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Prog Health Sci 2012, Vol 2 , No1 Test Mobile Phone Addiction
33
Mobile-phone addiction in adolescence: The Test of Mobile Phone
Dependence (TMD)
Chóliz M.
Department of Basic Psychology University of Valencia Avda Blasco Ibáñez, Spain
ABSTRACT
__________________________________________________________________________________________
Introduction: The mobile phone is among the
technological tools with the greatest presence in the
market. During a period of scarcely 10 years, it has
gone from being almost non-existent to being the
device most used (and desired) by adolescents. Its
physical characteristics as well as the psychological
processes involved in its use explain both the
fascination it elicits and the abuse or dependence it
can come to provoke or encourage in adolescents.
This study entailed the development and evaluation
of a questionnaire designed to evaluate dependence
on the mobile phone.
Materials and methods: The items included in this
instrument were developed based on criteria
contained in the Diagnostic and Statistical Manual
for Mental Disorders-Fourth Edition-Text Revision
(DSM-IV-TR; American Psychiatric Association,
2000) for dependence disorder. The questionnaires
were administered to a total of 2,486 adolescents
aged 12–18 years of age, and factor analyses were
then performed.
Results: The questionnaire is characterised by good
psychometric properties as well as by the ability to
discriminate between sexes and among age groups
in an adolescent sample. The factors comprising
this instrument are congruent with the concept of
dependence as defined in the DSM-IV-TR. The
process by which this questionnaire was developed
is described, and the final version of the
questionnaire is presented.
Conclusion: The Test of Mobile Phone
Dependence (TMP) is a questionnaire built taking
into account the dependence criteria of DSM-IV-
TR. The process by which this questionnaire was
developed is described, and the final version of the
questionnaire is presented.
Key words: Addiction; mobile dependence; mobile
phone; questionnaire; adolescence; sex differences.
__________________________________________________________________________________________
Corersponding author:
Department of Basic Psychology
University of Valencia
Avda Blasco Ibáñez, 21
46010-Valencia, Spain
Tel. 0034 96 3864853
Fax. 0034 96 3864822
E-mail: Mariano.Choliz@uv.es (Mariano Chóliz)
Received: 22.04.2012
Accepted: 20.06.2012
Progress in Health Sciences
Vol. 2(1) 2012 pp 33-44.
© Medical University of Bialystok, Poland
Prog Health Sci 2012, Vol 2 , No1 Test Mobile Phone Addiction
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INTRODUCTION
The mobile phone is among the most
prominent kinds of information and
communications technology (ICT) and is probably
also the one that has shown the most spectacular
development during the past few years with regard
to technological innovations, social impact, and
general use by the majority of the population.
One of the groups in which the increase in
mobile-phone use has been the most significant is
adolescents, not only because virtually all
adolescents have one of these devices but also
because the mobile phone acquires much greater
relevance in adolescence than it does in other
developmental stages (namely youth, adulthood, or
older age). The mobile phone has many attributes
and characteristics that make it especially attractive
to adolescents and that encourage its use among
members of this group. Indeed, possession and use
of a mobile phone by adolescents has several
functions [1]:
a) Reinforces personal autonomy, especially with
regard to parents [2]
b) Provides identity and prestige in the context of
relationships with peers [3], a purpose that is
quite evident in the newest or most
fashionable models [4]
c) Offers major technological innovations, tools
for which adolescents demonstrate a special
inclination and skill
d) Serves as a source of fun and entertainment
e) Supports the establishment and maintenance
of interpersonal relationships [5] via
technological resources, such as those that
track “missed calls”, which have a clear social
and affective function [6].
The fascination that the mobile phone
elicits from adolescents, together with its
usefulness, means that it becomes a true object of
desire for many in this age group. However, despite
the fact that it is an extraordinarily useful tool and
facilitates the performance of numerous social and
personal functions, uncontrolled, inappropriate, or
excessive use of mobile phones can give rise to
problems in interactions with parents and in other
areas. Excessive use of mobile phones, as
evidenced by cost and number of calls or messages
sent, interferes with other activities in daily life,
alters the rules for interpersonal relationships, and
can even affect the user’s health or well-being, for
example by having it on continually, even at night.
