Interacción entre el uso y la adicción a las redes
sociales y teléfonos móviles entre estudiantes
universitarios
Interaction between the use of and addiction to social media and
mobile phones among university students
Fuensanta López Rosales
Innovation and Evaluation in Health Psychology, Autonomous University
of Nuevo Leon, Mexico
fuensanta.lopezrs@uanl.edu.mx
José Luis Jasso Medrano
Center for Research in Nutrition and Public Health, Autonomous
University of Nuevo Leon, Mexico
jose.jassomd@uanl.edu.mx
doi: https://doi.org/10.36825/RITI.07.14.007
Recibido: Julio 31, 2019
Aceptado: Octubre 02, 2019
Resumen: El objetivo del presente estudio es analizar los principales
usos de las redes sociales entre hombres y mujeres, de acuerdo con las
horas diarias de uso y la conducta adictiva de las redes sociales. Se
aplicó un cuestionario de adicción a las redes sociales a
una muestra de 466 participantes. Del total, el 60.5% eran mujeres y
el 39.5% eran hombres. Se informaron diferencias significativas en el
modelo lineal entre los usos principales y el comportamiento adictivo
y las horas de uso. Además, se encontró una relación
significativa entre el uso, la adicción a las redes sociales y
los teléfonos móviles en hombres y mujeres. En
conclusión, existen diferencias específicas entre los usos
principales con el comportamiento adictivo y las horas diarias de uso.
Aunque la popularidad del uso de las redes sociales aumenta
significativamente, los factores de riesgo del uso poco saludable
también aumentan.
Palabras clave: Adicción, Redes Sociales, Móvil, Género,
Jóvenes.
Abstract: The objective of the present study is to analyze the main uses
of social media among men and women, according to the daily hours of
use and the addictive behavior to social media. A questionnaire of
addiction to social media was applied to a sample of 466 participants.
Of the total, 60.5% were women and 39.5% were men. Significant
differences were reported in the linear model between the main uses
and the addictive behavior and the hours of use. In addition, a
significant relationship was found between the use, addiction to
social media and to mobile phones in men and women. In conclusion,
there are specific differences between the main uses with addictive
behavior and the daily hours of use. Although the popularity of the
use of social media increases significantly, the risk factors of
unhealthy use also increase.
Keywords: Addiction, Social Media, Mobile Phone, Gender, Young People.
1. Introduction
1.1. Internet Addiction
During the last decades, information and communication technologies
(ICTs) have been a precursor of innovations that have emerged in
society thanks to the connectivity and interactivity they offer [1]
[2]. These technologies have mainly influenced young people who have
incorporated them in their training, socialization and entertainment,
especially everything related to the Internet [3] [4] [5]. Regarding
the use of ICTs, the mode that has increased its popularity is social
media, known to be virtual communities where profiles are created and
individuals can interact with other people, being mainly used to
maintain contact with others and share things [4] [6].
However, despite the fact that technology offers benefits for young
people, it also has involved negative aspects. An example that has
been reported and investigated in recent years is addictive behavior
or Internet addiction [7] [8]. It is considered an addiction when
there is excessive use, loss of control, withdrawal symptoms,
tolerance, and negative repercussions in daily life, associated with
loss of control, sleep deprivation, carelessness, and loss of interest
in other activities, decrease of physical activity, attention focus,
as well as anxiety to stay connected [9] [10]. Among the explanations
of addiction is the biopsychosocial perspective by Griffiths that
takes into consideration both psychosocial components, focused from
the cognitive-behavioral and socio-cognitive model, and biological
components, focused from the neuroscientific perspective [11] [12]
[13].
The study about Internet addiction has found relationships with some
factors such as the presence of comorbid psychiatric symptoms, the
specific use of Internet applications, and demographic elements such
as age [14]. Although it has not been recognized as a disorder
established in the review of the Diagnostic and Statistical Manual of
Mental Disorders (DSM), it has been considered as a behavioral problem
of particular growth among adolescents and young people [15] [16].
Currently, there are still debates about the term addiction, so other
terms have been used to describe the phenomenon, including:
problematic, compulsive or pathological use [17]. Unlike addictions to
substances, the Internet offers many benefits in our society, being a
necessary element today. This is why the extent of the impact due to
the complex diagnosis is just starting to be understood [18]
[19].
