Reliability and construct validity testing of a questionnaire to assess nomophobia (QANP)

Abstract

Background:
The real meaning of the term nomophobia remains somewhat obscure in studies assessing this disorder. There is an increasing interest in further exploring nomophobia: however, currently available measuring tools appear to only address mobile phone abuse and/or addiction. The objective of this study was to create a Spanish-language instrument to measure nomophobia.

Methods:
We developed an 11-item scale that we administered to 968 participants drawn from the population of Granada (Spain). We first performed an Exploratory Factor Analysis. After assessing the nomological validity of the scale, we conducted a Confirmatory Factor Analysis.

Results:
The Exploratory Factor Analysis revealed a three-factor structure. Factor 1 (Mobile Phone Abuse) comprised five items that described 19% of the variance; Factor 2 (Loss of Control) comprised three items that explained 12% of the variance; and Factor 3 (Negative Consequences) comprised three items that explained 10% of the variance. Cronbach’s Alpha reliability coefficient was 0.80.

Limitations:
Nomophobia is a modern disorder that has yet to be classified as a disease. Self-report measures are affected by biased replies, and therefore the presence of confounders may be a potential issue.

Conclusion:
This scale is reliable and valid. It provides future researchers with the means to measure nomophobia in the Spanish population.

Full text

Abstract
Background: The real meaning of the term nomophobia
remains somewhat obscure in studies assessing this disor-
der. There is an increasing interest in further exploring
nomophobia: however, currently available measuring tools
appear to only address mobile phone abuse and/or addiction.
The objective of this study was to create a Spanish-language
instrument to measure nomophobia.
Methods: We developed an 11-item scale that we administe-
red to 968 participants drawn from the population of Granada
(Spain). We rst performed an Exploratory Factor Analysis.
After assessing the nomological validity of the scale, we con-
ducted a Conrmatory Factor Analysis.
Results: The Exploratory Factor Analysis revealed a
three-factor structure. Factor 1 (Mobile Phone Abuse) com-
prised ve items that described 19% of the variance; Factor
2 (Loss of Control) comprised three items that explained
12% of the variance; and Factor 3 (Negative Consequences)
comprised three items that explained 10% of the variance.
Cronbach’s Alpha reliability coefcient was 0.80.
Limitations: Nomophobia is a modern disorder that has yet to
be classied as a disease. Self-report measures are affected
by biased replies, and therefore the presence of confounders
may be a potential issue.
Conclusion: This scale is reliable and valid. It provides future
researchers with the means to measure nomophobia in the
Spanish population.
Keywords: Reliability, Construct Validity, Nomophobia.
Corresponding author: Francisca López - Torrecillas. Department of Personality, Evaluation and Psychological Treatment, Uni-
versity of Granada. Facultad de Psicología. Campus Universitario de Cartuja 18071 GRANADA, España. E-mail: fcalopez@
ugr.es. E-mail of coauthor Ramón Ferri-García: rferri@ugr.es. E-mail of coauthor María Angustias Olivencia-Carrión: maoli-
vencia@ugr.es. E-mail of coauthor María del Mar Rueda: mrueda@ugr.es. E-mail of coauthor Manuel Gabriel Jiménez-Torres:
mjitor@ugr.es.
Vol. 12, nº 2, pp. 43-56
Julio-Diciembre 2019
ISSN 1989-3809
Reliability and construct validity testing of a questionnaire to
assess nomophobia (QANP)
Fiabilidad y validez del cuestionario para evaluar la nomofobia
(QANP)
Ramón Ferri-García1; María Angustias Olivencia-Carrión2, María del Mar Rueda1; Manuel Gabriel
Jiménez-Torres2; Francisca López-Torrecillas2
1Department of Statistics and Operations Research and IEMath-GR, University of Granada, Spain.
2Department of Personality, Evaluation and Psychological Treatment, University of Granada. Spain.
Escritos de Psicología
Psychological Writings
Resumen
Antecedentes: El verdadero signicado de la nomofobia
parece estar oculto en los estudios que evalúan este tras-
torno. Existe un creciente interés en profundizar en el estudio
de la nomofobia, sin embargo, las herramientas de medición
disponibles desarrolladas hasta ahora parecen centrarse
solo en el abuso y / o adicción a los teléfonos móviles. Por
ello, el objetivo de este estudio objetivo proponer y validar un
instrumento de medición de la nomofobia para la población
española.
Método: Desarrollamos una escala con 11 ítems que fue
administrada a 968 participantes de la población de Gra-
nada (España). En primer lugar se realizó un análisis
factorial exploratorio y posteriormente se realizó un análisis
factorial conrmatorio.
Resultados: El análisis factorial exploratorio reveló una
estructura de tres factores. El factor 1 (abuso de teléfonos
móviles) está compuesto por cinco ítems y explica un 19%
de la varianza; Factor 2 (Pérdida de control) incluye tres
ítems y explica el 12% de la varianza y Factor 3 (Conse-
cuencias negativas) contiene tres ítems y explica el 10% de
la varianza. El valor del coeciente de abilidad Alpha de
Cronbach fue 0.80.
Limitaciones: La nomofobia es un trastorno moderno que
aún no se ha clasicado como patología, las medidas de
autoinforme presentas respuestas sesgadas por lo que
podemos encontrar algún error o sesgo.
Conclusión: QANP es una escala able y válida y propor-
ciona a los investigadores una forma de medir la nomofobia
para futuros estudios en la población española.
Palabras clave: Fiabilidad, validez de constructo, nomofobia.
Please cite this article as: Ferri-García, R., Olivencia-Carrión, M. A., Rueda, M. M., Jiménez-Torres, M. G. y López-Torrecillas,
F. (2019). Reliability and construct validity testing of a questionnaire to assess nomophobia (QANP). Escritos de Psicología,
12, 43-56.
Escritos de Psicología, 12, 43-5643