These behaviours may be understood as reflective
of abuse in the sense used by the Diagnostic and
Statistical Manual for Mental Disorders-Fourth
Edition-Text Revision [7] (DSM-IV-TR; American
Psychiatric Association, 2000) in its definition of
substance abuse.
One question that must be addressed
concerns the term addiction itself, which does not
exist as a diagnostic category in classifications of
mental disorders. Both the DSM-IV-TR and the
International Classification of Diseases-Tenth
Edition [8] (ICD-10; World Health Organization,
1992) include disorders that are commonly
understood as addictive in either the section on
substance dependence (drug addictions) or that on
impulse control disorders (pathological gambling).
Other types of addiction are not included in any
other sections. A scientific debate about the
classification of pathological gambling as an
addictive disorder in the new Diagnostic and
Statistical Manual-Fifth Edition (DSM-V) is now
occurring [9, 10], although many people have
defended the position that pathological gambling is
an addictive behaviour with characteristics similar
to those of the drug addictions for quite some time
[11]. The main types of technological addictions
[12] currently being considered for inclusion in
DSM-V are those involving videogames, the
Internet, and mobile phones, all of which are main
tools used by adolescents for communication or
entertainment.
Recently, research on addiction to the
Internet and videogames has increased
considerably. This increase has included studies of
the addictions themselves [13 - 16], their
comorbidity with other psychological disorders [17,
18], and the development of psychometric
instruments for their evaluation [19, 20, 21.
However, research on the use and abuse of mobile
phones remains limited. Studies on appropriate
psychometric instruments are also scarce. Of the
extant measures, the Mobile Phone Dependence
Questionnaire (MPDQ) [22], the Scale of Problem
Mobile Phone Use [23], and the Scale of Self-
perception of Text-message Dependence [24] are
particularly prominent.
Several studies examining the pattern of
mobile-phone use in adolescents have reported
significant relationships between several of the
main parameters of mobile-phone use and problems
derived from the abuse of mobile phones; they have
also reported indicators of mobile-phone
dependence in terms of DSM-IV-TR criteria [25].
The following symptoms constitute several
of the most characteristic criteria of dependence:
a) Excessive use, manifested in both a high
economic cost and in numerous calls and
messages.
b) Problems, especially with parents, associated
with excessive use of mobile phones
c) Interference with other school or personal
activities
d) A gradual increase in use to obtain the same
level of satisfaction as well as the need to
replace functioning devices with new models
e) The need to call or send messages when time
has elapsed without using the mobile phone
Prog Health Sci 2012, Vol 2 , No1 Test Mobile Phone Addiction
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and emotional alterations when the use of the
phone is impeded.
The results obtained in this exploratory
study demonstrate the need for a questionnaire with
the appropriate psychometric requirements that can
be used to evaluate mobile-phone dependence
according to the DSM-IV-TR criteria for
dependence.
The main objective of this study was to
develop a questionnaire to evaluate mobile-phone
dependence in adolescents based on the DSM-IV-
TR criteria for dependence and similar to the
approaches used to evaluate other behavioural
addictions such as addiction to gambling (NORC
DSM-IV Screen for Gambling Problems) [26] or to
the Internet [20].
MATERIALS AND METHODS
Participants
The sample consisted of 2,833 adolescents
between 12 and 18 years of age. The research
project was financed by the Educational
Administration, and the participation of students
was approved by the appropriate committee.
Several high schools were randomly selected and
invited to participate in the study. The study was
conducted at 16 schools and high schools. Surveys
were given to all the classes at each degree with the
exception of one school, in which participating
classes were randomly selected due to the large
number of students. The research consisted of three
phases. An initial pilot study was conducted with a
sample of 542 students. The results of this study
were used to develop the penultimate instrument,
which consisted of 46 items, a reduction from the
101 contained in the initial version.
