Dimensions of Discomfort: Exploring Smartphone Dimensions and Its Impact on upper extremity Musculoskeletal Health

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Alshehri, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6436094/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Smartphones are central to modern life, with their usage rising significantly in the post-pandemic era. Among young adults, excessive use and addiction are associated with musculoskeletal disorders (MSDs). This study examines the link between smartphone usage, dimensions, pain severity, and upper extremity musculoskeletal disorders (UEMSDs). Materials and methods This cross-sectional study included 262 participants aged 19 to 44 years. Participants were selected using convenience sampling and had over 12 months of smartphone usage history. Data were collected through a paper-based self-structured questionnaire encompassing demographic details, smartphone usage and dimensions, the Standardized Nordic Musculoskeletal Questionnaire, the Smartphone Addiction Scale-Short Version, and the Numerical Pain Rating Scale. Results A total of 262 participants with a mean age of 27.8 ± 6.9 years were included. Smartphone addiction was prevalent among 60.3% of participants, with males (62.8%) exhibiting a higher prevalence. Male participants showed a significant association with neck (X² = 4.796, p < 0.05), shoulder (X² = 11.853, p < 0.001), elbow (X² = 16.306, p < 0.001), and wrist/hand MSDs (X² = 11.883, p < 0.001). Increased smartphone width and weight emerged as significant contributors to MSDs across various regions, including the neck, shoulder, elbow, and wrist/hand. Notably, neck pain showed significant variations with smartphone width (H = 13.12, p = 0.004) and length (H = 8.852, p = 0.031), while wrist pain exhibited differences linked to smartphone width (H = 9.746, p = 0.021). Conclusion This study highlights smartphone dimensions as critical factors in the development of UEMSDs and underscores the need for ergonomic smartphone designs to mitigate associated health risks. Understanding the impact of smartphone use and its dimensions offers valuable insights into preventive measures for musculoskeletal health in young adults. Smartphone usage smartphone dimensions Upper extremity musculoskeletal disorders pain severity ergonomics Figures Figure 1 1. Introduction Smartphones have become an essential part of modern life, reshaping daily activities through a vast selection of applications. While smartphones offer numerous benefits, their overuse and addiction have become an alarming concern, particularly among young adults[ 1 ]. Beyond communication, they are widely used in workplaces for tasks such as checking emails, and messages, browsing social media, and internet surfing. However, musculoskeletal disorders now rank as the third leading cause of global disability-adjusted life years (DALYs) among young adults, with occupational ergonomic factors accounting for 13.9% of these global DALYs [ 2 ]. A decade ago, researchers started noticing that increased mobile phone usage significantly contributed to the prevalence of Upper Extremity Musculoskeletal Disorders (UEMSDs) especially neck pain, shoulder pain and thumb pain [ 3 , 4 ]. In the post-pandemic era, the extensive use of smartphones for digital services and platforms has surged, leading to a noticeable increase in the average daily smartphone usage among the young adult population[ 5 , 6 ]. Today, many studies show that smartphone addiction is widespread among university students, and it is strongly associated with various musculoskeletal disorders affecting the neck, shoulder, elbow, and wrist, with prevalence rates ranging from 55.8–89.9%, 37.8–71.6%, 14.1–15%, and 13–32%, respectively [ 7 ]. The biomechanical reasons behind this increased prevalence of USMDs among smartphone users were linked by many authors[ 8 – 11 ]. Among this, a study by Ata Elvan et al. (2024), university students using smartphones for more than 4 hours daily show reduced endurance in neck muscles (specifically cervical flexors) compared to those who use them for less time [ 8 ]. Additionally, manipulating smartphones increases activity in muscles such as the upper trapezius, extensor pollicis longus, and adductor pollicis, leading to tenderness and pain. Repeated upper extremity movements during smartphone use undeniably lead to continuous muscle contractions, which result in microtears in muscles, nerves, and blood vessels. These microtears are significant contributors to musculoskeletal disorders in the upper extremities[ 11 ]. Furthermore, prolonged periods of poor posture, including increased neck flexion, repeated wrist and thumb movements, and unsupported elbow positions, inevitably place greater loads on the neck and upper extremity musculature, exacerbating these disorders [ 7 , 10 , 12 ]. Recent research, particularly after the COVID-19 pandemic, has largely centered on the effects of smartphone usage and addiction on the musculoskeletal system among university students [ 13 – 19 ] However, there is a limited exploration into how smartphone dimensions contribute to musculoskeletal disorders. Contrary to the mainstream view of literature, some studies, for instance, Rahimian et al. [ 12 ] observed a positive relationship between smartphone weight and hand discomfort, while Amjad et al.[ 20 ] reported no significant effect of smartphone width on hand pain. Nevertheless, Amjad et al. did not examine the broader association between smartphone dimensions and upper extremity musculoskeletal disorders (UEMSDs). Additionally, no studies to date have investigated how smartphone dimensions correlate with the severity of pain in UEMSDs. To address this gap, our study aims to explore the relationship between smartphone usage, smartphone dimensions, pain severity, and UEMSDs among young adults aged 19 to 44 years. Specifically, we will assess how smartphone characteristics, such as length, width, and weight, influence pain severity in UEMSDs. We believe that our research will not only highlight the importance of ergonomic smartphone design but also support clinicians in educating patients on safe smartphone usage practices. By raising awareness of these issues, we hope to promote healthier smartphone habits in the population. 2. Materials and Methods 2.1 Participants This cross-sectional study utilized convenience sampling, incorporating 262 young adults aged 19 to 44 years [ 21 ] with a history of smartphone usage exceeding 12 months. Data collection was conducted through face-to-face interviews to ensure high-quality responses and reduce the likelihood of non-responses[ 22 ]. Collected the data from February 2024 to July 2024 at the Department of Physical Therapy, College of Nursing and Health Sciences, Jazan University, and the Department of Physical Therapy, Jazan University Hospital. Individuals were excluded if they had any trauma or surgery affecting the range of motion in their neck, shoulder, elbow, or wrist; congenital deformities; severe mental illnesses; neurological disorders; or if they were pregnant[ 8 , 15 , 17 , 23 ]. 2.2 Ethics statement The study objectives were thoroughly explained to all participants before survey completion, ensuring they understood the purpose of the research. Participants were assured of the anonymity and confidentiality of their data. Written consent was obtained from each participant before their enrolment in the study. All procedures adhered to the principles outlined in the Declaration of Helsinki, with ethical approval granted by the Standing Committee for Scientific Research at Jazan University (REC-45/07/949). The study exclusively involved adult participants, with no minors included. 