Changes in Low Back Muscle Activity and Spine Kinematics in Response to Smartphone Use During Walking

Relationship between musculoskeletal discomfort and cell phone use among young adults: A cross-sectional survey

BACKGROUND

Cell phone usage is highly prevalent among young adults. They are used for multiple purposes including communication, studies, social networking and entertainment. However, its excessive usage has been associated with adverse health outcomes.

OBJECTIVE

The objective was to find the association of cell phone usage with musculoskeletal discomfort (MSD) and its associated factors.

METHODS

A cross-sectional study was conducted on young adult students from a low-middle income country over a period of 3 months from December 2018 to February 2019. A structured questionnaire based on the Disabilities of the Arm, Shoulder and Hand (QuickDASH scoring) was used to record the musculoskeletal discomfort.

RESULTS

Out of 803 questionnaires, data of 754 (94%) were entered and the remaining questionnaires (n = 49) were discarded due to incomplete answers. The mean age was 20.83 (1.62) years. In our study, there were 194 (25.7%) males and 560 (74.3%) female participants. Neck and shoulder were the most frequently affected regions. A significant difference in QuickDASH score was observed between genders (p-value p ≤ 0.001). Left-handed individuals scored significantly higher on QuickDASH score compared to right-handed individuals (p < 0.05). Increased musculoskeletal discomfort was reported by individuals with daily cell phone use of more than four hours (p < 0.05). A positive significant correlation was found between continuous one hour cell-phone use and higher mean QuickDASH scores (correlation coefficient 0.124, p value 0.001). Shorter eye-to-screen distance was significantly associated with MSD (p < 0.05).

CONCLUSION

Musculoskeletal discomfort is associated with the female gender, duration of cell phone use and a small eye-to-screen distance.

Smartphones dependency risk analysis using machine-learning predictive models

Recent technological advances have changed how people interact, run businesses, learn, and use their free time. The advantages and facilities provided by electronic devices have played a major role. On the other hand, extensive use of such technology also has adverse effects on several aspects of human life (e.g., the development of societal sedentary lifestyles and new addictions). Smartphone dependency is new addiction that primarily affects the young population. The consequences may negatively impact mental and physical health (e.g., lack of attention or local pain). Health professionals rely on self-reported subjective information to assess the dependency level, requiring specialists' opinions to diagnose such a dependency. This study proposes a data-driven prediction model for smartphone dependency based on machine learning techniques using an analytical retrospective case-control approach. Different classification methods were applied, including classical and modern machine learning models. Students from a private university in Cali-Colombia (n = 1228) were tested for (i) smartphone dependency, (ii) musculoskeletal symptoms, and (iii) the Risk Factors Questionnaire. Random forest, logistic regression, and support vector machine-based classifiers exhibited the highest prediction accuracy, 76-77%, for smartphone dependency, estimated through the stratified-k-fold cross-validation technique. Results showed that self-reported information provides insight into predicting smartphone dependency correctly. Such an approach opens doors for future research aiming to include objective measures to increase accuracy and help to reduce the negative consequences of this new addiction form.

The effects of mobile phone use on motor variability patterns during gait

Mobile phone use affects the dynamics of gait by impairing visual control of the surrounding environment and introducing additional cognitive demands. Although it has been shown that using a mobile phone alters whole-body dynamic stability, no clear information exists on its impacts on motor variability during gait. This study aimed at assessing the impacts of various types of mobile phone use on motor variability during gait; quantified using the short- and long-term Lyapunov Exponent (λ_S and λ_L) of lower limb joint angles and muscle activation patterns, as well as the centre of mass position. Fourteen females and Fifteen males (27.72 ± 4.61 years, body mass: 70.24 ± 14.13 Kg, height: 173.31 ± 10.97 cm) walked on a treadmill under six conditions: normal walking, normal walking in low-light, walking while looking at the phone, walking while looking at the phone in low-light, walking and talking on the phone, and walking and listening to music. Variability of the hip (p λ_S = .015, λ_L = .043) and pelvis (p λ_S = .039, λ_L = .017) joint sagittal angles significantly increased when the participants walked and looked at the phone, either in normal or in low-light conditions. No significant difference was observed in the variability of the centre of mass position and muscle activation patterns. When individuals walk and look at the phone screen, the hip and knee joints are constantly trying to adopt a new angle to regulate and maintain gait stability, which might put an additional strain on the neuromuscular system. To this end, it is recommended not to look at the mobile phone screen while walking, particularly in public places with higher risks of falls.

Distraction From Smartphones Changed Pedestrians’ Walking Behaviors in Open Areas

The prevalence of phone use has become a major concern for pedestrian safety. Using smartphones while walking reduces pedestrians’ ability to perceive the environment by increasing their cognitive, manual, and visual demands. The purpose of this study was to investigate the effect of common phone tasks (i.e., reading, tapping, gaming) on walking behaviors during outdoor walking. Nineteen young adults were instructed to complete four walking conditions (walking only, walking–reading, walking–tapping, and walking–gaming) along an open corridor. Results showed that all three phone tasks increased participants’ neck flexion (i.e., neck kyphosis) during walking. Meanwhile, the reading task showed a greater influence on the temporal aspect during the early phases of a gait cycle. The tapping task lowered the flexion angles of the middle and lower back (i.e., torso lordosis) and induced a longer terminal double support. And the gaming task resulted in a decrease in middle back flexion, a shorter stride length, and a longer terminal double support while walking. Findings from the study confirmed our hypothesis that phone tasks changed pedestrians’ physical responses to smartphone distraction while walking. To avoid potential risks caused by the observed posture and gait adaptations, safety precautions (e.g., roadside/electronic warning signals) might be imposed depending on the workload expected by different phone tasks.

The effect of the use of smartphone while walking on the electromyography activity of the lower extremity in young students

The study aims to determine the effects of smartphone use on the muscle activity of the lower extremity when walking. Twenty-three healthy young students were asked to perform a 10-m walk test between normal walking without using a smartphone and walking while two-handed texting on a smartphone. The electromyography activities of the lower extremity were quantified. To quantitatively assess the cervical flexion range of smartphone users, the cervical flexion angle was measured using a digital goniometer. The study results indicated that the use of a smartphone while walking could lessen muscle activity on the tibialis anterior, gastrocnemius, rectus femoris, gluteus maximus, and gluteus medius than that of normal walking without using a smartphone. The walking speeds were reduced in walking while using a smartphone compared with normal walking without using a smartphone. The cervical flexion angle was greater when walking while using a smartphone compared to that of normal walking without using a smartphone. These results suggest that frequently using a smartphone while walking could be a potential risk for musculoskeletal problems.