1.2. Addictive behavior to social media and problematic use of
Mobile phone
Addictive behavior to social media is considered as a subtype of
Internet addiction, sharing its characteristics with the use of
digital social media [20]. Among the main warning signs that they
share with Internet addiction are sleep deprivation, neglect of
important activities, loss of the notion of time, and constant
thoughts about what is happening in the social media, among others.
[8] [9]. Social media is considered the main internet activity of
Internet users in Mexico, so it is important to distinguish their
study. The Internet user population has increased significantly,
especially among young people. In 2017, the average daily connection
to Internet time was 8 hours and 1 minute, 47 minutes more than the
previous year, so its increase has been significant in recent years. A
total of 79% of Internet users access social media; Facebook,
WhatsApp, Youtube, and Twitter being the most popular [21].
Some authors distinguish different subtypes of Internet addiction
[22]. It seems that the main characteristics between the different
media could differentiate some important aspects related to addictive
behavior. For example, a strong relationship has been found between
Internet addiction and addiction to social media, however,
extraversion is a specific characteristic that is frequently shown
among social media users [23]. Some authors even make the observation
to differentiate between adaptation and technological addiction,
questioning whether the excessive use of social media could cause
serious consequences, just as other types of Internet addiction such
as video games [22].
However, some questions also arise regarding technology addiction. It
is considered that the use of technology is rather a means that allows
people to practice particular behaviors, such as the use of social
media. Therefore, the dependence on social media is related to its
content and not to the technology itself [24] [25].
The use of the mobile phone and being attached to it represents the
person cognitively and behaviorally, with characteristics of constant
thought and use, being similar to a behavioral addiction but without
pathologization consequences [26]. The use of mobile devices is
considered as a possible predictor of Internet addiction, since easy
connectivity to the Internet is related to the increase of interest
and excessive use, being able to produce a greater dependence than the
use of the computer [2] [9] [13] [27] [28] [29] [30].
1.3. Present study
Internet access devices in Mexico have been changing priority over
the years. According to the Asociación de Internet MX [21], 90%
of Mexican Internet users are mobile phone users, the mobile being the
most popular device. Laptops are used by 73% and desktop computers by
42%, while tablets are used by 52% of Mexican Internet users.
Adolescents and young people are the main Internet and social media
users, representing 39% of all Mexican Internet users [21].
Although the phenomenon is a subject that has brought the attention
of researchers, there is still a lot to study in this area. A common
limitation found among the studies about social media is that many
researches have focused only on Facebook, taking it as a synonym of
social media, leaving out other social media that may be important to
the population [11]. In the same way, sometimes the term addiction is
not clear, considering excessive use and addiction as part of the same
phenomenon. The differentiation between engagement or non-pathological
use could be a way to help answer the questions about addiction to
social media [12]. It has been found that frequent use is not
necessarily a predictor of addictive behavior, although it may be one
of the risk factors that produces the phenomenon [24] [31]. The
present study aims to analyze the main uses of social media between
men and women, according to their daily hours of use and their
addictive behavior to social media in order to know the panorama that
implies its use. It is expected that differences will be found between
uses and genders.
2. Method
2.1. Participants
The sample consisted of 466 participants with an average age of 19.80
(SD = 1.77), 60.5% were female (282) and 39.5% male (184). The
main social media reported as used by the participants were: WhatsApp
(59.4%), Facebook (31.1%), Twitter (3.5%) and Youtube (3%). Among the
main uses and activities in social media were: interacting with
friends (37.4%), entertainment (16.7%), interacting with their partner
(13.4%), and with classmates (10.6%).
Subjects were selected as they met the inclusion criteria. As
inclusion criteria, young people were required to be between 18 and 24
years of age, who at the time of the application were university
students, who were users of social media, and who agreed to
participate through informed consent.
2.2. Instruments
The instrument used was the Social Media Addiction (SMA)
questionnaire of Escurra y Salas [32]. It is a scale that consists of
24 Likert-type items with a range of 5 points (from 1 "never" to 5
"always"). The instrument is designed to evaluate the addiction to
social media in university students; it includes items such as "I feel
a great need to stay connected to social media" and "I feel anxious
when I cannot connect to social media." Most of the items had the same
direction, except for item 13, "I can disconnect from social networks
for several days", so it was reversed to measure the items in the same
direction and have a total score. The total internal consistency of
the scale was α = .93, so it is considered to have excellent reliability.
