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CNS & Neurological Disorders - Drug Targets

Editor-in-Chief

ISSN (Print): 1871-5273
ISSN (Online): 1996-3181

Systematic Review Article

Smartphone Addiction among Students and its Harmful Effects on Mental Health, Oxidative Stress, and Neurodegeneration towards Future Modulation of Anti-Addiction Therapies: A Comprehensive Survey based on SLR, Research Questions, and Network Visualization Techniques

Author(s): Faijan Akhtar, Parth K. Patel, Md Belal Bin Heyat, Saba Yousaf, Atif Amin Baig*, Rashenda Aziz Mohona, Muhamad Malik Mutoffar, Tanima Bhattacharya, Bibi Nushrina Teelhawod, Jian Ping Li*, Mohammad Amjad Kamal and Kaishun Wu*

Volume 22, Issue 7, 2023

Published on: 13 December, 2022

Page: [1070 - 1089] Pages: 20

DOI: 10.2174/1871527321666220614121439

open access plus

Abstract

Background: Addiction is always harmful to the human body. Smartphone addiction also affects students' mental and physical health.

Aim: This study aims to determine the research volume conducted on students who are affected by smartphone addiction and design a database. We intended to highlight critical problems for future research. In addition, this paper enterprises a comprehensive and opinion-based image of smartphone-addicted students.

Methodology: We used two types of methods, such as systematic literature review and research questions based on the Scopus database to complete this study. We found 27 research articles and 11885 subjects (mean ±SD: 440.19 ± 513.58) using the PRISMA technique in this study. Additionally, we have deeply investigated evidence to retrieve the current understanding of smartphone addiction from physical changes, mental changes, behavioural changes, impact on performance, and significant concepts. Furthermore, the effect of this addiction has been linked to cancers, oxidative stress, and neurodegenerative disorders.

Results: This work has also revealed the future direction and research gap on smartphone addiction among students and has also tried to provide goals for upcoming research to be accomplished more significantly and scientifically.

Conclusion: This study suggests future analysis towards identifying novel molecules and pathways for the treatment and decreasing the severity of mobile addiction.

Keywords: Addiction, Brain, Education, Health, Mobile, Neurological disorders, Nervous system, Oxidative stress, Student, Scopus, Side effect, Systematic literature review, Electromagnetic field, Radiations

