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Remittances Review
May 2024,
Volume: 9, No: S 2,pp. 149-161
ISSN : 2059-6588(Print) | ISSN 2059-6596(Online)
149 remittancesreview.com
Received : 05 March 2024, Accepted: 25 April 2024
DOI: https://doi.org/10.33282/rr.vx9i2.10
Nomophobia and Academic Performance: Exploring the Cognitive and
Behavioral Impacts on University Students
WAJAHAT REHMAN1, DR. SYEDA TEHMINA NAZ BUKHARI2, Dr NOSHEEN MALIK3,
DR. SHAISTA NOREEN4, SYEDA ALMAS FATIMA SHAMSI5, ANZA ABRAR6,
DR. RABIA TABASSAM7
1. M. Phil Scholar department of Education Islamia University of Bahawalpur
2. Assistant Professor Department of Education Islamia University of Bahawalpur Pakistan
tehmina.naz@iub.edu.pk
3. Assistant Professor department of Education Islamia University of Bahawalpur
nosheen.malik@iub.edu.pk
4. Assistant Professor. Department of Education Islamia University of Bahawalpur.
Shaista.noreen@iub.edu.pk
5. M. Phil Scholar department of Education. The Islamia University of Bahawalpur.
6. BS Scholar department of Information Technology. The Islamia University of Bahawalpur
7. Lecturer department of STEM Education Lahore College for Women University
rgreat786@yahoo.com, rabia786@lcwu.edu.pk(Corresponding Author)
Abstract
Technology, specifically the fear of being without a mobile phone known as nomophobia,
is on the rise among university students leading to arguments over its impact on learning activities
as well as its influence on the wellbeing of students. This research seeks to find out the prevalence
of nomophobia among university students, determine how it affects their performance, and
establish factors that contribute to nomophobia. A total of 200 students studying in different
universities in Punjab province participated in the study and data were collected using structured
questionnaires. This study further established that students experience high levels of nomophobia,
evident on measures of fear of being unable to communicate, lose connection, and inability to
access information. Discomforts such as eye strain and poor sleeping patterns were noted to be the
health concerns arising from use of smartphones. The present study further revealed that
nomophobia has a negative influence on the learning process as higher levels of nomophobia lead
to disruptions and lower levels of study. Gender, age and the program of study were some of the
demographic factors seen to have an effect on the level of nomophobia. Some measures entail:
awareness creation that focuses on the effects of nomophobia, counseling services, and probably
technology fasting to discourage use of the devices among students.
Keywords: nomophobia, mobile phone usage, academic performance, health issues, demographic
factors, smartphone dependency, learning activities, digital well-being, intervention strategies.
Remittances Review
May 2024,
Volume: 9, No: S 2,pp. 149-161
ISSN : 2059-6588(Print) | ISSN 2059-6596(Online)
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I. INTRODUCTION
A. Background of the Study
Nomophobia can be literally
translated as “no-mobile-phone phobia”, it is
the concern that people have when they
cannot use their mobile phones or when they
are separated from them (Leon-Mejia, 2021).
Unsurprisingly, mobile phones have gained
much prominence as a device that people use
in their day to day lives, as a tool of
communication, source of information and
entertainment. The highest level of
nomophobia is reported among university
students, for whom mobile technology is
widely used in different aspects of their life
and learning.
The effect of nomophobia on
university students’ learning activities is an
important research topic because
nomophobia influences academic
achievements and well-being. The
overdependency on these gadgets especially
mobile phones and the worry of being
without them hinders concentration, learning,
and production in classroom environments.
Knowledge of nomophobia prevalence and
its impact on the learning processes of
students is critical for educators,
policymakers, and mental health workers to
devise appropriate solutions to helping such
students.
One of the most recent works is Hsu
et al. They have found out that the use of
smartphone has influenced the psychological
and physical health of students in different
ways. For instance, Thomée et al. (2011)
conducted a style of young adult and noted
that those who mobilize phones frequently
reported elevated stress levels, poor sleep
quality,
and
or
symptoms
of
depression.
When combined with the various health
problems, nomophobia will not only worsen
the academic performance and well-being of
students but also add to it.
However, the findings show that
nomophobia creates a negative effect in
academic attainment, social interaction as
well as relationships. In a study by Yildirim
and Correia (2015) they observed that those
with high scores on the nomophobia scale
tend to avoid places and situations that make
it impossible for them to avoid mobile phone
use due to fear of being alone or socially
isolated. This can cause social isolation,
which, together with nomophobia, results in
loneliness, and in turn, impacts various
domains of life in a negative way.