© 2019 Escritos de Psicología
Introduction
The term nomophobia refers to a set of behaviours or symptoms linked to a mobile phone (MP) use.
It is the fear of not being able to use the MP or being left without coverage (Bragazzi & Del Puente,
2014; King et al., 2014). Nomophobia denes the fear of being out of MP contact and is considered a
modern phobia. It is the result of an interaction between people and information/communication mobile
technologies (Nagpal & Kaur, 2016). Nomophobia alludes feelings of non-conformity, anxiety, nervous-
ness, or distress because of not being in proximity with the MP (Asensio-Chico et al., 2018; King et al.,
2014; Kuss & Grifths, 2016) dene it as a modern age disorder, and only recently it has been described
as a discomfort or anxiety caused by the unavailability of a MP. People affected with nomophobia, or
nomophobics, have an irrational fear of being without MP contact or of not being able to use it and try to
eliminate any possibilities of this happening. When they are unable to use their MP, they develop intense
anxiety, depression, nervousness, and stress (Gao et al., 2018; Szyjkowska et al., 2014; Thomée et al.,
2011). Some studies have shown a relationship between MP abuse or nomophobia and common health
problems (Movvahedi et al., 2014; Stothart et al., 2015), such as headaches, difculties to concentrate,
memory or hearing loss, and fatigue. Furthermore, nomophobics can also develop physical and psy-
chological problems, e.g., rigidity, muscle pain, ocular affections (Aggarwal, 2013), auditory illusions
(pseudo-sensation that the MP is ringing) or tactile illusions (pseudo-sensation that the MP is vibrating)
(Lin et al., 2013; Verma et al., 2014), as well as pain and weakness of thumbs and wrists (Ali et al.,
2014). Overall, nomophobia has been described as a MP dependence (Dixit et al., 2010) or addiction to
MPs (Forgays et al., 2014). Although there are some arguments against MP addiction, the term nomo-
phobia refers to MP addiction or dependence. There is some disagreement on whether problematic
use of a mobile/nomophobia can be considered a behavioural addiction (Billieux et al., 2010; Chóliz, et
al., 2010; De-Sola et al., 2016; Foerster et al., 2015; Pedrero-Pérez et al., 2012). In previous decades,
behavioural addictions were included in the Impulse-Control Disorders section of the Diagnostic and
Statistical Manual of Mental Disorders [DSM, (APA, 2002)] from which only pathological gambling was
considered an independent diagnostic category and the rest were found in the chapter “Unspecied
Impulse-Control Disorders”. The creation of the category “Substance-Related and Addictive Disorders”
was suggested in the [DSM (APA, 2013)], although only pathological gambling was nally included,
not the other suggested substance-unrelated or behavioural addictions. Thus, there are no specic
agreed diagnostic criteria for this type of additions, neither in the [DSM (APA, 2013)]. The abusive use of
modern technologies is a real problem seriously affecting people who suffer it (Sánchez-Carbonell et al.,
2004), thus, currently, there is an increase in the number of studies on behavioural addictions, mobile
addiction amongst others. To date, addiction to MPs or nomophobia includes all that associated until
not so long with Internet addiction (Ishii, 2004). For this reason, at the present, it should be considered
a potentially multi-addictive platform with an endless range of reinforcement sources, which translates
into high acceptance among the younger population (Walsh et al., 2010).
Behavioural addictions, such as pathological gambling, are characterized by the maintenance
of the abusive behaviour despite the adverse consequences, as with drug addictions, where the short-
term reward is achieved with the intake of chemical substances. Something similar, from an emotional
or neurological perspective, occurs with behavioural addictions (Clark & Limbrick-Oldeld, 2013). To
date, pathological gambling is the substance-unrelated addiction that has received the most attention
and with the largest number of studies (Navas et al., 2017; Walther et al., 2012). An addictive behaviour
implies the loss of the capacity to choose freely whether to quit or continue the behaviour (loss of con-
trol) and this leads to behaviour-related adverse consequences (Contreras-Rodríguez et al., 2016). In
other words, the person is unable to predict with certainty when the behaviour will occur again, for how
long, when it will stop, or which other behaviours can be linked with the addictive one. Consequently,
other activities will be left aside, or if not, they will not be as pleasant as they once were. Other nega-
tive consequences of the addictive behaviour may include interference with life roles (e.g., work, social
activities, or hobbies), deterioration of social relationships, legal problems, involvement in dangerous
situations, physical lesions and deterioration, nancial losses, and emotional problems. Various stu-
dies (Contreras-Rodríguez et al., 2016; Navas et al., 2017; Walther et al., 2012) hold the existence of
similarities between pathological and substance-related addictions with regard to their phenomenology,
epidemiology, personality factors, genetics, neurobiological processes, recovery, and management.
Recently, an increasing number of studies (Müller et al., 2013; Pedrero-Pérez et al., 2012; Peirce et al.,
2013) have found a series of potentially addictive behaviours. These behaviours are not linked with the
use of substances but are a consequence of the technological society. Internet chats, compulsive shop-
ping, pornography and/or addiction to sex, abuse of television, and/or addiction to MPs/nomophobia are
the cause of many dependence cases in people that use these tools as a refuge that helps them escape
Escritos de Psicología, 12, 43-5644