Mobile Phone Problem Use Scale (MPPUS-10) was originally created by
Bianchi and Phillips [33] and adapted to its short version by
Foerster, Roser, Schoeni and Röösli [34]. The short version
consists of 10 Likert-scale items with a range of ten points, ranging
from "not entirely true" to "extremely true". The items are related to
the tolerance of the mobile phone, withdrawal syndrome, evasion, and
negative consequences in life. The scale was adapted to Spanish by
López-Fernández, Honrubia-Serrano and Freixa-Blanxart [35].
Due to the adaptation to this language, the writing of the items was
adapted for a better understanding for our sample (for example, the
word cell phone was used instead of mobile). It includes items such as
"I find it difficult to turn off my cell phone" and "My friends and
family complain because I use the cell phone a lot." The internal
consistency of the instrument in the present study was α = .88, which is why it is considered reliable due to its high
consistency.
To measure the daily hours of social media use, the items were added
within the sociodemographic data: "How many hours do you estimate that
you dedicate to your social media?". The main uses were measured by
the question "What is the main use that you give to your social
media?", offering different options and including the option "other"
to respond openly.
2.3. Procedure
Students were invited to participate in the survey with prior
authorization from the universities. The questionnaire was applied
through an online platform. The general objectives of the study were
explained and they were given instructions on how to access and
respond to the survey. The first page obtained the informed consent
allowing the participants to accept or reject in order to respond to
the survey. Once the participants agreed, they could begin to answer
the questions. The participants had to answer all the questions before
finalizing the survey. The anonymity of their answers was guaranteed.
The research and ethical aspects were approved by the corresponding
committee.
2.4. Data analysis
At first, the measurement of each one of the variables was indicated
by the sum and average of the items of the scales through the
statistical software SPSS. The adjustment of the distributions to a
normal curve was contrasted by the test of Kolmogorov-Smirnov. After
the review of the normality adjustment analysis and descriptive data
of the sample, non-parametric Mann-Whitney test analysis was perfomed
to analyze the comparison between males and females and Kruskal-Wallis
test to compare the main uses of social media. Secondly, it is
analyzed by means of a general linear model comparing daily hours of
use, addictive conduction to social networks and problematic use of
mobile among the main uses of social networks and sex. Finally,
Spearman’s nonparametric Rho correlation was used to analyze the
relationship between the variables of interest. Also, linear
regression analysis was perfomed.
3. Results
First, reliability and normality analysis of the scales was performed
(see Table 1). The scale of addiction to social media had an excellent
consistency (α = .94), however, the distribution did not adjust to a normal
curve (ZK-S = .06, p <.01). After the analysis, an average of 2.36
(SD = .70) was reported in the total score. On the other hand, the
hours dedicated to social media reported was 7.11 hours (SD = 4.68);
it did not adjust to a normal curve either (ZK-S = .16, p <.01).
Finally, to analyze the age range, an average of 19.80 years of age
was reported (SD = 1.77), without adjusting to a normal curve (ZK-S =
.20 p <.01).
Table
1. Descriptive statistics and normality test.
|
|
Total |
Female |
Male |
Z
K-S |
|||
|
M |
SD |
M |
SD |
M |
SD |
||
|
1 |
2.36 |
0.71 |
2.36 |
0.72 |
2.36 |
.71 |
.06* |
|
2 |
7.11 |
4.68 |
7.57 |
4.72 |
6.39 |
4.51 |
.16* |
|
3 |
4.16 |
1.92 |
4.03 |
1.91 |
4.37 |
1.93 |
.08* |
|
4 |
19.80 |
1.77 |
19.66 |
1.71 |
20.01 |
1.84 |
.20* |
1. SMA; 2. Hours of use; 3. MPPUS; 4. Age.
Range: SMA=1-5; MPPUS=1-10. Level of Significance * p < .01
In order to analyze if there are differences between the variables
and gender, the non-parametric Mann-Whitney test was performed, since
it did not fulfill a normal distribution. No significant difference
was found in the addictive behavior between male and female (Z = -
102, p = .919), however a difference was reported in the daily hours
of use (Z = -3.04, p <.01). Males reported fewer hours than
females. Finally, the age difference was analyzed, finding that
females averaged younger age than males (Z = -2.22, p <.01).
