Rajivgandhiuniversity of Health Science

RAJIV GANDHI UNIVERSITY OF HEALTH SCIENCE,

BENGALURU, KARNATAKA.

SYNOPSIS FOR REGISTRATION OF SUBJECT FOR DISSERTATION

1. NAME OF THE CANDIDATE AND Mr. NAIBIN YESUDAS

ADDRESS. SANTHI BHAVAN, CHANDANAVILLA, VELLIMON.P.O. CHERUMOODU.

KOLLAM. KERALA

2. NAME OF THE INSTITUTION M.S. RAMAIAH INSTITUTE OF

NURSING EDUCATION AND

RESEARCH, M.S.R.I.T.POST,

BANGALORE-54 3. COURSE OF STUDY AND M.SC NURSING.

SUBJECT. MENTAL HEALTH (PSYCHIATRIC) NURSING DISSERTATION TOOL 4 DATE OF ADMISSION. 10/06/2010. 5. TITLE OF THE STUDY:

EFFECTIVENESS OF STRUCTERED TEACHING PROGRAMME ON KNOWLEDGE

REGARDING CONSEQUENCES OF EXCESSIVE COMPUTER USE AMONG

ADOLESCENTS.

6. BRIEF RESUME OF INTENDED WORK

1 INTRODUTION :

A student represents the society’s investment for the future. Computer use is widely spread among adolescent for studying, communicating, entertainment, searching information. A larger proportion of student population does suffer from various psychological and physical problems including addiction. They need a comprehensive evaluation of attitudes, interest, personal problems which will guide them to a better future.1

Excessive use of computer or Computer addiction is the excessive or compulsive use of computers that interferes with daily life. This disorder effect the social interaction, mood, personality, work ethic, relationships, thought process and sleep of an individuals.

Computer addictives find the virtual realities on computer screens more attractive than everyday reality. They feel unhappy when they are away from the computer. They spend more time and money on computers and neglect their families and work.2

Ill effects leads to excessive use of computer are feelings of isolation, depression, stress and anxiety may lead to use of internet to relieve such feelings. Escape from reality of family conflict, Influence by peers, Lack of social skill and communication skill and

Fear of face-to-face interaction.3

There are different modalities of excessive computer usage. They are i)Video game addiction: Video game addiction, is excessive or compulsive use of computer and video games that interferes with daily life. Computer games consist of action, gambling, adventure, construction and management simulation, life simulation, role playing, strategy, and vehicle simulation. ii) Internet Addictive Disorder (IAD): is excessive internet use that interferes with daily life. Its excessive, or inappropriate pornography use,

2 gaming, online social networking, blogging, email, or Internet shopping. iii) Internet

Porn Addiction: This addiction crosses gender boundaries. Internet Porn Addiction is a problem shared by men and women alike. Pornography Addiction is a form of sexual addiction. This involves a non-contact sexual episode through private chats, either with or without a video connection. These sometimes develop into real world meetings. iv)

Information overload: Obsession with tracking down certain types of information and organizing it.3

The areas of consequences are i)Academic: decline in study habits, significant drop in grades, missed classes, placed on probation and poor integration in extracurricular activities due to lack of attention and concentration. ii)Psychological: Having a sense of well-being or euphoria while at the computer ,Inability to stop the activity ,Craving more and more time at the computer ,Neglect of family and friends, depressed, irritable when not at the computer ,Lying to family about activities, Problems with school.iii) Financial:

Since internet services are expensive addicts may spend all the money in online shopping or games. iv) Physical: Carpal tunnel syndrome, dry eyes, headaches, back aches, eating irregularities such as skipping meals and obesity , Failure to attend to personal hygiene,

Sleep disturbances and change in sleep pattern.3

6.1 NEED FOR THE STUDY

According to the survey done by ‘United Nations Population Fund'in( 2010 Oct

30) world population was 687,84,00,000. In India was 118,95,80,000. In Karnataka was

5, 27, 30,000 and in Bangalore was 4,301,326. According to WHO, the adolescence is the period between 11 – 18 years. In the worldwide, one in every five people is an adolescent, out of 1,20,00,00,000 adolescent worldwide. In India, there is 15,00,00,000

3 adolescent comprising 21% of India’s total population. According to the central statistic organization, New Delhi, the estimated ‘adolescents population’ in 2011 would be around, 19.6%.4

According to the survey done by Internet and Mobile Association of India (2005), the 26 cities that covered 65,000 persons in 16,500 household has shown 1.6 million school children use the internet for about 322 minutes a week and about 3.4 million college students use the internet about 433 minutes a week. Currently about 81 million internet users in India a number that will nearly triple by around 2015 to 237 million.5