The main study, conducted among 1,944
adolescents (51.4% girls and 48.6% boys), resulted
in the development of the final questionnaire.
A third study was conducted with 347
adolescents (51.6% girls and 48.2% boys) to
evaluate the construct validity of the questionnaire
by correlating it with the Mobile Phone
Dependence Questionnaire (MPDQ) [22].
Procedure
Data were collected via surveys
simultaneously completed by students in their
classrooms. Researchers and previously trained
teachers provided a series of instructions about how
to respond to the questions. They also emphasised
the need for honesty when filling out the survey and
guaranteed the confidentiality of the responses.
Instruments
All students completed surveys consisting
of various sections, the most prominent of which
focussed on the following:
a. Sociodemographic and academic
characteristics, such as sex, age, current grade in
school, grades repeated, number of brothers and
sisters and weekly allowance received.
b. Basic parameters of mobile-phone use,
including number of calls, messages, and missed
calls per day; average amount of time spent using
mobile phones per day (messages and calls);
monthly cost of mobile-phone use; ways of
financing this cost; form of payment (prepaid card
or contract); hours of the day and place of greatest
use and availability of the phone.
c. Test of Mobile-phone Dependence (TMD).
These items were constructed according to the
criteria contained in DSM-IV-TR for dependence
disorder. The initial 101-item questionnaire was
reduced to 46 items after the pilot study. The first
18 items were answered on a Likert-type scale
ranging from 0 (never) to 4 (frequently). The 28
remaining items asked respondents to use a Likert-
type scale ranging from 0 (completely disagree) to
4 (completely agree) to respond to a set of
statements. Six inverse items were included to
control for the acquiescence effect.
Statistical analysis
All the data were analysed using the SPSS
15 statistical program for Windows. Various
reliability analyses and an exploratory factor
analysis were performed. Principal-components
analysis was used to extract the factors, and promax
rotation with Kaiser normalisation and a value of 4
for kappa was applied [27]. Basic and central-
tendency descriptive statistics (Pearson bivariate
correlations, t-tests, analyses of variance
(ANOVAs), post hoc tests (Student–Newman–
Keuls, S-N-K), and minimum significant
differences (MSD)) were also calculated.
RESULTS
The main objective of this study is to
develop a questionnaire for the diagnosis of mobile
addiction. The more significant results are the
following Factor Structure of the Questionnaire
The final questionnaire consisted of 22
items and had high internal consistency
(Cronbach’s alpha = .94). The corrected
homogeneity index for each of the items was
greater than .5; that is, the correlation between each
of the items and the rest of the scale was equal to or
greater than .5, indicating that all of the items
measure the same construct, namely dependence on
the mobile phone.
Factor analysis was used to analyse the
structure of the questionnaire, principal-
components analysis was used to extract the factors,
and promax normalisation with a kappa value of 4
Prog Health Sci 2012, Vol 2 , No1 Test Mobile Phone Addiction
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was used to perform the rotation. This rotation
technique was used because it is assumed that the
factors were correlated with one another, as the
dimensions that constitute the construct (mobile-
phone dependence) are not independent of one
another. The Bartlett sphericity contrast (χ2 (231) =
10,257,452; P < .001) allowed rejection of the null
hypothesis that the variables used in the analysis
were not correlated in the population of the sample.
This allows consider the correlation matrix suitable
for factorisation. Furthermore, the Kaiser–Meyer–
Olkin measure of sample adequacy (KMO = .95)
also indicated that the correlation matrix was
adequate for the analysis. Three factors were
extracted from the factor analysis. The first factor
explained 42.69% of the variance and was
composed of items 8, 11, 13, 14, 15, 16, 20, 21, and
22 of the final questionnaire
Table 1. Rotated factor matrix.
