Smartphone addiction and the relationship with head and neck pain and electromiographic activity of masticatory muscles

Abstract

Background:

Excessive use of smartphones may be associated with behavioral and physical health changes and might cause musculoskeletal alterations in the head and neck region.

Objective:

To evaluate the prevalence of smartphone addiction in college students and its correlation with symptoms of head and neck pain and masticatory and trapezius muscle activity while resting, before and after smartphone use.

Methods:

Twenty university students participated in the study. They answered the Smartphone Addiction Scale and the Fonseca Anamnestic Index. Next, the participants were seated and prepared for electromyography through the placement of surface electrodes on the masseter, temporal, and trapezius muscles. Rest condition data were collected for 10 seconds before and after 30 minutes of smartphone use.

Results:

The results showed that 35% of the evaluated individuals were classified as smartphone addicted and 35% reported no head or neck pain in the previous 30 days. There was no association between smartphone use and head and neck pain. In the electromyography, there was an increase in RMS values after smartphone use in the right and left masseter muscles and the left trapezius.

Conclusion:

College students presented a high prevalence of smartphone addiction and head and neck pain, but these were not statistically associated. There was a change in muscle activity only in the right trapezius muscles before and after 30 minutes of smartphone use. These findings are contrary to the current belief that the use of smartphones correlates with pain in the neck region and changes in the electrical muscle activity, leading to fatigue in the cervical muscles.

Keywords

Cervical pain stomatognathic system muscle activity electromyography

1 Introduction

The use of smartphones has been increasing every year, and in Brazil the internet is preferably accessed via mobile phones or tablets [1]. Smartphones have made internet access possible in different places for both leisure and business purposes [2]. However, prolonged use of smartphones can cause adverse physical and mental effects, such as behavioral dependence [3]. These effects mainly affect the younger populati-on (15–24 years old) as they are always up to date with technology and devote more time to their devices [3].

Among the highlighted mental effects, some studies have shown that smartphone dependence is positively related to behavioral changes such as anxiety, aggression, and depression [3]. In addition, smartphone dependence is positively associated with pathophysiological symptoms, such as excessive alcohol consumption [4], smoking habits [5], and life dissatisfaction [6].

Regarding the physical effects, smartphone use can lead to the development of several repetitive strain injuries and musculoskeletal disorders [7]. The postures adopted during prolonged use of the smartphone promote abnormal alignments between body segments, which may cause changes and symptoms in the head, neck, and shoulder regions [8]. These changes generate overload of the neck muscles, increased muscle fatigue, and decreased working capacity, thus affecting the musculoskeletal system, including the masticatory muscles [9], as the temporomandibular joint is anatomically connected to the cervical spine joints [10].

Studies have shown that neck pain is positively correlated with fatigue and tension [8]. In addition, other risk factors from smartphone use are repetitive or prolonged cervical flexion posture and sitting posture. The static cervical flexion posture adopted during smartphone use while sitting leads to a muscle demand three to five times higher than the neutral cervical posture [11], thus generating a greater report of symptoms in this region. In addition, changes in the cervical spine have been related to dysfunctions and symptoms in the orofacial region [12]. Head posture has been studied by several authors as a possible factor related to temporomandibular dysfunction [13]. Therefore, it is believed that there is interdependence between the regions of the mandible and cervical spine, which has been extensively explored in the literature considering both postural, biomechanical, and neuroanatomic relationships [14, 15].

Some hypotheses have been raised to justify the association between changes in the cervical spine and symptoms in the facial region. One is related to Forward Head Posture (FHP), which causes flexion of the upper and lower cervical thoracic region, and hyperextension of the upper cervical region. This results in tension being generated in the infrahyoid muscles, lower and posterior traction on the hyoid, and traction transfer to the mandible, culminating in alteration of the positioning of the mandible (posteriorly and inferiorly) [16]. Therefore, activities that lead to the adoption of postures that generate head protrusion may give rise to the development of symptoms in the facial region, including alteration in the myoelectric activity of the masticatory muscles.

