Relationship between Individuals' Levels of Pain, Physical Activity and Problematic Internet Use in the COVID-19 Pandemic

Yıl 2021, Cilt: 22 Sayı: 4, 421 - 431, 27.12.2021

Anıl Özüdoğru , Önder Baltacı , Muhammed Samed Dalakçı , Ömer Faruk Akbulut

https://doi.org/10.51982/bagimli.935758

Cited By: 5

Öz

Objective: The aim of this research is to examine the role of sex with physical activity and problematic internet use as predictors of pain levels caused by individuals ' use of technology during the covid-19 pandemic.
Method: The research was carried out by relational screening method. The participants of the study are 296 adult individuals over the age of 18 living in Turkey, 198 of whom are female (66.9%) and 98 of whom are male (33.1%), who use the internet actively. In the study, "Problematic Internet Use Scale-Short Form-6", "International Physical Activity Questionnaire - Short Form" and "Personal Information Form" were used.
Results: A negatively significant association was found between pain levels and physical activity levels caused by individuals ' use of technology during the COVID-19 pandemic, while a positively significant association was found between problematic internet usage levels. In addition, gender, physical activity, and problematic internet use variables were found to together explain 18.3% of the total variance in pain caused by technology use.
Conclusion: During the pandemic period, physical activity, problematic internet use and gender factors were found to have an important place in the level of pain caused by individuals ' use of technology.

Anahtar Kelimeler

Pain, physical activity, problematic internet use, COVID-19, gender.

COVID-19 Pandemisinde Bireylerin Ağrı, Fiziksel Aktivite ve Problemli İnternet Kullanımı Düzeyleri Arasındaki İlişkiler

Öz

Amaç: Bu araştırmanın amacı, COVID-19 pandemisi döneminde bireylerin teknoloji kullanımlarından kaynaklı ağrı düzeylerinin yordayıcıları olarak fiziksel aktivite ve problemli internet kullanım düzeyi ile cinsiyetin rolünü incelemektir.
Yöntem: Araştırma, ilişkisel tarama yöntemi ile gerçekleştirilmiştir. Araştırmanın katılımcılarını, Türkiye’de yaşayan 18 yaş üzeri ve aktif internet kullanan 198’i kadın (%66.9) 98’i erkek olmak üzere (%33.1) 296 yetişkin birey oluşturmaktadır. Araştırmada; “Problemli İnternet Kullanımı Ölçeği-Kısa Form-6”, “Uluslararası Fiziksel Aktivite Anketi – Kısa Form” ve “Kişisel Bilgi Formu” kullanılmıştır.
Bulgular: Bireylerin COVID-19 pandemisi döneminde teknoloji kullanımlarından kaynaklı ağrı düzeyleri ile fiziksel aktivite düzeyleri arasında negatif yönde anlamlı bir ilişki bulunurken, problemli internet kullanımı düzeyleri arasında pozitif yönde anlamlı bir ilişki bulunmuştur. Ayrıca cinsiyet, fiziksel aktivite ve problemli internet kullanımı değişkenleri birlikte, teknoloji kullanımından kaynaklanan ağrıdaki toplam varyansın %18.3’ünü açıkladığı görülmüştür.
Sonuç: Pandemi döneminde bireylerin teknoloji kullanımlarından kaynaklanan ağrı düzeylerinde fiziksel aktivite, problemli internet kullanımı ve cinsiyet faktörlerinin önemli bir yere sahip olduğu görülmüştür.

