| Research Article (Open access) |
|---|
SSR Inst. Int. J. Life Sci., 10(1):
3477-3483,
Jan 2024
Evaluate Mobile Phone Usage and its Impact on Student Health.at Murarji Desai College of Residential Sciences, Bagalkot
Lakshmavva Gondi1*, Jayashree
Itti2
1Lecturer, Department of
Community Health Nursing, Shri B.V.V.S. Institute of Nursing Sciences,
Bagalkot, Karnataka, India
2Principal, Department of
Community Health Nursing, Shri B.V.V.S. Institute of Nursing Sciences,
Navanagar, Bagalkote, Karnataka, India
*Address for Correspondence: Lakshmavva Gondi, Lecturer, Department of Community Health Nursing, Shri
B.V.V.S. Institute of Nursing Sciences, Navanagar Bagalkot, Karnataka, India
Methods: A school-based cross-sectional study was conducted from
March 13 to April 8, 2023. A total of 80 students were selected using the
stratified random sampling technique. The study was conducted at Murarji Desai Residential Science College, Bagalkot. A
structured and prepared questionnaire was used to collect baseline data. Addiction
to mobile phones was assessed using a questionnaire and their health impacts.
Result: Assessment of Smartphone Addiction and its Health
Impacts on Students. The range value is 0 15, the mean value is 9.46, the
minimum value is 0, the maximum value is 15, the standard deviation is 0.48,
and the mean percentage is 31.95%. The calculated chi-square value of 4.14
(p=0.04) suggests there is a significant association between Smartphone
addiction and education among students. The calculated chi-square value of 4.13
(p=0.04) suggests there is a significant association between addiction to smartphone
and their health impacts (burning sensation of the eyes) among students.
Conclusion: The findings of this study showed that there is
an association between Smartphone addiction and their health impacts and the
need to improve their health among students.
Keywords: Health impacts, High school, PU students,
Smartphone addiction
INTRODUCTION- Mobile phones, often known as handphones, are potent communication tools
that were originally shown off by Motorola in 1973 and were on sale in 1984.[1]
Handphones have become an essential part of our lives in the past several
years. Every year, the number of mobile phone subscriptions rises steadily.
Globally, there were about seven billion users as of 2016. Between 2000 and
2015, the percentage of people using the internet climbed seven times, from
6.5% to 43% worldwide. Additionally, the proportion of homes having internet
connection grew from 18% in 2005 to 46% in 2015.[2] Parlay, there is
a growing trend of smartphone addiction. 84% of respondents to a 2012 Time
Mobility Poll said they couldn't go a single day without their mobile devices.[3]
It has been reported in over 206 published survey findings that 27% of parents
and 50% of teenagers believe they are addicted to their phones. [4]
According to recent studies, there is a rise in dependence on mobile phones,
which may lead to an increase in internet addiction.[5]
Targeting the lack of
growth and unfair life period in youth, Afteensh Adolematurity uses his films for many purposes. They will
experience everything, from the latest developments in mobile health to the use
of mobile in advertising, directly on mobile. Nowadays, children under the age
of 10 are attracted to mobile games, entertainment, cinema, etc. is interested.
However, this may negatively affect both the youth and the child's physical and
mental health.[6]
Connectivity has become more important than smartphones, with 53%
of Americans using smartphones during an unprecedented time in public health
history, according to information from the Pew Research Center. The use of
mobile devices also enables children to participate in distance learning;
nearly 29% of parents said their children should use a smartphone to complete
their education. These include anxiety, depression, behavioural
problems, and social problems. For example, a drug addict can easily become angry
when he cannot place a bet. Smartphone addicts may feel anxious or irritable
when they are away from their phones.[7]
Smartphone, although a computer, tablet, or smartphone can be an
incredibly useful tool, excessive usage of these gadgets can negatively impact
relationships, employment, and education. It might be time to reevaluate your
use of technology if you find yourself spending more time on social media or
playing games than you do interact with actual people or if you find yourself
constantly checking your emails, texts, or apps even when doing so has
detrimental effects on your life. [8]
Smartphones for Seniors
Electronic devices have become popular,and
smartphones are considered the most used electronic devices among young people,
especially teenagers. Smartphone use is a major problem among young people.
