INTRODUCTION:

Computers are probably one of the biggest scientific inventions of the modern era, and since then they have become an integral part of our life. The increased usage of computers has lead to variety of ocular symptoms which includes eye strain, tired eyes, irritation, redness, blurred vision, and diplopia, collectively referred to as Computer Vision Syndrome.

It may have impact not only on visual comfort but also occupational productivity since between 64% and 90% of computer users either at near or when looking into the distance after prolonged computer use. Worldwide incidence is estimated to be 60million people who experience vision problem as result of computer use¹. Over 75% of young students in India and Andhra Pradesh are reportedly, face the computer vision syndrome. The national institute of occupational safety and Healthy (NIOSH) stated that nearly 88% of all computer professionals will develop computer vision at same time in their lives². The symptoms related to eye and musculoskeletal system which were reported are moderate headache (64%) bodily fatigue and tiredness (44%) mild dry eye (64%) neck and shoulder pain (69%) double vision (47%) “Halos” appearing around the object (67%) and need to interrupt work frequently to rest eye (47%). Also, few factors such as length of use, type of device, duration of use (hours/day) and frequency of eye blinking posses the remarkable impact on incidence of computer vision syndrome. Among engineering students, the prevalence of CVS was found to be 81.9% (176/215) 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 reported symptoms of CVS were higher among engineering students compared with medical students³. In India, the current estimates indicate that about 85% of computer users suffer from vision syndrome. Nearly 60 million children connect to the internet each day either at home or at school. Also, 90% of workers who use computers for more than three hours daily, experience computer vision syndrome in some form or other. 95% of schools and 63% of all classrooms have had internet access. On a typical day, even children 2-5 years of age send an average of 27 minutes on a computer. Computer users are facing variety of ocular symptoms which include – tired eyes, irritation, redness, eye strain and double vision.

OBJECTIVES OF THE STUDY:

1. To assess the pre-test knowledge regarding computer vision syndrome among college students.

2. To assess the post-test knowledge regarding computer vision syndrome among college students.

3. To compare the pre-test and post-test knowledge regarding computer vision syndrome among college students.

4. To associate the selected demographic variables with the post-test knowledge regarding computer vision syndrome among college students.

ASSUMPTION:

1. The students of BCA may have more dependence on the computer.

2. Computer vision syndrome may be common among BCA students.

3. There may have adequate knowledge regarding computer vision syndrome among BCA students.

OPERATIONAL DEFINITION:

1. Assess:

Assessment is the process of gathering, verifying and communicating data about computer vision

2. Knowledge:

College students response regarding computer vision syndrome as assessed by a structured questionnaire.

3. Computer Vision Syndrome:

According to American Optometric Association, a complex of eye and vision problems related to the activities which stress the near vision and which are experienced in relation to or during the use of computer as assessed by structured questionnaire.

4. College Going Students:

BCA Students studying in Bhaskar degree college, Udhampur.

Delimitations:

1. This study was delimited to the college going BCA students at Bhaskar degree college, Udhampur.

2. This study was delimited to 100 samples.

Projected Outcomes:

· The study will help to assess the problems related to vision due to computer.

· The study will help to provide more awareness to the students regarding the problem that arise due to computer vision syndrome.

Research Approach:

The research approach for this study was quantitative approach.

Research Design:

The research design used for this study was pre-experimental research design.

Research Setting:

Thestudy was conducted in Bhaskar degree college, Udhampur.

Population:

Target Population:

The target population for the study was college going students.

Accessible Population:

The accessible population was the college going students at Bhaskar degree college, Udhampur.

Sample:

BCA students.

Sample Size:

100 college going students of BCA.

Sampling Technique:

In this study non probability sampling technique i.e. purposive sampling technique was used to select the sample.

Inclusion Criteria:

1. All college going students.

2. Available at the time of data collection.

3. The students who are able to understand English\Hindi.

Exclusion Criteria:

1. Students who are not willing to participate.

2. The students who are not available during the time of data collection.

Description of the Instrument:

In this study data collection was done by using self- structured questionnaire. The instrument was developed by the investigator with the help of various resources and review of literature. The questionnaire will assess the knowledge regarding computer vision syndrome.