Thus, considering that smartphone use is increasing in the young population (15–24 years old) and may be related to the adoption of biomechanically inappropriate postures in various regions, especially the head and neck regions, and that the adoption of these postures may lead to the emergence of painful symptoms in both regions, it was hypothesized that the prevalence of smartphone overuse is high among college students and that this condition is related to symptoms (i.e., pain, reduced range of motion) in the head and neck regions. In addition, it is believed that alterations will be observed in the electromyography activity of the masticatory and trapezius muscles in the muscle resting condition before and after smartphone use. This study is part of a larger project. The data regarding the muscle activity during smartphone use are still being analyzed and will be published in the future. In addition, it is widely known that pain can cause alterations in muscle activation, showing higher values in the electromyography evaluation during the rest period in people with pain [17, 18].

This study aimed to evaluate the prevalence of smartphone overuse in college students and its correlation with symptoms of pain in the head and neck region. An increasing number of people are using their cell phones during work and this, associated with work overload, can generate an accumulation of stress, fatigue, and pain. Several companies have already adopted social media as a working environment, and it is known that undergraduate students will soon be inserted into the work environment, which emphasizes the importance of knowledge on this population regarding smartphone use, in order to guide and prevent pain and overuse.

In addition, this study evaluated the activity of masticatory and trapezius muscles in the muscle resting condition before and after smartphone use.

2 Methods

2.1 Study design

The research is a cross-sectional observational study which was approved by the Research Ethics Committee of the Methodist University of Piracicaba UNIMEP (protocol No. 4917).

2.2 Sample

The convenience sample consisted of 20 female students from the Methodist University of Piracicaba UNIMEP with an average age of 22.6±3.0 years, height of 163.7±6.2 cm, and body mass of 59.9±10.4 kg. The volunteers were recruited through advertisements at the institution.

The students who agreed to participate signed a Consent Form (CF) and answered questionnaires that contained data regarding anthropometric characteristics; the Fonseca Anamnestic Index (FAI), used to identify pain in the head and neck region; Smartphone Addiction Scale - Short Version (SAS - SV), used to assess smartphone overuse; and surface electromyography (EMG), to record the activity of the masseter, anterior temporal, and trapezius anterior muscles bilaterally, analyzed during rest.

2.3 Inclusion criteria

University students, female, who use a smartphone, aged over 18 years, and who agreed to participate in the study by electronic acceptance of the free and informed consent form (CF), were included in the sample.

2.4 Exclusion criteria

Volunteers with a history of surgery or trauma in the cervical or orofacial area and BMI > 25 kg/m² (which can interfeer in the muscular activity acquisition due to the fat layer) were excluded.

2.5 Assessment tools

2.5.1 Fonseca anamnestic index (FAI)

The Fonseca Anamnestic Index is a scale developed in Portuguese that assesses the severity of myogenic temporomandibular disorder [19]. This instrument consists of 10 questions, which include information on the difficulty of opening the mouth and moving the jaw; tiredness and/or muscle pain when chewing; frequent headaches; neck pain and/or stiff neck; ear or TMJ pain; TMJ noises in the joint when opening the mouth or chewing; if the teeth are well articulated; and whether a person is tense/nervous and has the habit of teeth clenching or grinding. The scale presents three types of answers: “yes” with a score of 10, “sometimes” with a score of 5, and “no” with a score of 0. Through the final score obtained on the scale it is possible to characterize the degree of severity of temporomandibular dysfunction: 0 to 15 without TMD; 20 to 40 light TMD; 45 to 65 moderate TMD; and 70 to 100 severe TMD [19].

2.5.2 Smartphone addiction scale - short version (SAS - SV)

The smartphone addiction scale (Smartphone Addiction Scale - Short Version) aims to assess how much an individual is dependent on smartphone use. The scale was translated and validated to Brazilian Portuguese [20]. In order to be used as a quick, simple, and easily applied screening tool, the short version of the scale contains 10 self-answered items which evaluate 5 domains: 1) disorder of daily life; 2) remoteness; 3) orientation-cyberspace relationship; 4) overuse; and 5) tolerance. The scale includes 6 answer options: strongly disagree “1”; disagree in parts “2”; disagree “3”; agree in parts “4”; agree “5”; and strongly agree “6”. The cut-off value of smartphone addiction varies by sex, being 31 points for women and 33 points for men [3].

2.5.3 Surface electromyography

An eight-channel Delsys Trigno electromyography system was used to collect the electromyography signal from the masticatory muscles (16-bit resolution and 4000 Hz sampling frequency per channel was used, connected to a notebook via USB). The signals were analyzed off-line using MATLAB 8.3 software (R2018a), to which a zero-lag Butterworth type dual pole 10 Hz high pass and 400 Hz low pass digital filter of the 4th order was applied. To capture the muscle activation of the right and left masseter, right and left temporal, and right and left trapezius, differential, bipolar electrodes with a diameter of 1 cm each were used. They were positioned in the direction of the muscle fibers, over the bellies of the mentioned muscles.

