Hostname: page-component-76fb5796d-skm99 Total loading time: 0 Render date: 2024-04-26T19:26:34.866Z Has data issue: false hasContentIssue false
  • English
  • Français

Effects of Self-Management Training on Smartphone Dependence in Low to Moderate Adolescent Males’ Users

Published online by Cambridge University Press:  26 May 2022

Mostafa Motamedi Heravi Open the ORCID record for Mostafa Motamedi Heravi [Opens in a new window] ,
Shahla Khosravan ,
Aeen Mohammadi  and
Mohammad Reza Mansoorian
Mostafa Motamedi Heravi
Affiliation:
Department of community Health Nursing, Neyshabur University of Medical Sciences, Neyshabur, Iran
Shahla Khosravan
Affiliation:
Department of Community Health Nursing and Management, Nursing Faculty, Nursing Research Center, Gonabad University of Medical Sciences, Gonabad, Iran
Aeen Mohammadi
Affiliation:
Department of eLearning in Medical Education, Virtual School, Tehran University of Medical Sciences, Tehran, Iran
Mohammad Reza Mansoorian*
Affiliation:
Department of Community Health Nursing and Management, Nursing Faculty, Nursing Research Center, Gonabad University of Medical Sciences, Gonabad, Iran
*
*Corresponding author: Mohammad Reza Mansoorian, Department of Community Health Nursing and Management Nursing, Nursing Faculty, Nursing Research Center, Gonabad University of Medical Sciences, Asian Road, Gonabad, Khorasan Razavi, Iran. Email: mansoorian.ir@gmail.com
Get access

Abstract

While taking advantage of the educational benefits of smartphones, students also apply this device in inappropriate ways that cause certain disciplinary and educational problems. This study examines the effect of self-management training on smartphone dependence among male high school students. Methods: In this quasi-experimental study, data were collected using the Cell Phone Addiction Scale (Koo, 2009), which was completed by the trial and control groups before and after the educational intervention. After assessing their normal distribution, the data were analysed using the Chi-square test, the independent and paired t-tests, Mann–Whitney's U-test, and the Wilcoxon test at a significance level of p < .05. Results: The results showed significant post-intervention reductions in the mean score of smartphone dependence (35.10) and its three domains, including withdrawal/tolerance (14.80), life dysfunction (8.70), and compulsion/persistence (11.60), in the trial group compared to the controls (44.80, 16.2, 12.10, and 16.50) and also in the mean score of certain applications of smartphones (p < .05). Discussion and conclusions: Despite the existing limitations, the results confirmed the efficacy of self-management training in reducing smartphone dependence in the students. The implementation of this programme is recommended for reducing dependence and promoting the proper use of this device.

Keywords

dependenceself-management educationsmartphonehigh school student
Type
Standard Paper
Information
Behaviour Change , Volume 40 , Issue 1 , April 2023 , pp. 67 - 75
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of the Australian Association for Cognitive and Behaviour Therapy

