Article

Temperament and characteristics related to nomophobia

Abstract

Nomophobia is defined as the fear of being out of mobile phone contact and is considered to be a phobia of the modern age. The current study set out to establish the relationship between temperament and personality and the development of nomophobia. The sample was composed of 968 participants selected from the Andalusian population, of which there were 182 males and 785 females aged from 23.19 years. The instruments used were the Questionnaire to Assess Nomophobia (QANIP; Olivencia-Carrión et al., 2018) and the Temperament and Character Inventory Revised (TCI-R; Cloninger et al., 1993). We found that cooperation is a characteristic that significantly reduces nomophobic levels, particularly for the two factors of Mobile Phone Addiction and Negative Consequences. Furthermore, Reward Dependence appears to be positively related to two of the factors involved in nomophobia, namely Mobile Phone Addiction and Loss of Control, suggesting a relationship between Nomophobia and personality. These findings are discussed in terms of their usefulness for identifying the personality predictors of nomophobia in order to develop preventive and intervention strategies.
Contents lists available at ScienceDirect
Psychiatry Research
journal homepage: www.elsevier.com/locate/psychres
Temperament and characteristics related to nomophobia
Maria Angustias Olivencia-Carrión
a,
, Ramón Ferri-García
b
, María del Mar Rueda
b
,
Manuel Gabriel Jiménez-Torres
a
, Francisca López-Torrecillas
a,
a
Center Research Mind Brain and Behaviour (CIMCYC), University of Granada, Spain
b
Department of Statistics and Operations Research and IEMath-GR, University of Granada, Spain
ARTICLE INFO
Keywords:
Nomophobia
Temperament
Character
Cooperation
Reward dependence
ABSTRACT
Nomophobia is dened as the fear of being out of mobile phone contact and is considered to be a phobia of the
modern age. The current study set out to establish the relationship between temperament and personality and
the development of nomophobia. The sample was composed of 968 participants selected from the Andalusian
population, of which there were 182 males and 785 females aged from 23.19 years. The instruments used were
the Questionnaire to Assess Nomophobia (QANIP; Olivencia-Carrión et al., 2018) and the Temperament and
Character Inventory Revised (TCI-R; Cloninger et al., 1993). We found that cooperation is a characteristic that
signicantly reduces nomophobic levels, particularly for the two factors of Mobile Phone Addiction and Negative
Consequences. Furthermore, Reward Dependence appears to be positively related to two of the factors involved
in nomophobia, namely Mobile Phone Addiction and Loss of Control,suggesting a relationship between
Nomophobia and personality. These ndings are discussed in terms of their usefulness for identifying the per-
sonality predictors of nomophobia in order to develop preventive and intervention strategies.
1. Introduction
Nomophobia is considered to be a disorder of the modern world,
derived from the technological developments and advances that have
been produced by virtual communication. It is dened as the fear of
being out of mobile phone contact and is considered a modern age
phobia that has been introduced to our lives as a product of the inter-
action between people and mobile information and communication
technologies (Nagpal and Kaur, 2016). Although Nomophobia has been
regarded as a controversial term, it is referred to as dependence on
mobile phones (Dixit et al., 2010) or an addiction to mobile phones
(Forgays et al., 2014). Wang et al. (2014) dened it as the feelings of
discomfort, anxiety, nervousness or distress that result from being out
of contact with a mobile phone, even causing suicidal ideation as well
as attempts. King et al. (2014) revised the denition of nomophobia in
order to increase its modern day relevance as a fear of being unable to
communicate through a MP. Nomophobia is a term that refers to a
collection of behaviours or symptoms related to MP use. Therefore, in
the case of nomophobia, people with nomophobia or nomophobes
would have an irrational fear of being out of mobile phone contact or
being unable to use it, and thus they attempt to eliminate the chances of
not being able to use their mobile phone. In the case of being unable to
use their mobile phone, they experience intense feelings of anxiety and
distress (Szyjkowska et al., 2014; Thomée et al., 2011). In this regard, it
remains unclear as to how much distress and impairment can be caused
by nomophobia or the personality variables that are involved, and thus
there is uncertainty with regard to which dimensions merit inclusion in
personality classication. It is therefore necessary to determine whether
harmfulness is likely to occur as a consequence of the personality traits
inherent in nomophobic individuals.
Numerous studies have explored how personality traits contribute
to the onset and maintenance of addiction disorders in young adults,
with high impulsivity and low self-control scores being key factors in
addiction (Lee et al., 2012; Reynolds et al., 2006). Earlier studies have
found that self-control is negatively correlated with the use of tobacco,
alcohol, and cannabis, along with problematic gambling and computer
gaming. Depression and extraversion have also been shown to be spe-
cic to substance users (Walther et al., 2012).
Mobile phone abuse is related to both extraversion (Bianchi and
Phillips, 2005) and neuroticism (Kuss et al., 2014) although anxiety
levels and the frequency of neurotic personality traits increase the se-
verity of the addiction (Mok et al., 2014). Recently, high impulsivity
has been identied as one of the risk factors for addiction to social
networking sites among individuals who suer from mobile phone
abuse (Kim et al., 2016; Wu et al., 2013).
