
Adolescent (SOGS-RA), a screening tool for problem gambling in Adolescence (Winters
et al. 1993a, b, 1995), derived from the South Oaks Gambling Screen (SOGS) (Lesieur and
Blume 1987); Compulsive buying was evaluated with the Compulsive Buying Scale (CBS)
(Faber and O’Guinn 1992), Exercise Addiction with the Exercise Addiction Inventory
(EAI) (Terry et al. 2004; Griffiths et al. 2005), Work Addiction with the Work Addiction
Risk Test (WART) (Robinson 1989), Internet Addiction with the Interned Addiction Test
(IAT) (Young 1996, 1998).
All of these scales were self-administered by the students. The scales used are shortly
South Oaks Gambling Screen-Revised Adolescent
It is a 19-item questionnaire derived from the South Oaks Gambling Screen (Lesieur and
Blume 1987). It varies from the original SOGS by a decrease of one in the number of the
scoring items, minor changes in some response options and minor changes in the wording
of some items. It has an internal reliability of 0.80. Poulin (2002) produced further evi-
dence of its reliability and validity. Following indications from Ladouceur et al. (2000), in
the present study a cut-off score of 5 or higher was chosen to identify probable pathological
Compulsive Buying Scale
It contains 13 items derived from previous research and theoretical models of compulsive
buying. Subjects are asked to rate how true each item was for them on a scale ranging from
1 (not at all) to 7 (very much). The scale has a negative cut-off score of -1.34, identifying
compulsive buyers. Faber and O’Guinn (1992) found the scale to be highly reliable
(alpha = 0.95), one dimensional, and valid, and has been previously used in several studies
in adults and college students (Koran et al. 2006; Roberts 1998).
Internet Addiction Test
It is a 20-item questionnaire on which respondents are asked to rate each item on a five-
point Likert scale, according to how Internet use affects their daily routine, social life,
productivity, sleeping patterns and feelings. Young suggests that a score of 70 or more
J Gambl Stud
means that the internet use is causing significant problems. Widyanto and McMurran
(2004) supported the reliability and validity of this test.
Work Addiction Risk Test
is scored on a 4-point Likert scale. Scores C 70 identify work-addict individuals (Robinson
Robinson 1996; Robinson 1999; Robinson and Post 1994; Robinson et al. 1992).
Exercise Addiction Inventory
It consists of six statements based on a modified version of the components of behavioural
addiction (Griffiths 1996). Each statement had a five point Likert response option coded so
that high scores reflected attributes of addictive exercise behaviour. A cut-off score of 24
or more identifies individuals considered at risk for exercise addiction. The scale has been
demonstrated to have construct and content validity, and it has an internal reliability of
0.84 and a test-retest reliability of 0.85 (Terry et al. 2004; Griffiths et al. 2005).
Statistical analysis was conduced with by SPSS 12.0 for Windows.
We computed the total prevalence of behavioural dependences on the basis of cut-off
value defined by literature, and prevalence by gender and by age group (\18 and
Data were non-normally distributed; univariate analyses were made using Mann–
Whitney’s test, in order to assess the effect of gender on the scores of the specific scales.
ANOVA F test was used to evaluate multiple linear regression analyses, which were
conducted considering the scores from the different scales as dependent variables, age and
gender as independent variables.
A multiple logistic regression model was used considering age and gender as inde-
pendent variables and the occurrence of a behavioural addiction, as revealed by the self-
report measures, as dependent variables. Results are expressed as Odds Ratio (95%
Spearman’s correlation coefficient was used to assess correlations among the different
The statistical significance was set at P\0.05.
Of the 3249 students attending the schools involved, 2853 (87.8%) decided to take part in
The population was made of 1142 girls (40%) and 1711 boys (60%). The age range was
13–20; the mean age was 16.7, with a standard deviation of 1.9.
Prevalence rates are shown in Table 1. Compulsive Buying is the most prevalent dis-
order (11.3%), followed by Exercise Addiction (8.5%), Work Addiction (7.6%), Patho-
logical Gambling (7.0%), and Internet Addiction (1.2%).
J Gambl Stud
Males had higher scores than females on the SOGS-RA, with no effect for age on this
variable (ANOVA F test = 59.95, P\0.001).
Gender had no effect on the CBS scores, while age is correlated in a positively pro-
portional way with CBS scores (F test = 11.32, P\0.001), indicating a lower risk for
Compulsive Buying among older students.
For Internet Addiction, the F test scored 19.84 (P\0.001), with a higher risk for males
compared to females, and no effect of age on the IAT scores.
No correlation was found for WART scores with gender nor age (F test = 0.35,
P = 0.704).
EAI scores are higher among males, with no effect of age (F test = 46.14, P\0.001).
Males have a higher risk for developing Pathological Gambling, and exercise addiction.
Gender has no effect on the other variables. Younger students (less than 18 years old) are
at higher risk for Compulsive Buying, while age has no effect on other behaviours.
As shown in Table 2, the scores of all scales are positively correlated, except for the
Compulsive Buying Scale, which is negatively correlated to all the other scales; all of these
correlations show a high statistical significance, with P values\0.001.
In line with previous studies, both in the U.S. and in Italy (Shaffer et al. 1999; Di Martino
et al. 2006; Pallanti et al. 2006) our results indicate that behavioural addictions are quite
common among adolescents.