Based on the content of these items, the
first factor was called abstinence, as it refers both to
the discomfort felt when unable to use mobile
phones and to the use of these phones to alleviate
psychological problems. The second factor
explained 10.38% of the variance. It was composed
of six items (1, 2, 3, 4, 7, and 10) that refer to the
difficulty of stopping mobile-phone use despite
efforts to do so and to related problems. The second
factor was labelled lack of control and problems
derived from use. Finally, the third factor explained
5.64% of the variance and was composed of items
5, 6, 9, 12, 17, 18, and 19, which refer to increasing
use and interference with other important activities.
This factor was labelled tolerance and interference
with other activities. Table 1 shows the rotated
factor matrix. Items with saturation levels lower
than .30 were excluded from the factors.
Items
Component
I
Abstinence
II
Lack Control/Problems
III
Tolerance/Interference
Item1
-.011
.902
-.046
Item2
.079
.701
-.013
Item3
-.040
.928
-.074
Item4
.215
.430
.248
Item5
-.029
.066
.772
Item6
.192
.205
.422
Item7
-.064
.686
.224
Item8
.522
.056
.054
Item9
.340
.046
.387
Item13
.831
-.033
-.083
Item14
.747
-.018
.011
Item15
.941
-.061
-.180
Item10
-.060
.993
-.101
Item11
.666
.049
.113
Item12
-.070
-.035
.844
Item16
.787
.045
-.143
Item17
-.113
-.144
.995
Item18
.256
-.021
.511
Item19
-.028
.060
.733
Item20
.763
-.036
.018
Item21
.595
-.012
.123
Item22
.577
-.040
.235
Prog Health Sci 2012, Vol 2 , No1 Test Mobile Phone Addiction
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The structural matrix, or factor structure,
were extracted, which reflects the correlation of
each item with the oblique factor. This includes
both the direct effects of the factor on the item (as
in the oblique pattern) and the indirect effects of
other factors through their correlations with a given
factor (see Table 1). Both the factor structure and
the structural matrix (see Tables 1 and 2) show that
item 9 had saturations in both the first and third
factors and was correlated with both factors.
Table 2. Structural matrix.
However, because the factor loading and
the correlation were stronger for the third factor,
item 9 were included in the third factor. It is worth
mentioning that the same results were obtained with
the Kaiser oblimin rotation method, with a value of
equal to 0, which is the case when factors are
more oblique.
Items
Component
I
Abstinence
II
Lack Control/Problems
III
Tolerance/Interference
Item1
.390
.869
.493
Item2
.405
.731
.461
Item3
.355
.864
.461
Item4
.579
.683
.646
Item5
.496
.519
.794
Item6
.559
.551
.668
Item7
.406
.791
.598
Item8
.583
.338
.421
Item9
.609
.442
.632
Item10
.348
.903
.460
Item11
.762
.436
.569
Item12
.452
.442
.778
Item13
.763
.313
.429
Item14
.746
.345
.478
Item15
.797
.279
.385
Item16
.717
.334
.387
Item17
.454
.404
.836
Item18
.573
.410
.662
Item19
.469
.489
.751
Item20
.758
.340
.485
Item21
.667
.346
.496
Item22
.708
.377
.579
Table 3 shows the correlations among the three
factors extracted from the questionnaire.
Table 3. Correlations among factors.
This Table shows that these three factors
are indeed related in a direct and statistically
significant way.
Factor I
Abstinence
Factor II
Lack Control/Problems
Factor III
Tolerance/Interference
Factor I
Abstinence
1
-
-
Factor II
Lack Control/Problems
.450**
1
-
Factor III
Tolerance/Interference
.676**
.557**
1
** The correlation is significant at the level of .01 (two tailed).
Prog Health Sci 2012, Vol 2 , No1 Test Mobile Phone Addiction
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Results according to sex and age
With regard to the sex and age of the
participants in the study, girls had a higher degree
of dependence on mobile phones than did boys (see
Table 4). Likewise, girls had higher scores than
boys on each of the factors of the questionnaire.