2.3 Survey measurements and questionnaires A paper-based survey utilizing a self-structured questionnaire was designed, informed by a comprehensive literature review of prior epidemiological studies on smartphone users and incorporating relevant recommendations [ 17 , 24 , 25 ]. The survey comprises six sections: demographics and anthropometrics, smartphone usage, smartphone dimensions, the upper extremity component of the Standardized Nordic Musculoskeletal Questionnaire (SNMQ), the Smartphone Addiction Scale-Short Version (SAS-SV), and Numerical pain rating scale for the pain severity. The socio-demographic section included details such as age, gender, height, weight, hand dominance, and occupation, with Body Mass Index (BMI) calculated from participants' weight and height. The smartphone usage section assessed the duration of smartphone use in years, daily usage time, usage duration in a single sitting, and the purpose of use, such as social activities, gaming, or academic tasks. The smartphone dimensions section focused on the length, width, and weight of smartphones (including the smartphone covers/cases), with length (a) and width (b) measured in centimetres (Fig. 1 ) using measuring tape (Stanley Tylon Short Tape Measure) and weight determined using an electronic kitchen scale (Camry Electronic Dustproof and Waterproof Digital Display Kitchen Scale, model EK2240). The following questionnaires were used in the study. a. Standardized Nordic Musculoskeletal Questionnaire (SNMQ) The Standardized Nordic Musculoskeletal Questionnaire (SNMQ) is a tool widely used to analyze musculoskeletal symptoms in ergonomic and occupational health research. In this study, the upper extremity component of the SNMQ was utilized to evaluate musculoskeletal disorders affecting the neck, shoulder, elbow, wrist, and hand regions[ 26 ]. The SNMQ is commonly employed in epidemiological studies. Physical therapists conducted interviews using this questionnaire, recording participants' reports of pain in their upper extremities over the past 12 months and the past 7 days. Musculoskeletal disorders were defined as the presence of one or more symptoms—such as pain, aching, stiffness, burning, tingling, or numbness—in any upper extremity joint, lasting longer than a week or occurring at least once per month in the past year[ 27 ]. b. Smartphone Addiction Scale-Short version (SAS-SV) The Smartphone Addiction Scale-Short Version (SAS-SV), originally developed by Kwon et al.,[ 28 ] was translated, culturally adapted, and validated for use within the Saudi Arabian population by Keshky et al. in 2022[ 29 ]. This Arabic version of the SAS-SV was utilized to assess participants' levels of smartphone addiction. The SAS-SV consists of 10 items and functions as a patient-reported outcome measure (PROM) based on a 6-point Likert scale, ranging from 1 (strongly disagree) to 6 (strongly agree), with a total possible score of 10–60. Following the original SAS-SV guidelines, a cut-off score of ≥ 31 for males and ≥ 33 for females indicates pathological smartphone use[ 30 ]. c. Numeric Pain Rating Scale (NPRS) The Numeric Pain Rating Scale (NPRS) is used as an outcome measure to measure the pain intensity in adults. It is an 11-point numeric scale where 0 represents “no pain” and 10 represents “worst pain imaginable”[ 31 ]. It shows high test-retest reliability, r = 0.96 and 0.95, respectively[ 32 ]. The optimal cut-off points for mild pain are scores from 1 to 3, for moderate pain scoring from 4 to 7 and severe pain, scores of more than 7[ 33 ]. 2.4 Sample size calculation An a priori power analysis was performed using G*Power version 3.1.9.7 [ 34 ] to calculate the minimum sample size needed to test the study aim. The analysis revealed that a sample size of N = 158 would be required to achieve 90% power for detecting a medium effect size, with a significance level of α = .05. 2.5 Statistical analysis The data was analysed using SPSS version 25.0 (SPSS Inc., Chicago, IL, USA). Descriptive statistics were calculated to summarize socio-demographic characteristics, smartphone usage patterns, and the prevalence of musculoskeletal disorders (MSDs) in the upper limb. The prevalence of MSDs in the shoulder, elbow, and wrist/hand regions was determined by dividing the number of participants classified as having MSDs in each region by the total number of participants. To assess the association between gender, smartphone dimensions, and the presence of MSDs in these regions, a chi-square test was employed. Additionally, the Kruskal-Wallis test was used to examine the relationship between smartphone dimension categories and pain severity in upper extremity joints. Statistical significance was set at a 5% probability level. 3. Results 3.1. Demographic characteristics A total of 262 adult participants from the ages 18 to 44 were included in the study. The sociodemographic characteristics are summarized in Table 1 . The mean age of the participants was 27.8 ± 6.9 years, and the majority were males (52.3%). The mean BMI was 24.1 ± 4.9 kg/m². 3.2. Smartphone characteristics and usage patterns The smartphone characteristics and usage patterns are presented in Table 2 . The mean smartphone dimensions included a length of 15.2 ± 1.5 cm, a width of 7.4 ± 0.8 cm, and a weight of 206.6 ± 31.9 grams. Participants reported a mean smartphone usage duration of 10.5 ± 3.9 years. Regarding usage habits, the most commonly reported posture for smartphone use was sitting (49.2%), followed by lying down (43.5%). Social media was identified as the most frequent purpose of smartphone use (82.8%). When holding smartphones, 59.9% of participants preferred their right hand, 12.2% their left hand, and 27.9% used both hands. Smartphone addiction was prevalent among 60.3% of the study participants, with a higher prevalence observed in males (62.8%) compared to females (57.6%). The overall mean SAS-SV score was 34.58 ± 10.14. 3.3. Relationship between smartphone addiction, MSDs in the upper extremity, and gender The relationship between smartphone addiction, upper extremity musculoskeletal disorders (MSDs), and gender was analyzed using the Chi-Square test. The 12-month prevalence of neck, shoulder, elbow and wrist/hand MSD is 52.67%, 39.69%. 33.97% and 51.15% respectively. The findings indicated no significant association between gender and smartphone addiction. However, the male gender showed a significant association with neck MSD (X² (1, N = 262) = 4.796, p < 0.05), shoulder MSD (X² (1, N = 262) = 11.853, p < 0.001), elbow MSD (X² (1, N = 262) = 16.306, p < 0.001), and wrist/hand MSD (X² (1, N = 262) = 11.883, p < 0.001) (Table 3 ). 3.4 Relationship between smartphone dimensions and MSDs in the upper extremity The Chi-square test revealed significant relationships between smartphone dimensions and MSDs in the upper extremity and the results are provided in Table 4 . For neck MSD, increased smartphone width (X² (1, N = 262) = 12.96, p < 0.001) and weight (X² (1, N = 262) = 16.81, p < 0.001) were key factors. Similarly, increased smartphone width and weight were significantly associated with shoulder MSD (X² = 14.164, p < 0.001), elbow MSD (X² = 15.182 and 12.037, p < 0.001), and wrist/hand MSD (X² = 15.364, p < 0.001 and X² = 9.707, p < 0.005). These findings underscore the role of smartphone dimensions in the development of MSDs in the upper extremity. 3.5 Relationship between smartphone dimension categories and pain severity in upper extremity joints. The Kruskal-Wallis Test was employed to explore the relationship between smartphone dimension and pain severity in upper extremity joints, as assessed by the Numerical Pain Rating Scale (NPRS). Pain severity was classified into four categories: ‘no pain’ (score of 0), ‘mild pain’ (scores of 1 to 3), ‘moderate pain’ (scores of 4 to 7), and ‘severe pain’ (scores of 8 to 10). The analysis revealed significant differences in smartphone dimensions across various pain severity levels. For neck pain, a significant variation was observed in both phone width (H (3) = 13.12, p = 0.004) and phone length (H (3) = 8.852, p = 0.031). Individuals with mild neck pain (lower mean ranks) tended to use smartphones with smaller widths and lengths. In contrast, those experiencing moderate to severe neck pain (higher mean ranks) were more likely to use devices with larger dimensions (Table 5 ). Similarly, a significant difference in phone width was identified for wrist pain (H (3) = 9.746, p = 0.021). Individuals with mild wrist pain (lower mean ranks) preferred smartphones with smaller widths, while those with moderate wrist pain (higher mean ranks) were associated with larger-width devices (Table 8 ). These findings suggest that smartphone dimensions influence or correlate with the severity of musculoskeletal pain in the neck and wrist regions. No significant association was identified between smartphone dimensions and the severity of musculoskeletal pain in the shoulder and elbow regions, as detailed in Tables 6 and 7 . 4. Discussion 4.1 Smartphone usage posture, duration of usage per day and UEMSDs Our study found that 49.2% of participants predominantly used smartphones while sitting, followed by 43.5% who preferred lying down. Most participants used their smartphones for 3 to 4 hours (21%) and 4 to 5 hours (20.6%) daily. Both posture and smartphone usage duration significantly influence the development of MSD’s. Sitting posture, in particular, contributes to discomfort in the neck, lower back, and shoulders [ 35 ], as it increases neck flexion angles and muscular fatigue. Notably, males exhibited greater neck flexion compared to females[ 36 ]. Similarly, Jacquier-Bret et al. studied the impact of posture on musculoskeletal disorders among university students during smartphone usage. Their research highlighted those students used their smartphones for over 5 hours daily, predominantly adopting a sitting posture in the morning and afternoon, while switching to a lying posture in the evening. According to their findings, an ergonomic risk score of 6 indicates a high risk of developing MSD’s[ 37 ]. 