Anahtar Kelimeler

Ağrı, Fiziksel Aktivite, Problemli İnternet Kullanımı, COVID-19, Cinsiyet

Kaynakça

• 1. World Health Organization. WHO Director-General’s Opening Remarks at the Media Briefing on COVID-19.; 2020. https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020
• 2. T.C. Sağlık Bakanlığı. COVID-19 Bilgilendirme Sayfası. Published 2020. Accessed February 6, 2021. https://covid19.saglik.gov.tr/
• 3. Bostan S, Erdem R, Öztürk YE, Kılıç T, Yılmaz A. The Effect of COVID-19 Pandemic on the Turkish Society. Electron J Gen Med. 2020;17(6):em237. doi:10.29333/ejgm/7944
• 4. Liang L, Ren H, Cao R, et al. The effect of COVID-19 on youth mental health. Psychiatr Q. 2020;91(3):841-852. doi:10.1007/s11126-020-09744-3
• 5. Al Zubayer A, Rahman ME, Islam MB, et al. Psychological states of Bangladeshi people four months after the COVID-19 pandemic: An online survey. Heliyon. 2020;6(9):e05057.
• 6. Chen RN, Liang SW, Peng Y, et al. Mental health status and change in living rhythms among college students in China during the COVID-19 pandemic: A large-scale survey. J Psychosom Res. 2020;137:110219.
• 7. Planchuelo-Gómez Á, Odriozola-González P, Irurtia MJ, de Luis-García R. Longitudinal evaluation of the psychological impact of the COVID-19 crisis in Spain. J Affect Disord. 2020;277:842-849.
• 8. El Keshky MES, Alsabban AM, Basyouni SS. The psychological and social impacts on personal stress for residents quarantined for COVID-19 in Saudi Arabia. Arch Psychiatr Nurs. 2020;First Onli.
• 9. Baltacı Ö, Akbulut ÖF, Zafer R. COVID-19 pandemisinde problemli internet kullanımı: Bir nitel araştırma. Kırşehir Ahi Evran Üniversitesi Sağlık Bilim Enstitüsü Derg. 2020;1(3):126-140.
• 10. Sun Y, Li Y, Bao Y, et al. Brief report: increased addictive internet and substance use behavior during the COVID‐19 pandemic in China. Am J Addict. 2020;29(4):268-270.
• 11. Pausé C, Parker G, Gray L. Resisting the problematisation of fatness in COVID-19: In pursuit of health justice. Int J Disaster Risk Reduct. 2021;54:102021. doi:10.1016/j.ijdrr.2020.102021
• 12. Tar E, Atik D. Pandemi döneminde obezite riski. Diyabet, Obezite ve Hipertansiyonda Hemşirelik Forumu Derg. 2020;12(2):37-41.
• 13. Erdoğan R. Pandemi döneminde beden eğitimi ve spor yüksekokulu öğrencilerinin beslenme alışkanlıkları ve fiziksel aktivite düzeylerinin belirlenmesi. OPUS Uluslararası Toplum Araştırmaları Derg. 2021;17(Pandemi Özel Sayısı):145-164. doi:10.26466/opus.862585
• 14. Moawad RA. Online learning during the COVID-19 pandemic and academic stress in university students. Rev Românească pentru Educ Multidimens. 2020;12(1):100-107.
• 15. Chandra Y. Online education during COVID-19: perception of academic stress and emotional intelligence coping strategies among college students. Asian Educ Dev Stud. 2020;10(2):229-238. doi:10.1108/AEDS-05-2020-0097
• 16. Akbulut ÖF. Üniversite Öğrencilerinin Pandemi Döneminde Kariyer Streslerinin COVID-19 Korkusu, Kişilik Özellikleri ve Çeşitli Sosyo-Demografik Değişkenler Açısından İncelenmesi. In: FSMVU Eğitim Araştırmaları Kongresi. ; 2021. http://www.fsm.edu.tr/resim/Dosya/O?zet_Kitapc?ig?i2021-03-31-10-43-22pm.pdf
• 17. Autin KL, Blustein DL, Ali SR, Garriott PO. Career development impacts of COVID-19: Practice and policy recommendations. J Career Dev. 2020;47(5):487-494. doi:10.1177/0894845320944486
