Relationship between depression, smartphone addiction, and sleep among Chinese engineering students during the COVID-19 pandemic

The relationship between mobile phone dependence and academic burnout in Chinese college students: a moderated mediator model

Objective

The aim of this study was to examine the correlation between the level of mobile phone dependence among college students and their experience of academic burnout. Additionally, the study sought to explore the potential mediating effect of study engagement and the moderating role of love.

Methods

During October and December 2023, a cross-sectional study measuring mobile phone dependence, academic burnout, and study engagement among Chinese college students, using the UtrechtWork Engagement Scale-student (UWES-S), College Student Mobile Phone Dependence Questionnaire (CSMPDQ), and Academic Burnout Questionnaire (ABQ). To examine the hypothesis of mediating and moderating effect, SPSS PROCESS was utilized.

Results

The predictive effect of mobile phone dependence on academic burnout was significant (β = 0.410, t = 14.236, p < 0.001), and the predictive effect of mobile phone dependence on academic burnout remained significant when the mediating variable study engagement was introduced (β = 0.308, t = 10.288, p < 0.001), mobile phone dependence had a significant predictive effect on study engagement (β = -0.292, t = -11.639, p < 0.001), and study engagement had a significant positive predictive effect on academic burnout (β = -0.270, t = -9.028, p < 0.001). Love significantly negatively predicted study engagement (β = -0.564, t = -9.641, p < 0.001); and the interaction term for mobile phone dependence and love was significant (β = -0.211, t = -3.688, p < 0.001), indicating a significant moderating effect of love between mobile phone dependence and study engagement.

Conclusion

Mobile phones among college students has been found to have a direct correlation with academic burnout. It can also indirectly contribute to academic burnout by diminishing levels of academic engagement. This indirect relationship is further influenced by love. These findings can help researchers and educators better understand the underlying mechanisms between smartphone dependence and learning burnout in undergraduates.

Potential use of large language models for mitigating students' problematic social media use: ChatGPT as an example

The problematic use of social media has numerous negative impacts on individuals' daily lives, interpersonal relationships, physical and mental health, and more. Currently, there are few methods and tools to alleviate problematic social media, and their potential is yet to be fully realized. Emerging large language models (LLMs) are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life. In mitigating problematic social media use, LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users, providing personalized information and resources, monitoring and intervening in problematic social media use, and more. In this process, we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT, leveraging their advantages to better address problematic social media use, while also acknowledging the limitations and potential pitfalls of ChatGPT technology, such as errors, limitations in issue resolution, privacy and security concerns, and potential overreliance. When we leverage the advantages of LLMs to address issues in social media usage, we must adopt a cautious and ethical approach, being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.

The relationship between mobile phone addiction and time management disposition among Chinese college students：A cross-lagged panel model

Previous research has identified a negative association between mobile phone addiction and time management disposition among college students; however, the direction of this relationship remains divergent. This study utilized a cross-lagged panel model to elucidate the directionality of the relationship between mobile phone addiction and time management disposition. A total of 466 college students completed two measures at seven-month intervals. The findings revealed a prevalence of mobile phone addiction at 10.94 % and 13.73 % in the two surveys. Notably, both mobile phone addiction and time management disposition demonstrated stability over time. Furthermore, a discernible negative bidirectional relationship was observed between the two. The present findings underscore the importance of timely intervention for college students facing challenges in mobile phone usage and time management.

The relationship of smartphone addiction with depression, anxiety, and stress among medical students

Introduction

An increasing amount of research has shown a link between psychopathological behaviors such as smartphone addiction, depression, anxiety, and stress. The aim of this study was to assess the association of smartphone addiction with depression, anxiety, and stress.

Methods

A cross-sectional study was conducted between 26th January and 3rd March 2021. The sample was chosen using a convenient sampling technique and Raosoft tool. The survey assessed smartphone addiction using abbreviated versions of the Addiction Scale Short Version, a self-administered questionnaire that has been validated in the English and Arabic languages. Also, Depression and Anxiety Stress Scale was used to measure the level of depression, anxiety, and stress among the university students.

Results

A total of 367 university students from the Medical and Health Sciences College participated. Our findings showed that smartphone addiction exhibited positive correlations with depression (r = 0.375, p < 0.01), anxiety (r = 0.253, p < 0.01), and stress (r = 0.328, p < 0.05). In addition, there was a strong positive correlation between depression and both anxiety and stress (r = 0.731, p < 0.01) (r = 0.778, p < 0.01), respectively. Finally, stress and anxiety showed a positive correlation (r = 0.708, p < 0.01).

Conclusion

When combined, our data offer strong support for a bidirectional hybrid theory that takes into account the link between smartphone addiction and depression, anxiety, and stress. The current study's findings might assist national health authorities in strengthening their efforts to prevent depression, anxiety, and stress associated with the use of modern technology.