BibTex RIS Kaynak Göster

The effects of internet use intensity on quality of life, anxiety and depression scores in pediatric migraine

Yıl 2014, , 23 - 28, 01.03.2014
https://doi.org/10.5798/diclemedj.0921.2014.01.0367

Öz

Objective: We aim to compare the quality of life, anxiety and depression scores of schoolchildren and adolescent migraineurs with healthy subjects according to the intensity of their Internet use. Methods: The migraine and control groups consisted of 142 migraineurs and 128 healthy children (age 9-17 years), respectively. Subjects were divided into 3 groups according to the intensity of their Internet- use intensity: Group 1: occasional Internet users, Group 2: regular Internet users, group 3: heavy Internet users. The children were divided into two groups according to the age while psychiatric tests were done: school children (

Kaynakça

  • Chou C. Internet heavy use and addiction among Taiwanese college students: an online interview study. Cyberpsychol Behav 2001;4:573–585.
  • Hakala PT, Rimpela AH, Saarni LA, Salminen JJ. Frequent computer-related activities increase the risk of neck-shoul- der and low back pain in adolescents. Eur J Public Health 2006;16:536 –541.
  • Kim K, Ryu E, Chon MY, et al. Internet addiction in Korean adolescents and its relation to depression and suicidal ide- ation: a questionnaire survey. Int J Nurs Stud 2006;43:185– 192.
  • Ko CH, Yen JY, Chen CS, et al. Predictive values of psy- chiatric symptoms for internet addiction in adolescents: A 2-year prospective study. Arch Pediatr Adolesc Med 2009;163:937–943.
  • Olesen J. International Headache Society classification and diagnostic criteria in children: a proposal for revision. Dev Med Child Neurol 1997;39:138.
  • Headache Classification Subcommittee of the International Headache Society. The International Classification of Headache Disorders: 2 nd edition. Cephalalgia 2004; 24 suppl 1 :9.
  • Belanger RE, Akre C, Berchtold A, Michauld PA. A U- shaped association between intensity of Internet use and ad- olescent health. Pediatrics 2011;127:e330-5. doi: 10.1542/ peds.2010-1235.
  • Tsitsika A, Critselis E, Kormas G, et al. Internet use and misuse: A multivariate regression analyses of the predic- tive factors of internet use among Greek adolescents. Eur J Pediatr 2009;168:655-665.
  • Louacheni C, Plancke L, Israel M. Teenagers screen-watch- ing habits in their leisure time: use and misuse of internet, play stations and television. Psychotropes 2007;13:3-4.
  • Kovacs M. Rating scales to assess depression in schoolage children. Acta Paedopsychatr 1980;46:305-315.
  • Spielberger CD. Vagg PR. Psychometric properties of the STAI: a reply to Ramanaiah, Franzen, and Schill. J Pers Assess 1984;48: 87-95.
  • Varni JW, Seid M, Rode CA. The PedsQL: measurement model for the pediatric quality of life inventory. Med Care 1999;37:126-139.
  • Varni JW, Seid M, Kurtin PS. The PedsQLTM 4.0: reliabil- ity and validity of the Pediatric Quality of Life Inventory TM version 4.0 generic core scales in healthy and patient populations. Med Care 2001;39:800-812.
  • Varni JW, Burwinkle TM, Seid M. The PedsQL as a pe- diatric patient-reported outcome: reliability and validity of the PedsQL Measurement Model in 25,000 children. Expert Rev Pharmacoecon Outcomes Res 2005;5:705-719.
  • Cakin Memik N, Agaoglu B, Coskun A, et. al. The Valid- ity and Reliability of the Turkish Pediatric Quality of Life Inventory for Children 8-12 Years Old. Turkish Journal of Child and Adolescent Mental Health 2008; 15:87-98.
  • Memik NÇ, Ağaoğlu B, Coşkun A, et al. The Validity and Reliability of the Turkish Pediatric Quality of Life In- ventory for Children 13-18 Years Old. J Turkish Psych 2007;18:353-363.
  • Öy B. Children’s Depression Inventory: a study of reliabil- ity and validity. Turk J Psych 1991;2:132–136 (In Turkish).
  • Özusta S. Turkish standardization, reliability and validity of State Trait Anxiety Inventory for children. Turk J Psych 1995;10:32–44 (In Turkish).
  • Bados A, Gomez-Benito J, Balaguer G.The state-trait anxi- ety inventory, trait version: does it really measure anxiety? J Pers Assess 2010;92:560-567.
  • Shapira NA, Lessing MC, Goldsmith TD, et.al. Problematic internet use: proposed classification and diagnostic criteria. Depress Anxiety 2003;17:207-216.
  • Young KS. Internet addiction: the emergence of a new clini- cal disorder. Cyberpsychol Behav 1998;1:237-244.
  • Ko CH, Yen JY, Chen CC, et al. Proposed diagnostic crite- ria of internet addiction for adolescents. J Nerv Ment Dis 2005;193:728-733.
  • Kautiainen S, Koivusilta L, Lintonen T, et al. Use of in- formation and communication technology and prevalence of overweight and obesity among adolescent. Int J Obes 2005;29:925-933.
  • Kim JH, Lau CH, Cheuk KK, et al. Brief report:predictors of heavy internet use and associations with health-promot- ing and health risk behaviors among Hong Kong university students. J Adolesc 2010;33:215-220.
  • Berkey CS, Rockett HR, Colditz GA. Weight gain in older adolescent females: the internet, sleep, coffee, and alcohol. J Pediatr 2008;153:635-639.
  • Shapira NA, Goldsmith TD, Keck PE Jr, et al. Psychiatric features of individulas with problematic internet use. J Af- fect Disord 2000:57:267-272.
  • Kaczynski KJ, Claar RL, Lebel AA. Relations Between Pain Characteristics, Child and Parent Variables, and School Functioning in Adolescents With Chronic Headache: A Comparison of Tension-Type Headache and Migraine. J Pediatr Psychol 2012;32:123-127.
  • Bernardi S, Pallanti S. Internet addiction: A descriptive clinical study focusing on comorbidities and dissociative symptoms. Compr Psychiatry 2009;50:510-516.
  • Milani L, Osualdella D, Di BP. Quality of interpersonal relationships and problematic internet use in adolescence. Cyberpsychol Behav 2009;12:681-684.
  • Yen JY, Ko CH, Yen CF, et al. The comorbid psychiatric symptoms of internet addiction: attention deficit and hyper- activity disorder, depression, social phobia, and hostility. J Adolesc Health 2007;41:93-98.

