مقاله انگلیسی رایگان در مورد آنالیز شبکه ای از اعتیاد به اینترنت و افسردگی در بین دانشجویان در طول همه گیری COVID-19 – الزویر 2023

Abstract

Background

     There has been growing evidence of comorbidity between internet addiction and depression in youth during the COVID-19 period. According to the network theory, this may arise from the interplay of symptoms shared by these two mental disorders. Therefore, we examined this underlying process by measuring the changes in the central and bridge symptoms of the co-occurrence networks across time.

Methods

     A total of 852 Chinese college students were recruited during two waves (T1: August 2020; T2: November 2020), and reported their internet addiction symptoms and depressive symptoms. Network analysis was utilized for the statistical analysis.

Results

     The internet addiction symptoms “escape” and “irritable,” and depression symptoms “energy” and “guilty” were the central symptoms for both waves. At the same time, “guilty” and “escape” were identified as bridge symptoms. Notably, the correlation between “anhedonia” and “withdrawal” significantly increased, and that between “guilty” and “escape” significantly decreased over time.

Conclusions

     This study provides novel insights into the central features of internet addiction and depression during the two stages. Interestingly, “guilty” and “escape,” two functions of the defense mechanism, are identified as bridge symptoms. These two symptoms are suggested to activate the negative feedback loop and further contribute to the comorbidity between internet addiction and depression. Thus, targeting interventions on these internalized symptoms may contribute to alleviating the level of comorbidity among college students.

Methods

Participants and procedure

     From August to November 2020, using a cluster sampling method, 1,162 college students completed a survey via a Chinese online questionnaire at T1 (August 2020). The second wave (T2: November 2020) of data collection included 1,082 participants. Missing complete at random (MCAR) proposed by Little (1988) was utilized to assess whether the missing data were random. It is worth noting that during T1, college students were preparing to return to school, and T2 took place three months later to allow students to settle in.

     A total of 852 students who completed the questionnaire during both waves—through the matching of their phone numbers—were included in the final analysis. No missing data needed rejection because all items were required to be answered before submission. The research collected information including demographics, age, gender, family structure, current location, whether the participants had siblings or not, depression, and IA. The sample consisted of 300 (35.21%) males (Meanage = 20.22, SD = 2.07) and 552 (64.79%) females (Meanage = 20.79, SD = 2.15), with ages ranging from 17 to 28.

Conclusion

     To our knowledge, this study is the first to investigate network structure and its dynamic changes between IA and depression in Chinese college students. The results revealed that the IA symptom “escape” and depression symptom “guilty,” two functions of the defense mechanism, showed both central and bridge characteristics. These two symptoms were suggested to activate the negative feedback loop and to further contribute to the comorbidity between IA and depression. These bridge symptoms have an enlightening effect on interventions and treatments of comorbidity of IA and depression.