• 18. Mahmud MS, Talukder MU, Rahman SM. Does ‘Fear of COVID-19’trigger future career anxiety? An empirical investigation considering depression from COVID-19 as a mediator. Int J Soc Psychiatry. 2020;2:1-11. doi:https://dx.doi.org/10.1177%2F0020764020935488
• 19. Tison GH, Avram R, Kuhar P, et al. Worldwide effect of COVID-19 on physical activity: a descriptive study. Ann Intern Med. 2020;173(9):767-770. doi:10.7326/M20-2665
• 20. El-Tallawy SN, Nalamasu R, Pergolizzi J V., Gharibo C. Pain management during the COVID-19 pandemic. Pain Ther. 2020;9:453-466. doi:10.1007/s40122-020-00190-4
• 21. Shanthanna H, Strand NH, Provenzano DA, et al. Caring for patients with pain during the COVID‐19 pandemic: consensus recommendations from an international expert panel. Anaesthesia. 2020;75(7):935-944. doi:10.1111/anae.15076
• 22. Mathews JA. Back pain and sciatica. Rheumatology. 1988;27(4):331. doi:10.1093/rheumatology/27.4.331
• 23. Altınel L. Profesyonel hastane çalışanlarında bel ağrısı ve bel ağrısını etkileyen faktörler. Tıp Araştırmaları Derg. 2007;5(3):115-120.
• 24. Altınel L, Kose KC, Ergan V, et al. The prevalence of low back pain and risk factors among adult population in Afyon region, Turkey. Acta Orthop Traumatol Turc. 2008;42(5):328-333. doi:10.3944/AOTT.2008.328
• 25. Balague F, Troussier B, Salminen JJ. Non-specific low back pain in children and adolescents: risk factors. Eur Spine J. 1999;8(6):429-438. doi:10.1007/s005860050201
• 26. Bedson J, Mottram S, Thomas E, Peat G. Knee pain and osteoarthritis in the general population: what influences patients to consult? Fam Pract. 2007;24(5):443-453. doi:10.1093/fampra/cmm036
• 27. Shuval K, Donchin M. Prevalence of upper extremity musculoskeletal symptoms and ergonomic risk factors at a Hi-Tech company in Israel. Int J Ind Ergon. 2005;35(6):569-581.
• 28. Xavier FMF, Ferraz MPT, Marc N, Escosteguy NU, Moriguchi EH. Elderly people’s definition of quality of life. Revista Brasileira de Psiquiatria. Rev Bras Psiquiatr. 2003;25(1):31-39. doi:10.1590/S1516-44462003000100007
• 29. Briggs AM, Straker LM, Bear NL, Smith AJ. Neck/shoulder pain in adolescents is not related to the level or nature of self-reported physical activity or type of sedentary activity in an Australian pregnancy cohort. BMC Musculoskelet Disord. 2009;10(1):1-11. doi:10.1186/1471-2474-10-87
• 30. Holth HS, Werpen HKB, Zwart JA, Hagen K. Physical inactivity is associated with chronic musculoskeletal complaints 11 years later: Results from the Nord-Trøndelag Health Study. BMC Musculoskelet Disord. 2008;9:1-7. doi:10.1186/1471-2474-9-159
• 31. Morken T, Magerøy N, Moen BE. Physical activity is associated with a low prevalence of musculoskeletal disorders in the Royal Norwegian Navy: A cross sectional study. BMC Musculoskelet Disord. 2007;8:1-8. doi:10.1186/1471-2474-8-56
• 32. Vikat A, Rimpelä M, Salminen JJ, Rimpelä A, Savolainen A, Virtanen SM. Neck or shoulder pain and low back pain in Finnish adolescents. Scand J Public Health. 2000;28(3):164-173. doi:10.1177/14034948000280030401
• 33. Tesarz J, Schuster AK, Hartmann M, Gerhardt A, Eich W. Pain perception in athletes compared to normally active controls: A systematic review with meta-analysis. Pain. 2012;153:1253-1262.
