Level of Insomnia, Symptoms of Depression, and Anxiety among College Students with Mobile Phone Addiction: Basis for Guidance and Counseling Program Enhancement ()
1. Introduction
In the era of rapid technological advancement, the widespread use of smartphones has become an integral part of college students’ daily lives. These devices serve as versatile tools, facilitating communication, online shopping, and gaming, among other functions. When used appropriately, smartphones can enhance learning efficiency and contribute to students’ mental well-being. However, recent studies [1] have shed light on the growing issue of mobile phone addiction among college students, emphasizing its negative impact.
Research indicates that poor self-control and excessive smartphone use have led to a rising prevalence of mobile phone addiction. In fact, recent estimates among domestic college students suggest that this addiction affects between 15.3% and 28.9% of individuals [2] . Furthermore, mobile phone addiction has substantial consequences for both the physical and mental health of college students, impacting sleep quality, exacerbating symptoms of depression, and triggering anxiety.
In the context of the Internet’s ubiquity and the surge in mobile device usage, mobile phone addiction has gained recognition as a pressing issue in the digital age, attracting attention from researchers worldwide [3] . Consequently, it is imperative to investigate the relationship between mobile phone addiction and college students’ insomnia, symptoms of depression, and anxiety [4] .
Mobile phone addiction involves excessive and compulsive smartphone usage, resulting in adverse consequences across various aspects of an individual’s life [5] . Notably, it has been associated with detrimental effects on college students’ mental health, specifically manifesting as insomnia, symptoms of depression, and anxiety [6] [7] . Insomnia involves difficulties falling asleep, staying asleep, or experiencing restorative rest [6] . Symptoms of depression encompass persistent feelings of sadness, loss of interest in activities, and changes in appetite and sleep patterns [7] . Anxiety is characterized by excessive worry, restlessness, and physical symptoms like a rapid heartbeat and sweating [8] . Understanding the intricate relationships between mobile phone addiction, insomnia, symptoms of depression, and anxiety is crucial for addressing the holistic mental well-being of college students [4] .
2. Methods
2.1. Participants and Measures
In May 2023, we selected 399 students from a traditional Chinese medicine university in Guangxi Zhuang Autonomous Region based on their Mobile Phone Addiction Tendency Scale (MPATS) scores, with 155 scoring 32 or higher. Survey questionnaires were distributed through communication with schoolteachers due to participants’ unique identities. We initially screened with the MPATS for mobile phone addiction tendencies and subsequently assessed insomnia, depression, and anxiety severity using the Insomnia Severity Index (ISI), Hamilton Depression Scale (HAMD), and Hamilton Anxiety Scale (HAMA).
The Mobile Phone Addiction Tendency Scale (MPATS) demonstrated strong internal consistency reliability (Cronbach’s alpha = 0.87) and test-retest reliability (coefficient = 0.85), indicating stable measurement results. The development process included extensive literature and expert reviews for content validity, with a correlation of 0.75 with established measures, and factor analysis confirming a three-factor structure, affirming its effectiveness.
2.2. Data Analysis
Statistical analysis was performed on all data collected during the research process using SPSS 25.0 software. Descriptive statistical analysis was conducted on the raw data of the four standardized questionnaires using SPSS software. Frequency and percentage were used to describe the general characteristics of the survey participants, while means were used to evaluate the levels of smartphone addiction, insomnia, anxiety, and depression among the participants. Inferential statistics, including independent samples t-tests and one-way analysis of variance (ANOVA), were used to compare the differences in demographic variables. The Pearson product-moment correlation coefficient was employed to assess the relationships between variables.
2.3. Ethical Considerations
For purpose of ensuring that the study was executed in an appropriate manner, some of factors were considered. When conducting the study, all participants were asked to obtain informed consent to comply with ethical considerations. Ethical considerations were strictly followed, ensuring privacy, confidentiality, and ethical approval, safeguarding participants’ rights and well-being throughout the study.
3. Results
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Table 1. Profile distribution of the respondents (N = 155).
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Table 2. Respondents level of insomnia (n = 155).
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Table 3. Respondents symptoms of depression (N = 155).
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Table 4. Respondents level of anxiety (N = 155).
