A Descriptive Study to Assess Screen Viewing and Sleeping Hours among High and Low Achievers School Children (From Standard 3 – Standard 7) In Selected Schools at Mangalore

Ms. Teena Anu Tenson¹, Linson C.C², Mrs. Thereza Mathias³

¹MSc Nursing, Laxmi Memorial College of Nursing, AJ. Towers, Balmatta, Mangalore- 575002

²Associate Professor, Department of Psychiatric Nursing, Laxmi Memorial College of Nursing,

AJ.Towers, Balmatta, Mangalore- 575002

³Professor and HOD Department of Psychiatric Nursing, Laxmi Memorial College of Nursing,

AJ.Towers, Balmatta, Mangalore- 575002

*Corresponding Author Email: teenatenson56@gmail.com

ABSTRACT:

Our young children live in this world of interactive media. They are completely at ease with digital devices and they know how to use them. These devices help children in many ways too. Playing games increases the hand – eye co-ordination of the children and develops skills like problem solving, analytical estimation and quick decision making. Media affects the children in a negative way too. There are many controversies in the perception of media by children. The children spent most of their leisure time by watching movies, playing video or computer games or spending time on the internet. More than 50 years of media research and thousands of media effects shows that children’s aggressive behaviour, academic performances, obesity, sleeping disorders and sleep disturbances are directly linked to the injudicious use of media1.

Aim

The aim of the study is to assess screen viewing and sleeping hours among high and low achievers school children (from standard 3 – standard 7) in selected schools at Mangalore

Method

The research approach used for the study was descriptive research approach. Stratified random sampling technique was used to draw 100 school children. Data was collected by administering a structured rating scale on screen viewing and sleeping hours. The collected data was analyzed by using descriptive and inferential statistics.

Results

The findings of the study highlights that the calculated correlation coefficient of high achievers screen viewing and sleeping hours was -0.071and for low achievers it was 0.093.Chi-square test was used to find the significant association of performance of the students with selected demographic variables. There was a significant association of high achievers age, class, and study hours with performance of the school children and in low achievers, significant association of age and class with performance of the school children. But there was a no significant association of sleeping hours of high and low achievers with their demographic variables.

Interpretation and conclusion

The findings of the study concluded that there is a relationship between school children’s screen viewing and sleeping hours with academic performance. So giving time limitations for screen viewing would help to reduce sleep disturbances and improve academic performance of school children.

KEY WORDS: High achievers, Low achievers, Screen viewing, sleeping hours.

INTRODUCTION:

Mass media is a double – edged sword which has got both positive and negative influence on human beings. Impact of mass media at the present century is more powerful than ever.¹ Today’s children are living in a rapidly changing digital age that is far different from that of their parents and grandparents. When used wisely, technology and media can support learning and relationships. Every time a new media has been introduced, the primary concern of the society is how it affects children.² The ever-changing digital age provides guidance for early childhood educators on how technology and interactive media help to develop young learner’s cognitive, social, emotional, physical, and linguistic development. A broad range of digital devices such as computers, television, DVD, electronic toys games, e-book readers are always used by children. With new technology, new problems also arise. Students may be physically present in the classroom; their mind may be wandering around the entertainment provided by media.³

The Kaiser Family Foundation survey reveals that 99% of families own televisions, 97% own video players, 80% own video game systems, 86% own a computer, 82% have cable or satellite TV, 74% have internet access. An average household has 2.9 video players, 3.5 TVs, and 1.5 computers. The report says that children aged eight and above spent an average of 6.43 hours with media each day.² Another report by De Haan and Huysman in 2004 says that the only other activity that children spend more time other than media is sleeping. Nearly 90% of the children aged between 8- 18 have internet access at home, and one third has it in their bedroom. Half of young people surveyed say that they have a video game player in their room.⁴ Sleep disturbances are directly associated with the excessive use of many different forms of media now present in the bedroom. Sleep deprivation, has been associated with increased fatigue, and poor school performance. Children who spent less time on entertainment media scored higher on their perception of scholastic competence than the children who spent more time.⁵

A study was conducted to investigate the effects of television viewing and playing computer games on sleep patterns and memory of school children. Eleven school going children participated in the study. Children were exposed to the world of television and computer games. In the same night, tests were conducted to measure the sleep patterns and memory test before media stimulation and after the subsequent sleeping period. The results showed that computer game playing resulted in reduced amounts of sleep and significant declines in verbal memory performance. Television viewing reduced sleep efficiency significantly ⁶.

OBJECTIVES OF THE STUDY:

1. To assess the screen viewing habits among high and low achievers school children.

2. To assess the sleeping hours of high and low achievers school children.

3. To find relationship of screen viewing and sleeping habits of school children.

4. To find and an association of sleep habits with selected demographic variables.

Hypotheses

H1 - There will be significant relationship between screen viewing and sleeping hours with performance of students.

