DISSERTATION ON
A STUDY TO ASSESS THE EFFECTIVENESS OF STRUCTURED TEACHING PROGRAMME ON KNOWLEDGE REGARDING
PREVENTION OF COMPUTER VISION SYNDROME AMONG HIGHER SECONDARY STUDENTS AT SELECTED SCHOOLS, CHENNAI.
M.Sc (NURSING) DEGREE EXAMINATION BRANCH – IV COMMUNITY HEALTH NURSING
COLLEGE OF NURSING
MADRAS MEDICAL COLLEGE, CHENNAI – 600 003
A Dissertation submitted to
THE TAMIL NADU DR.M.G.R.MEDICAL UNIVERSITY, CHENNAI – 600 032
In partial fulfilment of the requirement for the award of degree of MASTER OF SCIENCE IN NURSING
OCTOBER - 2019
DISSERTATION ON
A STUDY TO ASSESS THE EFFECTIVENESS OF STRUCTURED TEACHING PROGRAMME ON KNOWLEDGE REGARDING
PREVENTION OF COMPUTER VISION SYNDROME AMONG HIGHER SECONDARY STUDENTS AT SELECTED SCHOOLS, CHENNAI.
Examination : M.Sc (Nursing) Degree Examination
Examination month and year : OCTOBER 2019
Branch & Course : IV – COMMUNITY HEALTH NURSING
Register No : 301726154
Institution : COLLEGE OF NURSING,
MADRAS MEDICAL COLLEGE, CHENNAI – 600 003.
Sd: ____________________________ Sd:____________________________
Internal Examiner External Examiner
Date: __________________________ Date: __________________________
THE TAMILNADU DR.M.G.R.MEDICAL UNIVERSITY,
CHENNAI-600 032
CERTIFICATE
This is to certify that this dissertation titled, “A STUDY TO ASSESS THE EFFECTIVENESS OF STRUCTURED TEACHING PROGRAMME ON KNOWLEDGE REGARDING PREVENTION OF COMPUTER VISION SYNDROME AMONG HIGHER SECONDARY STUDENTS AT SELECTED SCHOOLS, CHENNAI”, is a bonafide work done by S.PABITHA, M.Sc(Nursing) II year Student, College of Nursing, Madras Medical College, Chennai -03, submitted to the Tamil Nadu Dr.M.G.R. Medical University, Chennai in partial fulfillment of the requirement for the award of the degree of Master of Science in Nursing Branch – IV, Community Health Nursing under our guidance and supervision during academic year 2017 – 2019.
Ms. A.Thahira Begum, M.Sc(N)., MBA., M.Phil., Dr.R.Jayanthi, MD., FRCP.,(Glasg).,
Principal, Dean,
College of Nursing, Madras Medical College, Madras Medical College, Chennai -03.
Chennai -03.
DISSERTATION ON
A STUDY TO ASSESS THE EFFECTIVENESS OF STRUCTURED TEACHING PROGRAMME ON KNOWLEDGE REGARDING PREVENTION OF COMPUTER VISION SYNDROME AMONG HIGHER SECONDARY
STUDENTS AT SELECTED SCHOOLS, CHENNAI.
Approved by the dissertation committee on 24.07.2018 CLINICAL SPECIALITY GUIDE
Selvi. B. Lingeswari, M.Sc(N)., MBA., M.Phil., ___________________
Reader in Community Health Nursing , College of Nursing,
Madras Medical College, Chennai -03.
HEAD OF THE DEPARTMENT
Mrs.A.Thahira Begum, M.Sc(N)., MBA., M.Phil., ___________________
Principal,
College of Nursing, Madras Medical College, Chennai -03.
DEAN
Dr. R. Jayanthi, MD., F.R.C.P. (Glasg)., ____________________
Dean,
Madras Medical College, Chennai -03.
A Dissertation submitted to
THE TAMIL NADU DR.M.G.R.MEDICAL UNIVERSITY, CHENNAI – 600 032.
In partial fulfilment of the requirement for the award of degree of MASTER OF SCIENCE IN NURSING
OCTOBER - 2019
CERTIFICATE OF PLAGIARISM
This is to certify that the dissertation work titled,
“A STUDY TO ASSESS THE EFFECTIVENESS OF STRUCTURED TEACHING PROGRAMME ON KNOWLEDGE REGARDING PREVENTION OF COMPUTER VISION SYNDROME AMONG HIGHER SECONDARY STUDENTS AT SELECTED SCHOOLS, CHENNAI”, of the candidate S.PABITHA, for the partial fulfilment of M.Sc. Nursing programme in the branch of
COMMUNITY HEALTH NURSINGhas been verified for plagiarism through relevant plagiarism checker. We found that the uploaded thesis file from introduction to conclusion pages and rewrite shows ___ % of plagiarism ( ___ % uniqueness) in this dissertation.
CLINICAL SPECIALITY GUIDE / SUPERVISOR Selvi.B.Lingeswari, M.Sc(N)., MBA., M.Phil., Reader in Community Health Nursing ,
College of Nursing, Madras Medical College, Chennai -03.
PRINCIPAL
Mrs.A.Thahira Begum, M.Sc (N)., MBA.,M.Phil., Principal,
College of Nursing, Madras Medical College, Chennai-03.
ACKNOWLEDGEMENT
Acknowledgement and recognition from authoritative quarters are important to every artist.
……Sridevi
I am grateful to the almighty god for giving me all the grace that I need to pursue this study. I would also like to extend my gratitude to a number of people whose help was very valuable in this research.
I submit my heartiest gratitude to Dr.R.Jayanthi, MD., F.D.C.P.(Glasg)., Dean, Madras Medical college, Chennai-03 for permitting me to conduct the study in this prestigious institution.
I am more privileged to thank Institutional Ethics Committee, of Madras Medical College, Chennai-03 for me an approval to conduct this study.
My heartfelt gratitude to Ms.A.Thahira Begam, M.Sc (N)., M.B.A., M.Phil., Principal, College of Nursing, Madras Medical College, Chennai-03 for her encouragement, timely guidance and expertise suggestion throughout the study.
It is with immense pleasure, I thank Dr. R. Shankar Shanmugam, M.Sc(N)., M.B.A., Ph.D., College of Nursing, Madras Medical College, Chennai-03 for his perfect guidance, untiring support and scholastic suggestions for the successful completion of the study.
My great pleasure and privilege to express my gratitude to Selvi.B.Lingeswari, M.Sc(N)., Reader, Community Health Nursing Department, Madras Medical College, Chennai-03 for her support, encouragement, valuable suggestions and guidance.
I express my special thanks to Dr. Joy Patricia Pushparani, M.D., Professor, Institute of Community Medicine, Madras Medical College, Chennai -03 for her valuable suggestions and encouragement which enable me to accompalish this study.
My sincere thanks to Mrs.N.Sathyanarayani, M.Sc(N)., Reader, former lecturer in Community Health Nursing Department, Mrs.T.Ramanibhai, M.Sc(N)., Reader, Community Health Nursing Department, and Mrs.R.Sumathi, M.Sc(N)., Reader, Nursing Administrative Department in College of Nursing, Madras Medical College, Chennai-3 for their valuable guidance in completing this study.