Firstly, the skin was adequately prepared with the objective of reducing impedance that may interfere with the electromyography signal, using 70% alcohol soaked cotton to cleanse the site, thus removing grease and dead skin cells. The electrodes were fixed with adhesives (Delsys), for better positioning and identification of the muscle to be evaluated. The volunteers were asked to perform a function test, consisting of a voluntary muscle contraction, for each muscle, thus ensuring the fixation of the electrodes in the correct place. The electrodes were placed on the trapezius muscles following SENIAM norms, being positioned at half the distance between the acromion and the seventh cervical vertebra. The analysis was performed in the amplitude domain to obtain the Root Mean Square (RMS).

2.5.4 Evaluation protocol

Initially, the volunteers were invited to sign the informed consent form and report anthropometric data online (age, body mass, height and manual preference). The Fonseca Anamnestic Index (FAI), Smartphone Addiction Scale (SAS-SV), and presence or absence of neck pain were completed in the lab, just before EMG data collection.

Next, the surface collection electrodes were fixed to the masseter, temporal, and trapezius muscles, bilaterally. To collect the electromyography signal of the muscles, the volunteers were instructed to remain seated in a chair with their feet in a neutral position flat on the floor. A collection of 10 seconds was performed in the resting condition. Subsequently, the volunteer was instructed to remain in the sitting position, using their smartphone for 30 minutes. During this time the volunteer was allowed to use social networks or perform research on the smartphone, but could not talk to anyone. At the end, a further 10 seconds were collected in a second muscle resting condition.

Besides the variability in sEMG, according to Castroflorio et al., sEMG can be reliable when the experiment is carefully controlled [21]. This study highlights some conditions important for maintaining reliable sEMG data, such as: day of recording, location of the electrode, interelectrode distance, and training of the operators. In the present study, the recording was performed in the same session, following the guidelines for the placement of the electrodes, respecting the distance of 2 mm between the electrodes, and all the evaluators were trained by the same researcher, with more than 10 years of experience in the sEMG field, to maintain the consistency of the evaluation. In addition, all the rest recordings were checked in relation to noises before the data collection began, to guarantee the quality of the data.

The rest position for the data collection was sitting with the eyes closed. The volunteer was requested not to swallow during the recording. If this occurred, the recording was discarded and performed again. This position was adopted for all the rest recordings.

2.5.5 Statistical analysis

Data were initially analyzed descriptively (means and standard deviations). The chi-square association test was used to analyze if there was an association between smartphone use and the report of pain in the head and neck region. Electromyography data were tested for normality by the Shapiro Wilk test and as they did not meet this assumption (p = 0.041), the Wilcoxon test (repeated measures) was used for nonparametric data to identify if there was a difference in the resting condition of the trapezius, masseter, and right and left temporal muscles before and after smartphone use. Statistical significance was set at 5% (p < 0.05). Data analysis was performed using SPSS software, version 13.0.

3 Results

The results showed that 35% (n = 7) of the evaluated individuals were classified as smartphone dependent and 65% (n = 13) as non-dependent. The mean SAS-SV score for non-dependent individuals was 28.4±4.3 and for individuals classified as dependent 39.6±5.5. The mean score of individuals classified as non-dependent was high, that is, close to the cutoff values [31] indicating that even individuals classified as non-dependent used their smartphones a lot. During the use of the smartphone, the volunteers remained in the head forward position.

In total, 35% (n = 7) of the assessed individuals reported no head or neck pain in the previous 30 days and 65% (n = 13) reported head and neck pain in the previous 30 days, representing a high prevalence of individuals with head and neck pain.

There was no association between smartphone use and head and neck pain (p = 0.094). Table 1 shows the classification of the university students evaluated regarding smartphone use and the presence of symptoms in the head and neck region.

