Introduction
The term 'sleep,' usually associated with the act of resting or the desire to do so,
can be described as the physiological and cyclical state that is part of the circadian
rhythm between sleep and wakefulness 1. It is known that during this state a progressive and repetitive reversible decrease
in consciousness occurs, accompanied by a reduction in perception and response capacity
1,2. Sleep is influenced by four different aspects: The circadian rhythm, which refers
to the time of day it occurs; the internal elements of the body, such as age and sleep
patterns; the actions the individual takes to promote or restrict sleep, and, finally,
the environment in which you sleep 3.
On the other hand, the term 'quality of sleep' is understood as good sleep and adequate
rest during the night along with optimal daytime functioning 4, that is, an optimal level of concentration and attention when performing different
types of tasks during the day. The relevance of having quality sleep is not only essential
for health but also to promote a good quality of life 5.
The Internet, evidently, has become a tool that has impacted people's lives due to
its ability to facilitate recreational, academic, work, and social activities 6. This network is the most used to communicate, inform, entertain, and relate to users
7. It has been specified that the impact of the Internet has brought positive consequences
for the advancement of virtual education, as it facilitates telecommunications and
access to information updated in real time, among other qualities 8. But with the rise in access to digital platforms, unfavorable effects also arose
as a consequence of inappropriate use of the Internet 9. Several studies mention the term "Internet addiction" (IA), which was introduced
a few decades ago by the £ well-known psychiatrist Iván Goldberg 6,7,10.
This phenomenon can be defined as a behavior characterized by developing dependence
on the state of excitement generated by excessive browsing on the Internet platform,
generating an inability to disconnect from the web, and loss of limits regarding its
use 11.
This behavior causes problematic behaviors in the performance of various daily activities,
in addition to symptomatological consequences that generate significant discomfort
on the person 12.
However, this disorder is not included in the current version of the Diagnostic and
Statistical Manual of Mental Disorders (DSM-V), due to a lack of consensus in the
delimitation of the criteria for the diagnosis and treatment of this non-chemical
addiction, despite the empirical evidence which supports the existence of behavioral
addictions 13. To remedy the aforementioned limitation, the scientific community points out that
IA, as a psychological disorder, is characterized by its lack of control in its use,
abuse, compulsive use, and abstinence 14. In the same way, they have been in charge of creating various scales to measure
IA, highlighting the Kimberly Young addiction test 15.
One of the most used instruments to measure Internet dependence is the Internet Addiction
Test (IAT), which has been translated into several languages 7,10,16. To fully understand what this instrument measures, it is necessary to clarify some
concepts: 1) Emotional needs, that is, the dependence on the Internet to receive affection
and satisfaction of needs, which generates a preference for online navigation over
real situations 16,17; 2) Loss of control, refers to the inability that the user experiences to manage
the time allocated to the use of online platforms, triggering carelessness regarding
the important duties of daily life 17.
On the other hand, various investigations have been conducted on sleep quality, with
the Pittsburgh Sleep Quality Index (ICSPS) being one that presents great versatility.
This questionnaire was developed by the Department of Psychiatry at the University
of Pittsburgh, Pennsylvania, in 1988 18. Likewise, this index has been used in research in different countries such as: Spain,
where it was applied to 275 workers in the health area, aged between 18 and 65 years
and it showed that 65.8% of the workers in this area have poor sleep quality 19. In Peru, a study was conducted where the questionnaire was applied to 211 medical
students between 18 and 28 years old and it was shown that 68.7% of those evaluated
have poor sleep quality 20.
To achieve a better understanding of this research, it is necessary to clarify some
concepts of the questionnaire, for example: Subjective sleep quality, refers to how
the person perceives the quality of their rest; sleep latency refers to the amount
of time it takes for the person to fall asleep; sleep duration, total number of hours
that the person manages to sleep during the night; sleep efficiency, time spent asleep
compared to time spent lying down 21; sleep disturbances, presence of disorders such as: insomnia, sleep apnea, hypersomnia,
or bruxism, among others; use of sleeping medications, refers to the intake of hypnotic
medications, prescribed or not, to be able to fall asleep and reduce brain activity;
and, finally, daytime dysfunction, which refers to the feeling of drowsiness during
the day and the difficulties that this generates in daily life 22.
Due to the reasons presented, the aim of this study is to analyze the effect of the
Internet on the lives of young university students, as this population is the most
prone to developing patterns of inappropriate behavior or abuse, which affect their
quality of sleep. The purpose of this research is to relate the lack of quality of
sleep with IA in university students in Ñuble, Chile.