However, it is imperative to note that
nomophobia also has psychological and
social consequences and also alters the
cognitive functioning of students. Clayton
Leshner and Almond (2015) in their research
with college students have suggested that the
frequency of students to their mobile devices
can be counter productive because it has been
found to cause cognitive overload thereby
affecting the students’ ability to concentrate
on their course work. The kids may also have
a reduced capability to achieve good grades,
and it may even slow their learning process.
In addition, age, gender, and the field
of study might play a role in the extent to
which nomophobia affects students or the
manifestation of its symptoms. In a study
carried out by Gezgin, Şahin, and Yildirim in
(2017) revealed differences in Nomophobia
between students of the different faculties the
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May 2024,
Volume: 9, No: S 2,pp. 149-161
ISSN : 2059-6588(Print) | ISSN 2059-6596(Online)
151 remittancesreview.com
study revealed that humanities students
scored higher in Nomophobia than students
who were in sciences and engineering faculty
students. This indicates that the educational
environment and course content can have
some contribution to the development of
nomophobia.
In the light of the above findings,
intervention strategies to address the negative
impacts of nomophobia among students
cannot be overemphasized. Some of the
protective factors include sensitization on the
risks faced by individuals who spend a lot of
time using their mobile phones, consultation
services for students who are addicted to
technology, and support for programs
therefore enhancing the welfare of users of
technology. Prewitt Martin, Huebner, and
Marshall (2013) argued in a paper which was
reviewed by Elhai, Levine, Dvorak, and Hall
(2016) that mindfulness based intervention
self regulation and other such inter esting
techniques which can help to reduce
nomophobia in students and they can also
have a better mental health and improved
academic results.
The effects of digital addiction among
university students’ usage have been much
more profound and severe that has led to the
growth of concern in relation to academic
performance and additional personal
productivity indicators. Rather, digital
addiction refers to the disorder where a
person becomes obsessed with using gadgets,
for instance, mobile devices, in a way that
disrupts their normal functioning (Kuss and
Griffiths, as cited in Pontes and Griffiths,
2014). This type of addiction has been
reported to lead to several undesirable
consequences such as poor academic
performance, withdrawal from activities
within the society, mental problems among
them making it a crucial area to research on.
A research study has established that
the impact of digital addiction at this age
results in issues relating to sleep amongst
students. Another study conducted by
Demirci, Akgonul, and Akpinar (2015)
indicated that the students whose smartphone
addiction was more severe had relatively
lower quality of sleep and even less sleeping
duration at night than students with less
smartphone addiction. Sleep quality
disruption can also have a worse impact on
other cognitive abilities including memory,
concentration, and find solutions to
problems, all of which are crucial for the
learners’ performance.
Closely associated with this, there is
corroborative evidence of the link between
digital addiction and academic performance
based on an understanding that smartphones
are used to seek information and even engage
in other activities during class time. Junco
and Cotten (2012) make a postulation that
students who regularly use their smartphone
during study or learning sessions or lectures
get lower grades and lose interest in their
academics. This has been due to the
interferences and the switching behaviours
that distort the flow of information significan
tly.
Further, student should be aware that
they are vulnerable to developing digital
addiction that leads to high level of anxiety
and depression. Panova and Carbonell
(2018) noted that their analysis of 46 papers
Remittances Review
May 2024,
Volume: 9, No: S 2,pp. 149-161
ISSN : 2059-6588(Print) | ISSN 2059-6596(Online)
152 remittancesreview.com
on the negative impacts of smartphone use
showed that avid users exhibit elevated levels
of anxiety, depression, and stress. Such
psychological problems result in
externalization of destructive behavior
directing it towards the self, or internalization
of destructive behavior that becomes directed
inwards, which hampers student motivation,
undermines their self-esteem and coping
mechanisms, and consequently impacts ones
performance as well as well-being.
Some interventions that have been
proposed in universities include the provision
of options that are able to meet the need of a
digital detox and approaches that are able to
ensure that healthier practices in the use of
the internet are adopted. For illustration,
Roberts and Pirog (2013) in their study noted
that students who took part in the study on
digital detox had better and longer sleep, less
stress level and improved academic
performance. These results highlight the need
for the integration of effective digital well-
being interventions to youth educational
institutions to guide the utilization of
technology appropriately.