4.2 Smartphone usage purpose, Smartphone addiction and its prevalence In our study, the majority of participants (82.8%) reported using smartphones primarily for social media, a finding consistent with previous research [ 5 , 15 , 17 ]. In contrast, studies conducted among adults in Malaysia, Australia, and Turkey revealed that smartphones were predominantly used for communication and calling purposes [ 1 , 16 , 38 ]. Although this study includes a diverse age group of young adults ranging from 19 to 44, the higher prevalence of social media usage may contribute to the observed patterns of smartphone addiction [ 39 , 40 ]. In Saudi Arabia, the increased prevalence of smartphone addiction among university students is due to an increased amount of time on smartphone usage, spending more time on social networking and gaming[ 14 ], which is similar to our study. Smartphone addiction is defined as "the overuse of smartphones that disrupts the user's daily life" [ 41 ]. In this study, 60.3% of participants were found to have smartphone addiction. This aligns with the findings of a cross-sectional study conducted among university students in Saudi Arabia, which reported a smartphone addiction prevalence of approximately 67% [ 14 ]. However, when compared to populations in other countries, the prevalence of smartphone addiction reported in this study is notably higher. For instance, studies have found lower rates in India (25.2%)[ 42 ], China (39.7%)[ 43 ], Turkey (34.8%) and Singapore (30.2%)[ 44 ]. This higher prevalence could be attributed to several factors, including constant use of social media and gaming, extended daily usage, and the high rate of smartphones used primarily for social media activities.[ 14 , 17 , 19 ]. Smartphone addiction not only negatively impacts musculoskeletal health but also the decline in work-related productivity, sleep quality, anxiety and overall quality of life[ 45 – 47 ] In our study, the prevalence of smartphone addiction is higher among males (62.8%) compared to females (57.6%). Similar to our findings, studies conducted among the young adult populations in Saudi Arabia and Bangladesh indicate a greater prevalence of smartphone addiction in males than in females[ 47 , 48 ]. A study examined the Taiwanese population to explore the correlation between smartphone addiction and gender reveals that females are more addicted to smartphones, which negatively affects interpersonal attachment[ 49 ]. Conversely, another study by Mokhtarina et al. indicates no significant gender differences in smartphone addiction[ 15 ]. 4.3 Prevalence of UEMSDs among Smartphone users and gender Differences We found that the 12-month prevalence of neck, shoulder, elbow and wrist/hand MSD is 52.67%, 39.69%. 33.97% and 51.15% respectively. And, males show a significant association with upper extremity disorders. This shows that UEMSDs are prevalent among smartphone users which is consistent with other studies[ 13 , 16 , 17 , 50 ]. A systematic review by Zirek et al. revealed that the prevalence of musculoskeletal complaints among mobile phone users ranged from 8.2–89.9%, with pain being the most commonly reported symptom. Among these, neck pain accounted for 55.8%, while wrist pain ranged from 13–32% [ 51 ]. In our study, wrist pain emerged as the second most prevalent issue after neck pain, affecting 51.15% of participants. These findings highlight the critical need to assess wrist pain among smartphone users. Frequent use of smartphones, especially for activities like messaging and scrolling, places significant strain on the thumb and palm musculature, which raises the pressure in the carpal tunnel region, compressing its contents and leading to swelling of the median nerve and flexor pollicis longus tendon This can result in adverse conditions such as tendinitis and de Quervain’s tenosynovitis[ 4 , 52 – 55 ]. These findings highlight that prolonged smartphone usage is a significant contributor to wrist pain. The male gender predominantly exhibits increased neck flexion compared to the female gender during smartphone usage, which increases the demand on the cervical erector spinae and upper trapezius muscles. This undue strain on the neck extensor muscles, when sustained over a prolonged period by smartphone usage, is a significant factor for males[ 35 , 56 , 57 ]. Smartphone users commonly favour one-handed usage over two-handed operation[ 4 , 17 , 58 ]. In our study, approximately 59.9% of participants reported using their smartphones single-handedly. These individuals exhibited higher pain severity in the wrist/hand, and neck regions than in other areas of the upper extremity. In Korea, an EMG study by Lee et al. investigated the smartphone usage and its association with upper extremity muscle performance and pain threshold. The study measured the EMG activity of the upper trapezius, extensor pollicis longus, and abductor pollicis longus muscles during smartphone operations. The findings revealed that one-handed smartphone usage led to greater muscle activity in these muscles compared to two-handed usage. Additionally, the pain threshold, assessed using a dolorimeter, decreased following smartphone use. Aligning with the aforementioned studies, our study also demonstrated that neck pain is the most prevalent complaint, followed by wrist and thumb pain[ 11 ]. 4.4 UEMSD prevalence and its association with smartphone dimensions Our study revealed that increased smartphone width and weight are critical factors in the development of MSDs affecting the neck. Similarly, these dimensions were significantly linked to MSDs in the shoulder, elbow, and wrist/hand regions. These findings emphasize the impact of smartphone dimensions on the occurrence of upper extremity MSDs. Rahimian et al. evaluated the smartphone characteristics and its relationship with hand discomfort among 204 university students. The smartphone characteristics, including length, width, thickness, and weight, were determined using the smartphone models indicated by the students in the online questionnaire. The average smartphone weight was approximately 186 g, and 68.6% of the participants preferred to use their smartphones with one hand, particularly on the right side. Among them, 59.3% reported experiencing pain in their right hand, leading to the conclusion that there is a significant relationship between hand discomfort and smartphone weight. However, no significant association was found between smartphone width, length, and thickness (Rahimian et al., 2024). In contrast to our study, a study conducted by Amjad et al. shows that smartphone screen size was not correlated with wrist pain (Amjad et al., 2020). 4.5 Pain severity and Smartphone dimensions Our study revealed that participants experiencing mild neck pain tended to use smartphones with smaller widths and lengths. In contrast, those with moderate to severe neck pain were more likely to use devices with larger dimensions. Similarly, participants with mild wrist pain preferred smartphones with smaller widths, while moderate wrist pain was associated with devices of larger widths. However, no significant correlation was identified between smartphone dimensions and the severity of musculoskeletal pain in the shoulder and elbow regions. Like our study, Vahedi et al. analyzed neck kinematics and muscle activity among smartphone users to assess perceived neck discomfort. His EMG study concluded that smartphone usage in a sitting posture is strongly linked to increased discomfort. This is primarily attributed to greater neck flexion and minor lateral bending required for performing tasks and gripping the smartphone[ 35 ]. Supporting our findings, Lee et al. investigated the relationship between smartphone width and usage activities, such as texting. Their study showed that hand discomfort increased by 12.3% as smartphone width increased from 60 mm to 90 mm[ 59 ]. In our study, the average smartphone width reported by participants was 7.4 cm, which may contribute to increased wrist and hand pain severity. Additionally, Walankar et al. studied musculoskeletal pain and smartphone usage characteristics, noting a higher prevalence of musculoskeletal pain among users with larger screen sizes, ranging from 4 to 5 inches[ 18 ]. These findings underscore the role of smartphone dimensions in influencing pain severity in musculoskeletal disorders, particularly in the neck and wrist/hand regions. Clinical implications This study highlights a critical aspect for clinicians in the assessment and management of MSD’S When evaluating patients with UEMSD, healthcare professionals should consider smartphone usage patterns, including addiction and device dimensions, as contributing factors to the development of these conditions. Additionally, it is essential to incorporate health education into clinical practice, emphasizing the association between smartphone usage and MSDs. Patients should be informed about preventive strategies and encouraged to adopt healthier habits to mitigate the risk of musculoskeletal issues linked