Table 1
Sample classification (n = 20) according to smartphone addiction scale classification (SAS-SV) and head and neck pain report. Values expressed in frequency and percentage

Classification No pain Pain Total

Non excessive use 2 (10%) 5 (25%) 7 (35%)

Excessive use 5 (25%) 8 (40%) 13 (65%)

Total 7 (35%) 13 (65%) 20 (100%)

Classification	No pain	Pain	Total
Non excessive use	2 (10%)	5 (25%)	7 (35%)
Excessive use	5 (25%)	8 (40%)	13 (65%)
Total	7 (35%)	13 (65%)	20 (100%)

The data showed no statistically significant differences between the values of the RMS variable before and after 30 minutes using the smartphone for the muscles left temporal (LT) p = 0.550; left masseter (LM) p = 0.455; right temporal (RT) p = 0.263; right rasseter (RM) p = 0.179; left trapezius (LT) p = 0.067. However, a statistically significant difference was found in the RMS values before and after 30 minutes of smartphone use for the right trapezius muscle (RT) muscle (p = 0.048). The mean and standard deviation values of the RMS of the muscles evaluated before and after smartphone use are presented in Table 2.

Table 2

RMS values (mV) of the left and right temporal, masseter, and trapezius muscles before and after 30 minutes of smartphone use

	RMS pre	RMS post	α
Left temporalis	53.02±28.25	49.94±32.17	p = 0.550
Right temporalis	98.15±200.4	72.59±111.9	p = 0.263
Left masseter	37.25±15.53	39.81±33.95	p = 0.455
Right masseter	37.64±22.70	41.86±58.12	p = 0.179
Left trapezius	44.65±41.47	46.35±49.45	p = 0.067
Right trapezius	45.19±35.37	36.01±41.59	p = 0.048^*

The results demonstrate an increase in RMS values after smartphone use in the right and left masseter muscles and the left trapezius. For the right and left temporal and right trapezius muscles, there was a decrease in RMS values, and for the right trapezius muscle, this decrease was statistically significant. This fact may be justified because all volunteers were right-handed.

4 Discussion

The aim of the study was to evaluate smartphone use and its relation to head and neck pain symptoms, as well as to evaluate the activity of masticatory and trapezius muscles in the muscle resting condition before and after smartphone use. The results obtained in this research revealed that there is a prevalence of 65% of college students using smartphones excessively and a prevalence of 65% of pain in the head and neck regions. However, no correlation was found between pain in the head and neck region and excessive smartphone use. In addition, there were no differences in resting RMS values when comparing before and after smartphone use for the bilateral masseter and temporal muscles and left trapezius. There was a difference in resting RMS before and after smartphone use for the right trapezius muscle.

The data showed a high prevalence of students classified as smartphone dependent. These data corroborate a previous study with Brazilian university students that also found a high prevalence of smartphone addiction in this population (33.1%) [20]. In other countries, smartphone addiction prevalence rates for students were reported to be 71.9% in Saudi Arabia [22] and 16.9% in Switzerland [23].

Smartphone overuse has been associated with both emotional symptoms and alterations in the musculoskeletal system. Emotionally, overuse is related to pathophysiological symptoms, such as alcohol abuse, depression, anxiety, smoking, and low self-esteem [24]. Regarding musculoskeletal aspects, studies have pointed to an association between excessive smartphone use and pain in the wrist and hand regions, in addition to reduced muscle strength of the hand muscles and functionality of this region [25]. Furthermore, Kee et al. concluded that device dependence might have a deleterious influence on craniocervical mobility due to the significant decrease in movement in this region, caused by the cervical posture adopted during smartphone use.

The results of the present study showed a high prevalence of pain in the head and neck regions in young individuals. Studies have shown that neck pain is a common condition in the population and causes considerable dysfunction [26]. Gomes-Neto, Sampaio and Santos [27] also found a high prevalence of pain in college students, where 40.5% of students reported neck pain and 29.5% wrist pain.

No association was found between head and neck pain and excessive smartphone use. Although there is evidence that smartphone use alters head and neck positioning compared to the neutral position [28] and that the anterior neck posture may lead to increased mechanical loading of the joints, neck, and cervical spine ligaments [29], these changes do not seem to be reflected in an increase in pain in the cervical region of young individuals. Damasceno et al. [30], assessing the association between neck pain and texting, in young adults, found no association between neck pain and smartphone use.

