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Mobile Addiction and Anxiety: The Relationship Analysis Report

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Updated: Apr 15th, 2022

The purpose of the study is to establish the nature of the relationship that exists between mobile addiction and anxiety among students. In this insight, the study aimed to find out if there are significant differences between anxiety levels among three categories of participants, namely, low, medium, and high levels of mobile addiction. To determine this purpose and aim, the study hypothesised that the level of anxiety among students increases with an increase in the level of mobile addiction. The study selected 84 participants from a third-year psychology students (Females = 41 and Males =43). The participants filled surveys, which measured mobile addiction using an ordinal scale of low, medium, and high usage of phones. Moreover, the surveys measured the anxiety levels using interval scale. The statistical analysis that the study used are descriptive statistics, t-test, one-way analysis of variance, and post hoc analysis. The key results are that the mobile phone usage does not vary according to gender and the anxiety level increases with the increase in mobile addiction. Thus, these findings are very important because they enable psychologists, psychiatrists, and students understand how mobile addiction contributes to anxiety.

The purpose of the study is to establish the nature relationship that exists between mobile addiction and anxiety. The study of the relationship between mobile addiction and anxiety is important to psychology because it would explain the occurrence of anxiety among mobile users. Fundamentally, mobile addiction is common behaviour in modern society because of the advancement in the information technology (Massimini & Peterson, 2009). With mobile phones, people can perform numerous activities ranging from socialisation to business. Takao, Takahashi, and Kitamura (2009) state that mobile addiction is the inability of a mobile user to abstain from using mobile phones regularly. Hence, mobile addiction is a compulsive urge to use mobile phones as often as possible and developing sense of withdrawal when not using (Cheever, Rosen, Carrier, & Chavez, 2014). As mobile addiction is a compulsive urge, it makes mobile users to be anxious of numerous activities that involve them. According to Thomee, Harenstam, and Hagberg (2011), mobile phone addiction causes anxiety because it disturbs and destabilises emotional and psychological state of an individual. In this view, anxiety is disturbed emotions that affect the psychological health of mobile users. Therefore, mobile addiction is the independent variable, while anxiety is the dependent variable. To understand the effect of mobile addiction on anxiety, the study seeks to establish the nature of the relationship that exists between the two variables.

Mobile phones have revolutionised the way people communicate and interact in society. However, uncontrolled usage of mobile phones in modern society has led to mobile addiction, which has a negative effect on health. Learning and behavioural theory and cognitive behavioural theory are some of the theories that elucidate the occurrence of mobile addiction. Learning and behavioural theory holds that individuals become addicted to mobile phones because of social forces such as peers, social media, and social activities. Cognitive behavioural theory holds that individuals become addicted to mobile phones through the change of perceptions and constant usage. Mobile addiction is a new form of addiction in the 21st century because of technological advancement (Kim, 2013). Evidently, adolescents spend a great deal of their time in using mobile phones, and thus, they become addicted to them. Given that smartphones have many attractive features and allow users to multitask, they are more addictive than ordinary mobile phones. According to a study done on campus, 64% of students interacted with their smartphones or mobile devices at a given instance (Jones, 2014). The emergence of social sites, such as Facebook, Instagram, Pinterest, Google+, and YouTube, has contributed to increased mobile addiction among the young people.

Anxiety is an emotional disorder, which people experience when a number of issues disturb their emotions and psyche. Anxiety is a crippling emotional disorder because it triggers psychological disorders and make people unable to lead normal lives. Moral theory and learning theory explains how anxiety occurs among individuals. Since anxiety is an emotional and psychological disorder, moral theory holds that, it emanates from an individual’s inability to control self-consciousness resulting into great fear. Learning theory elucidates that people become anxious about certain things based on previous experiences, which trigger anxiety. Depending on the cause, anxiety can be a panic disorder, social anxiety disorder, phobia, or general anxiety (Rose, 2014). Anxiety has become one of the leading causes of psychological and emotional disorders, which impose huge burden on the healthcare system, caregivers, and families. Given that anxiety is an emotional disorder, patient-reported outcome is an appropriate assessment method for diverse psychological constructs of anxiety among individuals (Rose, 2014). Therefore, self-reported symptoms of anxiety give an accurate assessment of the degree of anxiety among individuals.

