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Research Article
Measuring Problematic Mobile Phone Use: Development and
Preliminary Psychometric Properties of the PUMP Scale
Lisa J. Merlo,1Amanda M. Stone,2,3 and Alex Bibbey2,4
1Department of Psychiatry, University of Florida, P.O. Box 100183, Gainesville, FL 32610-0183, USA
2University of Florida, Gainesville, FL 32610, USA
3Department of Emergency Medicine, Orlando Regional Medical Center, Orlando, FL 32806, USA
4Department of Radiology, Duke University, Durham, NC 27705, USA
Correspondence should be addressed to Lisa J. Merlo; lmerlo@u.edu
Received March ; Revised July ; Accepted August
Academic Editor: Dace Svikis
Copyright © Lisa J. Merlo et al. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
is study aimed to develop and assess the psychometric properties of an English language measure of problematic mobile phone
use. Participants were recruitedf rom a university campus, health science center, andother public locations. e sample included
individuals (.% female) aged –. Results supported a unidimensional factor structure for the -item self-report Problematic
UseofMobilePhones(PUMP)Scale.Internalconsistencywasexcellent(𝛼 = 0.94). Strong correlations (𝑟 = .76,𝑃 < .001)were
found between the PUMP Scale and an existing scale of cellular phone dependency that was validated in Asia, as well as items
assessing frequency and intensity of mobile phone use. Results provide preliminary support for the use of the PUMP Scale to
measure problematic use of mobile phones.
1. Introduction
Mobile phones (a.k.a., cellular telephones) have many per-
ceived benets, including increased accessibility and social
connection, eciency in the workplace, convenience, and
improvedsafety.However,inrecentyears,therehasbeen
increasing public interest in the negative consequences of
mobile phone use. In one Saudi Arabian study, .% of par-
ticipants related common health complaints such as head-
ache, trouble concentrating, memory loss, hearing loss, and
fatigue to their mobile phone use []. Another Saudi Arabian
study suggested that %-% of mobile phone users exhibit
problems such as tension, fatigue, sleep disturbance, and
dizziness related to their mobile phone use, and over %
complain of headaches []. Accidents caused by distracted
driving [,] have been highlighted as a public health con-
cern. In addition, anecdotal observation and media reports
suggest that the number of self-professed “cell phone addicts”
and compulsive users of “crack-berries” and other smart-
phones has increased as mobile phones have become ubiq-
uitous. Public recognition of this phenomenon is reected in
the many websites and blogs addressing the issue, as well as
numerous articles in the popular press describing cell phone
addiction. ough stories have appeared in publications such
as the New York Times [], the Los Angeles Times [], and
http://www.forbes.com/ [] for many years, the academic lit-
erature surrounding problematic mobile phone use remains
fairly limited, even when compared to other “behavioral
addictions” such as pathological gambling, problematic inter-
net use, and problem video gaming [–].
While “addiction” is a term commonly used and arguably
overused in society, the conceptualization of addiction
remains controversial even among researchers and clinicians
who specialize in substance use disorders and addictive
behaviors. Indeed, the Diagnostic and Statistical Manual of
Mental Disorders, Fourth Edition—Text Revision [DSM-IV-
TR][] did not include a condition called “addiction.” Rather,
it described substance abuse and substance dependence as
distinct psychiatric disorders, and failed to include discussion
of addictive behaviors that do not involve substance use.
