Department of Education, Doctor Harisingh Gour Vishwavidyalaya. (A Central University) Sagar (M.P.), India.

Corresponding author email: akhand.sharmandl@gmail.com

Article Publishing History

INTRODUCTION

Leisure is perceived as an antidote to all types of psychological and physiological problems, but if we used it in an improper way this pill will create problems for us. Most adolescents around the world are online and involved in social networking this has becomes popular activity among adolescents during their leisure time, in the past 10 years. Previous studies have found that 70–90 percent of adolescents use SNSs, most commonly Facebook  (Madden et al., 2013). The average time spent with screen media among 08-18-year-olds is more than twice the average amount of time spent in school every year (Kaiser Family Foundation Study, 2010 and National Center for Education Statistics, 2007–2008).

It is quite observed that during leisure time adolescents are using digital gadgets for their enjoyment, a study by, Pew Research Center (2015) found that 93 percent of smartphone owners aged18–29 years, use the device to avoid boredom. John Coleman and Leo Hendry’s focal theory linked age-graded relational concerns with leisure transitions during adolescence. In late adolescence, casual leisure gives way to commercialized leisure (e.g., visiting pubs, discotheques, sports clubs, or wellness centers), which adolescents use to affirm their maturity and independence from parents (Maria and Rainer, 2015 Gupta 2020).

Now from 22^nd March 2020 onwards due to pandemic COVID-19 schools were shut down and regular classes are not going on.  Classes are conducting through online mode for senior secondary classes, due to which the usage of electronic gadgets like smartphones has been increased among adolescents and now they are getting more leisure-time. Even in some cases, it is observed that students are bunking classes and are involved in online games, chatting, and other activities besides studying.

Public health expert and executive director of Population Foundation of India (PFI), Poonam Muttreja says, “In this digital day and age, being stuck at home during lockdown also means increased and sometimes unfettered access to television and social media, which can negatively impact their mental health”. “At 243 million, India has the largest adolescent population in the world who are greatly at risk today” (Muttreja, 2020).

Socialising in context to leisure activities implies social interaction (Kelly, 1981), consequently, when there is little or no interaction during an activity, the meaning changes and leisure is converted into entertainment (Rojek, 2006). The connection to a network of people communicating via machines, defined by Allen (2010) as social connectivity, differs from face-to-face interaction because digital technologies multiply the opportunities for social interaction (Allen, 2010). Technologies used for socialisation can be shown with the help of the given Table1. Participation in virtual environments (online games, social media, etc.) develops skills that facilitate interpersonal relationships (Schroeder, 2010).

Table 1. Popular Communication-Orientated Internet Technologies

Social network sites (SNSs)	Facebook(2006),  Bebo (2005), My Space (2003)
Mobile phone applications	Viber (2010), What’s App (2009)
Blogs	Blogger (2003), WordPress (2003)
Microblogs	Twitter (2006)
Video sharing	YouTube (2005)
Photo sharing	Instagram (2010)
Massively multiplayer online computer games (MMOG)	World of Warcraft (1994)
Virtual worlds	Club Penguin (2005), Moshi Monster (2007) Online simulated 3D environments where users construct avatars, assume fantasy roles and interact with other players.

Source: Kennedy and Lynch, 2016, p.3

The current generation of adolescents has been variously conceptualized with theoretical categories including “screenagers”, “digital native”, and as “Net Generation” by ( Rushkoff, 1999; Tapscott, 2008; Palfrey and Gasser, 2008). Social networking sites such as Facebook, MySpace, Google+, and Twitter are a regular part of leisure in everyday life among people of various age groups, genders, and racial/ethnic backgrounds (Iryna and Monika, 2015). A survey of young British people aged 11–16 found that participants chose different SNS platforms to ‘manage’ different types of friendship relationships. For example, Facebook was mainly used to communicate with ‘friends’, whereas Snapchat and Instagram were mainly used to communicate with ‘close friends’ (Wang and Edwards, 2016).

