Presently,in India, 28.4 per cent of the population (375 million) is using internet, outof which 10.
3 per cent are active on social media (136 million). Five yearsago, 2.5 per cent of the population was active on Facebook. This number isexpected to increase to 15 per cent by the end of 2016, with Facebookproactively targeting emerging economies with Facebook site for slow internetspeed in these regions. As per the Yral report, increased mobile webpenetration is also seen as a key contributor to increased growth in activesocial media usage. Statistic presents the social network penetration in India.As of the fourth quarter of 2016, the most popular social network were YouTubeand Facebook with 33 percent penetration rate each. WhatsApp was ranked thirdwith 28 percent reach.
India ranks second among countries with the most Facebook users, accounting for 11 percent of global Facebook audiences in April 2017. January 2017 data puts the active social networking penetration in India at only 14 percent of the population – one ofthe lowest rates worldwide.Social networking sites (SNSs) are Web-based platforms on whichindividuals connect with other users to generate and maintain socialconnections. Considerable disagreement exists as to associations that SNS usemay have with depression and anxiety. On the one hand, SNSs may protect frommental illness, as they support and enable social interaction and connectionand allow users to reflect aspects of their identity and express emotion thatmay be relevant to their livedexperience. On the other hand, there are manyopportunities for miscommunications and mismanaged expectations, andmaladaptive tendencies can be exaggerated, leaving individuals feeling agreater sense of isolation.
As a whole, the SNS environment may be just ascomplex as face-to-face interactions. As SNS membership continues to rise, itis becoming increasingly important to address the possible benefits anddetriments the use of SNSs may have on mental health.Affectivedisorders such as depression and anxiety have been shown to have bidirectionalinteractions with the social environment that influence the path of illnessonset and maintenance. Depression and anxiety have an approximate prevalence of4.7% and 7.3%, respectively, in the global population .
These disorders havehigh levels of comorbidity and impact the quality of social relationships. Depressionand anxiety may be implicated in determining the size and structure of anindividual’s social network, the quality of interactions within these networks,and how effectively social capital may be leveraged or developed to provide anindividual with social support. REVIEW OF LITERATURE:AncaDobrean(2016)In his study concluded cyberbullying victimization served asa full mediator in the relationship between the use of online social networkingsites and psychological distress/suicide attempts and acted as a partialmediator in the relationship between the use of online social networking sitesand suicidal ideation,Helou et al.,(2014) in his study revealed most of the students felt that the SocialNetworking Sites have more positive impact on their academic performanceespecially among the undergraduate students. Salvationand Azharuddin (2014).Intheir study concluded that more students prefer the use of facebook and twitterin academic related discussions in complementing conventional classroom teachingand learning process.Shahzad et al.
,(2014). The analysis revealed that there is no direct relationship betweenthe social media usage and the academic grades unless the usage does not becomeexcessive. Average use of social media by students exceeding 13 hours a weekand 2 hours a day has negative effect on their academic grades.
Tayseeret al., (2014) in their studyrevealed that students use social networks forsocial purposes more than the academics. Students consider social media asentertainment networks and it reduces stress and makes them forget aboutacademics. SIGNIFICANCE OF THE STUDY:Duringthe past decade, online social networking has caused profound changes in theway people communicate and interact. It is unclear, however, whether some ofthese changes may affect certain normal aspects of human behavior and causepsychiatric disorders. Several studies have indicated that the prolonged use ofsocial networking sites (SNS), such as Facebook, may be related to signs andsymptoms of depression. In addition, some authors have indicated that certainSNS activities might be associated with low self-esteem, especially in childrenand adolescents.
Other studies have presented opposite results in terms ofpositive impact of social networking on self-esteem. The relationship betweenSNS use and mental problems to this day remains controversial, and research onthis issue is faced with numerous challenges. This concise review focuses onthe recent findings regarding the suggested connection between SNS and mentalhealth issues such as depressive symptoms, changes in self-esteem, and Internetaddiction(Igor Pantic,2014).So the researcher was interested to study mentalhealth of users of social media.OBJECTIVES: To study the socio-demographic profile of the respondents. To find out the impact of social media on the respondents To study on mental health status of the respondents To suggest measures to improve the mental health status of respondents.Basedon the above objectives following few research hypotheses have been formulated.