In order to further investigate the
effects of excessive mobile phone usage in
educational institutions, this study aims to
establish a link between nomophobia and
university students' learning activities. Thus,
by clarifying the prevalence of nomophobia,
its origins, and its effects on student
motivation and success, the findings given in
this paper hope to enhance educational
methods and discourage negative interaction
with technology.
Thus, the findings provided in this pa
per aim to improve educational methods whi
le discouraging negative involvement with t
echnology by revealing the incidence of no
mophobia, its origins, and repercussions for
student motivation and accomplishment.
B. Theoretical Framework
This study's conceptual
underpinnings come from the notion of
technology anxiety and how it affects
students' well-being and academic
performance. Nomophobia is a kind of
technical phobia that has been recognized in
the literature. It is characterized by emotions
of unease, tension, and dependence on mob
(Leon-Mejia, 2021). Based on the ideas of
technology acceptance and psychological
responses to digital tool use, this study
determines how nomophobia affects students'
emotions, mental processes, and learning
styles. This study examines the effects of
nomophobia on students' learning styles,
thought processes, and emotions by drawing
on theories of technology adoption and
psychological responses to the usage of
digital technologies.
In addition, the theory of behavioral
psychology was used to underpin the study as
it concentrates on reinforcement, habits and
cognitive aspects of individuals and their
relation to technological artefacts. In doing
so, the present study employed and combined
these theoretical frameworks to show how
nomophobia affects the learning activities of
university students as well as offer potential
solutions to alleviate the adverse effects of
nomophobia.
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May 2024,
Volume: 9, No: S 2,pp. 149-161
ISSN : 2059-6588(Print) | ISSN 2059-6596(Online)
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C. Research Questions
1. What is the prevalence of
nomophobia among university
students, and how does it vary across
different demographic factors such as
gender, age, and program of study?
2. How do the primary indicators of
nomophobia manifest in university
students' daily mobile phone usage
patterns and behaviors?
These research questions aim to
investigate the extent of nomophobia among
university students, explore its
manifestations in their mobile phone usage,
and understand how demographic factors
may influence the prevalence of
nomophobia. By addressing these questions,
the study seeks to provide insights into the
impact of nomophobia on students' behaviors
and well-being in academic settings.
II. METHODOLOGY
A. Participants
The study targeted two hundred
university students from different
universities including The Islamia University
of Bahawalpur, CUVAS Bahawalpur and
Bahaudin Zakariya University Multan in the
Punjab province-A. Respondents were not
randomly selected and their selection
depended on the willingness of the
participant to take part in a study on
nomophobia and its impact on learning
activities.
B. Data Collection
Data collection was conducted using
a structured questionnaire consisting of five
sections: Demographic information of
students, method of using mobile phones,
nomophobia indicators, its repercussions on
health, and the influence on learning
processes. To achieve the identified
objectives, the following research questions
were developed: (a) Operationalization of
Mobile phone use: A self-constructed
questionnaire was developed to elicit
information about students’ mobile phone
usage patterns, nomophobia indicators,
health vulnerabilities associated with
smartphone use, and the correlation between
nomophobia and academic performance.
C. Data Analysis
The scores obtained were tabulated
and analyzed statistically using Statistical
Package for the Social Sciences (SPSS)
computer file. Descriptive statistics of
nominal data such as frequency, percentage,
continuous data such as mean, standard
deviation were used to analyze the data and
gain insights regarding the extent of
nomophobia that students they experience
and perceived change in their learning
behaviors due to nomophobia, and
correlation between nomophobia score and
demographic variables.
D. Questionnaire Development
The questionnaire that was used in the
study was developed to measure aspects of
nomophobia that university students may
display, their frequency of mobile phone
usage, symptoms of nomophobia, the effects
on health as well as learning activities. Since
the burden of evidence lies in the hands of the
researcher, the questionnaire aimed at
capturing all the details necessary to answer
the research questions and objectives.
E. Ethical Concerns
Before participating in the process of
data collection, concerns that bound to ethical
measures were observed to warrant
anonymity and the use of participant’s
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May 2024,
Volume: 9, No: S 2,pp. 149-161
ISSN : 2059-6588(Print) | ISSN 2059-6596(Online)
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pseudonyms. Written informed consent was
sought and received from all participants to
ensure that they complied willingly into the
study. The study conformed to standard
ethical practices of conducting and executing
research to safeguard the participants.