© 2019 Escritos de Psicología Escritos de Psicología, 12, 43-5645
from emotional or family problems. The behaviours are repetitive and pleasant at the beginning, but later
the individual cannot control them. As previously mentioned, there are no specic and agreed diagnostic
criteria for these types of addictions, although clinical experience exposes that excessive use of modern
technologies is a real problem that affects certain people (Müller et al., 2013; Pedrero-Pérez et al., 2012;
Peirce et al., 2013). History repeats itself. Pathological gambling was recognized as a nosological entity
in 1980, when the APA introduced it under the name «pathological gambling» in its DSM (APA, 2003)
which considered pathological gambling an Impulse-Control Disorder and the person who suffered it
became (in a chronic and progressive manner) unable to resist the impulse of gambling, and classied
with other disorders in the general section Impulse-Control Disorders Not Elsewhere Classied. Based
on the above analysis, the purpose of the present study is to develop a Spanish measuring tool for
nomophobia that will allow determining use vs abuse, type, frequency, and reason of MP use, time spent
with the MP, motivations, abuse effects, no mobile effect, consequences of abuse, self-perception, and
social perception.
Methods
Participants
The sample for this survey included 968 participants of Granada population with a mean age of 23.19
years and a standard deviation of 7.23. The majority of the respondents were women (81.1%). The
socio-demographic characteristics can be seen in Table 1. Participants were mainly recruited at their
workplace, via recruitment stands, advertisements and emails. Their bosses/teachers were sent e-mails
in which they were asked to help recruit their employees/students. It was their bosses/teachers who
provided us with those employees/students willing to participate in the study. They were recruited from
a range of types of workplace within Granada, including local authorities, healthcare providers and
retail outlets as well as institutions of higher and further education, and there was heterogeneity in their
geographical settings which spanned city centre and urban fringe locations. Participants were informed
about the aims of the study and provided signed informed consent. Ethical approval was obtained from
the Research Ethics Committee from University of Granada, Spain.
Sample and data collection
The sample size was estimated considering a 5% margin of error and a 95% condence level. Nine
hundred and sixty-eight young adults between 17 and 55 years were included in the survey. A summary
of the sociodemographic characteristics is shown in Table 1.
Table 1
Sociodemographic variables summary
Variable Mean Std. Dev.
Age 23.19 +- 7.23
Years of education 14.07 +- 4.12
Percentage Size
Gender
Male 18.8% N = 182
Female 81.1% N = 785
Studying
No 21.1% N = 204
Yes 78.9% N = 764
Working
No 81.3% N = 787
Yes 18.7% N = 181
Working sector
Technicians and business 3.3% N = 32
Services and army 6.3% N = 61
Manual labour 9.0% N = 87
Unemployment 81.4% N = 788
Scale development and procedure
In order to create a new Questionnaire to Assess Nomophobia (QANP), we conducted a systematic lite-
rature review (Beranuy-Fargues et al., 2009; Bianchi & Phillips, 2005; Billieux et al., 2008; Chóliz, 2012;
Chóliz et al., 2016; Güzeller & Coşguner, 2012; Ha et al., 2008; Igarashi et al., 2008; Jenaro et al., 2007;
Kwon et al., 2013; Leung, 2008; López-Fernández et al., 2012; Martinotti et al. 2011; Merlo et al., 2011;
Rutland & Sheets, 2007; Toda et al., 2004; Yildirim & Correia, 2015) to examine the existing measuring