RESEARCH HYPOTHESES :Ø There is a significant relationship between theage and mental health status of respondentsØ There is a significant difference betweennature of education and mental health status of the respondents.Ø There is a significant relationship betweenthe nature of education and mentalhealth status of respondents.Ø There is a significant relationship betweenthe native place and mental health status of respondents.
Ø There is a significant relationship betweenthe father’s income and mental health status of respondents.Ø There is a significant difference betweenrespondents type of family and mentalhealth status of respondents.Ø There is a significant difference betweenrespondents size of family and mental health status of respondents.Ø There is a significant difference between therespondents spend time in social media sites and mental health status of respondents.Ø There is a significant difference betweenrespondents members of social media and mental health status of respondents.MATERIALS AND METHODS:Thedescriptive research design is scientific method which involves observing anddescribing the behavior of the subject without influencing them in any way. Theresearcher collected information about the respondents which includes age,educational status, domicile, type of family, size of family, use of socialmedia, time spent in social media and level of mental health. DescriptiveResearch design was adopted in thepresent study.
The researcher studied all therespondents in the universe by adopting census method.The Sample size was 77 in number.The researchstudy was conducted among college students atVarshini hostel, near Malaikottai,Trichy.The researcher used interview schedule to collect the personal data fromthe respondents and used Mental Health Inventory a standardized tool developedby V.D. Augustine(1978) to assess mental health of the respondents. ANALYSIS ANDINTERPRETATIONTABLENO :1 DISTRIBUTION OF THE RESPONDENTS BY THEIR AGE AGE(IN YEARS) NO.
OF RESPONDENTS N=77 PERCENTAGE 16-20 56 72.7 21-25 20 25.9 26 AND ABOVE 1 1.2 The above table shows that the more than half(72.7 per cent) of the respondents belonged to the age group of 16-20 years while over one fourth (25.9 percent) of the respondents belonged to the age of 21-25 years and very few (1.
2 per cent) of therespondents belonged to the age group 26 years and above. TABLE NO:2 DISTRIBUTION OF THE RESPONDENTS BY THEIR EDUCATIONAL STATUS DEGREE NO.OF RESPONDENTS N=77 PERCENTAGE UG 60 77.9 PG and Mphil 17 22.1 The above table shows that majority of (77.9per cent) of respondents were in Under Graduation while less than one fourth (22.
1per cent ) of respondents were in Post Graduationand were pursuing their M.Phildegree.TABLE NO:3DISTRIBUTIONOF THE RESPONDENTS BY THEIR DOMICILE DOMICILE NO.OF RESPONDENTS N=77 PERCENTAGE RURAL 40 51.9 URBAN 37 48.1 Theabove table shows that more than half (51.9per cent)of the respondents were from rural area while nearly half (48.1 percent) of the respondents belonged to urban area.
TABLE NO:4 DISTRIBUTION OF THERESPONDENTS BY THEIRTYPE OF FAMILY TYPE OF FAMILY NO.OF RESPONDENTS N=77 PERCENTAGE NUCLEAR FAMILY 65 84.5 JOINT FAMILY 12 15.5 The above table shows that majority (84.5 percent)of respondents were from nuclear families while less than one fifth (15.5per cent )of the respondents’ family were joint families. TABLE NO:5DISTRIBUTION OF THE RESPONDENTS BY SIZE OF THEFAMILY SIZE OF FAMILY NO.
OF RESPONDENTS N=69 PERCENTAGE SMALL(2 -5) 52 75.3 BIG(6-9) 17 24.6 Theabove table shows that majority(75.
3 per cent) of respondents’ families were smallin size while one fourth (24.6 per cent) of respondents’ families were big insize.TABLE NO:6DISTRIBUTION OF THE RESPONDENTS BY THEIRUSE OF SOCIAL MEDIA USE OF SOCIAL MEDIA NO.
OF RESPONDENTS N=77 PERCENTAGE YES 55 71.4 NO 22 28.5 The above table reveals that majority (7.
