Behaviors and Effects of Smartphone Usage among High School Students, Nonthaburi Province

Main Article Content

ศักดิกร สุวรรณเจริญ
สุพัตรา ธรรมาอินทร์
สุวัฒนา เกิดม่วง
อังค์ริสา พินิจจันทร์
พรเลิศ ชุมชัย

Abstract

Smartphone usage behavior of teenagers has both positive and negative effects on them, their families and society. The objectives this descriptive correlational research study aimed to study the behaviors and effects of smartphone usage and examine the relationship between smartphone usage behaviors and the impact of using the smartphone among high school students, Nonthaburi province. A total of 291 high school students in the selected school, Nonthaburi province, were selected by simple random sampling. The data was collected using self-administrated questionnaires. The data were analyzed using descriptive statistics and Pearson’s Correlation Coefficient. The results showed that the sample was female (79.70%). The average age was 16.80 years (SD=.97). The average smartphone service charge per month was 394.60 baht (SD=243.32). The time of playing smart phone was after school (81.80%), and most of them played at home, 97.30%. The sample had a behavior of using smart phones at a medium to high level of 98.60 percent. The impact of the use of smart phones was at low to moderate level among 268 students (92.10%). Classification of impacts on each aspect showed moderate level on health and psychological impacts. The relationship between smartphone usage behaviors and the effects of using the smartphone among high school students was statistically significant (p<.01). The results of the study can be used as a guideline for related parties to formulate policies or methods to adjust behaviors that are problematic in the use of smartphones and to prevent further long-term problems.

Downloads

Download data is not yet available.

Article Details

How to Cite
1.
สุวรรณเจริญศ, ธรรมาอินทร์ส, เกิดม่วงส, พินิจจันทร์อ, ชุมชัยพ. Behaviors and Effects of Smartphone Usage among High School Students, Nonthaburi Province. NJPH (วารสาร พ.ส.) [Internet]. 2019Dec.20 [cited 2020Aug.12];29(3):107-1. Available from: https://he02.tci-thaijo.org/index.php/tnaph/article/view/230788
Section
บทความวิจัย

References

1. Wonganantnont P. Excessive internet usage behavioral in adolescents. Journal of the Royal Thai Army Nurses 2014;15(2):173-8. (in Thai).

2. Wanchaitanawong W, Choopun K. A survey of internet utilization and impacts of internet utilization on students of Boromarajonnani College of Nursing, Chiang Mai. Journal of Nursing and Education 2017;7(3):124-32. (in Thai).

3. DQ Institute. Outsmart the cyber-pandemic: Empower every child with digital intelligence by 2020 [internet]. 2018 [cited 2019 Aug 30]. Available from https://www.dqinstitute.org/wp-content/uploads/2018/08/2018-DQ-Impact-Report.pdf

4. Kitisri C, Nokham R, Phetcharat K. A smartphone using behavior and health status perception of nursing students. Community Health Development Quarterly Khon Kaen University 2017;5(1):19-34.(in Thai)

5. Akinbinu TR, Mashalla YJ. Impact of computer technology on health: Computer Vision Syndrome (CVS). Med Pract Rev2014;5(3):20-30.

6. Lee KE, Kim SH, Ha TY, Yoo YM, Han JJ, Jung JH, Jang JY. Dependency on smartphone use and its association with anxiety in Korea. Public Health Rep 2016;131(3):411-9.

7. Saartsri S, Jitaram P, Kitsanapun A, Tanawongphokin T. Smartphone usage and sleep quality among students at Sirindhorn College of Public Health, Suphanburi. Journal of Faculty of Physical Education 2017;20 (1):70-80. (in Thai).

8. Demirci K, Akgönül M, Akpinar A. Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. J Behav Addict 2015;4(2):85–92.

9. Suknonthamalee N, Kerdmuang S, Suwancharoen S, Chatrung C, Tangwongkit T. Game addiction and factors related to health behaviors among junior high school students in the selected school, Nonthaburi province. Community Health Development Quarterly Khon Kaen University 2019; 7(1): 69-87. (in Thai).

10. Krejcie RV, Morgan DW. Determining sample size for research activities. Edu Psychol Meas 1970;3:607-10.

11. Chaimay B. Sample size determination in descriptive study in public health. Thaksin J 2013;16(2):9-18. (in Thai).

12. Best JW. Research in education. (3rd ed.). Englewood Cliffs, New Jersey: Prentice Hall, Inc. 1977.

13. World Medical Association. Declaration of Helsinki: ethical principles for medical research involving human subjects. Fortaleza Brazil;2013.

14. Cohen J. Statistical power analysis for the behavioral sciences. (2nd ed.). Hillsdale, New Jersey:Lawrence Erlbaum Associates, Inc.1988.

15. Kempanya P. Internet usage behavior of senior high school students in the Mueang Nakhon Phanom Municipality Area. Nakhon Phanom University Journal 2018; Special issue of the 25th Nursing Conference:120-4. (in Thai).

16. Chuemongkon W, Inthitanon T, Wangsate J. Impact of smartphone and tablet use on health and academic performance of pharmacy students at Srinakharinwirot University. Srinagarind Med J 2019;34(1):90-8. (in Thai).

17. Intolo P, Sirininlakul N, Saksanit N, Kongdontree P, Thuwatorn P. Pain and muscle activity of neck, shoulder, upper back and arm during smartphone use in women aged 18-25 years old. J Health Syst Res 2016;10:351-60.

18. Matar boumosleh J, Jaalouk D. Depression, anxiety, and smartphone addiction in university students-a cross sectional study. PLoS ONE 2017;12:e0182239.

19. Jun-up P. Behavior and aftermath of social media usage of senior high school students in Phitsanulok. Independent Study, Master of Education (M.Ed.) in Educational Communication and Technology. Pitsanulok: Naresuan University.2017. (in Thai).

20. Lampetch S. Behavior and impact of using social network of secondary school students in Nonthaburi province. Suthiparithat 2016;30(93):116-30. (in Thai).

21. Thongjuerpong P. Factors and effects of smart phone addiction to job performance momo-phobia and conflict with others. JISB 2016;2(3):40-54. (in Thai).

Most read articles by the same author(s)