Teaching Metacognitive strategies on Metacognitive Behavior and Internet Self-Efficacy of Female Students at Risk of Internet Addiction during the COVID-19
DOI:
https://doi.org/10.22100/ijhs.v8i3.927Keywords:
Teaching metacognitive strategies, Metacognitive Behavior, Internet Self-Efficacy,, Female students, Internet addictionAbstract
Background: Adolescents, for whom the Internet is an indispensable part of their daily life, are the most significant group at risk of Internet addiction. The objective of this study was to investigate the effectiveness of metacognitive strategies on metacognitive behavior and internet self-efficacy of female students at risk of Internet addiction during the COVID-19.
Methods: The present research was quasi-experimental with pretest-posttest design with a control group. The statistics population for the academic year 2020-2021 comprised all secondary schools' females in Tehran's 15 district. In this study, purposeful sampling process was applied. Primarily, one school (Ebne Sina) was randomly selected from the secondary schools of region 15 in Tehran, in the second grade. Three classes were chosen from each grade in the form of Lottery and among 360 students, 30 students who were most at risk for internet addiction were randomly selected and assigned in the experimental (n=15) and control (n=15) groups via shad application. The experimental group received metacognitive strategies training for 8 treatment sessions (90 minutes for each session). The data were analyzed with SPSS-23 and analysis of covariance (ANCOVA).
Results: Mean and SD of age in the Transactional Analysis and the control groups were 15.87 ± 0.734 and 16±0.816, respectively. Moreover, our findings showed that the experimental and control groups differ significantly in their metacognitive behavior (p =0.01and F=55.349) and internet use self-efficacy during pretest control (p =0.01 and F=43.573).
Conclusions: The result of our study showed that metacognitive strategies had significant effects on Metacognitive Behavior and Internet self-efficacy of female students at risk of Internet addiction during the COVID-19. Therefore, psychological group therapy could be suggested to improve metacognitive behavior and increase internet self-efficacy and thus reduce behavioral and social damages.
keywords: Teaching metacognitive strategies, Metacognitive Behavior, Internet Self-Efficacy, Female students, Internet addiction
References
2. Servidio R, Bartolo MG, Palermiti AL, Costabile A. Fear of COVID-19, depression, anxiety, and their association with Internet addiction disorder in a sample of Italian students. Journal of Affective Disorders Reports. 2021; 4:100097.
3. Kar SK, Arafat SY, Sharma P, Dixit A, Marthoenis M, Kabir R. COVID-19 pandemic and addiction: Current problems and future concerns. Asian journal of psychiatry. 2020; 51:102064. doi: 10.1016/j.ajp.2020.102064.
4. Lin MP. Prevalence of internet addiction during the COVID-19 outbreak and its risk factors among junior high school students in Taiwan. International journal of environmental research and public health. 2020 Jan;17(22):8547. doi: 10.3390/ijerph17228547
5. Varma R, Das S, Singh T. Cyberchondria amidst COVID-19 pandemic: Challenges and management Strategies. Frontiers in psychiatry. 2021; 12:399. doi:10.3389/fpsyt.2021.618508
6. Wells A. Advances in metacognitive therapy. International Journal of Cognitive Therapy. 2013 Jun;6(2):186-201. doi:10.1521/ijct.2013.6.2.186
7. Akbari M. Metacognitions or distress intolerance: The mediating role in the relationship between emotional dysregulation and problematic internet use. Addictive Behaviors Reports. 2017 Dec 1; 6:128-33. doi:10.1016/j.abrep.2017.10.004
8. Spada MM, Marino C. Metacognitions and emotion regulation as predictors of problematic internet use in adolescents. Clinical Neuropsychiatry. 2017 Feb 1;14(1):59-63. https://openresearch.lsbu.ac.uk/item/870q1
9. Monacis L, Griffiths MD, Limone P, Sinatra M, Servidio R. Selfitis behavior: Assessing the Italian version of the Selfitis Behavior Scale and its mediating role in the relationship of dark traits with social media addiction. International journal of environmental research and public health. 2020 Jan;17(16):5738. doi:10.3390/ijerph17165738
10. Marci T, Marino C, Sacchi C, Lan X, Spada MM. Problematic Internet Use in early adolescence: The role of attachment and negative beliefs about worry. Journal of Behavioral Addictions. 2021 Apr 16;10(1):194-200. doi:10.1556/2006.2021.00001
11. Bogdanovskaya I, Koroleva N, Khodakovskaia O, Provorova A, Uglova A, Alekhin A. Metacognitive Strategy of students with Problematic Internet Use. InIMS 2020 (pp. 350-361). http://ceur-ws.org/Vol-2813/rpaper27.pdf
12. Caselli G, Marino C, Spada MM. Modelling online gaming metacognitions: The role of time spent gaming in predicting problematic Internet use. Journal of Rational-Emotive & Cognitive-Behavior Therapy. 2021;39(2):172-82. doi:10.1007/s10942-020-00365-0
13. Spada MM, Langston B, Nikčević AV, Moneta GB. The role of metacognitions in problematic Internet use. Computers in human behavior. 2008;24(5):2325-35. doi: 10.1016/j.chb.2007.12.002
14. Craparo G, Messina R, Severino S, Fasciano S, Cannella V, Gori A, Cacioppo M, Baiocco R. The relationships between self-efficacy, internet addiction and shame. Indian journal of psychological medicine. 2014 Jul;36(3):304-7. doi:10.4103/0253-7176.135386
15. Asdolahzadeh P, Sadeghi J, Abbasi Esfajir A. Modeling the Structural Equations of Mode Metacognition with a Tendency to Cyberspace Mediated by Self-efficacy in Gifted Students. Iranian journal of educational sociology. 2021 Aug 10;4(2):14-23. http://iase-idje.ir/files/site1/user_files_6d0946/saadeghi-A-10-724-1-df6570e.pdf
16. Chuang SC, Lin FM, Tsai CC. An exploration of the relationship between Internet self-efficacy and sources of Internet self-efficacy among Taiwanese university students. Computers in Human Behavior. 2015 Jul 1; 48:147-55. doi:10.1016/j.chb.2015.01.044
17. Kaur M, Kaur A. Construction and Standardization of Internet Self-Efficacy Scale for Secondary School Students. Int J Edu Sci. 2018 Jan 1;20(1-3):1-8. doi:10.1080/09751122.2017.1408453
18. Mosalanejad L, Ghobadifar MA. Analysis of Internet Addiction and its Relation to Metacognitive Beliefs among University Students. Middle East journal of psychiatry and Alzheimer. 2013;4. 13-19. doi:10.5742/MEJPA.2013.43317.