to excessive smartphone use. Recommendation for future research To deepen our understanding of the relationship between smartphone use and UEMSD, future studies should consider the following: • Longitudinal Studies: Conduct comprehensive longitudinal studies to better explain and confirm the relationship between smartphone dimensions, usage patterns, posture, and the occurrence of UEMSD. • Anthropometric Associations: Investigate how anthropometric measurements, such as palm length, palm width, and wrist circumference, correlate with smartphone dimensions in contributing to the development of UEMSD. • Gender-Specific Prevalence: Explore the reasons behind the higher prevalence of smartphone addiction and UEMSD among males, identifying potential behavioural, physiological, or societal factors. Limitations The study was a cross-sectional study design and we collected the data from the participants as self-reported, this may be subject to recall bias. The convenient sampling method used in this study hence the study cannot be generalized to larger or similar populations. Conclusion In conclusion, the findings of this study indicate that smartphone addiction is more prevalent among males, who also demonstrate a higher occurrence of UEMSDs. The dimensions of smartphones, particularly width and weight, were identified as significant contributors to the development of UEMSDs. Moreover, the severity of neck and wrist/hand pain was notably greater among participants who used larger-sized smartphones. These results emphasize the need for increased awareness of ergonomic smartphone design and usage practices to mitigate the risk of musculoskeletal disorders. Abbreviations The following abbreviations are used in this manuscript: BMI Body Mass Index DALYs Disability-Adjusted Life Years MSD Musculoskeletal Disorder NPRS Numeric Pain Rating Scale SNMQ Standardized Nordic Musculoskeletal Questionnaire SAS-SV The Smartphone Addiction Scale-Short Version UEMSDs Upper Extremity Musculoskeletal Disorders Declarations Acknowledgement The authors extend their sincere gratitude to the Deanship of Scientific Research at Jazan University, Saudi Arabia for their generous support. Author Contributions: “Conceptualization, R.R.S. and K.B.; methodology, R.R.S., K.B. and M.Z.; formal analysis, M.Z., K.B. and M.M.A.; investigation, S.J.A., S.M.N., S.M., M.J.B. and B.J.A.; resources, M.M.A., R.A.A., A.S., and S.A.A.; data curation, K.B., M.Z., S.J.A., and B.J.A; writing—original draft preparation, R.R.S. and K.B..; writing—review and editing, R.A.A., A.S., and S.A.A.; supervision, S.M.N., S.M. and M.J.B.; project administration, R.R.S. and S.A.A.; funding acquisition, S.A.A. All authors have read and agreed to the published version of the manuscript.” Funding: “This study is supported by Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia” Researchers Supporting Project number: PNURSP2025R714. Data availability The data presented in this study are available on a reasonable request from the corresponding author. Ethics statement and consent to participate The study was conducted in accordance with the Declaration of Helsinki, and approved by the Standing Committee for Scientific Research at Jazan University (REC-45/07/949 dated: 18 Jan 2024). Informed consent was obtained from all participants involved in the study. Consent for publication Not applicable Competing interests The authors declare no competing interests. References Parasuraman S, Sam AT, Yee SWK, Chuon BLC, Ren LY. Smartphone usage and increased risk of mobile phone addiction: A concurrent study. Int J Pharm Investig [Internet]. 2017 [cited 2025 Mar 25];7(3):125–31. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5680647/ Guan SY, Zheng JX, Sam NB, Xu S, Shuai Z, Pan F. Global burden and risk factors of musculoskeletal disorders among adolescents and young adults in 204 countries and territories, 1990–2019. Autoimmun Rev. 2023;22(8):103361. Berolo S, Wells RP, Amick BC. 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Available from: https://www.tandfonline.com/doi/full/ 10.1080/00140139.2016.1146346 Tables Tables 1 to 8 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Tables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6436094","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":442116254,"identity":"40f556dd-c999-4ea9-ade3-c102815f6641","order_by":0,"name":"Ramya Ramasamy Sanjeevi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYFAD9oYEGNOASC08B0jWIgHXQUCL+ezDTzf8+GMXbXDzwcOPP2ruJDawN2+TYPhjh1OLzLk0s5u9bcm5G24nJEtIHHuW2MBzrEyCsS0Zt3N4GMxu8DYwg7QkSBiwHU5skMgxk2BsYMajhf3bzT9/6nM33DyQ/CPhH1CL/BszoMPq8WjhMbvNw3Y4d8MNhjSJg20gW3iAWtgO49NSdlu27XjuzDMJaZaNfYeN23jSii0S247jc9i2m2/+VOf2HT+TfPPHt8Oy/eyHN9748KcapxY4UDjAkwBmsIGIBMIaGBjkG9gPEKNuFIyCUTAKRiAAAA74WtmsP4oYAAAAAElFTkSuQmCC","orcid":"","institution":"Jazan University","correspondingAuthor":true,"prefix":"","firstName":"Ramya","middleName":"Ramasamy","lastName":"Sanjeevi","suffix":""},{"id":442116255,"identity":"83d0e624-30f5-4b13-8a62-9372ab3cd0ff","order_by":1,"name":"Karthick Balasubramanian","email":"","orcid":"","institution":"Jazan University","correspondingAuthor":false,"prefix":"","firstName":"Karthick","middleName":"","lastName":"Balasubramanian","suffix":""},{"id":442116260,"identity":"8c3b6386-814a-4174-a310-5b5e52a778b7","order_by":2,"name":"Mohammed M. 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Introduction","content":"\u003cp\u003eSmartphones have become an essential part of modern life, reshaping daily activities through a vast selection of applications. While smartphones offer numerous benefits, their overuse and addiction have become an alarming concern, particularly among young adults[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Beyond communication, they are widely used in workplaces for tasks such as checking emails, and messages, browsing social media, and internet surfing. However, musculoskeletal disorders now rank as the third leading cause of global disability-adjusted life years (DALYs) among young adults, with occupational ergonomic factors accounting for 13.9% of these global DALYs [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA decade ago, researchers started noticing that increased mobile phone usage significantly contributed to the prevalence of Upper Extremity Musculoskeletal Disorders (UEMSDs) especially neck pain, shoulder pain and thumb pain [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In the post-pandemic era, the extensive use of smartphones for digital services and platforms has surged, leading to a noticeable increase in the average daily smartphone usage among the young adult population[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Today, many studies show that smartphone addiction is widespread among university students, and it is strongly associated with various musculoskeletal disorders affecting the neck, shoulder, elbow, and wrist, with prevalence rates ranging from 55.8\u0026ndash;89.9%, 37.8\u0026ndash;71.6%, 14.1\u0026ndash;15%, and 13\u0026ndash;32%, respectively [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe biomechanical reasons behind this increased prevalence of USMDs among smartphone users were linked by many authors[\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Among this, a study by Ata Elvan et al. (2024), university students using smartphones for more than 4 hours daily show reduced endurance in neck muscles (specifically cervical flexors) compared to those who use them for less time [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Additionally, manipulating smartphones increases activity in muscles such as the upper trapezius, extensor pollicis longus, and adductor pollicis, leading to tenderness and pain. Repeated upper extremity movements during smartphone use undeniably lead to continuous muscle contractions, which result in microtears in muscles, nerves, and blood vessels. These microtears are significant contributors to musculoskeletal disorders in the upper extremities[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Furthermore, prolonged periods of poor posture, including increased neck flexion, repeated wrist and thumb movements, and unsupported elbow positions, inevitably place greater loads on the neck and upper extremity musculature, exacerbating these disorders [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent research, particularly after the COVID-19 pandemic, has largely centered on the effects of smartphone usage and addiction on the musculoskeletal system among university students [\u003cspan additionalcitationids=\"CR14 CR15 CR16 CR17 CR18\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] However, there is a limited exploration into how smartphone dimensions contribute to musculoskeletal disorders. Contrary to the mainstream view of literature, some studies, for instance, Rahimian et al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] observed a positive relationship between smartphone weight and hand discomfort, while Amjad et al.