Phone addiction is a type of technology addiction. It is defined as a control
disorder in which a person is under the influence of technology through
excessive use of the internet, video games and mobile devices. [9]
Smartphones, particularly, aim Using a smartphone has become a
necessity for daily living. Widespread smartphone use is linked to several
conveniences, but for the past ten years, there have also been growing public
health concerns about problematic smartphone use, or PSU. In particular,
investigations on the developmental outcomes of children and adolescents have
highlighted additional concerns because of the lack of evidence regarding the
long-term effects of PSU. [10]
Materials and Methods
Research
design- A descriptive research design was used in the study. A
simple random technique was used to obtain 80 samples from the high school
urban area of Bagalkot, India. Data were collected using a structured
questionnaire to assess the addiction to smartphone and their health impacts
among students. The collected data were analyzed using descriptive and
inferential statistics.
Sources of Data- The present study data were collected from adolescents.
Descriptive survey approach- A descriptive
survey approach is designed when the purpose of the study is to describe the
prevalence or incidence of phenomena or to estimate the value of phenomena for
a population. In the present study, the main aim is to assess the
addiction to smartphone and their health impacts on students.
Research design- A descriptive study is research in which a one-time evaluation of students'
knowledge regarding smartphone addiction is made. The research design defines
the population, sample, size, variables, data collection tools and methods, and
data analysis plan.
Variables- Dependent variable- In this study, the
Smartphone addiction of students is the dependent variable.
Independent variable- In this study,
independent variables are the health impacts of students.
Socio-variables- It consists of 11 items: age,
gender, education status, education status of mother, education status of
father, monthly income, religion, occupation of father, do you have a
Smartphone, and how many hours per day you use a Smartphone?
Population- PUC 1st and 2nd students at
Murarji Desai Residential Science PU College,
Bagalkot, India.
Sample and sample technique- We chose 80
students and used stratified random sampling techniques conducted at Murarji Desai Residential Science PU College Bagalkot,
India.
Data Collection Tool- Data collection tools
are the procedures or instruments used by the researcher to observe or measure
the key variable in the research problem. A semi-structured questionnaire was
used to collect the data in the present study.
Procedure for data collection- Data collected from 13/03/2023
to 08/04/2023. Data collection was carried out in 3 phases: the first phase was
data collection regarding socio-demographic factors and the Smartphone
addiction of students. Second phase: data collection regarding Smartphone
addiction according to the severity of the students. Third phase: data
collection regarding the health impacts of students.
Data collected from all students based on their socio-demographic
factors and measurements of height and weight by using instruments like a
measuring scale for height and a weighing machine for weight determines the
health impact of students.
Statistical Analysis- Data analysis
is the systematic organization and synthesis of research data and the testing
of research hypotheses by using the collected data. The data was analyzed using
both descriptive and inferential statistics. A chi-square test was used to find
an association between the physical activity level and its relationship with
body image among students.
Ethical Approval- Ethical approval was
obtained from B.V.V.S. Institute of Nursing Sciences and Institutional Ethics
Committee, Bagalkot. Written informed consent was obtained from all
participants.
RESULT- Assessment of smartphone addiction and its health
impacts on students- The range value is 0 15, the mean value is 9.46, the minimum
value is 0, the maximum value is 15, the standard deviation is 0.48, and the
mean percentage is 31.95%. The calculated chi-square value of 4.14 (p-value
0.04) suggests there is a significant association between Smartphone addiction
and education among students. The calculated chi-square value of 4.13 (p-value
0.04) suggests there is a significant association between addiction to
smartphones and their health impacts (burning sensation of the eyes) among
students.
Among all samples, 11 (13.75%) students have mild addiction, 35
(43.75%) students have moderate addiction, and 34 (42.5%) students have severe
addiction. So many students have had health impacts and need to avoid using
smartphones for a long time, which helps improve their health (Table 1).