H2 - There will be significant association between performances of the students with selected demographic variables.

MATERIALS AND METHODS:

Research Approach

A non experimental descriptive approach was adopted to determine the screen viewing and sleeping hours among high and low achievers school children.

Research Design

Descriptive correlative research design is used in the present study.

Setting of the study

The study was conducted in selected schools at Mangalore.

Population

In this study, the population was school children from class three to class seven.

Sample

In this study, the sample is 100 school children from class 3- class 7 of selected schools at Mangalore.

Sampling technique

In this study, stratified random sampling technique was used with lottery method to select the sample from selected schools at Mangalore.

Inclusion criteria for sampling

Students

· Who are studying in class three to class seven

· Present during the period of data collection

Exclusion criteria for sampling

Students:

· Who are not willing to participate in the study

· Who are not present during data collection

Tool used

Section A: Demographic factors.

Section B: Rating scale to assess screen viewing habits.

Section c: Rating scale to assess sleeping hours.

RESULTS:

Section A: Description of demographic variables of the sample.

Table 1 shows that the highest percentage (60%) of both high and low achievers sample are in age group 8 – 10 and 40% of sample are in age group 11 -12.Majority (64%) of the sample are male and (36%) are female in high achievers group the least group (40%) are male and (60%) are female in low achievers group. All (100%) of the high and low achievers sample’s fathers are employed. Least (6%) of the high achievers sample’s mothers are employed and majority (94%) are unemployed. Least (10%) of the low achievers sample’s mothers are employed and majority (90%) are unemployed. All (100%) of high and low achievers sample has no failures in the previous classes. All (100%) of high and low achievers sample are doing homework daily.

Table 1: Frequency and percentage distribution of sample according to demographic variable

Sl. No.

Demographic variables

Frequency

Percentage

Frequency

Percentage

Age

a. 8-10

b. 11-12

c. > 12

60%

40%

60%

40%

Sex

a. Male

b. Female

64%

36%

40%

60%

Employed father

a. Yes

b. No

100%

Employed mother

a. Yes

b. No

94%

10%

90%

Failures

a. Yes

b. No

100%

Daily home work doing

a. Yes

b. No

100%

Leisure time activity?

a. Reading story books

b. Watching television

c. Outdoor play

38%

42%

20%

90%

10%

Late computer usage by family members

a. Yes

b. No

100%

94%

Bedroom television

a. Yes

b. No

100%

Study hrs/day

a. Less than hour

b. 1-2 hours

c. more than 2

70%

30%

100%

How often you play outdoor games?

a. Every day

b. Week ends

c. Sometimes

d. Not at all

96%

100%

Least (38%) of high achievers sample’s favourite leisure time activity are reading books , (42% ) of high achievers likes to watch television and (20%) likes outdoor games.

Majority (90%) of low achievers sample likes to watch television and least (10%) of low achievers likes outdoor games. All ( 100%) of high achievers sample’s family members are not using TV or computer late in the night, where as in low achievers sample majority ( 94% ) of family members are not using during late night and least (6%) family members are using the TV or computer in the late night. All (100%) of high and low achievers sample’s television is not placed in bedroom. Majority (70%) of high achievers samples are studying 1- 2 hours every day and least (30%) high achiever samples are studying more than 2 hours per day, where as in low achievers samples all (100%) of low achievers samples are studying 1- 2 hours every day. Majority (96%) of high achievers samples are going for outdoor games sometimes, least (2%) samples are going for outdoor games every day and least (2%) samples are going for outdoor games only on week end days. All (100%) of low achievers samples are going for outdoor games sometimes only.

Section B: Description of screen viewing hours and sleeping hours among school Children

Figure 1: Pie diagram showing percentage distribution of screen viewing of high and low achievers school children.

Figure 1 shows that the level of screen viewing of all (100%) high achievers was mild and level of screen viewing of all (100%) low achievers was moderate.

Figure 2: Pie diagram showing percentage distribution of sleep disturbances of high and low achievers school children.

Figure 2 shows that the level of sleeping disturbances of all (100%) high achievers was mild. Level of sleeping disturbances of (84%) low achievers was moderate and (16%) was mild.

Table 2 shows that the correlation between screen viewing and sleeping hours of high and low achievers school children was tested by using Karl Pearson’s correlation coefficient. The calculated correlation coefficient for high achievers was -0.071. This shows that there is negative relationship between screen viewing and sleeping hours of high achievers school children The correlation coefficient between screen viewing and sleeping hours of low achievers school children was 0.093. So H₀₁ i.e. there is no significant relationship between screen viewing and sleeping hours with performance of students is rejected.