Cloninger's personality model (Cloninger et al., 1993) is a four-di-
mensional structure comprised of the temperament dimensions referred
to as Novelty-Seeking (NS), Harm Avoidance (HA), Reward Dependence
https://doi.org/10.1016/j.psychres.2018.04.056
Received 5 October 2017; Received in revised form 22 February 2018; Accepted 29 April 2018
Corresponding authors.
E-mail addresses: maolivencia@ugr.es (M.A. Olivencia-Carrión), fcalopez@ugr.es (F. López-Torrecillas).
Psychiatry Research 266 (2018) 5–10
Available online 06 May 2018
0165-1781/ © 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).
T
(RD), and Persistence (P) along with three additional character di-
mensions. These character dimensions are Self-Directedness (SD), Co-
operativeness (C) and Self-Transcendence (ST). NS is the tendency to
approach novel situations for rewards, and to experience relief from
non-punishment. High NS includes impulsivity, quick temper, and
proneness to breaking rules. HA is the tendency to inhibit or avoid
responses to aversive cues, such as punishment and non-reward. RD is
the tendency to maintain responses that have been previously condi-
tioned through rewards. High RD is associated with being sociable and
sensitive to social cues. P is the tendency to maintain responses, despite
frustration and fatigue. High P is associated with persevering and being
ambitious. SD reects the ability to control, regulate, and adapt one's
behaviour to a situation in order to achieve one's goals and values. C
reects identication with, and acceptance of, others. Finally, ST is
thought to reect imaginativeness and spirituality. Cloninger's Psy-
chobiological Model provides a better t for the purpose of our goals,
for three reasons. First, the Temperament and Character Inventory (TCI-
R; Cloninger et al., 1993) predicts certain functional and clinical out-
comes (Arnau et al., 2008). Second, the model was specically devel-
oped for the purpose of analysing addiction (Gat-Lazer et al., 2017;
López-Torrecillas et al., 2014a,b; Pedrero-Pérez and Ruiz-Sánchez de
León, 2013; Pombo et al., 2017; Vitoratou et al., 2015). Third, research
has demonstrated that personality character proles predict life sa-
tisfaction. For instance, Park et al. (2015) examined the relationship
between life satisfaction and personality traits and found that the ST
prole was associated with the highest levels of life satisfaction,
whereas the depressive prole was associated with the lowest levels of
life satisfaction. Additionally, high SD, ST, and C were associated with
high life satisfaction. The SD was the strongest in the assessment of
one's quality of life, followed by ST and C. Similarly,
Gutiérrez et al. (2016) indicated that temperament and character aect
mental health, and in general, P stood out as the most important di-
mension regarding career success. SD was the best predictor of social
functioning and HA was linked with clinical problems.
There has been a substantial body of research on the role of dis-
positional constructs (NS, HA, RD, P, SD, C and ST) in the risk of sub-
stance abuse (Lu et al., 2014; Gutierrez et al, 2016). Studies of Internet
addiction have found decreased RD and increased NS among Internet-
addicted participants (Ko et al., 2010) with the latter obtaining higher
scores for TCI-R in NS, HA, P and ST; whilst lower scores in C also
tended to predict the presence of behavioural addiction (Farré et al.,
2015). In a similar survey, Kuss et al. (2014) identied increased
neuroticism and low agreeableness as risk factors for Internet addiction.
However, relatively few studies have examined personality traits
with regard to problematic and addictive abuse or nomophobia.
Problematic mobile phone abuse is related to extraversion and neuro-
ticism (Olivencia-Carrión et al., 2016; Takao, 2014), although anxiety
levels and frequency of neurotic personality traits increase the severity
of such an addiction (Mok et al., 2014). With regard to nomophobia,
King et al. (2014) investigated the appearance of emotional alterations
related to mobile phone abuse and found that nomophobes showed
signicant increases in anxiety, tachycardia, respiratory alterations,
trembling, perspiration, panic, fear and depression when they were
apart from or unable to use a mobile phone in comparison with healthy
volunteers. However, the relationship between nomophobia and other
psychological characteristics has received relatively little attention, and
it may be particularly important to examine the predictors of nomo-
phobia. Accordingly, Nagpal and Kaur (2016) studied the gender dif-
ferences in nomophobia and impulsiveness in college students between
the ages of 18 and 23 years and found that there were gender dier-
ences in nomophobia with male students exhibiting higher levels of
nomophobia in comparison with their female counterparts. However,
no gender dierences were found in impulsiveness or any of its com-
ponents.
1.1. Aims and hypothesis
The current study is an attempt to understand the modern age
mobile phone addiction known as nomophobia and its relationship with
temperament and personality in the adult population of the Spanish
autonomous community of Andalusia.
We take as our starting point the hypothesis that there are person-
ality variables (temperament and character) that protect against the
appearance of nomophobia. The temperament variables would be re-
ected in low scores in the Search for Novelty, Avoidance of Harm,
Dependence on Reward, and Persistence, whilst the character variables
would be represented by high scores on Self-directedness, Cooperation
and Self-transcendence and vice versa for the risk of the development of
nomophobia.