The effects of internet use intensity on quality of life, anxiety and depression scores in pediatric migraine

Yıl 2014, , 23 - 28, 01.03.2014
https://doi.org/10.5798/diclemedj.0921.2014.01.0367

Öz

Amaç: Migren tanısı ile takipli okul çocuğu ve ergenlerin internet kullanım sıklığına göre yaşam kalite indeksi, anksiyete ve depresyon skorlarının, sağlıklı çocuklarla karşılaştırılması amaçlanmıştır. Yöntemler: 9-17 yaş arasında, migren tanısı alan 142 hasta ile aynı yaş ve cinsiyetteki 128 sağlıklı çocuk çalışmaya alındı. Hastaların öykü, öz ve soy geçmiş ve antropometrik ölçümleri de içeren fizik muayene bulguları kaydedildi. Hastalar ergen (˃12 yaş) ve ergen öncesi (

Kaynakça

  • Chou C. Internet heavy use and addiction among Taiwanese college students: an online interview study. Cyberpsychol Behav 2001;4:573–585.
  • Hakala PT, Rimpela AH, Saarni LA, Salminen JJ. Frequent computer-related activities increase the risk of neck-shoul- der and low back pain in adolescents. Eur J Public Health 2006;16:536 –541.
  • Kim K, Ryu E, Chon MY, et al. Internet addiction in Korean adolescents and its relation to depression and suicidal ide- ation: a questionnaire survey. Int J Nurs Stud 2006;43:185– 192.
  • Ko CH, Yen JY, Chen CS, et al. Predictive values of psy- chiatric symptoms for internet addiction in adolescents: A 2-year prospective study. Arch Pediatr Adolesc Med 2009;163:937–943.
  • Olesen J. International Headache Society classification and diagnostic criteria in children: a proposal for revision. Dev Med Child Neurol 1997;39:138.
  • Headache Classification Subcommittee of the International Headache Society. The International Classification of Headache Disorders: 2 nd edition. Cephalalgia 2004; 24 suppl 1 :9.
  • Belanger RE, Akre C, Berchtold A, Michauld PA. A U- shaped association between intensity of Internet use and ad- olescent health. Pediatrics 2011;127:e330-5. doi: 10.1542/ peds.2010-1235.
  • Tsitsika A, Critselis E, Kormas G, et al. Internet use and misuse: A multivariate regression analyses of the predic- tive factors of internet use among Greek adolescents. Eur J Pediatr 2009;168:655-665.
  • Louacheni C, Plancke L, Israel M. Teenagers screen-watch- ing habits in their leisure time: use and misuse of internet, play stations and television. Psychotropes 2007;13:3-4.
  • Kovacs M. Rating scales to assess depression in schoolage children. Acta Paedopsychatr 1980;46:305-315.
  • Spielberger CD. Vagg PR. Psychometric properties of the STAI: a reply to Ramanaiah, Franzen, and Schill. J Pers Assess 1984;48: 87-95.
  • Varni JW, Seid M, Rode CA. The PedsQL: measurement model for the pediatric quality of life inventory. Med Care 1999;37:126-139.
  • Varni JW, Seid M, Kurtin PS. The PedsQLTM 4.0: reliabil- ity and validity of the Pediatric Quality of Life Inventory TM version 4.0 generic core scales in healthy and patient populations. Med Care 2001;39:800-812.