Graphical Abstract

[1]
Samaha M, Hawi NS. Relationships among smartphone addiction, stress, academic performance, and satisfaction with life. Comput Human Behav 2016; 57: 321-5.
[http://dx.doi.org/10.1016/j.chb.2015.12.045]
[2]
Thomée S, Härenstam A, Hagberg M. Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults--a prospective cohort study. BMC Public Health 2011; 11: 66.
[http://dx.doi.org/10.1186/1471-2458-11-66] [PMID: 21281471]
[3]
Cheever NA, Rosen LD, Carrier LM, Chavez A. Out of sight is not out of mind: The impact of restricting wireless mobile device use on anxiety levels among low, moderate and high users. Comput Human Behav 2014; 37: 290-7.
[http://dx.doi.org/10.1016/j.chb.2014.05.002]
[4]
Panova T, Lleras A. Avoidance or boredom: Negative mental health outcomes associated with use of Information and Communication Technologies depend on users’ motivations. Comput Human Behav 2016; 58: 249-58.
[http://dx.doi.org/10.1016/j.chb.2015.12.062]
[5]
Pontes HM, Griffiths MD. New concepts, old known issues: The DSM-5 and internet gaming disorder and its assessment. In: Psychological and Social Implications Surrounding Internet and Gaming Addiction. Pennsylvania, USA: IGI Global 2015.
[http://dx.doi.org/10.4018/978-1-4666-8595-6.ch002]
[6]
Billieux J, Maurage P, Lopez-Fernandez O, Kuss DJ, Griffiths MD. Can disordered mobile phone use be considered a behavioral addiction? an update on current evidence and a comprehensive model for future research. Curr Addict Rep 2015; 2: 156-62.
[http://dx.doi.org/10.1007/s40429-015-0054-y]
[7]
Aljomaa SS, Mohammad MF, Albursan IS, Bakhiet SF, Abduljabbar AS. Smartphone addiction among university students in the light of some variables. Comput Human Behav 2016; 2016: 41.
[http://dx.doi.org/10.1016/j.chb.2016.03.041]
[8]
Griffiths MD. Gaming addiction and internet gaming disorder. In: The Video Game Debate. Worldwide Science 2018.
[9]
Beranuy M, Oberst U, Carbonell X, Chamarro A. Problematic Internet and mobile phone use and clinical symptoms in college students: The role of emotional intelligence. Comput Human Behav 2009; 25(5): 1182-7.
[http://dx.doi.org/10.1016/j.chb.2009.03.001]
[10]
Alshorman O, Masadeh M, Heyat MBB, et al. Frontal lobe real-time EEG analysis using machine learning techniques for mental stress detection. J Integr Neurosci 2021; 21(1): 20.
[PMID: 35164456]
[11]
Ragu-Nathan TS, Tarafdar M, Ragu-Nathan BS, Tu Q. The consequences of technostress for end users in organizations: Conceptual development and empirical validation. Inf Syst Res 2008; 19(4): 417-33.
[http://dx.doi.org/10.1287/isre.1070.0165]
[12]
Heyat MBB, Akhtar F, Khan MH, et al. Detection, treatment planning, and genetic predisposition of bruxism: a systematic mapping process and network visualization technique. CNS Neurol Disord Drug Targets 2021; 20(8): 755-75.
[http://dx.doi.org/10.2174/1871527319666201110124954] [PMID: 33172381]
[13]
Bin Heyat MB, Akhtar F, Ansari MA, et al. Progress in detection of insomnia sleep disorder: A comprehensive review. Curr Drug Targets 2021; 22(6): 672-84.
[http://dx.doi.org/10.2174/1389450121666201027125828] [PMID: 33109045]
[14]
Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ 2021; 372(71)
[http://dx.doi.org/10.1136/bmj.n71] [PMID: 33782057]
[15]
Wittorski R. Professionalisation and the development of Competences in Education and Training In: Competence and Competence development,. Cohen-Scal. Berlin, Germany, Toranto: Barbara Budrich 2012; pp. 31-42.
[http://dx.doi.org/10.2307/j.ctvbkk2h9.6]
[16]
Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med 2009; 6(7): e1000097.
[http://dx.doi.org/10.1371/journal.pmed.1000097] [PMID: 19621072]
[17]
Sheikh S, Bin Heyat MB, AlShorman O, Masadeh M, Alkahatni F. A Review of Usability Evaluation Techniques for Augmented Reality Systems in Education. Innovation and New Trends in Engineering Science and Technology Education Conference (IETSEC) 16-18 May. Amman, Jordan 2021.
[http://dx.doi.org/10.1109/IETSEC51476.2021.9440506]
[18]
Akhtar F, Li JP, Heyat MBB, et al. Potential of Blockchain Technology in Digital Currency: A Review. In: 16th International Computer Conference on Wavelet Active Media Technology and Information Processing. 14-15 Dec. 2019; pp. 85-91.
[http://dx.doi.org/10.1109/ICCWAMTIP47768.2019.9067546]
[19]
Guragai B, AlShorman O, Masadeh M, Bin Heyat MB. A survey on deep learning classification algorithms for motor imagery. 32nd International Conference on Microelectronics (ICM). Aqaba, Jordan 14-17 Dec. 2020.
[http://dx.doi.org/10.1109/ICM50269.2020.9331503]
[20]
Akhtar F, Bin Heyat MB, Li JP, Patel PK. Role of Machine Learning in Human Stress: A Review. 17th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP). Chengdu, China 18-20 Dec. 2020; pp. 170-4.
[http://dx.doi.org/10.1109/ICCWAMTIP51612.2020.9317396]
[21]
Hussain K, Mohd Salleh MN, Cheng S, Shi Y. Metaheuristic research: A comprehensive survey. Artif Intell Rev 2018; 2018: 32526909.
[22]