Materials and Methodology
For this study, a quantitative, descriptive, non-experimental correlational paradigm
was used. Through non-probabilistic sampling, for convenience, a sample of 230 university
students in the health field, belonging to a private university from the region of
Ñuble, Chile, was selected. Third and fourth year students from Nursing, Nutrition
and Dietetics, Obstetrics and Childcare, Occupational Therapy and Psychology, who
had electronic devices with Internet connection, were included. Regarding the exclusion
criteria, two were applied: Students diagnosed or being treated for a mental health
pathology and students who did not complete the survey in its entirety.
Two instruments validated in the international and Chilean context were used to collect
the information. Firstly, to determine Internet addiction, the IAT was used, with
10 questions on a 6-point Likert scale (from 0 = not applicable, to 5 = always). This
questionnaire has two dimensions: Emotional Need and Loss of Control 23, and was validated, in the Latin American context, in a population of 500 people,
finding a reliability of between 0.89 and 0.94 24. In Chile, a cross-cultural adaptation and factor analysis was conducted in a population
of 425 participants, with a Cronbach's α of 0.85 25.
The second questionnaire, the ICSPS, consists of nine questions to determine whether
sleep quality is good or bad; this instrument has seven dimensions: Subjective Sleep
Quality, Sleep Latency, Sleep Duration, Habitual Sleep Efficiency, Sleep Disturbance,
Use of Sleep Medications, and Daytime Dysfunction 26. It was validated in Chile with a Cronbach's α of 0.92 27, and in Mexico, where it yielded a Cronbach's α of 0.79 28.
Data was collected using the Google Forms application using a QR code. Subsequently,
the data obtained were analyzed with the Jamovi program, using Spearman's correlation
coefficient and Chi-square as statistical tests. To preserve ethical principles, this
study obtained approval from the Scientific Ethics Committee of the university investigated
under dictum 2023-87. It is important to highlight the anonymity, privacy and confidentiality
of the information was assured following the principles established in the Declaration
of Helsinki.
Investigating Internet addiction and sleep quality in university students is crucial,
due to the increasing dependence on technology in this population. Internet addiction
can negatively impact mental and physical health, including sleep quality, which in
turn impacts academic performance and overall well-being. Understanding this relationship
will allow the development of policies and interven tion programs that promote healthy
use of the Internet, to improve sleep hygiene among students, thus contributing to
their academic success and comprehensive well-being.
Results
The sociodemographic data presented in Table 1 shows that, of the total population surveyed, 81.3% are female and the age range
is mostly between 20 and 25 years, with 88.7%. On the other hand, the majority of
respondents belong to the Nursing program, with 38.7%, where 58.3% are in their fourth
year.
Table 1
Sociodemographic Data from the Population of University Students
|
Gender prevalence
|
|
Gender
|
Prevalence
|
% of total
|
% accumulated
|
|
Femenine
|
187
|
81.3
|
81.3
|
|
Masculine
|
43
|
18.7
|
100
|
|
Career Prevalence
|
|
Nursing
|
89
|
38,7
|
38.7
|
|
Obstetrics
|
27
|
11,7
|
50.4
|
|
Nutrition
|
33
|
14,3
|
64.8
|
|
Occupational Therapy
|
21
|
9,1
|
73.9
|
|
Psychology
|
60
|
26,1
|
100.0
|
|
Grade Prevalence
|
|
Third Year
|
96
|
41,7
|
41.7
|
|
Fourth Year
|
134
|
58,3
|
100.0
|
|
Age Prevalence
|
|
15-19
|
1
|
0,4
|
0.4
|
|
20-25
|
204
|
88,7
|
89.1
|
|
26-30
|
20
|
8,7
|
97.8
|
|
31-35
|
5
|
2,2
|
100.0
|
Regarding Internet addiction, and according to their gender, it is observed that 52.2%
of women and 11.3% of men have a mild addiction, while only 1.7% of women have a severe
addiction. Regarding the academic year, 26.1% of third-year students and 37.4% of
fourth-year students show mild addiction, and both courses represent 0.9% of severe
addiction. In terms of majors, severe addiction is found in 1.3% of nursing students
and 0.4% of psychology students, with no impact on other majors.