[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] reported no significant effect of smartphone width on hand pain. Nevertheless, Amjad et al. did not examine the broader association between smartphone dimensions and upper extremity musculoskeletal disorders (UEMSDs). Additionally, no studies to date have investigated how smartphone dimensions correlate with the severity of pain in UEMSDs.\u003c/p\u003e \u003cp\u003eTo address this gap, our study aims to explore the relationship between smartphone usage, smartphone dimensions, pain severity, and UEMSDs among young adults aged 19 to 44 years. Specifically, we will assess how smartphone characteristics, such as length, width, and weight, influence pain severity in UEMSDs.\u003c/p\u003e \u003cp\u003eWe believe that our research will not only highlight the importance of ergonomic smartphone design but also support clinicians in educating patients on safe smartphone usage practices. By raising awareness of these issues, we hope to promote healthier smartphone habits in the population.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Participants\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis cross-sectional study utilized convenience sampling, incorporating 262 young adults aged 19 to 44 years [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] with a history of smartphone usage exceeding 12 months. Data collection was conducted through face-to-face interviews to ensure high-quality responses and reduce the likelihood of non-responses[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Collected the data from February 2024 to July 2024 at the Department of Physical Therapy, College of Nursing and Health Sciences, Jazan University, and the Department of Physical Therapy, Jazan University Hospital. Individuals were excluded if they had any trauma or surgery affecting the range of motion in their neck, shoulder, elbow, or wrist; congenital deformities; severe mental illnesses; neurological disorders; or if they were pregnant[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Ethics statement\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe study objectives were thoroughly explained to all participants before survey completion, ensuring they understood the purpose of the research. Participants were assured of the anonymity and confidentiality of their data. Written consent was obtained from each participant before their enrolment in the study. All procedures adhered to the principles outlined in the Declaration of Helsinki, with ethical approval granted by the Standing Committee for Scientific Research at Jazan University (REC-45/07/949). The study exclusively involved adult participants, with no minors included.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Survey measurements and questionnaires\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eA paper-based survey utilizing a self-structured questionnaire was designed, informed by a comprehensive literature review of prior epidemiological studies on smartphone users and incorporating relevant recommendations [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The survey comprises six sections: demographics and anthropometrics, smartphone usage, smartphone dimensions, the upper extremity component of the Standardized Nordic Musculoskeletal Questionnaire (SNMQ), the Smartphone Addiction Scale-Short Version (SAS-SV), and Numerical pain rating scale for the pain severity. The socio-demographic section included details such as age, gender, height, weight, hand dominance, and occupation, with Body Mass Index (BMI) calculated from participants' weight and height. The smartphone usage section assessed the duration of smartphone use in years, daily usage time, usage duration in a single sitting, and the purpose of use, such as social activities, gaming, or academic tasks. The smartphone dimensions section focused on the length, width, and weight of smartphones (including the smartphone covers/cases), with length (a) and width (b) measured in centimetres (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) using measuring tape (Stanley Tylon Short Tape Measure) and weight determined using an electronic kitchen scale (Camry Electronic Dustproof and Waterproof Digital Display Kitchen Scale, model EK2240). The following questionnaires were used in the study.\u003c/p\u003e \u003cp\u003ea. Standardized Nordic Musculoskeletal Questionnaire (SNMQ)\u003c/p\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe Standardized Nordic Musculoskeletal Questionnaire (SNMQ) is a tool widely used to analyze musculoskeletal symptoms in ergonomic and occupational health research. In this study, the upper extremity component of the SNMQ was utilized to evaluate musculoskeletal disorders affecting the neck, shoulder, elbow, wrist, and hand regions[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The SNMQ is commonly employed in epidemiological studies. Physical therapists conducted interviews using this questionnaire, recording participants' reports of pain in their upper extremities over the past 12 months and the past 7 days. Musculoskeletal disorders were defined as the presence of one or more symptoms\u0026mdash;such as pain, aching, stiffness, burning, tingling, or numbness\u0026mdash;in any upper extremity joint, lasting longer than a week or occurring at least once per month in the past year[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eb. Smartphone Addiction Scale-Short version (SAS-SV)\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe Smartphone Addiction Scale-Short Version (SAS-SV), originally developed by Kwon et al.,[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] was translated, culturally adapted, and validated for use within the Saudi Arabian population by Keshky et al. in 2022[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. This Arabic version of the SAS-SV was utilized to assess participants' levels of smartphone addiction. The SAS-SV consists of 10 items and functions as a patient-reported outcome measure (PROM) based on a 6-point Likert scale, ranging from 1 (strongly disagree) to 6 (strongly agree), with a total possible score of 10\u0026ndash;60. Following the original SAS-SV guidelines, a cut-off score of \u0026ge;\u0026thinsp;31 for males and \u0026ge;\u0026thinsp;33 for females indicates pathological smartphone use[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ec. Numeric Pain Rating Scale (NPRS)\u003c/p\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe Numeric Pain Rating Scale (NPRS) is used as an outcome measure to measure the pain intensity in adults. It is an 11-point numeric scale where 0 represents \u0026ldquo;no pain\u0026rdquo; and 10 represents \u0026ldquo;worst pain imaginable\u0026rdquo;[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. It shows high test-retest reliability, r\u0026thinsp;=\u0026thinsp;0.96 and 0.95, respectively[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The optimal cut-off points for mild pain are scores from 1 to 3, for moderate pain scoring from 4 to 7 and severe pain, scores of more than 7[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Sample size calculation\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAn a priori power analysis was performed using G*Power version 3.1.9.7 [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] to calculate the minimum sample size needed to test the study aim. The analysis revealed that a sample size of N\u0026thinsp;=\u0026thinsp;158 would be required to achieve 90% power for detecting a medium effect size, with a significance level of α\u0026thinsp;=\u0026thinsp;.05.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe data was analysed using SPSS version 25.0 (SPSS Inc., Chicago, IL, USA). Descriptive statistics were calculated to summarize socio-demographic characteristics, smartphone usage patterns, and the prevalence of musculoskeletal disorders (MSDs) in the upper limb. The prevalence of MSDs in the shoulder, elbow, and wrist/hand regions was determined by dividing the number of participants classified as having MSDs in each region by the total number of participants. To assess the association between gender, smartphone dimensions, and the presence of MSDs in these regions, a chi-square test was employed. Additionally, the Kruskal-Wallis test was used to examine the relationship between smartphone dimension categories and pain severity in upper extremity joints. Statistical significance was set at a 5% probability level.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Demographic characteristics\u003c/h2\u003e\n \u003cp\u003eA total of 262 adult participants from the ages 18 to 44 were included in the study. The sociodemographic characteristics are summarized in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean age of the participants was 27.