Development of Social Media Addiction Scale for COVID-19 Pandemic (SMACOP)
COVID-19 Social Media Addiction
Vol. 16 No. 2 : 2021 (237-248)
Abstract
The current COVID-19 pandemic and ‘new normal’ has resulted in much distress worldwide. Social media currently plays an essential role in information gathering. Thus, time spent on social media has increased drastically, further increasing the risk for internet-related addictions, such as social media addiction. This study aimed to develop a COVID-19-related measure of social media addiction based on the Bergen Social Media Addiction Scale (BSMAS) in order to aid in the identification and evaluation of at-risk individuals. Social Media Addiction Scale for COVID-19 Pandemic (SMACOP) was adapted from BSMAS to fit the context of COVID-19 and pilot tested on 20 individuals. A total of 80 participants were subsequently recruited through convenience sampling from the general public of a public university in Malaysia, comprising of patients’ family, visitors, or hospital staff. Construct validity was assessed using the Insomnia Severity Index (ISI), Generalized Anxiety Disorder 7 (GAD7) and Patient Health Questionnaire (PHQ9). A two-factor structure was found for SMACOP, comprising of the factors ‘Desire’ and ‘Distress’. SMACOP shows good internal consistency (α = 0.64) and validity. SMACOP scores were positively correlated with the PHQ9, GAD7, and ISI (p<.01). SMACOP is a psychometrically valid instrument with high internal consistency, which is especially useful during this time in assessing social media addiction in relevance to COVID-19.
Keywords :
COVID-19,
pandemic,
Social media addiction,
Correspondance Address
Ng Chong Guan. Department of Psychological Medicine, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia. Tel: +603-79492068 Email: chong_guan@um.edu.my
References
Alabi, O.F. 2013. A survey of Facebook addiction level among selected Nigerian University undergraduates. New Med Mass Commun 10: 70-80.
Bányai, F., Zsila, Á., Király, O., Maraz, A., Elekes, Z., Griffiths, M.D., Demetrovics, Z. 2017. Problematic social media use: Results from a large-scale nationally representative adolescent sample. PloS One 12(1): e0169839.
Brooks, S.K., Webster, R.K., Smith, L.E., Woodland, L., Wessely, S., Greenberg, N., Rubin, G.J. 2020. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet 395(10227): 912-20.
Dong, H., Yang, F., Lu, X., Hao, W. 2020. Internet addiction and related psychological factors among children and adolescents in China during the coronavirus disease 2019 (COVID-19) epidemic. Front Psychaitry 11: 00751.
Department of Statistics Malaysia. 2020. Current Statistics: COVID-19 by States in Malaysia. [Department of Statistics Malaysia Web site] https://ukkdosm.github.io/covid-19 [16 July 2021]
Griffiths, M.D. 2005. A components model of addiction within a biopsychosocial framework. J Subst Use 10(4): 191-7.
Ho, R.C., Zhang, M.W., Tsang, T.Y., Toh, A.H., Pan, F., Lu, Y., Cheng, C., Yip, P.S., Lam, L.T., Lai, C., Watanabe, H., Mak, K.K. 2014. The association between internet addiction and psychiatric co-morbidity: a meta-analysis. BMC Psychiatry 14: 183
Jafarkarimi, H., Sim, A.T.H., Saadatdoost, R., Hee, J.M. 2016. Facebook addiction among Malaysian students. Int J Inf Educ Technol 6(6): 465-9.
Kaiser, H.F. 1958. The varimax criterion for analytic rotation in factor analysis. Psychometrika 23(3): 187-200.
Kaiser, H.F. 1974. An index of factorial simplicity. Psychometrika 39(1): 31-6.
King, D., Koster, E., Billieux, J. 2019. Study what makes games addictive. Nature 573(7774): 346.
Kroenke, K., Spitzer, R.L., Williams, J.B. 2001. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 16(9): 606-13.
LaRose, R., Kim, J., Peng, W. 2010. Social networking: Addictive, compulsive, problematic, or just another media habit? In A networked self. Routledge; 59-81.