© 2019 Escritos de Psicología Escritos de Psicología, 12, 43-5646
instruments. Three experts in clinical psychology, educational psychology, and psychometrics worked
in collaboration in the writing, understanding, clarication, and consistency of the criteria. Furthermore,
we included items associated with nomophobia such as the consequences of not being able to use the
mobile phone.
Once the new QANP was created, we conducted a pilot study and collected data from a hete-
rogeneous small size sample representative of the target group; subjects were asked to express their
feelings, ideas, and attitudes towards MP use. Initially, the scale was designed with 13 items, however,
further experiments showed that only 11 could be used. The items were related with abuse in texting,
high frequency, spending more than four hours per day using the MP (spending all the time with the
MP), coping with negative emotions or problems, to feel better, extreme nervousness and aggressive
behaviour when deprived from the MP or impossibility to use it, and progressive deterioration in school/
work and social and family functioning, impairment of social and self-perception.
We examined the scale to assess the psychometric properties of the individual items, as well as
the scale as a whole. A numerical score from 1 to 5 was assigned to each item based on the use and
abuse or nomophobia statement structure. Further description of the scale can be found in the Annex.
Data Analysis
Participants were randomly divided into two groups, each with n = 484. One of the groups was used to
perform an Exploratory Factor Analysis (EFA) and the other for a Conrmatory Factor Analysis (CFA)
with the adjusted model obtained with the EFA. This data-driven approach is recommended when prior
knowledge about possible common factors and their inuences (Fabrigar et al., 1999) is insufcient.
Several steps were followed before the EFA to prove the validity of the sample for building new varia-
bles. Bartlett’s test for Sphericity was used to verify if the correlation matrix was equivalent to an identity
matrix; the Kaiser-Meyer-Olkin (KMO) test was applied with a threshold of 0.8 (Kline, 1994) to test Mea-
sures of Sampling Adequacy (MSA).
For EFA rotation, a Promax algorithm was used which assumes obliquity between items. The
reason behind this choice was to look for any strong relationship between the new factors, and if this
were not the case, orthogonally between items was assumed. Maximum Likelihood (ML) was used for
factoring, given that the results would be very similar to other factoring methods with the advantage
of being able to observe a greater number of the goodness of t indicators (Ferrando & Anguiano-Ca-
rrasco, 2010). The EFA was conducted several times, with a threshold for standardized loadings of 0.30
each (Cattell, 1988; McDonald, 1985), in order to nd an acceptable solution with the least number of
dimensions. The acceptableness of this step was measured following the usual measures in scale vali-
dation, i.e., Root Mean Square Error of Approximation (RMSEA), which provides values below 0.05 if the
adjustment is good, although values around 0.08 or below are indicators of an acceptable adjustment
(Ruiz et al., 2010). Other measures included the Tucker-Lewis Index (TLI) of factoring reliability and the
Root Mean Square of the Residuals (RMSR). Values above 0.95 for the TLI imply that the adjustment
is good, but it can be considered acceptable if it is above 0.90 (Baş et al., 2016). Regarding the RMSR,
values around the inverse of the square root of the sample size were considered indicators of a good
adjustment (Kelley, 1935). We discarded the Chi-Square Test value, as high values would be frequently
obtained due to the large sample size, which would result in misleading conclusions about the quality of
the adjustment, even with trivial data-model differences (Fabrigar et al., 1999).
Considering the adjusted factorial model in the rst step, and after assessing its nomological
validity, a CFA was performed with the second group. To assess the goodness of t in CFA, the same
measures used in the EFA were used as well as the Goodness of Fit Index (GFI), which for good adjust-
ments presents values around 0.95.
Further calculations were performed in order to assess the validity and reliability, in its different
dimensions (convergent, discriminant, and predictive), of the scale veried with the CFA. Cronbach’s
Alpha internal consistency coefcients were calculated for the items conforming each factor, whose
values are considered to be acceptable when they are between 0.60 and 0.70 or higher (Baş, et al.,
2016; Cronbach, 1949; Kelley, 1935). Item-total correlation was calculated for each item to verify that
variations were homogeneous (Churchill, 1979). Student’s t-tests were performed to evaluate the diffe-
rences between upper and lower groups in each item.
The factors generated from the EFA and CFA were analyzed from the Item Response Theory
(IRT) perspective using the Mokken scaling (Mokken, 1971). as an alternative to Classical Test Theory
(CTT). This scaling allows the researcher to apply a type of non-parametric method to assess the validity
of the scale, where the only assumption is that the answers are ordinal. The methods include the com-
puterization of the coefcient of homogeneity as dened by Loevinger (1948) for each pair of items (Hij),