Abelha M, Fernandes S, Mesquita D, Seabra F, Ferreira-Oliveira AT. Graduate employability and competence development in higher education—A systematic literature review using PRISMA. Sustainability 2020; 12(15): 5900.
[http://dx.doi.org/10.3390/su12155900]
[23]
Singh S, Kumar K. Review of literature of lean construction and lean tools using systematic literature review technique (2008–2018). Ain Shams Eng J 2020; 11(2): 465-71.
[http://dx.doi.org/10.1016/j.asej.2019.08.012]
[24]
Davey A, Nasser K, Davey S. Gender differential for smart phone addiction and its predictors among adolescents: Assessing relationship with self control via sem approach. J Indian Assoc Child Adolesc Ment Heal 2020; 2020: 225802879.
[25]
Soliman Elserty N, Ahmed Helmy N, Mohmed Mounir K. Smartphone addiction and its relation to musculoskeletal pain in Egyptian physical therapy students. Eur J Physiother 2020; 22(2): 70-8.
[http://dx.doi.org/10.1080/21679169.2018.1546337]
[26]
Liu X, Wang S, Zhou J, Cai H. Attention bias training for reducing smartphone addiction in Chinese college students. J Evid Based Psychother 2020; 20(1): 1-24.
[http://dx.doi.org/10.24193/jebp.2020.1.1]
[27]
Huang Y, Jung H-R, Lim C-H. Effects of Smartphone Addiction on Radiology Students’ Interpersonal Satisfaction. Med-Leg Update 2020; 20(1): 1971-5.
[http://dx.doi.org/10.37506/v20/i1/2020/mlu/194593]
[28]
Wang Z, Zheng J. Relationship between smartphone usage time and mental health of college students. De Clín Psicol 2020; 23: 177-86.
[http://dx.doi.org/10.24205/03276716.2020.23]
[29]
Hashmi AM, Naz S, Ali AA, Asif A. Smart phones and medical students: Pleasant distraction or dangerous addiction? J Pak Med Assoc 2019; 69(12): 1891-5.
[http://dx.doi.org/10.5455/JPMA.299735] [PMID: 31853123]
[30]
Shylaja J, Annapoorani M. Smartphone addiction predictors and subjective health problems among adolescent boys in technical college at Tirunelveli, South India. Int J Sci Technol Res 2019; 8(11): 1314-7.
[31]
Zou Y, Xia N, Zou Y, Chen Z, Wen Y. Smartphone addiction may be associated with adolescent hypertension: A cross-sectional study among junior school students in China. BMC Pediatr 2019; 19(1): 310.
[http://dx.doi.org/10.1186/s12887-019-1699-9] [PMID: 31484568]
[32]
Anju Philip T, Aswathy Krishnan S, Saju A, Athulya N. Mobile phone dependence and sleep quality among undergraduate students. Indian J Forensic Med Toxicol 2019; 13(3): 11-5.
[http://dx.doi.org/10.5958/0973-9130.2019.00156.7]
[33]
Direktör C, Nuri C. Personality beliefs as a predictor of smartphone addiction. Rev Psiquiatr Clin (Santiago) 2019; 46(3): 61-5.
[http://dx.doi.org/10.1590/0101-60830000000195]
[34]
Sok SR, Seong MH, Ryu MH. Differences of Self-control, daily life stress, and communication skills between smartphone addiction risk group and general group in Korean Nursing Students. Psychiatr Q 2019; 90(1): 1-9.
[http://dx.doi.org/10.1007/s11126-018-9596-1] [PMID: 30178221]
[35]
Jamir L, Duggal M, Nehra R, Singh P, Grover S. Epidemiology of technology addiction among school students in rural India. Asian J Psychiatr 2019; 40: 30-8.
[http://dx.doi.org/10.1016/j.ajp.2019.01.009] [PMID: 30716701]
[36]
Sert H, Taskin Yilmaz F, Karakoc Kumsar A, Aygin D. Effect of technology addiction on academic success and fatigue among Turkish university students. Fatigue 2019; 7(1): 41-51.
[http://dx.doi.org/10.1080/21641846.2019.1585598]
[37]
Venkatesh E, Jemal MYA, Samani ASA. Smart phone usage and addiction among dental students in Saudi Arabia: A cross sectional study. Int J Adolesc Med Health 2017; 31(1): 133.
[http://dx.doi.org/10.1515/ijamh-2016-0133] [PMID: 28384117]
[38]
Langseth ID, Sedal H. Smart phones in schools: In what ways can coaching empower students to make a valid judgement on when and how to use their smart phone? Hum IT 2019; 14(3): 48-82.
[39]
Erol O, Cirak NS. Exploring the loneliness and internet addiction level of college students based on demographic variables. Contemp Educ Technol 2019; 10(2): 156-72.
[http://dx.doi.org/10.30935/cet.554488]
[40]
Kheradmand A, Amirlatifi ES, Sohrabi MR, Meybodi AM. Validation of the Persian smartphone addiction scale among Tehran university students, Iran. Int J High Risk Behav Addict 2019; 8(1): 81176.
[http://dx.doi.org/10.5812/ijhrba.81176]
[41]
Elhai JD, Hall BJ, Erwin MC. Emotion regulation’s relationships with depression, anxiety and stress due to imagined smartphone and social media loss. Psychiatry Res 2018; 261: 28-34.
[http://dx.doi.org/10.1016/j.psychres.2017.12.045] [PMID: 29276991]
[42]
Alavi SS, Ghanizadeh M, Mohammadi MR, Mohammadi Kalhory S, Jannatifard F, Sepahbodi G. The survey of personal and national identity on cell phone addicts and non-addicts. Iran J Psychiatry 2018; 13(1): 15-21.
[PMID: 29892313]
[43]
Gao T, Xiang Y-T, Zhang H, Zhang Z, Mei S. Neuroticism and quality of life: Multiple mediating effects of smartphone addiction and depression. Psychiatry Res 2017; 258: 457-61.
[http://dx.doi.org/10.1016/j.psychres.2017.08.074] [PMID: 28917440]
[44]
