Understanding the Relationship Between Mood Engagement via Social Media Among Youngsters

  • Latifah Abd Latib Senior Lecturer
  • Hema Subramaniam
  • Siti Khadijah Ramli
Keywords: Mental health, Mood engagement severity, Multi-age group, Social media usage, Youngsters

Abstract

Social media usage severity among different age groups of youngsters is essential. Youngsters can be in the range of 13-30 years old but since this is a larger population, we face difficulty in providing mental health awareness programs to them. Understanding the specific age group could solve this issue. So the study aims to investigate social media mood engagement among different age groups of youngsters., examining the relationship between youngsters' age and mood participation on social media, and investigating the relationship between social media usage severity and mood engagement level. A web-based cross-sectional survey was conducted among 386 youngsters between the ages of 13 and 29 years old, recruited from secondary school, university students, and recent graduates with early careers. The identified data were gathered, and saved online before being exported and analysed in IBM SPSS Statistics (v26). The analysis includes the participants' exploratory analysis, analysis of variance (ANOVA), and post hoc tests. The survey's Cronbach's alpha was 0.751. The test indicated that the mean score for secondary school students (M = 1.04 and SD = 0.313) was significantly different from university students (M = 1.23 and SD = 0.675) that are also differed significantly from fresh graduates with early careers (M = 2.09 and SD = 0.995). The university students did not manage to control their emotions by posting pictures of their emotions on social media while the fresh graduates with early careers expressed negative emotions through social media. This study helps to comprehend youngsters' concerns.

References

Akram, W., & Kumar, R. (2017). A Study on Positive and Negative Effects of Social Media on Society. International Journal of Computer Sciences and Engineering, 5(10), 351–354. https://doi.org/10.26438/ijcse/v5i10.351354
Biernesser, C., Sewall, C. J. R., Brent, D., Bear, T., Mair, C., & Trauth, J. (2020). Social media use and deliberate self-harm among youth: A systematized narrative review. In Children and Youth Services Review (Vol. 116). https://doi.org/10.1016/j.childyouth.2020.105054
Diener;, E., Emmons;, R. A., Larsen;, R. J., & Griffin;, S. (2020). The Satisfaction With Life Scale. The Routledge Companion to Performance Philosophy, 347–350. https://doi.org/10.4324/9781003035312-41
Eberhardt, W., Bruine de Bruin, W., & Strough, J. N. (2019). Age differences in financial decision making: The benefits of more experience and less negative emotions. Journal of Behavioral Decision Making, 32(1), 79–93. https://doi.org/10.1002/bdm.2097
Glenn D. Israel. (2003). Determination of sample size. Malaysian Journal of Medical Sciences, 10(2), 84–86.
Institute, N. H. and M. S. 2017: A. H. and N. S. (2018). NATIONAL HEALTH AND MORBIDITY SURVEY ( NHMS ) 2017 : Key Findings from the Adolescent Health and Nutrition Surveys. April.
Khan, A., Shahid, H. M., & Khan, A. (2018). Analysis of Mental State of Users Using Social Media to Predict Depression! A Survey. International Journal of Advanced Research in Computer Science. www.ijarcs.info
Littman-Ovadia, H., & Russo-Netzer, P. (2019). Prioritizing positivity across the adult lifespan: initial evidence for differential associations with positive and negative emotions. Quality of Life Research, 28(2), 411–420. https://doi.org/10.1007/s11136-018-2012-3
Malaysia, D. of S. (2022). Poket STATS ST1 2022.
Malaysian Communication and Multimedia Commission (MCMC). (2020). Internet users survey 2020: Infographic. Statistics and Data Intelligence Department, Malaysian Communications and Multimedia Commission, 1–6. https://www.mcmc.gov.my/ms/resources/statistics/internet-users-survey
McMillan, J. H. ., & Schumacher, S. (2006). Research in Education. Boston: Pearson Education.
Nawaz, M. B. (2020). Code-Switching in Social Media : A Case Study of Facebook in Pakistan. 40(2), 1075–1084.
Santiago-Cruz;, I. A., Ramírez-Rivera;, E. de J., López-Espíndola;, M., Hidalgo-Contreras;, J. V., Prinyawiwatkul;, W., & Herrera-Corredor, J. A. (2021). Use of online questionnaires to identify emotions elicited by different types of corn tortilla in consumers of different gender and age groups. Journal of Sensory Studies, 36(2). https://doi.org/https://doi.org/10.1111/joss.12638
Tylee, A., Haller, D. M., Graham, T., Churchill, R., & Sanci, L. A. (2007). Youth-friendly primary-care services: how are we doing and what more needs to be done? Lancet, 369(9572), 1565–1573. https://doi.org/10.1016/S0140-6736(07)60371-7
Voorveld, H. A. M., van Noort, G., Muntinga, D. G., & Bronner, F. (2018). Engagement with Social Media and Social Media Advertising: The Differentiating Role of Platform Type. Journal of Advertising, 47(1), 38–54. https://doi.org/10.1080/00913367.2017.1405754
Widen, S. C., & Russell, J. A. (2008). Children acquire emotion categories gradually. Cognitive Development, 23(2), 291–312. https://doi.org/10.1016/j.cogdev.2008.01.002
Wright, K. B. (2005). Researching internet-based populations: Advantages and disadvantages of online survey research, online questionnaire authoring software packages, and web survey services. Journal of Computer-Mediated Communication, 10(3), 1–31. https://doi.org/10.1111/j.1083-6101.2005.tb00259.x
Wu, K.-C., & Huang, Y.-H. (2018). Emotions and eye-tracking of differing age groups searching on e-book wall. Aslib Journal of Information Management, 70(4), 434–454. https://doi.org/10.1108/AJIM-01-2018-0017
Published
2023-12-31
How to Cite
Latib, L., Subramaniam, H., & Ramli, S. K. (2023). Understanding the Relationship Between Mood Engagement via Social Media Among Youngsters. Selangor Science & Technology Review (SeSTeR), 7(2), PREPRINT. Retrieved from https://sester.journals.unisel.edu.my/ojs/index.php/sester/article/view/322