Research Article
Varsha Jagdish Galani*
Varsha Jagdish Galani*
Corresponding
Author
Department
of Pharmacology, Indubhai Patel College of Pharmacy and Research Centre,
Dharmaj-388430, Gujarat, India.
E-mail: vjgalani@gmail.com, Tel.: +91-9429161203
Kalpesh Bharatbhai Mistry
Kalpesh Bharatbhai Mistry
Indubhai Patel College of Pharmacy and Research Centre, Dharmaj-388430, Gujarat, India.
E-mail: kalpeshmistry2612@gmail.com
Aasim Sirajbhai Mafat
Aasim Sirajbhai Mafat
Indubhai Patel College of Pharmacy and Research Centre, Dharmaj-388430, Gujarat, India.
E-mail: aasimmafat4@gmail.com
Het Ketankumar Shah
Het Ketankumar Shah
Indubhai Patel College of Pharmacy and Research Centre, Dharmaj-388430, Gujarat, India.
E-mail: shahhet100@gmail.com
Vrajesh Nirajkumar Jayswal
Vrajesh Nirajkumar Jayswal
Indubhai
Patel College of Pharmacy and Research Centre, Dharmaj-388430, Gujarat, India.
Tej Jagdish Galani
Tej Jagdish Galani
PharmacyTechnician,
Mohawk College, Hamilton, Canada.
E-mail: tejphy07@gmail.com
Abstract
Digital
technology use has surged, especially among younger generations, raising
concerns about its impact on health. This study examined the effects of
increased screen time on the health of college students in Gujarat, India. A
random sample of 452 students (ages 17-23) from urban and rural backgrounds
participated in a Google Forms survey covering socio-demographic data, screen
time, physical health, mental health (depression, anxiety, mood swings), and
sleep quality. Among participants, 98.89% used mobile phones, 78.09% watched
television, 73.67% used laptops, and 54.20% used tablets. Notably, 10.42% spent
over 8 hours daily on mobile devices. Many primarily used screens for academic
work and social media. While 52.22% had a normal body weight, 34.07% were underweight,
and 13.71% were overweight, possibly due to screen use during meals. Common
physical issues included body aches, eye strain, and sleep disturbances, while
mental health concerns involved insomnia, anxiety, and depression. The
Pittsburgh Sleep Quality Index (PSQI) revealed that 44.46% had poor sleep
quality (PSQI ≥5), with an average score of 4.53 ± 2.32. Overall, excessive
screen time negatively affected both physical and mental health. Promoting
balanced screen use and increased physical activity is essential for improving
student well-being.
Keywords
Digital
technology, social media, smart phone, screen time, college students, Pittsburgh sleep quality index, physical activity, radiation.
1. Introduction
The modern digital era has advanced the comfort of human life through the use of devices like televisions, computers, and mobile electronics. The digital world connects people, putting everything at their fingertips. The coronavirus pandemic has led to the widespread adoption of work-from-home practices and online education, significantly increasing screen time and negatively impacting health [1]. Since the COVID-19 pandemic, a drastic rise in screen time has been observed, particularly among college students, which has adversely affected mental health, sleep patterns, overall well-being, and academic activities [2].
Most studies have found links between excessive screen exposure and its effects on various aspects of physical, mental, and psychological health. The physical hazards of excessive screen time include eye strain, neck and shoulder pain, and back pain. Consequences for physical health include risk factors for obesity and cardiovascular conditions such as hypertension, impaired stress regulation, low levels of HDL cholesterol, and insulin resistance. Mental health hazards include increased levels of depression, anxiety, fear of missing out, and other mood disorders. Psychological health impacts include suicidal ideation and depressive symptoms, which are linked to digital device dependency, poor sleep quality caused by excessive screen time, and negativity influenced by online content [3-6].
Excessive screen time is also linked to lower self-esteem, worsened mental health, addiction, slower learning, and a higher risk of early cognitive decline [7]. Radiofrequency-modulated electromagnetic fields emitted by mobile phones are predominantly absorbed by the user’s head, impacting cerebral glucose metabolism and altering neuronal excitability [8]. Rising passive entertainment has coincided with a sharp decline in youth participation in sports, exercise, and outdoor activities over the last 10–15 years, leading to weakened social skills, isolation, and rising teen suicide rates. Creativity has declined as less time is dedicated to hands-on, problem-solving activities [9].