  • Varni JW, Burwinkle TM, Seid M. The PedsQL as a pe- diatric patient-reported outcome: reliability and validity of the PedsQL Measurement Model in 25,000 children. Expert Rev Pharmacoecon Outcomes Res 2005;5:705-719.
  • Cakin Memik N, Agaoglu B, Coskun A, et. al. The Valid- ity and Reliability of the Turkish Pediatric Quality of Life Inventory for Children 8-12 Years Old. Turkish Journal of Child and Adolescent Mental Health 2008; 15:87-98.
  • Memik NÇ, Ağaoğlu B, Coşkun A, et al. The Validity and Reliability of the Turkish Pediatric Quality of Life In- ventory for Children 13-18 Years Old. J Turkish Psych 2007;18:353-363.
  • Öy B. Children’s Depression Inventory: a study of reliabil- ity and validity. Turk J Psych 1991;2:132–136 (In Turkish).
  • Özusta S. Turkish standardization, reliability and validity of State Trait Anxiety Inventory for children. Turk J Psych 1995;10:32–44 (In Turkish).
  • Bados A, Gomez-Benito J, Balaguer G.The state-trait anxi- ety inventory, trait version: does it really measure anxiety? J Pers Assess 2010;92:560-567.
  • Shapira NA, Lessing MC, Goldsmith TD, et.al. Problematic internet use: proposed classification and diagnostic criteria. Depress Anxiety 2003;17:207-216.
  • Young KS. Internet addiction: the emergence of a new clini- cal disorder. Cyberpsychol Behav 1998;1:237-244.
  • Ko CH, Yen JY, Chen CC, et al. Proposed diagnostic crite- ria of internet addiction for adolescents. J Nerv Ment Dis 2005;193:728-733.
  • Kautiainen S, Koivusilta L, Lintonen T, et al. Use of in- formation and communication technology and prevalence of overweight and obesity among adolescent. Int J Obes 2005;29:925-933.
  • Kim JH, Lau CH, Cheuk KK, et al. Brief report:predictors of heavy internet use and associations with health-promot- ing and health risk behaviors among Hong Kong university students. J Adolesc 2010;33:215-220.
  • Berkey CS, Rockett HR, Colditz GA. Weight gain in older adolescent females: the internet, sleep, coffee, and alcohol. J Pediatr 2008;153:635-639.
  • Shapira NA, Goldsmith TD, Keck PE Jr, et al. Psychiatric features of individulas with problematic internet use. J Af- fect Disord 2000:57:267-272.
  • Kaczynski KJ, Claar RL, Lebel AA. Relations Between Pain Characteristics, Child and Parent Variables, and School Functioning in Adolescents With Chronic Headache: A Comparison of Tension-Type Headache and Migraine. J Pediatr Psychol 2012;32:123-127.
  • Bernardi S, Pallanti S. Internet addiction: A descriptive clinical study focusing on comorbidities and dissociative symptoms. Compr Psychiatry 2009;50:510-516.
  • Milani L, Osualdella D, Di BP. Quality of interpersonal relationships and problematic internet use in adolescence. Cyberpsychol Behav 2009;12:681-684.
  • Yen JY, Ko CH, Yen CF, et al. The comorbid psychiatric symptoms of internet addiction: attention deficit and hyper- activity disorder, depression, social phobia, and hostility. J Adolesc Health 2007;41:93-98.
Toplam 30 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Araştırma Yazıları
Yazarlar