Table 1: Distribution
and descriptions of socio-demographic variables
|
Variables |
Categories |
Frequency |
Percentage (%) |
|
Age |
15-16 years |
20 |
25 |
|
16 17 years |
21 |
26.25 |
|
|
18 and above |
39 |
48.75 |
|
|
Sex |
Male |
39 |
48 |
|
Female |
41 |
51.25 |
|
|
Education status |
1st year |
37 |
46.25 |
|
2nd year |
43 |
53.75 |
|
|
Education of the father |
Primary |
38 |
47.5 |
|
High school |
24 |
30 |
|
|
PUC |
04 |
05 |
|
|
Degree |
14 |
17.5 |
|
|
Education of the mother |
Primary |
50 |
62.5 |
|
High school |
22 |
27.5 |
|
|
PUC |
05 |
06.25 |
|
|
Degree |
03 |
3.75 |
|
|
Monthly Income |
<10,000 |
42 |
51.21 |
|
10,000 to 20,000 |
15 |
18.75 |
|
|
>20,000 |
23 |
28.75 |
|
|
Religion |
Hindu |
65 |
81.25 |
|
Muslim |
12 |
15 |
|
|
Christian |
03 |
03.75 |
|
|
Occupation of the father |
Government employee |
12 |
15 |
|
|
Private employee |
29 |
36.25 |
|
Business |
25 |
31.25 |
|
|
Farmer |
14 |
17.5 |
|
|
Occupation of the mother |
Government employee |
17 |
21.25 |
|
Private employee |
11 |
13.75 |
|
|
Business |
04 |
05 |
|
|
Housewife |
48 |
60 |
|
|
Do you have a smartphone? |
Yes |
75 |
93.75 |
|
No |
05 |
06.25 |
|
|
Do you use your smartphone for how many hours per day? |
1 to 2 hours |
14 |
17.5 |
|
3 to 4 hours |
22 |
27.5 |
|
|
5 to 6 hours |
44 |
55 |
Description of students based on their categories- Distribution
of the sample according to age total of 80 students 20 (25%) were 15 16 years
old, 21 (26.25%) were 16 17 years old, and 39 (48.75%) were 18 and above
students. 39 (48%) were male, and 41 (51.25%) were female students. 37 (46.25%)
were studying in the 1st year of PUC, and 43 (53.75%) were
studying in the 2nd year of PUC. 38 (47.5%) were primary, 24
(30%) studied up to high school, 4 (05%) studied PUC, and 14 (17.5%) had
education status up to a degree. Distribution of subjects according to the
mother s education status 50 (62.5%) mothers had received only primary
education, 22 (27.5%) mothers studied up to high school, 05 (06.25%) studied
PUC, and 03 (03.75%) had education status up to degree.
Distribution of subjects according to their family's monthly
income 42 (51.21%) had a family monthly income below Rs 10,000, 15 (18.75%)
between Rs 10,000 and 20,000, and 23 (28.75%) had more than Rs 20,000 family
monthly income. 65 (81.25%) students were from the Hindu population, 12 (15%)
were from Muslim families, and 3 (03.75%) were from Christian families. 12
(15%) were government-employed, 29 (36.25%) were privately employed, 25
(31.25%) were doing business, and 14 (17.5%) were doing farming. Distribution
of subjects according to the mother occupation: 17 (21.25%) were
government-employed, 11 (13.75%) were privately employed, 04 (05%) were doing
business, and 48 (60%) were staying at home as housewives.
Distribution of students according to who has a smartphone 75
(93.75%) had a Smartphone, while the remaining 05 (6.25%) did not. Distribution
of the sample according to their time, hours, and days of Smartphone use 14
(17.5%) students used for 1 to 2 hours, 22 (27.5%) used for 3 to 4 hours, and
44 (55%) students were used for 5 to 6 hours (Table 2).
Table 2: Students according to mobile addiction and its severity
|
Level of mobile addiction |
Frequency |
Percentage (%) |
|
Mild addiction |
11 |
13.75 |
|
Moderate addiction |
35 |
43.75 |
|
Severe addiction |
34 |
42.5 |
According to the above table, out of 80 students, 13.75% have mild
addiction, 43.75% have moderate addiction, and 42.5% have severe addiction
(Table 3).
Table 3: Student's Mean, range, and standard deviation of smartphone
addiction among students
|
Range |
Mean |
Minimum |
Maximum |
Standard deviation |
Mean (%) |
|
0-15 |
9.46 |
0 |
15 |
0.48 |
31.95 |
The above table assesses Smartphone addiction and its health
impacts on students. The range value is 20, the mean value is 9.46, the
minimum value is 15, the maximum value is 30, the standard deviation is 0.48,
and the mean percentage is 31.95% (Table 4).
Table 4: Chi-square test shows an association between smartphone addictions
and socio-demographic variables
|
Socio-demographic
variables |
Chi-square
value |
p-value |
|
Age |
0.3 |
0.86* |
|
Sex |
0.45 |
0.50* |
|
Education status |
0.18 |
0.67* |
|
Education of the father |
3.86 |
0.04** |
|
Education of the mother |
4.14 |
0.04** |
|
Monthly income |
0.4 |
0.52* |
|
Religion |
0.24 |
0.63* |
|
Occupation of the father |
0.02 |
0.88* |
|
Occupation of the mother |
0.91 |
0.34* |
|
Do you have a Smartphone? |
0.9 |
0.76* |
|
Do you use a Smartphone for how many hours per day? |
0.02 |
0.88* |
p<0.05; α =0.05; *All the values are statistically
non-significant; **All the values are statistically significant
Assessing the addiction to smartphone and their health impacts
among students- The calculated chi-square value is 3.86 (p-value 0.04), indicating
that there is a significant relationship between mobile phone use and the
education level of the student's father. The calculated chi-square value
is 4.14 (p-value 0.04), which shows that there is a significant relationship
between students' mobile phone use and parents' education (Table 5).