With screens now nearly ubiquitous, the issue is
unlikely to be resolved on its own, especially as the use of portable devices
continues to rise rapidly. Research on the impact of digital screen usage
(television, mobile phones, computers, and other portable devices) on the youth
is limited in India. Hence, the present study examined the impact of excessive
screen time on the health of college students in Gujarat, India.
2. Materials and methods
A
cross-sectional online survey was conducted involving college students of both
genders from Gujarat, with data collection taking place from February 2024 to
April 2024. A structured, validated, self-administered Google Form
questionnaire was developed after an extensive literature review. The
questionnaire underwent content validation by a panel of subject matter experts
and was pilot-tested on a small group of students to ensure clarity,
reliability, and relevance before wider distribution. The final version was
disseminated via social media platforms for data collection. The form comprised
four sections. Section I included six questions on the socio-demographic
characteristics of respondents. Section II contained seven questions related to
screen time activities, including type of screen time, screen time for
different devices, changes in screen time after COVID-19, activities
contributing to screen time, commonly used apps, the specific absorption rate
of mobile phones, and internet speed. Section III focused on the physical
impacts of screen time with five questions, while Section IV addressed mental
health impacts with three questions and included two questions on participants'
opinions regarding screen time reduction. Further, the sleep quality of the
college students was assessed using Pittsburg Sleep Quality Index (PSQI) questionnaire, which is a validated questionnaire developed by the University of
Pittsburgh, addresses 7 components, i.e. subjective sleep quality, latency,
duration, efficiency, disturbance, need for medications to sleep and day
dysfunction due to sleepiness, with the maximum score of 21 points. A global score of more
than 5 indicates poor sleep quality [10]. Incomplete Google forms data was
excluded from the study. Data
collected in Google Form were analyzed using Microsoft Excel spreadsheet.
Descriptive statistics were calculated using frequencies and percentages. The data were analyzed through SPSS
20.0 and the Chi-square test was used to find out the association between
variables at a significance level of p < 0.05.
3. Results
Demographic data of the total of 452 students who participated in the study are shown in Table 1. Of the total participants, 57.3% were males and 42.6% were females. Additionally, 61.9% of participants were from rural areas, while 38.1% were from urban areas. Most students came from lower and middle-class backgrounds, with only 17.92% from high-income families. A total of 52.22% of participants had normal body weight, while the remaining participants were either underweight (34.07%) or overweight (13.71%).
Table1. Demographic data of the college students
Variables | Frequency (n=452) | Percentage (%) |
Gender |
|
|
Male | 259 | 57.3 |
Female | 193 | 42.6 |
Residence |
|
|
Rural | 280 | 61.95 |
Urban | 172 | 38.05 |
Socioeconomic status |
|
|
< 2 lacs (Lower class) | 94 | 20.79 |
2-4 lacs (Upper lower) | 31 | 6.86 |
4-8 lacs (Lower middle) | 99 | 21.90 |
8-16 lacs (Upper middle) | 147 | 32.52 |
>16 lacs (Upper class) | 81 | 17.92 |
Basal Metabolic Index (BMI) |
|
|
Underweight (<18.5 BMI) | 154 | 34.07 |
Normal (18.5-24.9BMI) | 236 | 52.22 |
Overweight (25.0-29.9 BMI) | 35 | 7.74 |
Obese (≥30.0 BMI) | 27 | 5.97 |
Data related to screen time activities are shown in Tables 2 and 3. A total of 63.05% of respondents engaged in both active and passive screen time, while 10.84% engaged only in active screen time and 5.75% engaged only in passive screen time. After COVID-19, screen time increased for 78.09% of participants. The devices used for screen time included mobile phones (98.89%), laptops (73.67%), tablets (54.20%), and televisions (78.09%). The screen time activities of students included college work (72.56%), social media (67.26%), watching movies/TV series/streaming platforms (46.02%), playing video games (32.52%), video calls (30.53%), and other activities (0.88%). Instagram was the most used app among participants (58.84%), followed by YouTube (29.21%), WhatsApp (18.58%), Chrome (11.72%), and Snapchat (8.85%). The specific absorption rate (SAR) of cell phones was found to be <1.60 W/kg in 98.23% of participants and >1.60 W/kg in 1.76% of participants.
