Neck pain associated with smartphone usage among university students

Author:

Maayah Mikhled FalahORCID,Nawasreh Zakariya H.,Gaowgzeh Riziq Allah M.,Neamatallah Ziyad,Alfawaz Saad S.,Alabasi Umar M.

Abstract

Objective Neck and shoulder pain has been linked to prolonged periods of flexed neck posture. However, the influences of factors related to individuals’ characteristics and the time duration and position of using smartphones on the severity and duration of neck and shoulder pain among university students are not well studied. The aim of this study was to identify factors related to individual demographics, the history of neck pain, and the time duration and positions of using the smartphone that could be associated with neck pain severity and duration and to determine the influence of these factors on neck pain severity and duration among university students. Subjects and methods A cross-sectional study was conducted on students from King Abdulaziz University in Jeddah, Saudi Arabia, using a self-administered online questionnaire. Data was collected between March 10th, 2020, and October 18th, 2020, with 867 questionnaires filled out using Google Forms as a web-based questionnaire. Questionnaires were distributed to students by posting them in their batch groups on Facebook, an online social media and social networking service. Students from five healthcare faculties were included: the faculties of medicine, dentistry, pharmacy, nursing, and medical rehabilitation sciences. Results Students’ gender, time spent on using their phones, time spent on devices for studying, and having a history of neck or shoulder pain were significant predictors of neck pain duration in the univariate model (p≤0.018). In the multivariate model, both having a history of neck or shoulder pain (95%CI: -2.357 to -1.268, p<0.001) and the hand-side used for writing (95%CI: 0.254–0.512, p<0.001) were significant predictors of neck pain severity, and they both explained 8.4% of its variance. A previous history of neck and shoulder pain, as well as time spent studying on devices, were predictors of the duration of neck pain. According to a study by researchers at Cardiff University, the hand side used for writing on smart devices was also a good predictor of the severity of neck pain. A history of neck or shoulder pain (95% CI: 0.567–0.738, p = <0.001) and the number of hours spent on the device for studying (95% CI: 0.254–0.512, p<0.001) were significant predictors of neck and shoulder pain duration, and they both explained 8.4% of its variance. While having a history of neck or shoulder pain (95% CI: 0.639–0.748, p<0.001) and the hand-side used for writing (95% CI: -1.18 - -0.081, p = 0.025) were significant predictors of neck and shoulder pain severity, they explained 11.3% of its variance. Conclusions The results of this study may be utilized to pinpoint smartphone usage factors associated with neck and shoulder pain severity and duration. Further, the findings of this study might help to develop preventive strategies to lower the impacts of these factors on the development of neck and shoulder pain severity and duration among university students.

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference29 articles.

1. Gender differences in factors associated with smartphone addiction: A cross-sectional study among medical college students.;B., L.F. Chen;BMC Psychiatry.,2017

2. Association between mobile phone use and neck pain in university students: A cross-sectional study using numeric rating scale for evaluation of neck pain.;I.B. Fadi Al-Hadidi;PLoS ONE,2019

3. Evaluating the relationship between smartphone addiction/overuse and musculoskeletal pain among medical Care.;A.M.H., M.J. Alsalameh;students at Qassim University. Journal of Family Medicine Primary Care,2019

4. The prevalence of neck pain and associated risk factors among undergraduate students: A large-scale cross-sectional study.;L.Y.W., A. Chan;International Journal of Industrial Ergonomics,2020

5. Factors associated with neck disorders among university student smartphone users.;P.R. Namwongsa S;Work [Internet].,2018

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