• 34. Can Sema , Arslan Erşan EG. Güncel bakış açısı ile fiziksel aktivite. Ankara Üniversitesi Beden Eğitimi ve Spor Yüksekokulu SPORMETRE Beden Eğitimi ve Spor Bilim Derg. 2014;12(1):1-10. doi:10.1501/sporm_0000000248
• 35. Adedoyin RA, Idowu BO, Adagunodo RE, Owoyomi AA, Idowu PA. Musculoskeletal pain associated with the use of computer systems in Nigeria. Technol Heal care. 2005;13(2):125-130.
• 36. Harris C, Straker L, Pollock C, Smith A. Children, computer exposure and musculoskeletal outcomes: The development of pathway models for school and home computerrelated musculoskeletal outcomes. J Ergon. 2015;58(10):1611-1623.
• 37. Statista. Coronavirus: impact on online usage in the U.S. - Statistics & Facts. Published 2021. Accessed January 30, 2021. https://www.statista.com/topics/6241/coronavirus-impact-on-online-usage-in-the-us/
• 38. Özdemir D, Arpacıoğlu S. Sosyal Medya Kullanımı, Sağlık Algısı ve Sağlık Arama Davranışının Koronavirüs Korkusu Üzerine Etkisi. Psikiyatr Güncel Yaklaşımlar. 2020;12(1):1-15. doi:10.18863/pgy.803145
• 39. Islam MS, Sujan MSH, Tasnim R, et al. Problematic internet use among young and adult population in Bangladesh: Correlates with lifestyle and online activities during the COVID-19 pandemic. Addict Behav Reports. 2020;12:100311. doi:https://doi.org/10.1016/j.abrep.2020.100311
• 40. Baltacı Ö, Akbulut ÖF, Yılmaz E. Problemli İnternet Kullanımında Güncel Bir Risk Faktörü: COVID-19 Pandemisi. Humanist Perspect. 2021;3(1):97-121. doi:10.47793/hp.872503
• 41. Duan L, Shao X, Wang Y, et al. An investigation of mental health status of children and adolescents in china during the outbreak of COVID-19. J Affect Disord. 2020;275:112-118.
• 42. Karimy M, Parvizi F, Rouhani MR, Griffiths MD, Armoon B, Fattah Moghaddam L. The association between internet addiction, sleep quality, and health-related quality of life among Iranian medical students. J Addict Dis. 2020;38(3):317-325. doi:10.1080/10550887.2020.1762826
• 43. Eliacik K, Bolat N, Koçyiğit C, et al. Internet addiction, sleep and health-related life quality among obese individuals: a comparison study of the growing problems in adolescent health. Eat Weight Disord Anorexia, Bulim Obes. 2016;21(4):709-717. doi:10.1007/s40519-016-0327-z
• 44. Lin YJ, Hsiao RC, Liu TL, Yen CF. Bidirectional relationships of psychiatric symptoms with internet addiction in college students: A prospective study. J Formos Med Assoc. Published online 2019:1-8.
• 45. Przepiorka A, Blachnio A, Cudo A. The role of depression, personality, and future time perspective in internet addiction in adolescents and emerging adults. Psychiatry Res. 2019;272:340-348.
• 46. Chi X, Hong X, Chen X. Profiles and sociodemographic correlates of internet addiction in early adolescents in Southern China. Addict Behav. 2020;106:1-7.
• 47. Xin M, Xing J, Pengfei W, Houru L, Mengcheng W, Hong Z. Online activities, prevalence of Internet addiction and risk factors related to family and school among adolescents in China. Addict Behav Reports. 2018;7:14-18. doi:https://doi.org/10.1016/j.abrep.2017.10.003