Table 2. Distribution of digital devices usage time in the college students.
Usage time | Mobile | Laptop | Tablet | Television |
< 1 hour | 67 14.82% | 188 41.59% | 184 40.71% | 184 40.71% |
1-2 hour | 91 20.13% | 82 18.14% | 32 7.08% | 87 19.24% |
2-4 hour | 121 26.77% | 30 6.64% | 32 7.08% | 48 10.62% |
4-8 hour | 121 26.77% | 27 5.97% | 23 5.09% | 28 6.19% |
>8 hour | 47 10.39% | 6 1.33% | 6 1.33% | 6 1.33% |
Not use at all | 5 1.11% | 119 26.32% | 173 38.27% | 99 21.90% |
Table 3. Distribution of screen time activities in the college students
Variables | Frequency (n=452) | Percentage (%) |
Types of Screentime use |
|
|
Active | 49 | 10.84 |
Passive | 26 | 5.75 |
Both | 285 | 63.05 |
Scrrentime increase after COVID-19 |
|
|
Yes | 353 | 78.09 |
No | 99 | 21.91 |
Activities contribute to screen time |
|
|
College work | 328 | 72.56 |
Social media | 304 | 67.26 |
Watching movies/T.V series/Streaming plateform | 208 | 46.02 |
Playing video | 147 | 32.52 |
Video call | 138 | 30.53 |
Others | 4 | 0.88 |
Apps most used |
|
|
Instagram | 266 | 58.84 |
YouTube | 132 | 29.21 |
Whats App | 84 | 18.58 |
Chrome | 53 | 11.72 |
Snapchat | 40 | 8.85 |
Other | 33 | 7.3 |
Specific absorption rate (SAR) |
|
|
>1.60 W/kg | 8 | 1.76 |
<1.60 W/kg | 444 | 98.23 |
Internet speed |
|
|
< 1 mbps | 128 | 28.32 |
1-5 mbps | 200 | 44.24 |
6-10 mbps | 56 | 12.38 |
>10 mbps | 68 | 15.04 |
Data regarding the impact of screen time on the physical health of participants is shown in Table 4. The per-day physical activity levels were as follows: <1 hour in 37.83%, 1-2 hours in 34.07%, 2-4 hours in 19.91%, and >4 hours in 8.19% of respondents. Additionally, 28.54% of participants used screens every day while eating, while 36.28% used screens occasionally during meals. Of those using screens during meals, 81.85% used them for up to 30 minutes, while 18.14% did not use screens at all during meals. A total of 17.04% of participants reported eye defects, including short-sightedness, long-sightedness, or both. Physical complaints due to excessive screen time included eye pain (13.05%), headaches (37.61%), lower back pain (8.84%), neck and shoulder pain (19.69%), and back pain (32.97%).
Table 4. Distribution of physical impact of screen time on the college students
Variables | Frequency (n=254) | Percentage (%) |
Physical work time |
|
|
<1 hr | 171 | 37.83 |
1-2 hrs | 154 | 34.07 |
2-4 hrs | 90 | 19.91 |
>4 hrs | 37 | 8.19 |
Screen time frequency during meal |
|
|
Everyday | 129 | 28.54 |
Sometimes | 164 | 36.28 |
Rarely | 77 | 17.03 |
Never | 82 | 18.14 |
Screen time during meal |
|
|
<10 min | 134 | 29.65 |
>30 min | 19 | 4.20 |
10-15 min | 140 | 30.97 |
16-25 min | 50 | 11.06 |
26-30 min | 27 | 5.97 |
None of these | 82 | 18.14 |
Eye Defect |
|
|
Yes | 77 | 17.04 % |
No | 375 | 82.96% |
Short sightedness (Myopia) | 66 | 14.60 % |
Long sightedness (hypermetropia) | 74 | 16.40 |
Both | 30 | 6.70 |
Not at all | 282 | 62.30 |
Body pain while using screen |
|
|
Eye pain (redness of eyes) | 59 | 13.05 |
Headache | 170 | 37.61 |
Lower back pain | 40 | 8.84 |
Neck and shoulder pain | 89 | 19.69 |
Back pain | 149 | 32.97 |
Data regarding the mental impacts of screen time on college students is shown in Table 5. A total of 46.24% of participants had the habit of watching screens while falling asleep. Additionally, 41.59% interacted with screens as soon as they woke up, 39.38% used screens within an hour of waking, and 19.03% used screens several hours after waking. Mental health changes, such as behavior changes, anxiety, depression, insomnia, guilt, irritability, eating disorders, trauma, and thoughts of suicide, were observed in 20.35% of participants.