That is, compared with their male counterparts,
adolescent girls had higher levels of tolerance and
experienced more interference with other activities,
were more likely to use mobile phones to avoid
uncomfortable mood states, were more likely to feel
Table 4. Differences according to sex.
bad if they could not use mobile phones, and had
greater economic and family problems as a result of
the cost associated with mobile phones. These
results are congruent with those for several of the
main parameters of mobile-phone use and show
that adolescent girls rely more heavily on mobile
phones (send more SMSs and spend more time and
money) than do boys. Furthermore, they also have
more problems with their parents due to their use of
the mobile phone.
Boys
Girls
F
p
Factor I
Abstinence
8.78
13.11
-9.49
.001
Factor II
Lack Control/Problems
4
6.28
-8.61
.001
Factor III
Tolerance/Interference
9.78
12.85
-7.86
.001
Global
19.22
27.65
-9.27
.001
The data also revealed differences among
the mean scores of the three age groups (12–14, 15–
16, and 17–18) (see Table 5). However, according
to post hoc tests (S-N-K and MSD), only the
differences between those 12–14 years of age and
those 15–16 or 17–18 years of age were statistically
significant; no statistically significant differences
on the TMD or on factors I and II were found
between participants 15–16 and those 17–18 years
of age.
Table 5. Differences according to age.
Statistically significant differences were
found among the scores obtained by three age
groups on factor III. In general, scores on the
questionnaire increased as age increased, especially
among those 15 or older. These results are
internally consistent in that participants 15–16 years
of age also had the most favourable attitudes
towards mobile phones and devoted more time and
resources to using these devices. They also reported
more problems with parents due to excessive use.
12-14 years
15-16 year
17-18 years
F
P
Factor I
Abstinence
Factor I
10.61
11.88
10.65
4.21
.015
Factor II
Lack Control/Problems
Factor II
4.62
5.75
5.19
7.80
.001
Factor III
Tolerance/Interference
Factor III
9.72
12.32
13.18
30.63
.001
Global
Global
21.08
25.89
25.04
11.87
.001
Prog Health Sci 2012, Vol 2 , No1 Test Mobile Phone Addiction
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Furthermore, the interaction between age
and sex had no effect on the mean scores obtained
on the questionnaire (F2,1633 = .64, p = n.s.) or on
any of its factors (factor I: F2,1337 = .025, p = n.s.;
factor II: F2,1630 = 2.20, p = n.s.; and factor III:
F2,1346 = 2.30; p = n.s.). The corresponding scales
were further developed based on these results (see
Appendix 2).
Table 6 shows the associations between
the TMD and each of its factors with several basic
parameters of mobile-phone use, especially those
referring to how much this device is used to
communicate. The results show a direct and
statistically significant relationship among degree
of dependence; lack of impulse control; use of
mobile phones to avoid unpleasant mood states;
problems derived from use of mobile phones; abuse
of mobile phones; number of daily calls, messages,
missed calls or “beeps”; and amount of time per
day devoted to calls and messages.
Table 6. Correlations between the TMD and patterns of mobile-phone use.
Calls
daily
Messages
daily
Missed
calls
Time
daily
Factor I
Abstinence
Factor I
.244**
.344**
.335**
.378**
Factor II
Lack Control/Problems
Factor II
.265**
.251**
.283**
.360**
Factor III
Tolerance/Interference
Factor III
.317**
.438**
.458**
.467**
Global
Global
.259**
.247**
.298**
.388**
** The correlation is significant at the level of .01 (two tailed).
Finally, Table 7 shows the correlations
between the TMD and the MPDQ (Toda et al.,
2006) in terms of global scores and scores on each
of the three factors of the TMD. In all cases, the
correlations were high and statistically significant.