My sincere thanks to Ms.G.Mala, M.Sc(N)., Ph.D., former Nursing Tutor, Mr.K.Kannan, M.Sc(N)., Nursing Tutor, and Mrs.P.Tamilselvi, M.Sc(N)., Nursing Tutor, College of Nursing, Madras Medical College, Chennai-03 for their valuable guidance and in carrying out of the study.
It is my privilege to express my gratitude to Mrs.L.Shanthi, M.Sc(N), former head of the Community Health Nursing Department, College of Nursing, Madras Medical College, Chennai-03 for their timely support in selection of the topic for the dissertation and preparing for the proposals.
I wish to express my gratitude to all the Faculty Members of College of Nursing, Madras Medical College, Chennai-03 for their valuable guidance in conducting this study.
I would like to express my special thanks to Mrs. G. Shobana Gangadharan, M.Sc(N)., Ph.D., Department of community health nursing, Apollo College of Nursing, Vanagaram, Chennai-95, and Mrs. S. Kanchana, M.Sc(N)., Department of community health nursing, Madha College of Nursing, Kundrathur, Chennai-69, for their provoking ideas through content validity in constructing tool for this study.
I would like to express my special thanks to Mr.Kumaravel pandian, I.A.S Deputy Commissioner [Education], Greater Chennai Corporation, Ripon Building, Chennai-03 for granting the permission to carry out my study in the corporation school.
My sincere thanks to Retd. Dr.A.Vengatesan, M.Sc., M.Phil., Ph.D., Deputy Director (Statistics), Directorate of Medical Education, Chennai for his critical statistical advice and willingness to help in statistical analysis and compiling of this study.
My special word of thanks to Mr. Ravi., M.A., MLIS., Librarian, College of Nursing, Madras Medical College, Chennai-03 for extending his support in providing all the necessary materials needed to complete the study in an organized manner.
My deepest gratitude to Mr.S.Perumal, M.A, B.Ed. B.T Assistant, Panchayat Union Middle School, Padappai for editing the tool and content in English and Mrs.R.Santhi, M.A, B.Ed. Head Master, P.U.M.School, Athancheri, for editing the tool in Tamil for this thesis work.
I am grateful to all my Colleagues for their support, interest, encouragement and guidance, thereby making me success in all the difficulties faced during the study.
I express my heartfelt gratitude to T.Mahendran, M.A., M.Ed., Headmaster, Chennai Higher Secondary School, Tondiarpet who had extended their kind co-operation during this study.
I am indebted, blessed and lucky to have my parents Mr.N.Sivakumar and Mrs.S.Ushamaheswari, Brother Mr.S.Lalithkumar all of whom stood by me in the joys and tensions with forbearance, unconditional support and inspiration which helped me to complete the study successfully.
I owe my great sense of gratitude to Mr.Syed Husain, B.Sc (Com), Citi Dot Net, and Mr.Ramesh, B.A., MSM Xerox for their enthusiastic help and sincere effort in alining the manuscript using valuable computer skills and also bringing this study into a printed form.
My heartfelt thanks to all the school students who have participated in this study for their wonderful cooperation.
ABSTRACT
In the modern world, the viewing of electronic displays has become a huge part of daily living at home, at work, during leisure time and the move. The use of laptop, desktop and tablet computers, smartphones and electronic reading devices has become ubiqui tous.
Without computer, world has no global awareness. More recently, visual and ocular problems are reported as the most frequently occurring health problems among computer users is named as computer Vision Syndrome(CVS). Computer Vision Syndrome may also be conferred with symptoms of eyes soreness, redness, fatigue, headaches, burning, glare sensitivity, contact lens discomfort, double vision and periodic blurring of near and distant vision.
TITLE
“A study to assess the effectiveness of structured teaching program on knowledge regarding prevention of computer vision syndrome among higher secondary students in selected schools at Chennai”.
OBJECTIVES
The study was carried out i) to assess the pre-test knowledge of higher secondary students regarding computer vision syndrome. ii) to assess the effectiveness of structure teaching program on knowledge of higher secondary students regarding prevention of computer vision syndrome.
iii) to compare the pre-test and post-test knowledge regarding prevention of computer vision syndrome among higher secondary students. iv) to findout the association between post-test knowledge score among higher secondary students with them selected demographic variables.
METHODOLOGY
The study was conducted with 60 samples of higher secondary school student s in quantitative approach. Pre-experimental one group pre test post test design, sample selection was done by purposive sampling technique method. Pre-existing knowledge was assessed by using semi structured questionnaires. After the pre test, structured programme was given regarding prevention of computer vision syndrome among higher secondary sch ool students.
After 7 days post-test was conducted by using same tool.
RESULTS
The findings of the study revealed that structured teaching programme had improved the knowledge regarding prevention of computer vision syndrome among higher secondary students with paired t test, p< 0.001. There is a statistically significance in knowledge attainment on prevention of computer vision syndrome shows effectiveness of structured teaching programme.
CONCLUSION
The result of the study shows that structured teaching programme was effective in improving knowledge regarding computer vision syndrome among higher secondary students.