Mobile addiction and anxiety are two variables that relate. A number of studies have established that there is a positive correlation between mobile addiction and anxiety (Kumar, 2014 Jones, 2014; Thomee et al., 2011). The findings of these studies imply that mobile addiction contributes to the increasing cases of anxiety among the youth, who are predominant mobile users. A study done among young adults aged between 20 and 24 indicates that the ones with high mobile phone usage experience sleep disturbances, stress, and depressive moods (Thomee et al, 2011). In this view, it is evident that mobile addiction, as indicated by high mobile usage, contributes to sleep disturbance, stress, and depression, which are psychological variables associated with anxiety. Another study done to determine the relationship between mental health and mobile phone usage shows that mental health inversely correlates with mobile addiction (Babadi-Akashe, Zamani, Abedini, Akbari, & Hedayati, 2014). From these findings, it is apparent that mobile addiction is a psychological problem that has a marked influence on the mental status of people. Hong, Chiu, and Huang (2012) studied how personality factors influence mobile addiction among Taiwanese female students and found out that extraversion has positive effects on mobile addiction, while self-esteem has negative effects on mobile addiction. In this view, it implies that the level of anxiety varies from one person to another depending on personality traits. Analysis of the aforementioned studies shows that their setbacks include a narrow range of age and the use of predefined scales. In this view, the study expanded the range of age and used customised scale in measuring anxiety and mobile addiction.

Given that the cases of anxiety among people have increased exponentially, the rationale for the study is that there is need to establish the role of mobile addiction in mediating anxiety. Kumar (2014) reports that increasing use of mobile phones contributes significantly to the occurrence of mental disorders among people in modern society where information and communication technology is undependable. In this view, understanding the relationship between mobile addiction and anxiety is very important to psychologists and psychiatrists because they can apply the knowledge is alleviating the impact of mobile phone usage in the society, particularly among the young people (Perez, Monje, & Leon, 2012). Numerous theories elucidate the relationship between mobile addiction and anxiety. Learning and behavioural theory is one of the theories, which elucidate how mobile addiction occurs owing to social forces such as peers, social media, and social activities. Moreover, cognitive behavioural theory elucidates how mobile addiction is a behaviour that emanates from constant usage of mobile phones. Since mobile addiction associates with anxiety, moral theory elucidates how individuals lose their ability to control their mobile usage resulting in anxiety. Additionally, learning theory explains how people become anxious about the usage of mobile phones. These theories, therefore, explain how and why mobile addiction occurs and associate with anxiety. Although previous researches have shown that mobile addiction is a common psychological disorder, they have not established the variation of anxiety according to the degree mobile addiction. Thus, the study is important because it seeks to establish how anxiety varies with mobile addiction.

Research Question

Do individuals with high, medium, and low levels of mobile addiction have significant differences in anxiety level?

Research Aim

To find out if there are significant differences in anxiety means among individuals with high usage, medium usage, and low usage of mobile phones.

Hypothesis

  • The hypothesis of the study is that the anxiety means increase with an increase in the level of mobile phone usage.

Method

Participants

The participants of the study were third-year psychology students. The study employed purposive sampling in selecting all third-year psychology students in the university. The selection criteria of the study were that the participants ought to have been third-year psychology students aged between 20 years and 30 years. Through purposive sampling the study selected 84 participants (Females = 41 and Males = 43). Most of the participants were young adults (M = 23.5 years of age, SD = 4.50).

Materials

The study used surveys in collecting data from the participants regarding mobile addiction and anxiety level. In mobile addiction, the study used a scale, which ranged from zero being the lowest level of addiction to 300 being the highest level of addiction. The survey categorised mobile users into three ordinal groups, namely, low, medium, and high addiction levels, in form of a Likert scale. Moreover, the study used anxiety scale, which ranged from zero to 20. The scale assesses anxiety on a continuous scale. The validity and reliability of the scales were determined using Cronbach’s alpha and were found to be valid. Informed consent forms are other materials that the study used in the collection of data from the third-year psychology students.

Procedure

The procedure of the study commenced with the formulation of survey questions and scales used in the measurement of mobile addiction and anxiety. When the surveys and scales were ready, researchers requested the students to participate in the study and employed purposive sampling in selecting third-year psychology students, who have the ages between 20 and 30 years. The selected participants signed the informed consent and started filling the surveys administered to them. The participants first filled mobile addiction surveys followed by anxiety surveys. The collected data was then entered into the SPSS, according to their scales. Age and anxiety values were entered directly into the SPSS as continuous data. In entering gender, females were scored as one and males were scored as two. The mobile addiction values were scored into an ordinal scale of low, medium, and high addiction levels using one, two, and three values.

Design

The study employed survey research design where the independent variable is mobile addiction, while the dependent variable is anxiety. The analysis of the study is one-way analysis of variance (one-way ANOVA). This form of analysis is appropriate because the data collected meets the assumptions of one-way ANOVA. The dependent variable, anxiety, meets the assumptions of one-way ANOVA because it exists as an interval scale, follows a normal distribution, independent of observation, and has no significant outliers. Moreover, the independent, mobile addiction, meets the assumption of two or more categorical groups of one-way ANOVA because it has three categories, namely, low, medium, and high addiction levels of mobile usage. Given that the dependent variable has three categorical groups, it meets the requirement of post hoc analysis.