Siddiqi N, Jahan F, Moin F, Al-Shehhi F, Al-Balushi F. Excessive use of mobile phones by medical students: Should precautions be taken? Biomed Pharmacol J 2017; 10(4): 1631-8.
[http://dx.doi.org/10.13005/bpj/1274]
[45]
Cohn J. ‘Devilish Smartphones’ and the ‘Stone-Cold’ Internet: Implications of the technology addiction trope in college student digital literacy narratives. Comput Compos 2016; 42: 80-94.
[http://dx.doi.org/10.1016/j.compcom.2016.08.008]
[46]
Ching SM, Yee A, Ramachandran V, et al. Validation of a malay version of the smartphone addiction scale among medical students in Malaysia. PLoS One 2015; 10(10): e0139337.
[http://dx.doi.org/10.1371/journal.pone.0139337] [PMID: 26431511]
[47]
Nath R, Chen L, Muyingi HN. An empirical study of the factors that influence in-class digital distraction among university students. Inf Resour Manage J 2015; 28(4): 1-18.
[http://dx.doi.org/10.4018/IRMJ.2015100101]
[48]
Park CJ, Hyun JS, Kim JY, Lee KE. Impact of personal time-related factors on smart phone addiction of female high school students. Lect Notes Eng Comput Sci 2014; 1: 311-5.
[49]
Zhou Y, Zhang X, Liang J-C, Tsai C-C. The relationship between parents addicted to mobile phone and adolescent addicted to the Internet. Proc 22nd Int Conf Comput Educ ICCE 2014 2014; 484-8.
[50]
Roberts JA, Pirog SF III. A preliminary investigation of materialism and impulsiveness as predictors of technological addictions among young adults. J Behav Addict 2013; 2(1): 56-62.
[http://dx.doi.org/10.1556/JBA.1.2012.011] [PMID: 26165772]
[51]
Akbulut Zencirci S, Aygar H, Göktaş S, Önsüz MF, Alaiye M, Metintaş S. Evaluation of smartphone addiction and related factors among university students. Int J Res Med Sci 2018; 6(7): 2210.
[http://dx.doi.org/10.18203/2320-6012.ijrms20182805]
[52]
Jeong SH, Kim HJ, Yum JY, Hwang Y. What type of content are smartphone users addicted to?: SNS vs. games. Comput Human Behav 2016; 54: 10-7.
[http://dx.doi.org/10.1016/j.chb.2015.07.035]
[53]
Rahmy L, Ilawaty S. Factors caused students addiction to handphone description study at state Junior High School 13 in Bengkulu City. J Cons 2020; 3(1): 23-37.
[54]
Agusta D. Risk factors of addiction using smartphone in students at Smk Negeri 1 Kalasan Yogyakarta. J Hasil Riset 2016; 5(3): 86-96.
[55]
Munasinghe PG. Factors influencing the smartphone addiction among students of the North Central Province in Sri Lanka. SSRN Electron J 2018; 2018; 2794735.
[http://dx.doi.org/10.2139/ssrn.2794735]
[56]
Archana G, Balaji P. Prevalence and psychological intervention of internet and smart phone addiction. Int J Recent Technol Eng 2020; 8(4S4): 273-6.
[http://dx.doi.org/10.35940/ijrte.D1072.1284S419]
[57]
Haque M, Mostafa A, Hoque R, Chakraborty R, Saifuddin Munna M. Internet use and addiction: A cross-sectional study to ascertain internet utilization level for academic & non-academic purpose among medical and university students of Bangladesh. Konuralp Tip Derg 2019; 11: 404-15.
[http://dx.doi.org/10.18521/ktd.522996]
[58]
Soomro KA, Zai SAY. Nasrullah, Hina QA. Investigating the impact of university students’ smartphone addiction on their satisfaction with classroom connectedness. Educ Inf Technol 2019; 24(6): 3523-35.
[http://dx.doi.org/10.1007/s10639-019-09947-7]
[59]
Soni R, Upadhyay R, Jain M. Prevalence of smart phone addiction, sleep quality and associated behaviour problems in adolescents. Int J Res Med Sci 2017; 5(2): 515.
[http://dx.doi.org/10.18203/2320-6012.ijrms20170142]
[60]
Tangmunkongvorakul A, Musumari PM, Tsubohara Y, et al. Factors associated with smartphone addiction: A comparative study between Japanese and Thai high school students. PLoS One 2020; 15(9): e0238459.
[http://dx.doi.org/10.1371/journal.pone.0238459] [PMID: 32898191]
[61]
Setiawan HS. Impact analysis of the impact of mobile games on association activities of students of Sdn Tanjung Barat 07 Jakarta. Fakt Exacta 2018; 11(2): 146.
[http://dx.doi.org/10.30998/faktorexacta.v11i2.2338]
[62]
Santosa ET. Rising Children Digital Era. Jakarta, Indonesia: Elex Media Komputindo 2015.
[63]
Rahmandani F, Tinus A, Ibrahim MM. Analysis of the impact of the use of gadget (smartphone) on the personality and character (strong) of students at Sma Negeri 9 Malang. J Civic Hukum 2018; 3(1): 18.
[http://dx.doi.org/10.22219/jch.v3i1.7726]
[64]
Wardhani FP. Student Gadget Addiction Behavior in the Perspective of Respectful Framework. Konselor 2018; 7(3): 116-23.
[http://dx.doi.org/10.24036/0201872100184-0-00]
[65]
Elhai JD, Levine JC, Dvorak RD, Hall BJ. Fear of missing out, need for touch, anxiety and depression are related to problematic smartphone use. Comput Human Behav 2016; 63: 509-16.
[http://dx.doi.org/10.1016/j.chb.2016.05.079]
[66]
Sharma B, Kumar P, Sharma P. Smartphone is It ‘Behaviour Addiction or Substance Abuse Disorder’: A Review To Find Chemistry Behind. Int J Pharamaceutical Sci Res 2021; 12(1): 57-64.
[http://dx.doi.org/10.13040/IJPSR.0975-8232.12(1).57-64]
[67]
Bianchi A, Phillips JG. Psychological predictors of problem mobile phone use. Cyberpsychol Behav 2005; 8(1): 39-51.