Considering the classification of sleep quality, according to gender, it is highlighted
that 10% of women and 2.6% of men have serious sleep problems. Additionally, most
women (52.6%) need care and treatment to improve their sleep. In relation to the academic
year, 8.7% of fourth-year students and 3.9% of third-year students were found to have
severe sleep problems. Regarding the program of the participants, it was evident that
4.8% of the Nursing students, 1.7% of the Obstetrics students, 2.2% of the Nutrition
students, 0.4% of the in Occupational Therapy and 3.5% of those in Psychology have
severe sleep problems.
Regarding the correlation between Internet addiction and sleep quality, the data presented
in Table 2 represent the connection of total sleep quality with Internet addiction (r=0.154
p=0.01), demonstrating that there is a correspondence weak positive between both variables.
Table 2
Relationship between Sleep Quality and Internet Addiction in University Students
|
Sleep Quality
|
|
Internet Addiction
|
Spearman's Rho
|
0,154
|
|
|
gl
|
228
|
|
|
P Value
|
0,019
|
The data presented in Table 3 represent the relationship between subjective sleep quality and Internet addiction.
The coincidence between these two variables is statistically significant (r=0.250
p=0.00) but weak.
Table 3
Relationship between Subjective Sleep Quality and Internet Addiction in University
Students
|
Subjective Sleep Quality
|
|
Internet Addiction
|
Spearman's Rho
|
0.250***
|
|
|
gl
|
228
|
|
|
P Value
|
< .001
|
The data presented in Table 4 represent the relationship between sleep duration and Internet addiction. The proximity
between these two variables is statistically significant (r=0.149 p=0.02).
Table 4
Relationship between Sleep Duration and Internet Addiction in University Students
|
Sleep Duration
|
|
Internet Addiction
|
Spearman's Rho
|
0,149*
|
|
|
gl
|
228
|
|
|
P Value
|
0,024
|
The data presented in Table 5 represents the sleep disturbances with an Internet addiction. The relationship between
these two variables is not statistically significant (p= 0.12), which shows that they
are significantly independent.
Table 5
Relationship between Sleep Disturbances and Internet Addiction in University Students
|
Sleep Disturbance
|
|
Internet Addiction
|
Spearman's Rho
|
0.102
|
|
|
gl
|
228
|
|
|
P Value
|
0.122
|
The data presented in Table 6 represents the relationship between daytime dysfunction and Internet addiction. The
relationship between these two variables is statistically significant (r=0.245 p=0.00).
Table 6
Relationship between Daytime Dysfunction and Internet Addiction in University Students
|
Daytime Dysfunction
|
|
Internet Addiction
|
Spearman's Rho
|
0.245***
|
|
|
gl
|
228
|
|
|
Valor p
|
< .001
|
Finally, the relationship between Internet addiction and hours of sleep (sleep efficiency
dimension) is a weak, negative correlation (p=0.004, Rho =-0.188). Moreover, the Chi-square
test was applied to determine the association between Internet addiction with sleep
latency (p=0.90) and medication use (p=0.52), where no statistically significant differences
were found.
Discussion
The most relevant findings from this research come from the relationship between sleep
quality and Internet addiction in university students. The dimensions that relate
the variables of the study to respond to the objective of the research are highlighted.
In accordance with the results found in Table 1, regarding the description of the sociodemographic aspects, the large number of female
population stands out, 81.3%, and young adults, 88.7%, who belong to the student community
of this research agree with what was found in the studies by Martínez 29 and Cecilia 30, who sought to quantify the university population to investigate psychological phenomena.
These authors mentioned that, when accounting for university students in the health
area, the sample with the greatest representation is that of women between 19 and
21 years old, represented in the first study with 55.2% of the students and the second
study with 75.82%.
On the other hand, according to the results obtained in Table 2, concerning sleep quality and Internet addiction, it was demonstrated that there
is a statistically significant correspondence between both variables. This finding
is corroborated by what was stated in an analytical study conducted at a university
community by the author Iñiguez 31, where sufficient empirical evidence was found to conclude that there is a statistically
relevant relationship between sleep quality and problematic Internet use. In their
study, 51% of participants had problems with Internet use and, at the same time, sleep
problems. In turn, Wang's study 32 mentions that problematic Internet use is related to poor sleep quality, since students
who spend more time online, 23.5% of the time, tend to not fall asleep, which negatively
impacts their level of rest, generating psychological discomfort.