• 48. Kee IK, Byun JS, Jung JK, Choi JK. The presence of altered craniocervical posture and mobility in smartphone-addicted teenagers with temporomandibular disorders. J Phys Ther Sci. 2016;28(2):339-346. doi:10.1589/jpts.28.339
• 49. Kelley KJ, Gruber EM. Problematic Internet use and physical health. J Behav Addict. 2013;2(2):108-112. doi:10.1556/jba.1.2012.016
• 50. Dol KS. Fatigue and pain related to Internet usage among university students. J Phys Ther Sci. 2016;28(4):1233-1237. doi:10.1589/jpts.28.1233
• 51. Hakala PT, Rimpelä AH, Saarni LA, Salminen JJ. Frequent computer-related activities increase the risk of neck–shoulder and low back pain in adolescents. Eur J Public Health. 2006;16(5):536-541. doi:10.1093/eurpub/ckl025
• 52. Burke A, Peper E. Cumulative trauma disorder risk for children using computer products: results of a pilot investigation with a student convenience sample. Public Health Rep. 2002;117(4):350-357. doi:10.1016/S0033-3549(04)50171-1
• 53. Yang G, Cao J, Li Y, et al. Association Between Internet Addiction and the Risk of Musculoskeletal Pain in Chinese College Freshmen – A Cross-Sectional Study . Front Psychol . 2019;10:1959. https://www.frontiersin.org/article/10.3389/fpsyg.2019.01959
• 54. Koca TT, Berk E. Influence of internet addiction on academic, sportive, and recreative activities in adolescents. J Public Health (Bangkok). 2019;27(4):531-536. doi:10.1007/s10389-018-0965-x
• 55. Jacobs K, Baker NA. The association between children’s computer use and musculoskeletal discomfort. Work. 2002;18(3):221-226.
• 56. Fillingim RB, Edwards RR, Powell T. The relationship of sex and clinical pain to experimental pain responses. Pain. 1999;83(3):419-425. doi:10.1016/S0304-3959(99)00128-1
• 57. Fillingim RB, Ness TJ. Sex-related hormonal influences on pain and analgesic responses. Neurosci Biobehav Rev. 2000;24(4):485-501. doi:10.1016/S0149-7634(00)00017-8
• 58. Özçaka Ö, Biçakçi N, Köse T. Effect of the menstrual cycle on pain experience associated with periodontal therapy: Randomized, pilot study. J Clin Periodontol. 2005;32(11):1170-1174. doi:10.1111/j.1600-051X.2005.00841.x
• 59. Büyüköztürk Ş, Kılıç Çakmak E, Akgün ÖE, Karadeniz Ş, Demirel F. Eğitimde Bilimsel Araştırma Yöntemleri. Pegem; 2018.
• 60. Göktaş S, Aygar H, Akbulut Zencirci S, Önsüz MF, Alaiye M, Metintaş S. Problematic internet use questionairre-short form-6 (PIUQ-SF 6): a validity and reliability study in Turkey. Int J Res Med Sci. 2018;6(7):2354-2360. doi:10.18203/2320-6012.ijrms20182816
• 61. Öztürk M. Üniversitede eğitim-ögretim gören öğrencilerde uluslararası fiziksel aktivite anketinin geçerliligi ve güvenirliği ve fiziksel aktivite düzeylerinin belirlenmesi. Published online 2005.
• 62. Demetrovics Z, Király O, Koronczai B, et al. Psychometric properties of the Problematic Internet Use Questionnaire Short-Form (PIUQ-SF-6) in a nationally representative sample of adolescents. PLoS One. 2016;11(8):e0159409. doi:10.1371/journal.pone.0159409
• 63. Craig CL, Marshall AL, Sjöström M, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sport Exerc. 2003;35(8):1381-1395.
• 64. Karlqvist L, Toomingas A, Hagberg M, Tornqvist EW, Hagman M. Self-reported working conditions of VDU operators and associations with musculoskeletal symptoms: a cross-sectional study focusing on gender differences. Int J Ind Ergon. 2002;30(4-5):277-294.