© 2019 Escritos de Psicología Escritos de Psicología, 12, 43-5647
each item (Hi), and the entire scale (H). A set of items were considered acceptable as per the criteria in
(Mokken, 1971) if each Hij > 0 and each Hi > 0.3, implying H > 0.3. If all of these assumptions are met, a
reliability coefcient rho (Molenaar & Sijtsma, 1988) can be computed for the scale, which is compara-
ble to Cronbach’s alpha. Further information on this procedure can be consulted in (van Schuur, 2003).
These calculations were made for all the data (n = 968).
Statistical analyses were carried out with the R program (R Core Team. 2015) and the packages
psych (Revelle, 2017), lavaan (Rosseel, 2012), psychometric (Fletche, 2010), and mokken (van der Ark,
2012), besides the base libraries.
Results
Exploratory Factor Analysis
The EFA procedure was conducted on the rst subsample to test the structure validity of the QANP
regarding the measurement of mobile phone addiction. Prior to this procedure, Bartlett’s test of Sphe-
ricity was applied to the subsample data. The null hypothesis of the test is P = P0, where P is the
population item correlation matrix and P0 is the identity matrix. Results of the test rejected the null hypo-
thesis (χ2 (n = 484) = 1242.549, df = 55, p < .0000) thus accepting the hypothesis that there is some
sort of relationship between items. Sampling adequacy was assessed with KMO procedure, obtaining
an overall MSA of 0.84, which means that the joint relationship of the variables is adequate considering
the threshold of 0.80 for MSA.
The conduction of the EFA provided as a result that the scale should have a structure of three
factors with 11 items. Based on the criteria of the 0.30 threshold for standardized loadings, items 2 and
3 were dropped from the analysis (out of the original 13-item scale) as their contribution was not enough
to full the specied requirements. Factor 1 (Mobile Phone Abuse) consisted of ve items (1, 3, 4, 7 and
8) whose factor loadings rotated by Promax were in the range between 0.36 and 0.94 and explained
a 19% of the variance. Factor 2 (Loss of Control) consisted of three items (2, 5, and 6) whose factor
loadings rotated by Promax varied from 0.47 to 0.76, explaining a 12% of the variance. Finally, Factor
3 (Negative Consequences) consisted of three items (9, 10, and 11), with factor loadings rotated by
Promax between 0.52 and 0.78, which explained 10% of the variance. Further information about factor
loadings with Promax rotation can be found in Table 2.
Table 2
Rotated factor loadings for the factors
Items Factor 1 Factor 2 Factor 3
10.94 -0.07 -0.14
2 0.11 0.68 -0.01
30.50 -0.02 -0.05
40.36 0.06 0.16
5-0.22 0.76 -0.03
6 0.22 0.47 0.03
70.71 0.01 -0.04
80.52 0.09 0.08
9-0.03 0.08 0.52
10 0.11 -0.10 0.52
11 -0.22 -0.02 0.78
The total variance explained by the scale was found to be 41%, which could be remarked as
sufcient in social science studies according to the author (Kline, 1994). RMSR index for EFA with three
factors was 0.03, meaning that few relationships are left to be explained thus the adjustment is good.
Tucker-Lewis Index was 0.943, which is around the levels of acceptance, and the RMSEA index was
0.051 with a 90% condence interval of [0.032 – 0.068], which is also within the limits of acceptance
recommended by the references mentioned at Section 2.4. As a nal remark for EFA, correlation matrix
for factors can be observed in Table 3.
Table 3
Correlation coefcient between factors
Factor 1 Factor 2 Factor 3
Factor 1 10.63 0.55
Factor 2 0.63 10.57
Factor 3 0.55 0.57 1

© 2019 Escritos de Psicología Escritos de Psicología, 12, 43-5648
It is noticeable that correlations are numerically relevant; the correlation between Factor 1 and
Factor 2 is 0.63 and between Factor 2 and Factor 3 is 0.55. These numbers prove that the obliquity
assumption is pertinent for the factor analysis performed.
A summary diagram for the factor loadings of each item, as well as the correlations between fac-
tors, can be observed in Figure 1.
Figure 1
Factor Analysis
Conrmatory Factor Analysis
CFA was performed on the factor structure obtained in EFA, in order to verify it, on the second split (n =
484) done on the original sample. As a result, values for goodness-of-t measures could be observed.
SRMR was found out as 0.048, which is very close to the inverse of the square root of the sample size
(with n = 484, the value is 0.04545455), so it can be considered as an evidence of a good t. Good-
ness-of-Fit Index (GFI) was found to be 0.966, which can be considered as evidence of a good t as it
is above 0.95 (the considered threshold of perfect t). Tucker-Lewis Index (TLI) was found out at 0.936,
which is also above the threshold of acceptance. Finally, the RMSEA value was 0.055, with a 90% con-
dence interval of [0.041 – 0.068]. Given that RMSEA indexes around 0.05 and 0.08 can be considered
as sufcient, the value obtained for RMSEA in the CFA is also evidence of an acceptable t.
Questionnaire validity and reliability
The result of Cronbach’s Alpha calculation for measuring internal consistency of the whole scale and of
all items was 0.80. Furthermore, we calculated the internal consistency of each factor and the following
coefcients were obtained: 0.75 for Factor 1, 0.64 for Factor 2, and 0.57 for Factor 3. These values for
reliability coefcients can be considered sufcient (Cronbach, 1949).
Convergent validity was assessed by calculating item-total correlation coefcients for each item.
Table 4 shows the results accompanied by the mean and SD. Pearson’s correlation test revealed that
all correlations were signicant with a condence level above 99.99%. In addition, differences of the
means between items suggest unequal difculty among them, which justies the application of the Item
Response Theory (IRT) analysis (van Schuur, 2003).