2. Methods
2.1. Data collection
A sample of 968 respondents from the city of Granada (Spain) was
employed in this experiment. The sample size was calculated according
to the sampling design used, based on a sampling error of + 5 per-
centage points and a condence level of 95%. Participants were mainly
recruited at their workplace, via recruitment stands, advertisements,
and emails. Their managers/teachers were sent e-mails in which they
were asked to help recruit their employees/students. It was their
managers/teachers who provided us with details of 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 geo-
graphical settings, which spanned city center and urban fringe loca-
tions. Participants were informed about the aims of the study and
provided signed informed consent. Ethical approval was obtained from
the Research Ethics Committee from the University of Granada, Spain.
The participants had an average age of 23.19 years (SD 7.23),
ranging between 17 and 55 years old, and the majority (81.1%) being
women. Sociodemographic variables revealed that the majority of the
sample was unemployed (81.3%), which is most likely to be a con-
sequence of the large proportion of students in the sample (78.9%). Of
the respondents who were employed (18.7%), 46.4% were working in
manual jobs, 33.7% in the services and army sector, and 17.7% in the
technological and business sectors. The average number of years of
education for the respondents was 14.07 years (SD 4.12).
2.2. Data preprocessing
An initial search was conducted for missing values, but only one was
found across all the predictor variables (the seven dimensions of the
TCI-R) and thus no action was taken. The individual that presented the
missing value was later excluded from the analysis, as this happened to
be an outlier. Skewness statistics were calculated for all variables
(predictor and predicted) to detect variables with high levels of asym-
metry, in order to transform these according to the nature of the
skewness and its severity. Square-root and log transformations were
used (Tabachnick and Fidell, 2000). Negative skewed variables were
reected before the transformations, and after completion of the
skewness correction they were reected again to recover their original
value (Osborne, 2005).
Tukey's (1997) criterion for nding outliers using the interquartile
range was used to nd extreme univariate outliers, which resulted in
the exclusion of 3 individuals. In the case of multivariate outliers,
Mahalanobis distance was used, given that it approximately follows a
Chi-square distribution (Afifi and Azen, 1972), although Sidak (1967)
correction had to be used due to the multiple comparisons that take
place in the hypothesis test. Thus, with a nal value of 0.00014 for
M.A. Olivencia-Carrión et al. Psychiatry Research 266 (2018) 5–10
6
alpha, 5 individuals were excluded using this process.
Pearson's correlation coecient matrix was calculated for the multi-
collinearity check in predictor variables. Every pair of correlations was
below the selection criteria of 0.99 (Tabachnick and Fidell, 2000),
meaning that there is no multi-collinearity in predictor variables.
2.3. Weight adjustment
The recruitment of respondents was not probabilistic and could lead
to biased estimates since certain groups are substantially under-re-
presented. Moreover, the sampling frame does not cover the entire
population to which survey results are to be extrapolated. These errors
can be overcome by the use of reweighting or calibration techniques.
Calibration was dened in Särndal (2007) as "the determining of
weights or expansion factors, incorporating auxiliary information to
calculate adjusting factors to the weights originally dened in the
sample design, the use of these weights to calculate population totals
and other parameters in nite population, and the seizing of the cali-
bration adjustments to reduce signicantly the bias contribution in the
presence of non-response and other non-sampling errors". The usage of
calibration estimators ensures that survey estimates are coherent with
those already in the public domain, while simultaneously reducing
sampling error and non-coverage (see Cabrera-León et al., 2015, 2017).
For the calibration conducted in this article, population totals of
gender, age, and years of schooling were used as auxiliary variable
totals. These quantities were retrieved from the 2013 population gures
provided by the Spanish National Institute of Statistics (INE), in the case
of gender and age, and from the 2011 Population and Households
Census (also conducted by the INE) in the case of years of schooling.
The retrieval was made for the region of Andalusia. Given that the
sampling frame was located inside this territory, this approach is fea-
sible if the study is to be carried out with the least possible bias.
The new sampling weights obtained in the calibration will be ap-
plied to a regression model using Raking calibration weights with all of
the three auxiliary variables under consideration. The purpose of the
regression is to obtain some measure of the eect that each dimension
of the TCI-R has on the nomophobia questionnaire, with calibration
playing an important role as it provides a certain level of safety in terms
of being able to generalize the measured eects to the entire popula-
tion. To test the hypothesis of whether the eects are null or sig-
nicantly dierent from null, p-values from the Wald test (Wald, 1943)
and its correction known as the working likelihood ratio (Rao and
Scott, 1984) will be provided, as these are the recommended tests to
apply when the sampling design is complex (Lohr, 2010).