Section C: Analysis of correlation between screen viewing hours and sleeping hours with performance of students.

Table 2: Correlation between screen viewing and sleeping hours among high and low achievers

N=100

Group	Areas	Obtained range	Mean	Median	S.D	Correlation	p value
High achievers	Screen viewing	5 - 14	10.32	11	2.965	-0 .071	0.634
High achievers	Sleeping hours	4 - 12	7.188	7	1.818
Low achievers	Screen viewing	15-26	21.9	21	2.652	0 .093	0.519
Low achievers	Sleeping hours	12 - 20	14.96	15	1.714

Section D: Association of performance of the students with selected demographic variables.

Table 3: Association between screen viewing of high and low achievers school children with selected demographic variables.

N=100

Demographic variable	High achievers				Low achievers
Demographic variable	χ2	d.f	Table value	inference	χ2	d.f	Table value	inference
Age	14.0	1	3.841	Significant	10.470	1	3.841	Significant
sex	0.11	1	3.841	Not Significant	5.860	1	3.841	Significant
With Parents	3.54	1	3.841	Not Significant	0	1	3.841	Not Significant
Bedroom television	0	1	3.841	Not Significant	0	1	3.841	Not Significant
Study hrs/day	7.68	2	5.991	Significant	0	2	5.991	Not Significant

Table 3 shows there is a significant association of high achievers age and study hours with performance of the school children and also there was a significant association of low achievers age with performance of the school children as the calculated value was more than the table value at 0.05 level of significance. So the null hypothesis H₀₂ was rejected for these variables. However, no significant association was found between high achievers sex, watching TV with parents or siblings, television in bedroom, study hours per day and also no significant association was found between low achievers sex, watching TV with parents , study hours per day .Hence the null hypothesis is accepted for these variables and research hypothesis is rejected at 0.05 level of significance.

Table 4: Association between sleeping hours of high and low achievers school children with selected demographic variables

N=100

Demographic variable	High achievers				Low achievers
Demographic variable	χ2	d.f	Table value	inference	χ2	d.f	Table value	inference
Age	0.004	1	3.841	Not significant	0.238	1	3.841	Not Significant
sex	2.009	1	3.841	Not significant	0.015	1	3.841	Not Significant
With parents	3.54	1	3.841	Not significant	0	1	3.841	Not Significant
Bedroom television	0	1	3.841	Not significant	0	1	3.841	Not Significant
Study hrs/day	0.548	2	5.991	Not significant	0	2	5.991	Not Significant

Table 4 shows there was a no significant association of high achievers and low achievers age, sex, Television in bedroom, watching TV with parents with performance of the school children. Hence the null hypothesis is accepted for these variables and research hypothesis is rejected at 0.05 level of significance.

DISCUSSION:

Discussion of demographic characteristics of the sample

In accordance with 100 samples, it is observed that:

The highest percentage (60%) of both high and low achievers sample are in age group is 8 – 10.Majority (64%) of the sample are male in high achievers group and (60%) are female in low achievers group. All (100%) of the high and low achievers sample’s fathers are employed. Majority (94%) of the high achievers and highest (90%) of the low achievers sample’s mothers are unemployed. All (100%) of high and low achievers sample has no failures in the previous classes and are doing homework daily. Highest (42%) of high achievers sample’s favourite leisure time activity is watching television and in low achievers majority (90%) likes to watch television. All ( 100%) of high achievers sample’s and majority ( 94% ) of low achievers sample’s family members are not using TV or computer late in the night. Majority ( 98%) of high achievers and in low achievers sample all ( 100% ) are watching TV with parents or siblings. All (100%) of high and low achievers sample’s television is not placed in bedroom. Majority (70%) of high achievers samples and all (100%) of low achievers are studying 1- 2 hours every day .All (100%) of high and low achievers samples are spending less than an hour for outdoor games. Majority (96%) of high achievers samples and all (100%) of low achievers samples are going for outdoor games sometimes only.

A survey was conducted to determine the amount of television viewing and computer use in urban school-aged Chinese children, and to examine their associations with sleep/wake patterns, duration of sleep, and sleep disorders. The sample comprised of 19,299 elementary-school children. The study findings revealed that 49.7% boys and 50.3% girls, with a mean age of 9.00 years, participated in the survey. A television or computer was present in the bedroom of 18.5% of Chinese school-aged children. Media presence in the bedroom and media use was positively correlated with later bedtimes, later awakening times, and a shorter duration of sleep during weekdays and weekends. Study shows that television viewing more than 2 hours per day on weekends, with a prevalence of 48.8%, was the predominant risk factor for all sleep disorders.⁷This study sample’s mean age is similar to the current study whereas the sex and media presence is contrasting to the current study.