Results

Descriptive Statistics

The table 1 below shows descriptive statistics of gender, mobile phone usage, and anxiety of 84 participants.

Table 1

Descriptive Statistics
N Minimum Maximum Mean Std. Deviation Skewness Kurtosis
Statistic Statistic Statistic Statistic Statistic Statistic Std. Error Statistic Std. Error
Gender 84 1.00 2.00 1.5119 .50286 -.049 .263 -2.047 .520
MPU_TOTAL2 84 27.00 225.00 101.6071 47.16518 .495 .263 -.509 .520
Anxiety_2 84 .00 20.00 4.7024 4.54901 1.052 .263 .676 .520
Valid N (listwise) 84

The descriptive statistics of gender indicate that the participants have approximately equal number of male and female participants with positive skewness and negative kurtosis. The distribution of mobile phone usage has positive skewness and negative kurtosis. The anxiety, which is the dependent variable, has both significant positive skewness and positive kurtosis. Overall, mobile phone usage data and anxiety data approximately follow a normal distribution.

T-test

Table 2 below shows comparison of means of mobile phone usage between male and female participants.

Table 2

Group Statistics
Gender N Mean Std. Deviation Std. Error Mean
MPU_TOTAL2 Female 41 103.4390 49.29505 7.69859
Male 43 99.8605 45.55718 6.94740

The group statistics indicate that there is an apparent difference in means of mobile phone usage between male and female participants. The mean of mobile phone usage for female participants is higher than that of male participants.

Table 3 shows the anxiety tests, which examine equality of variances and equality of means between male and female participants.

Table 3

Independent Samples Test
Levene’s Test for Equality of Variances t-test for Equality of Means
F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference
Lower Upper
MPU_TOTAL2 Equal variances assumed .101 .752 .346 82 .730 3.57856 10.35025 -17.01138 24.16850
Equal variances not assumed .345 80.704 .731 3.57856 10.36990 -17.05543 24.21255

Regarding the equality of variances, the test shows that variances of male and female participants have no significant difference, F(82) = 0.101, p = 0.730. Moreover, the test of equality of means indicate that means of male and female participants have no significant difference, t(80.704) = 3.45, p = 0.731.

ANOVA Test

Table 4 depicts descriptive statistics of anxiety scores among the three groups, namely, low, medium, and high addiction levels.

Table 4

Descriptive Statistics of Anxiety
MPU_TOTAL2 (Binned) Mean Std. Deviation N
Low 2.2143 2.68545 28
Med 5.1000 5.14848 30
High 6.9231 4.23248 26
Total 4.7024 4.54901 84

The descriptive statistics shows that there are apparent differences in the means of anxiety scores among the three groups. The mean of anxiety scores increases as mobile phone usage increases.

Table 5 below shows that ANOVA table, which determine if the apparent differences are significant.

Table 5

Univariate Tests
Sum of Squares df Mean Square F Sig. Partial Eta Squared
Contrast 306.299 2 153.150 8.790 .000 .178
Error 1411.260 81 17.423

The ANOVA table shows that there is statistically significant difference between means of the three groups, F(81) = 0.8.790, p = 0.000.

Post Hoc Analysis

Table 6 below shows post hoc analysis since the independent variable has three categories.

Table 6

Multiple Comparisons
(I) MPU_TOTAL2 (Binned) (J) MPU_TOTAL2 (Binned) Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval
Lower Bound Upper Bound
Low Med -2.8857* 1.09682 .036 -5.6209 -.1506
High -4.7088* 1.13682 .000 -7.5437 -1.8739
Med Low 2.8857* 1.09682 .036 .1506 5.6209
High -1.8231 1.11843 .271 -4.6121 .9660
High Low 4.7088* 1.13682 .000 1.8739 7.5437
Med 1.8231 1.11843 .271 -.9660 4.6121

In post hoc analysis, the difference between the anxiety means of low addiction is significantly from the anxiety means of medium addition (p = 0.036) and high addiction (p = 0.000). The anxiety mean of medium addiction is not significantly different from the anxiety mean of high addiction (p = 0.271).

Discussion

In the analysis of data, the study aims to establish if there are significant differences in anxiety means between individuals with high usage, medium usage, and low usage of mobile phones. The findings of the study support the hypothesis that the anxiety means increase with an increase in the level of mobile phone usage. Essentially, there are significant differences in the anxiety means of the three groups of participants, namely, low, medium, and high phone users.

