Mobile usage among degree college students in industrial township of western Maharashtra - “A descriptive study”

Abstract

Background:

With the advent of smartphones, there is an exponential increase in mobile usage and addiction. The statistics pointing toward mobile dependence in adolescents are of paramount importance to assess the prevalence in them and suggest measures accordingly.

Aim:

To observe the usage and dependence among the degree college students in an industrial township.

Materials and Methods:

A validated and structured questionnaire was distributed among the students at a women's degree college in western Maharashtra and responses were collected after obtaining consent. Along with sociodemographic details, qualitative and quantitative information regarding mobile usage were collected. Data were cleaned, coded, and analyzed after ensuring the confidentiality of their information using SPSS v26.0.

Results:

The mean age of the participants was 18.9+/-1.8 years. The mean time spent on mobile was 2.4+/-0.4 hours per day. Mobile dependency was found in 48% of participants. The mean total score was 92. The primary purpose for using the internet was to browse (41%) and social media 36%. The main benefit of using the internet was searching for information urgently (62.5%). A major limitation of using was felt as the internet to be very slow 61 (42.3%).

Conclusion:

There is a high prevalence of smartphone dependence in college students.

Technology has permeated people, irrespective of gender, age, or area of living, because of developments that have taken place in the improvement of basic feature phones to smartphones. In the past 10 years, mobile phones have transformed from being the main tool for communication either between one to one or between groups or among groups. With the advent of smartphones, this exponential transition is furthered. The main benefit is that it is real-time, portable, and has access to the Internet most of the time, anywhere, with a variety of social media applications. These capabilities have led to a wider acceptance of and increased usage of cell phones among children and adolescents in addition to adults. With 560 million Internet users (almost 41%) in 2018, India is the largest field for digitalization and is growing swiftly in this aspect.[1] More than the people using mobiles in the United States of America and China, the average time spent on social media by Indians is 17 hours per week. The COVID-19 pandemic had its effect on this augmentation.[1] Adolescent population in our country, India is one of the highest in the world (253 million), and they are one-fifth of the total Indian population. Adolescents constitute one-fifth of the total Indian population, approximately 25 crores. The majority of the 15-year-old to 24-year-old entry-level smartphone users in India are students. Teen dependence on mobile phones has developed into a type of behavioral addiction that is becoming more common overall.[2] This mobile dependence has increased three-fold during the first wave of the COVID-19 pandemic, where people were asked to dwell inside their homes due to lockdown restrictions.[3] The mobile and television were the major means of communication to the happenings of the outside world. Although TV was the bigger and heavier mode, which cannot be afforded by everyone compared to the affordable mobile. This made mobile more reachable to all levels of society and easier to get dependent or addicted. The storm of development in digitalizing India, in the 21^st century precisely from 3G to 4G and 5G made the mobile an irreplaceable one to all levels of society. Linking Aadhaar, PAN, and Bank accounts also made mobile a necessity. This was coupled with the reduction of the cost of mobile data which made it reachable to all levels of society. As the mobile is a double-edged sword, the negative shades are the most alarming ones. Mobile addiction has also led to an increase in the number of suicides in society due to bank frauds and addiction to monetary games such as mobile rummy and others.[4] The age of initiation of mobile usage is coming down significantly for which the adverse effects are imminent. For example, when the discriminatory capacity of the child is not fully developed and the child starts to use all aspects of mobile features, it is likely to have a negative impact in the real world compared to the virtual mobile world. In view of the above present study was undertaken to observe the usage and dependence among the degree college students in an industrial township.

MATERIALS AND METHODS

This observational cross-sectional study was planned after looking at and understanding the gravity of the issue. Institutional scientific and ethical committee permissions were obtained before the start of the study (vide letter No.: I.E.S.C./152/2022). The study was undertaken from June 1, 2022 to August 15, 2022.

Study population

The sample was drawn from Degree College in an industrial township of western Maharashtra. There were no specific exclusion criteria and all the students had a mobile and were willing to participate in the study constituting the sample of the population under study.

Sample size

Considering the prevalence of mobile dependency by Gangadharan et al.[2] to be 33% at an acceptable difference of 8%, with a significance level of 95% and a power of 80%, the minimum sample size is calculated to be 133. The software used was WinPepi v11.68.