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alizadeh-Navaei, R and Hosseini, SH (2014). Mental health status of Iranian students until 2011: A systematic review. Journal of Clinical Excellence, 2, 1–10. Retrieved from: http://ce.mazums.ac.ir/article-1-75-fa.htm (in Persian).Google Scholar
Amiri, N and Habibzade, A (2016). Analysis of the virtual social networks (based on SWOT). Rahborde Ejtemaei Farhangi, 5, 7–35. Retrieved from: https://www.sid.ir/fa/journal/JournalListPaper.aspx?ID=56876 (in Persian).Google Scholar
Anie, KA, Green, J, Tata, P, Fotopoulos, CE, Oni, L and Davies, SC (2002). Self-help manual-assisted cognitive behavioural therapy for sickle cell disease. Behavioural and Cognitive Psychotherapy, 30, 451–458. doi:10.1017/S135246580200406X.CrossRefGoogle Scholar
Chiu, S-I (2014). The relationship between life stress and smartphone addiction on Taiwanese university student: A mediation model of learning self-efficacy and social self-efficacy. Computers in Human Behavior, 34, 49–57. doi:10.1016/j.chb.2014.01.024.CrossRefGoogle Scholar
Choi, NY and Han, Eg (2006). Predictors of children's and adolescents’ game addiction: Impulsivity, communication with parents and expectation about the internet games. Journal of Korean Home Management Association, 24, 209–219. Retrieved from: http://www.koreascience.or.kr/article/ArticleFullRecord.jsp?cn=GJGRBW_2006_v24n2s80_209Google Scholar
Dekovic, M (1999). Risk and protective factors in the development of problem behavior during adolescence. Journal of Youth and Adolescence, 28, 667–685.doi:10.1023/A:1021635516758.CrossRefGoogle Scholar
Delavar, Z and Karimi, F (2016). The effect of teaching time management on self-directed learning in the first grade of second cycle of secondary school girl's students. Research in Curriculum Planning, 12, 158–167. Retrieved from: http://jsr-e.khuisf.ac.ir/article_534408_b7c0788db6069544d7ec060aa6e3348b.pdf (in Persian).Google Scholar
Diamantes, T (2010). Recent court rulings regarding student use of cell phones in today's schools. Education, 131, 404–407. Retrieved from: https://eric.ed.gov/?id=EJ930611.Google Scholar
Haug, S, Castro, RP, Kwon, M, Filler, A, Kowatsch, T and Schaub, MP (2015). Smartphone use and smartphone addiction among young people in Switzerland. Journal of Behavioral Addiction, 4, 299–307. doi:10.1556/2006.4.2015.037.CrossRefGoogle ScholarPubMed
Inyang, I, Benke, G, Dimitriadis, C, Simpson, P, McKenzie, R and Abramson, M (2010). Predictors of mobile telephone use and exposure analysis in Australian adolescents. Journal of Paediatrics and Child Health, 46, 226–233. doi:10.1111/j.1440-1754.2009.01675.x.CrossRefGoogle ScholarPubMed
Jonkman, NH, Schuurmans, MJ, Jaarsma, T, Shortridge-Baggett, LM, Hoes, AW and Trappenburg, JC (2016). Self-management interventions: Proposal and validation of a new operational definition. Journal of Clinical Epidemiology, 80, 34–42. doi:10.1016/j.jclinepi.2016.08.001.CrossRefGoogle ScholarPubMed
Jordan, A, Trentacoste, N, Henderson, V, Manganello, J and Fishbein, M (2007). Measuring the time teens spend with media: Challenges and opportunities. Media Psychology, 9, 19–41.CrossRefGoogle Scholar
Khalili, L (2015). Use of social networks by university students. Human Information Interaction, 2, 59–73. Retrieved from: http://hii.khu.ac.ir/article-1-2467-fa.html (in Persian).Google Scholar
Khazaee, T, Saadatjoo, A, Shabani, M, Senobari, M and Baziyan, M (2013). Prevalence of mobile phone dependency and its relationship with students’ self esteem. Journal of Knowledge & Health, 8, 156–162. doi:10.22100/jkh.v8i4.46 (in Persian).Google Scholar
Khazaei, T, Gh, Sharifzadeh, Sarawani M, Jahed, Khazaei, T and Hedayati, H (2014). The relationship between emotional intelligence and mobile dependency of students in Birjand Azad University, 2012. Modern Care, Scientific Quarterly of Birjand Nursing and Midwifery Faculty, 10, 279–287. Retrieved from: http://sid.bums.ac.ir/dspace/handle/bums/5007 (in Persian).Google Scholar
Koo, HY (2009). Development of a cell phone addiction scale for Korean adolescents. Journal of Korean Academy of Nursing, 39, 818–828. doi:10.4040/jkan.2009.39.6.818.CrossRefGoogle ScholarPubMed
Koo, HJ and Kwon, JH (2014). Risk and protective factors of internet addiction: A meta-analysis of empirical studies in Korea. Yonsei Medical Journal, 55, 1691–1711. doi:10.3349/ymj.2014.55.6.1691.CrossRefGoogle ScholarPubMed
Krossbakken, E, Torsheim, T, Mentzoni, RA, King, DL, Bjorvatn, B, Lorvik, IM and Pallesen, S (2018). The effectiveness of a parental guide for prevention of problematic video gaming in children: A public health randomized controlled intervention study. Journal of Behavioral Addictions, 7, 52–61. doi:10.1556/2006.6.2017.087.CrossRefGoogle ScholarPubMed
Lenoci, J.M., Telfair, J., Cecil, H and Edwards, RR (2002). Self-care in adults with sickle cell disease. Western Journal of Nursing Research, 24, 228–245. doi:10.1177/01939450222045879.CrossRefGoogle ScholarPubMed