2.4. Questionnaire to assess nomophobia (QANIP; Olivencia-Carrión et al.,
2018)
This questionnaire was developed by Olivencia-Carrión et al. (2018)
and consists of 11 items related to text message abuse, high frequency
of use, spending more than 4 hours per day using the mobile phone
(using the mobile phone all of the time) to cope with negative emotions
or problems, to feel better, showing extreme nervousness and ag-
gressive behaviour when deprived or unable to use the mobile phone,
progressive deterioration in school/work and social and family func-
tioning, and impairments in self and social perception. Each item is
scored from one to ve and they describe a four-factor structure ac-
cording to the Exploratory Factor Analysis (EFA) and Conrmatory
Factor Analysis (CFA) performed on the sample of participants de-
scribed in Section 2.1: Factor 1 (Mobile Phone Abuse) consists of four
items (1, 3, 7 and 8) that described 18% of the variance. Factor 2 (Loss
of Control) involves three items (2, 5, and 6) that explained 11% of the
variance. Factor 3 (Negative Consequences) contains three items (9, 10,
and 11) that explained 10% of the variance. Finally, Factor 4 (Sleep
Interference) consists of only one item (number 4) that explained 6% of
the variance. Goodness-of-t indices for EFA were 0.02 for RMSR,
0.976 for Tucker-Lewis Index (TLI), and 0.033 for RMSEA [CI 90%
00.57], while for CFA these were 0.045 for SRMR, 0.969 for Goodness-
of-Fit Index (GFI), 0.941 for TLI and 0.053 for RMSEA [CI 90%
0.0390.067]. The Cronbach's Alpha reliability coecient value for the
sample of the present study was 0.80. Convergent validity was assessed
with item-total correlations, which were all signicant, while dis-
criminant validity was assessed testing the null hypothesis of mean
equality between the upper and lower groups of each item, which was
rejected for all of the items. Further details on scale analysis and
questionnaire validity can be found in Olivencia-Carrión et al. (2018).
As noted previously, the sample of 968 participants was used for both
the scale and factor analysis and for the weighted regression analysis.
2.5. Temperament and character inventory revised (TCI-R; Cloninger et al.,
1993)
This questionnaire consists of 240 items (5 of these on validity),
with a 5-point Likert-type response scale, grouped into 4 temperament
dimensions (NS, HA, RD, and P) and 3 character dimensions (SD, C and
ST). This instrument has been validated in a general Spanish population
(Gutiérrez-Zotes et al., 2004) and has satisfactory psychometric prop-
erties (Pelissolo et al., 2005).
3. Results
In order to meet required normality assumptions, Factors 2, 3 and 4
were log-transformed to reduce their original skewness. After these
transformations, the residuals of every regression model presented in
this section are normally distributed. Regression models were computed
using R (R Core Team, 2017), and the packages sampling(Tillé and
Matei, 2015) and survey(Lumley, 2014; Lumley, 2004). Partial cor-
relations and R-squared coecients were obtained using the SSE-based
approach (Efron, 1978) and computed in R using the package rsq
(Zhang, 2017). Linear regression models obtained for all of the factors
of the scale using calibration weighting on the Andalusia population
totals are displayed in Table 1.
The main outcomes to emerge from these regression analyses are
the following: a) Cooperativeness signicantly reduces nomophobic
levels, particularly for Factor 1, and b) Reward Dependence appears to
increase nomophobic levels for all of the factors, but primarily for
Factors 1 and 2, where its eect is signicantly non-null.
The role of the remaining personality characteristics present in TCI-
R is unclear according to the models. However, several results are
worth noting: First, Novelty-Seeking was important for Factor 3 as a
nomophobia-enhancing characteristic. Second, Harm Avoidance, Self-
Transcendence, and Persistence (of marginal signicance) were im-
portant for the same factor. Based on the R-squared values, the model
for Factor 3 is the most explanatory (explaining 0.1460, i. e. 14.6% of
the variability). However, R-squared values for all models are generally
low, meaning that non-controlled variables could be having a great
impact on nomophobia.
The model used to explain the behaviour of the total scale revealed
that Reward Dependence and Cooperation are statistically signicant
contributors, with the former being positively linked to nomophobia,
and the latter having a negative correlation with this pathology.
Persistence also emerged as a marginally signicant (in statistical
terms) addiction enhancer.
4. Discussion
The main purpose of the present study was to examine the re-
lationship between temperament and personality in nomophobia. Our
study showed that Cooperation (C) signicantly reduces Nomophobic
levels for two of the various factors measured (Mobile Phone Addiction
and Negative Consequences), whereas RD appears to increase nomo-
phobic levels for all factors. Other variables such as Novelty Seeking
M.A. Olivencia-Carrión et al. Psychiatry Research 266 (2018) 5–10
7
(NS), Harm Avoidance (HA) and Self-Transcendence (T) also show a
positive, albeit weaker, relationship with Nomophobia. Similar results
have been found in previous studies on behavioural addiction (Farré
et al., 2015). Our results, however, tend to partially refute other pre-
vious ndings. In particular, in our study we failed to nd signicant
dierences in terms of the Self Directedness (SD) dimension, although
the Persistence (P) character dimension emerged as a marginally sig-
nicant addiction enhancer.