Discussion of screen viewing hours and sleeping hours of school children

In the present study total sample size were 100 and in that 50 school children were under high achieves group and other 50 belongs to low achievers group. The mean obtained for high achievers screen viewing is (10.32), median (11) and standard deviation (2.965). Level of screen viewing was mild in high achievers. Low achievers group has a mean of (21.9), median (21) and standard deviation (2.652). Level of screen viewing was moderate in low achievers. The sleeping hours of high achievers has a mean of (7.188), median (7) and standard deviation (1.818) and the level of sleep disturbances were mild where as in low achievers the mean for sleeping hours was (14.96), median (15), standard deviation (1.714) and the level of sleep disturbances was moderate in low achievers.

A telephone survey administered to 1454 parents of children less than 11 years old to determine the media usage in children less than 11 years of age. Mean daily reported child media use was television (1.45 hours; SD, 1.5); videos (1.1 hours; SD, 1.30); and computer games (0.54 hours; SD, 0.96). Having a television in a child's bedroom was associated with increased hours of television (0.25 hours [0.07, 0.43]), video viewing (0.31 hours [0.16, 0.47]), and computer games (0.21hours [0.10, 0.32])⁸. The findings of this study are similar to the findings of the current study conducted by the investigator.

Discussion of findings of correlation between screen viewing hours and sleeping hours with performance of sample

The present study revealed that there was a significant correlation between screen viewing and sleeping hours. The calculated correlation coefficient between screen viewing and sleeping hours of high achievers was -0.071, i.e. negative correlation and p value was 0.634. The calculated correlation coefficient between screen viewing and sleeping hours of low achievers was 0.093, i.e. weak positive correlation and p value was 0.519.

Discussion of findings of association of performance of the students with selected demographic variables

In the current study the demographic characteristics such as age, sex, and study hours has a significant association with the performance and screen viewing of school children. There is no impact of demographic characteristics on the performance and sleeping hours of school children.

A study on Impact of television on children was carried out at Sir Padampat Mother & Child Health Institute, Jaipur. The aim was to study the effects of television viewing on a child’s general physical health, physical activities, and interest in study and school performance. 250 children of 3-10 years age groups were studied for a period of nine months Average duration of television exposure to an individual child was 18.5 hours per week in the study. Significant changes were observed in a child’s, physical activity, sleep pattern, interest in study and general physical health. In 30.4% cases decrease in physical activity was found, 18.4% children showed decreased interest in study, while 10% children showed decrease in school performance, and sleep pattern was disturbed in 24% children. The study concluded that impact of television is more on children’s physical activity, sleep hours; school performance.¹⁰This study shows that there is a significant association between screen viewing, sleep hours and performance of the school children, so these study findings are contrasting with the current study conducted by the investigator.

CONCLUSION:

The present study proved that there is a significant relationship between screen viewing and sleeping hours among high and low achievers school children. So by reducing the screen viewing time we can improve the academic performance as well as we can reduce the sleep disturbances. Thus steps can be taken to incorporate these and other measures in improving the academic performance of school children and further research can be conducted in the same.

REFERENCES:

1. Victor .C, and Strasburger. Children, Adolescent and the Media.1st ed. Saunders Publishers, Mexico 2012.

2. Kim Y. The impact of the internet on children’s daily lives: physical, social and psychological well-being. Available from: URL:http://www.science- direct.com.

3. Russo MF. Technology and Interactive Media as Tools in Early Childhood Programs Serving Children from Birth through Age. Journal of the American Academy of Paediatrics .Sep 8; 2009.

4. Jaswal S.Impact of media use on sleep patterns and sleep disorders, A Eurovision For parliament. Available from: URL:http://www.pubmed.com.

5. Sharif I, James. D. Association between television, movie and videogame Exposure and school Performance. Journal of the American academy of paediatrics. Oct 2; 2012.

6. Priebe G .The effects of television viewing and computer game consumption on sleep pattern and memory performance. Available from: URL: http://www.pubmed.com.

7. Li.S, Jin X. The impact of media use on sleep patterns and sleep disorders among - school aged children in China. Available from: URL://www.pubmed.com.

8. Dimitri.A, Beth E. Television, video and computer game usage in children. Journal of Paediatrics. Nov 145: 5; 2004: 652-56.

9. Priebe G .The effects of television viewing and computer game consumption on sleep pattern and memory performance. Available from: URL: http://www.pubmed.com

10. Gupta K, Acharya U. Impact of television on children. Available from: URL: http://www.pubmed.com.

Received on 05.06.2014 Modified on 10.07.2014

Asian J. Nur. Edu. & Research 4(3): July- Sept., 2014; Page 328-333