For the majority of the muscles evaluated, no statistically significant differences in muscle activation levels (RMS values) were found before and after smartphone use. These results are contrary to the initial hypothesis of the study, that changes in RMS values were expected after smartphone use. Prolonged use of smartphones and the neck position adopted for this activity, could generate changes in the electrical activity of both the cervical and masticatory muscles [31], due to the interdependence of these regions. Studies have shown that injury or disease in one area can induce dysfunction and pain in the other [32]. Studies have found a reduction in the median frequency (EMG MF) of the right trapezius muscle after 30-minutes of smartphone use [33]. Park et al. found a reduction in the EMG MF in the trapezius muscle bilaterally after a 20 minute smartphone activity and reported a higher load on the right shoulder when compared to the left shoulder, since the right shoulder region is used more frequently [34]. However, these findings were not confirmed by the present study. It is widely known that pain can cause alterations in the activation of the muscle activity, showing higher values in the electromyography evaluation during rest periods in people with pain.

The results show a decrease in RMS values after smartphone use for the right trapezius muscle (TRD), which might be related to the manual preference as all the volunteers are right-handed. Therefore, it is possible that the volunteers used the right side more during the 30 minutes of smartphone use, which could cause more muscle activity in the right side and, possibly, muscle fatigue. This factor could generate a decrease in the RMS values after the prolonged use of the smartphone [24 , 35].

Another hypothesis for the decrease in RMS values for the RT muscle may be due to the condition in which the muscle was maintained during the smartphone use period, i.e., the muscle was initially relaxed, then went through a 30-minute period of maintained activity, and, finally, was at rest for 10 seconds at the end. While using the smartphone, volunteers kept the head and neck flexed, which consequently leads to craniocervical misalignment [10, 36] and stretching of the neck flexor muscles, generating an isometric contraction of the masticatory and trapezius muscles, thus triggering physiological effects of neuromuscular origin.

The hypothesis of the present study was that alterations would be observed in the electromyography activity of the masticatory and trapezius muscles in the muscle resting condition before and after smartphone use. Therefore, was not mentioned the increase of the muscle activity after the use of smartphone. An alteration occurred in all the muscles, however, this was statically significant only in the right trapezius. This could have happened due to the low number of volunteers, and the fact that all the volunteers presented the right side as dominant, therefore, the volunteers used the device for more time with the right hand, causing more fatigue on this side. In addition, the volunteers of this study were not characterized related to orofacial pain, which could promote fatigue in the facial muscles.

Ries et al. [35] conducted a study with 49 volunteers, with the objective of evaluating the contraction and relaxation time of the masticatory muscles through the variables RMS and Median Frequency (MF), according to the presented data. Maximum voluntary contraction time causes stimuli for muscle relaxation, and in clinical practice the control of this maximum voluntary contraction time is extremely important to avoid fatigue, which may result in alterations in the mechanics of the muscular system. Finally, the hypothesis of the present study was partially confirmed, since a prevalence of 65% of college students used smartphones excessively and a prevalence of 65% reported pain in the head and neck regions. However, there was no association between smartphone dependence and head and neck pain, and no difference in muscle electrical activity of the right and left temporal, right and left masseter, and left trapezius muscles before and after 30 minutes of smartphone use. The only difference observed was for the right trapezius muscle.

4.1 Strengths and limitations of the study

As strengths, this study included EMG evaluation to verify the effects of using the smartphone. The present study has several limitations including (1) the low number of volunteers, (2) the use of a convenience sample of female university students which prevents generalization of the prevalence of smartphone addiction to the broader population of young people in Brazil, (3) smartphone use indicators were assessed via self-report rather than objectively, and (4) the level of physical activity of the volunteers or whether they had a paid job were not verified.

4.2 Suggestion for future studies

Future studies should (1) focus on the assessment of smartphone use and indicators of smartphone addiction in a representative sample of young people, (2) unravel the inconsistent prevalence of smartphone addiction in males and females, (3) assess smartphone use indicators via objectively recorded data rather than self-report, and (4) check the level of physical activity of the volunteers and if they perform a remunerated activity.

5 Conclusion

Thus, it can be concluded that there is a prevalence of 65% of smartphone-dependent college students and also a prevalence of 65% of head and neck pain, but that these are not associated. It is also concluded that there is no change in the muscle activity of the left and right temporal, right and left masseter, and left trapezius muscles before and after using a smartphone for 30 minutes. A difference was observed only for the right trapezius muscle. These findings are contrary to the current belief that the use of smartphones is positively correlated with pain in the neck region as well as with changes in the electrical muscle activity, leading to fatigue in the cervical muscles.

Conflict of interest

None to report.

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