© 2019 Escritos de Psicología Escritos de Psicología, 12, 43-5649
Table 4
Items’ summary statistics and item-total correlation
Items Mean Std. Dev. Item-total correlation
14.51 1.19 0.688
22.57 1.35 0.701
32.11 0.95 0.490
4 2.42 1.23 0.596
51.49 1.18 0.471
62.45 1.25 0.672
7 3.01 1.13 0.667
82.52 0.95 0.632
91.56 1.16 0.496
10 1.48 0.81 0.514
11 1.21 0.63 0.383
To assess discriminant validity, t-tests were performed to analyse the differences between the
groups with the lower 27% scores and the upper 27% scores for each item. The results of the tests can
be consulted in Table 5.
Table 5
Discriminant validity of the scale
Item Upper 27% Lower 27% t-value Degrees of
freedom p-value
Mean Std. Dev. Mean Std. Dev.
Item 1 503.18 1.70 17.30 260 3.666244E-45
Item 2 4.25 0.43 1 0 121.49 261 1.011690E-231
Item 3 3.03 0.23 1 0 143.16 261 4.745320E-250
Item 4 4.14 0.35 1 0 144.29 261 6.337468E-251
Item 5 2.80 1.66 1 0 17.56 261 4.277777E-46
Item 6 4.00 1.79 1 0 61.26 261 6.562641E-157
Item 7 4.30 0.46 1.59 0.87 44.25 392.317 1.303952E-154
Item 8 3.22 0.42 1.02 0.14 81.05 316.765 7.309143E-214
Item 9 3.04 1.36 1 0 24.28 261 6.569342E-69
Item 10 2.51 0.82 1 0 29.59 261 2.277419E-85
Item 11 1.75 0.99 1 0 12.27 261 1.271764E-27
It can be observed in Table 5 that the upper group scores are signicantly higher than lower group
scores for every item of the scale, with a condence level higher than 99.99%. These results show that
the items have good discriminant power.
Mokken scaling
Results of mokken scaling proved that the 11-item total scale is adequate; when analysed, every Hij
coefcient for each pair of items (i, j) was above 0, every Hi coefcient for each item i was above 0.30
(from item 1 to 11: 0.81, 0.45, 0.34, 0.36, 0.32, 0.41, 0.44, 0.48, 0.32, 0.36 and 0.32 respectively) and
the total H coefcient was 0.413.
The independent analysis of each factor also proved the validity of all of them. Factor 1 presented
Hij > 0 for every pair of items in the factor and Hi > 0.3 for each item i (0.67 for item 7, 0.82 for item 1,
0.54 for item 3, 0.82 for item 4, and 0.61 for item 8). The total H coefcient for Factor 1 was 0.537. Factor
2 presented Hij > 0 for every pair of items in the factor and Hi > 0.3 for each item i (0.55 for item 2, 0.49
for item 5 and 0.44 for item 6). The total H coefcient for Factor 2 was 0.491. Factor 3 presented Hij > 0
for every pair of items in the factor and Hi > 0.3 for each item i (0.35 for item 9, 0.40 for item 10 and 0.41
for item 11). The total H coefcient for Factor 3 was 0.383. These results prove that the homogeneity of
the QANP scale and its factors (subscales) was adequate, according to the criteria stipulated in Mokken
(1971) for homogeneity coefcients.
Rho coefcient for the whole scale, calculated with the MS method, was 0.83, while for Factors 1,
2 and 3 was 0.78, 0.65 and 0.60 respectively. These reliability coefcients, comparable to Cronbach’s
alpha, prove that the proposed factor structure is reliable given that all the values are above acceptabi-
lity thresholds (Cronbach, 1949).