Emel Torun Bu kişi benim

Serhat Güler Bu kişi benim

Mehmet Küçükkoç Bu kişi benim

Sema Ölçer Bu kişi benim

Yayımlanma Tarihi 1 Mart 2014
Gönderilme Tarihi 2 Mart 2015
Yayımlandığı Sayı Yıl 2014

Kaynak Göster

APA Torun, E., Güler, S., Küçükkoç, M., Ölçer, S. (2014). The effects of internet use intensity on quality of life, anxiety and depression scores in pediatric migraine. Dicle Tıp Dergisi, 41(1), 23-28. https://doi.org/10.5798/diclemedj.0921.2014.01.0367
AMA Torun E, Güler S, Küçükkoç M, Ölçer S. The effects of internet use intensity on quality of life, anxiety and depression scores in pediatric migraine. diclemedj. Mart 2014;41(1):23-28. doi:10.5798/diclemedj.0921.2014.01.0367
Chicago Torun, Emel, Serhat Güler, Mehmet Küçükkoç, ve Sema Ölçer. “The Effects of Internet Use Intensity on Quality of Life, Anxiety and Depression Scores in Pediatric Migraine”. Dicle Tıp Dergisi 41, sy. 1 (Mart 2014): 23-28. https://doi.org/10.5798/diclemedj.0921.2014.01.0367.
EndNote Torun E, Güler S, Küçükkoç M, Ölçer S (01 Mart 2014) The effects of internet use intensity on quality of life, anxiety and depression scores in pediatric migraine. Dicle Tıp Dergisi 41 1 23–28.
IEEE E. Torun, S. Güler, M. Küçükkoç, ve S. Ölçer, “The effects of internet use intensity on quality of life, anxiety and depression scores in pediatric migraine”, diclemedj, c. 41, sy. 1, ss. 23–28, 2014, doi: 10.5798/diclemedj.0921.2014.01.0367.
ISNAD Torun, Emel vd. “The Effects of Internet Use Intensity on Quality of Life, Anxiety and Depression Scores in Pediatric Migraine”. Dicle Tıp Dergisi 41/1 (Mart 2014), 23-28. https://doi.org/10.5798/diclemedj.0921.2014.01.0367.
JAMA Torun E, Güler S, Küçükkoç M, Ölçer S. The effects of internet use intensity on quality of life, anxiety and depression scores in pediatric migraine. diclemedj. 2014;41:23–28.
MLA Torun, Emel vd. “The Effects of Internet Use Intensity on Quality of Life, Anxiety and Depression Scores in Pediatric Migraine”. Dicle Tıp Dergisi, c. 41, sy. 1, 2014, ss. 23-28, doi:10.5798/diclemedj.0921.2014.01.0367.
Vancouver Torun E, Güler S, Küçükkoç M, Ölçer S. The effects of internet use intensity on quality of life, anxiety and depression scores in pediatric migraine. diclemedj. 2014;41(1):23-8.