The Tools Consists of Two Parts:

PART A: It contains the variables used to collect the socio demographic profile of all subjects. The demographic variables such as age, sex, area, use of frequent computer digital screen, hours spending on digital screen, spendingof hours on screen in dark rooms, wearing of corrective glasses while working at the computer.

PART B: It includes knowledge questionnaire (Multiple choice questions) regarding computer vision syndrome.

Data Collection Procedure:

The data was collected in the month of February 2019. Purpose of the study was explained to the college authorities. The college students were approached by the investigator. An initial rapport was established with college students and details of study were explained to them. A convenient time and date was fixed for data collection. Purposive sampling technique was used for selecting samples to assess the effectiveness of structured teaching program regarding computer vision syndrome. 13 structured questionnaire were made and used for pre-test to determine the knowledge regarding computer vision syndrome among 100 college students in bhaskar degree college students, Udhampur. The time limit was 30 minutes. The post-test was administered to the same group after 1 week of planned teaching program. All the college students were very cooperative.

Data Analysis and Interpretation:

The findings of the study were represented in this chapter under the following headings:

1. Distribution of Bhaskar degreecollege students based on the demographic variables.

2. Distribution of pretest and post-test knowledge regarding computer vision syndrome among Bhaskar degree college students.

3. Comparison between pretest and post-test level of knowledge among Bhaskar degree college students.

4. Association of post-test level of knowledge with the selected demographic variables among Bhaskar degree college students.

DISCUSSION:

The current study was first to assess the level of knowledge about Computer Vision syndrome. We conducted our study on college students which reflects little knowledge about computer vision syndrome. The sample size was 100. We used the structured questionnaire to find out the knowledge about computer vision syndrome. The response was analyzed through descriptive (mean, standard deviation) and inferential statistics (t- test and chi square). Discussion on the findings was arranged in the order of the objective of the stud The first objective of study was to assess the pre-test level of knowledge regarding Computer vision syndrome among college students.

The pre-test level of knowledge regarding Computer vision syndrome among college students were 36(36%) of students had inadequate knowledge, 57(57%) students had moderate knowledge, and 7(7%) had adequate knowledge. The group of investigator felt that the existing knowledge about computer vision syndrome was poor.

This study was consistent with the study conducted by Bhanderi in 2008 on knowledge on computer vision syndrome among universities students. The study results revealed that most of students have poor knowledge on computer vision syndrome. 40% of students had inadequate knowledge, 50% had moderate knowledge and 10% had inadequate knowledge.

The second objective of study was to assess the post -test level of knowledge regarding computer vision syndrome among college students.

The post-test level of knowledge regarding computer vision syndrome among college students were 46(46%) of students have moderate knowledge, 54(54%) of students have adequate knowledge whereas no one of them had inadequate knowledge. The group of investigator felt that the existing knowledge about computer vision syndrome in post-test was appreciable. This study was consistent with the study conducted by Parveen Parmar in 2009 from five universities in Malaysia. The study results revealed that total of 100 students, aged between 18 and 25 years have appreciable knowledge on computer vision syndrome. 40% of students had inadequate knowledge and 60% of students had adequate knowledge.

The third objective of the study was to compare the pre-test, post-test level of knowledge regarding computer vision syndrome among college students. The pre-test level of knowledge regarding computer vision syndrome among college students were 36(36%) of students had inadequate knowledge, 57(57%) students had moderate knowledge and 7(7%) of students had adequate knowledge. The post-test level of knowledge regarding Computer vision syndrome among college students were 46(46%) of students had moderate knowledge, 54(54%) of students had adequate knowledge whereas no one of them had inadequate knowledge. This shows that students have less knowledge in pre-test then that in post-test. The “t” test value 5.41(S) found to be highly significant at the level of p<0.05. It is inferred that there is improvement in the level of knowledge among students of bhaskar Degree College after planned teaching program. These findings was consistent with the study conducted by Akshitarpana, Shirodhara and an ayurvedic compound in childhood computer vision syndrome in June 2011 reported that the students have less knowledge in pre test then that in post test. The t-test value 5.3 (S) implies that the difference in the pre test and post test knowledge score found highly significant (P<0.05).