The NS dimension increases the score on the negative consequences
factor. These results have been observed in other studies of diverse
substance and behavioural addictions (Farré et al., 2015; Gutiérrez
et al., 2016; Lee et al., 2012; Lu et al., 2014; Reynolds et al., 2006). NS
has been dened as the tendency to seek reward signals and strong new
sensations about unknown stimuli. Individuals with high NS scores tend
to be impulsive, enthusiastic, exploratory, and curious. Hence, in-
dividuals high on NS may be more likely to be involved in frequent
communication by mobile phone, which is directly related to nomo-
phobia.
Regarding HA, the present study conrmed that high scores tend to
be associated with an increase in the Negative Consequences factor. HA
is considered as the tendency to respond to aversive stimuli with in-
hibition in order to avoid suering, punishment, and frustration. High
scorers are regarded as apprehensive worriers that have strong feelings
of anxiety during unpredictable situations (Cross et al., 2011). Only a
few studies have found an increase of HA in nomophobic individuals;
nonetheless, the current results are consistent with other studies that
have found a link between HA or feelings of anxiety with substance
abuse or behavorial addiction (Mok et al., 2014; Gutiérrez et al., 2016).
Thus, overall it appears that temperament and character can have a
substantial impact on career, relationships, and mental health.
It is important to note that in the current study the RD dimension
was higher in nomophobics, primarily in the mobile phone addiction
and loss of control factors. RD is dened as the tendency to respond
constantly and intensely to signals of reward and avoid punishment,
showing a sensitivity to threat cues. It has also been further classied as
a tendency towards pessimism and having feelings of anxiety in un-
predictable situations. There are too little data in the literature on this
dimension to determine if this nding could be linked to other studies.
To our knowledge, the only available study for comparison is the one
reported by Walther et al. (2012) that established lower levels of RD
among Internet addicts. However, Aluja and Blanch (2011) associate
RD with extraversion, and thus our results are consistent with the work
of other authors (Olivencia-Carrión et al., 2016; Takao, 2014; Walther
et al., 2012) who have found that extraversion predicts addictive be-
haviours.
The C character dimension emerges as a characteristic that sig-
nicantly reduces levels of nomophobia, particularly for the factors of
mobile phone addiction and negative consequences. In the present
study, non-dependent excessive users were characterized by high levels
of C, which suggests that this category includes people who are more
socially tolerant, empathic, helpful, and compassionate. Thus, they may
be more likely to have peers to communicate with Lu et al. (2014)
which has been suggested to be a protective factor for mental health
(Gutiérrez et al., 2016). Individuals high on C have been described as
socially tolerant, empathic, helpful, and compassionate, as opposed to
intolerant, callous, unhelpful, and vengeful. Cooperativeness has been
used to describe people who show unconditional acceptance of others,
empathy with others' feelings, and willingness to help without a desire
for selsh domination. Cloninger et al. (1993) regarded high coopera-
tiveness as a sign of psychological maturity and advanced moral de-
velopment. Cooperativeness is assessed using ve subscales in the
Temperament and Character Inventory: 1) Social acceptance vs. intol-
erance (C1); 2) Empathy vs. social disinterest (C2); 3) Helpfulness vs.
unhelpfulness (C3); 4) Compassion vs. revengefulness (C4), and 5)
Principles vs. self-advantage (C5). It has been found that drug depen-
dence is associated with lower C scores (Evren et al., 2007). It has also
Table 1
Regression models weighted with ranking calibration on age group, gender, and education level for Andalusia.
Factor 1 Factor 2 Factor 3 Factor 4 Total scale
(Mobile phone abuse) (Loss of control) (Negative consequences) (Sleep interference)
(Intercept) β
0
11.55
⁎⁎⁎
1.89
⁎⁎⁎
1.57
⁎⁎⁎
1.20
⁎⁎⁎
24.10
⁎⁎⁎
Std. Err. (0.14) (0.02) (0.02) (0.02) (0.32)
Novelty-seeking β
1
0.24 0.00 0.05
⁎⁎
0.05 0.40
Std. Err. (0.20) (0.04) (0.02) (0.03) (0.48)
Partial cor. 0.1852 0.0990 0.2080 0.1239 0.1449
Harm avoidance β
2
0.20 0.01 0.05*0.05 0.43
Std. Err. (0.22) (0.04) (0.02) (0.05) (0.57)
Partial cor. 0.1778 0.1003 0.1575 0.0642 0.1423
Reward dependence β
3
0.44
⁎⁎
0.06*0.03
+
0.01 1.04
⁎⁎
Std. Err. (0.17) (0.02) (0.01) (0.02) (0.36)
Partial cor. 0.2561 0.1947 0.1529 0.0000 0.2388
Persistence β
4
0.20 0.04 0.04
+
0.00 0.73
+
Std. Err. (0.18) (0.03) (0.02) (0.02) (0.41)
Partial cor. 0.1862 0.1529 0.1694 0.0000 0.1806
Self-directedness β
5
0.29 0.02 0.01 0.01 0.26
Std. Err. (0.19) (0.03) (0.02) (0.03) (0.45)
Partial cor. 0.1950 0.1023 0.1126 0.0000 0.1386
Cooperativeness β
6
0.57
⁎⁎
0.03 0.04*0.03 1.12*
Std. Err. (0.20) (0.02) (0.02) (0.03) (0.44)
Partial cor. 0.2732 0.1341 0.1654 0.0781 0.2295
Self-transcendence β
7
0.05 0.01 0.07
⁎⁎⁎
0.03 0.24
Std. Err. (0.15) (0.02) (0.02) (0.03) (0.35)
Partial cor. 0.1689 0.1026 0.2540 0.0619 0.1366
SSE-based R-squared 0.0977 0.0474 0.1460 0.0530 0.0833
Model deviance 5047.79 110.36 54.75 97.54 27,106.17
Dispersion 5.26 0.12 0.06 0.10 28.27
Number of observations (n) 960 960 960 960 960
⁎⁎⁎
p< 0.001,
⁎⁎
p< 0.01,
p< 0.05,
+
p< 0.1
M.A. Olivencia-Carrión et al. Psychiatry Research 266 (2018) 5–10
8
been found that Schizophrenia patients have lower C scores than con-
trols (Calvo de Padilla et al., 2006; Glatt et al., 2006; Molina et al.,
2017). Similarly, most individuals with personality disorders (e.g.,
obsessive compulsive disorder) are low in C, show poor interpersonal
functioning, and are described as intolerant, narcissistic, hostile or
disagreeable, critical, unhelpful, or vengeful (Kim et al., 2009).