TABLE OF CONTENTS
Chapter Content Page No
I INTRODUCTION 1
1.1 Need for the study 5
1.2 Statement of the problem 7
1.3 Objectives 8
1.4 Operational definitions 8
1.5 Hypothesis 9
1.6 Assumptions 9
1.7 Delimitation 9
1.8 Conceptual framework 10
II REVIEW OF LITERATURE
2.1 Literature review related to the study 13 III METHODOLOGY
3.1 Research approach 27
3.2 Research design 27
3.3 Setting of the study 27
3.4 Duration of the study 28
3.5 Study population 28
3.6 Sample 28
3.7 Sample size 28
3.8 Sampling technique 28
3.9 Research variables 29
3.10 Development and description of the tool 29
3.11 Score interpretation 30
3.12 Content validity 31
3.13 Ethical consideration 32
3.14 Reliability 33
3.15 Pilot study 33
3.16 Data collection procedure 34
3.17 Data analysis 35
IV DATA ANALYSIS AND INTERPRETATION 37
V DISCUSSION 55
VI SUMMARY AND CONCLUSION
6.1 Summary 63
6.2 Implications 65
6.3 Recommendations 67
6.4 Limitations 68
6.5 Conclusion 68
REFERENCES ANNEXURES
LIST OF TABLES
Table. No Title Page No
3.1 Intervention protocol for pre-experimental group 34 4.1 Description of demographic variables of the study
participants 38
4.2 Description of pre-test knowledge level of knowledge
among school students. 46
4.3 Description of post-test knowledge level of knowledge
among school students. 47
4.4 Comparison of pre-test and post-test level of knowledge
score 48
4.5 Effectiveness of structured teaching programme and
generalization of knowledge gain score 50
4.6 Association between student’s post-test level of knowledge
and their selected demographic variables. 52
LIST OF FIGURES
Fig.No Title Page No
1.1 Primary health care model in community health nursing 7 1.2 Conceptual framework based on CIPP evaluation model 12
3.1 Schematic Representation of the methodology 36
4.1 Age Distribution 40
4.2 Gender Distribution 40
4.3 Type of family 41
4.4 Education status of father 41
4.5 Occupation status of father 42
4.6 Education status of mother 42
4.7 Occupation status of mother 43
4.8 Monthly income of family 43
4.9 Hobbies of the students 44
4.10 Duration of computer use per day 44
4.11 Reason for computer use 45
4.12 Pre-test Knowledge Score of the participants 46
4.13 Post-test Knowledge Score of the participants 47 4.14 Comparison of pre-test and post-test level of knowledge score 49 4.15 Effectiveness of structured teaching programme 51 4.16 Association between post-test level of knowledge score and
their age. 53
4.17 Association between post-test level of knowledge score and
their gender. 53
4.18 Association between post-test level of knowledge score and
type of family 54
4.19 Association between post-test level of knowledge score and
duration of computer use. 54
ANNEXURES
S.N
o
Content1. Certificate of approval from Institutional Ethics Committee 2. Permission letter from Chief Educational Officer
3. Certificate of content validity
4. Informed consent - English and Tamil 5. Certificate of English Editing
6. Certificate of Tamil Editing
7. Tool for Data Collection - English and Tamil 8. Lesson plan - English and Tamil
9. Photograph
10. Booklet regarding prevention of computer vision syndrome
LIST OF ABBREVIATION
S.No Abbreviation Expansion
1 CI Confidence Interval
2 DF Degree of freedom
3 Fig Figure
4 H1 and H2 Research hypothesis
5 SD Standard Deviation
6 P Significance
7 X2 Chi square test
8 STP Structured Teaching Programme
9 LED Light Emitting Diode
10 CVS Computer Vision Syndrome
11 VDT Video Display Terminal
12 NIOSH National Institute of Occupational Safety and Health
13 AOA American Optometric Association
14 LCD Liquid Cristal Display
15 IT Information Technology
Chapter-I
INTRODUCTION
CHAPTER - I INTRODUCTION
“Originality is simply a pair eyes”
-Thomas.W.Higginson
In the modern world, the viewing of electronic displays has become a huge part of daily living at home, at work, during leisure time and the move. The use of laptop, desktop and tablet computers, smartphones and electronic reading devices has become ubiquitous.
Without computer, world has no global awareness. The computer has become backbone of today’s occupational settings. From primitive tools of the stone age, today we have entered a new era, the computer age-an age which owes everything to inventors. It has created a brand new environment. They are the heartbeats of the modern world.
Now a day’s children and technology are practically connected. Whether for educational purposes or others, children are spending a good portion of their day on "LED screen" staring at computers, smartphones and other digital devices.
For those children without a personal home PC, friends often provide them with access to a computer, most commonly to play computer games. Today’s youth learn to play computer games as an expected rite of development in our high tech society. These games help teach many of the basic skills and knowledge is necessary to use a computer, such as the use of the mouse and/or joystick, basic keyboard commands, starting and ending programs, and learning how to save and store files. Learning these basic skills enable youngsters to feel comfortable with computing and give them an ability to learn to use educational software more easily at school.
Blue light is emitted by the LED screens of computers, smartphones and other digital devices. Many researchers and ophthalmologist are concerned that the added blue light exposure from computers and other digital devices might increase a risk of age-related eye diseases like macular degeneration in future life.
Over the past 15 years, there has been a great development in the information technology. The use of computer in each work has created life easier and increase output
hugely. Computer has become virtually an essential piece of apparatus each at workplace and reception. More recently, visual and ocular problems are reported as the most frequently occurring health problems among computer users is named as Computer Vision Syndrome (CVS).
Computer Vision Syndrome may also be conferred with symptoms of eyes soreness, redness, fatigue, headaches, burning, glare sensitivity, contact lens discomfort, double vision and periodic blurring of near and distant vision. Computer Vision Syndrome is common complaint in majority of individuals unceasingly use laptops, mobile Internet and other technology gadgets that strain the eye. Over 75% of young software professionals and college students in India’s IT capital of Bangalore are reportedly face the vision disorder Computer Vision Syndrome. In the world it's been calculable that almost sixty million folks expertise vision issues as a results of computer use. Millions of new cases occur each year.
Increased use of computers has semiconductor diode to a rise within the variety of patients with ocular complaints are being classified along as computer Vision Syndrome (CVS). This new entity, frequently mentioned in the World Wide Web and the lay press, is now being accepted in medical literature.
Computer Vision Syndrome (CVS) may be a temporary condition ensuing from focusing the eyes on a computer screen for drawn-out, uninterrupted periods of time.
Some symptoms of Computer Vision Syndrome (CVS) like headaches, blurred vision, neck pain, fatigue, eye strain, dry, irritated eyes, double vision, polyopia, and difficulty refocusing the eyes.
Video Display Terminal (VDT) related vision problems are at least as significant a health concern as the musculoskeletal disorders. Most studies indicate that visual symptoms occur in 50-90% of Video Display Terminal (VDT) workers, while a study released by a survey of optometrists indicated that ten million primary eye care examinations are provided annually during this country primarily thanks to visual issues at Video Display Terminal
(VDTs) - not a little public health issue. Vision issues are pervasive among computer staff and are the supply of employee discomfort and attenuate work performance.
BACKGROUND OF THE STUDY:
Computer vision syndrome is a complex of vision problem due to prolonged use of computer. Due to advanced development of technology, the children and students of any age group prefers gadgets like computer, laptop, mobiles and tablet for both education and entertainment purpose. Now a day’s students collect all the information through internet by browsing the computers or smart phones more frequently for their homework purpose.
According to the American Optometric Association (AOA), the most common health complaints among computer workers are vision-related problems. The studies suggest its prevalence may be fifty to ninety percent among computer workers. These symptoms include eye strain, dry eyes, eye irritation, blurred vision and double vision. With more and more of us using a computer at work and smartphones for so many purposes, CVS is becoming a major public health issue. The AOA reports that a survey of optometrists found that approximately 10 million eye exams being performed annually for reasons related to computer vision syndrome.
One reason the problem is so pervasive: Unlike words printed on a page that have sharply defined edges, electronic characters, which are made up of pixels, have blurred edges, making it more difficult for eyes to maintain focus. Unconsciously, the eyes repeatedly attempt to rest by shifting their focus to an area behind the screen, and this constant switch between screen and relaxation point creates eyestrain and fatigue. Another unconscious effect is a greatly reduced frequency of blinking rate, which can result in dry, irritated eyes. Instead of a normal blink rate of 17 or more blinks a minute, while working on a computer the blink rate is often reduced to only about 10 to 12 blinks.
Too much time in front of a computer screen can lead to eye discomfort, fatigue, blurred vision and headaches," said by Dr. Leonard Press, optometrist and AOA's Vision & Learning Specialist. "However, some unique aspects of how children use computers may make them even more susceptible than adults to these problems."