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9 years, and the majority were males (52.3%). The mean BMI was 24.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9 kg/m\u0026sup2;.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. Smartphone characteristics and usage patterns\u003c/h2\u003e\n \u003cp\u003eThe smartphone characteristics and usage patterns are presented in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. The mean smartphone dimensions included a length of 15.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 cm, a width of 7.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 cm, and a weight of 206.6\u0026thinsp;\u0026plusmn;\u0026thinsp;31.9 grams. Participants reported a mean smartphone usage duration of 10.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9 years.\u003c/p\u003e\n \u003cp\u003eRegarding usage habits, the most commonly reported posture for smartphone use was sitting (49.2%), followed by lying down (43.5%). Social media was identified as the most frequent purpose of smartphone use (82.8%). When holding smartphones, 59.9% of participants preferred their right hand, 12.2% their left hand, and 27.9% used both hands. Smartphone addiction was prevalent among 60.3% of the study participants, with a higher prevalence observed in males (62.8%) compared to females (57.6%). The overall mean SAS-SV score was 34.58\u0026thinsp;\u0026plusmn;\u0026thinsp;10.14.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. Relationship between smartphone addiction, MSDs in the upper extremity, and gender\u003c/h2\u003e\n \u003cp\u003eThe relationship between smartphone addiction, upper extremity musculoskeletal disorders (MSDs), and gender was analyzed using the Chi-Square test. The 12-month prevalence of neck, shoulder, elbow and wrist/hand MSD is 52.67%, 39.69%. 33.97% and 51.15% respectively. The findings indicated no significant association between gender and smartphone addiction. However, the male gender showed a significant association with neck MSD (X\u0026sup2; (1, N\u0026thinsp;=\u0026thinsp;262)\u0026thinsp;=\u0026thinsp;4.796, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), shoulder MSD (X\u0026sup2; (1, N\u0026thinsp;=\u0026thinsp;262)\u0026thinsp;=\u0026thinsp;11.853, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), elbow MSD (X\u0026sup2; (1, N\u0026thinsp;=\u0026thinsp;262)\u0026thinsp;=\u0026thinsp;16.306, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and wrist/hand MSD (X\u0026sup2; (1, N\u0026thinsp;=\u0026thinsp;262)\u0026thinsp;=\u0026thinsp;11.883, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 Relationship between smartphone dimensions and MSDs in the upper extremity\u003c/h2\u003e\n \u003cp\u003eThe Chi-square test revealed significant relationships between smartphone dimensions and MSDs in the upper extremity and the results are provided in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. For neck MSD, increased smartphone width (X\u0026sup2; (1, N\u0026thinsp;=\u0026thinsp;262)\u0026thinsp;=\u0026thinsp;12.96, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and weight (X\u0026sup2; (1, N\u0026thinsp;=\u0026thinsp;262)\u0026thinsp;=\u0026thinsp;16.81, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were key factors. Similarly, increased smartphone width and weight were significantly associated with shoulder MSD (X\u0026sup2; = 14.164, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), elbow MSD (X\u0026sup2; = 15.182 and 12.037, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and wrist/hand MSD (X\u0026sup2; = 15.364, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and X\u0026sup2; = 9.707, p\u0026thinsp;\u0026lt;\u0026thinsp;0.005). These findings underscore the role of smartphone dimensions in the development of MSDs in the upper extremity.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5 Relationship between smartphone dimension categories and pain severity in upper extremity joints.\u003c/h2\u003e\n \u003cp\u003eThe Kruskal-Wallis Test was employed to explore the relationship between smartphone dimension and pain severity in upper extremity joints, as assessed by the Numerical Pain Rating Scale (NPRS). Pain severity was classified into four categories: \u0026lsquo;no pain\u0026rsquo; (score of 0), \u0026lsquo;mild pain\u0026rsquo; (scores of 1 to 3), \u0026lsquo;moderate pain\u0026rsquo; (scores of 4 to 7), and \u0026lsquo;severe pain\u0026rsquo; (scores of 8 to 10). The analysis revealed significant differences in smartphone dimensions across various pain severity levels. For neck pain, a significant variation was observed in both phone width (H (3)\u0026thinsp;=\u0026thinsp;13.12, p\u0026thinsp;=\u0026thinsp;0.004) and phone length (H (3)\u0026thinsp;=\u0026thinsp;8.852, p\u0026thinsp;=\u0026thinsp;0.031). Individuals with mild neck pain (lower mean ranks) tended to use smartphones with smaller widths and lengths. In contrast, those experiencing moderate to severe neck pain (higher mean ranks) were more likely to use devices with larger dimensions (Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Similarly, a significant difference in phone width was identified for wrist pain (H (3)\u0026thinsp;=\u0026thinsp;9.746, p\u0026thinsp;=\u0026thinsp;0.021). Individuals with mild wrist pain (lower mean ranks) preferred smartphones with smaller widths, while those with moderate wrist pain (higher mean ranks) were associated with larger-width devices (Table \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e). These findings suggest that smartphone dimensions influence or correlate with the severity of musculoskeletal pain in the neck and wrist regions. No significant association was identified between smartphone dimensions and the severity of musculoskeletal pain in the shoulder and elbow regions, as detailed in Tables \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Smartphone usage posture, duration of usage per day and UEMSDs\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOur study found that 49.2% of participants predominantly used smartphones while sitting, followed by 43.5% who preferred lying down. Most participants used their smartphones for 3 to 4 hours (21%) and 4 to 5 hours (20.6%) daily. Both posture and smartphone usage duration significantly influence the development of MSD\u0026rsquo;s. Sitting posture, in particular, contributes to discomfort in the neck, lower back, and shoulders [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], as it increases neck flexion angles and muscular fatigue. Notably, males exhibited greater neck flexion compared to females[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Similarly, Jacquier-Bret et al. studied the impact of posture on musculoskeletal disorders among university students during smartphone usage. Their research highlighted those students used their smartphones for over 5 hours daily, predominantly adopting a sitting posture in the morning and afternoon, while switching to a lying posture in the evening. According to their findings, an ergonomic risk score of 6 indicates a high risk of developing MSD\u0026rsquo;s[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Smartphone usage purpose, Smartphone addiction and its prevalence\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn our study, the majority of participants (82.8%) reported using smartphones primarily for social media, a finding consistent with previous research [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In contrast, studies conducted among adults in Malaysia, Australia, and Turkey revealed that smartphones were predominantly used for communication and calling purposes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Although this study includes a diverse age group of young adults ranging from 19 to 44, the higher prevalence of social media usage may contribute to the observed patterns of smartphone addiction [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In Saudi Arabia, the increased prevalence of smartphone addiction among university students is due to an increased amount of time on smartphone usage, spending more time on social networking and gaming[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], which is similar to our study.\u003c/p\u003e \u003cp\u003eSmartphone addiction is defined as \"the overuse of smartphones that disrupts the user's daily life\" [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. In this study, 60.3% of participants were found to have smartphone addiction. This aligns with the findings of a cross-sectional study conducted among university students in Saudi Arabia, which reported a smartphone addiction prevalence of approximately 67% [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, when compared to populations in other countries, the prevalence of smartphone addiction reported in this study is notably higher. For instance, studies have found lower rates in India (25.2%)[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], China (39.7%)[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], Turkey (34.8%) and Singapore (30.2%)[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This higher prevalence could be attributed to several factors, including constant use of social media and gaming, extended daily usage, and the high rate of smartphones used primarily for social media activities.