KnE Social Sciences
ISSN: 2518-668X
The latest conference proceedings on humanities, arts and social sciences.
Validation of the Smartphone Addiction Scale-Short Version (SAS-SV) for Measuring Problematic Smartphone Use in Indonesian Adolescents
Published date: Apr 18 2025
Journal Title: KnE Social Sciences
Issue title: The 7th International Conference on Education and Social Science Research (ICESRE)
Pages: 255 - 269
Authors:
Abstract:
In recent years, research has highlighted that excessive smartphone use in adolescents can potentially lead to problematic smartphone use (PSU) and negatively impact their daily lives. Hence, more precise measurement methods are necessary, particularly in the Indonesian context. The purpose of this study was to validate the Smartphone Addiction Scale-Short Version (SAS-SV) among Indonesian adolescents. This study included 410 adolescents aged 12 to 18 from Medan, with a mean age M=15.39; SD=1.396 including 245 females and 165 males. The data analysis approach used first-order confirmatory factor analysis (CFA) with correlation factors. The results demonstrate an acceptable model fit for a single-factor structure, with the index criteria value X2 = 151.500 df = 35, p < 0,001, the Standardized Root Mean Square Residual (SRMR)=0.052, Root Mean Squared Error of Approximation (RMSEA)=0.090, Goodness of Fit Index (GFI)=0.986, Tucker-Lewis index (TLI)=0.862, and Comparative Fit Index (CFI)=0.893. Then, the internal consistency reliability coefficient shows good reliability with coefficient values Cronbach’s Alpha of 0.820 and McDonald’s Omega of 0.811, and a composite reliability of 0.824. It shows that using the SAS-SV is feasible and has a reliable scale to measure problematic smartphone use in Indonesian adolescents. Future research should explore the dynamics of problematic smartphone use across diverse regions in Indonesia to gain better understanding of the phenomenon within distinct cultural contexts.
Keywords: adolescent students, problematic smartphone use, smartphone addiction scale, validation
References:
[1] APJII. Survei Penetrasi Internet Indonesia 2024. Asosiasi Penyelenggara Jasa Internet Indonesia; 2024.
[2] Fang J, Wang X, Wen Z, Zhou J. Fear of missing out and problematic social media use as mediators between emotional support from social media and phubbing behavior. Addict Behav [Internet]. 2020;107(February):106430. Available from: https://doi.org/10.1016/j.addbeh.2020.106430.
[3] Sohn S, Rees P, Wildridge B, Kalk NJ, Carter B. Prevalence of problematic smartphone usage and associated mental health outcomes amongst children and young people: a systematic review, meta-analysis and GRADE of the evidence. BMC Psychiatry. 2019;21(19):1–10.
[4] Geng J, Lei L, Ouyang M, Niu J, Wang P. The influence of perceived parental phubbing on adolescents’ problematic smartphone use: A two-wave multiple mediation model. Addict Behav. 2021 Oct;121:106995.
[5] Davey S, Davey A. Assessment of smartphone addiction in Indian adolescents: A mixed-method study by systematic review and meta-analysis approach. Int J Prev Med. 2014;5(12):1500–11.
[6] Fathya R, Sari K, Mawarpury M, Afriani. Tingkat smartphone addiction pada penduduk di kota Banda Aceh. J Psikol. 2020;16(2):202–15.
[7] Arthy CC, Effendy ER, Amin MM, Loebis B, Camellia V, Husada MS. Indonesian version of addiction rating scale of smartphone usage adapted from smartphone addiction scale-short version (SAS-SV) in junior high school. Open Access Maced J Med Sci. 2019 Oct;7(19):3235–9.
[8] Kwon M, Lee JY, Won WY, Park JW, Min JA, Hahn C, et al. Development and validation of a smartphone addiction scale (SAS). PLoS One. 2013 Feb 27;8(2):e56936.
[9] Marini L, Hendriani W, Wulandari PY. Gambaran problematic smartphone use pada remaja. Psikobuletin Bul Ilm Psikol. 2024;5(1):43–55.
[10] Billieux J, Linden M, Van der Rochat L. The role of impulsivity in actual and problematic use of the mobile phone. Appl Cogn Psychol [Internet]. 2008;22:1195–210. Available from: http://apps.isiknowledge.com.libproxy.wustl. edu/full_record.do?product=WOS&search_mode=GeneralSearch&qid=2&SID= 3Fk8CLaLLbb42ErOOJ2i&page=1&doc=1.
[11] Yu S, Sussman S. Does smartphone addiction fall on a continuum of addictive behaviors? Int J Environ Res Public Health. 2020 Jan;17(2):422.
[12] Marini L, Hendriani W, Wulandari PY. Parental phubbing and smartphone addiction in adolescents: A meta-analysis review. Insight: Jurnal Ilmiah Psikologi. 2023;25(1):109–126. Available from: http://erjurnal.mercubuana-yogya.ac.id/index. php/psikologi/article/view/3423.
[13] Busch PA, McCarthy S. Antecedents and consequences of problematic smartphone use: A systematic literature review of an emerging research area. Comput Human Behav. 2019 Jul;2021:114.
[14] Wang X, Qiao Y, Wang S. Parental phubbing, problematic smartphone use, and adolescents’ learning burnout: A cross-lagged panel analysis. J Affect Disord. 2023 Jan;320:442–9.
[15] Sarfika R, Wijaya A, Putri ZM, Saifudin IM. Smartphone addiction and adolescent mental health: A cross-sectional study in West Sumatra province. Int J Public Health Sci. 2024;13(2):521.
[16] Mulyaningrum A, Kusumaningrum FA. Parental phubbing and smartphone addiction among adolescents. INSPIRA Indones J Psychol Res. 2022;3(1):23–30.
[17] Kline RB. Principles and practice of structural equation modeling. 5th ed. Guilford Publications; 2023.
[18] Tim JASP. JASP Versi 0.18.3.0. 2023.
[19] Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equ Modeling. 1999;6(1):1–55.
[20] Brown TA. Confirmatory factor analysis for applied research. The Guilford Press; 2015.
[21] Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate data analysis (Eighth Edition). 8th ed. Hampshire: Annabel Ainscow; 2019.
[22] Ghozali, Fuad. Structural equation model: Theory, concept, and application with LISREL 9.10. 4th ed. Semarang: Badan Penerbit Universitas Diponegoro; 2012.
[23] Huang C, Wang YM, Wu TW, Wang PA. An empirical analysis of the antecedents and performance consequences of using the Moodle platform. Int J Inf Educ Technol. 2013;3:217–21.
[24] Trizano-Hermosilla I, Alvarado JM. Best alternatives to Cronbach’s alpha reliability in realistic conditions: Congeneric and asymmetrical measurements. Front Psychol. 2016;7. Available from: https://doi.org/10.3389/fpsyg.2016.00769.
[25] McNeish D. Thanks coefficient alpha, we’ll take it from here. Psychol Methods. 2018 Sep;23(3):412–33.
[26] Kottner J, Audigier L, Brorson S, Donner A, Gajewski BJ, Hróbjartsson A, et al. Guidelines for reporting reliability and agreement studies (GRRAS) were proposed. J Clin Epidemiol. 2011;64(1):96–106.
[27] Curran PJ, West SG, Finch JF. The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychol Methods. 1996;1(1):16–29.