Furthermore, the recently released Diagnostic and Statistical
Manual of Mental Disorders, Fih Edition (DSM-5) describes
“substance use disorders” using the following criteria: ()
useinlargerquantitiesoroverlongeramountsoftimethan
Journal of Addiction
initially intended, () a desire to cut down or control use, ()
spending a great deal of time obtaining, using, or recovering
from the substance, () craving, () recurrent substance use
resulting in a failure to fulll major role obligations, () con-
tinued use despite social/interpersonal problems, () neglect
of other important activities because of substance use, () use
in situations in which it is physically hazardous, () continued
use of the substance despite adverse physical or psychological
consequences associated with use, () tolerance, and ()
withdrawal symptoms [].
ough the DSM-IV-TR and DSM-5 do not include any
disorders related to the problematic use of technology, patho-
logical gambling is included in DSM-IV as a diagnosable
condition under the category of impulse control disorders not
elsewhere classied [], and in DSM-5 as the rst “behavioral
addiction.” Even though pathological gambling does not
involve the use of a chemical substance, the similarities bet-
ween the diagnostic criteria for substance use disorders and
pathological gambling are striking. In general terms, both
may be described as disorders involving loss of control over a
compulsive, time- and resource-consuming behavior, which
persists in the face of adverse consequences, with continued
escalation of the behavior and/or withdrawal symptoms from
reduction of the behavior.
Similarly, it was suggested as early as (i.e., well before
the widespread use of mobile phones) that pathological use
of technology may exist in the form of “technodependence”
[]. e constructs of internet addiction and problem video
gaming are gaining both clinical and empirical support [,
]. In addition, though problematic mobile phone use has
not, to date, been recognized as a diagnosable condition,
experts in the eld are debating its inclusion as one []. While
evidence is scarce regarding a true “addiction” to mobile
phones, data from recent studies suggest that some mobile
phone users exhibit serious problematic behaviors analogous
to the diagnostic criteria for substance use disorders or
pathological gambling. ese symptoms include preoccu-
pation with mobile phone-based communication, excessive
time or money spent on mobile telephones/communication
plans, use of cellular devices in socially inappropriate or even
physically dangerous situations (e.g., “texting” while driving
an automobile), adverse eects on relationships, increased
frequency or duration of mobile phone communication, and
anxiety when separated from one’s telephone or when without
an adequate cellular signal [–]. Given these ndings,
it seems plausible that the consequences and psychological
dependence seen in problematic mobile phone use (like
pathological gambling and problematic internet and video
game use) seem to parallel substance use and dependence and
may be important to consider as a potential diagnostic entity
and target of intervention.
In order to evaluate the extent to which problematic
mobilephoneusemayberelatedtootheraddictivebehaviors,
research is needed to clarify the construct. To date, research
on problematic mobile phone use has been limited by the lack
of validated diagnostic criteria or standardized assessment
measures. For this study, we operationally dened “prob-
lematic mobile phone use” as any pattern of mobile phone use
resulting in subjective distress or impairment in important
areas of functioning. Given that some individuals have legit-
imate reason to use their mobile phone very frequently (e.g.,
for work obligations) and are able to do so without negative
consequences, we believed it was important to distinguish
“problematic” use from “very frequent” use. We expected
ratesofmobilephoneusetobehigheramongindividualswho
exhibited symptoms of problematic mobile phone use, just as
substance abusers generally tend to use substances in greater
quantities/frequencies than nonabusers. However, as with
substance use disorders, we did not feel that high frequency
use should be considered a symptom of the condition. For
this study, quantity of use was not included as a component of
“problematic mobile phone use,” except that individuals’ sub-
jective assessment of their use as excessive and troublesome
was considered.
e purpose of the present study was to develop an
English language measure of problematic mobile phone use
symptoms, based on adaptations of the DSM-5 substance use
disorder criteria. e study followed a similar methodology
to that utilized in previous studies regarding behavioral
addictions [,]. Specically, our overarching hypotheses
for this study included the following.
() Symptoms of problematic mobile phone use can be
measured reliably and validly using a self-report ques-
tionnaire.
() Scores on the preliminary measure of problematic
mobile phone use developed for this study will corre-
late signicantly with an existing measure of cellular
phone “dependency,” which was validated on Asian
samples.
() Symptoms of problematic mobile phone use will
correlate positively with frequency and intensity of
mobile telephone usage.