Table 5: Distribution of students according to their health impact
|
Items |
Frequency |
Percentage (%) |
|
Blurred vision Blurred vision |
49 |
61.25 |
|
Water eyes |
30 |
37.5 |
|
Dryness in the eyes |
45 |
56.25 |
|
Burning sensation in the eyes |
40 |
50 |
|
Eye pain |
45 |
56.25 |
|
Neck pain |
43 |
53.75 |
|
Irritation |
55 |
68.75 |
|
Restlessness |
45 |
56.25 |
|
Stress |
30 |
37.5 |
|
Aggressiveness |
45 |
56.25 |
Assessing
the addiction to smartphone and their health impacts among students- The calculated chi-square value of 4.13
(p-value 0.04) suggests there is a significant association between the
addiction to smartphone and their health impacts (burning sensation of the
eyes) among students (Table 6).
Table 6: Chi-Square test showing assessment of smartphone addiction and its
health impacts
|
Items |
Chi-square Value |
p<0.05 |
|
Blurred vision |
1.55 |
0.21* |
|
Water eyes |
0.12 |
0.72* |
|
Dryness in the eyes |
0.22 |
0.63* |
|
Burning sensation in the eyes |
4.13 |
0.04** |
|
Eye pain |
1.88 |
0.17* |
|
Neck pain |
0.68 |
0.40* |
|
Irritation |
0.02 |
0.88* |
|
Restlessness |
0.03 |
0.86* |
|
Stress |
0.06 |
0.80* |
|
Aggressiveness |
0.04 |
0.84* |
DF= 1; α=0.05; *All the values are statistically non-significant
**All the values are statistically
significant
DISCUSSION- To assess the
addiction to smartphones and their health impacts among students, a
cross-sectional descriptive design was used. The study was conducted at Murarji Desai Residential Science PU College Bagalkote Sector (44 Opposite). The study found a positive difference between misbehaviour and poor academic performance based on the total PUMP score, which could be attributed to smartphone use. Due to smartphone use, at least 43% of respondents felt they slept less and had less energy since they started using smartphones.[11]
The current study shows that only 16% of the participants are not addicted to their mobile phones, 28% are minor, 35% are moderate, and 21% are heavily addicted. Of the participants. Similar results were obtained in a study where researchers examined cell phone usage patterns; 58% of the sample reported not going a day without their phone. [12]
This study examined smartphone use among young adults and found four key findings. First of all, the German version of SASSV may be a suitable mechanism to measure smartphone protection. Second, long-term smartphone use is associated with addiction. Third, users who
pick up their smartphones early in the morning are more likely to become
addicted. Finally, users' social media addiction is the strongest indicator of
smartphone use. [13]
The research found that smartphone protection is more common among young adults and parents born outside Switzerland; this suggests that prevention plans should be considered, especially for this group of young people.
[14] A total of 540 participants were included in this study for
analysis, and the last ten questions were selected based on their validity as
determined by experts. The validity and effectiveness of these 10 questions
were evaluated with internal reliability, concurrent validity, and ROC
analysis. [15]
Research shows that young people who experience parental neglect have problems controlling their smartphone use. According to stress theory, our findings are consistent with previous research suggesting that adolescents engage in antisocial behaviour to avoid or reduce stress or stress resulting from parental neglect. Smartphone addiction can be considered a crime. [16]
This study concluded that mobile phone use is associated with young age and poor development and that recommending good internet use may be a protective factor. Early intervention through early detection can prevent problems related to smartphone use among children and adolescents. We hope that future research will focus on increasing the number of observers and validating the results with findings and conclusions.
[17]
CONCLUSIONS- In this
longitudinal study, overuse of Smartphones was observed for health impact. The
results showed that most of the students had eye health impacts, and many
students were at risk of health impacts from overuse of Smartphones. They need
to improve their health, provide awareness, and avoid excessive use of
Smartphones. Students had the same health impacts, like blurred vision, watery
eyes, and eye pain. The study shows most students overuse Smartphones by giving
health education, providing health tips on how to maintain good health, raising
awareness regarding health impacts, explaining the importance and limited use
of Smartphones, and explaining healthy lifestyles.