Procedure

All the degree colleges with student strength of more than 150 students were enumerated and given numbering. These numbers were placed in a lot and by lottery method one chit was picked up. The college turned out to be a women's degree college and we continued with the selection by the lottery.

Data collection

Data were collected using the structured, validated questionnaire. Questionnaire forms were distributed among the students and information was collected after assuring the confidentiality of their information.

Data analysis

Data analysis was done using Statistical Package for Social Sciences 26 (IBM, Armonk, USA). Continuous variables were expressed as mean and standard deviation or median and interquartile range according to the normality of the distribution. Categorical variables were expressed as proportions. Appropriate statistical tests were applied to test the association between the variables.

RESULTS

A total of 144 students participated in the study by filling out the forms. As this was a women's degree college, all the participants were females. Their age ranged from 17 to 35 years, with a mean and standard deviation of 18.94 and 1.81, respectively. The majority of them were 18 years old and living in a family size of 4. The monthly income of the family ranged from 30,000 INR to 250,000 INR, median and interquartile range of 30,000 INR. Almost two-thirds (68.7%) of the participants were using mobile phones for 2-3 hours, the average duration being 2.43 hours. Mobile dependence was measured according to the validated scoring scale and classified into four categories. Average test scores were 92+/-20.2, range 138-49. Approximately half (51.4%) of the participants were dependent on mobile. The majority of the participants had four family members, 52 (36.11). While almost one-third of the participants never play online games, 91 (66.67%) more than half gave a positive response about using mobile while being in bed. Almost 80% of students said that they interact with 5-15 people per day on average on social media, spend almost 2 hours on average per day, and make less than 10 calls per day. The positive side of turning off the mobile or keeping it in silent mode was observed in 62 (43.06%) students. The majority were living in a nuclear family 84 (57.64%). Less than 30% said that they go to sleep or sleep less because of their mobile phone. Around 40% of students felt that they were excessively using mobile phones. An agreement was made between the test dependence result and the personal grading and rating of mobile dependence. The weighted kappa statistics for the agreement were found to be 0.574+/- 0.05, which is a moderate-level agreement [Table 1]. For better appropriation, adjustment was done by categorizing the responses to test the independent association. Several important variables were significantly associated with mobile dependence, presented in Table 2. The primary purpose for using the internet was to browse (41%) and social media 36%. The main benefit of using the internet was searching for information urgently at any time (62.5%). A major limitation of using was felt as the internet to be very slow 61 (42.3%).

Table 1.

Independent association of significant variables with mobile dependence

Variables response		Dependence		Independent association
		Yes (%)	No (%)
Using mobile while being in bed	Yes	49 (66.22)	25 (33.78)	Chi-square=13.397, df=1, (p<0.0001)
	No	25 (35.71)	45 (64.29)
Use mobile because of being bored	Yes	57 (63.33)	33 (36.67)	Chi-square=13.706, df=1, (p<0.0001)
	No	17 (31.48)	37 (68.52)
I don’t think I could stand 1 week without mobile phone	Yes	37 (69.81)	16 (30.19)	Chi-square=11.394, df=1, (p<0.0001)
	No	37 (40.66)	54 (59.34)
The first thing I do when I get up in the morning is to see if someone has called me, sent me an SMS or written to me through social media	Yes	50 (66.67)	25 (33.33)	Chi-square=14.058, df=1, (p<0.0001)
	No	24 (35.29)	44 (64.71)
When my mobile phone is in my hand, I can’t stop using it	Yes	40 (72.73)	15 (27.27)	Chi-square=16.22, df=1, (p<0.0001)
	No	34 (38.2)	55 (61.8)
Lately I’ve been using my mobile phone more and more	Yes	57 (74.03)	20 (25.97)	Chi-square=33.948, df=1, (p<0.0001)
	No	17 (25.37)	50 (74.63)
When I haven’t used my mobile phone for a while, I feel the need to call someone, or to contact someone through social media	Yes	48 (76.19)	15 (23.81)	Chi-square=27.578, df=1, (p<0.0001)
	No	26 (32.1)	55 (67.9)
Hours on social media spent per day	<2	28 (35)	52 (65)	Chi-square=19.353, df=1, (p<0.0001)
	>2	46 (71.88)	18 (28.12)

Table 2.