2. Method
All procedures were approved by the University of Florida
Institutional Review Board. Participants were recruited for
this study using several methods. First, yers advertising the
study were posted around the university campus, the health
science center, and in public locations including a mobile
phone store. Individuals who were interested in study partici-
pationcalledtheresearchteamtoobtainasurveypacketorto
arrange a time to complete the survey. Second, university stu-
dents were recruited for the study via announcements made
in various undergraduate and graduate level courses. Ques-
tionnaires were passed out with a self-addressed, stamped
envelope for participants to return the survey to the research
team. ird, other participants learned of the study via word-
of-mouth and made contact with members of the research
team in order to participate. All surveys were completed
anonymously. Completion of the full study questionnaire
required – minutes, and no compensation was provided
to study participants.
2.1. Participants. Data were collected from individuals
(.% female) who ranged in age from to years old
Journal of Addiction
T : Pearson correlations between PUMP Scale, CPDQ, CUQ, and self-assessment items.
Item PUMPS total score P
CPDQatotal score . <.
CUQb,c
How frequently do you typically use the email function on your phone? . <.
How frequently do you typically use the internet feature of your phone? . <.
How frequently do you use the games feature of your cell phone? . .
How oen do you talk on the phone while driving? . <.
How oen do you write text messages or emails while driving? . <.
Self-assessment questions
I sometimes think that I might be “addicted” to my cell phone. . <.
I use my cell phone more oen than other people I know. . <.
Friends or family members have commented to me about my cell phone use. . <.
aCPDQ refers to the cell phone dependency tendency questionnaire.
bCUQ refers to the cell phone use questionnaire.
cAll CUQ item responses ranged from = never to = constantly.
(𝑀 = 29.8 years old, SD = . years). Participants were self-
identied as Caucasian (.%), Hispanic/Latino (.%),
Asian/Pacic Islander (.%), African American/Black
(.%), or Other (.%). e sample included university
students (.%), individuals employed full-time (.%),
individuals employed part-time (.%), and individuals who
were not currently employed or in school (.%). Annual
incomewasreportedby.%ofthesampleandranged
from to , (𝑀=24,562,SD=,).
2.2. Measures
2.2.1. Problematic Use of Mobile Phones (PUMP) Scale. Apool
of potential items for the PUMP Scale was developed by
the rst author based upon () informal interviews with sev-
eral self-identied “cell phone addicts” who contacted the rst
author to discuss their mobile phone usage, () adaptation
of the DSM-IV criteria for substance use disorders, and ()
review of existing measures assessing consequences of exces-
sive internet use. ese items were reviewed by undergrad-
uate research assistants for clarity but were not specically
pretested to assess psychometric properties before the ques-
tionnaires were distributed. Aer reviewing the proposed
criteria for substance use disorders in the DSM-5 [], which
was not yet published, the rst and second authors together
selected items for inclusion in the scale. Item selection
was guided by the rational method, with the authors together
choosing the items that best reected each of the
substance use disorder criteria proposed by the DSM-5 Tas k
Force on Substance-Related Disorders. All items were rated
on a -point scale ranging from = “strongly disagree” to =
“strongly agree.” Scale analysis was utilized to assess psycho-
metric properties of the individual items and the scale as
a whole. Further description of the scale is included in the
results section.
2.2.2. Cellular Phone Dependence Tendency Questionnaire
(CPDQ: [22]). e CPDQ was originally developed in Japan,
to assess cellular phone “dependency” among Japanese uni-
versity students. It was later translated from Japanese to ai
and was used to study high school and university students
in ailand []. Kawasaki and colleagues also published
an English translation of the CPDQ in the report of their
research []. For the present study, some items from this
English translation were reworded slightly to more closely
match the accepted local vernacular. e CPDQ is a -item
self-report measure. ough it taps the domain of “cell phone
addiction,” the CPD Q was not developed on the basis of either
DSM-IV or DSM-5 criteria for substance use disorders and
does not include items that would be considered reective
of “abuse” criteria per DSM-IV-TR guidelines. Rather, items
solely assess respondents’ perceived dependence on their cel-
lularphone(e.g.,“IwouldfeelworseifIlostmycellularphone
than if I lost my wallet” and “I send text messages even during
work or class”). Items are rated on a -point scale ranging
from “not true at all” to “true.” e CPDQ has demon-
strated good reliability and validity in non-English-speaking
populations [,,]. In addition, internal consistency for
the current sample was excellent (𝛼 = .91).