The last variable (subjective dependence) was
analysed based on values per item ranging from 0
to 10.
Table 7. Correlations between TMD and MPDQ.
Factor I
Abstinence
Factor II
Lack
Control/
Problems
Factor III
Tolerance/
Interference
Global
MPDQ
Subjective
dependence
Factor I Abstinence
1
-
-
-
-
-
Factor II
Lack Control/Problems
.569**
1
-
-
-
-
Factor III
Tolerance/Interference
.768**
.601**
1
-
-
-
Global
.932**
.765**
.909**
1
-
-
MPDQ
.824**
.575**
.800**
.857**
1
-
Subjective dependence
.620**
.422**
.636**
.654**
.670**
1
** The correlation is significant at the level of .01 (two tailed).
Prog Health Sci 2012, Vol 2 , No1 Test Mobile Phone Addiction
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DISCUSSION
Roman law used the term “addiction” to
refer to submission to an owner or lord; that is, it
referred to a relationship of dependence and a
limitation on personal freedom. This is one of the
most important characteristics of any addictive
process, regardless of whether it involves drugs or
the latest non-toxic activities. The technological
addictions [12] represent the most recent type of
addiction not involving. Despite the obvious fact
that the individual consequences of technological
addictions are not as serious as those associated
with drug dependence, these addictions should not
be viewed as less important.
Technological addictions in general and
mobile-phone dependence in particular are
especially important for several reasons. Firstly,
despite the fact that the technologies involved are
extremely useful and necessary (even beneficial)
for our society, they are also characterised by
factors that render them susceptible to abuse,
leading to addiction. Secondly, unlike the case with
other addictions, especially drugs, no social
consensus exists with regard to the risk for abuse
presented by these technologies. Thirdly, the
population that is most susceptible to abusing or
depending on these technologies consists of
adolescents. Teenagers are not only more
vulnerable to addiction processes because of
cortical development [28] but they are also more
likely to find the technologies under examination to
be fascinating and to develop skills for their use
that is superior to those of adults [1]. This special
vulnerability to addiction, together with the
accessibility of these technologies and their
excessive use, render the adolescent population
especially susceptible to this type of “modern-day”
addiction.
A recent study [25] showed that a segment
of the adolescent population used the mobile phone
excessively. Some of these individuals showed
clear signs of abuse, and some met the main DSM-
IV criteria for dependence. Thus, it was considered
important and even necessary to develop a
psychometric instrument that would evaluate
mobile-phone dependence in adolescents,
especially given that this problem is increasing.
A 101-item questionnaire that reflected the
seven criteria for dependence contained in the
DSM-IV-TR was developed. An initial pilot study
with 542 students enabled to reduce the initial
instrument to 46 items, and this measure was
completed by 1,944 adolescents between the ages
of 12 and 18 years.
The final instrument was composed of 22
items and had good psychometric indicators. The
factor structure of the questionnaire included three
factors
that represented the main characteristics of
dependence according to the DSM-IV-TR; this
justified the usefulness of the TMD as a diagnostic
instrument and as a support in the treatment of
mobile-phone addiction. This instrument measures
the main dependence criteria, and the results are
coherent with those obtained by other
questionnaires that measure various sorts of
technological addictions such as those involving the
Internet [19 - 21], and mobile phones [22 - 24]. All
these questionnaires are inspired by the addiction
literature. They assume that mobile phone addiction
has some problems, such as tolerance, withdrawals,
craving, difficulty to control the impulse, escape
from other problems, or negative consequences
upon daily life (at familiar, academic, professional
or social levels) [29 - 31].
In respect of this questionnaire, the first
factor, abstinence, explained the highest percentage
of the variance and addresses what is probably the
main criterion in the definition of addiction. The
items within this factor measure the degree of
discomfort produced by being deprived of mobile
phones as well as the use of these phones to resolve
affective problems that may or may not be related
to mobile-phone abuse. That is, addictive behaviour
is negatively reinforced, as it is in any dependence,
whether to drugs or any other substance or
phenomenon. Thus, the behaviour is produced to
relieve discomfort rather than to achieve pleasure.