Agreement between dependence test severity and personal grading of mobile dependence

Personal Grading	Dependence test severity				n (%)
	No	Mild	Moderate	Severe
No	52 (36.11)	12 (8.33)	1 (0.69)	0 (0)	65 (45.1%)
Mild	17 (11.8)	27 (18.75)	9 (6.25)	0 (0)	53 (36.8%)
Moderate	1 (0.69)	9 (6.25)	7 (4.86)	1 (0.69)	18 (12.5%)
Severe	0 (0)	6 (4.17)	1 (0.69)	1 (0.69)	8 (5.6%)
	70 (48.6%)	54 (37.5%)	18 (12.5%)	2 (1.4%)	144 (100%)
Weighted Kappa=0.57443			Standard error=0.05341

DISCUSSION

The diagnosis of mobile dependence or addiction remains controversial as there are no clear-cut definitions or criteria given by the classificatory systems.[4] There have been many studies conducted in India and worldwide on the aspect of mobile dependence, mobile addiction, and internet addiction using wide varied scales and tools. Studies conducted in Indian settings had reported the prevalence of mobile phone dependence to be 30%-40%.[5,6,7] Prevalence studies done across the world have presented a wide range of mobile dependence, from 0% to 60%.[8,9] The results were both surprising and alarming. A proportion more than half being mobile dependent in a women's degree college was not an expected finding. The proportion of mobile dependents is a little higher compared to studies done in other Indian settings, owing to the possible increase in mobile usage post-COVID-19. The average test score of 92 with a range of 138 and 49 gives a positive impression as there are a smaller number of severe mobile dependents. A good number of students were not dependent on mobile (48.6%). The type of family and number of people in the family were not associated with dependence similar to the findings of other studies. A rampant increase in social media coverage and usage is an alarming finding wherein students are spending almost 2-3 hours per day on social media via mobile.[5] The median time spent on mobile was comparable to a similar study conducted in Nepal where it was 3.5 hours. This amounts to significant amounts of time where productive activities could be carried out. The majority of the students were not turning off their mobiles before going to bed, not even in silent mode. Also, a significant proportion were using the mobile while in bed and even replying to text messages or social media notifications at the earliest. This opens Pandora's box of questions where the doubt arises, “Are we using the mobile or is it using us?”. When students agree either strongly or normally, to statements pointing to their compulsiveness to use mobile, it is an extremely important aspect of behavior to be addressed. “I use my mobile phone because I am bored,” “I go to sleep later or sleep less because of my mobile phone use,” “Lately I've been using my mobile phone more,' “When my mobile phone is in my hand, I can't stop using it,” and “I don't think I could stand 1 week without a mobile phone”. Many of the students feel they cannot withstand without a mobile for a week and agree that they have been using the mobile more and more recently. Agreement upon sleep disturbances or less sleep due to mobile usage has to be taken care of by the students themselves, family, and teachers. Advising proper ways to use mobile and not getting into the vicious cycle of usage is of paramount importance.[10]

Limitations

First, as this is a cross-sectional study, the inherent limitation is that causal relationships cannot be established. Second, women's degree college brings a gender drawback, but the study opens the scope of further research and also contributes to the meta-analysis. Third, data were collected using self-reported forms at a mass level, which might produce some response bias due to social desirability.

CONCLUSION

There is a high prevalence of “Mobile addiction” in college students. “Mobile addiction” can be said as an “addiction' when the usage of mobile goes beyond the need for usage and includes compulsiveness to the extent beyond voluntary control or failing to control so. The need for usage of mobile can be measured by the amount and quality of data retrieved by the user and depends on whether the information was sought or dumped. These data retrieved can be both useful and not useful, the useful data retrieved from the mobile can lead to an improvement in the knowledge of the person, and move the next step toward the academic career or improvement in the knowledge of a person. The nonuseful data retrieved are not useful but a temporary memory that just acts as time leaches. The balance between useful and nonuseful data shows us whether we are judicious mobile users or not. The mobile-dependent society is not to be blamed but alarmed and educated. They are to be guided toward betterment in their usage patterns. Health education and awareness campaigns along with sessions of training for the students would reap excellent results with augmentation of the technology.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.