2.2.3. Cellular Phone Usage Questionnaire (CUQ). e CUQ
is a compilation of items assessing specic mobile phone
usage patterns. It was developed for the present study as a gen-
eral measurement of mobile phone use and does not attempt
to distinguish excessive usage or identify consequences or
symptoms associated with mobile phone use. Items assess the
amount of time spent utilizing various components of cellular
phones (e.g., phone minutes, text messaging, emailing, inter-
net access, and video game play). Items are rated on a -point
scale ranging from “never” to “constantly.” Participants also
completed self-assessment questions regarding perceptions
of their mobile phone usage. Items are included in Table .
3. Results
All statistical analyses were conducted using PASW ..
In order to address isolated cases of missing data, mean
substitution was utilized for subscales in which at least %
of the data were complete.
Journal of Addiction
T : PUMP Scale item analysis.
Item M (SD) Range Corrected item
total correlation
Alpha if item
deleted
When I decrease the amount of time spent using my cell phone I
feel less satised. (Tolerance) . (.) – . .
Tolerance—I need more time using my cell phone to feel
satised than I used to need. (Tolerance) . (.) – . .
When I stop using my cell phone, I get moody and irritable.
(Withdrawal) . (.) – . .
It would be very dicult, emotionally, to give up my cell phone.
(Withdrawal) . (.) – . .
e amount of time I spend using my cell phone keeps me from
doing other important work. (Longer time than intended) . (.) – . .
I have thought in the past that it is not normal to spend as much
time using a cell phone as I do. (Longer time than intended) . (.) – . .
I think I might be spending too much time using my cell phone.
(Great deal of timespent) . (.) – . .
People tell me I spend too much time using my cell phone.
(Great deal of time spent) . (.) – . .
When I am not using my cell phone, I am thinking about using
it or planning the next time I can use it. (Craving) . (.) – . .
I feel anxious if I have not received a call or message in some
time. (Craving) . (.) – . .
I have ignored the people I’m with in order to use my cell
phone. (Activities given up or reduced) . (.) – . .
I have used my cell phone when I knew I should be doing
work/schoolwork. (Activities given up or reduced) . (.) – . .
I have used my cell phone when I knew I should be sleeping.
(Use despite physical or psychological problems) . (.) – . .
When I stop using my cell phone because it is interfering with
my life, I usually return to it. (Use despite physical or
psychological problems)
. (.) – . .
I have gotten into trouble at work or school because of my cell
phone use. (Failure to fulll role obligations) . (.) – . .
At times, I nd myself using my cell phone instead of spending
time with people who are important to me and want to spend
time with me. (Failure to fulll role obligations)
. (.) – . .
I have used my cell phone when I knew it was dangerous to do
so. (Use in physically hazardous situations) . (.) – . .
I have almost caused an accident because of my cell phone use.
(Use in physically hazardous situations) . (.) – . .
My cell phone use has caused me problems in a relationship.
(Use despite social or interpersonal problems) . (.) – . .
I have continued to use my cell phone even when someone
asked me to stop. (Use despite social or interpersonal problems) . (.) – . .
Note: item responses ranged from = strongly disagree to = strongly agree.
3.1. Mobile Phone Use Patterns. Participants reported having
a mobile phone for an average of . years (SD = ., range
= – years). e majority of respondents (.%) reported
havingapersonalcellularphonewithamonthlycontract,
.% reported having a personal cellular phone with a prepaid
contract, and .% reported sharing a cellular phone with at
least one other person. Of the sample, .% of respondents
denied having a cellular phone.