In order to analyze the different main uses regarding the use and
addictive behavior of social media, the uses were divided in 11
different categories. It was necessary to reduce the categories where
the type of use could overlap, so it was re-categorized as follows:
The categories were divided into 1) using social media to maintain
contact with their sentimental partner; 2) with your friends; 3)
relatives; 4) with classmates and / or coworkers); 5) Share and
express about your day to day activities; 6) meet people; 7) view
content of your contacts; 8) watch entertainment content; 9) follow
public figures; 10) carry out activities related to work; and 11)
other uses. It was observed that the most popular uses reported by
young people were: being in contact with friends (36.5%), followed by
entertainment (16.3%), and being in contact with the sentimental
partner (13.1%). Female and male participants reported a similar
distribution among the main uses, agreeing with the Pearson Chi-square
analysis to measure the relationship between categories and gender,
reporting no statistically significant difference (χ2 [10] = 14.06, p =. 17).
3.1. Main uses of social media and its interaction with daily hours
of use and gender
The young people who reported the most hours of daily use reported sharing and expressing themselves as the main use of social media, in addition to following celebrities, brands, or products. Females who spent more time on social media showed sharing and expressing themselves as their main use, following celebrities
and meeting people; male results were see content, follow products or celebrities
and share and express themselves. The uses that involved spending less daily hours were being in
contact with family, colleagues and other uses. Females agreed with
these uses, however males reported meet people, work and other uses (see Table 2).
Table
2. Hours of daily use according to the main uses of social media.
|
Use |
Female |
Male |
Total |
|||
|
M |
SD |
M |
SD |
M |
SD |
|
|
1. Partner |
8.26 |
4.79 |
6.48 |
4.03 |
7.59 |
4.57 |
|
2. Friend |
8.14 |
4.79 |
6.60 |
4.92 |
7.53 |
4.89 |
|
3. Family |
5.50 |
3.44 |
5.57 |
4.08 |
5.52 |
3.52 |
|
4. Classmates |
6.21 |
4.37 |
5.42 |
4.30 |
5.90 |
4.31 |
|
5. Express |
11.0 |
6.84 |
7.33 |
6.56 |
9.84 |
6.80 |
|
6. Meeting |
9.00 |
5.66 |
4.14 |
3.63 |
5.22 |
4.29 |
|
7. Contacts |
7.46 |
5.11 |
8.11 |
6.37 |
7.73 |
5.52 |
|
8. Enterteinment |
6.93 |
3.74 |
7.12 |
4.03 |
7.01 |
3.84 |
|
9. Public Figures |
10.5 |
7.78 |
8.00 |
- |
9.67 |
5.69 |
|
10. Work |
8.50 |
5.92 |
4.22 |
1.48 |
5.93 |
4.30 |
|
11. Others |
4.67 |
2.78 |
5.33 |
4.16 |
4.83 |
2.98 |
|
Total |
7.57 |
4.72 |
6.39 |
4.52 |
7.10 |
4.68 |
Since normality in the distribution was not achieved, the
nonparametric test of Kruskal Wallis was performed to analyze the
difference between the categories. Significant differences were found
in the main uses of social media and addictive behavior (χ2 [10] = 19.57, p <.05). A generalized linear model was used to
analyze the hours of daily use and the variables gender and main uses
of social media using the inter-subject effects test (see Figure 1).
Significant differences were reported in the corrected model (F [21] =
1.79, p <.05, R2 = .078), reporting a moderate effect size through
the Eta square analysis (η2 = .078). Interception was significant (F [1] = 304.37, p <.001, η2 = .407). There was no significant interaction between the main use
factors and gender (F [1] = 0.76, p = .65, η2 = .017), because the use variable did not have an effect on the
daily hours (F [10] = 1.36, p = .198, η2 = .030). The tendency of women to report more daily hours of use
than men was in the activities of sharing and expressing themselves,
meeting people, following public figures and work (F [1] = 4.06, p
<.05, η2 = .030).