Nurses are key persons in the health team, who play an important role in prevention of disease and maintenance of health among the community. As a school health nurse, the investigator feels and aspect of health care system to start creating awareness among people who are at risk for developing Computer vision syndrome and also believes that this study are going to be a stepping stone during this direction.
1.1 NEED FOR THE STUDY:
“An ounce of prevention is worth pounds of cure.”
- Henry De Bractor
Computers become a permanent a part of our lives. Today in virtually every corporate cubicle on the desk of every secretary or executives sits a computer that allows us to write design, compute, research, and communicate faster than we ever could before. Yet this communication has not come without a price to our health and general comfort level. Young generating are opting software job and due to stress lead in psychological distress.
American Optometric Association (AOA) has reported a substantial increase in employee complaints about Computer vision syndrome. The report also states that this trend is very much alarming. Despite the fact that 99.99% of the risk factors are100% preventable, no concrete efforts are taken to ensure computer workers health. Sheedy stated that up to 90% of computer users report visual problems and 22% report musculoskeletal fatigue and 10 million cases of Computer vision syndrome need medical help annually.
The prevalence of eye symptoms among computer users ranges from 25-93% as reported by various investigations. Computers have become indispensable in the workplace. The combination of fixed and constrained body postures, work overload and unsuitable work stations can lead to health problem. The most common complaints among computer users are ache and pains in the shoulder, forearm, and wrist, hand, back, neck and eye strain.
The U.S Bureau of labor statistics reports that more than 75 million workers sit at a computer every day. More than 143 million Americans work on a computer each day, with 88%
of them suffering from computer eye strain, according to estimates. In addition nearly 54 million
children work at a computer each day either at home or at school. Currently, there are 135 million visually disabled in the world and 90% of these live in developing countries. The present rate is likely to double by 2020. This prompted WHO and its member states to launch a global initiative in 1999 called” VISION 2020-The Right to Sight”. The programmer aims at eliminating the preventable causes of visual impairment and in this context, prevention of computer related eye strain receives major attention.
The National Institute of Occupational Safety and Health (NIOSH) reports that nearly 88% of all computer professionals will develop CVS at some time in their lives. Eye strain is the number one complaints of office workers. The more time you spend working at a computer, the more likely you are to report problem with eye strain.
Investigator has his own experience, by the contact of people who are working in software companies, who work in front of computer for long hours. Investigator was able to identify the symptoms of CVS by watching them closely through a continuous period of time.
Initially people with good eye sight were becoming weaker with their vision, mainly due to restless work in front of computer, and the investigator has identified that it was due to CVS.
Based on primary health care model emphasize the development of universally affordable and accessible essential health services that are community based and emphasize health promotion and maintenance, self reliance and community participation in decision making about health.
Fig.1.1 PRIMARY HEALTH CARE MODEL IN COMMUNITY HEALTH NURSING
Primary health care incorporate community based practice, involvement of the community in the health care decision, a focus on disease prevention and health promotion.
School students are the major part in the community with various health needs. As a nurse researcher to educate the students on prevention of computer vision syndrome through this the students can prevent the computer vision syndrome.
As students pursuing computer science group in higher secondary school are the future IT and software engineers, preventive strategies adopted by them will significantly decrease the burden of computer vision syndrome and improve productivity of the profession.
Thus, this present study aim is to impart the knowledge regarding prevention of computer vision syndrome among the higher secondary school students.
1.2 STATEMENT OF THE PROBLEM:
“A study to assess the effectiveness of structured teaching program on knowledge regarding prevention of computer vision syndrome among higher secondary students in selected schools at Chennai”.
1.3 OBJECTIVES OF THE STUDY:
1. To assess the pretest knowledge of higher secondary students regarding computer vision syndrome.
2. To evaluate the effectiveness of structure teaching program (post-test) on knowledge of higher secondary students regarding prevention of computer vision syndrome.
3. To compare the pre-test and post-test knowledge regarding prevention of computer vision syndrome among higher secondary students.
4. To findout the association between post-test knowledge scores among higher secondary students and selected demographic variables.
1.4 OPERATIONAL DEFINITION:
Assess:
In this study it refers to find out the knowledge of adolescents regarding prevention of computer vision syndrome.
Effectiveness:
In this study it refers to significant increase in the level of knowledge among adolescents regarding prevention of computer vision syndrome which is measured by pre-test, structured teaching program and posttest.
Structured teaching program:
In this study it refers to lecture (30 mins) giving to adolescents regarding usage of computer, complications, precautions for prevention of computer vision syndrome.
Knowledge:
In this study it refers to awareness of prevention of computer vision syndrome among adolescents.
Prevention:
In this study it refers to the measures taken to decrease the incidence and to limit the progression of computer vision syndrome.
Computer vision syndrome:
In this study it refers to a complex of eye and vision problem related to excessive exposure to computer and its use.
Higher secondary students:
In this study it refers to higher secondary(11th & 12th) school students who belongs to computer science group.
1.5 HYPOTHESIS:
H1: There will be a significant difference between pre-test and post-test level of knowledge regarding prevention of computer vision syndrome among higher secondary students.
H2: There will be a significant association between post-test level of knowledge and their selected demographic variables.
1.6 ASSUMPTION:
1. Higher secondary students may have some knowledge regarding prevention of computer vision syndrome.
2. Administration of structure teaching program may enhance the knowledge of higher secondary students on prevention of computer vision syndrome.
1.7 DELIMITATION:
The study is limited to higher secondary students in selected schools.
The study is limited to 4 weeks.
1.8 CONCEPTUAL FRAMEWORK
Conceptual framework selected for this study is based upon the concepts of CIPP (context, input, and product) - evaluation model developed by Danie L. Stuffle beams (1999).
Details of the CIPP Model
Context : Environment and needs Input : Strategies and resources Process : Monitoring implementation
Product outcomes- both quality and significance Context evaluation
Context evaluation assesses the needs, problems and opportunities as bases for defining goals and priorities and judging the significance of outcomes. In this study context evaluation includes the identification of the demographic variables. Through context evaluation the investigator identified that many of computer users have poor knowledge regarding computer vision syndrome. This was identified with the help of structured questionnaire to assess the level of knowledge on computer vision syndrome.
Input evaluation
Input evaluation assesses the alternative approaches to meet the need of planning programs and resources. In this study the researcher understood the need to give education to the higher secondary students on prevention of computer vision syndrome in future. For that the
researcher identified structure teaching programme on prevention of computer vision syndrome through LCD as resource.
Process evaluation
Process evaluation assesses the implementation of plans to guide activities and later help to explain outcomes. In this study process refers to administration of structured teaching programme regarding prevention of computer vision syndrome with the use of LCD.
Product evaluation
Product evaluation identifies the intended and unintended outcomes. Both help to keep the process on track and to determine the effectiveness. In this study product is the outcome of structured teaching programme that is change in the level of knowledge of higher secondary students regarding computer vision syndrome which is measured by conducting a posttest using the same questionnaire.