3.2. Reliability Analysis. e items of the proposed PUMP
Scaleweresubjectedtoscaleanalysis.Resultsdemonstrated
that the items assessing the DSM criterion “desire to cut
down”(i.e.,“IwouldfeelrelievedifIwassomewherethatmy
cellphonedidnotwork”and“IsometimeswishIcouldgetrid
of my cell phone”) had extremely low item total correlations
(. and ., resp.). Aer rst considering their theoretical
importance, it was decided that these items should be deleted
Journal of Addiction
T : PUMP Scale item frequencies.
Item Strongly disagree % Disagree % Neutral % Agree % Strongly agree %
When I decrease the amount of time spent using my
cell phone I feel less satised. . . . . .
I need more time using my cell phone to feel satised
than I used to need. . . . . .
When I stop using my cell phone, I get moody and
irritable. . . . . .
It would be very dicult, emotionally, to give up my
cell phone. . . . . .
e amount of time I spend using my cell phone keeps
me from doing other important work. . . . . .
I have thought in the past that it is not normal to spend
as much time using a cell phone as I do. . . . . .
I think I might be spending too much time using my
cell phone. . . . . .
People tell me I spend too much time using my cell
phone. . . . . .
When I am not using my cell phone, I am thinking
about using it or planning the next time I can use it. . . . . .
I feel anxious if I have not received a call or message in
some time. . . . . .
I have ignored the people I’m with in order to use my
cell phone. . . . . .
I have used my cell phone when I knew I should be
doing work/schoolwork. . . . . .
I have used my cell phone when I knew I should be
sleeping. . . . . .
When I stop using my cell phone because it is
interfering with my life, I usually return to it. . . . . .
I have gotten into trouble at work or school because of
my cell phone use. . . . . .
At times, I nd myself using my cell phone instead of
spending time with people who are important to me
and want to spend time with me.
. . . . .
I have used my cell phone when I knew it was
dangerous to do so. . . . . .
I have almost caused an accident because of my cell
phone use. . . . . .
My cell phone use has caused me problems in a
relationship. . . . . .
I have continued to use my cell phone even when
someone asked me to stop. . . . . .
fromthenalscale,astheydidnotappeartottheoverall
constructofproblematicmobilephoneuse.enalPUMP
Scale demonstrated excellent internal consistency ( items,
𝛼 = .94).Removalofanyitemwouldhaveresultedinaneg-
ativeimpactonthescalealpha.Itemsincludedinthenal
PUMP Scale are listed in Tab l e .
3.3. Factorial Validity. A principal components analysis was
utilized to assess the factor structure of the -item PUMP
Scale. Results supported a one-factor solution, with factor
loadings for all items ≥.. e one-factor solution explained
.% of the variance, meeting Carmines and Zeller’s
criterion []. Analysis of the Scree plot also supported a
one-factor solution [], with the eigenvalue of the rst
component (.) far exceeding the eigenvalue of the second
component (.), which was not signicantly dierent from
the remaining eigenvalues.
3.4. Convergent and Discriminant Validity Data. Scores on
the PUMP Scale ranged from to (𝑀 = 38.40, SD = .)
out of a possible score of . Frequency counts for each item
response are listed in Tabl e .PUMPscoreswerecompared
to scores on the Cellular Phone Dependency Tendency Ques-
tionnaire (CPDQ), the Cell Phone Use Questionnaire (CUQ),
and the self-assessment items. Results are listed in Table .Itis
noteworthy that PUMP Scale total scores were not associated
Journal of Addiction
with the length of time the individual has owned a mobile
phone (Pearson 𝑟 = −.08, ns) or with the amount of money
spent per month for mobile phone minutes (Pearson 𝑟=
−.04, ns). However, PUMP Scale scores were positively cor-
related with the amount of time spent engaging in any form
of mobile phone use (see Ta b l e ), as well as the amount of
money spent for text messaging service (𝑟 = .27,𝑃 < .001). As
seen in Tab l e , PUMP Scale scores also correlated positively
with perceptions of excessive mobile phone usage, including
self-reported feelings of “addiction” to the mobile phone.