Finally, the ST character dimension appears increase the score on
the factor of Negative Consequences. ST can be dened as having
spiritual maturity and the desire for spiritual realization, along with the
capacity for meditation and non-materialistic thinking. Moreover, it has
been linked to high levels of life satisfaction, which was highlighted in
some studies (Cloninger et al., 1993) mentioned in the literature re-
view.
Nomophobia can be considered within the framework of non-sub-
stance behaviour addictions. It could be described as a syndrome ana-
logous to substance addiction, but with a focus on a certain behaviour
which, similar to substance consumption, produces short-term reward
and may persist despite harmful consequences (due to diminished
control over the behaviour). The DSM-5 (APA, 2013) broadens the
category of Substance-Related Disordersto Substance Use and Ad-
dictive Disordersincluding substance and non-substance-related ad-
dictions. However, non-substance behaviour addictions currently only
include pathological gambling.
There are no specic and agreed diagnostic criteria for non-sub-
stance behaviour addictions like nomophobia, although clinical ex-
perience shows that the excessive use of new technologies is a real
problem that seriously aects certain individuals. Once again, history
repeats itself: Gambling was recognized as a nosological entity in 1980,
when the APA introduced it under the name of "pathological gambling";
however, its existence was recognized by professionals much earlier.
Currently only pathological gambling is recognized as a non-substance
behaviour addiction, whereas the remaining addictions without sub-
stance use (such as the newly emerged internet and mobile phone use)
are still subject to controversy and confusion. However, from clinical
experience, it is clear that the abusive use of new technologies (mobile
or internet) is a real problem that seriously aects people who suer
from it (Sánchez-Carbonell et al., 2008).
The acknowledgement of behavioural addictions can be traced as
far back as Marlatt et al. (1988) who referred to a repetitive habit
pattern that increases the risk of disease and/or associated personal and
social problems. Addictive behaviours are often experienced sub-
jectively as a loss of control and persistence of the behavour despite
volitional attempts to abstain or achieve moderate use. Furthermore, in
the last decade, a growing amount of research has established psy-
chological and neurobiological similarities between the excessive
practice of these behaviours (e.g., mobile phone abuse/nomophobia,
shopping, sex, internet, video gambling, and eating) and addictive
patterns of use (Billieux et al., 2010; Mentzoni et al., 2011). Research
on the neurobiology of addiction has revealed the existence of a
common mechanism between substance addictions and behavioural
addictions (Leeman and Potenza, 2013; Weinstein and Lejoyeux, 2015).
The problem is that the relationship between the substances that are
included within the diagnostic criteria and those behaviours that are
supposed to be addictive is unknown, because the latter are not in-
cluded in the DSM-5. However, there is now enough evidence to suggest
that alcohol, drugs, and pathological gambling are not the only crip-
pling addictions. Addiction statistics are scarce because many destruc-
tive habits are not yet ocially recognized as addictions, these include
mobile phone addiction/nomophobia, gaming, eating, shopping, and
sex, all of which are problematic for a number of reasons. Some of them
involve direct manipulation of pleasure through the use of products that
are ingested into the body, such as drug use disorders and food-related
disorders. The diculty we have is that we do not know to what extent
these behaviours are addictive because they are not included in the
DSM-5 (APA, 2013) or any other diagnostic tool. Nevertheless, the aim
of our study was to examine the relationship between temperament and
personality in nomophobia. This in turn commits us to advance along
the path of nomophobia research and treatment. A denition of no-
mophobia must take into account the following symptoms: text message
abuse; high frequency of use, spending more than 4 hours per day using
the mobile phone (using the mobile phone all of the time) to cope with
negative emotions or problems or to feel better; showing extreme ner-
vousness and aggressive behaviour when deprived of or unable to use
the mobile phone; progressive deterioration in school/work and social
and family functioning; and impairment in self and social perception.