Being unable to perform or finding it difficult to
perform the behaviour in question produces
discomfort that is resolved by engaging in the
behaviour again. The second factor, lack of control
and problems derived from use, includes two basic
characteristics of addiction. On the one hand, it
includes difficulty controlling the behaviour once
the environmental conditions that favour its
expression are in place. Difficulty controlling
impulses is common to all kinds of drug
dependence, and pathological gambling is currently
included in this category. On the other hand, one of
the characteristics common to all addictions is that
the repetition of the behaviour has undesirable
consequences. Yet, despite these consequences, the
behaviour continues to be performed, probably due
to the difficulty of controlling it. Conceptually, it is
significant that both of these quite relevant criteria
belonged to the same factor in our questionnaire;
that is, two elements that conceptually have
elements in common also appeared as
methodologically correlated. The third factor,
tolerance and interference with other activities, also
included two basic aspects of addiction that, again,
appear to be correlated and have common
conceptual underpinnings. One aspect is tolerance
or progressively greater use to obtain the desired
effects. Tolerance also appears in any dependence
and is due not only to chemical variables.
Prog Health Sci 2012, Vol 2 , No1 Test Mobile Phone Addiction
41
Conditioned tolerance, which is produced in the
presence of situational cues, is fundamental to
explaining the addictive process of even drug
dependence [32]. Obviously, when consumption
increases to excessively high levels or to levels that
impair functioning, addictions come to interfere
with other activities that are incompatible with the
high use because less time is available for these
activities when excessive time is spent on the
activity involved in the dependence. That both
criteria appeared in the same factor makes
conceptual sense, and this methodological
corroboration confirms the validity of this factor.
Additionally, the TMD showed strong and
statistically significant correlations with the MPDQ
[22]. This questionnaire was also shown to be
sensitive to sex and age differences among
adolescents, which makes it especially relevant as a
diagnostic instrument. Thus, global TMD scores
and scores for each of the factors were higher in
girls. This result is congruent with data showing
that girls use mobile phones more than do boys and
that girls are more likely to engage in mobile-phone
abuse and to experience problems with their parents
due to excessive use. With regard to age, the
questionnaire was sensitive to differences between
those 12–14 years of age and those 15–16 or 17–18
years of age. Although mobile-phone use begins
during the first phases of adolescence, or even
before puberty, the most severe consequences of
abuse occur in those 15–16 years of age, especially
with respect to increased use (tolerance and
problems derived from excessive use).
This study has several limitations that
should be noted. Although data on concurrent
validity were presented in relation to the main
parameters of the use of mobile phones, additional
analyses are necessary to examine associations
between the scale and mental health conditions (for
example depression, anxiety) and other indicators
of psychosocial dysfunction. But the main problem
is related, precisely, with the impressive growth of
technological functions and applications of the
mobile. The use of Internet by the mobile, or the
development of applications as WhatsApp, not only
modifies the pattern of use of the mobile, but are
some crucial variables which can also induce the
abuse, or the dependence of the mobile phone. This
is particularly relevant for teenagers, because the
adolescents’ dependence on mobile phone is a
problem that is not only new, but also on the rise. It
is necessary to continue to study the conditions that
foster this dependence, to develop prevention and
treatment programs, and to make available
assessment and diagnostic instruments that enable
effective intervention
CONLUSIONS
The results obtained in previous
exploratory studies showed that the mobile phone is
one of the technological tools more used by
adolescents. Some of the teenagers show the main
symptoms which characterized the dependence
disorders, such as: excessive use, problems with
parents, difficulty in controlling the use,
interference with other activities, emotional
discomfort when they cannot use the mobile phone.
