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Journals / Addicta: The Turkish Journal on Addictions / 2022 / Cilt: 9 - Sayı: 1

Pilot Study to Predict Smartphone Addiction Through Usage Pattern of Installed Android Applications and to Derive Correlations Between Addiction and Phone Usage Behavior

Swati AGGARWAL
Shubbi GUPTA
Simrat Pal Singh SATIA
Shivin SALUJA
Varshika GAMBHIR
Pages
63–74
Publication Date
2022-10-11
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The study also includes gender-wise variations of smartphone usage patterns and explicit parallelism between usage patterns of addicted and non-addicted users.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Mobile phone technology has been completely revolutionized in recent years.
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Key Findings & Data:From being used for calls and text messages, the usage pattern has now shifted, and involves heavy applications (apps) based on platforms such as Android and iOS.
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Conclusion & Impact:The study also includes gender-wise variations of smartphone usage patterns and explicit parallelism between usage patterns of addicted and non-addicted users.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Mobile phone technology has been completely revolutionized in recent years. From being used for calls and text messages, the usage pattern has now shifted, and involves heavy applications (apps) based on platforms such as Android and iOS. Therefore, people have become exceedingly dependent on smartphones, with most of them suffering from a smartphone addiction disorder. In this study, the authors collect app usage patterns and categorize all apps into five buckets: social, entertainment, utility, gaming, and shopping/food and beverage. The data were collected through a self-developed app, named Activity Tracker, installed in the smartphones of individuals participating in the study. Activity Tracker also collects additional phone usage features such as call duration, number of texts/calls, and screen-on duration. The authors predict smartphone addiction using supervised machine-learning algorithms with good accuracy. This is a promising attempt to uncover multi-dimensional aspects of smartphone addiction by studying the usage patterns of installed Android applications. The study also includes gender-wise variations of smartphone usage patterns and explicit parallelism between usage patterns of addicted and non-addicted users.

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Cite This Article

AGGARWAL, S., GUPTA, S., SATIA, S. P. S., SALUJA, S., GAMBHIR, V. (2022). Pilot Study to Predict Smartphone Addiction Through Usage Pattern of Installed Android Applications and to Derive Correlations Between Addiction and Phone Usage Behavior. Addicta: The Turkish Journal on Addictions, Cilt: 9 - Sayı: 1, 63–74. https://ajindex.com/articles/428254

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References (3)

  1. Ahmed, I., & Perji K. A. (2011). Mobile phone to youngsters: Necessity or addiction. Information Management and Business Review, 2(5), 229–238. [CrossRef] Bhattacharya, S., Bashar, M. A., Srivastava, A., & Singh, A. (2019). Nomophobia: No mobile phone phobia. Journal of Family Medicine and Primary Care, 8(4), 1297–1300. [CrossRef] Bianchi, A., & Phillips, J. G. (2005). Psychological predictors of problem mobile phone use. Cyberpsychology and Behavior, 8(1), 39–51. [CrossRef] Bisen, S., & Deshpande, Y. (2016). An analytical study of smartphone addiction among engineering students: A gender differences. International Journal of Indian Psychology, 4(1), 70–83. Bødker, M., Gimpel, G., & Hedman, J. (2009). The user experience of smart phones: a consumption values approach. 8th global mobility roundtable, GMR. De-Sola, J., Talledo, H., Rodríguez de Fonseca, F., & Rubio, G. (2017). Prevalence of problematic cell phone use in an adult population in Spain as assessed by the mobile phone problem use scale (mppus). PLoS One, 12(8), e0181184. [CrossRef] Ding, X., Xu, J., Chen, G., & Xu, C. (2016). Beyond smartphone overuse: Identifying addictive mobile apps. In Proceedings of the 2016 CHI conference extended abstracts on human factors in computing systems (pp. 2821–2828).
  2. San Jose, CA, USA: CHI ’16. Elhai, J. D., Levine, J. C., Dvorak, R. D., & Hall, B. J. (2016). Fear of missing out, need for touch, anxiety and depression are related to problematic smartphone use. Computers in Human Behavior, 63, 509–516. [CrossRef] Ferreira, D., J., Kostakos, V., Barkhuus, L., & Dey, A. K. (2014). Contextual experience sampling of mobile application micro-usage. In Proceedings of the 16th international conference on Human-computer interaction with mobile devices & services (pp. 91–100).
  3. Toronto, Ontario, Canada: MobileHCI ‘14. Hooper, V., & Zhou, Y. (2007). Addictive, dependent, compulsive? A study of mobile phone usage. BLED 2007 Proceedings, p. 38. Bureau, E. (2020). India to have over 800 million smartphone users by 2022: Cisco study. The Economic Times. Kwon, M., Kim, D. J., Cho, H., & Yang, S. (2013). The smartphone addiction scale: Development and validation of a short version for adolescents. PLoS One, 8(12), e83558. [CrossRef] Lee, U., Lee, J., Ko, M., Lee, C., Kim, Y., Yang, S., Yatani, K., Gweon, G., Chung, K.-M., & Song, J. (2014). Hooked on smartphones: An exploratory study on smartphone overuse among college students. In Proceedings of the 32nd annual ACM conference on