Our results should be evaluated in the context of several limitations
including that the Questionnaire to Assess Nomophobia (QANIP;
Olivencia-Carrión et al., 2018) employed in the present study requires
further psychometric evaluation. Nevertheless, the scale has been found
to have excellent psychometric properties and oers a concise measure
of nomophobia for use in future studies. Third, even those individuals
who are interested in seeking therapeutic change and admit to negative
personality characteristics sometimes portray themselves in an overly
positive light. Thus, when nomophobes are rewarded for a positive
presentation of themselves, the possibility for a dishonest response style
increases. Therefore, one limitation of this study refers to the accuracy
of participantsresponses, since all of our measures relied upon self-
report.
5. Conclusion
There is a relationship between nomophobia and personality. In
particular, the probability of presenting nomophobia increases when an
individual has high RD scores, and decreases when the person has high
C scores. Other variables such as NS, HA and ST also appear to show
positive, albeit weaker, relationships with several nomophobic factors.
Undoubtedly, prevention and/or intervention techniques should target
personality traits, since these appear to have an impact on the devel-
opment of nomophobia.
Funding
No source of funding.
Declaration of interest
None to declare.
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Addictive behaviors have traditionally been associated with low self-esteem, and Problematic Smartphone Use (PSU) has recently received increasing scientific attention as a potential behavioral addiction. The present meta-analysis aims to examine the strength of the relationship between PSU symptoms and global self-esteem. A keyword-based systematic literature search was performed to identify studies in which PSU symptoms and global self-esteem were assessed. Thirty-one independent studies with a total of 27.004 participants (F % = 54.21%; mean age = 17.37 ± 4.97; range: 12.10–34.39 years old) were included. Meta-analytic results of the random effects model applied to a total of 31 independent samples show a negative correlation between self-esteem and PSU (Fisher's Z = −0.25; CI -0.28, −0.21; Z = −14.63; p < 0.001). Age, gender and geographical area did not moderate the association. The magnitude of the effect size can be considered small according to Cohen's criteria (1992), and medium according to Hemphill's criteria (2003). The sensitivity analysis and analyses of publication bias confirm that these results are robust. The findings show that low self-esteem is an important hallmark of PSU. Overall, our findings emphasize the importance of addressing self-esteem and corresponding core beliefs in the prevention and treatment of PSU.
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Background: Smartphone use patterns may predict daily life efficacy and performance improvements in sports. Additionally, personal characteristics may be associated with smartphone overuse. Methods: We investigated the correlation between the temperament and character inventory (TCI) and academic performance using smartphone log data. We hypothesized that the elite and general groups, divided based on academic performance, differed according to the TCI and downloadable smartphone apps (applications). Additionally, we hypothesized a correlation between smartphone app usage patterns and TCI. A total of 151 students provided smartphone log data of the previous four weeks. They also completed the TCI and provided academic records of the previous year. Results: The first and second most frequently used apps by both groups of students were social networking and entertainment, respectively. Elite students scored higher on novelty seeking, reward dependence, persistence, self-directedness, and self-transcendence than general students. In all participants, the usage time of serious apps was correlated with the scores for novelty seeking (r = 0.32, P < 0.007), reward dependence (r = 0.32, P < 0.007), and self-transcendence (r = 0.35, P < 0.006). In the elite group, the usage time of serious apps was correlated with the scores for novelty seeking (r = 0.45, P < 0.001), reward dependence (r = 0.39, P = 0.022), and self-transcendence (r = 0.35, P = 0.031). In the general group, the usage time of serious apps was correlated only with self-transcendence (r = 0.32, P < 0.007). Conclusion: High usage time of serious apps can help sports majors to excel academically. Particularly among sports majors, serious apps are related to activity, the desire for rewards and recognition, and the tendency to transcend themselves.
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The fear of being without a mobile phone has emerged as a global psycho-social phenomenon impacting smartphone users and their behaviour. Determining whether higher levels of nomophobia are associated with an increased likelihood of illegal smartphone use in vehicles may provide driver licencing authorities with avenues to reduce risk by developing programs and training aimed at mitigating nomophobia. This study builds upon a previous analysis that revealed only one of nomophobia's four factors—the fear of being without access to information—predicted the likelihood of illegal smartphone use while driving. By measuring total nomophobia scores in terms of severity, not factors, this study identified a stronger relationship than previously thought between driver's illegal smartphone use and the fear of being without a mobile phone. Indeed, using a sample of 2773 Australian smartphone users from the state of Victoria, individuals with ‘severe’ nomophobia were 85% more likely to engage in illegal use while driving. In other words, the odds of engaging in illegal smartphone use among those with severe nomophobia increased by a factor of 6.6. Given the global prevalence of severe nomophobia is over 20%, these findings become significant for road users around the world, especially in low to middle income countries where 90% of road traffic deaths occur. Developing educational and/or behavioural programs reducing nomophobia may reduce road traffic deaths.