Video game addiction is a particularly severe problem in Asian countries such as

China, Korea and India. 2.6% Indian of aged 9 to 39 suffer from game addiction, with another 10.8% at risk of addiction. 8.5% of youths (between the ages of 8 - 18) are video game addicts. While another 23% of youths would say that they are addicted to video games.6

Incidence rate of internet using in world is 123 million adolescents had gone online, of which 14.9% were teenagers below 18 years old. Incidence rate of Internet addiction among Bangalore college students was 5.9%. and 10.6% of Indian college students were identified as in Internet addicts.7

Computer and phone game blur children`s vision. Doctors are seeing more younger children with refractive errors in their eyes.8 Excessive computer usage in children’s could have negative impact on student mathematics and reading.9 Excessive internet browsing can lead to negative outcome like social isolation, depression, insomnia, and obesity, especially among teenagers. 10

4 A cross sectional study conducted on 2010 July to assess the insomnia symptoms among 2195 Greek adolescent with excessive use of computer, using the adolescent computer addiction test and Athens insomnia scale. It revealed that female scored

F(1,1723=49.814, P < 0.01 ) higher than males on insomnia. Computer uses can significant cause of insomnia complaint in an adolescent population.11

A survey conducted in 2010 to assess the excessive recreational computer use and specific food consumption behavior among 4029 California's adolescents aged 12-17, using California Health Interview Survey. Logistic regressions showed excessive weekday recreational computer use (O.R=O.66, P<0.01) and excessive weekend recreational computer use. (O.R=O.78, P

An article published in an online edition of Hindu news paper said that Excessive computer use can lead to sleep deprivation and restlessness apart from the physical problems such as backache and eyestrain. “Such addicts don’t care for relations, tell lies and also to stealing sometimes,” H.B. Dinesh, Secretary of Karnataka State Temperance

Board (KSTB), said the board was all out to create awareness on various addictions.

“You students and teachers can help us spread awareness about new age addictions.” 13

Many studies have been carried out to find the extent and nature of excessive computer use among various adolescents groups both in India as well as in abroad.

However these studies do suffer from various lacunae such as faulty selection, sample size, methods of data collection and so on. Moreover very few studies have concentrated

5 on the effectiveness of knowledge regarding excessive use of computer. Thus the investigator is interested to conduct this study.

6.2 REVIEW OF LITERATURE

A cross-sectional survey was conducted by using stratified random sampling to asses the intensity of computer use and insomnia epidimology among 2195 greek high school students to find whether excessive computer use is a risk factor for developing insomnia symptom in Thessaly, Grease 2010. The questionnaire used was adolescent computer addiction test and Athens insomnia scale. The study revealed that out of 2155 students, 1077 were male and 1118 female. Of those male, 109 were classified as suffering from insomnia and females was 142. A statistically significant trend for older students to present with more insomnia (mann-whitney z=5.489,p< 0.001). After controlling for computer usage ,there remains a significant difference between males and females in insomnia complaints (F (1,1723) = 49.814, p<0.001). Computer use can be a significant cause of insomnia complaints in adolescent population regarless of whether the individual is classified as addicted or not.11

A survey conducted to assess the excessive recreational computer use and specific food consumption behavior among 4029 California's adolescents aged 12-17, in 2010.

The questionnaire used was the 2005 adolescent simple of California Health Interview

Survey (CHIS). They have measured both media consumption behaviour and food consumption patterns among adolescents to explore the association between excessive recreational computer use and specific food consumption. They measured the responders average number of hours spends on a weekday, and the average numbers of hours spent

6 on playing with computers on a weekend day. Logistic regressions showed excessive weekday recreational computer use (O.R=O.66, P<0.01) and excessive weekend recreational computer use. (O.R=O.78, P

A cross-sectional survey was conducted to asses the life style pattern and behavior based on the level of internet addiction among 853 Korean junior high school students selected using stratified random sampling in Soul, Korea. The self reported questionnaire used was Korean internet addiction scale. The study revealed that boys were high-risk internet users than girls(31.4% vs 14.0%). Younger adolescent were significantly more likely to be higher risk internet users than older adolescent( p<0.001). High and potential risk internet users suffered from sleep disturbance (81.1% and 76.1%) and higher prevalence of skipping dinner. In this study high internet users have inappropriate dietary behavior and poor diet quality. It result in stunded growth and development14

An exploratory study was conducted to find the prevalence of internet addiction and comparison of internet addicts and non-addicts among 1968 Iranian high schools students, using cluster sampling. Results showed that, 977 students were Internet users, who were classified into 37 Internet addicts, 304 possible Internet addicts, and 636 moderate users. Since possible addicts, moderate users, and nonusers can all be considered nonaddicts, to make a comprehensive and controlled comparison between addicts and nonaddicts, 37 possible addicts, 37 moderate users and 37 nonusers were matched with the Internet addicts. Results suggest that Internet addicts are lonelier and

7 have lower self-esteem and poorer social skills than moderate users, but not necessarily than possible addicts or nonusers15

A survey was conducted to assess the prevalence of Internet addiction among

2,200 Greek adolescent students, ages 12 to 18, using randomized stratified sampling.