The scores of all of the scales are positively correlated among each other, except CBS
scores which show a negative correlation with the scores from all the other scales. By the
Table 1 Prevalence (%)
Males 9.712.7 1.37.810.1
Total 7.011.31.2 7.68.5
Bold values were used for p values\0.05, indicating statistical significance
Table 2 Correlation analysis (Spearman’s correlation coefficient)
IAT 0.252*-0.226*– 0.245* 0.208*
WART 0.215*-0.268*0.245*– 0.255*
Ex Dep0.218*-0.142*0.208* 0.255*–
J Gambl Stud
way, lower scores in the CBS indicate a more problematic buying behaviour, so the
negative correlation between the scores of the scales reflects a positive correlation between
compulsive buying and other behavioural addictions. These correlations suggest the
presence of a common psychopathological dimension underlying different problematic
addictive behaviours. This is in line with previous research from Black and Moyer (1998),
Greenberg et al. (1999), Grant et al. (2005), and Di Nicola et al. (2010). As supposed for
alcohol use (Brown et al. 2008), adolescent problem behaviour may both reflect an
underlying disposition toward under controlled behaviour and alter the course of adoles-
cent behaviour in a way that increases the likelihood of untoward outcomes. Behavioural
dependences are correlated with social disability (Pallanti et al. 2006) and they may
sometimes reflect, as for Internet Addiction, a difficulty in social interactions (Allison et al.
In previous studies Lejoyeux et al. (2008) found an association between compulsive
buying and exercise dependence, while Lejoyeux et al. (2007) found no correlation
between compulsive buying, mobile phone use and time spent on the internet. Both studies
were conduced on adult population and involved smaller samples of subjects, so they may
lack potency to discover a less apparent correlation.
Our study has some limitations as well: the tests used are screening instruments, as the
SOGS-RA, which may overestimate the prevalence rates of Pathological Gambling (La-
douceur et al. 2000; Derevensky et al. 2003), but still it is the most commonly used in
Furthermore, the SOGS-RA is the only scale among those we used to be specifically
students (Roberts 1998), the EAI (Terry et al. 2004; Griffiths et al. 2005) and the IAT
(Widyanto and McMurran 2004) have been validated on University students, but the use of
the WART may not be appropriate in adolescent populations. We could not assess the
concurrentassociation withsubstance-relatedorotherpsychiatricdisorder,norwe coulduse
were delivered during school hours, in order to involve a majority of the students.
Further insight in the psychopathology of these conditions is needed in order to draw
general implications for treatment; each case needs an accurate evaluation as behavioural
addictions can be associated with other severe conditions (Petry et al. 2005; Black and
Moyer 1998; Bamber et al. 2000).
At-risk behaviours as gambling, shopping, physical exercise, are often considered as a
legitimate form of entertainment and tend to be socially approved or tolerated; but
sometimes they can lead to behavioural addictions, which are often under-recognized, by
both therapists and patients: Adolescents may be less likely to perceive a gambling
problem, with an apparent discrepancy between self perception and objective reports of
problem gambling behaviours (Cronce et al. 2007). In spite of this, behavioural addictions
should become a main public health issue: The NESARC study found a high comorbidity
between Pathological Gambling and substance use, mood, anxiety, and personality dis-
orders, in the adult population of the United States (Petry et al. 2005).
Behavioural addictions can be very dangerous in adolescence, as they could lead to
many negative outcomes in adulthood: Early adolescent onset gambling, for instance,
compared to adult onset gambling, is associated with higher ASI gambling, psychiatric and
medical scores (Burge et al. 2004) and with increased severity of psychiatric, family/social
and substance abuse problems, with cognitive problems, suicidal ideation, a history of
impatient psychiatric treatment, and less satisfaction with actual living situation (Burge
et al. 2006).
J Gambl Stud
Most of the data available focus only on Pathological Gambling, and come from ret-
rospective studies; prospective studies should be designed in order to better evaluate the
health and social consequences of behavioural addictions emerging in adolescence.
Little is known about the disruptive effects of other behavioural addictions, but some
concerns can be raised: in the study by Koran et al. (2006), compulsive buyers had lower
incomes than other respondents, and compulsive buying among college students is asso-
ciated to irrational credit card use (Roberts 1998), and it can directly lead to financial
problems and legal entanglements (Black 2007).
Some of these phenomena, as excessive internet use, have appeared only in the last
years; these new media are becoming increasingly common in the Italian adolescent
population (Istituto Nazionale di Statistica 2008), with 82% of Italian youth aged 14–17
using the internet. Long-term consequences of their excessive use could become a main
social issue in the next decades: Hakala et al. (2006) demonstrated that excessive computer
use is a risk factor for orthopaedic problems in adolescence, while Messerlian et al. (2004)
has underlined the dangers deriving from the easy accessibility of on-line gambling
websites for underage youth; our data indicating a common vulnerability for problematic
internet use and gambling support their concernments. Exercise addiction can lead to
inadequate patterns of physical activity, which can in turn cause musculoskeletal (Frisch
et al. 2009) and cardiovascular (Delise et al. 2005) harms.
Accordingly, behavioural addictions must be viewed as a community/social issue, and
research on their epidemiology and psychopathology is strongly needed, in order to
develop effective preventive efforts, with an adolescent target, ranging from denormal-
ization, to harm reduction strategies (Messerlian et al. 2005), remembering how, in
accordance with Blaszczynski and Nower’s hypothesis, a pathway could lead adolescents
who experience gambling activities through classical and operant conditioning and
habituation to the development of Pathological Gambling (Blaszczynski and Nower 2002).
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