© 2019 Escritos de Psicología Escritos de Psicología, 12, 43-5650
Discussion
The recognition of behavioural addictions goes back to Marlatt et al. (1988) who reported a repetitive
habit pattern that increased the risk of disease and/or associated personal and/or social problems.
Addictive behaviours are characterized by the loss of control. The behaviour is done again despite the
volitional attempt of stopping or moderating it. Over the last decade a growing number of studies (Billieux
et al., 2010; Mentzoni, et al., 2011) have established psychological and neurobiological similarities in
the sustained practise of these behaviours (purchase, sex, Internet, video games, eating, MP overuse/
nomophobia). Neurobiological research on addiction has revealed the existence of a common mecha-
nism between substance addiction and behavioural addictions (Leeman & Potenza, 2013; Weinstein
& Lejoyeux, 2015). Regarding similarities between MP overuse/nomophobia and substance addiction,
the results of different studies (Cheung & Wong, 2011; Gao et al., 2018; Jenaro et al., 2007; Morissette
et al., 2014; Ozturk et al., 2013; Reed et al., 2015; Thomée et al., 2011) indicate a variety of adverse
effects for health, such as depression, social anxiety, insomnia, and hyperactivity. Further studies about
these problems are necessary and specic tools to assess these constructs. i.e., nomophobia would
facilitate our understanding. The primary goal of this study is to develop and validate a questionnaire to
assess nomophobia. In this study, we also conrm a three-factor structure for an 11-item self-reported
instrument to assess nomophobia.
The central point to be mentioned is that the conrmatory factor analysis emphasized that QANP
has an acceptable t and measures three factors. Factor 1 (Mobile Phone Abuse) consisted of ve items
(1, 3, 4, 7 and 8) as frequency use, bill pay, sleep interference, who to use the mobile phone with and
effects, that describe a 19% of the variance. Factor 2 (Loss of Control) consisted of three items (2, 5, and
6) as to cope negatives emotion or problems; aggressive behaviour, feel bad or depression when depri-
ved or can´t use that explain a 12% of the variance. Finally, Factor 3 (Negative Consequences) contains
three items (9, 10, and 11) as to require help to abuse the mobile phone and explain a 10% the variance.
In this study, we conrmed and extended previous results regarding the symptoms proposed
previously (Gao et al., 2018; Movvahedi et al., 2014; Szyjkowska et al., 2014; Thomée et al., 2011).
Furthermore, the new results presented in this study can specically be used to assess nomophobia,
as there is, to the best of our knowledge, no other available tool for this purpose. In one study (Nagpal
& Kaur, 2016) gender differences in nomophobia and impulsiveness was examined, although there was
no reference to the instrument used to assess nomophobia. Until now, it was only possible to assess MP
addiction with the available instruments (Beranuy-Fargues et al., 2009; Bianchi & Phillips, 2005; Billieux
et al., 2008; Chóliz, 2012; Chóliz et al., 2016; Güzeller & Coşguner, 2012; Ha et al., 2008; Igarashi et
al., 2008; Jenaro et al., 2007; Kwon et al., 2013; Leung, 2008; López-Fernández et al., 2012; Martinotti
et al. 2011; Merlo et al., 2011; Rutland and Sheets, 2007; Toda et al., 2004; Walsh et al., 2010; Yen et
al., 2009).
The Cronbach’ Alpha value was 0.80. Internal consistency of each factor was 0.75 for Factor
1, 0.64 for Factor 2 and 0.57 for Factor 3. As stated (Cronbach, 1949), these values for reliability coe-
fcients can be considered as sufcient. These results from the present study’s investigation of the
Instrument to Assess the Nomophobia (QANP) provide evidence that the measure is psychometrically
sound.
The main research question of this study concerned an exploration of psychometric properties
of the Questionnaire to Assess the Nomophobia (QANP), which provided solid evidence to support the
reliability and validity of three subscales: Mobile Phone Abuse (Factor 1), Loss of Control (Factor 2), and
Negative Consequences (Factor 3). Factor-based reliability indices including Cronbach’s alphas were
computed as a measure of internal consistency reliability. The Questionnaire to Assess the Nomophobia
(QANP) was demonstrated to have good-to-excellent reliability. Content validity was supported by the
use of an expert panel review process in generation of scale items.
Evidence of convergent validity was demonstrated in the strong positive correlations between
item-total correlation coefcients. Discriminant validity was further supported by the evidence of statis-
tically signicant differences between the groups with the lower 27% scores and the upper 27% scores
for each item.
Item Response Theory analysis also provided results which proved the validity and the homo-
geneity of the scale. Homogeneity coefcients were above the acceptability thresholds, and reliability
coefcients computed using the MS approach provided adequate results.
Regarding the clinical implications, the development of the QANP to detect MP overuse is an
important step for the development of diagnostic/therapeutic procedures and prevention/intervention
strategies. Future studies should examine the relationships between variables such as solitude, depres-
sion, self-esteem, well-being, academic success, and other demographic features, with nomophobia.

© 2019 Escritos de Psicología Escritos de Psicología, 12, 43-5651
Further understanding of nomophobia will provide additional data to be included in the DSM criteria,
particularly when referring to addictions linked to modern age technologies. Moreover, certain construct
validity evidence should be reviewed. Gender and age group invariance analyses are necessary to
obtain empirical evidence on the equivalence in the constructs and items used in the QANP. Once the
above is guaranteed, Differential Item Functioning and thorough comparative analysis of the considered
variables will be necessary to ensure the validity of the decisions through the scorings in the tests. With
these results, a score ≥40 or above could be considered as a high level of Nomophobia.
Limitations and future research
Our results should be evaluated in view of several important limitations. First, nomophobia should be
investigated considering a number of variables, such as demographics, personality, and clinical cha-
racteristics. This would allow a better understanding of human-technology interactions, as well as the
nature and causes of technology-related addictions. To the best of our knowledge, to date, there is no
valid and reliable questionnaire to measure nomophobia. The questionnaire presented in this study
(QANP) is an adequate instrument to measure MP addiction in future investigations on this modern
disorder although this is a self-reported measure and consequently unmeasured potential confounders.
Some people are interested in a therapeutic change and admit having negative personality features, but
have a very positive image. Thus, a second limitation to our study is the accuracy of participant self-re-
ported responses
Future studies should be carried out to elucidate the mechanisms underlying problematic MP use
and determine whether it is a primary phenomenon or a symptom of underlying pathology (e.g., anxiety
disorders, impulse control decits, personality factors). Long-term research on nomophobia should
focus on the identication and treatment of problematic users or those at risk. Nomophobia should be
classied as an important pathology. This would allow maximizing MP usefulness while minimizing the
damaging consequences of high frequency of texting, overuse, spending more than four hours per day
with the MP (spending all the time with the MP), coping with negative emotions or problems, to feel
better, extreme nervousness and aggressive behaviour when deprived from the MP or impossibility to
use it, and progressive deterioration in school/work and social and family functioning, impairment of
social and self-perception. Further evaluation and denition of nomophobia will allow developing inter-
ventions or prevention programs.
Role of funding sources
We would like to thank all of the participants in this study. This research was partially supported by Minis-
terio de Educación, Cultura y Deporte (grant MTM2015-63609-R Spain).
Acknowledgements
We would like to thank all participants for their contribution in this study.
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RECIBIDO: 14 de octubre de 2019
MODIFICADO: 25 de enero de 2020
ACEPTADO: 22 de junio de 2020