Participants were asked to complete the Diagnostic Questionnaire for Internet Addiction

(YDQ), as well as an inventory that included socio demographic factors and questions about the use of Internet, their social life, and their habits. Results showed that, 70.8% of adolescents had access to the Internet. Proportions are also calculated only on the frequent Internet users, which results in 11% fulfilling five YDQ criteria. The most frequent type of Internet use is online games, representing 50.9% of Internet users, and information services, representing 46.8%. The prevalence of Internet addiction among

Internet users of Central Greece is 8.2%, and it concerns mainly the male students who play online games and visit Internet cafés16

STATEMENT OF PROBLEM

A study to assess the effectiveness of structured teaching programme on knowledge regarding consequences of excessive computer use among adolescents in selected schools at Bangalore.

6.3. OBJECTIVES

1. To asses the pretest knowledge regarding consequences of excessive computer

use among adolescents.

2. To determine the effectiveness of structured teaching programme on

knowledge regarding consequences of excessive computer use by comparing

pretest and posttest scores of experimental group.

8 3. To assess the effectiveness of structured teaching programme on knowledge

regarding consequences of excessive computer use by comparing post test scores

of experimental and control groups.

4) To find association between the pre test level of knowledge and selected socio

demographic variables.

6.4 HYPOTHESES:

H1 - there is statistically significant difference between pre test and post test

knowledge scores in experimental group.

H2 – there is statistically significant difference in the post test scores between

experimental and control groups.

H3 – there is statistically significant association between pretest level of knowledge

and selected socio demographic variables.

6.5. OPERATIONAL DEFINITIONS

 Effectiveness: - In this study it refers to a significant increase in the level of

knowledge regarding consequences of excessive computer use among adolescents

after the structured teaching programme which is measured by difference in pre

and post test knowledge scores.

 Structured teaching programme:- It refers to organized and systematic group

teaching strategy for an hour using lecture cum discussion method to impart

knowledge regarding consequences of excessive computer use which include

academic psychological, financial , physical consequences.

9  Knowledge: - It is refers to the information and understanding of the adolescents

regarding consequences of excessive computer use in terms of their responses to

the structured knowledge questionnaire.

 Adolescent: In this study an adolescent refers to a person in developmental stage

that occurs between the ages of 13 and16 years studying in the selected schools.

 Consequences of excessive computer use : In this study, refer to psychological,

social, physical and academical problems of adolescents as a result of excessive

(more than two hours/day or nine hours/week) computer use.

6.6 ASSUMPTIONS

1. Adolescents may not have adequate knowledge regarding consequences of

excessive use of computer.

2. Adolescents will be willing to express their knowledge about consequences of

excessive use of computer.

3. Structured teaching programme is an accepted teaching strategy aimed at

improving adolescents knowledge.

6.7. DELIMITATIONS

1. Adolescents studying in the selected schools.

2. Study for a period of 4 weeks,

7 MATERIALS & METHODS

7.1 SOURCE OF DATA

Adolescents in selected schools at Bangalore.

10 7.2. METHODS OF DATA COLLECTIONS

7.2.1. TYPES OF STUDY/ APPROACHES

Evaluative study

7.2.2. RESEARCH DESIGN.

non equivalant control group pre test post test design

7.2.3. VARIABLES

INDEPENDENT VARIABLE: structured teaching program

DEPENDENT VARIABLE: knowledge regarding Consequences of excessive

use of computer.

ATTRIBUTE VARIABLE : socio demographic which include age ,gender, native

place, number of siblings, religion, standard/class, type of family, family income.,

presence of computer at present residence, time spent on computer, number of

computer hour in school, mobile phone internet usage.

7.2.4. SAMPLING TECHNIQUE

Simple random sampling technique.

7.2.5. SAMPLE AND SAMPLE SIZE.

60 adolescents who fulfills selection criteria. (30 experimental and 30 control

group)

7.2.6. SELECTION CRITERIA.

Inclusion criteria

1. Adolescents available during period of data collection.

2. Adolescents those who uses computer.

3. Adolescents those who can read, speak and understand Kannada or English.

11 Exclusion criteria

1. Not willing to participate in the study

7.2.7. FOLLOW UP

Post test will be conducted after 7 days, among both experimental and control

groups.

7.2.8. COMPARISION PARAMETER

Pretest and post test knowledge level of experimental and control groups will be

compared.