19. Karpov AA, Karpov AV, Karabushchenko NB, Ivashchenko AV. The interconnection of learning ability and the organization of metacognitive processes and traits of personality. Psychology in Russia. 2017;10(1):181. doi:10.11621/pir.2017.0105
20. Eastin, M.S.; LaRose, R. Internet self-efficacy and the psychology of the digital divide. J. Comput. Commun. 2000, 6, JCMC611.
21. Luo, Z.H.; Wan, J.J.; Liu, Q.X.; Fang, X.Y. The relationship of Internet use, Internet special self-efficacy and Internet addiction in university students. Psychol. Dev. Educ. 2010, 26, 618–626
22. Mohammadsalehi N, mohmmadbeigi A, Jadidi R, Anbari Z, et al. Psychometric Properties of Persian Language Version of Yang Internet Addiction Questionnaire; an Explanatory Factor Analysis. International Journal of High Risk Behaviors and Addiction. 2015 Accepted.
23. Dargahi H, Razavi S. Internet addiction and its related factors: a study of an Iranian Population. Payesh.2007
24. Young KS. Internet addiction: The emergence of a new clinical disorder. CyberPsychology & Behavior. 2000;5(2):151–159.
25. Zhou H, Dang L, Lam LW, Zhang MX, Wu AM. A cross-lagged panel model for testing the bidirectional relationship between depression and smartphone addiction and the influences of maladaptive metacognition on them in Chinese adolescents. Addictive Behaviors. 2021 Sep 1; 120:106978. doi: 10.1016/j.addbeh.2021.106978.
26. Lee SY, Kim MS, Lee HK. Prevention strategies and interventions for internet use disorders due to addictive behaviors based on an integrative conceptual model. Current Addiction Reports. 2019 Sep;6(3):303-12. doi: 10.1007/s40429-019-00265-z
27. Geng J, Han L, Gao F, Jou M, Huang CC. Internet addiction and procrastination among Chinese young adults: A moderated mediation model. Computers in Human Behavior. 2018 Jul 1; 84:320-33.
28. Wu CY, Lee MB, Liao SC, Chang LR. Risk factors of internet addiction among internet users: an online questionnaire survey. PloS one. 2015;10(10):e0137506. doi: 10.1371/journal.pone.0137506
29. Moradi S, Yeganeh T, Najafi K, Abolghasemi A, Haghparast N. The Role of Cognitive Failure, Innovation and Risk-Taking in Explanation of Internet Addiction. Journal of Health and Care. 2017 Sep 10;19(2):177-88.
30. Abchar B, Qara Bigloo H. Analysis of the role of using cognitive and metacognitive strategies on the academic performance of students of Khorramshahr University of Science and Technology. Quarterly Journal of Management on Disciplinary Education, 1399; 1399 (50): 164-184. http://journals.police.ir/article_94000_0bd4d201a2c9ee628777eb9045c4a15c.pdf
31. Liang JC, Tsai CC. Internet self-efficacy and preferences toward constructivist Internet-based learning environments: A study of pre-school teachers in Taiwan. Journal of Educational Technology & Society. 2008 Jan 1;11(1):226-37.
32. Cera R, Mancini M, Antonietti A. Relationships between metacognition, self-efficacy and self-regulation in learning. Journal of Educational, Cultural and Psychological Studies (ECPS Journal). 2013 Jul 1;4(7):115-41. doi:10.7358/ecps-2013-007-cera
Published
Issue
Section
License
The Copyright Form should be downloaded and signed by corresponding author in the fourth step "upload supplementary files" during submission process.
After acceptance, copyright form should be downloaded and signed by all authors one by one ( "summery --> supp. file" part and click on "add a supplementary file" link).