Table 5. Distribution of mental impacts of screen time on the college students
Variables | Frequency (n=452) | Percentage (%) |
Fall asleep while watching screen of devices |
|
|
Yes | 209 | 46.24 |
No | 243 | 53.76 |
Interact screen while waking up |
|
|
As soon as wake up | 188 | 41.59 |
Within an hour of waking up | 178 | 39.38 |
Several hours after waking up | 86 | 19.03 |
Mental changes observed | 92 | 20.35 |
Trauma | 2 | 0.44 |
Thoughts of suicide | 3 | 0.66 |
Irritability | 21 | 4.65 |
Guilty | 22 | 4.86 |
Behaviour changes | 50 | 11.06 |
Depression | 15 | 3.32 |
Eating disorder | 21 | 4.65 |
Insomnia | 27 | 5.97 |
Anxiety | 35 | 7.74 |
Sleep quality was assessed using the validated Pittsburgh Sleep Quality Index (PSQI), which has seven components. The results are shown in Table 6. Based on responses to the PSQI questionnaire, 7.52% of students rated their subjective sleep quality as "fairly bad" or "very bad." A total of 10.6% of students had a sleep latency of >30 minutes, and 20.79% of participants had a sleep duration of <6 hours per day. Habitual sleep efficiency of <75% was observed in 23.67% of respondents. Approximately 40.26% of respondents reported sleep disturbances, such as waking at night, getting up to use the bathroom, difficulty breathing, snoring, feeling too hot or cold, bad dreams, pain, or other reasons. About 23.23% reported using sleep medications, and 33.62% reported daytime dysfunction and reduced enthusiasm in the past month due to sleep disturbances and inadequate sleep. A total of 201 (44.46%) participants had a global PSQI score ≥5, indicating poor sleep quality, while 251 (55.53%) participants had a global PSQI score <5. The mean global PSQI score was 4.53 ± 2.32.
Table 6. Pittsburg sleep quality index of the college students
PSQI | Grade ‘0’ (Very good) | Grade ‘1’ (Fairly good) | Grade ‘2’ (Fairly bad) | Grade ‘3’ (Very bad) | Mean | SD | ||||
n | % | n | % | n | % | n | % | | | |
Sleep quality | 304 | 67.3 | 114 | 25.2 | 23 | 5.1 | 11 | 2.4 | 0.41 | 0.33 |
Sleep latency | 230 | 50.9 | 126 | 27.9 | 48 | 10.6 | 48 | 10.6 | 0.81 | 0.42 |
Sleep duration | 209 | 46.2 | 149 | 33 | 66 | 14.6 | 28 | 6.2 | 0.80 | 0.39 |
Habitual sleep efficiency | 200 | 44.2 | 145 | 32.1 | 56 | 12.4 | 51 | 11.3 | 0.91 | 0.34 |
Sleep disturbance | 270 | 59.7 | 87 | 19.2 | 55 | 12.2 | 40 | 8.8 | 0.70 | 0.44 |
Sleep medication | 347 | 76.8 | 59 | 13.1 | 33 | 7.3 | 13 | 2.9 | 0.36 | 0.19 |
Day time dysfunction | 300 | 66.4 | 78 | 17.3 | 61 | 13.5 | 13 | 2.9 | 0.54 | 0.21 |
Global score: 0 – 21 | 4.53 | 2.32 |
4. Discussion
Recent data show that 67% of the global population, or 5.4 billion people, are using the internet [11]. The Digital India initiative and growing internet access have led to over 751 million active users in India as of January 2024. Notably, 96% of internet users aged 16 to 64 in India own a mobile phone, and 5% own virtual reality devices. There are 462 million active social media users in India [12, 13]. The affordability of internet access is increasing across regions and income groups, with no significant differences in digital device usage across gender, socioeconomic status, or urban/rural areas in our study.