Overall, one-way ANOVA test supports the hypothesis that the anxiety means vary significantly among low, medium, high phone users. T-test was done to establish if mobile addition was independent of gender as a possible confounding variable. From the data, it is evident that anxiety level increases with an increase in the level mobile addiction. According to Hong et al. (2012), mobile addiction contributes to psychological disturbances, which include stress, depression, and anxiety. These findings support the hypothesis because they hold that mobile addiction causes psychological disturbances that relate to anxiety. Sahin, Ozdemir, Unsal, and Temiz (2013) state that stress, depression, and sleep disturbance associate with mobile addiction. The statement supports the hypothesis of the study because descriptive analysis shows that anxiety level increases with an increase in the level of mobile addiction. The findings support moral theory and learning theory, which explain how individual develop anxiety owing to their experiences with the use of mobile phones.

Anxiety is a complex emotional and psychological disturbance that occurs due to multiple factors. Anxiety is a product of multiple factors, and thus, it is difficult to establish the specific cause (Rose, 2014). However, the findings contradict the statement because it is similar to numerous findings, which support the assertion that mobile addiction causes psychological and emotional disturbances, thus, contributing to high levels of anxiety among people (Jones, 2014; Takao et al., 2009). Moral theory and learning theory are appropriate because they support the occurrence of anxiety. As morality and learning processes vary from one social setup to another, the anxiety means and the levels of mobile addiction may be inaccurate.

The findings of the study have theoretical importance because they elucidate the nature of relationship that exists between anxiety and mobile addiction. In this view, with knowledge of mobile addiction, one can predict the level of anxiety. The practical importance is that psychologists and psychiatrists can apply these findings in alleviating the level of anxiety in patients. In learning institutions, the findings have practical implications because students need to understand how mobile addiction occurs and contributes to their performance through anxiety.

The first limitation of the study is low internal validity. Given that the study used designed surveys with low validity and reliability, the findings obtained are weak. The second limitation is low external validity. The study selected a limited number of participants, who do not reflect the entire population of students. Researchers’ bias is another limitation that the study encountered because they were aware of the nature of research and expected outcomes. To overcome these limitations, future research should consider using established scales for collecting data and assessing mobile addiction and anxiety accurately. Moreover, the future research should consider blinding the researchers to prevent biases associated with their perceptions.

In conclusion, the study aimed to establish if there are significant differences in anxiety means between individuals with high usage, medium usage, and low usage of mobile phones. The findings established that there are significant differences in anxiety means of low, medium, and high phone users. Essentially, the level of anxiety among participants increases with the level of mobile addiction. These findings are beneficial because they enable psychologists, psychiatrists, and students to understand how to manage anxiety.

References

Babadi-Akashe, Z., Zamani, B., Abedini, Y., Akbari, H., Hedayati, N. (2014). The Relationship between Mental Health and Addiction to Mobile Phones ‎among University Students of Shahrekord, Iran. Addiction & Health, 6(3), 12-33.

Brian, J. (2013). Two days with no phone. Scholastic Action, 37(1), 4-6.

Cheever, N., Rosen, L., Carrier, M., & Chavez, A. (2014). Out of sight is not out of mind: The impact of restricting wireless mobile device use on anxiety levels among low, moderate and high users. Computers in Human Behaviour, 37(1), 290-297.

Hong, F., Chiu, S., & Huang, D. (2012). A model of the relationship between psychological characteristics, mobile phone addiction and use of mobile phones by Taiwanese university female students. Computer in Human Behaviour, 28(6), 2152-2159.

Jones, T. (2014). Students’ cell phone addiction and their opinions. The Elon Journal of Undergraduate Research in Communications, 5(1), 74-80.

Kim, H. (2013). Exercise rehabilitation for smartphone addiction. Journal of Exercise Rehabilitation, 9(6), 500-505.

Kumar, K. (2014). Mobile phone and adolescents: Addiction a mindful check in! International Journal of Advanced Studies, 3(1), 42-46.

Massimini, M., & Peterson, M. (2009). Information and communication technology: Affects on U.S. college students. Cyberpsycology, 3(1), 1-15.

Perez, P., Monje, R., & Leon, R. (2012). Mobile phone abuse or addiction: A review of literature. Adicciones, 24(2), 139-152.

Rose, M. (2014). Assessment of patient-reported symptoms of anxiety. Dialogues in Clinical Neuroscience, 16(2), 197-211.

Sahin, S., Ozdemir, K., Unsal, A., & Temiz, N. (2013). Evaluation of mobile phone addiction level and sleep quality in university students. Pakistan Journal of Medical Sciences, 29(4), 913-918.

Takao, M., Takahashi, S., & Kitamura, M. (2009). Addictive personality and problematic mobile phone use. Cyber Psychology & Behaviour, 12(5), 501-507.

Thomee, S., Harenstam, A., & Hagberg, M. (2011). Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults: A prospective cohort study. BMC Public Health, 11(66), 1-11.

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