[http://dx.doi.org/10.1089/cpb.2005.8.39] [PMID: 15738692]
[68]
Gowda GS, Komal S, Sanjay TN, Mishra S, Kumar CN, Math SB. Sociodemographic, legal, and clinical profiles of female forensic inpatients in Karnataka: A retrospective study. Indian J Psychol Med 2019; 41(2): 138-43.
[http://dx.doi.org/10.4103/IJPSYM.IJPSYM_152_18] [PMID: 30983661]
[69]
Fransson A, Chóliz M, Håkansson A. Addiction-like mobile phone behavior – validation and association with problem gambling. 2018; 9: 1-13.
[http://dx.doi.org/10.3389/fpsyg.2018.00655]
[70]
Kuss DJ, Kanjo E, Crook-Rumsey M, Kibowski F, Wang GY, Sumich A. Problematic mobile phone use and addiction across generations: The roles of psychopathological symptoms and smartphone use. J Technol Behav Sci 2018; 3(3): 141-9.
[http://dx.doi.org/10.1007/s41347-017-0041-3] [PMID: 30238057]
[71]
Kwon M, Lee JY, Won WY, et al. Development and validation of a smartphone addiction scale (SAS). PLoS One 2013; 8(2): e56936.
[http://dx.doi.org/10.1371/journal.pone.0056936] [PMID: 23468893]
[72]
Seo DG, Park Y, Kim MK, Park J. Mobile phone dependency and its impacts on adolescents’ social and academic behaviors. Comput Human Behav 2016; 63: 282-92.
[http://dx.doi.org/10.1016/j.chb.2016.05.026]
[73]
Hs AH, Hidayat B. Solusi Gangguan Smartphone Addiction Berdasarkan Pendekatan Psikologi Islam. Al-Hikmah J Agama dan Ilmu Pengetah 2021; 18(1): 65-78.
[http://dx.doi.org/10.25299/al-hikmah:jaip.2021.vol18(1).6652]
[74]
Subramaniam S, Dhillon JS, Kah Hoe AC, Shanmugam M, Gunasekaran SS. Evaluating smartphone addiction disorder among university students. Int Conf Inf Technol Multimedia ICIMU 2020; 2020: 348-53.
[http://dx.doi.org/10.1109/ICIMU49871.2020.9243566]
[75]
Rathakrishnan B, Bikar Singh SS, Kamaluddin MR, et al. Smartphone addiction and sleep quality on academic performance of university students: An exploratory research. Int J Environ Res Public Health 2021; 18(16): 8291.
[http://dx.doi.org/10.3390/ijerph18168291] [PMID: 34444042]
[76]
Kwon M, Kim D-J, Cho H, Yang S. The smartphone addiction scale: Development and validation of a short version for adolescents. PLoS One 2013; 8(12): e83558.
[http://dx.doi.org/10.1371/journal.pone.0083558] [PMID: 24391787]
[77]
Kopecký K, Fernández-Martín F-D, Szotkowski R, Gómez-García G, Mikulcová K. Behaviour of children and adolescents and the use of mobile phones in primary schools in the Czech Republic. Int J Environ Res Public Health 2021; 18(16): 8352.
[http://dx.doi.org/10.3390/ijerph18168352] [PMID: 34444102]
[78]
Vintilă M, Tudorel OI, Goian C, Bărbat C. Determining the structure of smartphone addiction scale: A bifactor model analysis. Curr Psychol 2021; 40: 1107-14.
[http://dx.doi.org/10.1007/s12144-018-0035-0]
[79]
Buysse DJ, Reynolds CF III, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Res 1989; 28(2): 193-213.
[http://dx.doi.org/10.1016/0165-1781(89)90047-4] [PMID: 2748771]
[80]
Pavia L, Cavani P, Di Blasi M, Giordano C. Smartphone Addiction Inventory (SPAI): Psychometric properties and confirmatory factor analysis. Comput Human Behav 2016; 63: 170-8.
[http://dx.doi.org/10.1016/j.chb.2016.05.039]
[81]
Lin Y-H, Chang L-R, Lee Y-H, Tseng H-W, Kuo TBJ, Chen S-H. Development and validation of the Smartphone Addiction Inventory (SPAI). PLoS One 2014; 9(6): e98312.
[http://dx.doi.org/10.1371/journal.pone.0098312] [PMID: 24896252]
[82]
Chen SH, Weng LJ, Su YJ, Wu HM, Yang PF. Development of Chinese Internet Addiction Scale and its psychometric study. Chin J Psychol 2003; 2003: 279-94.
[83]
Al Qudah MF, Albursan IS, Hammad HI, et al. Anxiety about COVID-19 infection, and its relation to smartphone addiction and demographic variables in Middle Eastern Countries. Int J Environ Res Public Health 2021; 18(21): 11016.
[http://dx.doi.org/10.3390/ijerph182111016] [PMID: 34769539]
[84]
Diksha G. Development, standardization of a scale to measure smartphone addiction among college students. Int J Educ Sci Res 2018; 2018: 149644742.
[http://dx.doi.org/10.24247/ijesrfeb201813]
[85]
Saadika K. Does smartphone connectivity impact on undergraduate dental studnets. Environ Stress 2018; 2018: 228-33.
[86]
Kibona L, Mgaya G. Smartphones’ Effects on Academic Performance of Higher Learning Students. J Multidiscip Eng Sci Technol 2015; 2(4): 3159-40.
[87]
Felisoni DD, Godoi AS. Cell phone usage and academic performance: An experiment. Comput Educ 2018; 117: 175-87.
[http://dx.doi.org/10.1016/j.compedu.2017.10.006]
[88]
Bianchi A, Phillips JG, Thang MP. Mobile Phone Problem Use Scale. Cyberpsychol Behav 2005; 8: 39-51.
[http://dx.doi.org/10.1089/cpb.2005.8.39]
[89]
Chen L, Yan Z, Tang W, Yang F, Xie X, He J. Mobile phone addition levels and negative emotions among Chinese young adults: The mediating role of interpersonal problems. Comput Human Behav 2016; 55: 856-66.
[http://dx.doi.org/10.1016/j.chb.2015.10.030]
[90]
Demirci K, Akgönül M, Akpinar A. Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. J Behav Addict 2015; 4(2): 85-92.