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Table 5. Insomnia severity and anxiety as predictors of depression
a. Predictors: (Constant), HAMA, ISI.
4. Discussion
Table 1 displays the participant characteristics. Out of 399 distributed questionnaires, 155 students met the criteria for mobile phone addiction. Among these, 54 (34.8%) were male, and 101 (65.2%) were female. The age distribution indicated a prevalence of younger individuals with mobile phone addiction, with 47.7% aged 20 and below, 38.7% aged 21 - 23, 12.9% aged 24 - 26, and 0.6% aged 27 and above. Traditional Chinese Medicine had the highest proportion of addicted students (58.7%), followed by Medicine of Zhuang nationality (12.3%). Fourth and fifth-year students exhibited the highest prevalence of mobile phone addiction (22.6% and 23.9%, respectively). In terms of daily mobile phone usage, the majority reported using their phones for 7-8 hours (31.6%) or above 9 hours (30.3%) per day. Social media apps were the most commonly used (25.7%), followed by entertainment apps (23.8%). However, a gender imbalance exists in the university, which limits the statistical significance of gender’s association with mobile phone addiction.
Table 2 presents insomnia levels among respondents, with weighted mean scores and standard deviations indicating moderate to mild insomnia problems. The total weighted mean score for all statements was approximately 11.6065, indicating subthreshold insomnia.
Table 3 outlines respondents’ symptoms of depression, showing weighted mean scores and standard deviations for each symptom. Scores ranged from approximately 0.9548 to 2.2387, suggesting moderate depression overall.
Table 4 focuses on anxiety levels, displaying weighted mean scores and standard deviations for various anxiety-related items. Scores ranged from approximately 0.9290 to 1.7548, indicating mild to moderate anxiety.
Table 5 presents a statistical model exploring the relationship between insomnia severity and anxiety as predictors of depression. The model explains approximately 55.7% of depression variance and is statistically significant (p < 0.001).
5. Conclusions
This study presents a comprehensive view of college students’ mental health and mobile phone use, revealing insights. Most respondents are female, under 20 years, studying Traditional Chinese Medicine in their 5th year, averaging 7 - 8 daily phone hours with social media involvement. Worth noting, the gender disparity skews results, diminishing gender’s role in phone addiction. Findings indicate sub-threshold insomnia, moderate depression, and anxiety. These challenges yield social withdrawal, relationship struggles, and heightened isolation risks.
In conclusion, addressing the issue of mobile phone addiction among college students holds significant practical implications and calls for actionable strategies:
Promoting Healthy Interactions: Encouraging students to engage in face-to-face interactions, group activities, and meaningful relationships can enhance sleep hygiene and reduce symptoms of depression and anxiety [9] .
Digital Detox Initiatives: Teachers can advocate for regular “digital detox” breaks, encouraging students to participate in non-tech activities like sports, hobbies, and mindfulness to reduce mobile device usage [10] .
Awareness and Education: Health educators should raise awareness about the adverse effects of excessive phone use on mental health and educate students on healthy phone habits, including setting boundaries and managing screen time.
Sleep Hygiene Integration: University counselors can incorporate sleep hygiene practices into mental health programs, educating students on sleep schedules, conducive sleep environments, and relaxation techniques to improve sleep quality.
Partnerships with Tech Companies: School officials can collaborate with technology companies to develop tools like screen time trackers and notification management features, aiding students in effectively monitoring and limiting screen time.
Research and Intervention: University project teams can seek funding to conduct further research on the relationships between mobile phone addiction, insomnia, depression, and anxiety, exploring various intervention strategies to improve mental health.
Program Enhancement Validation: The proposed Guidance and Counseling program enhancements should undergo expert validation and long-term outcome evaluations to assess their effectiveness.
Implementing these recommendations collectively can contribute to the well-being and mental health of college students, offering a holistic approach to mitigating the challenges posed by mobile phone addiction.
While these findings are insightful, it’s essential to acknowledge the potential sample bias due to the limited number of participants with high mobile phone addiction scores. To address this issue, increasing the sample size or refining the selection criteria may enhance representativeness. In future research, we plan to expand the sample size for a more in-depth investigation.