There are currently around 1.28 billion monthly active users (MAUs) of Facebook worldwide, with a yearly increase of 15% (Facebook, 2014). For adolescents, SNSs are now “a primary way of communicating with and acquiring information about others in their social network”, including family and friends (Engelberg and Sjöberg, 2004; Spies and Margolin, 2014). Bargh and McKenna (2004) maintained that this is because SNS’s possess unique features for sharing personal information including photos, “likes”, and reflections via “wall posts” and “status updates” (Bargh and McKenna, 2004).

SNS activities have become a core part of teen culture, redefining the meaning of the word friend in this global digital community and it provides a platform to enjoy their leisure time by using digital technology. SNSs may, therefore, provide an advantage in understanding adolescents’ inner lives and in building relationships with them (Subrahmanyam et al., 2009). Social activities with friends continue to be identified by many adolescents as the most important and valued leisure activities (Abbott-Chapman, 2001).

Technology and adolescent’s worlds were identified in 2009 as an important area for development (Fok et al., 2009). Digital technologies for adolescents are essentially and primarily “tools for leisure and sociability” (Sánchez-Navarro and Aranda, 2013). Individuals’ engagements with these technologies are increasingly being considered forms of “technologically mediated leisure”, or “digital leisure” (Parry and Penny Light, 2014; Sintas et al., 2015; Spracklen, 2015; Valtchanov et al., 2016). Digital leisure activities, including social interaction, have been transformed into the traditional way of planning and performing face-to-face leisure activities, it’s all due to digital technologies.

Digital leisure significantly expands  the “sphere of sociability” in which individuals can come together online (Parry and 2013; Laura et al., 2016). Digital leisure helps in receiving support, form friendships, and explore mutual interests and identities (Drotner, 2008). Adolescents’ digital leisure takes many forms and is frequently done simultaneously (Tapscott, 2008), including texting friends, downloading music, uploading videos, sharing photos, perusing Facebook profiles, and updating Twitter comments, to name a few common practices (Bronwen and Parry, 2017).

Social media usage and Asia’s present position along with India’s are highlighted through, published reports, there were 3.5 billion social media users worldwide and this number is continuously growing (Emarsys, 2019). Social media usage is one of the most popular online activities, in 2018, around 2.65 billion people were using social media worldwide, a number projected to be increased to almost 3.1 billion in 2021 and the number of social media users in India were 326.1 million in 2018 and expected to be almost 448 million in 2023 (Clement, 2019).

Global Digital Year Book,  the report showed that the average amount of time per day spent by Indians on the internet; surfing via mobile phone 03:43 hours and through computers (desktops, laptops or tablet) 04:03 hours whereas social media usage via any device, 02:32 hours. The report, highlighted the facts related to digital technology shown in the given Fig.1 (Kemp, 2019).

Figure 1:  Digital Technology and its Users

Source: Global Digital Year Book, 2019, p.7

The world’s most visited websites as per the report by Hootsuite; Google stands first, as far as social networking sites were concerned Facebook stands third, Twitter, seventh, and Instagram, tenth. Mobile social media growth rankings are concerned India ranked second with an absolute increase of +60 million users and growth rate of +26 percent. According to 2018-19, monthly mobile data use by North-East Asia is 12.1 billion gigabytes which are highest than other regions of the world, whereas Global Mobile App rankings by monthly active users; Facebook ranks first, WhatsApp Messenger second, Facebook Messenger third and WeChat ranks fourth place (Global Digital Year Book, 2019).

The above discussion covers all the aspects related to digital technology, emphasizing social networking sites and the active user worldwide. It is seen that adolescents nowadays engaged in online activities, during leisure time for socialising with peers and making new relationships, The need and significance of the proposed study, to explore the facts related to digital leisure, adolescence, and social activities.

The study will help in creating awareness amongst adolescents, parents, school teachers, and administrators about the negative impacts of social media and provide suggestions to channelise the potential of adolescents in the right direction. The study supports, Family Media Use Plan, minimise unhealthy habits and behaviours due to the use of traditional and new media that can negatively affect health, wellness, social and personal development, and academic performance and success (Reid-Chassiakos, 2016).