F. Limitations
An important thing to understand
would be that there are definite limitations of
the work where the sample size of the study
is one big limitation, Self-reported data and
the generality of the data in other population.
Such limitations may affect the analysis and
meaning of the conclusions obtained in the
course of research.
III. RESULTS AND DISCUSSION
A.
Nomophobia
Table 1 Nomophobia
Mean
Std.
Deviation
Fear of Unable to
Communicate with Others
3.43
1.02
Fear of Losing Connection
3.02
1.00
Not Being able to Access
Information
3.38
.97
Sacrificing Comfort
3.42
1.23
Overall
3.31
1.06
The data on nomophobia is
summarized in Table 1, with each aspect
assessed by its mean and standard deviation.
The fear of being unable to communicate
with others had a mean (Mean=3.43,
S.D=1.02). The fear of losing connection
showed a mean (Mean=3.02, S.D=1.00).
Concern about not being able to access
information was reflected by a mean
(Mean=3.38, S.D=0.97). Sacrificing comfort
had a mean (Mean=3.42, S.D=1.23). The
overall impact of nomophobia had a mean
(Mean=3.31, S.D=1.06).
These results are consistent with
empirical evidence portrayed in prior studies
focusing on nomophobia and its penetration
in people’s routine. Research has pointed out
the fact that nomophobia leads to high stress
levels, which compromises productivity and
social adaptation (Thomée, A. , Härenstam,
and M. Hagberg, 2011). Furthermore, the
psychosocial consequences of nomophobia
that include risk of being isolated from other
people (Whisman, M.A., and Uebelacker,
L.A 2009) and mobile devices are indications
of potential anxiety and depression disorders
that are detrimental to mental health
(Yildirim, C. , and Correia, A. P. , 2015).
The insight into basic characteristics
of nomophobia and its fear-related
manifestations is vital for purposes of
designing effective intervention aimed at
minimizing negative impacts of nomophobia.
This work contributes to the understanding of
how nomophobia arises and how it manifests
itself in target individuals, and as such can be
effective in helping educators and healthcare
professionals reduce anxiety related to
mobile phone dependence by implementing
best practices and informed habits that can
help break negative patterns of technology
use.
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May 2024,
Volume: 9, No: S 2,pp. 149-161
ISSN : 2059-6588(Print) | ISSN 2059-6596(Online)
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B.
Impact on Health
Table 2 Impact on Health
Mean
S.D.
Disturbance of sleep
3.32
1.61
Headache
3.48
1.48
Decreased participation in
social activities
3.36
1.44
Lack of activity next day
3.32
1.47
Decreased academic
performance
3.30
1.43
weight gain
3.03
1.53
Road traffic accidents
3.47
1.47
Depression
3.43
1.48
Neck Problems
3.57
1.42
Relationship Problems
3.67
1.45
Overall
3.40
1.48
The impact on health from various
issues is depicted in Table 2, where each
health concern is assessed by its mean and
standard deviation. Disturbance of sleep had
a mean (Mean=3.32, S.D=1.61), indicating
moderate concern. Headache was slightly
higher (Mean=3.48, S.D=1.48). Decreased
participation in social activities had a mean
(Mean=3.36, S.D=1.44), while lack of
activity the next day also had a mean
(Mean=3.32, S.D=1.47). Decreased
academic performance was noted with a
mean (Mean=3.30, S.D=1.43). Weight gain
had a relatively lower mean (Mean=3.03,
S.D=1.53). Road traffic accidents had a
significant impact (Mean=3.47, S.D=1.47).
Depression was also notable (Mean=3.43,
S.D=1.48). Neck problems had one of the
highest means (Mean=3.57, S.D=1.42), and
relationship problems topped the list
(Mean=3.67, S.D=1.45). The overall impact
on health had a mean (Mean=3.40,
S.D=1.48).
These results are consistent with
Grandner, M. A. , Jackson, N. , Gerstner, J.
R. , and Knutson, K. L. (2014) and Hossain,
J. L. , and Shapiro, C. M. (2002) and
Haldeman, Carroll, L., and Cassidy, J.D.