Figure
1. Comparison by gender of the daily hours of use according to the
main uses of social media.
3.2. Main uses of social media and their interaction with addictive
behavior and gender
In order to analyze the differences between the main uses, the
addictive behavior and gender, the descriptive analyzes were performed
first. The main use that reported the highest score in the addiction
scale to social media was meeting people through social media,
followed by viewing content from their contacts, and sharing and
expressing themselves. Females reported higher scores on the scale of
addictive behavior to social media in sharing and expressing
themselves, meeting people and seeing content. In contrast, males
reported higher scores in meeting people, entertainment and viewing
content. The uses with the lowest scores were those of contact with
family and companions, in addition to the category of other uses, for
both male and female (see Table 3).
Table
3. Addictive behavior to social media according to the main uses.
|
Use |
Female |
Male |
Total |
|||
|
M |
SD |
M |
SD |
M |
SD |
|
|
1. Partner |
2.14 |
.59 |
2.16 |
.53 |
2.15 |
.57 |
|
2. Friend |
2.41 |
.68 |
2.41 |
.71 |
2.41 |
.69 |
|
3. Family |
1.97 |
.57 |
2.41 |
.71 |
2.07 |
.62 |
|
4. Classmates |
2.11 |
.63 |
1.94 |
.51 |
2.04 |
.59 |
|
5. Express |
3.07 |
.94 |
2.33 |
.60 |
2.84 |
.90 |
|
6. Meeting |
3.04 |
.41 |
3.03 |
.42 |
3.03 |
.40 |
|
7. Contacts |
3.01 |
.64 |
2.55 |
1.04 |
2.82 |
.83 |
|
8. Enterteinment |
2.40 |
.68 |
2.56 |
.76 |
2.47 |
.71 |
|
9. Public Figures |
2.71 |
.24 |
2.21 |
- |
2.54 |
.33 |
|
10. Work |
2.73 |
.84 |
2.14 |
.71 |
2.38 |
.79 |
|
11. Others |
1.89 |
.59 |
1.93 |
.82 |
1.90 |
.61 |
|
Total |
2.36 |
.72 |
2.36 |
.71 |
2.36 |
.71 |
The nonparametric test of Kruskal Wallis was performed to analyze the
difference between the categories. Significant differences were found
in the main uses of social media and addictive behavior (χ2 [10] = 50.21, p <.001). It was analyzed using a generalized
linear model to measure the inter-subject effect test between the
addictive behavior to social media and gender, and main uses of social
media (see Figure 2). Significant differences were reported in the
corrected model (F [21] = 3.52, p <.001, R2 = .143), reporting a
moderate effect size through the analysis of Eta square (η2 = .143). Interception was also significant (F [1] = 1660.27, p
<.001, η2 = .789). There was no significant interaction between the main use
factors and gender (F [10] = 1.42, p = .17, η2 = .031). This is due to the fact that the gender variable did not
have an effect on the addictive behavior to social media (F [1] =
1.88, p = .17, η2 = .004), however it did have a significant effect with the
different uses (F [10] = 4.39, p <.001, η2 = .09).
Figure
2. Comparison by gender of the average of the Social Network
Addiction scale according to the main uses.
3.3. Main uses of social media and their interaction with the
problematic mobile use
To analyze the differences between the main uses and the problematic
mobile use between both genders, the descriptive analysis was
performed. The main use that reported the highest score was the
content of their contacts, followed by the use to meeting people.
Females and males reported higher scores on the scale of addictive
behavior to social media in meeting people and viewing contact content
(see Table 4).
Likewise, the nonparametric test of Kruskal Wallis was performed to
analyze the difference between the different uses. Significant
differences were found between the main uses of social networks and
problematic mobile phone use (χ2 [10] = 46.15, p <.001). It was analyzed using a generalized
linear model to measure the inter-subject effect test between the
addictive behavior to social media and the variables gender and main
uses of social media (see Figure 3). Significant differences were
found in the corrected model (F [21] = 2.76, p <.001; R2 = .119),
reporting a moderate size effect through the Eta square analysis
(η2 = .119). Interception was also significant (F [1] = 683.13, p
<.001, η2 = .615). No significant interaction was reported between the main
use factors and gender (F [10] = 4.29, p = .95, η2 = .009). This is due to the fact that the gender did not have an
effect on the mobile problematic use (F [1] = 0.06, p = .81, η2 = .001), however there was a significant effect with the different
uses (F [10] = 4.29, p <.001, η2 = .09).