7.2.9. DURATION OF THE STUDY

4 weeks period of data collection

7.2.10. TOOL/ INSTRUMENT

Section A: socio demographic Performa which include age, gender, native place,

number of sibling, religion, standard/class, presence of computer at present

residents, time spend on computer, type of family, family monthly income,

number of computer hour in school, mobile phone internet usage.

Section B: Structured knowledge questionnaire regarding consequences of

excessive `use of computer.

7.2.11. DATA COLLECTION PROCEDURE

o Formal permission will be obtained from the concerned authority.

o Student researcher introduces self and explains purpose of the study.

o Written assent will be obtained from the subject.

o Subject will be randomly selected the experimental and control group

12 o Pre test will be conducted by using structured knowledge questionnaires for the

both groups.

o The structured teaching programme will be given to the adolescent in the

experimental group.

o Post test will be conducted for both groups using the same questionnaires after 7

7.2.12. PLAN FOR STATISTICAL ANALYSIS

The data analysis will be done using descriptive statistics and inferential statistics.

Descriptive statistics:

o The frequency and percentage distribution will be used to describe the socio

demographic variable and level of knowledge.

o Mean, mean percentage and standard deviation will be used for pre test and post

test level of knowledge.

Inferential statistics:

o Paired `t’ test will be used to compare pre test and post test level of knowledge

scores in experimental groups.

o Student `t’ test will be used to compare pre test scores of experimental and control

group.

o Chi – square will be used to determine association between pre test level of

knowledge and selected socio demographic variable

13 7.3. DOES THE STUDY REQUIRE ANY INVESTIGATION OR

INTERVENTION TO BE CONDUCTED ON PATIENT OR OTHER HUMAN? IF

SO PLEASE DESCRIBE BRIEFLY.

Yes, structured knowledge questionnaire will be administered for the both

group to assess the pretest and post test level of knowledge. And structured

teaching programme will be administered for the experimental group.

7.4. HAS ETHICALCLEARANCE BEEN OBTAINED FROM YOUR

INSTITUTION IN CASE OF 7.3.

Ethical clearance will be obtained from the concerned ethical committee and written assent will be taken from the adolescent’s for maintaining the confidentiality and anonymity.

14 8. LIST OF REFERANCES

1) Shotton MA. Computer addiction, videogame addiction, internet addiction.

[online]. 2007 Dec 01 [cited 2010 Oct 21]; Available from: URL:http:

//myaddiction.org.

2) Cromie JW. The Harvard university gazette; computer addiction. [Online]. 1999

Jan 21 [cited 2010 Oct 21]; Available from:

URL: http: // [email protected] .

3) Dawn H. Computer addiction. [online]. 2007 Aug 01 (cited 2009 Oct 28);

Available from: URL: http://hubpages/alltopics/health/mental health /addiction.

4) United Nations Population Fund. (2000). Adolescents in India: A Profile. New

Delhi. p.6.

5) Internet and Mobile Association of India. Hindustan Times 2007 Oct 18; p.

3(col3).

6) Video addiction and industry statistics. [Online]. 2009 Dec 12 (cited 2008 Oct

20); Available from: URL: http : //techmission.org.

7) Addiction statistics and facts. [Online]. 2010 Jan 02 (cited 2009 Oct19); Available

from: URL: http: //my addiction.com.

8) Seethalakshmi S. PCs and phone games blur children`s vision. The Times of India

2010 Jul 7; 5 (col5).

9) Using computer weakens teen`s reading. The Times of India. 2010 sep21; 4(col8).

15 10) Excessive internet browsing could cause depression. The Hindu newspaper 2010

sep 26; 5(col6).

11) Siomos KE, Bramiotis D, Florors GD, Dafoulis v, Angelopoulos NS. Insomnia

symptoms among Greek adolescent students with excessive computer use.

Hippokratia 2010 Feb 16:14 (3): p. 203-7.

12) Shi L, Mao Y. Excessive recreational computer use and food consumption

behavior among adolescents. IJP 2010 Aug 5:36(52).

13) Krishnan S, Ranganathan S. Deconstructing ‘Internet addiction’. The Hindu 2009

Aug Sunday 30; 4(col5).

14) Kim Y, Park YJ, kim BS, Jung I, Lim SY, Kim J. The effect of internet addiction

on the lifestyle and dietary behavior of Korean adolescents. Nutr Res pract.

2010;4(1):51-7.

15) Ghassemzadeh L, Shahraray M, Moradi A. Prevalence of internet addiction and

comparison of internet addicts and non-addicts in Iranian high schools.

Cyberpsychol Behav. 2008 Dec;11(6):731-3.

16) Siomos KE, Dafouli ED, Braimiotis DA, Mouzas OD, Angelopoulos NV. Internet

addiction among Greek adolescent students. Cyberpsychol Behav. 2008

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