Fig.1.2 Stuffle Beam CIPP Model
DEMOGRAPHIC VARIABLES
Age
Gender
Family type
Education
Occupation
Monthly income
Hobby
Duration of computer use per day
Reason for computer use
CONTEXT INPUT PROCESS PRODUCT
Pretest level of knowledge
regarding prevention of
computer vision syndrome with
structure questionnaire.
Administration of structured
teaching programme on
prevention of computer
vision syndrome
Transformation ofknowledge on prevention of computer
vision syndrome
Posttest level of knowledge
regarding computer vision syndrome with same questionnaire
ADEQUATE
MODERATE
INADEQUATE
Feedback
CHAPTER- II
RIVIEW OF LITERATURE
CHAPTER- II
REVIEW OF LITERATURE
This chapter presents a review of related literature relevant to the study among higher secondary school students regarding prevention of computer vision syndrome. The purpose of review of literature is to obtain comprehensive knowledge base and in depth information about the awareness regarding computer vision syndrome among higher secondary students.
2.1. The review of literature for the current study has been grouped under following headings:
2.1.1. Statistics related to computer usage.
2.1.2. Incidence of computer related health hazards.
2.1.3. Signs and symptoms of computer vision syndrome
2.1.4. Benefits of teaching programme regarding prevention of health hazards of prolonged computer usage.
2.1.1. STATISTICS RELATED TO COMPUTER USAGE.
L. Jamira et al (2019) conducted a cross sectional study on Epidemiology of technology addiction among school students in India. Study sample was 885 school students in north India.
The mean age of the study participants was 15.1 years. Among the participants, 30.3% met the dependence criteria. One-third (33%) of the students stated that their grades had gone down due to gadget use. Technology addiction was higher in male students, those having a personal mobile phone 2.98, (1.52–5.83), use smart phone (2.77, 1.46–5.26), use one additional gadget (2.12, 1.14–3.94) and those who were depressed (3.64, 2.04–6.49).
Mohammed Iqbal et al (2018) conducted a study on Computer Vision Syndrome Survey among the Medical Students in Sohag University Hospital, Egypt. There were 100 medical students included in this study (50 males and 50 females). The most remarkable result in this study was recording that 86% of the medical students sample was used to spend 3 hours or more on a daily basis thus were complaining of one or more of CVS manifestations.
Sohini Mitter (2018) according to Com Score’s Video Metrix Multi-Platform (December 2017), YouTube reaches 85 percent of all highly engaged internet users (18-plus years) in India who watch a video within 48 hours of it going live.
Menon et al (2018) Internet addiction: A research study of college students in India, in this study, we found the addiction was more in the range of moderate to mild addiction. This study indicated that there is a high degree of correlation between age and internet addiction with older students being more addicted to the Internet than younger students. Also with regard to Internet usage, there were significant differences with regard to gender with men being more addicted than women. This is in accordance with precious studies that also indicate similar findings. The study found that there are no differences between the students in terms of the study year.
2.1.2. INCIDENCE OF COMPUTER RELATED HEALTH HAZARDS.
Sudip Poudel (2019) conducted a study,Effect Of Display Gadgets On Eyesight Quality (Computer Vision Syndrome) Of M.Sc.(CSIT) Students in Tribhuvan University.The prevalence of symptoms of CVS (one or more) was found to be 80.4%; the most disturbing symptom was Eyestrain (15.2%) followed by Tired Eye (13.2%). Students who used VDT Display Gadgets for more than 4 hours per day experienced significantly more symptoms of CVS.
Parul Ichhpujan et al (2019) conducted a cross-sectional study on visual implications of digital device usage in school children. The study included 576 adolescents attending urban schools. 20% of students aged 11 in the study population use digital devices on a daily basis, in comparison with 50% of students aged 17. The majority of students preferred sitting on a chair while reading (77%; 445 students), with only 21% (123 students) preferring to lie on the bed and 8 students alternating between chair and bed. There was a significant association between the students who preferred to lie down and those who experienced eyestrain, as reported by a little
over one fourth of the student population (27%). Out of 576 students, 18% (103) experienced eyestrain at the end of the day after working on digital devices.
Saira Maroof et al (2019) conducted a cross sectional survey on Relationship of screen hours with digital eye strain from teenagers. Mean age of the participant’s was 14.9 ± 1.99 years while mean hours of computer and digital screen use was 2.45 ± 1.49 hours. The most frequently experienced symptoms were headache 47.3%, followed by tired eyes 33.7%, blurred vision 25%, eye strain 22.3%, lightning or glare discomfort 20.5%, irritated or sore eyes 15% and dry eyes reported by 9.6% participants. There was a statistically significant relationship between Digital Eye Strain and screen hours (p<0.05).
Pragnya Rao Donthinenia et al (2019) Incidence, demographics, types and risk factors of dry eye disease in India: Electronic medical records driven big data analytics report, this was an observational hospital-based study of 1,458,830 new patients presenting between 2010 and 2018.
The result shows that overall, 21,290 (1.46%) patients were diagnosed with recent-onset DED.
The incidence of DED was 2688 and 16,482 per million population in children and adults, respectively (p < 0.0001). While incidence was significantly greater in males in 3rd, 4th, 9th and 10th decade (p < 0.03), it was greater in females in 5th and 6th decade (p < 0.0001) of life.
Classified etiologically 35.5%, 20.6% and 39.9% of patients had evaporative, aqueous deficient and mixed type of DED, respectively.
Anjila Basnet et al (2018) conducted a study on Computer Vision Syndrome Prevalence and Associated Factors among the Medical Student in Kist Medical College. Among 100 medical students 74% of the medical students sampled who used to spend 2 hours or more on their digital screens on a daily basis were complaining of one or more of CVS manifestation in that dry eye was associated with CVS in 58 % in right eye and 55% in left eye according to-Tear film break up time measurement whereas 59 % students have dry eye in right eye and 57% students have dry eye in left eye according to Schirmer’s test – I measurement.
S chyada et al (2018) conducted a Comparative Study of Computer Vision Syndrome and Smart Devices among the Employers and Students in College of health and Medical Technique of University. Students that they have vision affects due to employing of these devices in such of ages about [(19-23), (24-32)] in male and female, but the first ages have slightly higher rates than
other)] by percentage (50%) of the students that suffer from computer vision syndrome from all proportion, whereas 2nd group of another ages has low significant differences in comparison with previous by the percentage closely (36.36%). Finally they concluded that using of computers and smart devices of students more than employers. Appearing different enfluencing of eye glass wearing of students and employers that utilizing different computers and smart devices with some of risk factors according to others.
MN Zaman et al (2018) conducted a study on Computer Vision Syndrome in Visual Display Terminal users (VDT)A total of 144 subjects with mean age of 27.73 ± 4.88years old (range 18–35 years). Of all these 94 (65.28%) were having CVS where mean score of CVS was 7.50±5.86. Out of that 65.95% of male and 34.04% of female were having CVS. 34 subjects were using Visual Display Terminal for 4–6 hours per day, 63 subjects were using Visual Display Terminal for 7–10 hour per day and 47 subjects were using Visual Display Terminals for more than 10 hours per day.