The term ‘social network sites’ is relatively new, there has been a growing body of literature focused on their impact on psychological health (Lemola et al., 2015; Moreau et al., 2015). Some of these studies have found a relationship between depression and the amount of time spent on SNSs (Pantic et al., 2012; Wright et al., 2013). However, others have reported no direct relationship between the amount of time spent on SNSs and depressive symptoms (Datu and 2012; Jelenchick and 2013; Simoncic et al., 2014).

The above reports reflected that due to excessive use of technology and engagement on  SNS, makes our youth ‘digitoholic’. It will affect their academic achievement, mental health, physiological problems, disturbed family, social relations , and various other problems, being a researchers we must find the best plausible solution for this. The understudy follows the instructions and moves ahead in this direction, to study the indulgement of an adolescent in online activities and later suggested remedial measures for it. Research is needed on how parents can supervise and guide their children’s media use (Reid-Chassiakos, 2016).

Objectives of the Study: To check the mediating effect of  Digital leisure in the  relation of independent variable LIM to  dependent variable Adolescent health problems, to study the social activities of boys and girls students, to study the Digital Leisure (DL)  of science and non-science students and to study the Digital Leisure (DL)  of boys and  girls  students.

Hypotheses of the Study:i) Ho: Digital Leisure mediates the  effect of Leisure Interest Measure on Adolescent Health Problems ii) Ho: There will be statistically no significant difference between boys and girls social  activities. iii) Ho: There will be statistically no significant difference between science and non-science student’s  digital leisure, iv) Ho: There will be statistically no significant difference between boys and girls  digital leisure

MATERIAL AND METHODS

The study was a descriptive survey-based, conducted on adolescents studying in  Grade XII between (16-19 years) in CBSE affiliated schools from India and BHSEC governed schools in Bhutan. Two-stage stratified sampling was used; firstly based on geographical locations and secondly based on the demographic stat. The study had selected, 460 adolescents, studying in senior secondary classes in science and non-science streams, from three regions of India; north, central and north-eastern parts as well two schools randomly selected from Bhutan.

The schematic representation of the selected sample has been shown in tabular form:

Table 2. Selected Sample for Study

S. No.	Region	School Location	Science Students	Non-Science Students	Total Students
1.	Central India	Sagar (M.P. Gwalior (M.P.)	30 33	26 55	56 88
2.	North India	Agra (U.P.) Bhimtal (U.K.)	58 –	62 31	120 31
3.	North-East India	Guwahati (Assam)	35	27	62
4.	Bhutan	Two Schools Selected	59	44	103
GRAND TOTAL			215	245	460

The study had used two questionnaires: Leisure Interest Measure (LIM), 29 items; 17 items had been selected from reading, physical, outdoor, artistic and social sections. A standardised questionnaire, designed by the investigator; Smart Phone Usage Pattern (SPUP), was used for studying the digital activities during leisure time (Beard and Ragheb, 1980). The study tried to understand the socialisation activities amongst adolescents using digital technology.

Dependent Variable- LIM, Social Activities, Anxiety Level, Time Spent _SNS, Health Problems, Independent Variable- Boys and Girls, Science and Non-Science Stream and  Mediating Variable-  Leisure using Digital Technology (Digt_Leis). SPSS-21 and AMOS- 23 were used for testing the research model and hypotheses. Apart from it, qualitative analyses were used to explore other additional facts. Model fit criteria proposed by Bagozzi and Yi (1988) and regarding cut-off values for the indices (Beard and Ragheb, 1980; Bagozzi and Yi, 1988; Hair et al., 2006).

RESULTS AND DISCUSSION

Ho: Digital Leisure mediates the effect of Leisure Interest Measure on Adolescent Health Problems

Figure 2:  Mediation Effect

Mediation was a type of multiple regressions; here LIM as an independent variable (IV), Health Problems as a dependent variable (DV) and DL as mediating variable also an independent variable (IV). The methodology was, first of all, to check the direct effect of IV on DV, and then the indirect effect of IV on DV in the presence of a mediator. Baron and Kenny, (1986) discussed three types of mediation, partial, full, and indirect mediation, later on, Prof. Hayes (2009) criticised that there are only two types of mediation;  partial and full (Baron and Kenny, 1986).