© 2019 Escritos de Psicología Escritos de Psicología, 12, 43-5656
Annex. Questionnaire to Assess the Nomophobia (QANP)
Question about use mobile phone Response categories
12345
I01 How often do you use mobile phone use? Twice more over
month
Weekend Daily Two hours a day More than four hours
a day.
I02 What are you raison for use mobile phone? Feeling happy Look up to my friends Enjoy whit it Coping stress and
problem
Coping sadness,
loneliness and
compassion myself
I03 How do you pay bill? Wage Credit card Family Partner Stolen
I04 What time do you use the mobile phone? At night After class or work During class or work Morning, when I
wake up
I get up at night and
use it
I05 Why do you use mobile phone? To communicate with
my friends
I feel lonely Because my friends
use it
To escape my problem To quit the routine
I06 Sometimes happens that I trouble keeping
up with my mobile
phone´s friends
It`s difcult for me to
answer when I receive
messages / whatsapps
I persistently call the
same person
I feel sad when they
do not answer me
I get depressed or
irritated if I can´t use
my mobile phone
I07 Who do you use your mobile phone? Parents or Family Brothers and sisters Partner Friends Strangers
I08 How do you feel when you use your mobile
phone?
I feel well and relaxed I feel euphoric In connection with my
friends
Heavy and sick Absolutely lost, if I
couldn´t use it
I09 What are the consequences of using? Neither Social relations
problem
I lost out on having a
lot of good times
Economic problem Family and/or partner
problem
I10 How do you feel about your mobile phone
using?
I haven´t problem I can control I can control but I´m
using by my friends
I feel bad when I think
of using
I need help or
treatment
I11 How do you perceive others about your
using?
Normal on my age When I use neglect my
family responsibilities
When I use neglect my
friends responsibilities
My family or friends
advises me to control
using
My family or friends
advises me to
treatment
Spanish Version. Questionnaire to Assess the Nomophobia (QANP)
Preguntas acerca del uso del teléfono
móvil Categorías de Respuestas
12345
I01 ¿Cuántas veces utilizas el teléfono
móvil?
2 o 3 veces al mes Semanalmente Diariamente 2 horas al día Más de 4 horas al día
I02 Señala las razones que tienes para usar el
teléfono móvil
Sentirme feliz Ser como mis amigos Divertirme Evadirme de mis
problemas y estrés
Salir de mi tristeza,
soledad y lastima de
mí mismo/a
I03 ¿Cmo consigues pagar la factura
del teléfono móvil?
Trabajando Con la tarjeta de
crédito
De mi familia De mi pareja Robando
I04 ¿A qué hora del día sueles usar el
teléfono móvil?
Por la noche Después de salir de
clase o del trabajo
Durante las clases o
el trabajo
Por la mañana,
cuando me despierto
Me levanto durante la
noche y lo suelo usar
I05 ¿Por qué usas el teléfono mvil? Para comunicarme
con mis amigos/as
Porque me siento
solo/a
Porque mis amigos
lo usan
Para evadirme de mis
problemas
Para salir de la rutuna
I06 A veces me ocurre que… Me cuesta seguir
el ritmo del uso del
teléfono móvil con mis
amigos
Me cuesta contestar
mensajes/whatsapps
Llamo de manera
persistente a la misma
persona
Me siento triste
cuando no me
contestan
Me deprimo o irrito
si no puedo usar el
teléfono móvil
I07 ¿Con quién usas el teléfono mvil? Con mis padres o
familiares
Con mis hermanos o
hermanas
Con mi pareja Con mis amigos Con desconocidos
I08 ¿Qué sientes cuando usas el
teléfono móvil?
Sensación de
bienestar y relajación
Sensación de euforia Conectado con los
amigos/as
Muy pesado/a
como si sufriera una
enfermedad
Totalmente perdido/a,
si no lo pudiera usar
I09 ¿Cuáles han sido las
consecuencias del uso del teléfono
móvil a lo largo de tu vida?
Ninguna Ha interferido en mis
relaciones sociales
Ha evitado que tenga
buenos momentos
Me he visto en apuros
económicos
He tenido problemas
con mis padres y/o
pareja
I10 ¿Cmo te sientes cuando te
planteas tu uso de teléfono móvil?
No tengo problemas Puedo controlarlo Puedo controlarlo pero
mis amigos me incitan
al uso
Me siento mal cuando
pienso en el uso
Necesito ayuda
(tratamiento) para
controlarme con el uso
I11 ¿Cmo te perciben los demás en
relación a tu uso con el teléfono
móvil?
Lo normal para mi
edad
Cuando lo uso
descuido las
responsabilidades con
mi familia
Cuando lo uso
descuido las
responsabilidades con
mis amigos
Mi familia o amigos me
aconsejan controlar o
reducir el uso
Mi familia o amigos
ya han ido a buscar
ayuda (tratamiento)
por mi uso del teléfono
móvil