Prevalence, correlates, and network analysis of Internet addiction symptoms among Chinese pregnant and postpartum women

Objective: Excessive Internet use is a common health problem globally. This study aimed to assess the prevalence, correlates, and network structure of Internet addiction symptoms (Internet addiction hereafter) among Chinese pregnant and postpartum women. Methods: This was a multicenter cross-sectional study using Internet Addiction Test (IAT) and the World Health Organization Quality of Life Questionnaire (WHOQOL-BREF) to evaluate Internet addiction and quality of life (QOL), respectively. Univariate analyses, multivariate logistic regression analyses, and network analyses were performed. Results: Of a total of 1,060 women who completed the study, 320 (30.19%, 95% CI=27.42%-32.96%) women reported Internet addiction during or after pregnancy. Women with previous adverse pregnancy experiences (OR=1.831, P=0.001) and physical comorbidities (OR=1.724, P=0.004) had a higher likelihood of developing Internet addiction. Internet addiction was significantly associated with poor QOL in all domains. Network analyses revealed that IAT item 16 (request an extension for longer time spent online) was the most central symptom in the analyses, and also one of the strongest bridging symptoms linking the Internet addiction and QOL communities. Limitations: This was a cross-sectional study, all study findings were based on self-reported data, and possible recall bias and selection bias may exist. Conclusion: Internet addiction is common among Chinese pregnant and postpartum women, and is significantly associated with lower QOL. Effective strategies, especially focusing on central symptoms, are needed to reduce the impact of Internet addiction and improve QOL in pregnant and postpartum women.

Automated summary

This study assessed the prevalence, correlates, and network structure of Internet addiction among Chinese pregnant and postpartum women. The results showed that Internet addiction is common and significantly associated with lower quality of life in this population. The study also identified the central symptoms of Internet addiction and their links with quality of life.