(2008) who also observed negative impacts
of such factors such as sleep disturbances,
headaches and social isolation on ones health
and well being. Likewise, problems like
gaining weight, traffic mishaps, depression,
neck issues, and relationship concerns depict
a range within which they differ in their
perceptions of the issue, receiving mean
scores that point towards considerable
concern. These findings are in support with
previous literatures on the impact of weight
gain in which it is shown to affect the health
negatively (Wing, R. R. , and Phelan, S. ,
2005), road traffic accidents that also carry
negative impacts on health as highlighted in
the works of Singh, R. , and Singh, H. K. ,
2014), and depression (Darwish et al,2018).
C. Nomophobia Effects on Students
Learning
Table 3
Mean
S.D.
I study on my
smartphone since
it's a more
convenient method
that lets me learn
anywhere, at any
time.
3.79
1.41
In order to
efficiently seek up
information that I
did not understand
in class, I utilize
my smartphone.
3.78
1.28
I use a smartphone
due to it's a more
practical way to
conduct research.
3.87
1.25
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The effects of nomophobia on
students' learning are summarized in Table 3,
with each statement assessed by its mean and
standard deviation. Using smartphones for
learning because it is a more flexible method
had a mean (Mean=3.79, S.D=1.41).
Utilizing smartphones to look up something
not understood during class had a mean
(Mean=3.78, S.D=1.28). The convenience of
smartphones for research purposes showed a
mean (Mean=3.87, S.D=1.25). Using
smartphones as a quicker method of getting
feedback had a mean (Mean=3.93,
S.D=1.30). Reading articles or assignments
given by teachers using smartphones had a
mean (Mean=3.95, S.D=1.23). Smartphones'
role in spreading knowledge through
discussions with many students had a mean
(Mean=3.76, S.D=1.35). Understanding
learning material between lessons using
smartphones had a mean (Mean=3.89,
S.D=1.31). Improving communication
between students and teachers through
smartphones had a mean (Mean=3.79,
S.D=1.38). The importance of mobile phone
brands in motivating the learning process had
a mean (Mean=3.79, S.D=1.30). Using
smartphones for taking notes during lectures
had a mean (Mean=3.88, S.D=1.35). The
overall impact of using smartphones in the
learning process had a mean (Mean=3.84,
S.D=1.32).
These findings are consistent with
prior research asserting the expansion of
mobile application use in education in
general and its ability to positively impact
Since using a
smartphone to
receive learning
feedback is faster, I
use it in my
learning process.
3.93
1.30
I use my
smartphone to read
assignments from
teachers or articles
as part of my
learning process.
3.95
1.23
I use my
smartphone to
engage in discourse
with a big number
of learners in order
to share
knowledge.
.
3.76
1.35
In the interim
between lessons, I
utilize my
smartphone to
comprehend the
content.
3.89
1.31
Using a smartphone
throughout the
learning process
facilitates better
communication
between the teacher
and the students.
3.79
1.38
The brand of
mobile phone is a
major factor in
motivating the
learning process.
3.79
1.30
I take notes during
lectures using my
3.88
1.35
smartphone as part
of my learning
process.
Overall
3.84
1.32
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students’ achievement (Kukulska-Hulme A,
and Shield, L, 2008; Sharples et al. , 2016).
But still, the strong side of integrating mobile
devices in learning is obvious while weak one
contains a number of points such as
distractions and lack of concentration which
are the weaknesses of using SMART
technologies in learning and it is necessary to
minimize them while taking the strengths.
ANOVA
gender. For age groups, the between-groups
variance was 2.061, with an F-value of 3.511
and a significance level of .016, suggesting a
statistically significant difference in
nomophobia by age group. Regarding the
effects of nomophobia on students' learning,
the between-groups variance was 1.294, with
an F-value of 3.583 and a significance level
of .000, indicating a highly significant effect.
The within-groups variance for gender, age,
and students' learning were 120.082,
115.070, and .361, respectively, and the total
variances were 121.255 for both gender and
age groups, and 232.379 for students'
learning effects. These results highlight that
age and the impact on students' learning show
significant differences in nomophobia, while
gender does not.
Table 4
Correlation
The ANOVA results provide insights
into the variance in nomophobia across
different groups. For gender, the between-
groups variance for nomophobia was 1.173,
with an F-value of 1.934 and a significance
level of .166, indicating no statistically
significant difference in nomophobia by
A Pearson correlation coefficient of
.591 with the hypothesis that evidence
nomophobia significantly affect students’
learning and with the test of normality, p<.
Test Variables
Mean
F
Sig.