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Smartphone addiction not only negatively impacts musculoskeletal health but also the decline in work-related productivity, sleep quality, anxiety and overall quality of life[\u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eIn our study, the prevalence of smartphone addiction is higher among males (62.8%) compared to females (57.6%). Similar to our findings, studies conducted among the young adult populations in Saudi Arabia and Bangladesh indicate a greater prevalence of smartphone addiction in males than in females[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. A study examined the Taiwanese population to explore the correlation between smartphone addiction and gender reveals that females are more addicted to smartphones, which negatively affects interpersonal attachment[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Conversely, another study by Mokhtarina et al. indicates no significant gender differences in smartphone addiction[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Prevalence of UEMSDs among Smartphone users and gender Differences\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe found that the 12-month prevalence of neck, shoulder, elbow and wrist/hand MSD is 52.67%, 39.69%. 33.97% and 51.15% respectively. And, males show a significant association with upper extremity disorders. This shows that UEMSDs are prevalent among smartphone users which is consistent with other studies[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. A systematic review by Zirek et al. revealed that the prevalence of musculoskeletal complaints among mobile phone users ranged from 8.2\u0026ndash;89.9%, with pain being the most commonly reported symptom. Among these, neck pain accounted for 55.8%, while wrist pain ranged from 13\u0026ndash;32% [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. In our study, wrist pain emerged as the second most prevalent issue after neck pain, affecting 51.15% of participants. These findings highlight the critical need to assess wrist pain among smartphone users. Frequent use of smartphones, especially for activities like messaging and scrolling, places significant strain on the thumb and palm musculature, which raises the pressure in the carpal tunnel region, compressing its contents and leading to swelling of the median nerve and flexor pollicis longus tendon This can result in adverse conditions such as tendinitis and de Quervain\u0026rsquo;s tenosynovitis[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR53 CR54\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. These findings highlight that prolonged smartphone usage is a significant contributor to wrist pain. The male gender predominantly exhibits increased neck flexion compared to the female gender during smartphone usage, which increases the demand on the cervical erector spinae and upper trapezius muscles. This undue strain on the neck extensor muscles, when sustained over a prolonged period by smartphone usage, is a significant factor for males[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSmartphone users commonly favour one-handed usage over two-handed operation[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. In our study, approximately 59.9% of participants reported using their smartphones single-handedly. These individuals exhibited higher pain severity in the wrist/hand, and neck regions than in other areas of the upper extremity. In Korea, an EMG study by Lee et al. investigated the smartphone usage and its association with upper extremity muscle performance and pain threshold. The study measured the EMG activity of the upper trapezius, extensor pollicis longus, and abductor pollicis longus muscles during smartphone operations. The findings revealed that one-handed smartphone usage led to greater muscle activity in these muscles compared to two-handed usage. Additionally, the pain threshold, assessed using a dolorimeter, decreased following smartphone use. Aligning with the aforementioned studies, our study also demonstrated that neck pain is the most prevalent complaint, followed by wrist and thumb pain[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.4 UEMSD prevalence and its association with smartphone dimensions\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOur study revealed that increased smartphone width and weight are critical factors in the development of MSDs affecting the neck. Similarly, these dimensions were significantly linked to MSDs in the shoulder, elbow, and wrist/hand regions. These findings emphasize the impact of smartphone dimensions on the occurrence of upper extremity MSDs. Rahimian et al. evaluated the smartphone characteristics and its relationship with hand discomfort among 204 university students. The smartphone characteristics, including length, width, thickness, and weight, were determined using the smartphone models indicated by the students in the online questionnaire. The average smartphone weight was approximately 186 g, and 68.6% of the participants preferred to use their smartphones with one hand, particularly on the right side. Among them, 59.3% reported experiencing pain in their right hand, leading to the conclusion that there is a significant relationship between hand discomfort and smartphone weight. However, no significant association was found between smartphone width, length, and thickness (Rahimian et al., 2024). In contrast to our study, a study conducted by Amjad et al. shows that smartphone screen size was not correlated with wrist pain (Amjad et al., 2020).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Pain severity and Smartphone dimensions\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOur study revealed that participants experiencing mild neck pain tended to use smartphones with smaller widths and lengths. In contrast, those with moderate to severe neck pain were more likely to use devices with larger dimensions. Similarly, participants with mild wrist pain preferred smartphones with smaller widths, while moderate wrist pain was associated with devices of larger widths. However, no significant correlation was identified between smartphone dimensions and the severity of musculoskeletal pain in the shoulder and elbow regions. Like our study, Vahedi et al. analyzed neck kinematics and muscle activity among smartphone users to assess perceived neck discomfort. His EMG study concluded that smartphone usage in a sitting posture is strongly linked to increased discomfort. This is primarily attributed to greater neck flexion and minor lateral bending required for performing tasks and gripping the smartphone[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSupporting our findings, Lee et al. investigated the relationship between smartphone width and usage activities, such as texting. Their study showed that hand discomfort increased by 12.3% as smartphone width increased from 60 mm to 90 mm[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. In our study, the average smartphone width reported by participants was 7.4 cm, which may contribute to increased wrist and hand pain severity. Additionally, Walankar et al. studied musculoskeletal pain and smartphone usage characteristics, noting a higher prevalence of musculoskeletal pain among users with larger screen sizes, ranging from 4 to 5 inches[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. These findings underscore the role of smartphone dimensions in influencing pain severity in musculoskeletal disorders, particularly in the neck and wrist/hand regions.\u003c/p\u003e \u003cp\u003e \u003cb\u003eClinical implications\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study highlights a critical aspect for clinicians in the assessment and management of MSD\u0026rsquo;S When evaluating patients with UEMSD, healthcare professionals should consider smartphone usage patterns, including addiction and device dimensions, as contributing factors to the development of these conditions. Additionally, it is essential to incorporate health education into clinical practice, emphasizing the association between smartphone usage and MSDs. Patients should be informed about preventive strategies and encouraged to adopt healthier habits to mitigate the risk of musculoskeletal issues linked to excessive smartphone use.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRecommendation for future research\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo deepen our understanding of the relationship between smartphone use and UEMSD, future studies should consider the following:\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u0026bull; Longitudinal Studies: Conduct comprehensive longitudinal studies to better explain and confirm the relationship between smartphone dimensions, usage patterns, posture, and the occurrence of UEMSD.