This paper shows an instrument built in
order to evaluate the dependence of mobile in
adolescents taking into account the DSM-IV-TR
criteria for dependence disorders, a problem that is
not only new but also on the rise. It is necessary to
continue to study the conditions that foster this
dependence, to develop prevention and treatment
programs, and to make available assessment and
diagnostic instruments that enable effective
intervention. We believe (and hope) that this
instrument can be useful for researchers and
therapists working with mobile-phone dependence.
This study has several limitations that
should be noted. Although data on concurrent
validity were presented in relation to the main
parameters of the use of mobile phones, additional
analyses are necessary to examine associations
between the scale and mental health conditions (for
example, example depression, anxiety) and other
indicators of psychosocial dysfunction. However,
the main problem is related, precisely, with the
impressive growth of technological functions and
applications of the mobile. The use of the Internet
by the mobile, or the development of applications
as WhatsApp, not only modifies the pattern of use
of the mobile, but are some crucial variables, which
can also induce the abuse, or the dependence of the
mobile phone. This is particularly relevant for
teenagers, because the adolescents’ dependence on
mobile phone is a problem that is not only new, but
also on the rise. It is necessary to continue to study
the conditions that foster this dependence, to
develop prevention and treatment programs, and to
make available assessment and diagnostic
instruments that enable effective intervention.
Conflicts of interest
We declare that we have no conflicts of interest.
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Appendix
Test of Mobile-phone Dependence (TMD)
Indicate how frequently the statements that appear below apply to you using the following scale as a guide:
0
Never
1
Rarely
2
Sometimes
3
Often
4
Frequently
1
I have been called on the carpet or warned about using my mobile phone too much.
0
1
2
3
4
2
I have put a limit on my mobile phone use and I couldn’t stick to it.
0
1
2
3
4
3
I have argued with my parents or family members about the cost of my mobile phone.
0
1
2
3
4
4
I spend more time than I would like to talking on the mobile phone, sending SMSs, or
using WhatsApp.
0
1
2
3
4
5
I have sent more than five messages in one day.
0
1
2
3
4
6
I have gone to bed later or slept less because I was using my mobile phone.
0
1
2
3
4
7
I spend more money on my mobile phone (calls, messages…) than I had expected.
0
1
2
3
4
8
When I’m bored, I use my mobile phone.
0
1
2
3
4
9
I use my mobile phone (calls, SMSs, WhatsApp...) in situations where, even though not
dangerous, it is not appropriate to do so (eating, while other people talk to me, etc.).
0
1
2
3
4
10
I have been criticized because of the cost of my mobile phone.
0
1
2
3
4
Indicate to what degree you agree or disagree with the statements presented below.
0
Completely disagree
1
Disagree somewhat
2
Neutral
3
Agree somewhat
4
Completely agree
11
When I haven’t used my mobile phone for a while, I feel the need to call someone, send an
SMS, or use WhatsApp.
0
1
2
3
4
12
Since I got my mobile phone, I have increased the number of calls I make.
0
1
2
3
4
13
If my mobile phone were broken for an extended period of time and took a long time to
fix, I would feel very bad.
0
1
2
3
4
14
I need to use my mobile phone more and more often.
0
1
2
3
4
15
If I don’t have my mobile phone, I feel bad.
0
1
2
3
4
16
When I have my mobile phone with me, I can’t stop using it.
0
1
2
3
4
17
Since I got my mobile phone, I have increased the number of SMSs I send
0
1
2
3
4
18
As soon as I get up in the morning, the first thing I do is see who has called me on my
mobile phone or if someone has sent me an SMS.
0
1
2
3
4
19
I spend more money now on my mobile phone now than when I first got it.
0
1
2
3
4
20
I don’t think I could stand spending a week without a mobile phone.
0
1
2
3
4
21
When I feel lonely, I use the mobile phone (calls, SMSs, WhatsApp...).
0
1
2
3
4
22
I would grab my mobile phone and send a message or make a call right now.
0
1
2
3
4