The fourth objective of the study was to associate the selected demographic variables with the post-test level of knowledge regarding computer vision syndrome.Association between the post-test level of knowledge with demographic variables such as age, sex, area, frequent computer digital screen use, hours spend on digital screen, hours spend on screen in dark room and wear corrective glasses while working at the computer. According to the age, the chi square value was 13.5 (p<0.05) which was significant. Age has association with level of knowledge. According to the sex, the chi square value was 0.01 (p>0.05) which was not significant. Sex has no association with level of knowledge. According to area, the chi square value was 0.67 (p>0.05) which was not significant. Area has no association with level of knowledge. According to digital screen used, the chi square value was 14.55 (p<0.05) which was significant. Digital screen used has association with level of knowledge. According to hours spend on digital screen, the chi square value was 7.3 (p>0.05) which was not significant. Hours spend on digital screen has no association with level of knowledge. According to hours spend on screen in dark room, the chi square value was 3.22 (p>0.05) which was not significant. Hours spend on screen in dark room has no association with level of knowledge. According to wear of corrective glasses while working at the computer, the chi square value was 9.99 (p>0.05) which was not significant. Wear corrective glasses has no association with level of knowledge.

SUMMARY OF THE STUDY FINDINGS:

In study findings, more than half of the respondents (61%) fell under the age group of 18 years-20 years, more than half of students (52%) were females, more than half of students (55%) were from urban area. Regarding frequent computer vision digital screen use, half of students (51%) were use Android mobile. Regarding hours spend on digital screen, 44% of students were spend 1-2 hour. Regarding hours spend on screen in dark rooms, 40% of students were spend <1 hour. More than half of students (57%) were not wear corrective glasses while working at the computer.

The present study confirms that the overall knowledge regarding computer vision syndrome in pretest was inadequate. This may be due to lack of education, unawareness, lack of exposure to health education program regarding computer vision syndrome.

There was a considerable improvement of knowledge after the planned teaching program on computer vision syndrome. The post test results showed that more than half of students 54% had adequate knowledge, 46% had moderate knowledge and no one had inadequate knowledge.

The “t” test score between the pretest and post-test knowledge regarding computer vision syndrome among college students was 5.41 (significant at the level of 0.05). This suggested that the planned teaching program was effective and it increased the knowledge of Bhaskar degree college students on computer vision syndrome. According to the age, the chi square value was 13.5 (p<0.05) which was significant. Age has association with level of knowledge. According to digital screen used, the chi square value was 14.55 (p<0.05) which was significant. Digital screen used has association with level of knowledge.

CONCLUSION:

The main study concluded that the existing level of knowledge regarding computer vision syndrome was inadequate. So the researcher prepared the planned teaching program effectively with power point presentation and videos. The planned teaching program created the influence about the computer vision syndrome among Bhaskar degree college students. Finally the researcher believed that those who have taken part in research study had created the awareness regarding computer vision syndrome.

NURSING IMPLICATIONS:

The findings of study have several implications in following fields. It can be discussed on four areas namely nursing practice, nursing administration, nursing education and nursing research.

Nursing practice:

1. The study findings will encourage the nurse to create awareness among students.

2. Nurse should prepare a booklet, pamphlet, charts, posters on prevention (looking away from the computer, distance for atleast 20 seconds every 20 minutes, reducing glare from nearby light sources, using a screen glare filter, etc.) of computer vision syndrome.

Nursing administration:

1. The administration shall allocate separate budget for organizing screening camps for rulingout computer vision syndrome.

2. The administration shall maintain records related to computer visionsyndrome.

Nursing Education:

1. The findings will help the nursing student for motivating the students for eyescreening and organizing camps.

2. The findings of the study will also help the nursing students to gain knowledge about computer visionsyndrome.

Nursing Research:

1. The information contained in the present study can be valuable source of data for future researchers.

2. Evidence based practice can be done in clinical as well as educational level.

RECOMMENDATIONS:

Keeping in view the findings of the present study, the following recommendations have been made

1. A similar study can be replicated on large sample size, in different settings, with in different population as longitudinal study.

2. A descriptive study can be conducted for assessing the knowledge regarding computer vision syndrome.

3. A longitudinal study can be conducted to assess the knowledge and attitude regarding computer vision syndrome.

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Received on 20.04.2022 Modified on 09.05.2022

Int. J. of Advances in Nur. Management. 2022; 10(3):177-181.

DOI: 10.52711/2454-2652.2022.00045