Since a normal distribution was not fulfilled, it was decided to
analyze the relationship of the variables by Spearman's nonparametric
Rho correlation analysis (see Table 5). First, the correlation of the
variables in general was analyzed and finally analyzed divided by
gender. There was a high and significant correlation between the
addiction to social media and the mobile problematic use (rs = .75, p
<.01), however the relationship with the daily hours of use was
lower (rs = .38, p < .01 and rs = .28, p <.01). Females tended
to have higher scores on the variables in relation to the daily hours
of use.
Table
4.
Addictive behavior to social networks according to the main
uses.
|
Use |
Female |
Male |
Total |
|||
|
M |
DE |
M |
DE |
M |
DE |
|
|
1. Partner |
3.76 |
1.48 |
3.82 |
1.79 |
3.78 |
1.58 |
|
2. Friend |
4.19 |
1.96 |
4.50 |
1.88 |
4.31 |
1.93 |
|
3. Family |
3.04 |
1.68 |
3.83 |
2.04 |
3.22 |
1.76 |
|
4. Classmates |
3.45 |
1.61 |
3.32 |
0.91 |
3.40 |
1.37 |
|
5. Express |
5.11 |
2.63 |
4.62 |
1.62 |
4.95 |
2.32 |
|
6. Meeting |
6.10 |
1.27 |
5.78 |
1.34 |
5.86 |
1.25 |
|
7. Contacts |
5.65 |
1.49 |
6.20 |
3.04 |
5.87 |
2.19 |
|
8. Enterteinment |
4.19 |
1.99 |
4.59 |
1.78 |
4.37 |
1.90 |
|
9. Public figures |
4.25 |
0.64 |
2.80 |
- |
3.77 |
0.95 |
|
10. Work |
3.93 |
1.80 |
3.60 |
2.31 |
3.73 |
2.05 |
|
11. Other |
2.79 |
1.38 |
4.26 |
2.38 |
3.19 |
1.72 |
|
Total |
4.03 |
1.91 |
4.37 |
1.93 |
4.16 |
1.92 |
Figure
3. Relationship between the addictive behavior to social media,
problematic mobile use and daily hours of use.
Table
4. Matrix of bivariate correlations using the Rho coefficient of
Spearman.
|
|
|
1 |
2 |
|
General |
1. Daily hours of use |
1 |
|
|
|
2. SMA |
.38** |
1 |
|
|
3. MPPUS |
.28** |
.75** |
|
Female |
1. Daily hours of use |
1 |
|
|
|
2. SMA |
.42** |
1 |
|
|
3. MPPUS |
.32** |
.76** |
|
Male |
1 Daily hours of use |
1 |
|
|
|
2. SMA |
.31** |
1 |
|
|
3. MPPUS |
.25** |
.75** |
Level of significance ** p < .01
Finally, a simple linear regression analysis was performed among the
study variables where the addictive behavior to social media was the
dependent variable. Both variables were significant predictors. The
general regression model reported that the daily use hours explained
15% of the variance of addiction to social media and the problematic
mobile use 77% of the variance. Regarding the analysis by gender,
females reported higher prediction with daily hours, explaining 17% of
the variance, in contrast to 13% of males (see Table 6).
4. Discussion
A descriptive analysis of the study variables was conducted.
Regarding the psychometric properties, a high reliability was found
according to the internal consistency of the social media addiction
questionnaire. Regarding the average of the reported score, it was
found that, although no addictive behavior was found, the reported
score was close to the intermediate, so that some characteristics of
the addictive behavior could be present. This agrees with the
influence of social media nowadays, where young people incorporate it
on a regular basis, resulting in some problematic behaviors such as
attachment [12], without it becoming a pathological use. In the case
of the daily use of social networks, an average of 7.11 hours was
reported, supporting the hours that have been reported in Mexico
[21].