Lin, C.-Y., Broström, A., Nilsen, P., Griffiths, M. D., & Pakpour, A.H. 2017. Psychometric validation of the Persian Bergen Social Media Addiction Scale using classic test theory and Rasch models. J Behav Addict 6(4): 620-9.
MacCallum, R.C., Austin, J.T. 2000. Applications of structural equation modeling in psychological research. Annu Rev Psychol 51(1): 201-6.
Monacis, L., de Palo, V., Griffiths, M.D., Sinatra, M. 2017. Social networking addiction, attachment style, and validation of the Italian version of the Bergen Social Media Addiction Scale. J Behav Addict 6(2): 178-86.
Morgan, J.P. 2020. Media consumption in the age of Covid-19. Against the backdrop of the Coronavirus pandemic, increased media consumption is helping to fill the time. [JP Morgan Web site] https://www.jpmorgan.com/global/research/media-consumption [9 September 2020].
Morin, C.M., Belleville, G., Bélanger, L., Ivers, H. 2011. The Insomnia Severity Index: psychometric indicators to detect insomnia cases and evaluate treatment response. Sleep 34(5): 601-8.
Schou Andreassen, C., Billieux, J., Griffiths, M.D., Kuss, D.J., Demetrovics, Z., Mazzoni, E., Pallesen, S. 2016. The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: A large-scale cross-sectional study. Psychol Addict Behav 30(2): 252-62.
Sharma, M.K., Anand, N., Vishwakarma, A., Sahu, M., Thakur, P.C., Mondal, I., Singh, P., Sj, A., N, S., Biswas, A.R.A., John, N., Tapatrikar, A., Murthy, K.D. 2020. Mental health issues mediate social media use in rumors: implication for media based mental health literacy. Asian J Psychiatr 53: 102132.
Spitzer, R.L., Kroenke, K., Williams, J.B., Löwe, B. 2006. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med 166(10): 1092-7.
Sun, Y., Li, Y., Bao, Y., Meng, S., Sun, Y., Schumann, G., Shi, J. 2020. Brief report: increased addictive internet and substance use behavior during the COVID-19 pandemic in China. Am J Addict 29(4): 268-70.
Tanaka, J.S. 1987. "How big is big enough?": Sample size and goodness-of-fit in structural equation models with latent variables. Child Dev 58(1): 136-46.
Wang, C.W., Ho, R., Chan, C., Tse, S. 2015. Exploring personality characteristics of Chinese adolescents with internet-related addictive behaviours: Trait differences for gaming addiction and social networking addiction. Addict Behav 42: 32-5.
Westerman, D., Spence, P. R., Van Der Heide, B. 2012. A social network as information: The effect of system generated reports of connectedness on credibility on Twitter. J Comput-Mediat Comm 28(1): 199-206.
Wolniczak Rodriguez, I., Aguila, C.-D., Alonso, J., Palma-Ardiles, G., Arroyo, K.J., Solés-Visscher, R., Paredes-Yauri, S., Mego-Aquije, K, & Bernabe-Ortiz, A. 2014. Association between Facebook Dependence and Poor Sleep Quality: A Study in a Sample of Undergraduate Students in Peru. PLos One 8(3): e59087.
Wong, B.Z.R., Goh, S.J., Hui, J.Y. 2020. Dark triad and social media addiction: the mediating roles of coping strategies. (Doctoral dissertation, UTAR).
Xue, Y., Dong, Y., Luo, M., Mo, D., Dong, W., Zhang, Z, Liang, H. 2018. Investigting the impact of mobile SNS addiction on individual’s self-rated health. Internet Research 28(2): 278-92.
Yam, C.-W., Pakpour, A.H., Griffiths, M.D., Yau, W.-Y., Lo, C.-L. M., Ng, J.M., Leung, H. 2019. Psychometric testing of three Chinese online-related addictive behavior instruments among Hong Kong university students. Psychiatric Quarterly 90(1): 117-28.
Zhao, N., Zhou, G. 2021. COVID-19 Stress and Addictive Social Media Use (SMU): Mediating Role of Active Use and Social Media Flow. Front Psychiatry 12: 635546