Mobile phones are the most widely used digital devices among youth participants (95%), with most spending over 2 hours daily on screens, which is consistent with other Indian studies [13-15]. Most participants reported increased screen time post-COVID, using devices for academic work and social media. Instagram was the most popular app, followed by YouTube, WhatsApp, Chrome, and Snapchat [16]. Nearly all participants (98.6%) used mobile phones with a SAR below 1.60 W/kg, complying with international safety standards [17]. The lack of physical activity among participants may lead to cardiovascular issues, obesity, and chronic conditions like diabetes and heart disease [3]. Prolonged screen exposure was linked to eye pain, myopia, hypermetropia, and headaches [18-21], as well as musculoskeletal pain in the neck, shoulders, and back [22-24]. Blue light exposure at night may impair sleep quality and duration [25, 26]. Mental health issues such as insomnia, depression, anxiety, eating disorders, and suicidal thoughts were reported by some participants, aligning with previous studies [5, 27, 28].
Sleep disturbances are increasingly prevalent, especially among young people, and worsened by technology use. The Pittsburgh Sleep Quality Index (PSQI) revealed that 7.5% of participants had poor sleep quality, while 20% faced issues with sleep latency, duration, and disturbances. Increased screen time was linked to shorter sleep duration, poor sleep quality, and longer sleep latency. A global PSQI score ≥5, indicating poor sleep, was reported by 44.46% of participants, while 55.53% scored <5, indicating good sleep quality. The mean PSQI score for college students was 4.53 ± 2.32, suggesting overall good sleep quality, though still influenced by excessive screen time, in line with findings from other studies in India [29, 30].
The findings highlight the need to reduce screen time and promote healthier lifestyles. The government should set screen time guidelines, integrate digital detox into public health campaigns, and promote digital literacy in schools and colleges. Educational institutions can regulate screen exposure through structured breaks and a balanced digital-traditional approach. Employers should adopt wellness policies with screen breaks, ergonomic setups, and blue light reduction. Implementing these measures can help India foster a healthier digital lifestyle while ensuring technology benefits overall well-being.
5. Conclusions
Excessive screen time among Gujarat college students negatively impacts physical and mental health, causing eye strain, headaches, musculoskeletal pain, anxiety, depression, and poor sleep. High usage, mainly for academics and social media, underscores the need for balanced screen time, physical activity, and better sleep hygiene. Implementing guidelines, digital literacy, and wellness policies can help foster healthier lifestyles and maximize technology’s benefits.
Authors’ contributions
Concept and wrote manuscript, V.G., T.G.; Collected data and analyzed, K.M., A.M., H.S., V.J.
Acknowledgements
The authors don't have anything to acknowledge.
Funding
This research received no external funding.
Availability of data and materials
All relevant data are within the paper and its supporting information files. Additional data will be made available on request according to the journal policy.
Conflicts of interest
Authors declare that there is no conflict of interest.
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Abstract
Digital
technology use has surged, especially among younger generations, raising
concerns about its impact on health. This study examined the effects of
increased screen time on the health of college students in Gujarat, India. A
random sample of 452 students (ages 17-23) from urban and rural backgrounds
participated in a Google Forms survey covering socio-demographic data, screen
time, physical health, mental health (depression, anxiety, mood swings), and
sleep quality. Among participants, 98.89% used mobile phones, 78.09% watched
television, 73.67% used laptops, and 54.20% used tablets. Notably, 10.42% spent
over 8 hours daily on mobile devices. Many primarily used screens for academic
work and social media. While 52.22% had a normal body weight, 34.07% were underweight,
and 13.71% were overweight, possibly due to screen use during meals. Common
physical issues included body aches, eye strain, and sleep disturbances, while
mental health concerns involved insomnia, anxiety, and depression. The
Pittsburgh Sleep Quality Index (PSQI) revealed that 44.46% had poor sleep
quality (PSQI ≥5), with an average score of 4.53 ± 2.32. Overall, excessive
screen time negatively affected both physical and mental health. Promoting
balanced screen use and increased physical activity is essential for improving
student well-being.
Abstract Keywords
Digital
technology, social media, smart phone, screen time, college students, Pittsburgh sleep quality index, physical activity, radiation.

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This work is licensed under the
Creative Commons Attribution 4.0
License.(CC BY-NC 4.0).