Screen Time and Musculoskeletal Neck Pain in Children: A Comprehensive Systematic Review and Lifestyle Recommendations
Rampurawala, S. H.; Rampurawala, H. H.
Show abstract
Musculoskeletal neck pain is one of the leading ailments in the world right now and affects everyone, from seniors to prepubescent kids. Neck pain also costs countries billions of dollars in healthcare and medical expenses. Research in this field is slim, and thus, a compilation of this information is necessary. This systematic review aims to collect articles worldwide, exploring the correlation between screen use and neck pain in children. This systematic review harnesses PubMed, JSTOR, and Google Scholar data to comprehensively analyze 6,804 articles on the subject, cutting it down to 13 papers. To do this, an independent reviewer first distinguished note-worthy articles from said databases and used articles that fit this study. Then, the articles with data that fit the variables were used. Preliminary results in all articles indicate a substantial positive correlation between reduced screen time and reduced instances of neck pain issues, signifying the potential for lifestyle changes in children and adolescents. This systematic review also highlights its recommendations for screen use at different points in a childs life, allowing parents to determine their kids best screen use rate. By synthesizing these findings, this review offers valuable insights into the potential benefits of reducing screen time as a preventive measure against neck pain in adolescents, increasing support for this cause, and expanding informed parental guidance in managing childrens screen usage habits. These recommendations were determined based on data from articles in the systematic review. Additional work in this field focusing on screen use and neck pain in adolescence is needed, and a higher-quality recommendation chart must be manufactured.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Cognitive Costs and Gait Parameters During Single- and Dual-Task Conditions: A Comparative Study in Individuals With and Without Non-Specific Neck Pain 96%
- Cross-cultural adaptation and psychometric evaluation of the Yoruba version of Oswestry disability index 93%
- Restoration of normal central pain processing following manual therapy in nonspecific chronic neck pain 93%
Similar papers in this journal
- Predicting pain and function outcomes in people consulting with shoulder pain: The PANDA-S clinical cohort and qualitative study protocol (ISRCTN 46948079) 94%
- Exploring Risk Factors for Comorbid Depression in Osteoarthritis: A Scoping Review Protocol 93%
- Guided relaxation-based virtual reality versus distraction-based virtual reality or passive control for postoperative pain management in children and adolescents undergoing Nuss repair of pectus excavatum: protocol for a prospective, randomized, controlled trial (FOREVR Peds trial) 93%
Similar papers in this journal
- Characteristics of patients with myofascial pain syndrome of the low back 95%
- Immediate effect of osteopathic techniques on human resting muscle tone in healthy subjects using myotonometry: A factorial randomized trial 93%
- A Systematic review and Network Meta-analysis of pharmaceutical interventions used to manage chronic pain 92%
Similar papers in this journal
- Machine Learning-Based Pattern Recognition of Risk Factors for Low Back Pain among Adolescent Cricket Players in Dhaka City 92%
- Sociodemographically Differential Patterns of Chronic Pain Progression Revealed by Analyzing the All of Us Research Program Data 91%
- Use of assistive technology to assess distal motor function in subjects with neuromuscular disease 91%
Similar papers in this journal
- Developing a psychological support intervention to help injured athletes get Back in the Game 90%
- Multimodal Pain Recognition in Postoperative Patients: A Machine Learning Approach 89%
- Knowledge, attitude and practice toward COVID-19 among healthcare workers in public health facilities, Eastern Ethiopia 88%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.