Nomophobia by
Gender (Between
Groups)
1.173
1.934
.166
Nomophobia by
Gender (Within
Groups)
120.082
-
-
Nomophobia by
Gender (Total)
121.255
-
-
Nomophobia by Age
Group (Between
Groups)
2.061
3.511
.016
Nomophobia by Age
Group (Within
Groups)
115.070
-
-
Nomophobia by Age
Group (Total)
121.255
-
-
Nomophobia Effects
on Students Learning
(Between Groups)
1.294
3.583
.000
Nomophobia Effects
on Students Learning
(Within Groups)
.361
-
-
Nomophobia Effects
on Students Learning
(Total)
232.379
-
-
Correlations
Nomo-
phobia
Nomophobia
Effects on
Students
Learning
Pearson
Correlation
1
.347**
Nomophobia
Sig. (2-
tailed)
.000
N
200
200
Nomophobia
Effects on
Students
Learning
Pearson
Correlation
.347**
1
Sig. (2-
tailed)
.000
N
200
200
**. Correlation is significant at the 0.01 level (2-
tailed).
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05, there is a significant positive relationship
between nomophobia and the effects on the
students’ learning. The overall findings
indicated a statistically significant difference
with p <.01 at 347 (Rubart et al., 2012).
Taking this into consideration, it can be
stated that individuals with higher levels of
nomophobia also report more significant
impact in the process of learning. In the same
way the two variables have a negative and
significant relationship with each other with
Pearson correlation being equal to. Similarly,
there was a remixed positive correlation
between community involvement and self-
esteem, F (3, 276) = 347, p <.01, implying
that these two factors had a reciprocal impact
on one another. This means that a direct
correlation exists between nomophobia and
perceived pat impact on students where the
higher the former, the higher the latter also is.
The studies presented in this paper support
the relationship between nomophobia and its
effects on academic performance or
achievement, which eventually emphasizes
the need to address nomophobia within
academic institutions for a better and
healthier environment.
IV. CONCLUSION AND
RECOMMENDATIONS
A. Conclusion
This paper on the prevalence, impact,
and the factors that led to the nomination of
nomophobia among university students has
offered useful information in controlling this
fear of having no mobile phone.
Consequently, the prevalence of nomophobia
was revealed to be quite high among
university students who claimed to exhibit
signs of this condition in varying degrees.
Some primary Gothic conceptions of
nomophobia include the fear of being unable
to communicate, losing connection, and not
being able to access information were evident
among the learners. Bearing in mind the
negative effects of the overuse of smart
mobile phones, students attributed some of
the health problems they were experiencing
as follows: aching eyes, headaches, and
difficulties in getting to sleep. The
respondents’ nomophobia level was found to
correlate with the prevalence of unhealthy
and ill health confirming a symbiosis of the
mind and body. Nomophobia affected the
students’ learning by making them lose focus
and be unable to fully concentrate on
whatever they were learning, hence altering
and reducing their performance rates until
they were deemed mere observers of the
assignments given.
There is a statistically significant
difference in the level of nomophobia among
university students in different gender, age,
and program of study In order to answer the
above hypothesis, a Statistical Package for
the Social Science (SPSS) was used to
analyse and compare results based on gender,
age, and program of study Among the
participants, male students were more
dependent on their smartphones than female
students This study found that as the age of
the
B. Recommendations
Having analyzed all the findings of
the study, the following recommendations
can be given:
Awareness Campaigns: Advise
students on improved mobile phone
etiquette, provide a health check on
students’ mobile phone use, and
undertake campaigns to teach students
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May 2024,
Volume: 9, No: S 2,pp. 149-161
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some of the ways of combating
nomophobia.
Counseling Services: counsel those
students who spend extremely long
hours using the phone and developing
mental health related complications.
Technology Detox Programs: Policy
recommendations based on this should
include introducing technology detox
programmes or activities to sensitize
the students to cut on the time spent on
their devices and engage in more real-
life interactions.
Research and Policy Development:
Invest further in nomophobia and its
effects on learners and create strategies
in order to manage smartphone usage
within the college.
Collaboration with Health
Professionals: Consult with other
health-oriented personnel in order to
seek a way on how to minimize the
health impacts of using smartphones
and enhance the overall health of
students.
The universities can adopt these
recommendations in order to minimize the
negative effects of mobile phone use and
instill healthy habits among students, which
will have a positive impact on their health and
academic achievements.
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