Acknowledgement- We thank the anonymous referees for their useful
suggestions. The heart is full, and words are few to express my sincere
gratitude towards those helping hands.
CONTRIBUTION OF AUTHORS
Research
concept: Jayashree Itti
Research
design: Lakshmavva Gondi
Supervision: Lakshmavva Gondi
Materials: Lakshmavva Gondi, Jayashree Itti
Data
Collection: Lakshmavva
Gondi, Jayashree Itti
Analysis and interpretation of data: Lakshmavva Gondi, Jayashree Itti
Data analysis: Lakshmavva Gondi, Jayashree Itti
Writing of the article: Lakshmavva
Gondi, Jayashree Itti
Critical review: Lakshmanva Gondi
Article editing: Lakshmavva Gondi
REFERENCES
2.
ICT Facts and
Figures-The World in 2015. [Last accessed on 2016 Nov 02]. Available from:
https://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2015.pdf.
3.
Duerson MH.
We're Addicted to our Phones: 84% Worldwide say they couldn't go a Single day
without their Mobile Device in their Hand. New York Daily News. [Last accessed
on 2016 Nov 05]. Available from:
http://www.nydailynews.com/life-style/addicted-phones-84-worldwide-couldn-single-daymobiledevice-hand-article-1.1137811.
4.
Wallace K. Half
of Teens Think they're Addicted to their Smartphones. [Last accessed on 2016
Nov 05]. Available from:
http://www.edition.cnn.com/2016/05/03/health/teens-cell-phone-addiction-parents/.
5.
Billieux
JL, van der Linden M, Rochat L. The role of impulsivity in actual and
problematic use of the mobile phone. Appl Cogn
Psychol., 2008; 22: 1195 210.
6.
Gracy GS. A
Descriptive Study to Assess the Relationship between Mobile Phone Addiction and
Risk Taking Behviour among Adolescents in Selected
Schools at Bharuch. Int J Sci Res., 2018:
8(3): 1672-75.
7.
Prime Insights. Smartphone Addiction: How technology affects public
health and social relationships.
Available at: https://primeinsights.in/smartphone-addiction/, 2015.
8.
Panwar P,
Pushpa, Raksha Y. Smartphone addiction and its health impacts among b.sc. (hons) Nursing students. Int J Adv Res., 2022;
10(08): 103-09.
9.
Balan
R, Soon S, Bikar S, Azizi Y, et al. Smartphone Addiction and Sleep Quality on
Academic Performance of University Students. J
Environ Res Public Health, 2021; 18(16): 8291. doi:
10.3390/ijerph18168291.
10.
Seung
YL, Hae KL, Jung SC, et al. The Matthew Effect in Recovery from Smartphone
Addiction in a 6-Month Longitudinal Study of Children and Adolescents. J Environ Res Public Health, 2020; 17(13): 4751. doi: 10.3390/ijerph17134751.
11. Hatem MDA, Alyahya MDH, Shaik S, et al. Smartphone addiction among university students in Riyadh, Saudi Arabia. Saudi Med J., 2016; 37(6): 675 83.
12.
Nehal B, Muninarayanappa NV, Nageshwar V. Mobile Phone Dependence
Level and Sleep Quality among Students of Selected Colleges of Moradabad.
Indian J Public Health Res Dev., 2017; 8(1): 41-45.
13.
Severin H,
Raquel PC, Min K, Andreas F, Tobias K, et al. Smartphone use and smartphone
addiction among young people in Switzerland. J Behav
Addictions, 2015; 4(4): 299 307. doi:
10.1556/2006.4.2015.037.
14.
Haug S, Paz
CR, Kwon M, et al. Smartphone use and smartphone addiction among young people
in Switzerland. J Behav Addictions, 2015; 4(4): 299
307. doi: 10.1556/2006.4.2015.037.
15.
Kwon M, Kim
DJ, Cho H, et al. The Smartphone Addiction Scale: Development and Validation of
a Short Version for Adolescents. PLOS One, 2013; 8(12): e83558.
16.
Kwak
JY, Kim JY, Won YY. Effect of parental neglect on smartphone addiction in
adolescents in South Korea. Child Abuse Neglect., 2018; 77: 75-84. doi:
10.1016/j.chiabu.2017.12.008.
17. Tateno M, Kim AR, Toe
E, et al. Smartphone Addiction in Japanese College Students: Usefulness of
the Japanese Version of the Smartphone Addiction Scale as a Screening Tool for
a New Form of Internet Addiction. Psychiatry Investig., 2019; 16(2): 115 20. doi:
30773/pi.2018.12.25.2.