Additionally, regarding the results of Table 3, the relationship between subjective sleep quality and Internet addiction is understood
and shown to be statistically significant, a fact that coincides with what was established
by Gutiérrez 33 in his research on a population student, in which the association between the appreciation
of the nature of sleep and academic performance is influenced by the amount of time
the Internet is used. Similarly, the study by Alimoradi 34 reveals solid evidence supporting that excessive Internet use has a relevant and
negative impact on the perception of the degree of sleep of students, reporting that
52% of them have a problematic use of the Internet and are more likely to suffer from
sleep disorders.
Regarding the results presented in Table 4, which represent the relationship between sleep duration and Internet addiction,
it is observed that both variables are statistically significant. This can be corroborated
with the study by Fajardo and Collante 35, which indicates that 15% of the students evaluated have very poor quality of rest,
a fact that generates intrapersonal conflicts or problems in daily tasks. According
to the study by Chui 36, conducted among the § university population, there is a statistically significant
relationship £ between the variables studied; Internet addiction is an unfavorable
2 predictor for overall rest time, with a moderate correlation.
Moreover, the data presented in Table 5 represents the relationship between sleep disturbance and Internet addiction, demonstrating
they are independent variables, but with a weak positive correlation = between both.
The study by Fajardo and Collante 35 does not agree with what was found in this research, since it mentions that there
isa statistically significant connection since there is evidence that explains that,
when faced with a dependence on the Internet, sleep disturbances can be generated
that end up aggravating the quality of the latter. As in the study by Fajardo and
Collante 35, the study from Echeverria 37 states that in the population studied, 51.7% presented a serious level of sleep disturbances,
which leads to the understanding that this variable is negatively altered by different
environmental factors, one of these being the use of electronic devices.
Finally, Table 6 shows the results that represent the relationship g between daytime dysfunction and
Internet addiction. This association is statistically significant and indicates that
there is a s weak positive correlation between the variables, which can be verified
in the study by Ochoa 38, conducted on students. This research shows that excessive use of the mobile phone
affects the student's daily activities, as fatigue and daytime sleepiness occur. On
the other hand, Celis 39 mentions that using the Internet before sleep has a significant effect, as it causes
excessive daytime sleepiness.
Conclusions
This research led to the conclusion that there is a weak positive relationship between
sleep quality and Internet addiction in university students from Ñuble. In the statistical
analysis, a Rho value of 0.15 was found, and the significance found was 0.01, with
respect to the theoretical significance, which is 0.05.
It is specified that, according to the sociodemographic data of the student population
in the health area, it is composed mainly of young adults belonging to nursing studies,
with a predominance of the female gender.
It was determined that there is a weak positive relationship between subjective sleep
quality and Internet addiction in the students of this research: the statistical test
showed a Rho value of 0.25, with a significance of 0.00 less than the significance
theoretical, which is 0.05.
It was established there is a relationship between the duration of rest and Internet
addiction in the population studied: the statistical test applied showed a Rho value
of 0.14, which shows there is a weak positive relationship with a significance of
0. 02, being less than the theoretical significance of 0.05.
It was determined there is no connection between sleep disturbances and Internet addiction
in the group of people studied. The statistical test revealed a Rho value of 0.10,
indicating a weak positive relationship. The significance found was 0.12, which is
greater than the theoretical significance of 0.05.
It was concluded there is a relationship between daytime dysfunction and Internet
addiction in the sample studied. Statistical analysis indicated a Rho correlation
coefficient of 0.24, indicating a weak positive correlation. Furthermore, the significance
level was found to be 0.00, lower than the theoretical threshold of 0.05.
Research on the relationship between sleep and Internet addiction in university students
has great value for practical application in the disciplines of nursing and psychology.
It allows the development of intervention strategies and support programs that address
mental and physical health problems derived from excessive Internet use, improving
the quality of sleep and, consequently, the general well-being and academic performance
of students. This research also provides nursing and psychological professionals with
fundamental data to design preventive and therapeutic approaches specific to this
population, promoting healthy habits and an appropriate balance between the use of
technology and rest.
Limitations
-
Examine correlation coefficients or other measures to determine the magnitude or direction
of the relationship.
-
Little number of studies related to the two variables.
-
Participants may have little objectivity about their own Internet addiction and its
influence on sleep quality.
-
The IAT instrument measures the extent of an individual's involvement with the computer.
Recommendations
-
Expand the study to other universities in the area.
-
Apply this study to a different sociodemographic group.
-
Conduct a longitudinal study to examine how variables change over time.
