Trait-level non-clinical ADHD symptoms in a community sample and their association with technology addictions
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Published:2023-09-13
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Volume:
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ISSN:1046-1310
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Container-title:Current Psychology
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language:en
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Short-container-title:Curr Psychol
Author:
Aydin TubaORCID, Parris Benjamin A.ORCID, Arabaci GizemORCID, Kilintari MarinaORCID, Taylor JacquiORCID
Abstract
AbstractAn increasing number of studies have reported the existence of ADHD symptoms to be risk factors for technology addictions among young adults. In contrast to previous studies, the aim of the present study was to examine different dimensions of technology addiction in a community sample of adults and to examine their association with the individual trait-level ADHD symptoms of inattention and hyperactivity-impulsivity. A community sample of one hundred and fifty adults were recruited to participate in this study via convenience sampling. Participants completed the Adult ADHD Self-Report Scale Symptom Checklist, the Bergen Social Media Addiction Scale, the Smartphone Addiction Scale, Young’s Internet Addiction Test, the Compulsive Online Shopping Scale, and a Demographic Information Form. Composite ADHD score, inattention and hyperactivity/impulsivity were positively associated with technology addictions (internet, social media, smartphone, and online shopping addiction). Hierarchical regression analysis revealed inattention and hyperactivity-impulsivity were predictors of social media addiction and smartphone addiction, whereas they were not for online shopping addiction. Furthermore, inattention was the only predictor of internet addiction. People with non-clinical, trait-level ADHD, especially those showing a preponderance of inattention symptoms appear to be more vulnerable to developing some forms of technology addiction.
Funder
Turkish Ministry of Education Bournemouth University
Publisher
Springer Science and Business Media LLC
Subject
General Psychology
Reference85 articles.
1. Adler, L., Kessler, R. C., Spencer, T., & World Health, O. (2013). Adult ADHD Self-Report Scale (ASRS-v1. 1) Symptom Checklist Instructions. World Health Organization (WHO). 2. Alageel, A. A., Alyahya, R. A., A Bahatheq, Y., Alzunaydi, N. A., Alghamdi, R. A., Alrahili, N. M., ... & Iacobucci, M. (2021). Smartphone addiction and associated factors among postgraduate students in an Arabic sample: A cross-sectional study. BMC psychiatry, 21(1), 1-10. https://doi.org/10.1186/s12888-021-03285-0 3. Alimoradi, Z., Lotfi, A., Lin, C. Y., Griffiths, M. D., & Pakpour, A. H. (2022). Estimation of behavioral addiction prevalence during COVID-19 pandemic: a systematic review and meta-analysis. Current addiction reports, 1-32. https://doi.org/10.1007/s40429-022-00435-6. 4. Amudhan, S., Prakasha, H., Mahapatra, P., Burma, A. D., Mishra, V., Sharma, M. K., & Rao, G. N. (2022). Technology addiction among school-going adolescents in India: Epidemiological analysis from a cluster survey for strengthening adolescent health programs at district level. Journal of Public Health, 44(2), 286–295. https://doi.org/10.1093/pubmed/fdaa257 5. Andreassen, C. S., 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. Psychology of Addictive Behaviors, 30(2), 252. https://doi.org/10.1037/adb0000160
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