Step A. To study whether there any direct relation between LIM and Health Problems

The value of R² of the dependent variable (Hlth_ Prb) was 0.000 (0%) whereas the value of β (Effect Size) was 0.03. Now to check whether this relation, significant or not

TabeI I.1 Regression Weights: (Group number 1 – Default model)

			Estimate	S.E.	C.R.	P	Label
Hlth_Prb	<-	LIM	.004	.006	.689	.491

The relation between IV to DV, since the p-value 0.491 (greater than 0.05) relation was non-significant. Therefore the direct relation between LIM and Health problems was non-significant, so it reflects that there will be no mediation between them.

Step B. To study the indirect effect of independent variable LIM on dependent variable Health Problems in the presence of mediator DL; significant or not.

Prof. Hayes said that two direct relations together never make indirect so now we will check the indirect effect between them.

Table I.2 Regression Weights: (Group number 1 – Default model)

			Estimate	S.E.	C.R.	P	Label
Digt_Leis	<—	LIM	.017	.044	.382	.702
Hlth_Prb	<—	LIM	.002	.003	.754	.451
Hlth_Prb	<—	Digt_Leis	.124	.003	40.804	***

Only the relation between Digt_Leis to Hlth-Prb was significant while the other two relations were non-significant. The total effect on Hlth-Prb was 0.004 now R² increased and becomes 0.78 (78%), out of which the direct effect was 0.002 whereas the indirect effect was also 0.002. The advisable was Standardise Indirect Effect which was 0.016, this was significant we had to check this.

Table I.3. Standardized Indirect Effects – Two-Tailed Significance (BC) (Group number 1 – Default model)

	LIM	Digt_Leis
Digt_Leis	…	…
Hlth_Prb	.729

The p-value of 0.729 (greater than 0.05) represented that this effect was non-significant it reflected that there was no mediation effect.  It means that if there was an indirect effect then there will be mediation if it didn’t exist then there will be no mediation effect and if there was no initial direct relation between independent and dependent variables then there will be no mediation effect.

Now the question arises if there was any mediation than what will be its type, it depends on in the presence of mediator what was the relationship between independent (LIM) and dependent variable (Hlth_Prb), initially the relation was not significant. Now in the presence of a mediator, if this relation changed, it will affect the mediation type.

Table 1.4. Regression Weights: (Group number 1 – Default model)

			Estimate	S.E.	C.R.	P	Label
Digt_Leis	<—	LIM	.017	.044	.382	.702
Hlth_Prb	<—	LIM	.002	.003	.754	.451
Hlth_Prb	<—	Digt_Leis	.124	.003	40.804	***

Now in the presence of mediator Digt_Leis, the relationship between LIM to Hlth_Prb was  0.451 which was still insignificant whereas the relationship between mediator to independent variable Digt_Leis to Hlth_Prb was significant which shows there was only one relationship exist which was between Digt_Leis and Hlth_Prb, it means neither full nor partial mediation worked. Thus the result showed that initially when we studied the direct relation in absence of a mediator between independent (LIM) and dependent variable (Hlth_Prb) existed a non-significant effect.

In the presence of mediation, the standardised indirect effect of .016, sig. value 0.729 (greater than 0.05) indicates there was no mediation effect and later when we check LIM to Hlth_Prb it was0.451 again showed a non-significant result, which reflected that there was no mediation effect. There was only one relationship that existed which was a direct relationship between Digt_Leis to Hlth_Prb which had no importance. Therefore the null hypothesis was rejected; it reflected that there was no mediation effect exists.