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Identifying endophenotypes of schizophrenia is of critical importance and has profound implications on clinical practice. Here we propose an innovative approach to clarify the mechanims through which temperament and character deviance relates to risk for schizophrenia and predict long-term treatment outcomes. We recruited 61 antipsychotic naïve subjects with chronic schizophrenia, 99 unaffected relatives, and 68 healthy controls from rural communities in the Central Andes. Diagnosis was ascertained with the Schedules of Clinical Assessment in Neuropsychiatry; parkinsonian motor impairment was measured with the Unified Parkinson’s Disease Rating Scale; mesencephalic parenchyma was evaluated with transcranial ultrasound; and personality traits were assessed using the Temperament and Character Inventory. Ten-year outcome data was available for ~40% of the index cases. Patients with schizophrenia had higher harm avoidance and self-transcendence (ST), and lower reward dependence (RD), cooperativeness (CO), and self-directedness (SD). Unaffected relatives had higher ST and lower CO and SD. Parkinsonism reliably predicted RD, CO, and SD after correcting for age and sex. The average duration of untreated psychosis (DUP) was over 5 years. Further, SD was anticorrelated with DUP and antipsychotic dosing at follow-up. Baseline DUP was related to antipsychotic dose-years. Further, ‘explosive/borderline’, ‘methodical/obsessive’, and ‘disorganized/schizotypal’ personality profiles were associated with increased risk of schizophrenia. Parkinsonism predicts core personality features and treatment outcomes in schizophrenia. Our study suggests that RD, CO, and SD are endophenotypes of the disease that may, in part, be mediated by dopaminergic function. Further, SD is an important determinant of treatment course and outcome.
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The purpose of this study was to identify personality factor-associated predictors of smartphone addiction predisposition (SAP). Participants were 2,573 men and 2,281 women (n = 4,854) aged 20–49 years (Mean ± SD: 33.47 ± 7.52); participants completed the following questionnaires: the Korean Smartphone Addiction Proneness Scale (K-SAPS) for adults, the Behavioral Inhibition System/Behavioral Activation System questionnaire (BIS/BAS), the Dickman Dysfunctional Impulsivity Instrument (DDII), and the Brief Self-Control Scale (BSCS). In addition, participants reported their demographic information and smartphone usage pattern (weekday or weekend average usage hours and main use). We analyzed the data in three steps: (1) identifying predictors with logistic regression, (2) deriving causal relationships between SAP and its predictors using a Bayesian belief network (BN), and (3) computing optimal cut-off points for the identified predictors using the Youden index. Identified predictors of SAP were as follows: gender (female), weekend average usage hours, and scores on BAS-Drive, BAS-Reward Responsiveness, DDII, and BSCS. Female gender and scores on BAS-Drive and BSCS directly increased SAP. BAS-Reward Responsiveness and DDII indirectly increased SAP. We found that SAP was defined with maximal sensitivity as follows: weekend average usage hours > 4.45, BAS-Drive > 10.0, BAS-Reward Responsiveness > 13.8, DDII > 4.5, and BSCS > 37.4. This study raises the possibility that personality factors contribute to SAP. And, we calculated cut-off points for key predictors. These findings may assist clinicians screening for SAP using cut-off points, and further the understanding of SA risk factors.
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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.
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Background: Although a mobile phone is useful and attractive as a tool for communication and interpersonal interaction, there exists the risk of its problematic or addictive use. Objectives: This study aims to investigate the correlation between the big-five personality domains and problematic mobile phone use. Materials and Methods: The Mobile Phone Problem Usage Scale and the NEO Five-Factor Inventory (NEO-FFI) were employed in this study. Survey data were gathered from 504 university students for multiple regression analysis. Results: Problematic mobile phone use is a function of gender, extraversion, neuroticism, openness-to-experience; however, it is not a function of agreeableness or conscientiousness. Conclusions: The measurement of these predictors would enable the screening of and intervening in the potentially problematic behaviors of mobile phone users.
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Background: On the way toward an agreed dimensional taxonomy for personality disorders (PD), several pivotal questions remain unresolved. We need to know which dimensions produce problems and in what domains of life; whether impairment can be found at one or both extremes of each dimension; and whether, as is increasingly advocated, some dimensions measure personality functioning whereas others reflect style. Method: To gain this understanding, we administered the Temperament and Character Inventory to a sample of 862 consecutively attended outpatients, mainly with PDs (61.2%). Using regression analysis, we examined the ability of personality to predict 39 variables from the Life Outcome Questionnaire concerning career, relationships, and mental health. Results: Persistence stood out as the most important dimension regarding career success, with 24.2% of explained variance on average. Selfdirectedness was the best predictor of social functioning (21.1%), and harm avoidance regarding clinical problems (34.2%). Interpersonal dimensions such as reward dependence and cooperativeness were mostly inconsequential. In general, dimensions were detrimental only in one of their poles. Conclusions: Although personality explains 9.4% of life problems overall, dimensions believed to measure functioning (character) were not better predictors than those measuring style (temperament). The notion that PD diagnoses can be built upon the concept of “personality functioning” is unsupported.