[http://dx.doi.org/10.1556/2006.4.2015.010] [PMID: 26132913]
[91]
Utami AN. The negative impact of smartphone use addiction on the personal academic aspects of adolescents. Perspekt Ilmu Pendidik 2019; 33(1): 1-14.
[http://dx.doi.org/10.21009/PIP.331.1]
[92]
Tugtekin U, Barut Tugtekin E, Kurt AA, Demir K. Associations between fear of missing out, problematic smartphone use, and social networking services fatigue among young adults. Soc Media Soc 2020; 6(4): 2-17.
[http://dx.doi.org/10.1177/2056305120963760]
[93]
Uri D, Hatch KE. Determining the effects of technology on children. Sage 2011; 6(4): 2-17.
[94]
Park C, Park YR. The Conceptual Model on Smart Phone Addiction among Early Childhood. Int J Soc Sci Humanit 2014; 4(2): 147-50.
[http://dx.doi.org/10.7763/IJSSH.2014.V4.336]
[95]
Kushlev K, Dunn EW. Smartphones distract parents from cultivating feelings of connection when spending time with their children. JSPR 2019; 36(6): 1619-39.
[http://dx.doi.org/10.1177/0265407518769387]
[96]
Chiu CT, Chang YH, Chen CC, Ko MC, Li CY. Mobile phone use and health symptoms in children. J Formos Med Assoc 2015; 114(7): 598-604.
[http://dx.doi.org/10.1016/j.jfma.2014.07.002] [PMID: 25115529]
[97]
Lauricella AR, Wartella E, Rideout VJ. Young children’ s screen time : The complex role of parent and child factors. J Appl Dev Psychol 2015; 36: 11-7.
[http://dx.doi.org/10.1016/j.appdev.2014.12.001]
[98]
Kushlev K, Hunter JF, Proulx J, Pressman SD, Dunn E. Computers in Human Behavior Smartphones reduce smiles between strangers. Comput Human Behav 2019; 91(2018): 12-6.
[http://dx.doi.org/10.1016/j.chb.2018.09.023]
[99]
Arribas P, Sánchez P. We are IntechOpen, the world ’ s leading publisher of Open Access books Built by scientists, for scientists 12. Seman Scholor 2012; 2012: 13800674.
[100]
Philosophy L, Rather M. Impact of Smartphones on Young Generation DigitalCommons @ University of Nebraska - Lincoln Impact of Smartphones on Young Generation 2019; 2019: 2384.
[101]
Kim H, Min J-Y, Kim H-J, Min K-B. Association between psychological and self- assessed health status and smartphone overuse among Korean college students Association between psychological and self-assessed health status and smartphone overuse among Korean college students. J Ment Health 2017; 2017: 1370641.
[http://dx.doi.org/10.1080/09638237.2017.1370641] [PMID: 28868959]
[102]
Taywade A. Gender differences in smartphone usage patterns of adolescents 2019.
[103]
Fischer-Grote L, Kothgassner OD, Felnhofer A. Risk factors for problematic smartphone use in children and adolescents: A review of existing literature. Neuropsychiatrie 2019; 33(4): 179-90.
[http://dx.doi.org/10.1007/s40211-019-00319-8]
[104]
Wu AMS, Cheung VI, Ku L, Hung EPW. Psychological risk factors of addiction to social networking sites among Chinese smartphone users. J Behav Addict 2013; 2(3): 160-6.
[http://dx.doi.org/10.1556/JBA.2.2013.006] [PMID: 25215198]
[105]
Osorio-Molina C, Martos-Cabrera MB, Membrive-Jiménez MJ, et al. Smartphone addiction, risk factors and its adverse effects in nursing students: A systematic review and meta-analysis. Nurse Educ Today 2021; 98: 104741.
[http://dx.doi.org/10.1016/j.nedt.2020.104741] [PMID: 33485161]
[106]
Liu S, Xiao T, Yang L, Loprinzi PD. Exercise as an alternative approach for treating smartphone addiction: A systematic review and meta-analysis of random controlled trials. Int J Environ Res Public Health 2019; 16(20): E3912.
[http://dx.doi.org/10.3390/ijerph16203912] [PMID: 31618879]
[107]
Malinauskas R, Malinauskiene V. A meta-analysis of psychological interventions for Internet/smartphone addiction among adolescents. J Behav Addict 2019; 8(4): 613-24.
[http://dx.doi.org/10.1556/2006.8.2019.72] [PMID: 31891316]
[108]
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.
[PMID: 25709785]
[109]
Lu X, Watanabe J, Liu Q, Uji M, Shono M, Kitamura T. Internet and mobile phone text-messaging dependency: Factor structure and correlation with dysphoric mood among Japanese adults. Comput Human Behav 2011; 27(5): 1702-9.
[http://dx.doi.org/10.1016/j.chb.2011.02.009]
[110]
Bian M, Leung L. Linking loneliness, shyness, smartphone addiction symptoms, and patterns of smartphone use to social capital. Soc Sci Comput Rev 2015; 2015: 61-79.
[http://dx.doi.org/10.1177/0894439314528779]
[111]
Deshpande A. Mobile Addiction and associated factors amongst youth. Indian J Ment Heal 2015; 2(3): 244.
[http://dx.doi.org/10.30877/IJMH.2.3.2015.244-248]
[112]
Repacholi MH. Health risks from the use of mobile phones. Toxicol Lett 2001; 120(1-3): 323-31.
[http://dx.doi.org/10.1016/S0378-4274(01)00285-5]
[113]
Zhao TY, Zou SP, Knapp PE. Exposure to cell phone radiation up-regulates apoptosis genes in primary cultures of neurons and astrocytes. Neurosci Lett 2007; 412(1): 34-8.
[http://dx.doi.org/10.1016/j.neulet.2006.09.092] [PMID: 17187929]
[114]
Kim JH, Lee JK, Kim HG, Kim KB, Kim HR. Possible effects of radiofrequency electromagnetic field exposure on central nerve system. Biomol Ther (Seoul) 2019; 27(3): 265-75.