Significant differences were found between the hours of use and
gender; however, it was not reported in the addictive behavior. It has
been reported in some studies that there is no difference between the
frequency of use [36] [37], so one possible explanation is that
females reported lower age in the sample mean, a factor that has an
impact on the use of social media. Among the most popular uses of
social networks were entertainment and being in contact with friends
and partners, being similar between males and females. Regarding the
main uses, this study agrees with other studies where interactivity
with friendships is one of the preferred uses of young people [38]
[39]. On the other hand, there were no significant differences between
the uses, contrary to other studies where they found some differences
between the use among males and females [36] [37].
Before data analysis, it was necessary to re-categorize the main uses
to specifically identify the uses, without leaving aside some that
could be differentiated, so that there were a total of 11 categories
that would cover the uses reported by the young people. Among the most
popular uses in general were to be in contact with friends,
entertainment, and to be in contact with their partner. No significant
difference was reported between uses and gender, the main uses being
the same for both genders. Although there are studies that indicate
some differences, it has also been found that both males and females
use social media with similar purposes [39] [40].
One of the objectives of the study was to analyze the main uses in
addictive behavior, daily hours of use and their interaction with both
genders. The sample reported more addictive behavior, with the main
use of knowing people. Those who did not report a specific activity
reported the least addictive behavior score. On the other hand,
females reported a greater number of connection hours than males. Both
reported more daily hours dedicated to the activity of sharing and
expressing themselves. Although interaction with friends and partners
was one of the most popular uses, it did not report a greater number
of connection hours or characteristics of addictive behavior than the
other activities. Recent studies have found that the frequency of use
is directly related to leisure activities, school / work activities
and communication [41].
A difference was found among genders in the intensity of use but not
in the addictive behavior. These results agree with other studies that
have found that females are the most involved in social media
activities and are those that use them most extensively and
intensively [42] [43]. As previously reported, females spend more time
on social media to express themselves and share, while males use it to
meet people, so the trend of greater use of social media goes towards
interactivity activities within of the virtual space [41] [42].
Finally, it was found that there was a significant correlation
between the daily hours of use and addiction to social media and the
problematic mobile use in males and females, reporting greater
relationship strength in females. Thus, it seems that in women, more
technological addiction can be determined based on the intensity of
use. Likewise, we can also observe a small difference in the
regression analysis. Previous studies have analyzed this relationship
between frequency of use and addiction, finding that the frequency of
use does not determine the problematic use but it can be a predictor
of it [31]. In addition, there has been a distinction between
addictive behavior and excessive use, where psychopathological factors
are a determinant of addiction [12] [44].
It is important to give the relevance of the impact of social
networks on young people. Although the healthy use of social networks
does not necessarily affect school performance, it can have an impact
on daily activities in order to continue using social networks, even
affecting daily sleep hours [45]. In addition, inappropriate use of
social media has negative consequences in the academic, family and
social nature [41]. These negative consequences can be a risk factor,
related to the symptoms of addictive behavior [44] [46]. Moreover,
addictive behavior of social media was related and predicted by the
problematic use of mobile phone, so it is important to consider it as
a risk factor [31] [47].
In conclusion, specific differences between the main uses, the
addictive behavior, problematic use of mobile phone and the daily
hours of use were found. Although there is still debate on whether the
problematic use of social media should be included as a disorder
associated to addiction and its psychopathological meaning [15] [17],
there is scientific evidence that supports the presence of symptoms
related to addiction [25]. Although the popularity of the use of
social media increases significantly, risk factors also increase, also
increasing unhealthy use and considering it a current public health
problem [29] [48] [49]. Therefore, it is important to continue
developing research, differentiating between addictive behavior and
use of social media, and deepening the understanding of the
characteristics that make up these behaviors. Excessive use has been
considered as a non-pathological behavior, unlike addiction [12]
[44].
It is important to continue investigating the use of social media and
addictive behavior. It is essential to point out that one limitation
of the study was that there were no open interviews or focus groups,
so the qualitative and mixed approach is recommended for further
research in order to have a better understanding of the phenomenon.
Likewise, it is recommended to focus research on vulnerable
populations and propose preventive and intervention programs to
promote the healthy use of social media.
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