41per cent) of respondents were using social media while more than one fourth(28.5 per cent ) of respondents are not using it.TABLE NO:7DISTRIBUTION OF THE RESPONDENTS BYTHEIR AGE AT STARTED USING SOCIAL MEDIA AGE (In Years) NO.OF RESPONDENTS N=55 PERCENTAGE 15-20 54 98.1 21 and above 1 1.9 Theabove table revealsthatvast majority (98.
1 per cent) of the respondents startedusing social media from 15-20 years while very few (1.9 per cent) of therespondents used social media at the ageof 21years and above.From the above table it is clear that the respondentsstarted using social media very young age. TABLE NO:8DISTRIBUTIONOF THE RESPONDENTS BY THEIR TIME SPENT IN SOCIAL MEDIA TIME SPENT (In hours) NO.OF RESPONDENTS N=55 PERCENTAGE 1-2 24 43.6 3-4 25 45.4 5-6 6 10.
9 The above table reveals about the time spent per day in social mediaby the respondents. Less than half (45.4per cent and 43.
6 per cent) of the respondents spent 3-4 hours and 1-2 hoursper day respectively in social media while few(10.9 per cent) respondents arespending 5-6 hours per day in social media. From the above table it could beinferred that the respondents who are using social media are becoming almostaddicted to electronic gadgets since they use it every day wasting their mostprecious time without studying.TABLE NO:9 DISTRIBUTION OF THE RESPONDENTS BY THE LEVELOF MENTAL HEALTH MENTAL HEALTH NO.OF RESPONDENTS N=77 PERCENTAGE LOW 1 1.2 MODERATE 38 49.3 HIGH 38 49.3 The above table shows that nearly half (49.
3per cent and49.3 per cent)) of respondents’mental health status was moderate and high level respectively while very few (percent) of respondents’ had low level of mental health.TABLE NO:10 ‘t’ TEST FOR USERS AND NON USERS OF SOCIAL MEDIA AND MENTAL HEALTH STATUS OF THERESPONDENTS MEMBER OF SOCIAL MEDIA MEAN SD STATISTICAL INFERENCE YES (N=55) 38.64 6.
285 T=-1.110 -1.144<0.05 NOT SIGNIFICANT NO (N=22) 40.
36 5.860 There is no significant difference between respondents using social media andmental health status of respondents. Hence null hypothesis was accepted. Fromthe above table it could be inferred that use of social media didn’t influence the mental health status ofthe respondents. TABLE NO:11KARLPEARSON’S C0-EFFCIENT CORRELATION BETWEEN AGE OF USING SOCIAL MEDIA AND MENTAL HEALTH STATUS VARIABLES CORRELATION VALUE RESULT AGE OF USING SOCIAL MEDIA AND MENTAL HEALTH STATUS .
283 P< 0.05 SIGNIFICANT There is a significant relationship betweenthe age and mental health status of respondents. Hence research hypothesis wasaccepted and null hypothesis was rejected. From the above table it could beinferred that as the age of the respondents increased the mental health status ofthe respondents also increased. TABLE NO:12 t' TEST FOR NATURE OF EDUCATION AND MENTAL HEALTH STATUSOF THE RESPONDENTS NATURE OF EDUCATION MEAN SD STATISTICAL INFERENCE ARTS (N=31) 39.48 7.496 T=.
411 .383<0.05 SIGNIFICANT SCIENCE (N=46) 38.89 5.182 There is a significant difference between thediscipline and mental health status of respondents.
Hence research hypothesis wasacceptedand null hypothesis was rejected. From the above table it could be inferredthat arts students had good mental health status than the science students. TABLE NO:13KARLPEARSON’S C0-EFFCIENT CORRELATION BETWEEN FATHER’S INCOME AND MENTAL HEALTH STATUS VARIABLES CORRELATION VALUE RESULT FATHER’S INCOME & MENTAL HEALTH STATUS .359 P< 0.05 SIGNIFICANT There is a significant relationship betweenthe father's income and mental health status of respondents. Hence researchhypothesis was accepted and null hypothesis was rejected. From the above tableit could be inferred that as the father's income of the respondents increasedthe mental health status of the respondents also increased.