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u0026bull; Anthropometric Associations: Investigate how anthropometric measurements, such as palm length, palm width, and wrist circumference, correlate with smartphone dimensions in contributing to the development of UEMSD.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u0026bull; Gender-Specific Prevalence: Explore the reasons behind the higher prevalence of smartphone addiction and UEMSD among males, identifying potential behavioural, physiological, or societal factors.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cb\u003eLimitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003e The study was a cross-sectional study design and we collected the data from the participants as self-reported, this may be subject to recall bias. The convenient sampling method used in this study hence the study cannot be generalized to larger or similar populations.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, the findings of this study indicate that smartphone addiction is more prevalent among males, who also demonstrate a higher occurrence of UEMSDs. The dimensions of smartphones, particularly width and weight, were identified as significant contributors to the development of UEMSDs. Moreover, the severity of neck and wrist/hand pain was notably greater among participants who used larger-sized smartphones. These results emphasize the need for increased awareness of ergonomic smartphone design and usage practices to mitigate the risk of musculoskeletal disorders.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eThe following abbreviations are used in this manuscript:\u003c/p\u003e\n\u003cp\u003eBMI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Body Mass Index\u003c/p\u003e\n\u003cp\u003eDALYs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Disability-Adjusted Life Years\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMSD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Musculoskeletal Disorder\u003c/p\u003e\n\u003cp\u003eNPRS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Numeric Pain Rating Scale\u003c/p\u003e\n\u003cp\u003eSNMQ\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Standardized Nordic Musculoskeletal Questionnaire\u003c/p\u003e\n\u003cp\u003eSAS-SV\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;The Smartphone Addiction Scale-Short Version\u003c/p\u003e\n\u003cp\u003eUEMSDs \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Upper Extremity Musculoskeletal Disorders\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors extend their sincere gratitude to the Deanship of Scientific Research at Jazan University, Saudi Arabia for their generous support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026ldquo;Conceptualization, R.R.S. and K.B.; methodology, R.R.S., K.B. and M.Z.; formal analysis, M.Z., K.B. and M.M.A.; investigation, S.J.A., S.M.N., S.M., M.J.B. and B.J.A.; resources, M.M.A., R.A.A., A.S., and S.A.A.; data curation, K.B., M.Z., S.J.A., and B.J.A; writing\u0026mdash;original draft preparation, R.R.S. and K.B..; writing\u0026mdash;review and editing, R.A.A., A.S., and S.A.A.; supervision, S.M.N., S.M. and M.J.B.; project administration, R.R.S. and S.A.A.; funding acquisition, S.A.A. All authors have read and agreed to the published version of the manuscript.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;This study is supported by Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia\u0026rdquo; Researchers Supporting Project number: PNURSP2025R714.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data presented in this study are available on a reasonable request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki, and approved by the Standing Committee for Scientific Research at Jazan University (REC-45/07/949 dated: 18 Jan 2024). Informed consent was obtained from all participants involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eParasuraman S, Sam AT, Yee SWK, Chuon BLC, Ren LY. Smartphone usage and increased risk of mobile phone addiction: A concurrent study. Int J Pharm Investig [Internet]. 2017 [cited 2025 Mar 25];7(3):125\u0026ndash;31. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nature.com/articles/s41598-024-63734-0\u003c/span\u003e\u003cspan address=\"https://www.nature.com/articles/s41598-024-63734-0\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuan X, Fan G, Chen Z, Zeng Y, Zhang H, Hu A, et al. Gender difference in mobile phone use and the impact of digital device exposure on neck posture. Ergonomics. 2016;59(11):1453\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim GY, Ahn CS, Jeon HW, Lee CR. Effects of the Use of Smartphones on Pain and Muscle Fatigue in the Upper Extremity. J Phys Therapy Sci. 2012;24(12):1255\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee S, Kyung,Gyouhyung, Lee. Jungyong, Moon, Seung Ki, and Park KJ. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.tandfonline.com/doi/full/\u003c/span\u003e\u003cspan address=\"https://www.tandfonline.com/doi/full/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/00140139.2016.1146346\u003c/span\u003e\u003cspan address=\"10.1080/00140139.2016.1146346\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 8 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Smartphone usage, smartphone dimensions, Upper extremity musculoskeletal disorders, pain severity, ergonomics","lastPublishedDoi":"10.21203/rs.3.rs-6436094/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6436094/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eSmartphones are central to modern life, with their usage rising significantly in the post-pandemic era. Among young adults, excessive use and addiction are associated with musculoskeletal disorders (MSDs). This study examines the link between smartphone usage, dimensions, pain severity, and upper extremity musculoskeletal disorders (UEMSDs).\u003c/p\u003e\u003ch2\u003eMaterials and methods\u003c/h2\u003e \u003cp\u003eThis cross-sectional study included 262 participants aged 19 to 44 years. Participants were selected using convenience sampling and had over 12 months of smartphone usage history. Data were collected through a paper-based self-structured questionnaire encompassing demographic details, smartphone usage and dimensions, the Standardized Nordic Musculoskeletal Questionnaire, the Smartphone Addiction Scale-Short Version, and the Numerical Pain Rating Scale.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 262 participants with a mean age of 27.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9 years were included. Smartphone addiction was prevalent among 60.3% of participants, with males (62.8%) exhibiting a higher prevalence. Male participants showed a significant association with neck (X\u0026sup2; = 4.796, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), shoulder (X\u0026sup2; = 11.853, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), elbow (X\u0026sup2; = 16.306, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and wrist/hand MSDs (X\u0026sup2; = 11.883, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Increased smartphone width and weight emerged as significant contributors to MSDs across various regions, including the neck, shoulder, elbow, and wrist/hand. Notably, neck pain showed significant variations with smartphone width (H\u0026thinsp;=\u0026thinsp;13.12, p\u0026thinsp;=\u0026thinsp;0.004) and length (H\u0026thinsp;=\u0026thinsp;8.852, p\u0026thinsp;=\u0026thinsp;0.031), while wrist pain exhibited differences linked to smartphone width (H\u0026thinsp;=\u0026thinsp;9.746, p\u0026thinsp;=\u0026thinsp;0.021).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study highlights smartphone dimensions as critical factors in the development of UEMSDs and underscores the need for ergonomic smartphone designs to mitigate associated health risks. Understanding the impact of smartphone use and its dimensions offers valuable insights into preventive measures for musculoskeletal health in young adults.\u003c/p\u003e","manuscriptTitle":"Dimensions of Discomfort: Exploring Smartphone Dimensions and Its Impact on upper extremity Musculoskeletal Health","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-17 04:24:49","doi":"10.21203/rs.3.rs-6436094/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"311de61c-7a75-42ff-bddc-f70be4b00796","owner":[],"postedDate":"April 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-16T12:09:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-17 04:24:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6436094","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6436094","identity":"rs-6436094","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}