• 65. Fillingim RB, King CD, Ribeiro-Dasilva MC, Rahim-Williams B, Riley III JL. Sex, gender, and pain: A review of recent clinical and experimental findings. J pain. 2009;10(5):447-485. doi:10.1016/j.jpain.2008.12.001
• 66. Esen H, Fiğlali N, Üniversitesi K, Fakültesi M, Mühendisliği Bölümü E. Der. 17. Cilt, 1. Sayı, s. 41-51. SAU J Sci. 2013;17(1):41-51.
• 67. Önen Tekin H. Ofi̇s çalişanlarinda fi̇zi̇ksel akti̇vi̇te düzeyi̇ni̇n kas i̇skelet si̇stemi̇ rahatsizliklarina etki̇si̇. Published online 2018.
• 68. Delisle A, Larivière C, Plamondon A, Imbeau D. Comparison of three computer office workstations offering forearm support: Impact on upper limb posture and muscle activation. Ergonomics. 2006;49(2):139-160. doi:10.1080/10610270500450739
• 69. Holth HS, Werpen HKB, Zwart JA, Hagen K. Physical inactivity is associated with chronic musculoskeletal complaints 11 years later: Results from the Nord-Trøndelag Health Study. BMC Musculoskelet Disord. 2008;9:1-7. doi:10.1186/1471-2474-9-159
• 70. Morken T, Magerøy N, Moen BE. Physical activity is associated with a low prevalence of musculoskeletal disorders in the Royal Norwegian Navy: A cross sectional study. BMC Musculoskelet Disord. 2007;8:1-8. doi:10.1186/1471-2474-8-56
• 71. Haskell WL, Lee IM, Pate RR, et al. Physical activity and public health: Updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc. 2007;39(8):1423-1434. doi:10.1249/mss.0b013e3180616b27
• 72. Uz Tunçay S, Yeldan İ. Is physical inactivity associated with musculoskeletal disorders? Aǧrı Ağrı Derneği’nin Yayın organıdır = J Turkish Soc Algol. 2013;25(4):147-155. doi:10.5505/agri.2013.09825
• 73. Kuru T, Yelan I, Zengin A, et al. Erişkinlerde aĝri ve farkli aĝri tedavilerinin prevalansi. Agri. 2011;23(1):22-27. doi:10.5505/agri.2011.40412
• 74. Bilgin E. Bilgisayar Kullanımı İle İlişkili Boyun ve Üst Ekstremite Rahatsızlıkları. STED / Sürekli Tıp Eğitimi Derg. 2017;26(6):251-247.
• 75. Gün İ, Özer A, Ekinci E, Öztürk A. Bilgisayarla Çalışan Kişilerin İfade Ettikleri Sağlık Sorunları ve Bilgisayar Kullanım Özellikleri. Erciyes Tıp Derg. 2004;26(4):153-157.
• 76. Moom RK, Sing LP, Moom N. Prevalence of Musculoskeletal Disorder among Computer Bank Office Employees in Punjab (India): A Case Study. Procedia Manuf. 2015;3(Ahfe):6624-6631. doi:10.1016/j.promfg.2015.11.002
• 77. GÜSSÜN G. “ Bġlgġ Ve Belge Merkezlerġ Çaliġanlarinin Ġġ Ortamindan Kaynaklanan Sağlik Ġġkayetlerġ Ve Rġsk Faktörlerġ ” “ Bġlgġ Ve Belge Merkezlerġ Çaliġanlarinin Ġġ Ortamindan Kaynaklana N Sağlik Ġġkayetlerġ Ve Rġsk Faktörlerġ .” Published online 2009.
• 78. Nang H, Harfield A. The nature of technology consumption among school children in lower northern Thailand. Int J Interact Mob Technol. 2019;13(5):137-146. doi:10.3991/ijim.v13i05.10309
• 79. IJmker S, Huysmans MA, Blatter BM, Van Der Beek AJ, Van Mechelen W, Bongers PM. Should office workers spend fewer hours at their computer? A systematic review of the literature. Occup Environ Med. 2007;64(4):211-222. doi:10.1136/oem.2006.026468
• 80. Gerr F, Marcus M, Ensor C, et al. A prospective study of computer users: I. Study design and incidence of musculoskeletal symptoms and disorders. Am J Ind Med. 2002;41(4):221-235. doi:10.1002/ajim.10066