4. Discussion
e purpose of the present study was to develop and validate
a self-report measure of problematic mobile phone use (i.e.,
“cell phone addiction”) for English-speaking respondents,
based on criteria utilized for other addictive behaviors.
Results indicated that problematic mobile phone use can
be measured via self-report. e Problematic Use of Mobile
Phones (PUMP) Scale demonstrated a single-factor struc-
ture, with excellent internal consistency. It also displayed con-
vergent validity when compared to an existing measure of cel-
lular phone dependency [the CPDQ []], items measuring
the frequency and intensity of cellular phone use behaviors
(the CUQ), and self-reported feelings of “addiction” to the
mobile phone. ese data provide preliminary support for
the use of the PUMP Scale in research examining problematic
mobile phone use in English-speaking samples.
Items included on the PUMP Scale instrument covered
a wide range of symptoms. Most participants did not report
symptoms, but it is noteworthy that a signicant minority of
respondents endorsed experiencing harm to their relation-
ships, nances, and safety as a result of excessive phone use
or use in inappropriate circumstances. Some respondents also
acknowledged subjective loss of control over escalating phone
use, as well as withdrawal-like symptoms when unable to use
their phone. Finally, individuals who reported more symp-
toms of problematic mobile phone use on the PUMP Scale
were more likely to endorse feeling “addicted” to their cellular
phone. ese ndings support the popular construct of
problematic mobile phone use (sometimes referred to as “cell
phone addiction”) and suggest that this area merits further
study.
When considering these ndings, it is important to
acknowledge some limitations of the present study. First,
like many instrument development studies, the sample was
relatively small (𝑁 = 244) and was comprised of individuals
recruited through convenience. Many of the participants
were recruited from a college campus, and some were
recruited from a mobile phone store, which may have intro-
duced selection bias. us, the generalizability of results to
the population as a whole may be limited. Future validation
eorts should include larger, more diverse samples that are
randomly selected. Second, the use of self-report, particularly
regarding past behaviors and experiences, may have intro-
duced biases due to faulty recall, social desirability, or shared
methods variance. Obtaining more objective measures (i.e.,
mobile phone records, collateral reports) would strengthen
the data. ird, no “gold standard” measure (i.e., accepted
formal diagnostic criteria) exists for problematic mobile
phone use. erefore, it was not possible to assess the oper-
ating characteristics of the PUMP Scale. Future research is
needed to identify the cut-point(s) of the PUMP Scale for the
purpose of detecting clinically signicant symptoms.
It must also be emphasized that the construct of problem-
atic mobile phone use is not yet well-studied or supported in
the literature. e merits and implications of considering this
construct should be further explored and developed. Clearly,
some individuals use their mobile phones more than others,
but the reasons for this may be multifaceted. Job require-
ments, safety issues, and family and social factors all may con-
tribute. However, “problematic mobile phone use” appears to
extend beyond frequency of use, to the extent that mobile
phone use produces social, occupational, and psychological
distress; it may be useful to identify these symptoms as poten-
tial targets for prevention and intervention. More research is
needed to support the results of the current study. Finally,
futurestudiesshouldelucidatethemechanismsunderlying
problematic mobile phone use, in order to determine whether
it exists as a primary phenomenon or alternatively is a symp-
tom of other underlying pathology (e.g., anxiety disorders,
impulse control decits, personality factors). e long-term
goal of research into problematic mobile phone use should be
to eectively identify and treat problem users or those at risk
for problematic use and ultimately to maximize communica-
tion utility of mobile technology while minimizing resulting
dysfunction.
Acknowledgment
Lisa J. Merlo’s work was supported in part by National
Institute on Drug Abuse (NIDA) Training Grant no. T-DA-
- (PI: Linda B. Cottler).
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