[http://dx.doi.org/10.4062/biomolther.2018.152] [PMID: 30481957]
[115]
Kesari KK, Siddiqui MH, Meena R, Verma HN, Kumar S. Cell phone radiation exposure on brain and associated biological systems. Indian J Exp Biol 2013; 51(3): 187-200.
[116]
Hardell L, Carlberg M, Hansson Mild K. Use of cellular telephones and brain tumour risk in urban and rural areas. Occup Environ Med 2005; 62(6): 390-4.
[http://dx.doi.org/10.1136/oem.2004.017434] [PMID: 15901886]
[117]
Hardell L, Carlberg M, Söderqvist F, Mild KH, Morgan LL. Long-term use of cellular phones and brain tumours: Increased risk associated with use for > or =10 years. Occup Environ Med 2007; 64(9): 626-32.
[http://dx.doi.org/10.1136/oem.2006.029751] [PMID: 17409179]
[118]
Bortkiewicz A, Gadzicka E, Szymczak W. Mobile phone use and risk for intracranial tumors and salivary gland tumors - A meta-analysis. Int J Occup Med Environ Health 2017; 30(1): 27-43.
[http://dx.doi.org/10.13075/ijomeh.1896.00802] [PMID: 28220905]
[119]
Hardell L, Carlberg M, Söderqvist F, Mild KH. Case-control study of the association between malignant brain tumours diagnosed between 2007 and 2009 and mobile and cordless phone use. Int J Oncol 2013; 43(6): 1833-45.
[http://dx.doi.org/10.3892/ijo.2013.2111] [PMID: 24064953]
[120]
Myung SK, Ju W, McDonnell DD, et al. Mobile phone use and risk of tumors: A meta-analysis. J Clin Oncol 2009; 27(33): 5565-72.
[http://dx.doi.org/10.1200/JCO.2008.21.6366] [PMID: 19826127]
[121]
Swerdlow AJ, Feychting M, Green AC, Leeka Kheifets LK, Savitz DA. Mobile phones, brain tumors, and the interphone study: Where are we now? Environ Health Perspect 2011; 119(11): 1534-8.
[http://dx.doi.org/10.1289/ehp.1103693] [PMID: 22171384]
[122]
Repacholi MH, Lerchl A, Röösli M, et al. Systematic review of wireless phone use and brain cancer and other head tumors. Bioelectromagnetics 2012; 33(3): 187-206.
[http://dx.doi.org/10.1002/bem.20716] [PMID: 22021071]
[123]
Coureau G, Bouvier G, Lebailly P, et al. Mobile phone use and brain tumours in the CERENAT case-control study. Occup Environ Med 2014; 71(7): 514-22.
[http://dx.doi.org/10.1136/oemed-2013-101754] [PMID: 24816517]
[124]
Correction: Mobile phone use and incidence of brain tumour histological types, grading or anatomical location: A population-based ecological study. BMJ Open 2018; 8: e024489.
[http://dx.doi.org/10.1136/bmjopen-2018-024489]
[125]
Röösli M, Lagorio S, Schoemaker MJ, Schüz J, Feychting M. Brain and salivary gland tumors and mobile phone use: Evaluating the evidence from various epidemiological study designs. Annu Rev Public Health 2019; 40: 221-38.
[http://dx.doi.org/10.1146/annurev-publhealth-040218-044037] [PMID: 30633716]
[126]
Benson VS, Pirie K, Schüz J, Reeves GK, Beral V, Green J. Mobile phone use and risk of brain neoplasms and other cancers: Prospective study. Int J Epidemiol 2013; 42(3): 792-802.
[http://dx.doi.org/10.1093/ije/dyt072] [PMID: 23657200]
[127]
Sato Y, Kiyohara K, Kojimahara N, Yamaguchi N. Time trend in incidence of malignant neoplasms of the central nervous system in relation to mobile phone use among young people in Japan. Bioelectromagnetics 2016; 37(5): 282-9.
[http://dx.doi.org/10.1002/bem.21982] [PMID: 27197787]
[128]
Bin Heyat B. A review on neurological disorder epilepsy affected in the human body. iAEMR 2016; 3: 1-4.
[129]
Dubey RB, Hanmandlu M, Gupta SK. Risk of brain tumors from wireless phone use. J Comput Assist Tomogr 2010; 34(6): 799-807.
[http://dx.doi.org/10.1097/RCT.0b013e3181ed9b54] [PMID: 21084892]
[130]
Wang H, Zhang X. Magnetic fields and reactive Oxygen Species. Int J Mol Sci 2017; 18(10): 2175.
[http://dx.doi.org/10.3390/ijms18102175] [PMID: 29057846]
[131]
Scaiano JC, Mohtat N, Cozens FL, McLean J, Thansandote A. Application of the radical pair mechanism to free radicals in organized systems: Can the effects of 60 Hz be predicted from studies under static fields? Bioelectromagnetics 1994; 15(6): 549-54.
[http://dx.doi.org/10.1002/bem.2250150608] [PMID: 7880168]
[132]
de Vries HE, Kuiper J, de Boer AG, Van Berkel TJC, Breimer DD. The blood-brain barrier in neuroinflammatory diseases. Pharmacol Rev 1997; 49(2): 143-55.
[PMID: 9228664]
[133]
Frey AH. Headaches from cellular telephones: Are they real and what are the implications? Environ Health Perspect 1998; 106(3): 101-3.
[http://dx.doi.org/10.1289/ehp.98106101] [PMID: 9441959]
[134]
Arendash GW, Sanchez-Ramos J, Mori T, et al. Electromagnetic field treatment protects against and reverses cognitive impairment in Alzheimer’s disease mice. J Alzheimers Dis 2010; 19(1): 191-210.
[http://dx.doi.org/10.3233/JAD-2010-1228] [PMID: 20061638]
[135]
Terzi M, Ozberk B, Deniz OG, Kaplan S. The role of electromagnetic fields in neurological disorders. J Chem Neuroanat 2016; 75(Pt B): 77-84.
[http://dx.doi.org/10.1016/j.jchemneu.2016.04.003] [PMID: 27083321]
[136]
Houston BJ, Nixon B, King BV, De Iuliis GN, Aitken RJ. The effects of radiofrequency electromagnetic radiation on sperm function. Reproduction 2016; 152(6): R263-76.