Ho: There will be statistically no significant difference between boys and girls social activities

Table II.1  Group Statistics

	Gender	N	Mean	Std. Deviation	Std. Error Mean
Social Activities During Leisure Time	BOY	240	9.9792	1.94366	.12546
	GIRL	220	9.7864	2.16337	.14585

Table II.2 Independent Samples Test

		Levene’s Test for Equality of Variances		t-test for Equality of Means
		F	Sig.	t	df	Sig.    (2-tailed)	Mean Difference	Std. Error Difference	95% Confidence Interval of the Difference
									Lower	Upper
Social Activities During Leisure Time	Equal variances assumed	4.970	.026	1.007	458	.315	.19280	.19150	-.18352	.56913
	Equal variances   not assumed			1.002	441.499	.317	.19280	.19239	-.18531	.57092

The first table showed the descriptive statistics the mean score for Boy and Girl were almost approximately equal to 10, which falls under Active_ Social Activist. Nearly 286 adolescents fall under this category of active social activists (10-12), 158 (65.83%) boys and 128 (58.18%) girls are active in social activities. It reflects that boys are more active than girls in social activities during leisure time. The first table reflects that social activities of boys and girls were almost the same during leisure time.

The second table showed inferential statistics with, t value=1.007 which was smaller than CV=1.96, which means that mean values were not different, p value=0.315(greater than 0.05), which reflected that test was not significant, it, means that test scores didn’t differ significantly between the groups. The 95% confidence interval of the difference Lower (-0.18352) and Upper (0. 56913), the confidence interval includes 0. Therefore Ho was accepted at t value=1.007, with df= 458 and p-value = .315(greater than 0.05), because it satisfied all the three conditions.

Ho: There will be statistically no significant difference between science and non-science student’s digital leisure

Table III.1 Group Statistics

	Students Opted Science and Non- Science Stream	N	Mean	Std. Deviation	Std. Error Mean
Digital Leisure	Science Group	215	8.9488	3.49261	.23819
	Non-Science Group	245	9.6286	3.49191	.22309

Table III.2. Independent Samples Test

		Levene’s Test for Equality of Variances		t-test for Equality of Means
		F	Sig.	t	df	Sig. (2-tailed)	Mean Difference	Std. Error Difference	95% Confidence Interval of the Difference
									Lower	Upper
Digital Leisure	Equal variances assumed	.678	.411	-2.083	458	.038	-.67973	.32635	-1.32106	-.03841
	Equal variances not assumed			-2.083	450.250	.038	-.67973	.32635	-1.32110	-.03837

The Group Statistics table showed the descriptive statistics, the mean score for Science and Non-science student’s digital leisure differed; Science mean score was 9 whereas for Non-science mean score was 10, both fall under Moderate_ DLA. Nearly 209 students fall under this category of moderate digital leisure (8-12), 99 (47.37%) science, and 110 (52.63%) non-science were moderate digital leisure active. It reflects that non-science students were more active in digital leisure activities than science students during leisure time.

The first table reflected that digital leisure of science differed from non-science students during leisure time. Independence Samples Test table showed inferential statistics with t value= -2.083 which was greater than CV= +_ 1.96, reflected that mean values were different, p value= 0.038 (smaller than 0.05), it reflected that test was significant, it means that test scores differed significantly between the groups. The 95% confidence interval of the difference between Lower (-1.32106) and Upper (-0.03841), the confidence interval didn’t include 0. Therefore Ho was rejected at t value= -2.083, with df= 458 and p value= 0.038 (smaller than 0.05), it didn’t satisfied all three conditions.

Ho: There will be statistically no significant difference between boys and girls digital leisure

Table IV. 1 Group Statistics

	Gender	N	Mean	Std. Deviation	Std. Error Mean
Digital Leisure	BOY	240	9.6708	3.55294	.22934
	GIRL	220	8.9182	3.41667	.23035

Table IV. 2. Independent Samples Test

		Levene’s Test for Equality of Variances		t-test for Equality of Means
		F	Sig.	t	df	Sig.(2 tailed)	Mean Difference	Std. Error Difference	95% Confidence Interval of the Difference
									Lower	Upper
Digital Leisure	Equal variances assumed	.544	.461	2.312	458	.021	.75265	.32561	.11278	1.39252
	Equal variances not assumed			2.315	456.942	.021	.75265	.32505	.11387	1.39144

The Group Statistics table showed the descriptive statistics, the mean score for Boys and Girls student’s digital leisure differed.  Boy’s mean score was 10 whereas Girl’s mean score was 9, both fall under Moderate_ DLA. Nearly 209 students fall under this category of moderate digital leisure (8-12), 118 (56.45%) boys and 91 (43.54%) girls were moderate digital leisure active. The first table reflected that digital leisure of boys differed from girls students during leisure time.