Lorig, KR and Holman, HR (2003). Self-management education: History, definition, outcomes, and mechanisms. Annals of Behavioral Medicine, 26, 1–7. doi:10.1207/S15324796ABM2601_01.CrossRefGoogle ScholarPubMed
Mazloomy Mahmoudabad, S, Zolghadr, R, Mirzaei, AM and Baigi, H (2011). Relationship between chronic stress and quality of life in female students in Yazd city in 2011. Toloo-e-Behdasht, 10, 1–10. Retrieved from: http://jfmh.mums.ac.ir/article_10484_en.html (in Persian).Google Scholar
Meldrum, RC, Young, JTN and Weerman, FM (2012) Changes in self-control during adolescence: investigating the influence of the adolescent peer network. Journal of Criminal Justice 40, 452–462. doi:10.1016/j.jcrimjus.2012.07.002CrossRefGoogle Scholar
Moeini, B, Rezapur-Shahkolai, F, Faradmal, J and Soheylizad, M (2014). Effect of an educational program based on the health belief model to reduce cell phone usage during driving in taxi drivers. Journal of Education And Community Health, 1, 56–66. doi:10.20286/jech-010256 (in Persian).Google Scholar
Mojaye, E (2015). Mobile phone usage among Nigerian university students and its impact on teaching and learning. Global Journal of Arts Humanities and Social Sciences, 3, 29–38.Google Scholar
Most visited domains in Iran. Available at: www.alexa.com/topsites/countries/IR.Google Scholar
Najafi, M and Foladjang, M (2007). The relationship between self-efficacy and mental health among high school students. Daneshvar Raftar, 14, 69–82. Retrieved from: http://cpap.shahed.ac.ir/article-1-283-en.html (in Persian).Google Scholar
Nicol, A and Fleming, MJ (2010). “I h8 u”: The influence of normative beliefs and hostile response selection in predicting adolescents’ mobile phone aggression—a pilot study. Journal of School Violence, 9, 212–231. doi:10.1080/15388220903585861.CrossRefGoogle Scholar
Okada, M, Suzue, T and Jitsunari, F (2010). Association between interpersonal relationship among high-school students and mental health. Environmental Health and Preventive Medicine, 15, 57. doi:10.1007/s12199-009-0108-7.CrossRefGoogle ScholarPubMed
Orzack, MH, Voluse, AC, Wolf, D and Hennen, J (2006). An ongoing study of group treatment for men involved in problematic Internet-enabled sexual behavior. CyberPsychology & Behavior, 9, 348–360. doi: 10.1089/cpb.2006.9.348.CrossRefGoogle ScholarPubMed
Osborne, RH, Elsworth, GR and Whitfield, K (2007). The Health Education Impact Questionnaire (heiQ): An outcomes and evaluation measure for patient education and self-management interventions for people with chronic conditions. Patient Education and Counseling, 66, 192–201.CrossRefGoogle ScholarPubMed
Park, BW and Lee, KC (2011). The effect of users’ characteristics and experiential factors on the compulsive usage of the smartphone. Communications in Computer and Information Science, 151, 438–446. doi:10.1007/978-3-642-20998-7_52.CrossRefGoogle Scholar
Park, N, Kim, YC, Shon, HY and Shim, H (2013). Factors influencing smartphone use and dependency in South Korea. Computers in Human Behavior, 29, 1763–1770. doi:10.1016/j.chb.2013.02.008.CrossRefGoogle Scholar
Raskauskas, J (2009). Text-bullying: Associations with traditional bullying and depression among New Zealand adolescents. Journal of School Violence, 9, 74–97. doi:10.1080/15388220903185605.CrossRefGoogle Scholar
Rutland, JB, Sheets, T and Young, T (2007) Development of a scale to measure problem use of short message service: the SMS Problem Use Diagnostic Questionnaire. Cyberpsychol Behav 10, 841–843. doi: 10.1089/cpb.2007.9943. PMID: 18085975.CrossRefGoogle ScholarPubMed
Tang, S and Davis-Kean, PE (2015). The association of punitive parenting practices and adolescent achievement. Journal of Family Psychology, 29, 873–883. doi: 10.1037/fam0000137.CrossRefGoogle ScholarPubMed
Takao, M, Takahashi, S, Kitamura, M (2009). Addictive personality and problematic mobile phone use. Cyberpsychol Behav, 12, 501–507. doi: 10.1089/cpb.2009.0022.CrossRefGoogle ScholarPubMed
Van Deursen, Ajam, Bolle, CL, Hegner, SM, Hegner, S and Kommers, PAM (2015) Modeling habitual and addictive smartphone behavior: The role of smartphone usage types, emotional intelligence, social stress, self-regulation, age, and gender. Computers in human behavior 45, 411–420. doi:10.1016/j.chb.2014.12.039CrossRefGoogle Scholar
Wu, AM, Cheung, VI, Ku, L and Hung, EP (2013) Psychological risk factors of addiction to social networking sites among Chinese smartphone users. J Behav Addict 2, 160–166. doi: 10.1556/JBA.2.2013.006CrossRefGoogle ScholarPubMed
Zareipour, M, Eftekharardabili, H and Azam, K (2012) Study of Mental health and its relationship with family welfare in pre-university students in Salmas city in 2010. Journal of Research Development in Nursing and Midwifery 9, 84–93. Retrieved from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=298844 (in Persian).Google Scholar