Ganga et al (2017): The incidence of Computer Vision Syndrome is as high as 50%-90%
among the employees of computer profession. In this clinical study on “Computer Vision Syndrome”, a total number of 55 patients were registered and out of these, 53 patients completed the whole treatment. The general observations and the effect of therapy quoted include the data of 53 patients who have completed the entire course of treatment. Oral administration of Saptamrita Lauha tablets, 500 mg bd/day with unequal quantity of Madhu , Ghrita and Triphala eye drops one drop in each eye, 4 times/day for 30 days has found to be effective in the management of CVS.
S Munshi et al (2017) conducted a study on Computer vision syndrome a common cause of unexplained visual symptoms in the modern era.Information was collected from Medline, Embase & National Library of Medicine over the last 30 years up to March 2016. The bibliographies of relevant articles were searched for additional references. The result shows that the Patients with Computer vision syndrome present to a variety of different specialists, including General Practitioners, Neurologists, Stroke physicians and Ophthalmologists. While the condition is common, there is a poor awareness in the public and among health professionals.
W Jaschinski et al (2015) conducted a study on Computer vision syndrome in presbyopia and beginning presbyopia: effects of spectacle lens type. Statistical factor analysis identified five specific aspects of the complaints. In the subgroup of 25 users between the ages of 36 and 57 years, who wore distance‐vision lenses and performed more demanding occupational tasks, the reported extents of ‘ocular strain’, ‘musculoskeletal strain’ and ‘headache’ increased with the daily duration of computer work and explained up to 44 per cent of the variance (r = 0.66). In the other subgroups, this effect was smaller, while in the complete sample (n = 175), this correlation was approximately r = 0.2. The subgroup of 85 general‐purpose progressive lens users (mean age 54 years) adopted head inclinations that were approximately seven degrees more elevated than those of the subgroups with single vision lenses.
M Logaraj et al (2014) conducted a study on Computer Vision Syndrome and Associated Factors among Medical and Engineering Students in Chennai. A cross sectional study was conducted. Students who used computer in the month preceding the date of study were included in the study. Results shows that among engineering students, the prevalence of CVS was found to be 81.9% while among medical students; it was found to be 78.6% (158/201). A significantly higher proportion of engineering students 40.9% (88/215) used computers for 4.6 h/day as compared to medical students 10% (20/201) (P < 0.001). The result shows that the significant correlation was found between increased hours of computer use and the symptoms redness, burning sensation, blurred vision and dry eyes.
2.1.3. SIGNS AND SYMPTOMS OF COMPUTER VISION SYNDROME
V. Mohan et al (2019) conducted a study on Prevalence of complaints of arm, neck, and shoulders among computer professionals in Bangalore: A cross-sectional study. Prevalence of CANS in the study group was 58.6%. Neck complaints topped the list followed by shoulder, wrist, hand, elbow, upper arm, and lower arm complaints in the descending order. Women had overall higher prevalence and significantly higher prevalence of upper limb complaints than men. Inadequate space, maintaining good posture, and repetition of same tasks have emerged as an independent factors associated with CANS.
CM Maria (2018) A quantitative cross-sectional observational study, in which the workers underwent a clinical ophthalmologic examination and answered a questionnaire. For the Visual
Function Questionnaire (VFQ-25) a Kolmogorov-Smirnov test was performed to characterise the study population, and the ANOVA, Mann-Whitney and Kruskal-Wallis tests were used to analyse the associated factors. A multiple linear regression model was created, using stepwise forward, with variables that presented significance levels with p<0.20. They remained in the final model, the variables that presented descriptive levels p<0.05. In the work effort, the items that appeared as the main sources of stress were: ‘interruptions at work’ (3.7%),’overtime work’
(3.6%) and increased demand (3.6%).
Mowatt L et al (2018). Four hundred and nine students participated; 78% were females. The mean age was 21.6 years. Neck pain (75.1%), eye strain (67%), shoulder pain (65.5%) and eye burn (61.9%) were the most common CVS symptoms. Dry eyes (26.2%), double vision (28.9%) and blurred vision (51.6%) were the least commonly experienced symptoms. Eye burning (P = .001), eye strain (P = .041) and neck pain (P = .023) were significantly related to level of viewing. Moderate eye burning (55.1%) and double vision (56%) occurred in those who used handheld devices (P = .001 and .007, respectively). Moderate blurred vision was reported in 52%
who looked down at the device compared with 14.8% who held it at an angle. Severe eye strain occurred in 63% of those who looked down at a device compared with 21% who kept the device at eye level. Shoulder pain was not related to pattern of use.
Layan Al Tawil et al (2018) conducted a study on Prevalence of self-reported computer vision syndrome symptoms and its associated factors among university students. The results say that most common symptom due to prolonged computer use was neck or shoulder pain, reported by 82.2% of the subjects. Overall, 66.5% of the subjects suffered from headache and 51.5% from dry eyes, in mild, moderate, or severe form. Business students were 1.6 times as likely as medical students to suffer from computer vision syndrome (odds ratio = 1.65; 95% confidence interval: 1.22, 2.24). The use of electronic devices for more than 5 h (odds ratio = 1.52; 95%
confidence interval: 1.07, 2.16) was also associated with experiencing computer vision syndrome symptoms. Regarding computer vision syndrome prevention, factors such as hours of use, screen distance, screen brightness, and room illumination showed statistically significant difference between the two groups (p < 0.0001).
Ranju Kharel Sitaula et al (2018) conducted a study A descriptive cross-sectional survey on Knowledge, attitudes and practice of Computer Vision Syndrome among medical students
and its impact on ocular morbidity among 1st- 4th-year MBBS students of the Institute of Medicine and 80 students underwent detailed ocular evaluation. Among 80 medical students randomly selected for detail eye examinations (63.7% male;36.2% female), the prevalence of Computer vision syndrome was 71.6%. The commonest ocular complaint was a headache (50%) and dry eyes (45%). Myopia was the commonest refractive error (31.2%) and the orthoptic problem was prevalent among 17.5% students.
S. Ardalan Cardoso et al (2018) conducted a study Prevalence rate of neck, shoulder and lower back pain in association with age, body mass index and gender among Malaysian office workers. They are 752 subjects (478 women and 274 men) were randomly selected from the Malaysian office workers population of 10,000 individuals. All participants completed the Cornell Musculoskeletal Discomfort Questionnaire and the study result shows that a significant association between pain severity in gender and right (p = 0.046) and left (p = 0.041) sides of the shoulders. There was also a significant association between BMI and severity of pain in the lower back area (p = 0.047). It was revealed that total pain score in the shoulders was significantly associated with age (p = 0.041).
Sultan H. Al Rashidi et al (2017) conducted a study on Computer vision syndrome prevalence, knowledge and associated factors among Saudi Arabia University Students. A total of 634 students with a mean age of 21. 40, Std 1.997 and Range 7 (18-25) were included as study subjects with a male predominance (77.28%). Of the total patients, majority (459, 72%) presented with acute symptoms while remaining had chronic problems. A clear-cut majority was carrying the symptoms for <5 days and >1 month. The statistical analysis revealed serious symptoms in the majority of study subjects especially those who are permanent users of a computer for long hours.