[http://dx.doi.org/10.1530/REP-16-0126] [PMID: 27601711]
[137]
Saini R, Saini S, Sharma S. Neurological dysfunction and mobile phones. J Neurosci Rural Pract 2010; 1(1): 57-8.
[http://dx.doi.org/10.4103/0976-3147.63110] [PMID: 21799627]
[138]
Shoukat S. Cell phone addiction and psychological and physiological health in adolescents. EXCLI J 2019; 18: 47-50.
[http://dx.doi.org/10.17179/excli2018-2006] [PMID: 30956638]
[139]
Oral B, Guney M, Ozguner F, et al. Endometrial apoptosis induced by a 900-MHz mobile phone: Preventive effects of vitamins E and C. Adv Ther 2006; 23(6): 957-73.
[http://dx.doi.org/10.1007/BF02850217] [PMID: 17276964]
[140]
Balci M, Devrim E, Durak I. Effects of mobile phones on oxidant/antioxidant balance in cornea and lens of rats. Curr Eye Res 2007; 32(1): 21-5.
[http://dx.doi.org/10.1080/02713680601114948] [PMID: 17364731]
[141]
Henschenmacher B, Bitsch A, de Las Heras Gala T, et al. The effect of radiofrequency electromagnetic fields (RF-EMF) on biomarkers of oxidative stress in vivo and in vitro: A protocol for a systematic review. Environ Int 2022; 158: 106932.
[http://dx.doi.org/10.1016/j.envint.2021.106932] [PMID: 34662800]
[142]
Desai NR, Kesari KK, Agarwal A. Pathophysiology of cell phone radiation: Oxidative stress and carcinogenesis with focus on male reproductive system. Reprod Biol Endocrinol 2009; 7: 114.
[http://dx.doi.org/10.1186/1477-7827-7-114] [PMID: 19849853]
[143]
Leszczynski D, Joenväärä S, Reivinen J, Kuokka R. Non-thermal activation of the hsp27/p38MAPK stress pathway by mobile phone radiation in human endothelial cells: Molecular mechanism for cancer- and blood-brain barrier-related effects. Differentiation 2002; 70(2-3): 120-9.
[http://dx.doi.org/10.1046/j.1432-0436.2002.700207.x] [PMID: 12076339]
[144]
van Eck NJ, Waltman L. Measuring Scholarly Impact: Methods and Practice. Cham: Springer 2014.
[145]
van Eck NJ, Waltman L, van Eck NJ, Waltman L. Visualizing Bibliometric Networks. Cham: Springer 2014; pp. 285-320.
[146]
Pal R, Heyat MB, You Z, et al. Effect of Maha Mrityunjaya HYMN recitation on human brain for the analysis of single EEG Channel C4-A1 using machine learning classifiers on yoga practitioner. Int Comput Conf Wavelet Active Media Technol Inform Proc (ICCWAMTIP) 2020; 2020: 89-92.
[http://dx.doi.org/10.1109/ICCWAMTIP51612.2020.9317384]
[147]
Bin Heyat MB, Akhtar F, Khan A, et al. A novel hybrid machine learning classification for the detection of Bruxism patients using physiological signals. Appl Sci (Basel) 2020; 10(21): 7410.
[http://dx.doi.org/10.3390/app10217410]
[148]
Lai D, Bin Heyat MB, Khan FI, Zhang Y. Prognosis of sleep Bruxism using power spectral density approach applied on EEG signal of both EMG1-EMG2 and ECG1-ECG2 channels. IEEE Access 2019; 7: 82553-62.
[http://dx.doi.org/10.1109/ACCESS.2019.2924181]
[149]
Teelhawod BN, Akhtar F, Heyat MB, et al. Machine learning in E-health: A Comprehensive Survey of Anxiety. International Conference on Data Analytics for Business and Industry (ICDABI). 25-26 Oct. 2021 Sakheer, Bahrain ; pp. 167-72.
[http://dx.doi.org/10.1109/ICDABI53623.2021.9655966]
[150]
AlShorman O, Masadeh M, Alzyoud A, Bin Heyat MB, Akhtar F. The effects of emotional stress on learning and memory cognitive functions: An eeg review study in education. Sixth Int Conf e- Learn (econf) 2020; 2020: 177-82.
[http://dx.doi.org/10.1109/econf51404.2020.9385468]
[151]
Chola C, Heyat MB, Akhtar F, et al. IoT based intelligent computer-aided diagnosis and decision making system for health care. Int Conf Inform Technol (ICIT) 2021; 2021: 184-9.
[http://dx.doi.org/10.1109/ICIT52682.2021.9491707]
[152]
Bin Heyat MB, Lai D, Khan FI, Zhang Y. Sleep Bruxism detection using decision tree method by the combination of C4-P4 and C4-A1 channels of scalp EEG. IEEE Access 2019; 7: 102542-53.
[http://dx.doi.org/10.1109/ACCESS.2019.2928020]
[153]
Lai D, Zhang X, Zhang Y, Bin Heyat MB. Convolutional neural network based detection of atrial fibrillation combing R-R intervals and F-wave Frequency Spectrum. Annu Int Conf IEEE Eng Med Biol Soc 2019; 2019: 4897-900.
[http://dx.doi.org/10.1109/EMBC.2019.8856342]
[154]
Ukwuoma CC, Zhiguang Q, Bin Heyat MB, Ali L, Almaspoor Z, Monday HN. Recent advancements in fruit detection and classification using deep learning techniques. Math Probl Eng 2022; 2022: 1-29.
[http://dx.doi.org/10.1155/2022/9210947]
[155]
Ukwuoma CC, Heyat MB, Masadeh M, et al. Image inpainting and classification agent training based on reinforcement learning and generative models with attention mechanism. In: International Conference on Microelectronics (ICM). New Cairo City, Egypt 19-22 Dec. 2021; pp. 96-101.
[http://dx.doi.org/10.1109/ICM52667.2021.9664950]
[156]
Iqbal MS, Abbasi R, Heyat MB, et al. Recognition of mRNA N4 Acetylcytidine (ac4C) by using non-deep vs. deep learning. Appl Sci (Basel) 2022; 12(3): 1-16.
[http://dx.doi.org/10.3390/app12031344]

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