Independent Samples Test table showed inferential statistics with t value= 2.312 which was greater than CV= 1.96, it reflected that means values were different, p value= 0.021 (smaller than 0.05), therefore the test was significant, it highlighted that test scores differ significantly between the groups. The 95% confidence interval of the difference between Lower (0.11278) and Upper (1.39252), the confidence interval didn’t include zero. Therefore Ho was rejected at t value= 2.312, with df= 458 and p value= 0.021 (smaller than 0.05), it didn’t satisfied all three conditions.

It was found that girls were generally involved in household activities apart from their studies whereas boys were generally free from household or other activities. The results revealed that adolescents especially boys and non-science students involved in digital activities than girls and science students. Adolescents were active on social networking sites; 286 nearly 65% were active most of their time on Facebook and Twitter, they were spending on an average 06-08 hours daily on online activities.

The study highlighted the health facts while discussing with adolescents, most of them claimed that they were facing headache and eye problems, whereas quite a few were facing sleeping problems and psychological problems as anger, fear and depression. Indian adolescents were facing severe health problems in comparison to Bhutanese students as they were on an  average 3.5 hours less time engaged in online activities  It was found that the risks associated with overuse of SNS by adolescents; depression, anxiety, sleeping disorder, decreased self-esteem and the suicidal tendency was quite common. It has been asserted that adolescents may reveal their emotions and thoughts on SNSs (Subrahmanyam et al., 2009; Memon et al., 2018).

Adolescents are of greater risk side, risks from abusers within, or outside the family, their close friends or acquaintance in this digital sphere. With the rapidly growing number of social media users globally, suicidality and self-harm behavior become a more complex issue depression and suicidality (Luxton and 2012; Memon et al., 2018). Despite, divergent views and the so-called generation gap, parents should try to bridge the gap with their children by regularly talking and discussing their scholastic, non-scholastic, and leisure time activities; friends, and other social interaction activities in a friendly manner, so that children can share their activities with them.

Parents should discuss the drawbacks of such technology with adolescents and suggest them to use it for a specified period; otherwise, it will affect them in all spheres right from their academic to health issues. It should be seriously taken, as it was observed that, heavy parent use of mobile devices is associated with fewer verbal and nonverbal interactions between parents and children and may be associated with more parent–child conflict (Radesky et al., 2014; Radesky et al., 2015; Singh and Sharma, 2019).

CONCLUSION

Education and Health accelerate the process of human development backed up by sound financial position. The findings of the study revealed that adolescents are using digital technologies in most of their leisure- time, especially boys in comparison to girls due to which they are facing health problems.  Now the question arises how we overcome the problem of digital dependency, and ‘screen addiction’, among adolescents? The study suggested that the ministry of education should run programs in schools for adolescents, which creates awareness, how young people use SNS? Even the parents and teachers must keep eye on the activities of students regarding the usage of technology in school and at home and discussed with them the adverse effects of this technology. The study concluded that we should help adolescents in realising that digital technology assists them in shaping their future but it should be used in a proper way otherwise they will mislead from their path and their dreams will be shattered. We should tame the technology as well as treat it as our mate, but there will be a mete between both roles, it is in our hand how to handle the technology adequately.

ACKNOWLEDGEMENTS

The authors are highly grateful to the resource persons and teaching faculties in the selected Kendriya Vidyalaya Sangathan (KVS) Schools in India and Government Schools of Bhutan governed by  BHSEC who help us a lot in collecting data and facts while interacting with the students studying in Grade XII^th, it makes field-work easier and comfortable.

Conflict of Interests: Authors declare that the work and data present in the study are our original and innovative research, carried out by us. The study is not published earlier and we have not misused the facts and evidence.

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