N. Assefa et al (2017) conducted a study on Prevalence and associated factors of computer vision syndrome among bank workers in Gondar City, northwest Ethiopia. A cross-sectional institution-based study was conducted. Among the total 304 computer-using bank workers, the prevalence of CVS was 73% (95% confidence interval [CI]=68.04, 78.02). Blurred vision (42.4%), headache (23.0%) and redness (23.0%) were the most experienced symptoms.
Inappropriate sitting position was 2.3 times (adjusted odds ratio [AOR]=2.33; 95% CI=1.27,
4.28) more likely to be associated with CVS when compared with appropriate sitting position.
Those working on the computer for more than 20 minutes without break were nearly 2 times (AOR=1.93; 95% CI=1.11, 3.35) more likely to have suffered from CVS when compared with those taking break within 20 minutes, and those wearing eye glasses were 3 times (AOR=3.19;
95% CI=1.07, 9.51) more likely to suffer from CVS when compared with those not wearing glasses.
Eduardo C Sa et al (2017) conducted a study on Computer vision syndrome and visual function in computer user workers in saopaulo: prevalence and associated factors. A quantitative cross-sectional observational study was carried out between 2014 and 2015, in which the workers underwent a clinical ophthalmologic examination and answered a questionnaire. The result was the most frequent symptoms were ‘tiredness at work’ (47.9%), ‘weight in the eye at work’ (38.3%) and ‘tiredness at home’ (36.3%). It was found an association between age (OR 0.188; 95% CI: −0.276 to −0.161) and effort at work (OR 0.656; CI −0.928 to −0.383) with visual function. In the work effort, the items that appeared as the main sources of stress were:
‘interruptions at work’ (3.7%),’overtime work’ (3.6%) and increased demand (3.6%).
C M Bogdănici et al (2016), A prospective observational study on 60 people who were divided into two groups: Group 1 – 30 middle school pupils with a mean age of 11.9 ± 1.86 and Group 2 – 30 patients evaluated in the Ophthalmology Clinic, “Sf. Spiridon” Hospital, Iași, with a mean age of 21.36 ± 7.16 years. A questionnaire was also distributed, which contained 8 questions that highlighted the gadget’s impact on the eyesight. A small amount of refractive errors (especially myopic shift) was objectively recorded by various studies on near work. Dry eye syndrome could also be identified, and an improvement of visual comfort could be observed after the instillation of artificial tears drops. Computer Vision Syndrome is still under-diagnosed, and people should be made aware of the bad effects the prolonged use of gadgets has on eyesight.
P. Ranasinghe et al (2016) conducted a study on Computer vision syndrome among computer office workers in a developing country: an evaluation of prevalence and risk factors.
Sample size was 2210 (response rate—88.4 %). Mean age was 30.8 ± 8.1 years and 50.8 % of the sample were males. The 1-year prevalence of CVS in the study population was 67.4 %.
Female gender (OR: 1.28), duration of occupation (OR: 1.07), daily computer usage (1.10), pre-
existing eye disease (OR: 4.49), not using a VDT filter (OR: 1.02), use of contact lenses (OR:
3.21) and ergonomics practices knowledge (OR: 1.24) all were associated with significantly presence of CVS. The duration of occupation (OR: 1.04) and presence of pre-existing eye disease (OR: 1.54) were significantly associated with the presence of ‘severe CVS’.
JanFrölich et al (2016) conducted a study on Computer game misuse and addiction of adolescents in a clinically referred study sample. They were 183 patients from a child and adolescent psychiatric clinic were assessed for computer game misuse or addiction using the CSV-S scale in order to distinguish between regular and excessive computer gaming. This study shows that the patients' group with problematic computer gaming especially male patients with the highest addiction score spent significantly more time on computer gaming and presented more school performance problems as well as other comorbidities. Excessive gaming correlated significantly with conduct and emotional problems. No specific psychiatric disorders correlated to computer game misuse or addiction.
Thomas J. Albin (2015) conducted a study on Computer Ergonomics: The State of the Art, Symptoms reported by computer users are classified into internal ocular symptoms (strain and ache), external ocular symptoms (dryness, irritation, burning), visual symptoms (blur, double vision) and musculoskeletal symptoms (neck and shoulder pain). The major factors associated with CVS are either environmental (improper lighting, display position and viewing distance) and/or dependent on the user’s visual abilities.
2.1.4. BENEFITS OF TEACHING PROGRAMME REGARDING PREVENTION OF HEALTH HAZARDS OF PROLONGED COMPUTER USAGE.
Pinnita Prabhasawat et al (2019) conducted a crossover study on Tear film change and ocular symptoms after reading printed book and electronic book among 30 healthy volunteers, in that some of whom read an e-book and others a printed book for 20 minutes and then switched the following week. Questionnaires about seven ocular symptoms were evaluated before and after reading by both reading methods and the study was concluded that Reading an e-book affected tear film instability and significantly increased burning sensation and tearing to a larger extend than reading a printed book.
Galit Hirsh-Yechezkel et al (2019) conducted a study on Mobile Phone-Use Habits among Adolescents. The vast majority (96.1 percent) used the mobile phone for voice calls daily. Girls were heavier users than boys, and ninth graders were heavier users than seventh graders. Among students attending religious schools, the rate of heavy users was lower than among those attending secular schools. About half of the students did not use hands-free devices at least half of the time. Leisure activities of the samples were significantly associated with mobile phone use. This study demonstrates that several variables, including socio demographics and leisure activities, may predict heavy mobile phone use among teenagers.
Mahasweta et al (2018) conducted a study on Screen-based media use and screen time assessment among adolescents in New Delhi, India. A community-based cross-sectional study was conducted in an Urban Resettlement Colony, New Delhi. The study included 550 adolescents between the age group of 10 to 19 years were selected for this study. About 98% of the adolescents used SBM. Television formed the maximum used media (96.5%). The mean (standard deviation) of the screen time was found to be 3.8 (2.77) h/day. Out of the total screen time, time contributed by television is 2.8 h/day followed by other SBM. About 68% of adolescents reported having screen time more than the recommended (>2 h). Significant association was observed between screen time and watching television while eating.
Fong-Ching Chang et al (2018) conducted a study on computer/Mobile Device Screen Time of Children and Their Eye Care Behavior: Data were obtained from a sample of 2,454 child- parent from 30 primary schools in Taipei city and New Taipei city, Taiwan. Children who reported lower academic performance, who were from non-intact families, reported lower levels of risk perception of mobile device use, had parents who spent more time using computers and mobile devices, and had lower levels of parental mediation were more likely to spend more time using computers and mobile devices; whereas children who reported higher academic performance, higher levels of risk perception, and higher levels of parental mediation were more likely to engage in higher levels of eye care behavior. This study revealed that risk perception by children and parental practices are associated with the amount of screen time that children regularly engage in and their level of eye care behavior.