TABLE NO:14t’ TEST FOR TYPE OF FAMILY ANDMENTAL HEALTH STATUS OF THE RESPONDENTS TYPE OF FAMILY MEAN SD STATISTICAL INFERENCE NUCLEAR (N=65) 38.95 6.109 T=-579 -541<0.05 NOT SIGNIFICANT JOINT (N=12) 40.08 6.735 There is no significant difference between respondents' family type and mental health status of respondents.Hence null hypothesis was accepted. From the above table it could be inferredthat family type didn't influence the mental health status of the respondents.
TABLE NO:15 ‘t’TEST FOR SIZE OF THE FAMILY AND MENTALHEALTH STATUS OF THE RESPONDENTS SIZE OF THE FAMILY MEAN SD STATISTICAL INFERENCE SMALL N=52 39.15 5.682 T=-908 -847<0.05 NOT SIGNIFICANT BIG N=17 40.65 6.499 There is no significant difference between respondents' family size and mentalhealth status of respondents. Hence null hypothesis was accepted.
From theabove table it could be inferred that size of family didn’t influence the mental health status ofthe respondents. TABLE NO:16KARLPEARSON’S C0-EFFCIENT CORRELATION BETWEEN TIME SPENT BY THE RESPONDENTSIN SOCIAL MEDIA SITES AND MENTAL HEALTH STATUS VARIABLES CORRELATION VALUE RESULT RESPONDENTS TIME SPEND IN SOCIAL MEDIA SITES AND MENTAL HEALTH STATUS .485 P< 0.05 SIGNIFICANT There is a significant relationship betweenthe time spent by the respondents and mental health status of respondents.Hence research hypothesis was accepted and null hypothesis was rejected.
Fromthe above table it could be inferred that time spent in social media influenced the mental health status of the respondents positively. MAJOR FINDINGS:· Majority (72.7 per cent)ofrespondents were in the age group of 16-20years.· Majority( 77.9 per cent)of respondents wereunderundergraduates.· More than half(59.
8 percent)of respondents were from science stream of education.· More than half (51.9per cent)of the respondents were from rural area.· Less than half (41.
5per cent) of respondents’fatherswere educated upto high school.· Less than half (44.1per cent) of respondents’motherswereeducatedupto high school.· Vast majority ( 84.
5per cent) of respondents’ families were nuclear.· Majority ( 75.3per cent)of respondents’familieswere small in size.
· Vast Majority ( 90.9per cent) of respondent wereusing social media for 1-4 years.· Less than half (45.4percent) of respondents were using social media 3-4 hours.
· More than half( 50.9per cent) of respondents were victim of online bullying.· Nearly half(49.3 percent) of respondents of users of social media had moderate and high level ofmental health status.
SUGESSTIONS:· Parents and thecaretakers have to alert themselves regarding negative impactofsocial media.· Family discussions arealso one of the recommendations which will help youngsters avoid usinginternet.· Parents should beconcerned about the online protection and sharing of individual information andphotos.· Students may be exposedto bad posture, eye strain, physical and mental stress.
Too much use of technologyfor accessing social media bystudents is harmful and there must be a limit.· Students must beoriented on positive& negativeimpacts of social media by parents as well as teachers. SOCIALWORK INTERVENTION:From this research , researcherunderstood that use of whatsapp and facebook is maximum and 47 per cent of respondents were using twosocial media sites . The inevitability of the communication technologydevelopment was drowsing the youth. Their aim or goal in life is being crushed,smashed and swapped by social media. To solve this issue many youth hinderacademic part particularly teenaged or college students are almost having anaddiction towards social media. . This is the age for them to set up a positivefocus , set a goal for life rather than time being eaten by social media.
Individualcounseling and group counseling can be given to reduce the negative impact ofsocial media.CONCLUSION:SinceSocial Networking Sites can provide all the ways and means to develop personaland social aspects, the young people have to explore the potentialities ofthese sites. Even though it creates a few negative impacts on youth, we cannotthink of a world without these sites today. So, corrective and preventivemeasures should be taken towards these negative effects and the young peopleshould be well educated and must have proper awareness regarding such problemsof Social media. Social Networking Sites influence the lifestyle of youth sothat the brands and companies can exploit the space of Social Networking Sitesto create loyalty among youth. If the Social Networking Sites promote a healthylife style through its posts, videos and messages, that will help to develop ahealthy young generation.