Yumei Zheng et al (2016) conducted a study on Internet Use and Its Impact on Individual Physical Health This paper aims to identify the most common physical complaints associated
with Internet use, and further investigate the association between the frequency of Internet use and individual physical health.513 participants completed the questionnaires by online or offline manner, which covers demographic questions and questions concerning Internet use and physical complaints. The most common complaints were involving dry eyes, decreased vision, and cervical pain. The positive pearson correlation coefficient were found between the level of physical complaints and the frequency of Internet use, place of residence and education.
Especially, the higher amount of time for the Internet use is strongly associated with a higher level of physical complaints.
K. Kawabe et al (2016) conducted a study on Internet addiction: Prevalence and relation with mental states among adolescents. Junior high school students (aged 12–15 years) were assessed. Based on total IAT scores, 2.0% (male, 2.1%; female, 1.9%) and 21.7% (male, 19.8%;
female, 23.6%) of the total 853 participants (response rate, 97.6%) were classified as addicted and possibly addicted, respectively. Total GHQ scores were significantly higher in the addicted (12.9 ± 7.4) and possibly addicted groups (8.8 ± 6.0) than in the non‐addicted group (4.3 ± 4.6; P
< 0.001, both groups). A comparison of the percentage of students in the pathological range of GHQ scores revealed significantly higher scores in the possibly addicted group than in the non‐
addicted group. Further, accessibility to smartphones was significantly associated with Internet addiction.
Kudryavtsev et al (2016) conducted a study influence of studying in higher educational establishment on students’ harmful computer habits. In the research 1st-3rd year students (803 boys and 596 girls) participated. All they specialized in discipline “physical culture The results shows that in average students have 2 computer habits everyone. Student, who has these habits, spends more than 4 hours a day for them. 33% of 1st year boys and 16% of 1st year girls spend more than 2 hours a day for computer games. 15-20 % of boys and 25-30% of year girls waste more than 4 hours a day in internet. 10-15% of boys spend more than 4 hours a day for computer games. It is very probable that these students already have computer games’ addiction.
RahulBhargava et al (2015) conducted a study on Oral omega-3 fatty acids treatment in computer vision syndrome related dry eye. 478 symptomatic patients using computers for more than 3 h per day for minimum 1 year were randomized into two groups: 220 patients received
two capsules of omega-3 fatty acids each containing 180 mg eicosapentaenoic acid (EPA) and 120 mg docosahexaenoic acid (DHA) daily (O3FA group) and 236 patients received two capsules of a placebo containing olive oil daily for 3 months (placebo group). The primary outcome measure was improvement in dry eye symptoms and secondary outcome measures were improvement in Nelson grade and an increase in Schirmer and TBUT scores at 3 months.
K. W. Müller et al (2015) conducted a study on Regular gaming behavior and internet gaming disorder in adolescents: results from a cross-national representative survey of prevalence, predictors, and psychopathological correlates. 1.6 % of the adolescents meet full criteria for IGD, with further 5.1 % being at risk for IGD by fulfilling up to four criteria. The prevalence rates are slightly varying across the participating countries. IGD is closely associated with psychopathological symptoms, especially concerning aggressive and rule-breaking behavior and social problems. This survey demonstrated that IGD is a frequently occurring phenomenon among adolescents and is related to psychosocial problems. The need for youth-specific
prevention and treatment programmes become eviden
CHAPTER-III
RESEARCH METHODOLOGY
CHAPTER –III
RESEARCH METHODOLOGY
This chapter explains the methodology in detail. It includes research design, setting of the study, sampling technique, tools, pilot study, data collection process and plan for the data analysis. The study was conducted to assess the effectiveness of structure teaching programme on knowledge regarding prevention of computer vision syndrome among higher secondary students at selected school, Chennai
3.1. RESEARCH APPROACH
The research approach was adopted for this study is a quantitative approach.
3.2. RESEARCH DESIGN
The research design selected in this study is Pre experimental one group pre test and post test research design.
DIAGRAMMATICAL REPRESENTATION OF RESEARCH DESIGN
Group Pre-test STP Post-test
Higher secondary school students
01 X 02
01 - Assessment of pre-test level of knowledge of group of study participants.
X – Administration of structured teaching programme on prevention of computer vision syndrome among selected higher secondary students for 30 – 45 minutes
02 – Assessment of post- test level of knowledge of same group of study participants.
3.3 SETTING OF THE STUDY
The study was conducted in the Chennai Higher Secondary School, Appaswamy lane Tondiarpet, Chennai.
3.4. DURATION OF THE STUDY
The study was conducted for a period of four weeks from 02.02.19 to 04.03.19
3.5 STUDY POPULATION 3.5.1 Target population
It comprises of school students who are studying in Chennai Higher Secondary School, Tondiarpet, Chennai.
3.5.2 Accessible population
School students of 11th standard those who are studying in computer science group at selected Chennai Higher Secondary School, Tondiarpet, Chennai.
3.6 SAMPLE
In this study, higher secondary school students who met the inclusion criteria were selected as samples.
3.7 SAMPLE SIZE
The sample size was 60 students studying in 11th standard in Chennai higher secondary school, Chennai.
3.7.1 Inclusion Criteria
Students of 11th standard those who are belongs to computer science group.
The students those who are willing to participate.
The students those who are able to understand Tamil and English.
3.7.2 Exclusion Criteria
The other class students those who are studying in selected Government school, Chennai
The absentees at the time of data collection 3.8 SAMPLING TECHNIQUE
In this study Non Probability Purposive sampling Technique was used to select the subjects.
3.9 RESEARCH VARIABLES OF THE STUDY 3.9.1 Independent Variable
In the present study the independent variable is structured teaching programme on prevention of computer vision syndrome given by the investigator.
3.9.2 Dependent Variable
In the present study, knowledge of students regarding prevention of computer vision syndrome is the dependent variable which is assessed using the pre test and post test scores.
3.9.3 Demographic variable
It includes age, gender, type of family, education, occupation and income of parents, hobby, duration of computer use per day and reason for computer use.
3.10 DEVELOPMENT AND DESCRIPTION OF THE TOOL
Data collection tools are the procedures or instruments used by the researcher to observe the key variables in the research problem
3.10.1 Development of the tool
Appropriate structured questionnaire has been developed after extensive review of literature and obtained expert opinion, content validity from medical, nursing and statistical experts. Construction of the tool, pre testing of the tool, reliability of the tool was ascertained by test-retest method.
3.10.2 Description of tool
The tool for data collection consists of 2 sections Section - I
It consists of demographic details of the school students which comprises of the items such as age, gender, type of family, education, occupation and income of parents, hobby, duration of computer use per day and reason for computer use.
Section - II
It consists of 20 structured multiple choice questions with three options. The concept included for developing the tools which includes 3 questions related to basic knowledge regarding computer vision syndrome, 6 questions related to causes and symptoms, 8 questions related to preventive measures and 3 questions related to eye exercises.